id	sid	tid	token	lemma	pos
ajst-5348	1	1	academic	academic	ADJ
ajst-5348	1	2	journal	journal	NOUN
ajst-5348	1	3	of	of	ADP
ajst-5348	1	4	science	science	NOUN
ajst-5348	1	5	and	and	CCONJ
ajst-5348	1	6	technology	technology	NOUN
ajst-5348	1	7	issn	issn	NOUN
ajst-5348	1	8	:	:	PUNCT
ajst-5348	1	9	2771	2771	NUM
ajst-5348	1	10	-	-	SYM
ajst-5348	1	11	3032	3032	NUM
ajst-5348	1	12	|	|	NOUN
ajst-5348	1	13	vol	vol	NOUN
ajst-5348	1	14	.	.	PROPN
ajst-5348	2	1	5	5	NUM
ajst-5348	2	2	,	,	PUNCT
ajst-5348	2	3	no	no	INTJ
ajst-5348	2	4	.	.	NOUN
ajst-5348	2	5	1	1	NUM
ajst-5348	2	6	,	,	PUNCT
ajst-5348	2	7	2023	2023	NUM
ajst-5348	2	8	57	57	NUM
ajst-5348	2	9	kinship	kinship	NOUN
ajst-5348	2	10	verification	verification	NOUN
ajst-5348	2	11	based	base	VERB
ajst-5348	2	12	on	on	ADP
ajst-5348	2	13	global	global	ADJ
ajst-5348	2	14	and	and	CCONJ
ajst-5348	2	15	local	local	ADJ
ajst-5348	2	16	attention	attention	NOUN
ajst-5348	2	17	mechanism	mechanism	NOUN
ajst-5348	2	18	decai	decai	PROPN
ajst-5348	2	19	li1	li1	NOUN
ajst-5348	2	20	,	,	PUNCT
ajst-5348	2	21	2	2	NUM
ajst-5348	2	22	,	,	PUNCT
ajst-5348	2	23	a	a	DET
ajst-5348	2	24	,	,	PUNCT
ajst-5348	2	25	xingguo	xingguo	PROPN
ajst-5348	2	26	jiang1	jiang1	PROPN
ajst-5348	2	27	,	,	PUNCT
ajst-5348	2	28	2	2	NUM
ajst-5348	2	29	,	,	PUNCT
ajst-5348	2	30	*	*	PUNCT
ajst-5348	2	31	1artificial	1artificial	NUM
ajst-5348	2	32	intelligence	intelligence	NOUN
ajst-5348	2	33	key	key	ADJ
ajst-5348	2	34	laboratory	laboratory	NOUN
ajst-5348	2	35	of	of	ADP
ajst-5348	2	36	sichuan	sichuan	PROPN
ajst-5348	2	37	province	province	PROPN
ajst-5348	2	38	,	,	PUNCT
ajst-5348	2	39	sichuan	sichuan	PROPN
ajst-5348	2	40	university	university	PROPN
ajst-5348	2	41	of	of	ADP
ajst-5348	2	42	science	science	NOUN
ajst-5348	2	43	and	and	CCONJ
ajst-5348	2	44	engineering	engineering	NOUN
ajst-5348	2	45	,	,	PUNCT
ajst-5348	2	46	zigong	zigong	PROPN
ajst-5348	2	47	643000	643000	NUM
ajst-5348	2	48	,	,	PUNCT
ajst-5348	2	49	china	china	PROPN
ajst-5348	2	50	2school	2school	NUM
ajst-5348	2	51	of	of	ADP
ajst-5348	2	52	automation	automation	NOUN
ajst-5348	2	53	and	and	CCONJ
ajst-5348	2	54	information	information	NOUN
ajst-5348	2	55	engineering	engineering	NOUN
ajst-5348	2	56	,	,	PUNCT
ajst-5348	2	57	sichuan	sichuan	PROPN
ajst-5348	2	58	university	university	PROPN
ajst-5348	2	59	of	of	ADP
ajst-5348	2	60	science	science	NOUN
ajst-5348	2	61	and	and	CCONJ
ajst-5348	2	62	engineering	engineering	NOUN
ajst-5348	2	63	,	,	PUNCT
ajst-5348	2	64	zigong	zigong	PROPN
ajst-5348	2	65	643000	643000	NUM
ajst-5348	2	66	,	,	PUNCT
ajst-5348	2	67	china	china	PROPN
ajst-5348	2	68	a1340998024@qq.com	a1340998024@qq.com	PROPN
ajst-5348	2	69	,	,	PUNCT
ajst-5348	2	70	*	*	PUNCT
ajst-5348	2	71	corresponding	correspond	VERB
ajst-5348	2	72	author	author	NOUN
ajst-5348	2	73	:	:	PUNCT
ajst-5348	2	74	750655632@qq.com	750655632@qq.com	NUM
ajst-5348	2	75	abstract	abstract	NOUN
ajst-5348	2	76	:	:	PUNCT
ajst-5348	2	77	kinship	kinship	NOUN
ajst-5348	2	78	verification	verification	NOUN
ajst-5348	2	79	is	be	AUX
ajst-5348	2	80	an	an	DET
ajst-5348	2	81	important	important	ADJ
ajst-5348	2	82	and	and	CCONJ
ajst-5348	2	83	challenging	challenging	ADJ
ajst-5348	2	84	problem	problem	NOUN
ajst-5348	2	85	in	in	ADP
ajst-5348	2	86	computer	computer	NOUN
ajst-5348	2	87	vision	vision	NOUN
ajst-5348	2	88	.	.	PUNCT
ajst-5348	3	1	how	how	SCONJ
ajst-5348	3	2	to	to	PART
ajst-5348	3	3	extract	extract	VERB
ajst-5348	3	4	discriminative	discriminative	NOUN
ajst-5348	3	5	features	feature	NOUN
ajst-5348	3	6	is	be	AUX
ajst-5348	3	7	the	the	DET
ajst-5348	3	8	key	key	NOUN
ajst-5348	3	9	to	to	PART
ajst-5348	3	10	improve	improve	VERB
ajst-5348	3	11	the	the	DET
ajst-5348	3	12	accuracy	accuracy	NOUN
ajst-5348	3	13	of	of	ADP
ajst-5348	3	14	kinship	kinship	NOUN
ajst-5348	3	15	verification	verification	NOUN
ajst-5348	3	16	.	.	PUNCT
ajst-5348	4	1	at	at	ADP
ajst-5348	4	2	present	present	ADJ
ajst-5348	4	3	,	,	PUNCT
ajst-5348	4	4	convolutional	convolutional	ADJ
ajst-5348	4	5	neural	neural	ADJ
ajst-5348	4	6	networks	network	NOUN
ajst-5348	4	7	(	(	PUNCT
ajst-5348	4	8	cnns	cnns	PROPN
ajst-5348	4	9	)	)	PUNCT
ajst-5348	4	10	for	for	ADP
ajst-5348	4	11	feature	feature	NOUN
ajst-5348	4	12	extraction	extraction	NOUN
ajst-5348	4	13	in	in	ADP
ajst-5348	4	14	the	the	DET
ajst-5348	4	15	field	field	NOUN
ajst-5348	4	16	of	of	ADP
ajst-5348	4	17	computer	computer	NOUN
ajst-5348	4	18	vision	vision	NOUN
ajst-5348	4	19	has	have	AUX
ajst-5348	4	20	achieved	achieve	VERB
ajst-5348	4	21	remarkable	remarkable	ADJ
ajst-5348	4	22	success	success	NOUN
ajst-5348	4	23	,	,	PUNCT
ajst-5348	4	24	making	make	VERB
ajst-5348	4	25	it	it	PRON
ajst-5348	4	26	the	the	DET
ajst-5348	4	27	most	most	ADJ
ajst-5348	4	28	scholars	scholar	NOUN
ajst-5348	4	29	used	use	VERB
ajst-5348	4	30	to	to	PART
ajst-5348	4	31	study	study	VERB
ajst-5348	4	32	kinship	kinship	NOUN
ajst-5348	4	33	verification	verification	NOUN
ajst-5348	4	34	related	relate	VERB
ajst-5348	4	35	issues	issue	NOUN
ajst-5348	4	36	.	.	PUNCT
ajst-5348	5	1	however	however	ADV
ajst-5348	5	2	,	,	PUNCT
ajst-5348	5	3	few	few	ADJ
ajst-5348	5	4	people	people	NOUN
ajst-5348	5	5	use	use	VERB
ajst-5348	5	6	the	the	DET
ajst-5348	5	7	self	self	NOUN
ajst-5348	5	8	-	-	PUNCT
ajst-5348	5	9	attention	attention	NOUN
ajst-5348	5	10	mechanism	mechanism	NOUN
ajst-5348	5	11	with	with	ADP
ajst-5348	5	12	global	global	ADJ
ajst-5348	5	13	capture	capture	NOUN
ajst-5348	5	14	capability	capability	NOUN
ajst-5348	5	15	to	to	PART
ajst-5348	5	16	build	build	VERB
ajst-5348	5	17	a	a	DET
ajst-5348	5	18	backbone	backbone	NOUN
ajst-5348	5	19	feature	feature	NOUN
ajst-5348	5	20	classification	classification	NOUN
ajst-5348	5	21	network	network	NOUN
ajst-5348	5	22	.	.	PUNCT
ajst-5348	6	1	therefore	therefore	ADV
ajst-5348	6	2	,	,	PUNCT
ajst-5348	6	3	this	this	DET
ajst-5348	6	4	paper	paper	NOUN
ajst-5348	6	5	proposes	propose	VERB
ajst-5348	6	6	a	a	DET
ajst-5348	6	7	backbone	backbone	NOUN
ajst-5348	6	8	feature	feature	NOUN
ajst-5348	6	9	extraction	extraction	NOUN
ajst-5348	6	10	network	network	NOUN
ajst-5348	6	11	model	model	NOUN
ajst-5348	6	12	based	base	VERB
ajst-5348	6	13	on	on	ADP
ajst-5348	6	14	a	a	DET
ajst-5348	6	15	non	non	ADJ
ajst-5348	6	16	-	-	NOUN
ajst-5348	6	17	convolution	convolution	NOUN
ajst-5348	6	18	,	,	PUNCT
ajst-5348	6	19	which	which	PRON
ajst-5348	6	20	expands	expand	VERB
ajst-5348	6	21	the	the	DET
ajst-5348	6	22	selection	selection	NOUN
ajst-5348	6	23	range	range	NOUN
ajst-5348	6	24	of	of	ADP
ajst-5348	6	25	traditional	traditional	ADJ
ajst-5348	6	26	classification	classification	NOUN
ajst-5348	6	27	networks	network	NOUN
ajst-5348	6	28	for	for	ADP
ajst-5348	6	29	kinship	kinship	NOUN
ajst-5348	6	30	verification	verification	NOUN
ajst-5348	6	31	related	relate	VERB
ajst-5348	6	32	issues	issue	NOUN
ajst-5348	6	33	.	.	PUNCT
ajst-5348	7	1	specifically	specifically	ADV
ajst-5348	7	2	,	,	PUNCT
ajst-5348	7	3	the	the	DET
ajst-5348	7	4	paper	paper	NOUN
ajst-5348	7	5	proposes	propose	VERB
ajst-5348	7	6	to	to	PART
ajst-5348	7	7	use	use	VERB
ajst-5348	7	8	vision	vision	NOUN
ajst-5348	7	9	transformers	transformer	NOUN
ajst-5348	7	10	as	as	ADP
ajst-5348	7	11	the	the	DET
ajst-5348	7	12	basic	basic	ADJ
ajst-5348	7	13	backbone	backbone	NOUN
ajst-5348	7	14	feature	feature	NOUN
ajst-5348	7	15	extraction	extraction	NOUN
ajst-5348	7	16	network	network	NOUN
ajst-5348	7	17	,	,	PUNCT
ajst-5348	7	18	combined	combine	VERB
ajst-5348	7	19	with	with	ADP
ajst-5348	7	20	cnn	cnn	PROPN
ajst-5348	7	21	with	with	ADP
ajst-5348	7	22	local	local	ADJ
ajst-5348	7	23	attention	attention	NOUN
ajst-5348	7	24	mechanism	mechanism	NOUN
ajst-5348	7	25	,	,	PUNCT
ajst-5348	7	26	to	to	PART
ajst-5348	7	27	provide	provide	VERB
ajst-5348	7	28	a	a	DET
ajst-5348	7	29	unique	unique	ADJ
ajst-5348	7	30	integrated	integrate	VERB
ajst-5348	7	31	solution	solution	NOUN
ajst-5348	7	32	in	in	ADP
ajst-5348	7	33	kinship	kinship	NOUN
ajst-5348	7	34	verification	verification	NOUN
ajst-5348	7	35	.	.	PUNCT
ajst-5348	8	1	the	the	DET
ajst-5348	8	2	proposed	propose	VERB
ajst-5348	8	3	glanet	glanet	NOUN
ajst-5348	8	4	model	model	NOUN
ajst-5348	8	5	is	be	AUX
ajst-5348	8	6	used	use	VERB
ajst-5348	8	7	for	for	ADP
ajst-5348	8	8	kinship	kinship	NOUN
ajst-5348	8	9	verification	verification	NOUN
ajst-5348	8	10	and	and	CCONJ
ajst-5348	8	11	can	can	AUX
ajst-5348	8	12	verify	verify	VERB
ajst-5348	8	13	11	11	NUM
ajst-5348	8	14	kinship	kinship	NOUN
ajst-5348	8	15	pairs	pair	NOUN
ajst-5348	8	16	.	.	PUNCT
ajst-5348	9	1	the	the	DET
ajst-5348	9	2	final	final	ADJ
ajst-5348	9	3	experimental	experimental	ADJ
ajst-5348	9	4	results	result	NOUN
ajst-5348	9	5	show	show	VERB
ajst-5348	9	6	that	that	SCONJ
ajst-5348	9	7	in	in	ADP
ajst-5348	9	8	the	the	DET
ajst-5348	9	9	fiw	fiw	PROPN
ajst-5348	9	10	dataset	dataset	PROPN
ajst-5348	9	11	,	,	PUNCT
ajst-5348	9	12	compared	compare	VERB
ajst-5348	9	13	with	with	ADP
ajst-5348	9	14	the	the	DET
ajst-5348	9	15	rfiw2020	rfiw2020	PROPN
ajst-5348	9	16	challenge	challenge	NOUN
ajst-5348	9	17	leading	lead	VERB
ajst-5348	9	18	method	method	NOUN
ajst-5348	9	19	,	,	PUNCT
ajst-5348	9	20	the	the	DET
ajst-5348	9	21	proposed	propose	VERB
ajst-5348	9	22	method	method	NOUN
ajst-5348	9	23	has	have	VERB
ajst-5348	9	24	better	well	ADJ
ajst-5348	9	25	verification	verification	NOUN
ajst-5348	9	26	effect	effect	NOUN
ajst-5348	9	27	in	in	ADP
ajst-5348	9	28	kinship	kinship	NOUN
ajst-5348	9	29	,	,	PUNCT
ajst-5348	9	30	and	and	CCONJ
ajst-5348	9	31	the	the	DET
ajst-5348	9	32	accuracy	accuracy	NOUN
ajst-5348	9	33	rate	rate	NOUN
ajst-5348	9	34	can	can	AUX
ajst-5348	9	35	reach	reach	VERB
ajst-5348	9	36	79.6	79.6	NUM
ajst-5348	9	37	%	%	NOUN
ajst-5348	9	38	.	.	PUNCT
ajst-5348	10	1	keywords	keyword	NOUN
ajst-5348	10	2	:	:	PUNCT
ajst-5348	10	3	kinship	kinship	NOUN
ajst-5348	10	4	verification	verification	NOUN
ajst-5348	10	5	,	,	PUNCT
ajst-5348	10	6	resnet50	resnet50	NOUN
ajst-5348	10	7	,	,	PUNCT
ajst-5348	10	8	vision	vision	NOUN
ajst-5348	10	9	transformers	transformer	NOUN
ajst-5348	10	10	,	,	PUNCT
ajst-5348	10	11	siamese	siamese	ADJ
ajst-5348	10	12	neural	neural	ADJ
ajst-5348	10	13	network	network	NOUN
ajst-5348	10	14	,	,	PUNCT
ajst-5348	10	15	deep	deep	ADJ
ajst-5348	10	16	learning	learning	NOUN
ajst-5348	10	17	.	.	PUNCT
ajst-5348	11	1	1	1	X
ajst-5348	11	2	.	.	X
ajst-5348	11	3	introduction	introduction	NOUN
ajst-5348	11	4	face	face	NOUN
ajst-5348	11	5	images	image	NOUN
ajst-5348	11	6	contain	contain	VERB
ajst-5348	11	7	a	a	DET
ajst-5348	11	8	large	large	ADJ
ajst-5348	11	9	number	number	NOUN
ajst-5348	11	10	of	of	ADP
ajst-5348	11	11	biological	biological	ADJ
ajst-5348	11	12	features	feature	NOUN
ajst-5348	11	13	.	.	PUNCT
ajst-5348	12	1	existing	exist	VERB
ajst-5348	12	2	psychological	psychological	ADJ
ajst-5348	12	3	and	and	CCONJ
ajst-5348	12	4	sociological	sociological	ADJ
ajst-5348	12	5	studies[1	studies[1	NUM
ajst-5348	12	6	]	]	PUNCT
ajst-5348	12	7	have	have	AUX
ajst-5348	12	8	shown	show	VERB
ajst-5348	12	9	that	that	SCONJ
ajst-5348	12	10	face	face	NOUN
ajst-5348	12	11	is	be	AUX
ajst-5348	12	12	an	an	DET
ajst-5348	12	13	important	important	ADJ
ajst-5348	12	14	clue	clue	NOUN
ajst-5348	12	15	to	to	PART
ajst-5348	12	16	judge	judge	VERB
ajst-5348	12	17	the	the	DET
ajst-5348	12	18	similarity	similarity	NOUN
ajst-5348	12	19	of	of	ADP
ajst-5348	12	20	kinship	kinship	NOUN
ajst-5348	12	21	.	.	PUNCT
ajst-5348	13	1	kinship	kinship	NOUN
ajst-5348	13	2	verification	verification	NOUN
ajst-5348	13	3	is	be	AUX
ajst-5348	13	4	a	a	DET
ajst-5348	13	5	new	new	ADJ
ajst-5348	13	6	research	research	NOUN
ajst-5348	13	7	topic	topic	NOUN
ajst-5348	13	8	in	in	ADP
ajst-5348	13	9	the	the	DET
ajst-5348	13	10	field	field	NOUN
ajst-5348	13	11	of	of	ADP
ajst-5348	13	12	computer	computer	NOUN
ajst-5348	13	13	vision	vision	NOUN
ajst-5348	13	14	,	,	PUNCT
ajst-5348	13	15	which	which	PRON
ajst-5348	13	16	is	be	AUX
ajst-5348	13	17	used	use	VERB
ajst-5348	13	18	to	to	PART
ajst-5348	13	19	predict	predict	VERB
ajst-5348	13	20	whether	whether	SCONJ
ajst-5348	13	21	there	there	PRON
ajst-5348	13	22	is	be	VERB
ajst-5348	13	23	a	a	DET
ajst-5348	13	24	kinship	kinship	NOUN
ajst-5348	13	25	between	between	ADP
ajst-5348	13	26	a	a	DET
ajst-5348	13	27	given	give	VERB
ajst-5348	13	28	face	face	NOUN
ajst-5348	13	29	image	image	NOUN
ajst-5348	13	30	.	.	PUNCT
ajst-5348	14	1	there	there	PRON
ajst-5348	14	2	are	be	VERB
ajst-5348	14	3	significant	significant	ADJ
ajst-5348	14	4	differences	difference	NOUN
ajst-5348	14	5	between	between	ADP
ajst-5348	14	6	kinship	kinship	NOUN
ajst-5348	14	7	verification	verification	NOUN
ajst-5348	14	8	and	and	CCONJ
ajst-5348	14	9	face	face	NOUN
ajst-5348	14	10	recognition	recognition	NOUN
ajst-5348	14	11	.	.	PUNCT
ajst-5348	15	1	face	face	NOUN
ajst-5348	15	2	recognition	recognition	NOUN
ajst-5348	15	3	object	object	NOUN
ajst-5348	15	4	is	be	AUX
ajst-5348	15	5	the	the	DET
ajst-5348	15	6	same	same	ADJ
ajst-5348	15	7	person	person	NOUN
ajst-5348	15	8	,	,	PUNCT
ajst-5348	15	9	the	the	DET
ajst-5348	15	10	same	same	ADJ
ajst-5348	15	11	person	person	NOUN
ajst-5348	15	12	’s	’s	PART
ajst-5348	15	13	facial	facial	ADJ
ajst-5348	15	14	features	feature	NOUN
ajst-5348	15	15	in	in	ADP
ajst-5348	15	16	the	the	DET
ajst-5348	15	17	short	short	ADJ
ajst-5348	15	18	term	term	NOUN
ajst-5348	15	19	little	little	ADJ
ajst-5348	15	20	change	change	NOUN
ajst-5348	15	21	.	.	PUNCT
ajst-5348	16	1	the	the	DET
ajst-5348	16	2	face	face	NOUN
ajst-5348	16	3	images	image	NOUN
ajst-5348	16	4	used	use	VERB
ajst-5348	16	5	for	for	ADP
ajst-5348	16	6	kinship	kinship	NOUN
ajst-5348	16	7	verification	verification	NOUN
ajst-5348	16	8	come	come	VERB
ajst-5348	16	9	from	from	ADP
ajst-5348	16	10	different	different	ADJ
ajst-5348	16	11	people	people	NOUN
ajst-5348	16	12	.	.	PUNCT
ajst-5348	17	1	these	these	DET
ajst-5348	17	2	face	face	NOUN
ajst-5348	17	3	images	image	NOUN
ajst-5348	17	4	have	have	VERB
ajst-5348	17	5	great	great	ADJ
ajst-5348	17	6	differences	difference	NOUN
ajst-5348	17	7	in	in	ADP
ajst-5348	17	8	posture	posture	NOUN
ajst-5348	17	9	,	,	PUNCT
ajst-5348	17	10	illumination	illumination	NOUN
ajst-5348	17	11	,	,	PUNCT
ajst-5348	17	12	expression	expression	NOUN
ajst-5348	17	13	,	,	PUNCT
ajst-5348	17	14	age	age	NOUN
ajst-5348	17	15	,	,	PUNCT
ajst-5348	17	16	gender	gender	NOUN
ajst-5348	17	17	,	,	PUNCT
ajst-5348	17	18	occlusion	occlusion	NOUN
ajst-5348	17	19	and	and	CCONJ
ajst-5348	17	20	other	other	ADJ
ajst-5348	17	21	conditions	condition	NOUN
ajst-5348	17	22	.	.	PUNCT
ajst-5348	18	1	in	in	ADP
ajst-5348	18	2	addition	addition	NOUN
ajst-5348	18	3	,	,	PUNCT
ajst-5348	18	4	the	the	DET
ajst-5348	18	5	complexity	complexity	NOUN
ajst-5348	18	6	of	of	ADP
ajst-5348	18	7	genetic	genetic	ADJ
ajst-5348	18	8	characteristics	characteristic	NOUN
ajst-5348	18	9	also	also	ADV
ajst-5348	18	10	caused	cause	VERB
ajst-5348	18	11	a	a	DET
ajst-5348	18	12	variety	variety	NOUN
ajst-5348	18	13	of	of	ADP
ajst-5348	18	14	facial	facial	ADJ
ajst-5348	18	15	appearance	appearance	NOUN
ajst-5348	18	16	changes	change	NOUN
ajst-5348	18	17	.	.	PUNCT
ajst-5348	19	1	at	at	ADP
ajst-5348	19	2	present	present	ADJ
ajst-5348	19	3	,	,	PUNCT
ajst-5348	19	4	kinship	kinship	NOUN
ajst-5348	19	5	verification	verification	NOUN
ajst-5348	19	6	algorithms	algorithm	NOUN
ajst-5348	19	7	are	be	AUX
ajst-5348	19	8	roughly	roughly	ADV
ajst-5348	19	9	divided	divide	VERB
ajst-5348	19	10	into	into	ADP
ajst-5348	19	11	three	three	NUM
ajst-5348	19	12	categories	category	NOUN
ajst-5348	19	13	:	:	PUNCT
ajst-5348	19	14	methods	method	NOUN
ajst-5348	19	15	based	base	VERB
ajst-5348	19	16	on	on	ADP
ajst-5348	19	17	manual	manual	ADJ
ajst-5348	19	18	features	feature	NOUN
ajst-5348	19	19	[	[	X
ajst-5348	19	20	2	2	NUM
ajst-5348	19	21	-	-	SYM
ajst-5348	19	22	3	3	NUM
ajst-5348	19	23	]	]	PUNCT
ajst-5348	19	24	,	,	PUNCT
ajst-5348	19	25	methods	method	NOUN
ajst-5348	19	26	based	base	VERB
ajst-5348	19	27	on	on	ADP
ajst-5348	19	28	metric	metric	ADJ
ajst-5348	19	29	learning[4	learning[4	PROPN
ajst-5348	19	30	-	-	PUNCT
ajst-5348	19	31	5	5	NUM
ajst-5348	19	32	]	]	PUNCT
ajst-5348	19	33	,	,	PUNCT
ajst-5348	19	34	and	and	CCONJ
ajst-5348	19	35	methods	method	NOUN
ajst-5348	19	36	based	base	VERB
ajst-5348	19	37	on	on	ADP
ajst-5348	19	38	deep	deep	ADJ
ajst-5348	19	39	learning	learning	NOUN
ajst-5348	20	1	[	[	PUNCT
ajst-5348	20	2	6	6	NUM
ajst-5348	20	3	-	-	SYM
ajst-5348	20	4	8	8	NUM
ajst-5348	20	5	]	]	PUNCT
ajst-5348	20	6	.	.	PUNCT
ajst-5348	21	1	the	the	DET
ajst-5348	21	2	feature	feature	NOUN
ajst-5348	21	3	-	-	PUNCT
ajst-5348	21	4	based	base	VERB
ajst-5348	21	5	method	method	NOUN
ajst-5348	21	6	mainly	mainly	ADV
ajst-5348	21	7	uses	use	VERB
ajst-5348	21	8	artificial	artificial	ADJ
ajst-5348	21	9	features	feature	NOUN
ajst-5348	21	10	and	and	CCONJ
ajst-5348	21	11	traditional	traditional	ADJ
ajst-5348	21	12	classifiers	classifier	NOUN
ajst-5348	21	13	to	to	PART
ajst-5348	21	14	verify	verify	VERB
ajst-5348	21	15	kinship	kinship	NOUN
ajst-5348	21	16	.	.	PUNCT
ajst-5348	22	1	this	this	DET
ajst-5348	22	2	method	method	NOUN
ajst-5348	22	3	has	have	VERB
ajst-5348	22	4	low	low	ADJ
ajst-5348	22	5	verification	verification	NOUN
ajst-5348	22	6	accuracy	accuracy	NOUN
ajst-5348	22	7	and	and	CCONJ
ajst-5348	22	8	manual	manual	ADJ
ajst-5348	22	9	extraction	extraction	NOUN
ajst-5348	22	10	of	of	ADP
ajst-5348	22	11	features	feature	NOUN
ajst-5348	22	12	.	.	PUNCT
ajst-5348	23	1	based	base	VERB
ajst-5348	23	2	on	on	ADP
ajst-5348	23	3	the	the	DET
ajst-5348	23	4	metric	metric	ADJ
ajst-5348	23	5	learning	learning	NOUN
ajst-5348	23	6	method	method	NOUN
ajst-5348	23	7	,	,	PUNCT
ajst-5348	23	8	a	a	DET
ajst-5348	23	9	statistical	statistical	ADJ
ajst-5348	23	10	learning	learning	NOUN
ajst-5348	23	11	method	method	NOUN
ajst-5348	23	12	is	be	AUX
ajst-5348	23	13	used	use	VERB
ajst-5348	23	14	to	to	PART
ajst-5348	23	15	learn	learn	VERB
ajst-5348	23	16	an	an	DET
ajst-5348	23	17	effective	effective	ADJ
ajst-5348	23	18	classifier	classifier	NOUN
ajst-5348	23	19	or	or	CCONJ
ajst-5348	23	20	distance	distance	NOUN
ajst-5348	23	21	metric	metric	NOUN
ajst-5348	23	22	.	.	PUNCT
ajst-5348	24	1	the	the	DET
ajst-5348	24	2	learned	learn	VERB
ajst-5348	24	3	model	model	NOUN
ajst-5348	24	4	can	can	AUX
ajst-5348	24	5	increase	increase	VERB
ajst-5348	24	6	the	the	DET
ajst-5348	24	7	distance	distance	NOUN
ajst-5348	24	8	between	between	ADP
ajst-5348	24	9	non	non	ADJ
ajst-5348	24	10	-	-	ADJ
ajst-5348	24	11	kinship	kinship	ADJ
ajst-5348	24	12	pairs	pair	NOUN
ajst-5348	24	13	and	and	CCONJ
ajst-5348	24	14	reduce	reduce	VERB
ajst-5348	24	15	the	the	DET
ajst-5348	24	16	distance	distance	NOUN
ajst-5348	24	17	between	between	ADP
ajst-5348	24	18	kinship	kinship	NOUN
ajst-5348	24	19	pairs	pair	NOUN
ajst-5348	24	20	.	.	PUNCT
ajst-5348	25	1	although	although	SCONJ
ajst-5348	25	2	the	the	DET
ajst-5348	25	3	above	above	ADJ
ajst-5348	25	4	two	two	NUM
ajst-5348	25	5	methods	method	NOUN
ajst-5348	25	6	improve	improve	VERB
ajst-5348	25	7	the	the	DET
ajst-5348	25	8	accuracy	accuracy	NOUN
ajst-5348	25	9	of	of	ADP
ajst-5348	25	10	kinship	kinship	NOUN
ajst-5348	25	11	verification	verification	NOUN
ajst-5348	25	12	,	,	PUNCT
ajst-5348	25	13	how	how	SCONJ
ajst-5348	25	14	to	to	PART
ajst-5348	25	15	extract	extract	VERB
ajst-5348	25	16	more	more	ADV
ajst-5348	25	17	distinguishable	distinguishable	ADJ
ajst-5348	25	18	features	feature	NOUN
ajst-5348	25	19	from	from	ADP
ajst-5348	25	20	different	different	ADJ
ajst-5348	25	21	kinship	kinship	NOUN
ajst-5348	25	22	faces	face	VERB
ajst-5348	25	23	is	be	AUX
ajst-5348	25	24	the	the	DET
ajst-5348	25	25	key	key	NOUN
ajst-5348	25	26	to	to	PART
ajst-5348	25	27	improve	improve	VERB
ajst-5348	25	28	the	the	DET
ajst-5348	25	29	accuracy	accuracy	NOUN
ajst-5348	25	30	.	.	PUNCT
ajst-5348	26	1	the	the	DET
ajst-5348	26	2	method	method	NOUN
ajst-5348	26	3	based	base	VERB
ajst-5348	26	4	on	on	ADP
ajst-5348	26	5	deep	deep	ADJ
ajst-5348	26	6	learning	learning	NOUN
ajst-5348	26	7	is	be	AUX
ajst-5348	26	8	a	a	DET
ajst-5348	26	9	hot	hot	ADJ
ajst-5348	26	10	topic	topic	NOUN
ajst-5348	26	11	in	in	ADP
ajst-5348	26	12	current	current	ADJ
ajst-5348	26	13	research	research	NOUN
ajst-5348	26	14	.	.	PUNCT
ajst-5348	27	1	it	it	PRON
ajst-5348	27	2	mainly	mainly	ADV
ajst-5348	27	3	extracts	extract	VERB
ajst-5348	27	4	the	the	DET
ajst-5348	27	5	depth	depth	NOUN
ajst-5348	27	6	features	feature	NOUN
ajst-5348	27	7	of	of	ADP
ajst-5348	27	8	face	face	NOUN
ajst-5348	27	9	images	image	NOUN
ajst-5348	27	10	,	,	PUNCT
ajst-5348	27	11	analyzes	analyze	VERB
ajst-5348	27	12	the	the	DET
ajst-5348	27	13	depth	depth	NOUN
ajst-5348	27	14	features	feature	NOUN
ajst-5348	27	15	,	,	PUNCT
ajst-5348	27	16	and	and	CCONJ
ajst-5348	27	17	obtains	obtain	VERB
ajst-5348	27	18	the	the	DET
ajst-5348	27	19	verification	verification	NOUN
ajst-5348	27	20	results	result	NOUN
ajst-5348	27	21	of	of	ADP
ajst-5348	27	22	kinship	kinship	NOUN
ajst-5348	27	23	.	.	PUNCT
ajst-5348	28	1	the	the	DET
ajst-5348	28	2	method	method	NOUN
ajst-5348	28	3	based	base	VERB
ajst-5348	28	4	on	on	ADP
ajst-5348	28	5	deep	deep	ADJ
ajst-5348	28	6	learning	learning	NOUN
ajst-5348	28	7	further	far	ADV
ajst-5348	28	8	improves	improve	VERB
ajst-5348	28	9	the	the	DET
ajst-5348	28	10	accuracy	accuracy	NOUN
ajst-5348	28	11	,	,	PUNCT
ajst-5348	28	12	but	but	CCONJ
ajst-5348	28	13	most	most	ADJ
ajst-5348	28	14	of	of	ADP
ajst-5348	28	15	the	the	DET
ajst-5348	28	16	feature	feature	NOUN
ajst-5348	28	17	extraction	extraction	NOUN
ajst-5348	28	18	backbone	backbone	NOUN
ajst-5348	28	19	networks	network	NOUN
ajst-5348	28	20	use	use	VERB
ajst-5348	28	21	cnn	cnn	PROPN
ajst-5348	28	22	with	with	ADP
ajst-5348	28	23	local	local	ADJ
ajst-5348	28	24	attention	attention	NOUN
ajst-5348	28	25	mechanism	mechanism	NOUN
ajst-5348	28	26	,	,	PUNCT
ajst-5348	28	27	and	and	CCONJ
ajst-5348	28	28	build	build	VERB
ajst-5348	28	29	the	the	DET
ajst-5348	28	30	network	network	NOUN
ajst-5348	28	31	around	around	ADP
ajst-5348	28	32	the	the	DET
ajst-5348	28	33	vggface	vggface	NOUN
ajst-5348	28	34	-	-	PUNCT
ajst-5348	28	35	resnet50	resnet50	NOUN
ajst-5348	28	36	architecture	architecture	NOUN
ajst-5348	28	37	and	and	CCONJ
ajst-5348	28	38	some	some	PRON
ajst-5348	28	39	less	less	ADV
ajst-5348	28	40	commonly	commonly	ADV
ajst-5348	28	41	used	use	VERB
ajst-5348	28	42	cnn	cnn	PROPN
ajst-5348	28	43	models	model	NOUN
ajst-5348	28	44	.	.	PUNCT
ajst-5348	29	1	few	few	ADJ
ajst-5348	29	2	researchers	researcher	NOUN
ajst-5348	29	3	use	use	VERB
ajst-5348	29	4	the	the	DET
ajst-5348	29	5	vision	vision	NOUN
ajst-5348	29	6	transformers	transformer	NOUN
ajst-5348	29	7	(	(	PUNCT
ajst-5348	29	8	vit	vit	NOUN
ajst-5348	29	9	)	)	PUNCT
ajst-5348	29	10	model	model	NOUN
ajst-5348	29	11	with	with	ADP
ajst-5348	29	12	global	global	ADJ
ajst-5348	29	13	self	self	NOUN
ajst-5348	29	14	-	-	PUNCT
ajst-5348	29	15	attention	attention	NOUN
ajst-5348	29	16	mechanism	mechanism	NOUN
ajst-5348	29	17	as	as	ADP
ajst-5348	29	18	the	the	DET
ajst-5348	29	19	backbone	backbone	NOUN
ajst-5348	29	20	feature	feature	NOUN
ajst-5348	29	21	extraction	extraction	NOUN
ajst-5348	29	22	network	network	NOUN
ajst-5348	29	23	.	.	PUNCT
ajst-5348	30	1	aiming	aim	VERB
ajst-5348	30	2	at	at	ADP
ajst-5348	30	3	the	the	DET
ajst-5348	30	4	above	above	ADJ
ajst-5348	30	5	problems	problem	NOUN
ajst-5348	30	6	,	,	PUNCT
ajst-5348	30	7	this	this	DET
ajst-5348	30	8	paper	paper	NOUN
ajst-5348	30	9	proposes	propose	VERB
ajst-5348	30	10	a	a	DET
ajst-5348	30	11	siamese	siamese	ADJ
ajst-5348	30	12	neural	neural	ADJ
ajst-5348	30	13	network	network	NOUN
ajst-5348	30	14	glanet	glanet	NOUN
ajst-5348	30	15	,	,	PUNCT
ajst-5348	30	16	which	which	PRON
ajst-5348	30	17	combines	combine	VERB
ajst-5348	30	18	local	local	ADJ
ajst-5348	30	19	attention	attention	NOUN
ajst-5348	30	20	cnn	cnn	PROPN
ajst-5348	30	21	and	and	CCONJ
ajst-5348	30	22	a	a	DET
ajst-5348	30	23	vision	vision	NOUN
ajst-5348	30	24	transformer	transformer	NOUN
ajst-5348	30	25	with	with	ADP
ajst-5348	30	26	global	global	ADJ
ajst-5348	30	27	attention	attention	NOUN
ajst-5348	30	28	mechanism	mechanism	NOUN
ajst-5348	30	29	.	.	PUNCT
ajst-5348	31	1	the	the	DET
ajst-5348	31	2	resnet50[9	resnet50[9	NOUN
ajst-5348	31	3	]	]	PUNCT
ajst-5348	31	4	and	and	CCONJ
ajst-5348	31	5	pvt[10	pvt[10	NOUN
ajst-5348	31	6	]	]	X
ajst-5348	31	7	pre	pre	ADJ
ajst-5348	31	8	-	-	ADJ
ajst-5348	31	9	trained	train	VERB
ajst-5348	31	10	models	model	NOUN
ajst-5348	31	11	are	be	AUX
ajst-5348	31	12	used	use	VERB
ajst-5348	31	13	as	as	ADP
ajst-5348	31	14	the	the	DET
ajst-5348	31	15	backbone	backbone	NOUN
ajst-5348	31	16	of	of	ADP
ajst-5348	31	17	the	the	DET
ajst-5348	31	18	twin	twin	ADJ
ajst-5348	31	19	neural	neural	ADJ
ajst-5348	31	20	network	network	NOUN
ajst-5348	31	21	,	,	PUNCT
ajst-5348	31	22	and	and	CCONJ
ajst-5348	31	23	then	then	ADV
ajst-5348	31	24	the	the	DET
ajst-5348	31	25	features	feature	NOUN
ajst-5348	31	26	extracted	extract	VERB
ajst-5348	31	27	from	from	ADP
ajst-5348	31	28	the	the	DET
ajst-5348	31	29	backbone	backbone	NOUN
ajst-5348	31	30	model	model	NOUN
ajst-5348	31	31	are	be	AUX
ajst-5348	31	32	1×1	1×1	NUM
ajst-5348	31	33	convolution	convolution	NOUN
ajst-5348	31	34	and	and	CCONJ
ajst-5348	31	35	feature	feature	NOUN
ajst-5348	31	36	fusion	fusion	NOUN
ajst-5348	31	37	.	.	PUNCT
ajst-5348	32	1	finally	finally	ADV
ajst-5348	32	2	,	,	PUNCT
ajst-5348	32	3	the	the	DET
ajst-5348	32	4	generated	generate	VERB
ajst-5348	32	5	features	feature	NOUN
ajst-5348	32	6	are	be	AUX
ajst-5348	32	7	input	input	VERB
ajst-5348	32	8	into	into	ADP
ajst-5348	32	9	the	the	DET
ajst-5348	32	10	fully	fully	ADV
ajst-5348	32	11	connected	connected	ADJ
ajst-5348	32	12	network	network	NOUN
ajst-5348	32	13	for	for	ADP
ajst-5348	32	14	kinship	kinship	NOUN
ajst-5348	32	15	verification	verification	NOUN
ajst-5348	32	16	.	.	PUNCT
ajst-5348	33	1	experimental	experimental	ADJ
ajst-5348	33	2	results	result	NOUN
ajst-5348	33	3	show	show	VERB
ajst-5348	33	4	that	that	SCONJ
ajst-5348	33	5	this	this	DET
ajst-5348	33	6	method	method	NOUN
ajst-5348	33	7	can	can	AUX
ajst-5348	33	8	extract	extract	VERB
ajst-5348	33	9	features	feature	NOUN
ajst-5348	33	10	of	of	ADP
ajst-5348	33	11	kinship	kinship	NOUN
ajst-5348	33	12	more	more	ADV
ajst-5348	33	13	effectively	effectively	ADV
ajst-5348	33	14	and	and	CCONJ
ajst-5348	33	15	improve	improve	VERB
ajst-5348	33	16	the	the	DET
ajst-5348	33	17	accuracy	accuracy	NOUN
ajst-5348	33	18	of	of	ADP
ajst-5348	33	19	kinship	kinship	NOUN
ajst-5348	33	20	verification	verification	NOUN
ajst-5348	33	21	.	.	PUNCT
ajst-5348	34	1	compared	compare	VERB
ajst-5348	34	2	with	with	ADP
ajst-5348	34	3	the	the	DET
ajst-5348	34	4	leading	lead	VERB
ajst-5348	34	5	method	method	NOUN
ajst-5348	34	6	of	of	ADP
ajst-5348	34	7	the	the	DET
ajst-5348	34	8	fg2020	fg2020	PROPN
ajst-5348	34	9	challenge	challenge	NOUN
ajst-5348	34	10	,	,	PUNCT
ajst-5348	34	11	the	the	DET
ajst-5348	34	12	twin	twin	ADJ
ajst-5348	34	13	neural	neural	ADJ
ajst-5348	34	14	network	network	NOUN
ajst-5348	34	15	can	can	AUX
ajst-5348	34	16	achieve	achieve	VERB
ajst-5348	34	17	better	well	ADJ
ajst-5348	34	18	results	result	NOUN
ajst-5348	34	19	.	.	PUNCT
ajst-5348	35	1	2	2	X
ajst-5348	35	2	.	.	X
ajst-5348	35	3	feature	feature	NOUN
ajst-5348	35	4	extraction	extraction	NOUN
ajst-5348	35	5	backbone	backbone	NOUN
ajst-5348	35	6	network	network	NOUN
ajst-5348	35	7	2.1	2.1	NUM
ajst-5348	35	8	.	.	PUNCT
ajst-5348	35	9	resnet50	resnet50	NOUN
ajst-5348	35	10	feature	feature	NOUN
ajst-5348	35	11	extraction	extraction	NOUN
ajst-5348	35	12	network	network	NOUN
ajst-5348	35	13	the	the	DET
ajst-5348	35	14	residual	residual	ADJ
ajst-5348	35	15	neural	neural	ADJ
ajst-5348	35	16	network	network	NOUN
ajst-5348	35	17	(	(	PUNCT
ajst-5348	35	18	resnet	resnet	NOUN
ajst-5348	35	19	)	)	PUNCT
ajst-5348	35	20	proposed	propose	VERB
ajst-5348	35	21	by	by	ADP
ajst-5348	35	22	he	he	PRON
ajst-5348	35	23	kaiming	kaiming	PROPN
ajst-5348	35	24	,	,	PUNCT
ajst-5348	35	25	zhang	zhang	PROPN
ajst-5348	35	26	xiangyu	xiangyu	PROPN
ajst-5348	35	27	and	and	CCONJ
ajst-5348	35	28	others	other	NOUN
ajst-5348	36	1	[	[	X
ajst-5348	36	2	9	9	NUM
ajst-5348	36	3	]	]	PUNCT
ajst-5348	36	4	made	make	VERB
ajst-5348	36	5	the	the	DET
ajst-5348	36	6	main	main	ADJ
ajst-5348	36	7	contribution	contribution	NOUN
ajst-5348	36	8	to	to	ADP
ajst-5348	36	9	the	the	DET
ajst-5348	36	10	discovery	discovery	NOUN
ajst-5348	36	11	of	of	ADP
ajst-5348	36	12	"	"	PUNCT
ajst-5348	36	13	degradation	degradation	NOUN
ajst-5348	36	14	phenomenon	phenomenon	NOUN
ajst-5348	36	15	"	"	PUNCT
ajst-5348	36	16	,	,	PUNCT
ajst-5348	36	17	and	and	CCONJ
ajst-5348	36	18	a	a	DET
ajst-5348	36	19	residual	residual	ADJ
ajst-5348	36	20	structure	structure	NOUN
ajst-5348	36	21	is	be	AUX
ajst-5348	36	22	invented	invent	VERB
ajst-5348	36	23	for	for	ADP
ajst-5348	36	24	the	the	DET
ajst-5348	36	25	degradation	degradation	NOUN
ajst-5348	36	26	phenomenon	phenomenon	NOUN
ajst-5348	36	27	,	,	PUNCT
ajst-5348	36	28	which	which	PRON
ajst-5348	36	29	greatly	greatly	ADV
ajst-5348	36	30	eliminates	eliminate	VERB
ajst-5348	36	31	the	the	DET
ajst-5348	36	32	difficulty	difficulty	NOUN
ajst-5348	36	33	of	of	ADP
ajst-5348	36	34	training	train	VERB
ajst-5348	36	35	neural	neural	ADJ
ajst-5348	36	36	networks	network	NOUN
ajst-5348	36	37	with	with	ADP
ajst-5348	36	38	large	large	ADJ
ajst-5348	36	39	depth	depth	NOUN
ajst-5348	36	40	.	.	PUNCT
ajst-5348	37	1	subsequently	subsequently	ADV
ajst-5348	37	2	,	,	PUNCT
ajst-5348	37	3	the	the	DET
ajst-5348	37	4	network	network	NOUN
ajst-5348	37	5	models	model	NOUN
ajst-5348	37	6	such	such	ADJ
ajst-5348	37	7	as	as	ADP
ajst-5348	37	8	resnet-34	resnet-34	PROPN
ajst-5348	37	9	,	,	PUNCT
ajst-5348	37	10	resnet-50	resnet-50	PROPN
ajst-5348	37	11	and	and	CCONJ
ajst-5348	37	12	resnet101	resnet101	PROPN
ajst-5348	37	13	are	be	AUX
ajst-5348	37	14	derived	derive	VERB
ajst-5348	37	15	.	.	PUNCT
ajst-5348	38	1	the	the	DET
ajst-5348	38	2	residual	residual	ADJ
ajst-5348	38	3	principle	principle	ADJ
ajst-5348	38	4	diagram	diagram	NOUN
ajst-5348	38	5	is	be	AUX
ajst-5348	38	6	shown	show	VERB
ajst-5348	38	7	in	in	ADP
ajst-5348	38	8	fig	fig	NOUN
ajst-5348	38	9	.	.	PUNCT
ajst-5348	39	1	1	1	NUM
ajst-5348	39	2	.	.	X
ajst-5348	39	3	58	58	NUM
ajst-5348	39	4	figure	figure	NOUN
ajst-5348	39	5	1	1	NUM
ajst-5348	39	6	.	.	PUNCT
ajst-5348	39	7	residual	residual	ADJ
ajst-5348	39	8	structure	structure	NOUN
ajst-5348	39	9	among	among	ADP
ajst-5348	39	10	them	they	PRON
ajst-5348	39	11	,	,	PUNCT
ajst-5348	39	12	fig.1(a	fig.1(a	PROPN
ajst-5348	39	13	)	)	PUNCT
ajst-5348	39	14	is	be	AUX
ajst-5348	39	15	a	a	DET
ajst-5348	39	16	double	double	ADJ
ajst-5348	39	17	residual	residual	ADJ
ajst-5348	39	18	module	module	NOUN
ajst-5348	39	19	,	,	PUNCT
ajst-5348	39	20	the	the	DET
ajst-5348	39	21	main	main	ADJ
ajst-5348	39	22	branch	branch	NOUN
ajst-5348	39	23	is	be	AUX
ajst-5348	39	24	composed	compose	VERB
ajst-5348	39	25	of	of	ADP
ajst-5348	39	26	two	two	NUM
ajst-5348	39	27	layers	layer	NOUN
ajst-5348	39	28	of	of	ADP
ajst-5348	39	29	3×3	3×3	NUM
ajst-5348	39	30	convolution	convolution	NOUN
ajst-5348	39	31	layers	layer	NOUN
ajst-5348	39	32	,	,	PUNCT
ajst-5348	39	33	each	each	PRON
ajst-5348	39	34	of	of	ADP
ajst-5348	39	35	which	which	PRON
ajst-5348	39	36	is	be	AUX
ajst-5348	39	37	followed	follow	VERB
ajst-5348	39	38	by	by	ADP
ajst-5348	39	39	batch	batch	NOUN
ajst-5348	39	40	normalization	normalization	NOUN
ajst-5348	39	41	.	.	PUNCT
ajst-5348	40	1	residual	residual	ADJ
ajst-5348	40	2	structure	structure	NOUN
ajst-5348	40	3	is	be	AUX
ajst-5348	40	4	a	a	DET
ajst-5348	40	5	special	special	ADJ
ajst-5348	40	6	kind	kind	NOUN
ajst-5348	40	7	of	of	ADP
ajst-5348	40	8	constant	constant	ADJ
ajst-5348	40	9	mapping	mapping	NOUN
ajst-5348	40	10	,	,	PUNCT
ajst-5348	40	11	which	which	PRON
ajst-5348	40	12	does	do	AUX
ajst-5348	40	13	not	not	PART
ajst-5348	40	14	introduce	introduce	VERB
ajst-5348	40	15	many	many	ADJ
ajst-5348	40	16	parameters	parameter	NOUN
ajst-5348	40	17	and	and	CCONJ
ajst-5348	40	18	calculation	calculation	NOUN
ajst-5348	40	19	.	.	PUNCT
ajst-5348	41	1	the	the	DET
ajst-5348	41	2	residual	residual	ADJ
ajst-5348	41	3	structure	structure	NOUN
ajst-5348	41	4	is	be	AUX
ajst-5348	41	5	composed	compose	VERB
ajst-5348	41	6	of	of	ADP
ajst-5348	41	7	the	the	DET
ajst-5348	41	8	direct	direct	ADJ
ajst-5348	41	9	output	output	NOUN
ajst-5348	41	10	𝑥	𝑥	PROPN
ajst-5348	41	11	of	of	ADP
ajst-5348	41	12	the	the	DET
ajst-5348	41	13	right	right	ADJ
ajst-5348	41	14	branch	branch	NOUN
ajst-5348	41	15	and	and	CCONJ
ajst-5348	41	16	the	the	DET
ajst-5348	41	17	output	output	NOUN
ajst-5348	41	18	𝑓	𝑓	PRON
ajst-5348	41	19	𝑥	𝑥	NOUN
ajst-5348	41	20	of	of	ADP
ajst-5348	41	21	the	the	DET
ajst-5348	41	22	stack	stack	NOUN
ajst-5348	41	23	layer	layer	NOUN
ajst-5348	41	24	,	,	PUNCT
ajst-5348	41	25	and	and	CCONJ
ajst-5348	41	26	the	the	DET
ajst-5348	41	27	finally	finally	ADV
ajst-5348	41	28	output	output	NOUN
ajst-5348	41	29	is	be	AUX
ajst-5348	41	30	expressed	express	VERB
ajst-5348	41	31	as	as	ADP
ajst-5348	41	32	:	:	PUNCT
ajst-5348	41	33			PROPN
ajst-5348	42	1	y	y	PUNCT
ajst-5348	42	2	f	f	PROPN
ajst-5348	43	1	x	x	X
ajst-5348	43	2	x	x	PROPN
ajst-5348	43	3			X
ajst-5348	43	4	(	(	PUNCT
ajst-5348	43	5	1	1	X
ajst-5348	43	6	)	)	PUNCT
ajst-5348	43	7	in	in	ADP
ajst-5348	43	8	the	the	DET
ajst-5348	43	9	equation	equation	NOUN
ajst-5348	43	10	,	,	PUNCT
ajst-5348	43	11	𝑥	𝑥	X
ajst-5348	43	12	,	,	PUNCT
ajst-5348	43	13	y	y	PROPN
ajst-5348	43	14	denote	denote	VERB
ajst-5348	43	15	the	the	DET
ajst-5348	43	16	input	input	NOUN
ajst-5348	43	17	and	and	CCONJ
ajst-5348	43	18	output	output	NOUN
ajst-5348	43	19	respectively	respectively	ADV
ajst-5348	43	20	,	,	PUNCT
ajst-5348	43	21	𝑓	𝑓	PRON
ajst-5348	43	22	𝑥	𝑥	PROPN
ajst-5348	43	23	denote	denote	VERB
ajst-5348	43	24	the	the	DET
ajst-5348	43	25	residual	residual	ADJ
ajst-5348	43	26	mapping	mapping	NOUN
ajst-5348	43	27	.	.	PUNCT
ajst-5348	44	1	the	the	DET
ajst-5348	44	2	deeper	deep	ADJ
ajst-5348	44	3	resnet50	resnet50	NOUN
ajst-5348	44	4	,	,	PUNCT
ajst-5348	44	5	resnet101	resnet101	PROPN
ajst-5348	44	6	and	and	CCONJ
ajst-5348	44	7	resnet152	resnet152	PROPN
ajst-5348	44	8	use	use	VERB
ajst-5348	44	9	three	three	NUM
ajst-5348	44	10	-	-	PUNCT
ajst-5348	44	11	layer	layer	NOUN
ajst-5348	44	12	residual	residual	ADJ
ajst-5348	44	13	structure	structure	NOUN
ajst-5348	44	14	.	.	PUNCT
ajst-5348	45	1	fig.1(b	fig.1(b	ADJ
ajst-5348	45	2	)	)	PUNCT
ajst-5348	45	3	shows	show	VERB
ajst-5348	45	4	the	the	DET
ajst-5348	45	5	three	three	NUM
ajst-5348	45	6	-	-	PUNCT
ajst-5348	45	7	layer	layer	NOUN
ajst-5348	45	8	residual	residual	ADJ
ajst-5348	45	9	module	module	NOUN
ajst-5348	45	10	.	.	PUNCT
ajst-5348	46	1	the	the	DET
ajst-5348	46	2	dimension	dimension	NOUN
ajst-5348	46	3	’s	’s	PART
ajst-5348	46	4	reduction	reduction	NOUN
ajst-5348	46	5	&	&	CCONJ
ajst-5348	46	6	elevation	elevation	NOUN
ajst-5348	46	7	are	be	AUX
ajst-5348	46	8	realized	realize	VERB
ajst-5348	46	9	through	through	ADP
ajst-5348	46	10	two	two	NUM
ajst-5348	46	11	1×1convolution	1×1convolution	NUM
ajst-5348	46	12	layers	layer	NOUN
ajst-5348	46	13	,	,	PUNCT
ajst-5348	46	14	which	which	PRON
ajst-5348	46	15	can	can	AUX
ajst-5348	46	16	effectively	effectively	ADV
ajst-5348	46	17	solve	solve	VERB
ajst-5348	46	18	the	the	DET
ajst-5348	46	19	problem	problem	NOUN
ajst-5348	46	20	of	of	ADP
ajst-5348	46	21	excessive	excessive	ADJ
ajst-5348	46	22	parameters	parameter	NOUN
ajst-5348	46	23	of	of	ADP
ajst-5348	46	24	the	the	DET
ajst-5348	46	25	two	two	NUM
ajst-5348	46	26	-	-	PUNCT
ajst-5348	46	27	layer	layer	NOUN
ajst-5348	46	28	residual	residual	ADJ
ajst-5348	46	29	module	module	NOUN
ajst-5348	46	30	and	and	CCONJ
ajst-5348	46	31	time	time	NOUN
ajst-5348	46	32	-	-	PUNCT
ajst-5348	46	33	consuming	consume	VERB
ajst-5348	46	34	training	training	NOUN
ajst-5348	46	35	.	.	PUNCT
ajst-5348	47	1	resnet50	resnet50	NOUN
ajst-5348	47	2	is	be	AUX
ajst-5348	47	3	selected	select	VERB
ajst-5348	47	4	as	as	ADP
ajst-5348	47	5	the	the	DET
ajst-5348	47	6	backbone	backbone	NOUN
ajst-5348	47	7	feature	feature	NOUN
ajst-5348	47	8	extraction	extraction	NOUN
ajst-5348	47	9	network	network	NOUN
ajst-5348	47	10	of	of	ADP
ajst-5348	47	11	twin	twin	ADJ
ajst-5348	47	12	neural	neural	ADJ
ajst-5348	47	13	network	network	NOUN
ajst-5348	47	14	model	model	NOUN
ajst-5348	47	15	.	.	PUNCT
ajst-5348	48	1	the	the	DET
ajst-5348	48	2	detailed	detailed	ADJ
ajst-5348	48	3	parameters	parameter	NOUN
ajst-5348	48	4	of	of	ADP
ajst-5348	48	5	resnet50	resnet50	NOUN
ajst-5348	48	6	architecture	architecture	NOUN
ajst-5348	48	7	are	be	AUX
ajst-5348	48	8	shown	show	VERB
ajst-5348	48	9	in	in	ADP
ajst-5348	48	10	table	table	NOUN
ajst-5348	48	11	1	1	NUM
ajst-5348	48	12	.	.	PUNCT
ajst-5348	48	13	table	table	NOUN
ajst-5348	48	14	1	1	NUM
ajst-5348	48	15	.	.	PUNCT
ajst-5348	49	1	detailed	detailed	ADJ
ajst-5348	49	2	resnet50	resnet50	NOUN
ajst-5348	49	3	architecture	architecture	NOUN
ajst-5348	49	4	parameters	parameter	NOUN
ajst-5348	49	5	layer	layer	NOUN
ajst-5348	49	6	name	name	NOUN
ajst-5348	49	7	output	output	NOUN
ajst-5348	49	8	size	size	NOUN
ajst-5348	49	9	resnet50	resnet50	NOUN
ajst-5348	49	10	conv1	conv1	NOUN
ajst-5348	49	11	112	112	NUM
ajst-5348	49	12	112	112	NUM
ajst-5348	49	13	7	7	NUM
ajst-5348	49	14	7，64，stride2	7，64，stride2	NOUN
ajst-5348	49	15	3	3	NUM
ajst-5348	49	16	3max	3max	NUM
ajst-5348	49	17	pool，stride2	pool，stride2	PROPN
ajst-5348	49	18	conv2_x	conv2_x	VERB
ajst-5348	49	19	56	56	NUM
ajst-5348	49	20	56	56	NUM
ajst-5348	49	21	1	1	NUM
ajst-5348	49	22	,	,	PUNCT
ajst-5348	49	23	64	64	NUM
ajst-5348	49	24	3	3	NUM
ajst-5348	49	25	3	3	NUM
ajst-5348	49	26	,	,	PUNCT
ajst-5348	49	27	64	64	NUM
ajst-5348	49	28	3	3	NUM
ajst-5348	49	29	1	1	NUM
ajst-5348	49	30	,	,	PUNCT
ajst-5348	49	31	1	1	NUM
ajst-5348	49	32	1	1	NUM
ajst-5348	49	33	256	256	NUM
ajst-5348	49	34			NOUN
ajst-5348	49	35			NOUN
ajst-5348	49	36			NOUN
ajst-5348	49	37			PUNCT
ajst-5348	49	38			PROPN
ajst-5348	49	39			NOUN
ajst-5348	49	40			PROPN
ajst-5348	49	41			PROPN
ajst-5348	49	42			PROPN
ajst-5348	49	43	conv3_x	conv3_x	PROPN
ajst-5348	50	1	28	28	NUM
ajst-5348	50	2	28	28	NUM
ajst-5348	50	3	1,128	1,128	NUM
ajst-5348	50	4	3	3	NUM
ajst-5348	50	5	3,128	3,128	NUM
ajst-5348	50	6	4	4	NUM
ajst-5348	50	7	1	1	NUM
ajst-5348	50	8	,	,	PUNCT
ajst-5348	50	9	1	1	NUM
ajst-5348	50	10	121	121	NUM
ajst-5348	50	11	5	5	NUM
ajst-5348	50	12			NOUN
ajst-5348	50	13			NOUN
ajst-5348	50	14			NOUN
ajst-5348	50	15			PUNCT
ajst-5348	50	16			PROPN
ajst-5348	50	17			NOUN
ajst-5348	50	18			PROPN
ajst-5348	50	19			PROPN
ajst-5348	50	20			PROPN
ajst-5348	50	21	conv4_x	conv4_x	PROPN
ajst-5348	50	22	14	14	NUM
ajst-5348	50	23	14	14	NUM
ajst-5348	50	24	1	1	NUM
ajst-5348	50	25	,	,	PUNCT
ajst-5348	50	26	256	256	NUM
ajst-5348	50	27	3	3	NUM
ajst-5348	50	28	3	3	NUM
ajst-5348	50	29	,	,	PUNCT
ajst-5348	50	30	256	256	NUM
ajst-5348	50	31	6	6	NUM
ajst-5348	50	32	1	1	NUM
ajst-5348	50	33	,	,	PUNCT
ajst-5348	50	34	1	1	NUM
ajst-5348	50	35	1	1	NUM
ajst-5348	50	36	1024	1024	NUM
ajst-5348	50	37			NOUN
ajst-5348	50	38			NOUN
ajst-5348	50	39			NOUN
ajst-5348	50	40			PUNCT
ajst-5348	50	41			PROPN
ajst-5348	50	42			NOUN
ajst-5348	50	43			PROPN
ajst-5348	50	44			PROPN
ajst-5348	50	45			PROPN
ajst-5348	50	46	conv5_x	conv5_x	PROPN
ajst-5348	50	47	7	7	NUM
ajst-5348	50	48	7	7	NUM
ajst-5348	50	49	1	1	NUM
ajst-5348	50	50	,	,	PUNCT
ajst-5348	50	51	512	512	NUM
ajst-5348	50	52	3	3	NUM
ajst-5348	50	53	3	3	NUM
ajst-5348	50	54	,	,	PUNCT
ajst-5348	50	55	512	512	NUM
ajst-5348	50	56	3	3	NUM
ajst-5348	50	57	1	1	NUM
ajst-5348	50	58	,	,	PUNCT
ajst-5348	50	59	1	1	NUM
ajst-5348	50	60	1	1	NUM
ajst-5348	50	61	2048	2048	NUM
ajst-5348	50	62			NOUN
ajst-5348	50	63			NOUN
ajst-5348	50	64			NOUN
ajst-5348	50	65			PUNCT
ajst-5348	50	66			PROPN
ajst-5348	50	67			NOUN
ajst-5348	50	68			PROPN
ajst-5348	50	69			PROPN
ajst-5348	50	70			PROPN
ajst-5348	50	71	1	1	NUM
ajst-5348	50	72	1	1	NUM
ajst-5348	50	73	average	average	ADJ
ajst-5348	50	74	pool	pool	NOUN
ajst-5348	50	75	,	,	PUNCT
ajst-5348	50	76	1000	1000	NUM
ajst-5348	50	77	-	-	SYM
ajst-5348	50	78	d	d	NOUN
ajst-5348	50	79	fc	fc	PROPN
ajst-5348	50	80	2.2	2.2	NUM
ajst-5348	50	81	.	.	PUNCT
ajst-5348	51	1	pvt	pvt	PROPN
ajst-5348	51	2	feature	feature	NOUN
ajst-5348	51	3	extraction	extraction	NOUN
ajst-5348	51	4	network	network	NOUN
ajst-5348	51	5	pvt	pvt	PROPN
ajst-5348	51	6	is	be	AUX
ajst-5348	51	7	an	an	DET
ajst-5348	51	8	improved	improved	ADJ
ajst-5348	51	9	version	version	NOUN
ajst-5348	51	10	of	of	ADP
ajst-5348	51	11	vision	vision	NOUN
ajst-5348	51	12	transformer	transformer	NOUN
ajst-5348	51	13	proposed	propose	VERB
ajst-5348	51	14	by	by	ADP
ajst-5348	51	15	wang	wang	PROPN
ajst-5348	51	16	et	et	PROPN
ajst-5348	51	17	al.[10	al.[10	PROPN
ajst-5348	51	18	]	]	PUNCT
ajst-5348	51	19	,	,	PUNCT
ajst-5348	51	20	which	which	PRON
ajst-5348	51	21	has	have	VERB
ajst-5348	51	22	two	two	NUM
ajst-5348	51	23	main	main	ADJ
ajst-5348	51	24	advantages	advantage	NOUN
ajst-5348	51	25	:	:	PUNCT
ajst-5348	51	26	1	1	X
ajst-5348	51	27	)	)	PUNCT
ajst-5348	51	28	it	it	PRON
ajst-5348	51	29	generates	generate	VERB
ajst-5348	51	30	multi	multi	ADJ
ajst-5348	51	31	-	-	ADJ
ajst-5348	51	32	scale	scale	ADJ
ajst-5348	51	33	feature	feature	NOUN
ajst-5348	51	34	maps	map	NOUN
ajst-5348	51	35	between	between	ADP
ajst-5348	51	36	each	each	DET
ajst-5348	51	37	block	block	NOUN
ajst-5348	51	38	,	,	PUNCT
ajst-5348	51	39	combining	combine	VERB
ajst-5348	51	40	the	the	DET
ajst-5348	51	41	advantages	advantage	NOUN
ajst-5348	51	42	of	of	ADP
ajst-5348	51	43	cnn	cnn	PROPN
ajst-5348	51	44	.	.	PUNCT
ajst-5348	52	1	2	2	X
ajst-5348	52	2	)	)	PUNCT
ajst-5348	52	3	it	it	PRON
ajst-5348	52	4	introduces	introduce	VERB
ajst-5348	52	5	spatialreduction	spatialreduction	NOUN
ajst-5348	52	6	technology	technology	NOUN
ajst-5348	52	7	to	to	PART
ajst-5348	52	8	greatly	greatly	ADV
ajst-5348	52	9	reduce	reduce	VERB
ajst-5348	52	10	transformer	transformer	ADJ
ajst-5348	52	11	computation	computation	NOUN
ajst-5348	52	12	and	and	CCONJ
ajst-5348	52	13	memory	memory	NOUN
ajst-5348	52	14	to	to	PART
ajst-5348	52	15	train	train	VERB
ajst-5348	52	16	each	each	DET
ajst-5348	52	17	model	model	NOUN
ajst-5348	52	18	.	.	PUNCT
ajst-5348	53	1	an	an	DET
ajst-5348	53	2	overview	overview	NOUN
ajst-5348	53	3	of	of	ADP
ajst-5348	53	4	the	the	DET
ajst-5348	53	5	pvt	pvt	PROPN
ajst-5348	53	6	network	network	NOUN
ajst-5348	53	7	architecture	architecture	NOUN
ajst-5348	53	8	is	be	AUX
ajst-5348	53	9	shown	show	VERB
ajst-5348	53	10	in	in	ADP
ajst-5348	53	11	figure	figure	NOUN
ajst-5348	53	12	2	2	NUM
ajst-5348	53	13	.	.	NOUN
ajst-5348	53	14	59	59	NUM
ajst-5348	53	15	figure	figure	NOUN
ajst-5348	53	16	2	2	NUM
ajst-5348	53	17	.	.	X
ajst-5348	53	18	pvt	pvt	PROPN
ajst-5348	53	19	backbone	backbone	NOUN
ajst-5348	53	20	feature	feature	NOUN
ajst-5348	53	21	extraction	extraction	NOUN
ajst-5348	53	22	network	network	NOUN
ajst-5348	53	23	architecture	architecture	NOUN
ajst-5348	53	24	in	in	ADP
ajst-5348	53	25	pvt	pvt	PROPN
ajst-5348	53	26	,	,	PUNCT
ajst-5348	53	27	the	the	DET
ajst-5348	53	28	transformer	transformer	ADJ
ajst-5348	53	29	encoder	encoder	NOUN
ajst-5348	53	30	in	in	ADP
ajst-5348	53	31	stage	stage	NOUN
ajst-5348	53	32	i	i	PRON
ajst-5348	53	33	has	have	AUX
ajst-5348	53	34	li	li	PROPN
ajst-5348	53	35	encoder	encoder	NOUN
ajst-5348	53	36	layers	layer	NOUN
ajst-5348	53	37	,	,	PUNCT
ajst-5348	53	38	each	each	PRON
ajst-5348	53	39	of	of	ADP
ajst-5348	53	40	which	which	PRON
ajst-5348	53	41	consists	consist	VERB
ajst-5348	53	42	of	of	ADP
ajst-5348	53	43	an	an	DET
ajst-5348	53	44	attention	attention	NOUN
ajst-5348	53	45	layer	layer	NOUN
ajst-5348	53	46	and	and	CCONJ
ajst-5348	53	47	a	a	DET
ajst-5348	53	48	feedforward	feedforward	ADJ
ajst-5348	53	49	network	network	NOUN
ajst-5348	53	50	layer	layer	NOUN
ajst-5348	53	51	.	.	PUNCT
ajst-5348	54	1	pvt	pvt	PROPN
ajst-5348	54	2	is	be	AUX
ajst-5348	54	3	easier	easy	ADJ
ajst-5348	54	4	to	to	PART
ajst-5348	54	5	train	train	VERB
ajst-5348	54	6	because	because	SCONJ
ajst-5348	54	7	it	it	PRON
ajst-5348	54	8	replaces	replace	VERB
ajst-5348	54	9	the	the	DET
ajst-5348	54	10	traditional	traditional	ADJ
ajst-5348	54	11	multi	multi	ADJ
ajst-5348	54	12	-	-	ADJ
ajst-5348	54	13	head	head	ADJ
ajst-5348	54	14	attention	attention	NOUN
ajst-5348	54	15	layer[11	layer[11	NOUN
ajst-5348	54	16	]	]	PUNCT
ajst-5348	54	17	with	with	ADP
ajst-5348	54	18	a	a	DET
ajst-5348	54	19	spatial	spatial	ADJ
ajst-5348	54	20	-	-	PUNCT
ajst-5348	54	21	reduce	reduce	VERB
ajst-5348	54	22	attention	attention	NOUN
ajst-5348	54	23	(	(	PUNCT
ajst-5348	54	24	sra	sra	NOUN
ajst-5348	54	25	)	)	PUNCT
ajst-5348	54	26	layer	layer	NOUN
ajst-5348	54	27	.	.	PUNCT
ajst-5348	55	1	this	this	DET
ajst-5348	55	2	newly	newly	ADV
ajst-5348	55	3	designed	design	VERB
ajst-5348	55	4	sra	sra	NOUN
ajst-5348	55	5	layer	layer	NOUN
ajst-5348	55	6	performs	perform	VERB
ajst-5348	55	7	similar	similar	ADJ
ajst-5348	55	8	to	to	ADP
ajst-5348	55	9	multi	multi	ADJ
ajst-5348	55	10	-	-	ADJ
ajst-5348	55	11	head	head	ADJ
ajst-5348	55	12	attention	attention	NOUN
ajst-5348	55	13	,	,	PUNCT
ajst-5348	55	14	which	which	PRON
ajst-5348	55	15	receives	receive	VERB
ajst-5348	55	16	a	a	DET
ajst-5348	55	17	queryq	queryq	NOUN
ajst-5348	55	18	,	,	PUNCT
ajst-5348	55	19	a	a	DET
ajst-5348	55	20	key	key	ADJ
ajst-5348	55	21	k	k	NOUN
ajst-5348	55	22	,	,	PUNCT
ajst-5348	55	23	and	and	CCONJ
ajst-5348	55	24	a	a	DET
ajst-5348	55	25	valuevas	valuevas	NOUN
ajst-5348	55	26	input	input	NOUN
ajst-5348	55	27	and	and	CCONJ
ajst-5348	55	28	output	output	NOUN
ajst-5348	55	29	characteristics	characteristic	NOUN
ajst-5348	55	30	.	.	PUNCT
ajst-5348	56	1	however	however	ADV
ajst-5348	56	2	,	,	PUNCT
ajst-5348	56	3	sra	sra	PROPN
ajst-5348	56	4	reduces	reduce	VERB
ajst-5348	56	5	the	the	DET
ajst-5348	56	6	spatial	spatial	ADJ
ajst-5348	56	7	scale	scale	NOUN
ajst-5348	56	8	of	of	ADP
ajst-5348	56	9	k	k	PROPN
ajst-5348	56	10	and	and	CCONJ
ajst-5348	56	11	v	v	NOUN
ajst-5348	56	12	before	before	ADP
ajst-5348	56	13	the	the	DET
ajst-5348	56	14	attention	attention	NOUN
ajst-5348	56	15	operation	operation	NOUN
ajst-5348	56	16	to	to	PART
ajst-5348	56	17	reduce	reduce	VERB
ajst-5348	56	18	the	the	DET
ajst-5348	56	19	computational	computational	ADJ
ajst-5348	56	20	overhead	overhead	NOUN
ajst-5348	56	21	.	.	PUNCT
ajst-5348	57	1	the	the	DET
ajst-5348	57	2	detailed	detailed	ADJ
ajst-5348	57	3	description	description	NOUN
ajst-5348	57	4	of	of	ADP
ajst-5348	57	5	sra	sra	PROPN
ajst-5348	57	6	is	be	AUX
ajst-5348	57	7	as	as	SCONJ
ajst-5348	57	8	follows	follow	VERB
ajst-5348	57	9	:	:	PUNCT
ajst-5348	58	1			PROPN
ajst-5348	58	2			NOUN
ajst-5348	58	3	reduce	reduce	PROPN
ajst-5348	58	4	(	(	PUNCT
ajst-5348	58	5	)	)	PUNCT
ajst-5348	58	6	norm	norm	NOUN
ajst-5348	58	7	reshape	reshape	NOUN
ajst-5348	58	8	,	,	PUNCT
ajst-5348	58	9	s	s	VERB
ajst-5348	58	10	ix	ix	ADJ
ajst-5348	58	11	x	x	PUNCT
ajst-5348	58	12	r	r	NOUN
ajst-5348	58	13	w	w	NOUN
ajst-5348	58	14	(	(	PUNCT
ajst-5348	58	15	2	2	NUM
ajst-5348	58	16	)	)	PUNCT
ajst-5348	58	17	formula	formula	NOUN
ajst-5348	58	18	(	(	PUNCT
ajst-5348	58	19	2	2	X
ajst-5348	58	20	)	)	PUNCT
ajst-5348	58	21	describes	describe	VERB
ajst-5348	58	22	how	how	SCONJ
ajst-5348	58	23	to	to	PART
ajst-5348	58	24	spatially	spatially	ADV
ajst-5348	58	25	restore	restore	VERB
ajst-5348	58	26	the	the	DET
ajst-5348	58	27	input	input	NOUN
ajst-5348	58	28	sequence	sequence	NOUN
ajst-5348	58	29	.	.	PUNCT
ajst-5348	59	1	in	in	ADP
ajst-5348	59	2	the	the	DET
ajst-5348	59	3	formula	formula	NOUN
ajst-5348	59	4	,	,	PUNCT
ajst-5348	59	5	x	x	PRON
ajst-5348	59	6	represents	represent	VERB
ajst-5348	59	7	an	an	DET
ajst-5348	59	8	input	input	NOUN
ajst-5348	59	9	sequence	sequence	NOUN
ajst-5348	59	10	,	,	PUNCT
ajst-5348	59	11	r	r	NOUN
ajst-5348	59	12	represents	represent	VERB
ajst-5348	59	13	the	the	DET
ajst-5348	59	14	reduction	reduction	NOUN
ajst-5348	59	15	ratio	ratio	NOUN
ajst-5348	59	16	,	,	PUNCT
ajst-5348	59	17	w	w	PROPN
ajst-5348	59	18	is	be	AUX
ajst-5348	59	19	a	a	DET
ajst-5348	59	20	linear	linear	ADJ
ajst-5348	59	21	projection	projection	NOUN
ajst-5348	59	22	of	of	ADP
ajst-5348	59	23	the	the	DET
ajst-5348	59	24	dimension	dimension	NOUN
ajst-5348	59	25	reduction	reduction	NOUN
ajst-5348	59	26	of	of	ADP
ajst-5348	59	27	the	the	DET
ajst-5348	59	28	input	input	NOUN
ajst-5348	59	29	sequence	sequence	NOUN
ajst-5348	59	30	,	,	PUNCT
ajst-5348	59	31	and	and	CCONJ
ajst-5348	59	32	the	the	DET
ajst-5348	59	33	input	input	NOUN
ajst-5348	59	34	x	x	PUNCT
ajst-5348	59	35	is	be	AUX
ajst-5348	59	36	adjusted	adjust	VERB
ajst-5348	59	37	to	to	ADP
ajst-5348	59	38			NOUN
ajst-5348	60	1	2	2	PROPN
ajst-5348	60	2	2	2	NUM
ajst-5348	60	3	hw	hw	NOUN
ajst-5348	60	4	r	r	NOUN
ajst-5348	60	5	c	c	NOUN
ajst-5348	60	6	r	r	NOUN
ajst-5348	60	7			NOUN
ajst-5348	60	8	.	.	PUNCT
ajst-5348	61	1	head	head	NOUN
ajst-5348	61	2	attention	attention	NOUN
ajst-5348	61	3	(	(	PUNCT
ajst-5348	61	4	,	,	PUNCT
ajst-5348	61	5	,	,	PUNCT
ajst-5348	61	6	)	)	PUNCT
ajst-5348	61	7	softmax	softmax	NOUN
ajst-5348	62	1	tqk	tqk	PROPN
ajst-5348	62	2	q	q	PROPN
ajst-5348	63	1	k	k	PROPN
ajst-5348	63	2	v	v	ADP
ajst-5348	63	3	v	v	NOUN
ajst-5348	64	1	d	d	NOUN
ajst-5348	64	2			NOUN
ajst-5348	64	3			NOUN
ajst-5348	64	4			PROPN
ajst-5348	65	1			PROPN
ajst-5348	65	2			NOUN
ajst-5348	66	1			PROPN
ajst-5348	67	1			ADJ
ajst-5348	67	2			NOUN
ajst-5348	67	3	(	(	PUNCT
ajst-5348	67	4	3	3	X
ajst-5348	67	5	)	)	PUNCT
ajst-5348	67	6	head	head	NOUN
ajst-5348	67	7	attention	attention	NOUN
ajst-5348	67	8	(	(	PUNCT
ajst-5348	67	9	,	,	PUNCT
ajst-5348	67	10	reduce	reduce	VERB
ajst-5348	67	11	(	(	PUNCT
ajst-5348	67	12	)	)	PUNCT
ajst-5348	67	13	,	,	PUNCT
ajst-5348	67	14	reduce	reduce	VERB
ajst-5348	67	15	(	(	PUNCT
ajst-5348	67	16	)	)	PUNCT
ajst-5348	67	17	)	)	PUNCT
ajst-5348	67	18	q	q	PROPN
ajst-5348	68	1	k	k	PROPN
ajst-5348	68	2	v	v	X
ajst-5348	68	3	j	j	PROPN
ajst-5348	68	4	qw	qw	X
ajst-5348	68	5	k	k	PROPN
ajst-5348	68	6	w	w	PROPN
ajst-5348	68	7	v	v	PROPN
ajst-5348	68	8	w	w	NOUN
ajst-5348	68	9	(	(	PUNCT
ajst-5348	68	10	4	4	NUM
ajst-5348	68	11	)	)	PUNCT
ajst-5348	68	12			NOUN
ajst-5348	68	13	0sra	0sra	PROPN
ajst-5348	68	14	(	(	PUNCT
ajst-5348	68	15	,	,	PUNCT
ajst-5348	68	16	,	,	PUNCT
ajst-5348	68	17	)	)	PUNCT
ajst-5348	68	18	concat	concat	NOUN
ajst-5348	68	19	head	head	NOUN
ajst-5348	68	20	,	,	PUNCT
ajst-5348	68	21	,	,	PUNCT
ajst-5348	68	22	headniq	headniq	PROPN
ajst-5348	68	23	k	k	PROPN
ajst-5348	68	24	v	v	PROPN
ajst-5348	68	25			PROPN
ajst-5348	68	26			NOUN
ajst-5348	68	27	(	(	PUNCT
ajst-5348	68	28	5	5	NUM
ajst-5348	68	29	)	)	PUNCT
ajst-5348	68	30	the	the	DET
ajst-5348	68	31	rest	rest	NOUN
ajst-5348	68	32	of	of	ADP
ajst-5348	68	33	the	the	DET
ajst-5348	68	34	calculation	calculation	NOUN
ajst-5348	68	35	is	be	AUX
ajst-5348	68	36	the	the	DET
ajst-5348	68	37	same	same	ADJ
ajst-5348	68	38	as	as	ADP
ajst-5348	68	39	the	the	DET
ajst-5348	68	40	original	original	ADJ
ajst-5348	68	41	multihead	multihead	NOUN
ajst-5348	68	42	attention	attention	NOUN
ajst-5348	68	43	.	.	PUNCT
ajst-5348	69	1	first	first	ADV
ajst-5348	69	2	,	,	PUNCT
ajst-5348	69	3	attention	attention	NOUN
ajst-5348	69	4	is	be	AUX
ajst-5348	69	5	used	use	VERB
ajst-5348	69	6	to	to	PART
ajst-5348	69	7	calculate	calculate	VERB
ajst-5348	69	8	the	the	DET
ajst-5348	69	9	pairwise	pairwise	NOUN
ajst-5348	69	10	similarity	similarity	NOUN
ajst-5348	69	11	between	between	ADP
ajst-5348	69	12	two	two	NUM
ajst-5348	69	13	elements	element	NOUN
ajst-5348	69	14	of	of	ADP
ajst-5348	69	15	a	a	DET
ajst-5348	69	16	sequence	sequence	NOUN
ajst-5348	69	17	and	and	CCONJ
ajst-5348	69	18	their	their	PRON
ajst-5348	69	19	respectiveqand	respectiveqand	NOUN
ajst-5348	69	20	k	k	PROPN
ajst-5348	69	21	.	.	PUNCT
ajst-5348	70	1	qw	qw	INTJ
ajst-5348	70	2	,	,	PUNCT
ajst-5348	70	3	(	(	PUNCT
ajst-5348	70	4	)	)	PUNCT
ajst-5348	70	5	k	k	PROPN
ajst-5348	70	6	kw	kw	INTJ
ajst-5348	70	7	,	,	PUNCT
ajst-5348	70	8	vw	vw	PROPN
ajst-5348	70	9	are	be	AUX
ajst-5348	70	10	the	the	DET
ajst-5348	70	11	linear	linear	ADJ
ajst-5348	70	12	projection	projection	NOUN
ajst-5348	70	13	parameters	parameter	NOUN
ajst-5348	70	14	ofq	ofq	PROPN
ajst-5348	70	15	,	,	PUNCT
ajst-5348	70	16	k	k	PROPN
ajst-5348	70	17	andv	andv	PROPN
ajst-5348	70	18	,	,	PUNCT
ajst-5348	70	19	respectively	respectively	ADV
ajst-5348	70	20	.	.	PUNCT
ajst-5348	71	1	n	n	PRON
ajst-5348	71	2	is	be	AUX
ajst-5348	71	3	the	the	DET
ajst-5348	71	4	number	number	NOUN
ajst-5348	71	5	of	of	ADP
ajst-5348	71	6	heads	head	NOUN
ajst-5348	71	7	of	of	ADP
ajst-5348	71	8	attention	attention	NOUN
ajst-5348	71	9	layer	layer	NOUN
ajst-5348	71	10	in	in	ADP
ajst-5348	71	11	stage	stage	NOUN
ajst-5348	71	12	i.	i.	NOUN
ajst-5348	71	13	then	then	ADV
ajst-5348	71	14	,	,	PUNCT
ajst-5348	71	15	the	the	DET
ajst-5348	71	16	attention	attention	NOUN
ajst-5348	71	17	scores	score	NOUN
ajst-5348	71	18	of	of	ADP
ajst-5348	71	19	each	each	DET
ajst-5348	71	20	head	head	NOUN
ajst-5348	71	21	are	be	AUX
ajst-5348	71	22	calculated	calculate	VERB
ajst-5348	71	23	and	and	CCONJ
ajst-5348	71	24	concatenated	concatenate	VERB
ajst-5348	71	25	for	for	ADP
ajst-5348	71	26	the	the	DET
ajst-5348	71	27	final	final	ADJ
ajst-5348	71	28	sra	sra	NOUN
ajst-5348	71	29	output	output	NOUN
ajst-5348	71	30	.	.	PUNCT
ajst-5348	72	1	therefore	therefore	ADV
ajst-5348	72	2	,	,	PUNCT
ajst-5348	72	3	sra	sra	PROPN
ajst-5348	72	4	is	be	AUX
ajst-5348	72	5	a	a	DET
ajst-5348	72	6	simple	simple	ADJ
ajst-5348	72	7	but	but	CCONJ
ajst-5348	72	8	effective	effective	ADJ
ajst-5348	72	9	attention	attention	NOUN
ajst-5348	72	10	layer	layer	NOUN
ajst-5348	72	11	that	that	PRON
ajst-5348	72	12	can	can	AUX
ajst-5348	72	13	process	process	VERB
ajst-5348	72	14	high	high	ADJ
ajst-5348	72	15	-	-	PUNCT
ajst-5348	72	16	resolution	resolution	NOUN
ajst-5348	72	17	feature	feature	NOUN
ajst-5348	72	18	maps	map	NOUN
ajst-5348	72	19	while	while	SCONJ
ajst-5348	72	20	reducing	reduce	VERB
ajst-5348	72	21	computational	computational	ADJ
ajst-5348	72	22	and	and	CCONJ
ajst-5348	72	23	memory	memory	NOUN
ajst-5348	72	24	costs	cost	NOUN
ajst-5348	72	25	.	.	PUNCT
ajst-5348	73	1	the	the	DET
ajst-5348	73	2	final	final	ADJ
ajst-5348	73	3	output	output	NOUN
ajst-5348	73	4	of	of	ADP
ajst-5348	73	5	pvt	pvt	PROPN
ajst-5348	73	6	is	be	AUX
ajst-5348	73	7	a	a	DET
ajst-5348	73	8	feature	feature	NOUN
ajst-5348	73	9	vector	vector	NOUN
ajst-5348	73	10	that	that	PRON
ajst-5348	73	11	can	can	AUX
ajst-5348	73	12	be	be	AUX
ajst-5348	73	13	input	input	VERB
ajst-5348	73	14	into	into	ADP
ajst-5348	73	15	the	the	DET
ajst-5348	73	16	siamese	siamese	ADJ
ajst-5348	73	17	network	network	NOUN
ajst-5348	73	18	for	for	ADP
ajst-5348	73	19	downstream	downstream	ADJ
ajst-5348	73	20	tasks	task	NOUN
ajst-5348	73	21	of	of	ADP
ajst-5348	73	22	kinship	kinship	NOUN
ajst-5348	73	23	verification	verification	NOUN
ajst-5348	73	24	.	.	PUNCT
ajst-5348	74	1	3	3	X
ajst-5348	74	2	.	.	X
ajst-5348	74	3	glanet	glanet	NOUN
ajst-5348	74	4	model	model	NOUN
ajst-5348	74	5	and	and	CCONJ
ajst-5348	74	6	loss	loss	NOUN
ajst-5348	74	7	function	function	NOUN
ajst-5348	74	8	3.1	3.1	NUM
ajst-5348	74	9	.	.	PUNCT
ajst-5348	75	1	glanet	glanet	NOUN
ajst-5348	75	2	model	model	PROPN
ajst-5348	75	3	resnet50	resnet50	PROPN
ajst-5348	75	4	network	network	PROPN
ajst-5348	75	5	and	and	CCONJ
ajst-5348	75	6	pvt	pvt	PROPN
ajst-5348	75	7	network	network	NOUN
ajst-5348	75	8	are	be	AUX
ajst-5348	75	9	used	use	VERB
ajst-5348	75	10	to	to	PART
ajst-5348	75	11	construct	construct	VERB
ajst-5348	75	12	siamese	siamese	ADJ
ajst-5348	75	13	branches	branch	NOUN
ajst-5348	75	14	to	to	PART
ajst-5348	75	15	extract	extract	VERB
ajst-5348	75	16	features	feature	NOUN
ajst-5348	75	17	.	.	PUNCT
ajst-5348	76	1	for	for	ADP
ajst-5348	76	2	ease	ease	NOUN
ajst-5348	76	3	of	of	ADP
ajst-5348	76	4	description	description	NOUN
ajst-5348	76	5	,	,	PUNCT
ajst-5348	76	6	it	it	PRON
ajst-5348	76	7	is	be	AUX
ajst-5348	76	8	abbreviated	abbreviate	VERB
ajst-5348	76	9	as	as	ADP
ajst-5348	76	10	glanet	glanet	NOUN
ajst-5348	76	11	,	,	PUNCT
ajst-5348	76	12	and	and	CCONJ
ajst-5348	76	13	its	its	PRON
ajst-5348	76	14	architecture	architecture	NOUN
ajst-5348	76	15	is	be	AUX
ajst-5348	76	16	shown	show	VERB
ajst-5348	76	17	in	in	ADP
ajst-5348	76	18	figure	figure	NOUN
ajst-5348	76	19	3	3	NUM
ajst-5348	76	20	.	.	PUNCT
ajst-5348	77	1	the	the	DET
ajst-5348	77	2	two	two	NUM
ajst-5348	77	3	face	face	NOUN
ajst-5348	77	4	images	image	NOUN
ajst-5348	77	5	are	be	AUX
ajst-5348	77	6	extracted	extract	VERB
ajst-5348	77	7	by	by	ADP
ajst-5348	77	8	two	two	NUM
ajst-5348	77	9	backbone	backbone	NOUN
ajst-5348	77	10	twin	twin	ADJ
ajst-5348	77	11	networks	network	NOUN
ajst-5348	77	12	respectively	respectively	ADV
ajst-5348	77	13	.	.	PUNCT
ajst-5348	78	1	the	the	DET
ajst-5348	78	2	extracted	extract	VERB
ajst-5348	78	3	features	feature	NOUN
ajst-5348	78	4	are	be	AUX
ajst-5348	78	5	used	use	VERB
ajst-5348	78	6	to	to	PART
ajst-5348	78	7	reduce	reduce	VERB
ajst-5348	78	8	the	the	DET
ajst-5348	78	9	feature	feature	NOUN
ajst-5348	78	10	dimension	dimension	NOUN
ajst-5348	78	11	by	by	ADP
ajst-5348	78	12	feature	feature	NOUN
ajst-5348	78	13	fusion	fusion	NOUN
ajst-5348	78	14	and	and	CCONJ
ajst-5348	78	15	1×	1×	NUM
ajst-5348	78	16	1	1	NUM
ajst-5348	78	17	convolution	convolution	NOUN
ajst-5348	78	18	,	,	PUNCT
ajst-5348	78	19	and	and	CCONJ
ajst-5348	78	20	then	then	ADV
ajst-5348	78	21	combined	combine	VERB
ajst-5348	78	22	and	and	CCONJ
ajst-5348	78	23	connected	connect	VERB
ajst-5348	78	24	into	into	ADP
ajst-5348	78	25	a	a	DET
ajst-5348	78	26	long	long	ADJ
ajst-5348	78	27	vector	vector	NOUN
ajst-5348	78	28	.	.	PUNCT
ajst-5348	79	1	then	then	ADV
ajst-5348	79	2	the	the	DET
ajst-5348	79	3	long	long	ADJ
ajst-5348	79	4	vector	vector	NOUN
ajst-5348	79	5	is	be	AUX
ajst-5348	79	6	input	input	VERB
ajst-5348	79	7	into	into	ADP
ajst-5348	79	8	the	the	DET
ajst-5348	79	9	fully	fully	ADV
ajst-5348	79	10	connected	connected	ADJ
ajst-5348	79	11	network	network	NOUN
ajst-5348	79	12	full	full	ADJ
ajst-5348	79	13	connection	connection	NOUN
ajst-5348	79	14	(	(	PUNCT
ajst-5348	79	15	fc	fc	INTJ
ajst-5348	79	16	)	)	PUNCT
ajst-5348	79	17	to	to	PART
ajst-5348	79	18	measure	measure	VERB
ajst-5348	79	19	the	the	DET
ajst-5348	79	20	relative	relative	ADJ
ajst-5348	79	21	similarity	similarity	NOUN
ajst-5348	79	22	between	between	ADP
ajst-5348	79	23	the	the	DET
ajst-5348	79	24	two	two	NUM
ajst-5348	79	25	face	face	NOUN
ajst-5348	79	26	images	image	NOUN
ajst-5348	79	27	,	,	PUNCT
ajst-5348	79	28	and	and	CCONJ
ajst-5348	79	29	finally	finally	ADV
ajst-5348	79	30	determine	determine	VERB
ajst-5348	79	31	whether	whether	SCONJ
ajst-5348	79	32	the	the	DET
ajst-5348	79	33	two	two	NUM
ajst-5348	79	34	images	image	NOUN
ajst-5348	79	35	have	have	VERB
ajst-5348	79	36	kinship	kinship	NOUN
ajst-5348	79	37	.	.	PUNCT
ajst-5348	80	1	the	the	DET
ajst-5348	80	2	fc	fc	PROPN
ajst-5348	80	3	layer	layer	NOUN
ajst-5348	80	4	consists	consist	VERB
ajst-5348	80	5	of	of	ADP
ajst-5348	80	6	three	three	NUM
ajst-5348	80	7	fully	fully	ADV
ajst-5348	80	8	connected	connected	ADJ
ajst-5348	80	9	layers	layer	NOUN
ajst-5348	80	10	,	,	PUNCT
ajst-5348	80	11	two	two	NUM
ajst-5348	80	12	relu	relu	NOUN
ajst-5348	80	13	activation	activation	NOUN
ajst-5348	80	14	functions	function	NOUN
ajst-5348	80	15	and	and	CCONJ
ajst-5348	80	16	a	a	DET
ajst-5348	80	17	sigmoid	sigmoid	NOUN
ajst-5348	80	18	activation	activation	NOUN
ajst-5348	80	19	layer	layer	NOUN
ajst-5348	80	20	.	.	PUNCT
ajst-5348	81	1	in	in	ADP
ajst-5348	81	2	order	order	NOUN
ajst-5348	81	3	to	to	PART
ajst-5348	81	4	better	well	ADV
ajst-5348	81	5	extract	extract	VERB
ajst-5348	81	6	the	the	DET
ajst-5348	81	7	relative	relative	ADJ
ajst-5348	81	8	face	face	NOUN
ajst-5348	81	9	information	information	NOUN
ajst-5348	81	10	and	and	CCONJ
ajst-5348	81	11	speed	speed	VERB
ajst-5348	81	12	up	up	ADP
ajst-5348	81	13	the	the	DET
ajst-5348	81	14	model	model	NOUN
ajst-5348	81	15	training	training	NOUN
ajst-5348	81	16	speed	speed	NOUN
ajst-5348	81	17	,	,	PUNCT
ajst-5348	81	18	the	the	DET
ajst-5348	81	19	two	two	NUM
ajst-5348	81	20	feature	feature	NOUN
ajst-5348	81	21	extraction	extraction	NOUN
ajst-5348	81	22	backbone	backbone	NOUN
ajst-5348	81	23	networks	network	NOUN
ajst-5348	81	24	are	be	AUX
ajst-5348	81	25	pre	pre	ADJ
ajst-5348	81	26	-	-	VERB
ajst-5348	81	27	trained	train	VERB
ajst-5348	81	28	on	on	ADP
ajst-5348	81	29	the	the	DET
ajst-5348	81	30	large	large	ADJ
ajst-5348	81	31	data	datum	NOUN
ajst-5348	81	32	set	set	VERB
ajst-5348	81	33	imagenet[12	imagenet[12	PROPN
ajst-5348	81	34	]	]	PUNCT
ajst-5348	81	35	to	to	PART
ajst-5348	81	36	narrow	narrow	VERB
ajst-5348	81	37	the	the	DET
ajst-5348	81	38	appearance	appearance	NOUN
ajst-5348	81	39	gap	gap	NOUN
ajst-5348	81	40	between	between	ADP
ajst-5348	81	41	the	the	DET
ajst-5348	81	42	old	old	ADJ
ajst-5348	81	43	face	face	NOUN
ajst-5348	81	44	and	and	CCONJ
ajst-5348	81	45	the	the	DET
ajst-5348	81	46	young	young	ADJ
ajst-5348	81	47	face	face	NOUN
ajst-5348	81	48	,	,	PUNCT
ajst-5348	81	49	and	and	CCONJ
ajst-5348	81	50	can	can	AUX
ajst-5348	81	51	obtain	obtain	VERB
ajst-5348	81	52	more	more	ADV
ajst-5348	81	53	semantic	semantic	ADJ
ajst-5348	81	54	information	information	NOUN
ajst-5348	81	55	of	of	ADP
ajst-5348	81	56	the	the	DET
ajst-5348	81	57	face	face	NOUN
ajst-5348	81	58	.	.	PUNCT
ajst-5348	82	1	figure	figure	NOUN
ajst-5348	82	2	3	3	NUM
ajst-5348	82	3	.	.	PUNCT
ajst-5348	82	4	dsnn	dsnn	PROPN
ajst-5348	82	5	-	-	PUNCT
ajst-5348	82	6	tl	tl	PROPN
ajst-5348	82	7	model	model	NOUN
ajst-5348	82	8	architecture	architecture	NOUN
ajst-5348	82	9	60	60	NUM
ajst-5348	82	10	3.2	3.2	NUM
ajst-5348	82	11	.	.	PUNCT
ajst-5348	83	1	loss	loss	NOUN
ajst-5348	83	2	function	function	NOUN
ajst-5348	83	3	the	the	DET
ajst-5348	83	4	softmax	softmax	NOUN
ajst-5348	83	5	function	function	NOUN
ajst-5348	83	6	is	be	AUX
ajst-5348	83	7	mainly	mainly	ADV
ajst-5348	83	8	used	use	VERB
ajst-5348	83	9	to	to	PART
ajst-5348	83	10	solve	solve	VERB
ajst-5348	83	11	multiclassification	multiclassification	NOUN
ajst-5348	83	12	problems	problem	NOUN
ajst-5348	83	13	.	.	PUNCT
ajst-5348	84	1	the	the	DET
ajst-5348	84	2	results	result	NOUN
ajst-5348	84	3	obtained	obtain	VERB
ajst-5348	84	4	by	by	ADP
ajst-5348	84	5	softmax	softmax	NOUN
ajst-5348	84	6	represent	represent	VERB
ajst-5348	84	7	the	the	DET
ajst-5348	84	8	probability	probability	NOUN
ajst-5348	84	9	that	that	SCONJ
ajst-5348	84	10	the	the	DET
ajst-5348	84	11	input	input	NOUN
ajst-5348	84	12	image	image	NOUN
ajst-5348	84	13	is	be	AUX
ajst-5348	84	14	assigned	assign	VERB
ajst-5348	84	15	to	to	ADP
ajst-5348	84	16	each	each	DET
ajst-5348	84	17	category	category	NOUN
ajst-5348	84	18	.	.	PUNCT
ajst-5348	85	1	softmax	softmax	NOUN
ajst-5348	85	2	loss	loss	NOUN
ajst-5348	85	3	is	be	AUX
ajst-5348	85	4	a	a	DET
ajst-5348	85	5	loss	loss	NOUN
ajst-5348	85	6	function	function	NOUN
ajst-5348	85	7	that	that	PRON
ajst-5348	85	8	combines	combine	VERB
ajst-5348	85	9	softmax	softmax	NOUN
ajst-5348	85	10	and	and	CCONJ
ajst-5348	85	11	cross	cross	ADJ
ajst-5348	85	12	-	-	ADJ
ajst-5348	85	13	entropy	entropy	ADJ
ajst-5348	85	14	loss	loss	NOUN
ajst-5348	85	15	[	[	X
ajst-5348	85	16	13	13	NUM
ajst-5348	85	17	]	]	PUNCT
ajst-5348	85	18	.	.	PUNCT
ajst-5348	86	1	this	this	DET
ajst-5348	86	2	paper	paper	NOUN
ajst-5348	86	3	proposes	propose	VERB
ajst-5348	86	4	a	a	DET
ajst-5348	86	5	joint	joint	ADJ
ajst-5348	86	6	supervised	supervised	ADJ
ajst-5348	86	7	learning	learning	NOUN
ajst-5348	86	8	of	of	ADP
ajst-5348	86	9	softmax	softmax	NOUN
ajst-5348	86	10	loss	loss	NOUN
ajst-5348	86	11	and	and	CCONJ
ajst-5348	86	12	center	center	ADJ
ajst-5348	86	13	loss	loss	NOUN
ajst-5348	86	14	[	[	X
ajst-5348	86	15	14	14	NUM
ajst-5348	86	16	]	]	PUNCT
ajst-5348	86	17	,	,	PUNCT
ajst-5348	86	18	which	which	PRON
ajst-5348	86	19	reduces	reduce	VERB
ajst-5348	86	20	the	the	DET
ajst-5348	86	21	intra	intra	ADJ
ajst-5348	86	22	-	-	ADJ
ajst-5348	86	23	class	class	ADJ
ajst-5348	86	24	distance	distance	NOUN
ajst-5348	86	25	while	while	SCONJ
ajst-5348	86	26	increasing	increase	VERB
ajst-5348	86	27	the	the	DET
ajst-5348	86	28	inter	inter	ADJ
ajst-5348	86	29	-	-	ADJ
ajst-5348	86	30	class	class	ADJ
ajst-5348	86	31	distance	distance	NOUN
ajst-5348	86	32	,	,	PUNCT
ajst-5348	86	33	so	so	SCONJ
ajst-5348	86	34	that	that	SCONJ
ajst-5348	86	35	the	the	DET
ajst-5348	86	36	obtained	obtain	VERB
ajst-5348	86	37	features	feature	NOUN
ajst-5348	86	38	have	have	VERB
ajst-5348	86	39	stronger	strong	ADJ
ajst-5348	86	40	discrimination	discrimination	NOUN
ajst-5348	86	41	ability	ability	NOUN
ajst-5348	86	42	.	.	PUNCT
ajst-5348	87	1	as	as	SCONJ
ajst-5348	87	2	shown	show	VERB
ajst-5348	87	3	in	in	ADP
ajst-5348	87	4	(	(	PUNCT
ajst-5348	87	5	6	6	NUM
ajst-5348	87	6	)	)	PUNCT
ajst-5348	87	7	:	:	PUNCT
ajst-5348	87	8	(	(	PUNCT
ajst-5348	87	9	)	)	PUNCT
ajst-5348	87	10	(	(	PUNCT
ajst-5348	87	11	)	)	PUNCT
ajst-5348	87	12	(	(	PUNCT
ajst-5348	87	13	)	)	PUNCT
ajst-5348	87	14	2	2	NUM
ajst-5348	87	15	2	2	NUM
ajst-5348	87	16	1	1	NUM
ajst-5348	87	17	1	1	NUM
ajst-5348	87	18	1	1	NUM
ajst-5348	87	19	1	1	NUM
ajst-5348	87	20	log	log	NOUN
ajst-5348	87	21	2	2	NUM
ajst-5348	87	22	t	t	NOUN
ajst-5348	88	1	y	y	NOUN
ajst-5348	89	1	i	i	PRON
ajst-5348	89	2	tw	tw	VERB
ajst-5348	89	3	x	x	VERB
ajst-5348	89	4	il	il	VERB
ajst-5348	90	1	i	i	NOUN
ajst-5348	90	2	w	w	VERB
ajst-5348	90	3	x	x	VERB
ajst-5348	91	1	i	i	VERB
ajst-5348	91	2	m	m	VERB
ajst-5348	91	3	m	m	VERB
ajst-5348	92	1	i	i	INTJ
ajst-5348	92	2	yk	yk	INTJ
ajst-5348	93	1	i	i	PRON
ajst-5348	93	2	i	i	VERB
ajst-5348	93	3	l	l	NOUN
ajst-5348	93	4	e	e	X
ajst-5348	93	5	l	l	NOUN
ajst-5348	93	6	x	x	X
ajst-5348	93	7	c	c	NOUN
ajst-5348	93	8	m	m	PROPN
ajst-5348	93	9	e	e	NOUN
ajst-5348	93	10			ADJ
ajst-5348	93	11			PROPN
ajst-5348	93	12			PROPN
ajst-5348	93	13			PROPN
ajst-5348	93	14			PROPN
ajst-5348	93	15			ADJ
ajst-5348	93	16			NOUN
ajst-5348	93	17			NOUN
ajst-5348	93	18			NOUN
ajst-5348	94	1			PROPN
ajst-5348	94	2			PROPN
ajst-5348	94	3			PUNCT
ajst-5348	94	4			PROPN
ajst-5348	94	5			PROPN
ajst-5348	94	6			PROPN
ajst-5348	94	7			NOUN
ajst-5348	94	8			PROPN
ajst-5348	94	9			PROPN
ajst-5348	94	10			X
ajst-5348	94	11			X
ajst-5348	94	12			X
ajst-5348	94	13	(	(	PUNCT
ajst-5348	94	14	6	6	NUM
ajst-5348	94	15	)	)	PUNCT
ajst-5348	94	16	where	where	SCONJ
ajst-5348	94	17	m	m	NOUN
ajst-5348	94	18	represents	represent	VERB
ajst-5348	94	19	the	the	DET
ajst-5348	94	20	number	number	NOUN
ajst-5348	94	21	of	of	ADP
ajst-5348	94	22	samples	sample	NOUN
ajst-5348	94	23	,	,	PUNCT
ajst-5348	94	24	w	w	NOUN
ajst-5348	94	25	is	be	AUX
ajst-5348	94	26	the	the	DET
ajst-5348	94	27	weight	weight	NOUN
ajst-5348	94	28	of	of	ADP
ajst-5348	94	29	the	the	DET
ajst-5348	94	30	network	network	NOUN
ajst-5348	94	31	model	model	NOUN
ajst-5348	94	32	,	,	PUNCT
ajst-5348	94	33	xrepresents	xrepresent	VERB
ajst-5348	94	34	the	the	DET
ajst-5348	94	35	i	i	PROPN
ajst-5348	94	36	-	-	PUNCT
ajst-5348	94	37	th	th	VERB
ajst-5348	94	38	image	image	NOUN
ajst-5348	94	39	feature	feature	NOUN
ajst-5348	94	40	value	value	NOUN
ajst-5348	94	41	,	,	PUNCT
ajst-5348	94	42	iy	iy	PROPN
ajst-5348	94	43	represents	represent	VERB
ajst-5348	94	44	the	the	DET
ajst-5348	94	45	i	i	PROPN
ajst-5348	94	46	-	-	PUNCT
ajst-5348	94	47	th	th	X
ajst-5348	94	48	class	class	NOUN
ajst-5348	94	49	,	,	PUNCT
ajst-5348	94	50	and	and	CCONJ
ajst-5348	94	51	iy	iy	PROPN
ajst-5348	94	52	c	c	PROPN
ajst-5348	94	53	represents	represent	VERB
ajst-5348	94	54	the	the	DET
ajst-5348	94	55	center	center	NOUN
ajst-5348	94	56	of	of	ADP
ajst-5348	94	57	the	the	DET
ajst-5348	94	58	classification	classification	NOUN
ajst-5348	94	59	feature	feature	NOUN
ajst-5348	94	60	value	value	NOUN
ajst-5348	94	61	of	of	ADP
ajst-5348	94	62	the	the	DET
ajst-5348	94	63	i	i	PROPN
ajst-5348	94	64	-	-	PUNCT
ajst-5348	94	65	th	th	VERB
ajst-5348	94	66	image	image	NOUN
ajst-5348	94	67	.	.	PUNCT
ajst-5348	95	1	the	the	DET
ajst-5348	95	2	center	center	NOUN
ajst-5348	95	3	of	of	ADP
ajst-5348	95	4	the	the	DET
ajst-5348	95	5	classification	classification	NOUN
ajst-5348	95	6	to	to	PART
ajst-5348	95	7	which	which	PRON
ajst-5348	95	8	the	the	DET
ajst-5348	95	9	picture	picture	NOUN
ajst-5348	95	10	belongs	belong	VERB
ajst-5348	95	11	(	(	PUNCT
ajst-5348	95	12	the	the	DET
ajst-5348	95	13	center	center	NOUN
ajst-5348	95	14	of	of	ADP
ajst-5348	95	15	the	the	DET
ajst-5348	95	16	eigenvalues	eigenvalue	NOUN
ajst-5348	95	17	of	of	ADP
ajst-5348	95	18	the	the	DET
ajst-5348	95	19	classification	classification	NOUN
ajst-5348	95	20	)	)	PUNCT
ajst-5348	95	21	;	;	PUNCT
ajst-5348	95	22	λ	λ	NOUN
ajst-5348	95	23	is	be	AUX
ajst-5348	95	24	used	use	VERB
ajst-5348	95	25	to	to	PART
ajst-5348	95	26	balance	balance	VERB
ajst-5348	95	27	two	two	NUM
ajst-5348	95	28	losses	loss	NOUN
ajst-5348	95	29	.	.	PUNCT
ajst-5348	96	1	appropriate	appropriate	ADJ
ajst-5348	96	2	λ	λ	PROPN
ajst-5348	96	3	selection	selection	NOUN
ajst-5348	96	4	helps	help	VERB
ajst-5348	96	5	to	to	PART
ajst-5348	96	6	enhance	enhance	VERB
ajst-5348	96	7	the	the	DET
ajst-5348	96	8	feature	feature	NOUN
ajst-5348	96	9	discrimination	discrimination	NOUN
ajst-5348	96	10	ability	ability	NOUN
ajst-5348	96	11	of	of	ADP
ajst-5348	96	12	the	the	DET
ajst-5348	96	13	network	network	NOUN
ajst-5348	96	14	.	.	PUNCT
ajst-5348	97	1	when	when	SCONJ
ajst-5348	97	2	λ	λ	X
ajst-5348	97	3	=	=	SYM
ajst-5348	97	4	0	0	NUM
ajst-5348	97	5	,	,	PUNCT
ajst-5348	97	6	only	only	ADV
ajst-5348	97	7	softmax	softmax	NOUN
ajst-5348	97	8	loss	loss	NOUN
ajst-5348	97	9	supervised	supervised	ADJ
ajst-5348	97	10	learning	learning	NOUN
ajst-5348	97	11	is	be	AUX
ajst-5348	97	12	used	use	VERB
ajst-5348	97	13	to	to	PART
ajst-5348	97	14	train	train	VERB
ajst-5348	97	15	the	the	DET
ajst-5348	97	16	network	network	NOUN
ajst-5348	97	17	.	.	PUNCT
ajst-5348	98	1	4	4	X
ajst-5348	98	2	.	.	X
ajst-5348	98	3	experiment	experiment	NOUN
ajst-5348	98	4	and	and	CCONJ
ajst-5348	98	5	results	result	VERB
ajst-5348	98	6	4.1	4.1	NUM
ajst-5348	98	7	.	.	PUNCT
ajst-5348	99	1	experimental	experimental	ADJ
ajst-5348	99	2	setup	setup	NOUN
ajst-5348	99	3	and	and	CCONJ
ajst-5348	99	4	parameters	parameter	NOUN
ajst-5348	99	5	the	the	DET
ajst-5348	99	6	experimental	experimental	ADJ
ajst-5348	99	7	environment	environment	NOUN
ajst-5348	99	8	is	be	AUX
ajst-5348	99	9	windows	window	NOUN
ajst-5348	99	10	10	10	NUM
ajst-5348	99	11	,	,	PUNCT
ajst-5348	99	12	64	64	NUM
ajst-5348	99	13	-	-	PUNCT
ajst-5348	99	14	bit	bit	NOUN
ajst-5348	99	15	operating	operate	VERB
ajst-5348	99	16	system	system	NOUN
ajst-5348	99	17	,	,	PUNCT
ajst-5348	99	18	16	16	NUM
ajst-5348	99	19	gb	gb	NOUN
ajst-5348	99	20	memory	memory	NOUN
ajst-5348	99	21	,	,	PUNCT
ajst-5348	99	22	python	python	NOUN
ajst-5348	99	23	programming	programming	NOUN
ajst-5348	99	24	language	language	NOUN
ajst-5348	99	25	,	,	PUNCT
ajst-5348	99	26	tensorflow	tensorflow	ADJ
ajst-5348	99	27	deep	deep	ADJ
ajst-5348	99	28	learning	learning	NOUN
ajst-5348	99	29	framework	framework	NOUN
ajst-5348	99	30	,	,	PUNCT
ajst-5348	99	31	nvidia	nvidia	PROPN
ajst-5348	99	32	geforce	geforce	NOUN
ajst-5348	99	33	gtx	gtx	PROPN
ajst-5348	99	34	1650	1650	NUM
ajst-5348	99	35	and	and	CCONJ
ajst-5348	99	36	intel	intel	PROPN
ajst-5348	99	37	(	(	PUNCT
ajst-5348	99	38	r	r	NOUN
ajst-5348	99	39	)	)	PUNCT
ajst-5348	99	40	core	core	NOUN
ajst-5348	99	41	(	(	PUNCT
ajst-5348	99	42	tm	tm	NOUN
ajst-5348	99	43	)	)	PUNCT
ajst-5348	99	44	i7	i7	ADJ
ajst-5348	99	45	-	-	PUNCT
ajst-5348	99	46	10700f	10700f	NUM
ajst-5348	99	47	cpu@2.90	cpu@2.90	PROPN
ajst-5348	99	48	ghz	ghz	NOUN
ajst-5348	99	49	(	(	PUNCT
ajst-5348	99	50	16	16	NUM
ajst-5348	99	51	cpus	cpu	NOUN
ajst-5348	99	52	)	)	PUNCT
ajst-5348	99	53	,	,	PUNCT
ajst-5348	99	54	~2.9	~2.9	NUM
ajst-5348	99	55	ghz	ghz	NOUN
ajst-5348	99	56	.	.	PUNCT
ajst-5348	100	1	firstly	firstly	ADV
ajst-5348	100	2	,	,	PUNCT
ajst-5348	100	3	the	the	DET
ajst-5348	100	4	experiment	experiment	NOUN
ajst-5348	100	5	fine	fine	ADV
ajst-5348	100	6	-	-	PUNCT
ajst-5348	100	7	tuned	tune	VERB
ajst-5348	100	8	the	the	DET
ajst-5348	100	9	two	two	NUM
ajst-5348	100	10	pre	pre	ADJ
ajst-5348	100	11	-	-	ADJ
ajst-5348	100	12	training	training	ADJ
ajst-5348	100	13	models	model	NOUN
ajst-5348	100	14	,	,	PUNCT
ajst-5348	100	15	and	and	CCONJ
ajst-5348	100	16	all	all	DET
ajst-5348	100	17	the	the	DET
ajst-5348	100	18	parameters	parameter	NOUN
ajst-5348	100	19	of	of	ADP
ajst-5348	100	20	resnet50	resnet50	NOUN
ajst-5348	100	21	and	and	CCONJ
ajst-5348	100	22	pvt	pvt	PROPN
ajst-5348	100	23	feature	feature	NOUN
ajst-5348	100	24	extraction	extraction	NOUN
ajst-5348	100	25	backbone	backbone	NOUN
ajst-5348	100	26	network	network	NOUN
ajst-5348	100	27	layer	layer	NOUN
ajst-5348	100	28	were	be	AUX
ajst-5348	100	29	frozen	freeze	VERB
ajst-5348	100	30	.	.	PUNCT
ajst-5348	101	1	the	the	DET
ajst-5348	101	2	number	number	NOUN
ajst-5348	101	3	of	of	ADP
ajst-5348	101	4	neurons	neuron	NOUN
ajst-5348	101	5	in	in	ADP
ajst-5348	101	6	the	the	DET
ajst-5348	101	7	second	second	ADJ
ajst-5348	101	8	and	and	CCONJ
ajst-5348	101	9	third	third	ADJ
ajst-5348	101	10	layers	layer	NOUN
ajst-5348	101	11	is	be	AUX
ajst-5348	101	12	512	512	NUM
ajst-5348	101	13	and	and	CCONJ
ajst-5348	101	14	32	32	NUM
ajst-5348	101	15	respectively	respectively	ADV
ajst-5348	101	16	.	.	PUNCT
ajst-5348	102	1	in	in	ADP
ajst-5348	102	2	order	order	NOUN
ajst-5348	102	3	to	to	PART
ajst-5348	102	4	prevent	prevent	VERB
ajst-5348	102	5	overfitting	overfitting	NOUN
ajst-5348	102	6	,	,	PUNCT
ajst-5348	102	7	dropout	dropout	NOUN
ajst-5348	102	8	is	be	AUX
ajst-5348	102	9	introduced	introduce	VERB
ajst-5348	102	10	and	and	CCONJ
ajst-5348	102	11	set	set	VERB
ajst-5348	102	12	to	to	ADP
ajst-5348	102	13	0.1	0.1	NUM
ajst-5348	102	14	.	.	PUNCT
ajst-5348	103	1	then	then	ADV
ajst-5348	103	2	,	,	PUNCT
ajst-5348	103	3	the	the	DET
ajst-5348	103	4	method	method	NOUN
ajst-5348	103	5	of	of	ADP
ajst-5348	103	6	learning	learn	VERB
ajst-5348	103	7	rate	rate	NOUN
ajst-5348	103	8	linearly	linearly	ADV
ajst-5348	103	9	decreasing	decrease	VERB
ajst-5348	103	10	with	with	ADP
ajst-5348	103	11	the	the	DET
ajst-5348	103	12	training	training	NOUN
ajst-5348	103	13	epoch	epoch	NOUN
ajst-5348	103	14	is	be	AUX
ajst-5348	103	15	used	use	VERB
ajst-5348	103	16	to	to	PART
ajst-5348	103	17	prevent	prevent	VERB
ajst-5348	103	18	excessive	excessive	ADJ
ajst-5348	103	19	learning	learning	NOUN
ajst-5348	103	20	rate	rate	NOUN
ajst-5348	103	21	from	from	ADP
ajst-5348	103	22	oscillating	oscillate	VERB
ajst-5348	103	23	back	back	ADV
ajst-5348	103	24	and	and	CCONJ
ajst-5348	103	25	forth	forth	ADV
ajst-5348	103	26	when	when	SCONJ
ajst-5348	103	27	converging	converge	VERB
ajst-5348	103	28	to	to	ADP
ajst-5348	103	29	the	the	DET
ajst-5348	103	30	global	global	ADJ
ajst-5348	103	31	optimum	optimum	NOUN
ajst-5348	103	32	.	.	PUNCT
ajst-5348	104	1	after	after	ADP
ajst-5348	104	2	10	10	NUM
ajst-5348	104	3	epochs	epoch	NOUN
ajst-5348	104	4	per	per	ADP
ajst-5348	104	5	iteration	iteration	NOUN
ajst-5348	104	6	,	,	PUNCT
ajst-5348	104	7	the	the	DET
ajst-5348	104	8	learning	learning	NOUN
ajst-5348	104	9	rate	rate	NOUN
ajst-5348	104	10	is	be	AUX
ajst-5348	104	11	attenuated	attenuate	VERB
ajst-5348	104	12	by	by	ADP
ajst-5348	104	13	half	half	NOUN
ajst-5348	104	14	when	when	SCONJ
ajst-5348	104	15	the	the	DET
ajst-5348	104	16	maximum	maximum	ADJ
ajst-5348	104	17	verification	verification	NOUN
ajst-5348	104	18	accuracy	accuracy	NOUN
ajst-5348	104	19	is	be	AUX
ajst-5348	104	20	not	not	PART
ajst-5348	104	21	improved	improve	VERB
ajst-5348	104	22	.	.	PUNCT
ajst-5348	105	1	the	the	DET
ajst-5348	105	2	experimental	experimental	ADJ
ajst-5348	105	3	parameter	parameter	NOUN
ajst-5348	105	4	settings	setting	NOUN
ajst-5348	105	5	are	be	AUX
ajst-5348	105	6	shown	show	VERB
ajst-5348	105	7	in	in	ADP
ajst-5348	105	8	table	table	NOUN
ajst-5348	105	9	2	2	NUM
ajst-5348	105	10	.	.	PUNCT
ajst-5348	105	11	table	table	NOUN
ajst-5348	105	12	2	2	NUM
ajst-5348	105	13	.	.	PUNCT
ajst-5348	106	1	parameter	parameter	NOUN
ajst-5348	106	2	settings	setting	NOUN
ajst-5348	106	3	parameter	parameter	PROPN
ajst-5348	106	4	values	value	NOUN
ajst-5348	106	5	epoch	epoch	PROPN
ajst-5348	106	6	100	100	NUM
ajst-5348	106	7	batchsize	batchsize	VERB
ajst-5348	106	8	16	16	NUM
ajst-5348	106	9	optimizer	optimizer	NOUN
ajst-5348	106	10	adam	adam	PROPN
ajst-5348	106	11	learning	learning	NOUN
ajst-5348	106	12	-	-	PUNCT
ajst-5348	106	13	rate	rate	NOUN
ajst-5348	106	14	0.0001	0.0001	NUM
ajst-5348	106	15	4.2	4.2	NUM
ajst-5348	106	16	.	.	PUNCT
ajst-5348	107	1	experimental	experimental	ADJ
ajst-5348	107	2	data	datum	NOUN
ajst-5348	107	3	set	set	VERB
ajst-5348	107	4	the	the	DET
ajst-5348	107	5	fiw	fiw	NOUN
ajst-5348	108	1	[	[	X
ajst-5348	108	2	15	15	NUM
ajst-5348	108	3	]	]	X
ajst-5348	108	4	data	datum	NOUN
ajst-5348	108	5	set	set	VERB
ajst-5348	108	6	with	with	ADP
ajst-5348	108	7	the	the	DET
ajst-5348	108	8	largest	large	ADJ
ajst-5348	108	9	and	and	CCONJ
ajst-5348	108	10	most	most	ADV
ajst-5348	108	11	comprehensive	comprehensive	ADJ
ajst-5348	108	12	facial	facial	ADJ
ajst-5348	108	13	image	image	NOUN
ajst-5348	108	14	recognition	recognition	NOUN
ajst-5348	108	15	by	by	ADP
ajst-5348	108	16	relatives	relative	NOUN
ajst-5348	108	17	is	be	AUX
ajst-5348	108	18	adopted	adopt	VERB
ajst-5348	108	19	,	,	PUNCT
ajst-5348	108	20	and	and	CCONJ
ajst-5348	108	21	the	the	DET
ajst-5348	108	22	kinships	kinship	NOUN
ajst-5348	108	23	included	include	VERB
ajst-5348	108	24	are	be	AUX
ajst-5348	108	25	divided	divide	VERB
ajst-5348	108	26	into	into	ADP
ajst-5348	108	27	the	the	DET
ajst-5348	108	28	following	following	ADJ
ajst-5348	108	29	three	three	NUM
ajst-5348	108	30	types	type	NOUN
ajst-5348	108	31	:	:	PUNCT
ajst-5348	108	32	peer	peer	NOUN
ajst-5348	108	33	relationship	relationship	NOUN
ajst-5348	108	34	,	,	PUNCT
ajst-5348	108	35	brother	brother	NOUN
ajst-5348	108	36	-	-	PUNCT
ajst-5348	108	37	brother	brother	NOUN
ajst-5348	108	38	(	(	PUNCT
ajst-5348	108	39	bb	bb	NOUN
ajst-5348	108	40	)	)	PUNCT
ajst-5348	108	41	,	,	PUNCT
ajst-5348	108	42	sister	sister	NOUN
ajst-5348	108	43	-	-	PUNCT
ajst-5348	108	44	sister	sister	NOUN
ajst-5348	108	45	(	(	PUNCT
ajst-5348	108	46	s	s	NOUN
ajst-5348	108	47	-	-	PUNCT
ajst-5348	108	48	s	s	NOUN
ajst-5348	108	49	)	)	PUNCT
ajst-5348	108	50	and	and	CCONJ
ajst-5348	108	51	brother	brother	NOUN
ajst-5348	108	52	-	-	PUNCT
ajst-5348	108	53	sister	sister	NOUN
ajst-5348	108	54	(	(	PUNCT
ajst-5348	108	55	si	si	NOUN
ajst-5348	108	56	-	-	PUNCT
ajst-5348	108	57	bs	bs	NOUN
ajst-5348	108	58	)	)	PUNCT
ajst-5348	108	59	;	;	PUNCT
ajst-5348	108	60	the	the	DET
ajst-5348	108	61	first	first	ADJ
ajst-5348	108	62	generation	generation	NOUN
ajst-5348	108	63	relationships	relationship	NOUN
ajst-5348	108	64	:	:	PUNCT
ajst-5348	108	65	father	father	NOUN
ajst-5348	108	66	and	and	CCONJ
ajst-5348	108	67	daughter	daughter	NOUN
ajst-5348	108	68	(	(	PUNCT
ajst-5348	108	69	f	f	X
ajst-5348	108	70	-	-	PROPN
ajst-5348	108	71	d	d	NOUN
ajst-5348	108	72	)	)	PUNCT
ajst-5348	108	73	,	,	PUNCT
ajst-5348	108	74	father	father	NOUN
ajst-5348	108	75	and	and	CCONJ
ajst-5348	108	76	son	son	NOUN
ajst-5348	108	77	(	(	PUNCT
ajst-5348	108	78	f	f	PROPN
ajst-5348	108	79	-	-	PUNCT
ajst-5348	108	80	s	s	NOUN
ajst-5348	108	81	)	)	PUNCT
ajst-5348	108	82	,	,	PUNCT
ajst-5348	108	83	mother	mother	NOUN
ajst-5348	108	84	and	and	CCONJ
ajst-5348	108	85	daughter	daughter	NOUN
ajst-5348	108	86	(	(	PUNCT
ajst-5348	108	87	m	m	PROPN
ajst-5348	108	88	-	-	PROPN
ajst-5348	108	89	d	d	NOUN
ajst-5348	108	90	)	)	PUNCT
ajst-5348	108	91	and	and	CCONJ
ajst-5348	108	92	mother	mother	NOUN
ajst-5348	108	93	and	and	CCONJ
ajst-5348	108	94	son	son	NOUN
ajst-5348	108	95	(	(	PUNCT
ajst-5348	108	96	m	m	PROPN
ajst-5348	108	97	-	-	PUNCT
ajst-5348	108	98	s	s	NOUN
ajst-5348	108	99	)	)	PUNCT
ajst-5348	108	100	;	;	PUNCT
ajst-5348	108	101	the	the	DET
ajst-5348	108	102	second	second	ADJ
ajst-5348	108	103	generation	generation	NOUN
ajst-5348	108	104	:	:	PUNCT
ajst-5348	108	105	grandfather	grandfather	NOUN
ajst-5348	108	106	and	and	CCONJ
ajst-5348	108	107	granddaughter	granddaughter	NOUN
ajst-5348	108	108	(	(	PUNCT
ajst-5348	108	109	gf	gf	NOUN
ajst-5348	108	110	-	-	PUNCT
ajst-5348	108	111	gd	gd	NOUN
ajst-5348	108	112	)	)	PUNCT
ajst-5348	108	113	,	,	PUNCT
ajst-5348	108	114	grandfather	grandfather	NOUN
ajst-5348	108	115	and	and	CCONJ
ajst-5348	108	116	grandson	grandson	NOUN
ajst-5348	108	117	(	(	PUNCT
ajst-5348	108	118	gf	gf	NOUN
ajst-5348	108	119	-	-	PUNCT
ajst-5348	108	120	gs	gs	NOUN
ajst-5348	108	121	)	)	PUNCT
ajst-5348	108	122	,	,	PUNCT
ajst-5348	108	123	grandmother	grandmother	NOUN
ajst-5348	108	124	and	and	CCONJ
ajst-5348	108	125	granddaughter	granddaughter	NOUN
ajst-5348	108	126	(	(	PUNCT
ajst-5348	108	127	gm	gm	PROPN
ajst-5348	108	128	-	-	PUNCT
ajst-5348	108	129	gd	gd	NOUN
ajst-5348	108	130	)	)	PUNCT
ajst-5348	108	131	and	and	CCONJ
ajst-5348	108	132	grandmother	grandmother	NOUN
ajst-5348	108	133	and	and	CCONJ
ajst-5348	108	134	grandson	grandson	NOUN
ajst-5348	108	135	(	(	PUNCT
ajst-5348	108	136	gm	gm	PROPN
ajst-5348	108	137	-	-	PUNCT
ajst-5348	108	138	gs	gs	NOUN
ajst-5348	108	139	)	)	PUNCT
ajst-5348	108	140	,	,	PUNCT
ajst-5348	108	141	a	a	DET
ajst-5348	108	142	total	total	NOUN
ajst-5348	108	143	of	of	ADP
ajst-5348	108	144	11	11	NUM
ajst-5348	108	145	pairs	pair	NOUN
ajst-5348	108	146	of	of	ADP
ajst-5348	108	147	kinship	kinship	NOUN
ajst-5348	108	148	.	.	PUNCT
ajst-5348	109	1	faces	face	NOUN
ajst-5348	109	2	in	in	ADP
ajst-5348	109	3	fiw	fiw	PROPN
ajst-5348	109	4	dataset	dataset	VERB
ajst-5348	109	5	contain	contain	VERB
ajst-5348	109	6	changes	change	NOUN
ajst-5348	109	7	in	in	ADP
ajst-5348	109	8	posture	posture	NOUN
ajst-5348	109	9	,	,	PUNCT
ajst-5348	109	10	facial	facial	ADJ
ajst-5348	109	11	expression	expression	NOUN
ajst-5348	109	12	,	,	PUNCT
ajst-5348	109	13	occlusion	occlusion	NOUN
ajst-5348	109	14	and	and	CCONJ
ajst-5348	109	15	lighting	lighting	NOUN
ajst-5348	109	16	.	.	PUNCT
ajst-5348	110	1	some	some	DET
ajst-5348	110	2	images	image	NOUN
ajst-5348	110	3	of	of	ADP
ajst-5348	110	4	some	some	DET
ajst-5348	110	5	kinship	kinship	NOUN
ajst-5348	110	6	faces	face	NOUN
ajst-5348	110	7	are	be	AUX
ajst-5348	110	8	shown	show	VERB
ajst-5348	110	9	in	in	ADP
ajst-5348	110	10	fig	fig	NOUN
ajst-5348	110	11	.	.	PUNCT
ajst-5348	111	1	4	4	X
ajst-5348	111	2	.	.	X
ajst-5348	111	3	figure	figure	NOUN
ajst-5348	111	4	4	4	NUM
ajst-5348	111	5	.	.	NOUN
ajst-5348	111	6	face	face	NOUN
ajst-5348	111	7	images	image	NOUN
ajst-5348	111	8	of	of	ADP
ajst-5348	111	9	some	some	DET
ajst-5348	111	10	relatives	relative	NOUN
ajst-5348	111	11	in	in	ADP
ajst-5348	111	12	fiw	fiw	PROPN
ajst-5348	111	13	4.3	4.3	NUM
ajst-5348	111	14	.	.	PUNCT
ajst-5348	112	1	results	result	NOUN
ajst-5348	112	2	and	and	CCONJ
ajst-5348	112	3	analysis	analysis	NOUN
ajst-5348	112	4	first	first	ADV
ajst-5348	112	5	,	,	PUNCT
ajst-5348	112	6	the	the	DET
ajst-5348	112	7	joint	joint	ADJ
ajst-5348	112	8	loss	loss	NOUN
ajst-5348	112	9	function	function	NOUN
ajst-5348	112	10	parameter	parameter	NOUN
ajst-5348	112	11	λ	λ	PROPN
ajst-5348	112	12	is	be	AUX
ajst-5348	112	13	determined	determine	VERB
ajst-5348	112	14	.	.	PUNCT
ajst-5348	113	1	the	the	DET
ajst-5348	113	2	experimental	experimental	ADJ
ajst-5348	113	3	results	result	NOUN
ajst-5348	113	4	are	be	AUX
ajst-5348	113	5	shown	show	VERB
ajst-5348	113	6	in	in	ADP
ajst-5348	113	7	figure	figure	NOUN
ajst-5348	113	8	5	5	NUM
ajst-5348	113	9	.	.	PUNCT
ajst-5348	114	1	it	it	PRON
ajst-5348	114	2	can	can	AUX
ajst-5348	114	3	be	be	AUX
ajst-5348	114	4	seen	see	VERB
ajst-5348	114	5	from	from	ADP
ajst-5348	114	6	the	the	DET
ajst-5348	114	7	figure	figure	NOUN
ajst-5348	114	8	that	that	SCONJ
ajst-5348	114	9	the	the	DET
ajst-5348	114	10	superiority	superiority	NOUN
ajst-5348	114	11	of	of	ADP
ajst-5348	114	12	the	the	DET
ajst-5348	114	13	proposed	propose	VERB
ajst-5348	114	14	softmax	softmax	NOUN
ajst-5348	114	15	loss	loss	NOUN
ajst-5348	114	16	and	and	CCONJ
ajst-5348	114	17	center	center	NOUN
ajst-5348	114	18	loss	loss	NOUN
ajst-5348	114	19	joint	joint	ADJ
ajst-5348	114	20	supervised	supervised	ADJ
ajst-5348	114	21	learning	learn	VERB
ajst-5348	114	22	loss	loss	NOUN
ajst-5348	114	23	function	function	NOUN
ajst-5348	114	24	,	,	PUNCT
ajst-5348	114	25	and	and	CCONJ
ajst-5348	114	26	its	its	PRON
ajst-5348	114	27	kinship	kinship	NOUN
ajst-5348	114	28	verification	verification	NOUN
ajst-5348	114	29	accuracy	accuracy	NOUN
ajst-5348	114	30	is	be	AUX
ajst-5348	114	31	higher	high	ADJ
ajst-5348	114	32	than	than	ADP
ajst-5348	114	33	that	that	PRON
ajst-5348	114	34	of	of	ADP
ajst-5348	114	35	only	only	ADJ
ajst-5348	114	36	softmax	softmax	NOUN
ajst-5348	114	37	loss	loss	NOUN
ajst-5348	114	38	supervised	supervised	ADJ
ajst-5348	114	39	learning	learning	NOUN
ajst-5348	114	40	(	(	PUNCT
ajst-5348	114	41	when	when	SCONJ
ajst-5348	114	42	λ	λ	X
ajst-5348	114	43	=	=	NOUN
ajst-5348	114	44	0	0	NUM
ajst-5348	114	45	)	)	PUNCT
ajst-5348	114	46	.	.	PUNCT
ajst-5348	115	1	at	at	ADP
ajst-5348	115	2	the	the	DET
ajst-5348	115	3	same	same	ADJ
ajst-5348	115	4	time	time	NOUN
ajst-5348	115	5	,	,	PUNCT
ajst-5348	115	6	it	it	PRON
ajst-5348	115	7	can	can	AUX
ajst-5348	115	8	also	also	ADV
ajst-5348	115	9	be	be	AUX
ajst-5348	115	10	obtained	obtain	VERB
ajst-5348	115	11	from	from	ADP
ajst-5348	115	12	fig.4	fig.4	PROPN
ajst-5348	115	13	that	that	SCONJ
ajst-5348	115	14	a	a	DET
ajst-5348	115	15	suitable	suitable	ADJ
ajst-5348	115	16	λ	λ	NOUN
ajst-5348	115	17	value	value	NOUN
ajst-5348	115	18	helps	help	VERB
ajst-5348	115	19	to	to	PART
ajst-5348	115	20	improve	improve	VERB
ajst-5348	115	21	the	the	DET
ajst-5348	115	22	accuracy	accuracy	NOUN
ajst-5348	115	23	of	of	ADP
ajst-5348	115	24	kinship	kinship	NOUN
ajst-5348	115	25	verification	verification	NOUN
ajst-5348	115	26	,	,	PUNCT
ajst-5348	115	27	and	and	CCONJ
ajst-5348	115	28	the	the	DET
ajst-5348	115	29	best	good	ADJ
ajst-5348	115	30	result	result	NOUN
ajst-5348	115	31	of	of	ADP
ajst-5348	115	32	parameter	parameter	PROPN
ajst-5348	115	33	λ	λ	PROPN
ajst-5348	115	34	is	be	AUX
ajst-5348	115	35	0.003	0.003	NUM
ajst-5348	115	36	.	.	PUNCT
ajst-5348	115	37	61	61	NUM
ajst-5348	115	38	figure	figure	NOUN
ajst-5348	115	39	5	5	NUM
ajst-5348	115	40	.	.	PUNCT
ajst-5348	115	41	glanet	glanet	NOUN
ajst-5348	115	42	verification	verification	NOUN
ajst-5348	115	43	accuracy	accuracy	NOUN
ajst-5348	115	44	corresponding	correspond	VERB
ajst-5348	115	45	to	to	ADP
ajst-5348	115	46	different	different	ADJ
ajst-5348	115	47	λ	λ	PROPN
ajst-5348	115	48	then	then	ADV
ajst-5348	115	49	,	,	PUNCT
ajst-5348	115	50	for	for	ADP
ajst-5348	115	51	the	the	DET
ajst-5348	115	52	feature	feature	NOUN
ajst-5348	115	53	fusion	fusion	NOUN
ajst-5348	115	54	method	method	NOUN
ajst-5348	115	55	using	use	VERB
ajst-5348	115	56	cnn	cnn	PROPN
ajst-5348	115	57	backbone	backbone	NOUN
ajst-5348	115	58	network	network	NOUN
ajst-5348	115	59	with	with	ADP
ajst-5348	115	60	good	good	ADJ
ajst-5348	115	61	effect	effect	NOUN
ajst-5348	115	62	[	[	X
ajst-5348	115	63	6][7	6][7	NUM
ajst-5348	115	64	]	]	PUNCT
ajst-5348	115	65	,	,	PUNCT
ajst-5348	115	66	the	the	DET
ajst-5348	115	67	network	network	NOUN
ajst-5348	115	68	accuracy	accuracy	NOUN
ajst-5348	115	69	of	of	ADP
ajst-5348	115	70	glanet	glanet	NOUN
ajst-5348	115	71	model	model	NOUN
ajst-5348	115	72	under	under	ADP
ajst-5348	115	73	these	these	DET
ajst-5348	115	74	different	different	ADJ
ajst-5348	115	75	feature	feature	NOUN
ajst-5348	115	76	fusion	fusion	NOUN
ajst-5348	115	77	methods	method	NOUN
ajst-5348	115	78	is	be	AUX
ajst-5348	115	79	compared	compare	VERB
ajst-5348	115	80	.	.	PUNCT
ajst-5348	116	1	the	the	DET
ajst-5348	116	2	experimental	experimental	ADJ
ajst-5348	116	3	results	result	NOUN
ajst-5348	116	4	are	be	AUX
ajst-5348	116	5	shown	show	VERB
ajst-5348	116	6	in	in	ADP
ajst-5348	116	7	table	table	NOUN
ajst-5348	116	8	3	3	NUM
ajst-5348	116	9	.	.	PUNCT
ajst-5348	117	1	it	it	PRON
ajst-5348	117	2	can	can	AUX
ajst-5348	117	3	be	be	AUX
ajst-5348	117	4	seen	see	VERB
ajst-5348	117	5	from	from	ADP
ajst-5348	117	6	the	the	DET
ajst-5348	117	7	table	table	NOUN
ajst-5348	117	8	,	,	PUNCT
ajst-5348	117	9	the	the	DET
ajst-5348	117	10	third	third	ADJ
ajst-5348	117	11	group	group	NOUN
ajst-5348	117	12	of	of	ADP
ajst-5348	117	13	𝑥	𝑥	PROPN
ajst-5348	117	14	𝑦	𝑦	PROPN
ajst-5348	117	15	2	2	NUM
ajst-5348	117	16	,	,	PUNCT
ajst-5348	117	17	𝑥	𝑥	PRON
ajst-5348	117	18	𝑦	𝑦	NOUN
ajst-5348	117	19	2	2	NUM
ajst-5348	117	20	,	,	PUNCT
ajst-5348	117	21	𝑥	𝑥	PRON
ajst-5348	117	22	⋅	⋅	PROPN
ajst-5348	117	23	𝑦	𝑦	PROPN
ajst-5348	117	24	,	,	PUNCT
ajst-5348	117	25	x	x	SYM
ajst-5348	117	26	2	2	NUM
ajst-5348	117	27	𝑦2	𝑦2	NOUN
ajst-5348	117	28	fusion	fusion	NOUN
ajst-5348	117	29	methods	method	NOUN
ajst-5348	117	30	obtained	obtain	VERB
ajst-5348	117	31	the	the	DET
ajst-5348	117	32	highest	high	ADJ
ajst-5348	117	33	accuracy	accuracy	NOUN
ajst-5348	117	34	of	of	ADP
ajst-5348	117	35	79.6	79.6	NUM
ajst-5348	117	36	%	%	NOUN
ajst-5348	117	37	,	,	PUNCT
ajst-5348	117	38	and	and	CCONJ
ajst-5348	117	39	the	the	DET
ajst-5348	117	40	subsequent	subsequent	ADJ
ajst-5348	117	41	glanet	glanet	NOUN
ajst-5348	117	42	model	model	NOUN
ajst-5348	117	43	selected	select	VERB
ajst-5348	117	44	this	this	DET
ajst-5348	117	45	group	group	NOUN
ajst-5348	117	46	of	of	ADP
ajst-5348	117	47	fusion	fusion	NOUN
ajst-5348	117	48	methods	method	NOUN
ajst-5348	117	49	for	for	ADP
ajst-5348	117	50	experiments	experiment	NOUN
ajst-5348	117	51	.	.	PUNCT
ajst-5348	118	1	table	table	NOUN
ajst-5348	118	2	3	3	NUM
ajst-5348	118	3	.	.	PUNCT
ajst-5348	119	1	accuracy	accuracy	NOUN
ajst-5348	119	2	comparison	comparison	NOUN
ajst-5348	119	3	of	of	ADP
ajst-5348	119	4	glanet	glanet	NOUN
ajst-5348	119	5	with	with	ADP
ajst-5348	119	6	different	different	ADJ
ajst-5348	119	7	feature	feature	NOUN
ajst-5348	119	8	fusion	fusion	NOUN
ajst-5348	119	9	methods	method	NOUN
ajst-5348	119	10	feature	feature	VERB
ajst-5348	119	11	fusion	fusion	NOUN
ajst-5348	119	12	acc	acc	PROPN
ajst-5348	119	13	(	(	PUNCT
ajst-5348	119	14	%	%	NOUN
ajst-5348	119	15	)	)	PUNCT
ajst-5348	119	16	𝑥	𝑥	PRON
ajst-5348	120	1	𝑦、𝑥	𝑦、𝑥	PUNCT
ajst-5348	120	2	𝑦、𝑥	𝑦、𝑥	PUNCT
ajst-5348	120	3	⋅	⋅	PROPN
ajst-5348	120	4	𝑦、1/2	𝑦、1/2	PROPN
ajst-5348	120	5	𝑥	𝑥	PROPN
ajst-5348	120	6	𝑦	𝑦	NOUN
ajst-5348	120	7	78.5	78.5	NUM
ajst-5348	120	8	𝑥	𝑥	PRON
ajst-5348	120	9	𝑦、𝑥	𝑦、𝑥	PROPN
ajst-5348	120	10	𝑦、𝑥	𝑦、𝑥	PROPN
ajst-5348	120	11	⋅	⋅	PROPN
ajst-5348	120	12	𝑦	𝑦	X
ajst-5348	120	13	、	、	NOUN
ajst-5348	120	14	x	x	SYM
ajst-5348	120	15	𝑦	𝑦	NOUN
ajst-5348	120	16	78.7	78.7	NUM
ajst-5348	120	17	𝑥	𝑥	NOUN
ajst-5348	120	18	𝑦	𝑦	PROPN
ajst-5348	120	19	2	2	NUM
ajst-5348	120	20	、	、	ADP
ajst-5348	120	21	𝑥	𝑥	PRON
ajst-5348	120	22	𝑦	𝑦	NUM
ajst-5348	120	23	2、𝑥	2、𝑥	ADJ
ajst-5348	120	24	⋅	⋅	PROPN
ajst-5348	120	25	𝑦	𝑦	X
ajst-5348	120	26	、	、	NOUN
ajst-5348	120	27	x	x	SYM
ajst-5348	120	28	2	2	NUM
ajst-5348	120	29	𝑦2	𝑦2	NOUN
ajst-5348	120	30	79.6	79.6	NUM
ajst-5348	120	31	𝑥	𝑥	NOUN
ajst-5348	120	32	𝑦	𝑦	NUM
ajst-5348	120	33	2、√𝑥	2、√𝑥	NOUN
ajst-5348	120	34	𝑦、𝑥	𝑦、𝑥	ADP
ajst-5348	120	35	⋅	⋅	PROPN
ajst-5348	120	36	𝑦	𝑦	X
ajst-5348	120	37	、	、	NOUN
ajst-5348	120	38	x	x	SYM
ajst-5348	120	39	2	2	NUM
ajst-5348	120	40	𝑦2	𝑦2	NOUN
ajst-5348	120	41	79.3	79.3	NUM
ajst-5348	120	42	table	table	NOUN
ajst-5348	120	43	4	4	NUM
ajst-5348	120	44	.	.	PUNCT
ajst-5348	120	45	accuracy	accuracy	NOUN
ajst-5348	120	46	comparison	comparison	NOUN
ajst-5348	120	47	with	with	ADP
ajst-5348	120	48	fg2020	fg2020	ADJ
ajst-5348	120	49	challenge	challenge	NOUN
ajst-5348	120	50	leading	lead	VERB
ajst-5348	120	51	method	method	NOUN
ajst-5348	120	52	figure	figure	NOUN
ajst-5348	120	53	6	6	NUM
ajst-5348	120	54	.	.	PUNCT
ajst-5348	121	1	the	the	DET
ajst-5348	121	2	validation	validation	NOUN
ajst-5348	121	3	accuracy	accuracy	NOUN
ajst-5348	121	4	line	line	NOUN
ajst-5348	121	5	chart	chart	NOUN
ajst-5348	121	6	of	of	ADP
ajst-5348	121	7	11	11	NUM
ajst-5348	121	8	kinship	kinship	NOUN
ajst-5348	121	9	pairs	pair	NOUN
ajst-5348	121	10	77.2	77.2	NUM
ajst-5348	121	11	77.6	77.6	NUM
ajst-5348	121	12	78	78	NUM
ajst-5348	121	13	78.4	78.4	NUM
ajst-5348	121	14	78.8	78.8	NUM
ajst-5348	121	15	79.2	79.2	NUM
ajst-5348	121	16	79.6	79.6	NUM
ajst-5348	121	17	v	v	NOUN
ajst-5348	121	18	er	er	INTJ
ajst-5348	121	19	if	if	SCONJ
ajst-5348	121	20	ic	ic	PROPN
ajst-5348	121	21	at	at	ADP
ajst-5348	121	22	io	io	PROPN
ajst-5348	121	23	n	n	ADV
ajst-5348	121	24	a	a	PRON
ajst-5348	121	25	cc	cc	X
ajst-5348	121	26	ur	ur	INTJ
ajst-5348	122	1	ac	ac	PROPN
ajst-5348	122	2	y	y	PROPN
ajst-5348	122	3	(	(	PUNCT
ajst-5348	122	4	%	%	NOUN
ajst-5348	122	5	)	)	PUNCT
ajst-5348	122	6	λ/(at	λ/(at	PROPN
ajst-5348	122	7	log	log	PROPN
ajst-5348	122	8	scale	scale	NOUN
ajst-5348	122	9	)	)	PUNCT
ajst-5348	122	10	methods	method	NOUN
ajst-5348	122	11	f	f	NOUN
ajst-5348	122	12	-	-	PROPN
ajst-5348	122	13	d	d	NOUN
ajst-5348	122	14	f	f	X
ajst-5348	122	15	-	-	PUNCT
ajst-5348	122	16	s	s	NOUN
ajst-5348	122	17	m	m	NOUN
ajst-5348	122	18	-	-	PUNCT
ajst-5348	122	19	d	d	PROPN
ajst-5348	122	20	m	m	PROPN
ajst-5348	122	21	-	-	PUNCT
ajst-5348	122	22	s	s	PRON
ajst-5348	122	23	gf	gf	NOUN
ajst-5348	122	24	-	-	NOUN
ajst-5348	122	25	gd	gd	ADJ
ajst-5348	122	26	gf	gf	PROPN
ajst-5348	122	27	-	-	PUNCT
ajst-5348	122	28	gs	gs	INTJ
ajst-5348	122	29	gm	gm	PROPN
ajst-5348	122	30	-	-	PUNCT
ajst-5348	122	31	gd	gd	ADJ
ajst-5348	122	32	gm	gm	PROPN
ajst-5348	122	33	-	-	PUNCT
ajst-5348	122	34	gs	gs	INTJ
ajst-5348	122	35	b	b	PROPN
ajst-5348	122	36	-	-	PUNCT
ajst-5348	122	37	b	b	NOUN
ajst-5348	122	38	s	s	PROPN
ajst-5348	122	39	-	-	PUNCT
ajst-5348	122	40	s	s	PART
ajst-5348	122	41	si	si	ADJ
ajst-5348	122	42	-	-	ADJ
ajst-5348	122	43	bs	bs	ADJ
ajst-5348	122	44	avg	avg	PROPN
ajst-5348	122	45	.	.	PROPN
ajst-5348	122	46	baseline	baseline	PROPN
ajst-5348	122	47	0.61	0.61	NUM
ajst-5348	122	48	0.66	0.66	NUM
ajst-5348	122	49	0.69	0.69	NUM
ajst-5348	122	50	0.62	0.62	NUM
ajst-5348	122	51	0.66	0.66	NUM
ajst-5348	122	52	0.71	0.71	NUM
ajst-5348	122	53	0.73	0.73	NUM
ajst-5348	122	54	0.68	0.68	NUM
ajst-5348	122	55	0.57	0.57	NUM
ajst-5348	122	56	0.64	0.64	NUM
ajst-5348	122	57	0.5	0.5	NUM
ajst-5348	122	58	0.64	0.64	NUM
ajst-5348	122	59	stefhoer	stefhoer	NOUN
ajst-5348	122	60	0.77	0.77	NUM
ajst-5348	122	61	0.8	0.8	NUM
ajst-5348	122	62	0.77	0.77	NUM
ajst-5348	122	63	0.78	0.78	NUM
ajst-5348	122	64	0.7	0.7	NUM
ajst-5348	122	65	0.73	0.73	NUM
ajst-5348	122	66	0.64	0.64	NUM
ajst-5348	122	67	0.6	0.6	NUM
ajst-5348	122	68	0.66	0.66	NUM
ajst-5348	122	69	0.65	0.65	NUM
ajst-5348	122	70	0.76	0.76	NUM
ajst-5348	122	71	0.74	0.74	NUM
ajst-5348	122	72	ustc	ustc	NOUN
ajst-5348	122	73	-	-	PUNCT
ajst-5348	122	74	nelslip	nelslip	VERB
ajst-5348	122	75	0.76	0.76	NUM
ajst-5348	122	76	0.82	0.82	NUM
ajst-5348	122	77	0.75	0.75	NUM
ajst-5348	122	78	0.75	0.75	NUM
ajst-5348	122	79	0.79	0.79	NUM
ajst-5348	122	80	0.69	0.69	NUM
ajst-5348	122	81	0.76	0.76	NUM
ajst-5348	122	82	0.67	0.67	NUM
ajst-5348	122	83	0.75	0.75	NUM
ajst-5348	122	84	0.74	0.74	NUM
ajst-5348	122	85	0.72	0.72	NUM
ajst-5348	122	86	0.76	0.76	NUM
ajst-5348	122	87	deepblueai	deepblueai	NOUN
ajst-5348	122	88	0.74	0.74	NUM
ajst-5348	122	89	0.81	0.81	NUM
ajst-5348	122	90	0.75	0.75	NUM
ajst-5348	122	91	0.74	0.74	NUM
ajst-5348	122	92	0.72	0.72	NUM
ajst-5348	122	93	0.73	0.73	NUM
ajst-5348	122	94	0.67	0.67	NUM
ajst-5348	122	95	0.68	0.68	NUM
ajst-5348	122	96	0.77	0.77	NUM
ajst-5348	122	97	0.77	0.77	NUM
ajst-5348	122	98	0.75	0.75	NUM
ajst-5348	122	99	0.76	0.76	NUM
ajst-5348	122	100	vuvko	vuvko	NOUN
ajst-5348	122	101	0.75	0.75	NUM
ajst-5348	122	102	0.81	0.81	NUM
ajst-5348	122	103	0.78	0.78	NUM
ajst-5348	122	104	0.74	0.74	NUM
ajst-5348	122	105	0.78	0.78	NUM
ajst-5348	122	106	0.69	0.69	NUM
ajst-5348	122	107	0.76	0.76	NUM
ajst-5348	122	108	0.6	0.6	NUM
ajst-5348	122	109	0.8	0.8	NUM
ajst-5348	122	110	0.8	0.8	NUM
ajst-5348	122	111	0.77	0.77	NUM
ajst-5348	122	112	0.78	0.78	NUM
ajst-5348	122	113	glanet	glanet	NOUN
ajst-5348	122	114	0.77	0.77	NUM
ajst-5348	122	115	0.83	0.83	NUM
ajst-5348	122	116	0.77	0.77	NUM
ajst-5348	122	117	0.79	0.79	NUM
ajst-5348	122	118	0.8	0.8	NUM
ajst-5348	122	119	0.72	0.72	NUM
ajst-5348	122	120	0.78	0.78	NUM
ajst-5348	122	121	0.67	0.67	NUM
ajst-5348	122	122	0.81	0.81	NUM
ajst-5348	122	123	0.8	0.8	NUM
ajst-5348	122	124	0.78	0.78	NUM
ajst-5348	122	125	0.79	0.79	NUM
ajst-5348	122	126	0.45	0.45	NUM
ajst-5348	122	127	0.5	0.5	NUM
ajst-5348	122	128	0.55	0.55	NUM
ajst-5348	122	129	0.6	0.6	NUM
ajst-5348	122	130	0.65	0.65	NUM
ajst-5348	122	131	0.7	0.7	NUM
ajst-5348	122	132	0.75	0.75	NUM
ajst-5348	122	133	0.8	0.8	NUM
ajst-5348	122	134	0.85	0.85	NUM
ajst-5348	122	135	f	f	X
ajst-5348	122	136	-	-	PUNCT
ajst-5348	122	137	d	d	NOUN
ajst-5348	122	138	f	f	X
ajst-5348	122	139	-	-	PUNCT
ajst-5348	122	140	s	s	NOUN
ajst-5348	122	141	m	m	NOUN
ajst-5348	122	142	-	-	PUNCT
ajst-5348	122	143	d	d	PROPN
ajst-5348	122	144	m	m	PROPN
ajst-5348	122	145	-	-	PUNCT
ajst-5348	122	146	s	s	PRON
ajst-5348	122	147	gf	gf	NOUN
ajst-5348	122	148	-	-	NOUN
ajst-5348	122	149	gd	gd	ADJ
ajst-5348	122	150	gf	gf	PROPN
ajst-5348	122	151	-	-	PUNCT
ajst-5348	122	152	gs	gs	INTJ
ajst-5348	122	153	gm	gm	PROPN
ajst-5348	122	154	-	-	PUNCT
ajst-5348	122	155	gd	gd	ADJ
ajst-5348	122	156	gm	gm	PROPN
ajst-5348	122	157	-	-	PUNCT
ajst-5348	122	158	gs	gs	INTJ
ajst-5348	122	159	b	b	PROPN
ajst-5348	122	160	-	-	PUNCT
ajst-5348	122	161	b	b	NOUN
ajst-5348	122	162	s	s	PROPN
ajst-5348	122	163	-	-	PUNCT
ajst-5348	122	164	s	s	PART
ajst-5348	122	165	si	si	ADJ
ajst-5348	122	166	-	-	ADJ
ajst-5348	122	167	bs	bs	ADJ
ajst-5348	122	168	avg	avg	PROPN
ajst-5348	122	169	.	.	PROPN
ajst-5348	123	1	v	v	ADP
ajst-5348	123	2	er	er	INTJ
ajst-5348	123	3	if	if	SCONJ
ajst-5348	123	4	ic	ic	PROPN
ajst-5348	123	5	at	at	ADP
ajst-5348	123	6	io	io	PROPN
ajst-5348	123	7	n	n	ADV
ajst-5348	123	8	a	a	PRON
ajst-5348	123	9	cc	cc	X
ajst-5348	123	10	ur	ur	INTJ
ajst-5348	123	11	ac	ac	PROPN
ajst-5348	123	12	y	y	PROPN
ajst-5348	123	13	baseline	baseline	PROPN
ajst-5348	123	14	stefhoer	stefhoer	PROPN
ajst-5348	123	15	ustc	ustc	PROPN
ajst-5348	123	16	-	-	PUNCT
ajst-5348	123	17	nelslip	nelslip	VERB
ajst-5348	123	18	deepblueai	deepblueai	PROPN
ajst-5348	123	19	vuvko	vuvko	PROPN
ajst-5348	123	20	glanet	glanet	PROPN
ajst-5348	123	21	62	62	NUM
ajst-5348	123	22	in	in	ADP
ajst-5348	123	23	order	order	NOUN
ajst-5348	123	24	to	to	PART
ajst-5348	123	25	further	far	ADV
ajst-5348	123	26	verify	verify	VERB
ajst-5348	123	27	the	the	DET
ajst-5348	123	28	performance	performance	NOUN
ajst-5348	123	29	of	of	ADP
ajst-5348	123	30	the	the	DET
ajst-5348	123	31	glanet	glanet	NOUN
ajst-5348	123	32	model	model	NOUN
ajst-5348	123	33	,	,	PUNCT
ajst-5348	123	34	it	it	PRON
ajst-5348	123	35	is	be	AUX
ajst-5348	123	36	compared	compare	VERB
ajst-5348	123	37	with	with	ADP
ajst-5348	123	38	the	the	DET
ajst-5348	123	39	leading	lead	VERB
ajst-5348	123	40	method	method	NOUN
ajst-5348	123	41	of	of	ADP
ajst-5348	123	42	the	the	DET
ajst-5348	123	43	fg2020	fg2020	ADJ
ajst-5348	123	44	challenge	challenge	NOUN
ajst-5348	123	45	,	,	PUNCT
ajst-5348	123	46	and	and	CCONJ
ajst-5348	123	47	the	the	DET
ajst-5348	123	48	results	result	NOUN
ajst-5348	123	49	are	be	AUX
ajst-5348	123	50	shown	show	VERB
ajst-5348	123	51	in	in	ADP
ajst-5348	123	52	table	table	NOUN
ajst-5348	123	53	4	4	NUM
ajst-5348	123	54	.	.	PUNCT
ajst-5348	124	1	the	the	DET
ajst-5348	124	2	experimental	experimental	ADJ
ajst-5348	124	3	results	result	NOUN
ajst-5348	124	4	show	show	VERB
ajst-5348	124	5	that	that	SCONJ
ajst-5348	124	6	the	the	DET
ajst-5348	124	7	accuracy	accuracy	NOUN
ajst-5348	124	8	of	of	ADP
ajst-5348	124	9	glanet	glanet	NOUN
ajst-5348	124	10	is	be	AUX
ajst-5348	124	11	15	15	NUM
ajst-5348	124	12	%	%	NOUN
ajst-5348	124	13	higher	high	ADJ
ajst-5348	124	14	than	than	ADP
ajst-5348	124	15	that	that	PRON
ajst-5348	124	16	of	of	ADP
ajst-5348	124	17	the	the	DET
ajst-5348	124	18	baseline	baseline	NOUN
ajst-5348	124	19	model	model	NOUN
ajst-5348	124	20	and	and	CCONJ
ajst-5348	124	21	1.6	1.6	NUM
ajst-5348	124	22	%	%	NOUN
ajst-5348	124	23	higher	high	ADJ
ajst-5348	124	24	than	than	ADP
ajst-5348	124	25	that	that	PRON
ajst-5348	124	26	of	of	ADP
ajst-5348	124	27	vuvko	vuvko	NOUN
ajst-5348	124	28	,	,	PUNCT
ajst-5348	124	29	and	and	CCONJ
ajst-5348	124	30	the	the	DET
ajst-5348	124	31	glanet	glanet	NOUN
ajst-5348	124	32	method	method	NOUN
ajst-5348	124	33	obtains	obtain	VERB
ajst-5348	124	34	the	the	DET
ajst-5348	124	35	best	good	ADJ
ajst-5348	124	36	results	result	NOUN
ajst-5348	124	37	.	.	PUNCT
ajst-5348	125	1	the	the	DET
ajst-5348	125	2	line	line	NOUN
ajst-5348	125	3	chart	chart	NOUN
ajst-5348	125	4	of	of	ADP
ajst-5348	125	5	the	the	DET
ajst-5348	125	6	verification	verification	NOUN
ajst-5348	125	7	accuracy	accuracy	NOUN
ajst-5348	125	8	of	of	ADP
ajst-5348	125	9	11	11	NUM
ajst-5348	125	10	kinship	kinship	NOUN
ajst-5348	125	11	pairs	pair	NOUN
ajst-5348	125	12	is	be	AUX
ajst-5348	125	13	shown	show	VERB
ajst-5348	125	14	in	in	ADP
ajst-5348	125	15	fig.6.it	fig.6.it	PROPN
ajst-5348	125	16	can	can	AUX
ajst-5348	125	17	be	be	AUX
ajst-5348	125	18	seen	see	VERB
ajst-5348	125	19	that	that	SCONJ
ajst-5348	125	20	the	the	DET
ajst-5348	125	21	proposed	propose	VERB
ajst-5348	125	22	glanet	glanet	NOUN
ajst-5348	125	23	method	method	NOUN
ajst-5348	125	24	can	can	AUX
ajst-5348	125	25	achieve	achieve	VERB
ajst-5348	125	26	the	the	DET
ajst-5348	125	27	best	good	ADJ
ajst-5348	125	28	accuracy	accuracy	NOUN
ajst-5348	125	29	compared	compare	VERB
ajst-5348	125	30	with	with	ADP
ajst-5348	125	31	other	other	ADJ
ajst-5348	125	32	methods	method	NOUN
ajst-5348	125	33	in	in	ADP
ajst-5348	125	34	most	most	ADJ
ajst-5348	125	35	relationship	relationship	NOUN
ajst-5348	125	36	pairs	pair	NOUN
ajst-5348	125	37	.	.	PUNCT
ajst-5348	126	1	in	in	ADP
ajst-5348	126	2	gf	gf	PROPN
ajst-5348	126	3	-	-	PUNCT
ajst-5348	126	4	gs	gs	PROPN
ajst-5348	126	5	and	and	CCONJ
ajst-5348	126	6	gm	gm	PROPN
ajst-5348	126	7	-	-	PUNCT
ajst-5348	126	8	gs	gs	PROPN
ajst-5348	126	9	relation	relation	NOUN
ajst-5348	126	10	pairs	pair	NOUN
ajst-5348	126	11	,	,	PUNCT
ajst-5348	126	12	the	the	DET
ajst-5348	126	13	accuracy	accuracy	NOUN
ajst-5348	126	14	of	of	ADP
ajst-5348	126	15	the	the	DET
ajst-5348	126	16	methods	method	NOUN
ajst-5348	126	17	listed	list	VERB
ajst-5348	126	18	is	be	AUX
ajst-5348	126	19	low	low	ADJ
ajst-5348	126	20	,	,	PUNCT
ajst-5348	126	21	which	which	PRON
ajst-5348	126	22	is	be	AUX
ajst-5348	126	23	due	due	ADJ
ajst-5348	126	24	to	to	ADP
ajst-5348	126	25	the	the	DET
ajst-5348	126	26	small	small	ADJ
ajst-5348	126	27	number	number	NOUN
ajst-5348	126	28	of	of	ADP
ajst-5348	126	29	face	face	NOUN
ajst-5348	126	30	images	image	NOUN
ajst-5348	126	31	and	and	CCONJ
ajst-5348	126	32	age	age	NOUN
ajst-5348	126	33	.	.	PUNCT
ajst-5348	127	1	finally	finally	ADV
ajst-5348	127	2	,	,	PUNCT
ajst-5348	127	3	in	in	ADP
ajst-5348	127	4	order	order	NOUN
ajst-5348	127	5	to	to	PART
ajst-5348	127	6	further	far	ADV
ajst-5348	127	7	compare	compare	VERB
ajst-5348	127	8	the	the	DET
ajst-5348	127	9	feasibility	feasibility	NOUN
ajst-5348	127	10	and	and	CCONJ
ajst-5348	127	11	effectiveness	effectiveness	NOUN
ajst-5348	127	12	of	of	ADP
ajst-5348	127	13	introducing	introduce	VERB
ajst-5348	127	14	vit	vit	NOUN
ajst-5348	127	15	with	with	ADP
ajst-5348	127	16	global	global	ADJ
ajst-5348	127	17	autonomous	autonomous	ADJ
ajst-5348	127	18	attention	attention	NOUN
ajst-5348	127	19	mechanism	mechanism	NOUN
ajst-5348	127	20	,	,	PUNCT
ajst-5348	127	21	that	that	ADV
ajst-5348	127	22	is	is	ADV
ajst-5348	127	23	,	,	PUNCT
ajst-5348	127	24	using	use	VERB
ajst-5348	127	25	pvt	pvt	PROPN
ajst-5348	127	26	as	as	SCONJ
ajst-5348	127	27	the	the	DET
ajst-5348	127	28	backbone	backbone	NOUN
ajst-5348	127	29	feature	feature	NOUN
ajst-5348	127	30	extraction	extraction	NOUN
ajst-5348	127	31	network	network	NOUN
ajst-5348	127	32	,	,	PUNCT
ajst-5348	127	33	the	the	DET
ajst-5348	127	34	common	common	ADJ
ajst-5348	127	35	convolutional	convolutional	ADJ
ajst-5348	127	36	neural	neural	ADJ
ajst-5348	127	37	networks	network	NOUN
ajst-5348	127	38	vgg16	vgg16	PROPN
ajst-5348	127	39	,	,	PUNCT
ajst-5348	127	40	senet50	senet50	NOUN
ajst-5348	127	41	and	and	CCONJ
ajst-5348	127	42	inception	inception	NOUN
ajst-5348	127	43	-	-	PUNCT
ajst-5348	127	44	resnetv1	resnetv1	NOUN
ajst-5348	127	45	are	be	AUX
ajst-5348	127	46	used	use	VERB
ajst-5348	127	47	to	to	PART
ajst-5348	127	48	replace	replace	VERB
ajst-5348	127	49	the	the	DET
ajst-5348	127	50	pvt	pvt	PROPN
ajst-5348	127	51	backbone	backbone	NOUN
ajst-5348	127	52	feature	feature	NOUN
ajst-5348	127	53	extraction	extraction	NOUN
ajst-5348	127	54	network	network	NOUN
ajst-5348	127	55	in	in	ADP
ajst-5348	127	56	the	the	DET
ajst-5348	127	57	glanet	glanet	NOUN
ajst-5348	127	58	model	model	NOUN
ajst-5348	127	59	,	,	PUNCT
ajst-5348	127	60	and	and	CCONJ
ajst-5348	127	61	all	all	DET
ajst-5348	127	62	convolutional	convolutional	ADJ
ajst-5348	127	63	neural	neural	ADJ
ajst-5348	127	64	network	network	NOUN
ajst-5348	127	65	models	model	NOUN
ajst-5348	127	66	are	be	AUX
ajst-5348	127	67	pre	pre	ADJ
ajst-5348	127	68	-	-	VERB
ajst-5348	127	69	trained	train	VERB
ajst-5348	127	70	on	on	ADP
ajst-5348	127	71	imagenet	imagenet	NOUN
ajst-5348	127	72	.	.	PUNCT
ajst-5348	128	1	other	other	ADJ
ajst-5348	128	2	settings	setting	NOUN
ajst-5348	128	3	are	be	AUX
ajst-5348	128	4	consistent	consistent	ADJ
ajst-5348	128	5	with	with	ADP
ajst-5348	128	6	resnet50	resnet50	NOUN
ajst-5348	128	7	and	and	CCONJ
ajst-5348	128	8	pvt	pvt	PROPN
ajst-5348	128	9	as	as	ADP
ajst-5348	128	10	glanet	glanet	NOUN
ajst-5348	128	11	feature	feature	NOUN
ajst-5348	128	12	extraction	extraction	NOUN
ajst-5348	128	13	models	model	NOUN
ajst-5348	128	14	for	for	ADP
ajst-5348	128	15	maximum	maximum	ADJ
ajst-5348	128	16	accuracy	accuracy	NOUN
ajst-5348	128	17	.	.	PUNCT
ajst-5348	129	1	the	the	DET
ajst-5348	129	2	results	result	NOUN
ajst-5348	129	3	are	be	AUX
ajst-5348	129	4	shown	show	VERB
ajst-5348	129	5	in	in	ADP
ajst-5348	129	6	table	table	NOUN
ajst-5348	129	7	5	5	NUM
ajst-5348	129	8	.	.	PUNCT
ajst-5348	129	9	inception	inception	NOUN
ajst-5348	129	10	-	-	PUNCT
ajst-5348	129	11	resnetv1	resnetv1	NOUN
ajst-5348	129	12	and	and	CCONJ
ajst-5348	129	13	resnet50	resnet50	NOUN
ajst-5348	129	14	have	have	VERB
ajst-5348	129	15	higher	high	ADJ
ajst-5348	129	16	accuracy	accuracy	NOUN
ajst-5348	129	17	as	as	ADP
ajst-5348	129	18	backbone	backbone	NOUN
ajst-5348	129	19	networks	network	NOUN
ajst-5348	129	20	,	,	PUNCT
ajst-5348	129	21	reaching	reach	VERB
ajst-5348	129	22	77.8	77.8	NUM
ajst-5348	129	23	%	%	NOUN
ajst-5348	129	24	.	.	PUNCT
ajst-5348	130	1	however	however	ADV
ajst-5348	130	2	,	,	PUNCT
ajst-5348	130	3	the	the	DET
ajst-5348	130	4	accuracy	accuracy	NOUN
ajst-5348	130	5	is	be	AUX
ajst-5348	130	6	1.8	1.8	NUM
ajst-5348	130	7	%	%	NOUN
ajst-5348	130	8	lower	low	ADJ
ajst-5348	130	9	than	than	ADP
ajst-5348	130	10	that	that	PRON
ajst-5348	130	11	of	of	ADP
ajst-5348	130	12	glanet	glanet	NOUN
ajst-5348	130	13	model	model	NOUN
ajst-5348	130	14	,	,	PUNCT
ajst-5348	130	15	which	which	PRON
ajst-5348	130	16	proves	prove	VERB
ajst-5348	130	17	the	the	DET
ajst-5348	130	18	feasibility	feasibility	NOUN
ajst-5348	130	19	and	and	CCONJ
ajst-5348	130	20	effectiveness	effectiveness	NOUN
ajst-5348	130	21	of	of	ADP
ajst-5348	130	22	the	the	DET
ajst-5348	130	23	proposed	propose	VERB
ajst-5348	130	24	method	method	NOUN
ajst-5348	130	25	.	.	PUNCT
ajst-5348	131	1	table	table	NOUN
ajst-5348	131	2	5	5	NUM
ajst-5348	131	3	.	.	PUNCT
ajst-5348	132	1	accuracy	accuracy	NOUN
ajst-5348	132	2	comparison	comparison	NOUN
ajst-5348	132	3	using	use	VERB
ajst-5348	132	4	different	different	ADJ
ajst-5348	132	5	backbone	backbone	NOUN
ajst-5348	132	6	networks	network	NOUN
ajst-5348	132	7	backbone	backbone	NOUN
ajst-5348	132	8	acc	acc	PROPN
ajst-5348	132	9	vgg16&resnet50	vgg16&resnet50	PROPN
ajst-5348	132	10	74.2	74.2	NUM
ajst-5348	132	11	%	%	NOUN
ajst-5348	132	12	senet50&resnet50	senet50&resnet50	NOUN
ajst-5348	132	13	76.7	76.7	NUM
ajst-5348	132	14	%	%	NOUN
ajst-5348	132	15	inceptionresnetv1&resnet50	inceptionresnetv1&resnet50	NOUN
ajst-5348	132	16	77.8	77.8	NUM
ajst-5348	132	17	%	%	NOUN
ajst-5348	132	18	5	5	NUM
ajst-5348	132	19	.	.	PUNCT
ajst-5348	132	20	conclusion	conclusion	NOUN
ajst-5348	132	21	in	in	ADP
ajst-5348	132	22	this	this	DET
ajst-5348	132	23	paper	paper	NOUN
ajst-5348	132	24	,	,	PUNCT
ajst-5348	132	25	a	a	DET
ajst-5348	132	26	glanet	glanet	NOUN
ajst-5348	132	27	method	method	NOUN
ajst-5348	132	28	for	for	ADP
ajst-5348	132	29	kinship	kinship	NOUN
ajst-5348	132	30	verification	verification	NOUN
ajst-5348	132	31	is	be	AUX
ajst-5348	132	32	proposed	propose	VERB
ajst-5348	132	33	.	.	PUNCT
ajst-5348	133	1	by	by	ADP
ajst-5348	133	2	introducing	introduce	VERB
ajst-5348	133	3	a	a	DET
ajst-5348	133	4	vit	vit	ADJ
ajst-5348	133	5	model	model	NOUN
ajst-5348	133	6	with	with	ADP
ajst-5348	133	7	self	self	NOUN
ajst-5348	133	8	-	-	PUNCT
ajst-5348	133	9	attention	attention	NOUN
ajst-5348	133	10	mechanism	mechanism	NOUN
ajst-5348	133	11	to	to	PART
ajst-5348	133	12	make	make	VERB
ajst-5348	133	13	up	up	ADP
ajst-5348	133	14	for	for	ADP
ajst-5348	133	15	the	the	DET
ajst-5348	133	16	shortcomings	shortcoming	NOUN
ajst-5348	133	17	of	of	ADP
ajst-5348	133	18	the	the	DET
ajst-5348	133	19	traditional	traditional	ADJ
ajst-5348	133	20	convolutional	convolutional	ADJ
ajst-5348	133	21	neural	neural	ADJ
ajst-5348	133	22	network	network	NOUN
ajst-5348	133	23	with	with	ADP
ajst-5348	133	24	local	local	ADJ
ajst-5348	133	25	attention	attention	NOUN
ajst-5348	133	26	mechanism	mechanism	NOUN
ajst-5348	133	27	,	,	PUNCT
ajst-5348	133	28	a	a	DET
ajst-5348	133	29	siamese	siamese	ADJ
ajst-5348	133	30	network	network	NOUN
ajst-5348	133	31	is	be	AUX
ajst-5348	133	32	constructed	construct	VERB
ajst-5348	133	33	to	to	PART
ajst-5348	133	34	further	far	ADV
ajst-5348	133	35	fuse	fuse	VERB
ajst-5348	133	36	the	the	DET
ajst-5348	133	37	facial	facial	ADJ
ajst-5348	133	38	features	feature	NOUN
ajst-5348	133	39	of	of	ADP
ajst-5348	133	40	relatives	relative	NOUN
ajst-5348	133	41	and	and	CCONJ
ajst-5348	133	42	further	far	ADV
ajst-5348	133	43	extract	extract	VERB
ajst-5348	133	44	more	more	ADJ
ajst-5348	133	45	discriminative	discriminative	NOUN
ajst-5348	133	46	features	feature	NOUN
ajst-5348	133	47	for	for	ADP
ajst-5348	133	48	kinship	kinship	NOUN
ajst-5348	133	49	verification	verification	NOUN
ajst-5348	133	50	.	.	PUNCT
ajst-5348	134	1	the	the	DET
ajst-5348	134	2	experimental	experimental	ADJ
ajst-5348	134	3	results	result	NOUN
ajst-5348	134	4	prove	prove	VERB
ajst-5348	134	5	the	the	DET
ajst-5348	134	6	feasibility	feasibility	NOUN
ajst-5348	134	7	and	and	CCONJ
ajst-5348	134	8	effectiveness	effectiveness	NOUN
ajst-5348	134	9	of	of	ADP
ajst-5348	134	10	the	the	DET
ajst-5348	134	11	proposed	propose	VERB
ajst-5348	134	12	method	method	NOUN
ajst-5348	134	13	.	.	PUNCT
ajst-5348	135	1	compared	compare	VERB
ajst-5348	135	2	with	with	ADP
ajst-5348	135	3	the	the	DET
ajst-5348	135	4	leading	lead	VERB
ajst-5348	135	5	method	method	NOUN
ajst-5348	135	6	of	of	ADP
ajst-5348	135	7	fg2020	fg2020	PROPN
ajst-5348	135	8	challenge	challenge	NOUN
ajst-5348	135	9	,	,	PUNCT
ajst-5348	135	10	the	the	DET
ajst-5348	135	11	accuracy	accuracy	NOUN
ajst-5348	135	12	of	of	ADP
ajst-5348	135	13	kinship	kinship	NOUN
ajst-5348	135	14	verification	verification	NOUN
ajst-5348	135	15	is	be	AUX
ajst-5348	135	16	better	well	ADJ
ajst-5348	135	17	,	,	PUNCT
ajst-5348	135	18	reaching	reach	VERB
ajst-5348	135	19	79.6	79.6	NUM
ajst-5348	135	20	%	%	NOUN
ajst-5348	135	21	.	.	PUNCT
ajst-5348	136	1	acknowledgment	acknowledgment	NOUN
ajst-5348	136	2	this	this	DET
ajst-5348	136	3	paper	paper	NOUN
ajst-5348	136	4	was	be	AUX
ajst-5348	136	5	supported	support	VERB
ajst-5348	136	6	by	by	ADP
ajst-5348	136	7	the	the	DET
ajst-5348	136	8	open	open	ADJ
ajst-5348	136	9	foundation	foundation	NOUN
ajst-5348	136	10	of	of	ADP
ajst-5348	136	11	artificial	artificial	ADJ
ajst-5348	136	12	intelligence	intelligence	NOUN
ajst-5348	136	13	key	key	NOUN
ajst-5348	136	14	laboratory	laboratory	NOUN
ajst-5348	136	15	of	of	ADP
ajst-5348	136	16	sichuan	sichuan	PROPN
ajst-5348	136	17	province	province	PROPN
ajst-5348	136	18	under	under	ADP
ajst-5348	136	19	grant	grant	PROPN
ajst-5348	136	20	2020rzj03	2020rzj03	PROPN
ajst-5348	136	21	,	,	PUNCT
ajst-5348	136	22	and	and	CCONJ
ajst-5348	136	23	the	the	DET
ajst-5348	136	24	scientific	scientific	ADJ
ajst-5348	136	25	research	research	NOUN
ajst-5348	136	26	foundation	foundation	PROPN
ajst-5348	136	27	of	of	ADP
ajst-5348	136	28	sichuan	sichuan	PROPN
ajst-5348	136	29	university	university	PROPN
ajst-5348	136	30	of	of	ADP
ajst-5348	136	31	science	science	NOUN
ajst-5348	136	32	and	and	CCONJ
ajst-5348	136	33	engineering	engineering	NOUN
ajst-5348	136	34	under	under	ADP
ajst-5348	136	35	grant	grant	PROPN
ajst-5348	136	36	2019rc12	2019rc12	NUM
ajst-5348	136	37	.	.	PUNCT
ajst-5348	136	38	references	reference	NOUN
ajst-5348	137	1	[	[	X
ajst-5348	137	2	1	1	NUM
ajst-5348	137	3	]	]	PUNCT
ajst-5348	137	4	debruine	debruine	NOUN
ajst-5348	137	5	l	l	PROPN
ajst-5348	137	6	m	m	PROPN
ajst-5348	137	7	,	,	PUNCT
ajst-5348	137	8	smith	smith	PROPN
ajst-5348	137	9	f	f	PROPN
ajst-5348	137	10	g	g	PROPN
ajst-5348	137	11	,	,	PUNCT
ajst-5348	137	12	jones	jones	PROPN
ajst-5348	137	13	b	b	PROPN
ajst-5348	137	14	c	c	PROPN
ajst-5348	137	15	,	,	PUNCT
ajst-5348	137	16	et	et	PROPN
ajst-5348	137	17	al	al	PROPN
ajst-5348	137	18	.	.	PROPN
ajst-5348	137	19	kin	kin	PROPN
ajst-5348	137	20	recognition	recognition	PROPN
ajst-5348	137	21	signals	signal	NOUN
ajst-5348	137	22	in	in	ADP
ajst-5348	137	23	adult	adult	NOUN
ajst-5348	137	24	faces[j	faces[j	PROPN
ajst-5348	137	25	]	]	PUNCT
ajst-5348	137	26	.	.	PUNCT
ajst-5348	138	1	vision	vision	PROPN
ajst-5348	138	2	research	research	PROPN
ajst-5348	138	3	,	,	PUNCT
ajst-5348	138	4	2009	2009	NUM
ajst-5348	138	5	,	,	PUNCT
ajst-5348	138	6	49(1	49(1	NUM
ajst-5348	138	7	):	):	PUNCT
ajst-5348	138	8	38	38	NUM
ajst-5348	138	9	-	-	SYM
ajst-5348	138	10	43	43	NUM
ajst-5348	138	11	.	.	PUNCT
ajst-5348	139	1	[	[	X
ajst-5348	139	2	2	2	NUM
ajst-5348	139	3	]	]	X
ajst-5348	139	4	fang	fang	X
ajst-5348	139	5	r	r	PROPN
ajst-5348	139	6	,	,	PUNCT
ajst-5348	139	7	tang	tang	NOUN
ajst-5348	139	8	k	k	PROPN
ajst-5348	140	1	d	d	PROPN
ajst-5348	140	2	,	,	PUNCT
ajst-5348	140	3	snavely	snavely	ADV
ajst-5348	140	4	n	n	CCONJ
ajst-5348	140	5	,	,	PUNCT
ajst-5348	140	6	et	et	NOUN
ajst-5348	140	7	al.towards	al.towards	ADP
ajst-5348	140	8	computational	computational	ADJ
ajst-5348	140	9	models	model	NOUN
ajst-5348	140	10	of	of	ADP
ajst-5348	140	11	kinship	kinship	NOUN
ajst-5348	140	12	verification[c]//2010	verification[c]//2010	PROPN
ajst-5348	140	13	ieee	ieee	PROPN
ajst-5348	140	14	international	international	PROPN
ajst-5348	140	15	conference	conference	NOUN
ajst-5348	140	16	on	on	ADP
ajst-5348	140	17	image	image	NOUN
ajst-5348	140	18	processing	processing	NOUN
ajst-5348	140	19	.	.	PUNCT
ajst-5348	141	1	ieee	ieee	PROPN
ajst-5348	141	2	,	,	PUNCT
ajst-5348	141	3	2010	2010	NUM
ajst-5348	141	4	:	:	PUNCT
ajst-5348	141	5	1577	1577	NUM
ajst-5348	141	6	-	-	SYM
ajst-5348	141	7	1580	1580	NUM
ajst-5348	141	8	.	.	PUNCT
ajst-5348	142	1	[	[	X
ajst-5348	142	2	3	3	X
ajst-5348	142	3	]	]	X
ajst-5348	142	4	yan	yan	PROPN
ajst-5348	142	5	h	h	PROPN
ajst-5348	142	6	,	,	PUNCT
ajst-5348	142	7	lu	lu	PROPN
ajst-5348	142	8	j	j	PROPN
ajst-5348	142	9	,	,	PUNCT
ajst-5348	142	10	deng	deng	PROPN
ajst-5348	142	11	w	w	PROPN
ajst-5348	142	12	,	,	PUNCT
ajst-5348	142	13	et	et	PROPN
ajst-5348	142	14	al.discriminative	al.discriminative	NOUN
ajst-5348	142	15	multimetric	multimetric	ADV
ajst-5348	142	16	learning	learn	VERB
ajst-5348	142	17	for	for	ADP
ajst-5348	142	18	kinship	kinship	NOUN
ajst-5348	142	19	verification[j].ieee	verification[j].ieee	NOUN
ajst-5348	142	20	transactions	transaction	NOUN
ajst-5348	142	21	on	on	ADP
ajst-5348	142	22	information	information	NOUN
ajst-5348	142	23	forensics	forensic	NOUN
ajst-5348	142	24	and	and	CCONJ
ajst-5348	142	25	security,2014,9(7	security,2014,9(7	NOUN
ajst-5348	142	26	):	):	PUNCT
ajst-5348	142	27	1169	1169	NUM
ajst-5348	142	28	-	-	SYM
ajst-5348	142	29	1178	1178	NUM
ajst-5348	142	30	.	.	PUNCT
ajst-5348	143	1	[	[	X
ajst-5348	143	2	4	4	X
ajst-5348	143	3	]	]	X
ajst-5348	143	4	zhou	zhou	X
ajst-5348	143	5	x	x	PUNCT
ajst-5348	143	6	z	z	X
ajst-5348	143	7	,	,	PUNCT
ajst-5348	143	8	jin	jin	PROPN
ajst-5348	143	9	k	k	PROPN
ajst-5348	143	10	,	,	PUNCT
ajst-5348	143	11	xu	xu	PROPN
ajst-5348	143	12	m	m	PROPN
ajst-5348	143	13	,	,	PUNCT
ajst-5348	143	14	et	et	PROPN
ajst-5348	143	15	al	al	PROPN
ajst-5348	143	16	.	.	PUNCT
ajst-5348	144	1	learning	learn	VERB
ajst-5348	144	2	deep	deep	ADJ
ajst-5348	144	3	compact	compact	ADJ
ajst-5348	144	4	similarity	similarity	NOUN
ajst-5348	144	5	metric	metric	ADJ
ajst-5348	144	6	for	for	ADP
ajst-5348	144	7	kinship	kinship	NOUN
ajst-5348	144	8	verification	verification	NOUN
ajst-5348	144	9	from	from	ADP
ajst-5348	144	10	face	face	NOUN
ajst-5348	144	11	images	image	NOUN
ajst-5348	144	12	[	[	X
ajst-5348	144	13	j	j	X
ajst-5348	144	14	]	]	X
ajst-5348	144	15	.	.	PUNCT
ajst-5348	145	1	information	information	NOUN
ajst-5348	145	2	fusion,2019,48:84	fusion,2019,48:84	NOUN
ajst-5348	145	3	-	-	SYM
ajst-5348	145	4	94	94	NUM
ajst-5348	145	5	.	.	PUNCT
ajst-5348	146	1	[	[	X
ajst-5348	146	2	5	5	X
ajst-5348	146	3	]	]	X
ajst-5348	146	4	lu	lu	PROPN
ajst-5348	146	5	j	j	PROPN
ajst-5348	146	6	,	,	PUNCT
ajst-5348	146	7	zhou	zhou	PROPN
ajst-5348	146	8	x	x	PROPN
ajst-5348	146	9	,	,	PUNCT
ajst-5348	146	10	tan	tan	PROPN
ajst-5348	146	11	y	y	PROPN
ajst-5348	146	12	p	p	PROPN
ajst-5348	146	13	,	,	PUNCT
ajst-5348	146	14	et	et	PROPN
ajst-5348	146	15	al.neighborhood	al.neighborhood	NOUN
ajst-5348	146	16	repulsed	repulse	VERB
ajst-5348	146	17	metric	metric	ADJ
ajst-5348	146	18	learning	learning	NOUN
ajst-5348	146	19	for	for	ADP
ajst-5348	146	20	kinship	kinship	NOUN
ajst-5348	146	21	verification[j].ieee	verification[j].ieee	NOUN
ajst-5348	146	22	transactions	transaction	NOUN
ajst-5348	146	23	on	on	ADP
ajst-5348	146	24	pattern	pattern	NOUN
ajst-5348	146	25	analysis	analysis	NOUN
ajst-5348	146	26	and	and	CCONJ
ajst-5348	146	27	machine	machine	NOUN
ajst-5348	146	28	intelligence	intelligence	NOUN
ajst-5348	146	29	,	,	PUNCT
ajst-5348	146	30	2014,36(2):331345	2014,36(2):331345	ADJ
ajst-5348	146	31	.	.	PUNCT
ajst-5348	147	1	[	[	X
ajst-5348	147	2	6	6	NUM
ajst-5348	147	3	]	]	X
ajst-5348	147	4	dornaika	dornaika	PROPN
ajst-5348	148	1	f	f	X
ajst-5348	148	2	,	,	PUNCT
ajst-5348	148	3	arganda	arganda	ADJ
ajst-5348	148	4	-	-	PUNCT
ajst-5348	148	5	carreras	carreras	X
ajst-5348	148	6	i	i	NOUN
ajst-5348	148	7	,	,	PUNCT
ajst-5348	148	8	serradilla	serradilla	NOUN
ajst-5348	148	9	o.	o.	NOUN
ajst-5348	148	10	transfer	transfer	NOUN
ajst-5348	148	11	learning	learning	NOUN
ajst-5348	148	12	and	and	CCONJ
ajst-5348	148	13	feature	feature	NOUN
ajst-5348	148	14	fusion	fusion	NOUN
ajst-5348	148	15	for	for	ADP
ajst-5348	148	16	kinship	kinship	NOUN
ajst-5348	148	17	verification[j	verification[j	NOUN
ajst-5348	148	18	]	]	PUNCT
ajst-5348	148	19	.	.	PUNCT
ajst-5348	148	20	neural	neural	ADJ
ajst-5348	148	21	computing	computing	NOUN
ajst-5348	148	22	and	and	CCONJ
ajst-5348	148	23	applications	application	NOUN
ajst-5348	148	24	,	,	PUNCT
ajst-5348	148	25	2020	2020	NUM
ajst-5348	148	26	,	,	PUNCT
ajst-5348	148	27	32(11	32(11	NUM
ajst-5348	148	28	):	):	PUNCT
ajst-5348	148	29	7139	7139	NUM
ajst-5348	148	30	-	-	SYM
ajst-5348	148	31	7151	7151	NUM
ajst-5348	148	32	.	.	PUNCT
ajst-5348	149	1	[	[	X
ajst-5348	149	2	7	7	X
ajst-5348	149	3	]	]	X
ajst-5348	149	4	robinson	robinson	PROPN
ajst-5348	149	5	j	j	PROPN
ajst-5348	149	6	p	p	PROPN
ajst-5348	149	7	,	,	PUNCT
ajst-5348	149	8	yin	yin	PROPN
ajst-5348	149	9	y	y	PROPN
ajst-5348	149	10	,	,	PUNCT
ajst-5348	149	11	khan	khan	PROPN
ajst-5348	149	12	z	z	PROPN
ajst-5348	149	13	,	,	PUNCT
ajst-5348	149	14	et	et	PROPN
ajst-5348	149	15	al	al	PROPN
ajst-5348	149	16	.	.	PUNCT
ajst-5348	150	1	recognizing	recognize	VERB
ajst-5348	150	2	families	family	NOUN
ajst-5348	150	3	in	in	ADP
ajst-5348	150	4	the	the	DET
ajst-5348	150	5	wild	wild	ADJ
ajst-5348	150	6	(	(	PUNCT
ajst-5348	150	7	rfiw	rfiw	NOUN
ajst-5348	150	8	):	):	PUNCT
ajst-5348	150	9	the	the	DET
ajst-5348	150	10	4th	4th	ADJ
ajst-5348	150	11	edition[c]//2020	edition[c]//2020	PROPN
ajst-5348	150	12	15th	15th	ADJ
ajst-5348	150	13	ieee	ieee	PROPN
ajst-5348	150	14	international	international	ADJ
ajst-5348	150	15	conference	conference	NOUN
ajst-5348	150	16	on	on	ADP
ajst-5348	150	17	automatic	automatic	ADJ
ajst-5348	150	18	face	face	NOUN
ajst-5348	150	19	and	and	CCONJ
ajst-5348	150	20	gesture	gesture	NOUN
ajst-5348	150	21	recognition	recognition	NOUN
ajst-5348	150	22	(	(	PUNCT
ajst-5348	150	23	fg	fg	PROPN
ajst-5348	150	24	2020	2020	NUM
ajst-5348	150	25	)	)	PUNCT
ajst-5348	150	26	.	.	PUNCT
ajst-5348	151	1	ieee	ieee	PROPN
ajst-5348	151	2	,	,	PUNCT
ajst-5348	151	3	2020	2020	NUM
ajst-5348	151	4	:	:	PUNCT
ajst-5348	151	5	857	857	NUM
ajst-5348	151	6	-	-	SYM
ajst-5348	151	7	862	862	NUM
ajst-5348	151	8	.	.	PUNCT
ajst-5348	152	1	[	[	X
ajst-5348	152	2	8	8	NUM
ajst-5348	152	3	]	]	X
ajst-5348	152	4	dahan	dahan	PROPN
ajst-5348	152	5	e	e	PROPN
ajst-5348	152	6	,	,	PUNCT
ajst-5348	152	7	keller	keller	PROPN
ajst-5348	152	8	y.	y.	PROPN
ajst-5348	152	9	a	a	DET
ajst-5348	152	10	unified	unified	ADJ
ajst-5348	152	11	approach	approach	NOUN
ajst-5348	152	12	to	to	ADP
ajst-5348	152	13	kinship	kinship	NOUN
ajst-5348	152	14	verification[j	verification[j	NOUN
ajst-5348	152	15	]	]	PUNCT
ajst-5348	152	16	.	.	PUNCT
ajst-5348	153	1	ieee	ieee	NOUN
ajst-5348	153	2	transactions	transaction	NOUN
ajst-5348	153	3	on	on	ADP
ajst-5348	153	4	pattern	pattern	NOUN
ajst-5348	153	5	analysis	analysis	NOUN
ajst-5348	153	6	and	and	CCONJ
ajst-5348	153	7	machine	machine	NOUN
ajst-5348	153	8	intelligence	intelligence	NOUN
ajst-5348	153	9	,	,	PUNCT
ajst-5348	153	10	2020	2020	NUM
ajst-5348	153	11	,	,	PUNCT
ajst-5348	153	12	43(8	43(8	NUM
ajst-5348	153	13	):	):	PUNCT
ajst-5348	153	14	2851	2851	NUM
ajst-5348	153	15	-	-	SYM
ajst-5348	153	16	2857	2857	NUM
ajst-5348	153	17	.	.	PUNCT
ajst-5348	154	1	[	[	X
ajst-5348	154	2	9	9	NUM
ajst-5348	154	3	]	]	X
ajst-5348	154	4	wang	wang	PROPN
ajst-5348	154	5	w	w	PROPN
ajst-5348	154	6	,	,	PUNCT
ajst-5348	154	7	xie	xie	PROPN
ajst-5348	154	8	e	e	PROPN
ajst-5348	154	9	,	,	PUNCT
ajst-5348	154	10	li	li	PROPN
ajst-5348	154	11	x	x	PROPN
ajst-5348	154	12	,	,	PUNCT
ajst-5348	154	13	et	et	PROPN
ajst-5348	154	14	al	al	PROPN
ajst-5348	154	15	.	.	PROPN
ajst-5348	155	1	pyramid	pyramid	PROPN
ajst-5348	155	2	vision	vision	PROPN
ajst-5348	155	3	transformer	transformer	PROPN
ajst-5348	155	4	:	:	PUNCT
ajst-5348	155	5	a	a	DET
ajst-5348	155	6	versatile	versatile	ADJ
ajst-5348	155	7	backbone	backbone	NOUN
ajst-5348	155	8	for	for	ADP
ajst-5348	155	9	dense	dense	ADJ
ajst-5348	155	10	prediction	prediction	NOUN
ajst-5348	155	11	without	without	ADP
ajst-5348	155	12	convolutions[c]//proceedings	convolutions[c]//proceeding	NOUN
ajst-5348	155	13	of	of	ADP
ajst-5348	155	14	the	the	DET
ajst-5348	155	15	ieee	ieee	NOUN
ajst-5348	155	16	/	/	SYM
ajst-5348	155	17	cvf	cvf	NOUN
ajst-5348	155	18	international	international	ADJ
ajst-5348	155	19	conference	conference	NOUN
ajst-5348	155	20	on	on	ADP
ajst-5348	155	21	computer	computer	NOUN
ajst-5348	155	22	vision	vision	NOUN
ajst-5348	155	23	.	.	PUNCT
ajst-5348	156	1	2021	2021	NUM
ajst-5348	156	2	:	:	PUNCT
ajst-5348	157	1	568	568	NUM
ajst-5348	157	2	-	-	SYM
ajst-5348	157	3	578	578	NUM
ajst-5348	157	4	.	.	PUNCT
ajst-5348	158	1	[	[	X
ajst-5348	158	2	10	10	NUM
ajst-5348	158	3	]	]	PUNCT
ajst-5348	158	4	he	he	PRON
ajst-5348	158	5	k	k	PROPN
ajst-5348	158	6	,	,	PUNCT
ajst-5348	158	7	zhang	zhang	PROPN
ajst-5348	158	8	x	x	PROPN
ajst-5348	158	9	,	,	PUNCT
ajst-5348	158	10	ren	ren	PROPN
ajst-5348	158	11	s	s	PROPN
ajst-5348	158	12	,	,	PUNCT
ajst-5348	158	13	et	et	PROPN
ajst-5348	158	14	al	al	PROPN
ajst-5348	158	15	.	.	PUNCT
ajst-5348	159	1	deep	deep	ADJ
ajst-5348	159	2	residual	residual	ADJ
ajst-5348	159	3	learning	learning	NOUN
ajst-5348	159	4	for	for	ADP
ajst-5348	159	5	image	image	NOUN
ajst-5348	159	6	recognition[c]//proceedings	recognition[c]//proceeding	NOUN
ajst-5348	159	7	of	of	ADP
ajst-5348	159	8	the	the	DET
ajst-5348	159	9	ieee	ieee	NOUN
ajst-5348	159	10	conference	conference	NOUN
ajst-5348	159	11	on	on	ADP
ajst-5348	159	12	computer	computer	NOUN
ajst-5348	159	13	vision	vision	NOUN
ajst-5348	159	14	and	and	CCONJ
ajst-5348	159	15	pattern	pattern	NOUN
ajst-5348	159	16	recognition	recognition	NOUN
ajst-5348	159	17	.	.	PUNCT
ajst-5348	160	1	2016	2016	NUM
ajst-5348	160	2	:	:	PUNCT
ajst-5348	161	1	770	770	NUM
ajst-5348	161	2	-	-	SYM
ajst-5348	161	3	778	778	NUM
ajst-5348	161	4	.	.	PUNCT
ajst-5348	162	1	[	[	X
ajst-5348	162	2	11	11	NUM
ajst-5348	162	3	]	]	ADJ
ajst-5348	162	4	dosovitskiy	dosovitskiy	NOUN
ajst-5348	162	5	a	a	PRON
ajst-5348	162	6	,	,	PUNCT
ajst-5348	162	7	beyer	beyer	PROPN
ajst-5348	162	8	l	l	PROPN
ajst-5348	162	9	,	,	PUNCT
ajst-5348	162	10	kolesnikov	kolesnikov	PROPN
ajst-5348	162	11	a	a	PROPN
ajst-5348	162	12	,	,	PUNCT
ajst-5348	162	13	et	et	PROPN
ajst-5348	162	14	al	al	PROPN
ajst-5348	162	15	.	.	PUNCT
ajst-5348	163	1	an	an	DET
ajst-5348	163	2	image	image	NOUN
ajst-5348	163	3	is	be	AUX
ajst-5348	163	4	worth	worth	ADJ
ajst-5348	163	5	16x16	16x16	NUM
ajst-5348	163	6	words	word	NOUN
ajst-5348	163	7	:	:	PUNCT
ajst-5348	163	8	transformers	transformer	NOUN
ajst-5348	163	9	for	for	ADP
ajst-5348	163	10	image	image	NOUN
ajst-5348	163	11	recognition	recognition	NOUN
ajst-5348	163	12	at	at	ADP
ajst-5348	163	13	scale[j	scale[j	NOUN
ajst-5348	163	14	]	]	PUNCT
ajst-5348	163	15	.	.	PUNCT
ajst-5348	164	1	arxiv	arxiv	PROPN
ajst-5348	164	2	preprint	preprint	VERB
ajst-5348	164	3	arxiv:2010.11929	arxiv:2010.11929	NOUN
ajst-5348	164	4	,	,	PUNCT
ajst-5348	164	5	2020	2020	NUM
ajst-5348	164	6	.	.	PUNCT
ajst-5348	165	1	[	[	X
ajst-5348	165	2	12	12	NUM
ajst-5348	165	3	]	]	X
ajst-5348	165	4	deng	deng	PROPN
ajst-5348	165	5	j	j	PROPN
ajst-5348	165	6	,	,	PUNCT
ajst-5348	165	7	dong	dong	PROPN
ajst-5348	165	8	w	w	PROPN
ajst-5348	165	9	,	,	PUNCT
ajst-5348	165	10	socher	socher	NOUN
ajst-5348	165	11	r	r	NOUN
ajst-5348	165	12	,	,	PUNCT
ajst-5348	165	13	et	et	PROPN
ajst-5348	165	14	al	al	PROPN
ajst-5348	165	15	.	.	PROPN
ajst-5348	165	16	imagenet	imagenet	PROPN
ajst-5348	165	17	:	:	PUNCT
ajst-5348	165	18	a	a	DET
ajst-5348	165	19	large	large	ADJ
ajst-5348	165	20	-	-	PUNCT
ajst-5348	165	21	scale	scale	NOUN
ajst-5348	165	22	hierarchical	hierarchical	ADJ
ajst-5348	165	23	image	image	NOUN
ajst-5348	165	24	database[c]//2009	database[c]//2009	PROPN
ajst-5348	165	25	ieee	ieee	NOUN
ajst-5348	165	26	conference	conference	NOUN
ajst-5348	165	27	on	on	ADP
ajst-5348	165	28	computer	computer	NOUN
ajst-5348	165	29	vision	vision	NOUN
ajst-5348	165	30	and	and	CCONJ
ajst-5348	165	31	pattern	pattern	NOUN
ajst-5348	165	32	recognition	recognition	NOUN
ajst-5348	165	33	.	.	PUNCT
ajst-5348	166	1	ieee	ieee	PROPN
ajst-5348	166	2	,	,	PUNCT
ajst-5348	166	3	2009	2009	NUM
ajst-5348	166	4	:	:	PUNCT
ajst-5348	166	5	248	248	NUM
ajst-5348	166	6	-	-	SYM
ajst-5348	166	7	255	255	NUM
ajst-5348	166	8	.	.	PUNCT
ajst-5348	167	1	[	[	X
ajst-5348	167	2	13	13	NUM
ajst-5348	167	3	]	]	SYM
ajst-5348	167	4	de	de	PROPN
ajst-5348	167	5	boer	boer	PROPN
ajst-5348	167	6	p	p	PROPN
ajst-5348	167	7	t	t	PROPN
ajst-5348	167	8	,	,	PUNCT
ajst-5348	167	9	kroese	kroese	NOUN
ajst-5348	167	10	d	d	X
ajst-5348	167	11	p	p	PROPN
ajst-5348	167	12	,	,	PUNCT
ajst-5348	167	13	mannor	mannor	PROPN
ajst-5348	167	14	s	s	PROPN
ajst-5348	167	15	,	,	PUNCT
ajst-5348	167	16	et	et	PROPN
ajst-5348	167	17	al	al	PROPN
ajst-5348	167	18	.	.	PUNCT
ajst-5348	168	1	a	a	DET
ajst-5348	168	2	tutorial	tutorial	NOUN
ajst-5348	168	3	on	on	ADP
ajst-5348	168	4	the	the	DET
ajst-5348	168	5	cross	cross	NOUN
ajst-5348	168	6	-	-	ADJ
ajst-5348	168	7	entropy	entropy	ADJ
ajst-5348	168	8	method[j	method[j	PROPN
ajst-5348	168	9	]	]	PUNCT
ajst-5348	168	10	.	.	PUNCT
ajst-5348	169	1	annals	annal	NOUN
ajst-5348	169	2	of	of	ADP
ajst-5348	169	3	operations	operation	NOUN
ajst-5348	169	4	research	research	NOUN
ajst-5348	169	5	,	,	PUNCT
ajst-5348	169	6	2005	2005	NUM
ajst-5348	169	7	,	,	PUNCT
ajst-5348	169	8	134(1	134(1	NUM
ajst-5348	169	9	):	):	PUNCT
ajst-5348	169	10	19	19	NUM
ajst-5348	169	11	-	-	SYM
ajst-5348	169	12	67	67	NUM
ajst-5348	169	13	.	.	PUNCT
ajst-5348	170	1	[	[	X
ajst-5348	170	2	14	14	NUM
ajst-5348	170	3	]	]	X
ajst-5348	170	4	wen	wen	PROPN
ajst-5348	170	5	y	y	PROPN
ajst-5348	170	6	,	,	PUNCT
ajst-5348	170	7	zhang	zhang	PROPN
ajst-5348	170	8	k	k	PROPN
ajst-5348	170	9	,	,	PUNCT
ajst-5348	170	10	li	li	PROPN
ajst-5348	170	11	z	z	PROPN
ajst-5348	170	12	,	,	PUNCT
ajst-5348	170	13	et	et	PROPN
ajst-5348	170	14	al	al	PROPN
ajst-5348	170	15	.	.	PUNCT
ajst-5348	171	1	a	a	DET
ajst-5348	171	2	discriminative	discriminative	NOUN
ajst-5348	171	3	feature	feature	NOUN
ajst-5348	171	4	learning	learn	VERB
ajst-5348	171	5	approach	approach	NOUN
ajst-5348	171	6	for	for	ADP
ajst-5348	171	7	deep	deep	ADJ
ajst-5348	171	8	face	face	NOUN
ajst-5348	171	9	recognition[c]//european	recognition[c]//european	ADJ
ajst-5348	171	10	conference	conference	NOUN
ajst-5348	171	11	on	on	ADP
ajst-5348	171	12	computer	computer	NOUN
ajst-5348	171	13	vision	vision	NOUN
ajst-5348	171	14	.	.	PUNCT
ajst-5348	172	1	springer	springer	NOUN
ajst-5348	172	2	,	,	PUNCT
ajst-5348	172	3	cham	cham	PROPN
ajst-5348	172	4	,	,	PUNCT
ajst-5348	172	5	2016	2016	NUM
ajst-5348	172	6	:	:	PUNCT
ajst-5348	172	7	499	499	NUM
ajst-5348	172	8	-	-	SYM
ajst-5348	172	9	515	515	NUM
ajst-5348	172	10	.	.	PUNCT
ajst-5348	173	1	[	[	X
ajst-5348	173	2	15	15	NUM
ajst-5348	173	3	]	]	X
ajst-5348	173	4	robinson	robinson	PROPN
ajst-5348	173	5	j	j	PROPN
ajst-5348	173	6	p	p	PROPN
ajst-5348	173	7	,	,	PUNCT
ajst-5348	173	8	shao	shao	PROPN
ajst-5348	173	9	m	m	PROPN
ajst-5348	173	10	,	,	PUNCT
ajst-5348	173	11	wu	wu	PROPN
ajst-5348	173	12	y	y	PROPN
ajst-5348	173	13	,	,	PUNCT
ajst-5348	173	14	et	et	PROPN
ajst-5348	173	15	al	al	PROPN
ajst-5348	173	16	.	.	PROPN
ajst-5348	173	17	visual	visual	ADJ
ajst-5348	173	18	kinship	kinship	NOUN
ajst-5348	173	19	recognition	recognition	NOUN
ajst-5348	173	20	of	of	ADP
ajst-5348	173	21	families	family	NOUN
ajst-5348	173	22	in	in	ADP
ajst-5348	173	23	the	the	DET
ajst-5348	173	24	wild[j	wild[j	NOUN
ajst-5348	173	25	]	]	PUNCT
ajst-5348	173	26	.	.	PUNCT
ajst-5348	174	1	ieee	ieee	NOUN
ajst-5348	174	2	transactions	transaction	NOUN
ajst-5348	174	3	on	on	ADP
ajst-5348	174	4	pattern	pattern	NOUN
ajst-5348	174	5	analysis	analysis	NOUN
ajst-5348	174	6	and	and	CCONJ
ajst-5348	174	7	machine	machine	NOUN
ajst-5348	174	8	intelligence	intelligence	NOUN
ajst-5348	174	9	,	,	PUNCT
ajst-5348	174	10	2018	2018	NUM
ajst-5348	174	11	,	,	PUNCT
ajst-5348	174	12	40(11	40(11	NUM
ajst-5348	174	13	):	):	PUNCT
ajst-5348	174	14	2624	2624	NUM
ajst-5348	174	15	-	-	SYM
ajst-5348	174	16	2637	2637	NUM
ajst-5348	174	17	.	.	PUNCT