id	sid	tid	token	lemma	pos
fcis-31244	1	1	frontiers	frontier	NOUN
fcis-31244	1	2	in	in	ADP
fcis-31244	1	3	computing	computing	NOUN
fcis-31244	1	4	and	and	CCONJ
fcis-31244	1	5	intelligent	intelligent	ADJ
fcis-31244	1	6	systems	system	NOUN
fcis-31244	1	7	issn	issn	VERB
fcis-31244	1	8	:	:	PUNCT
fcis-31244	1	9	2832	2832	NUM
fcis-31244	1	10	-	-	SYM
fcis-31244	1	11	6024	6024	NUM
fcis-31244	1	12	|	|	NOUN
fcis-31244	1	13	vol	vol	NOUN
fcis-31244	1	14	.	.	PROPN
fcis-31244	2	1	12	12	NUM
fcis-31244	2	2	,	,	PUNCT
fcis-31244	2	3	no	no	INTJ
fcis-31244	2	4	.	.	NOUN
fcis-31244	2	5	3	3	NUM
fcis-31244	2	6	,	,	PUNCT
fcis-31244	2	7	2025	2025	NUM
fcis-31244	2	8	73	73	NUM
fcis-31244	2	9	lightweight	lightweight	ADJ
fcis-31244	2	10	dynamic	dynamic	ADJ
fcis-31244	2	11	gesture	gesture	NOUN
fcis-31244	2	12	recognition	recognition	NOUN
fcis-31244	2	13	based	base	VERB
fcis-31244	2	14	on	on	ADP
fcis-31244	2	15	shufflenetv2‐mamba	shufflenetv2‐mamba	NOUN
fcis-31244	2	16	hybrid	hybrid	ADJ
fcis-31244	2	17	architecture	architecture	NOUN
fcis-31244	2	18	jiaxuan	jiaxuan	PROPN
fcis-31244	2	19	chai	chai	NOUN
fcis-31244	2	20	,	,	PUNCT
fcis-31244	2	21	mingge	mingge	NOUN
fcis-31244	2	22	sun	sun	PROPN
fcis-31244	2	23	*	*	PROPN
fcis-31244	2	24	,	,	PUNCT
fcis-31244	2	25	dongxuan	dongxuan	PROPN
fcis-31244	2	26	huang	huang	PROPN
fcis-31244	2	27	,	,	PUNCT
fcis-31244	2	28	sen	sen	PROPN
fcis-31244	2	29	ye	ye	PROPN
fcis-31244	2	30	school	school	NOUN
fcis-31244	2	31	of	of	ADP
fcis-31244	2	32	information	information	NOUN
fcis-31244	2	33	and	and	CCONJ
fcis-31244	2	34	control	control	PROPN
fcis-31244	2	35	engineering	engineering	PROPN
fcis-31244	2	36	,	,	PUNCT
fcis-31244	2	37	jilin	jilin	PROPN
fcis-31244	2	38	institute	institute	PROPN
fcis-31244	2	39	of	of	ADP
fcis-31244	2	40	chemical	chemical	PROPN
fcis-31244	2	41	technology	technology	PROPN
fcis-31244	2	42	,	,	PUNCT
fcis-31244	2	43	jilin	jilin	PROPN
fcis-31244	2	44	,	,	PUNCT
fcis-31244	2	45	jilin	jilin	PROPN
fcis-31244	2	46	132022	132022	NUM
fcis-31244	2	47	,	,	PUNCT
fcis-31244	2	48	china	china	PROPN
fcis-31244	2	49	*	*	PUNCT
fcis-31244	2	50	corresponding	correspond	VERB
fcis-31244	2	51	author	author	NOUN
fcis-31244	2	52	:	:	PUNCT
fcis-31244	2	53	mingge	mingge	NOUN
fcis-31244	2	54	sun	sun	PROPN
fcis-31244	2	55	abstract	abstract	NOUN
fcis-31244	2	56	:	:	PUNCT
fcis-31244	2	57	dynamic	dynamic	ADJ
fcis-31244	2	58	gesture	gesture	NOUN
fcis-31244	2	59	recognition	recognition	NOUN
fcis-31244	2	60	has	have	VERB
fcis-31244	2	61	important	important	ADJ
fcis-31244	2	62	application	application	NOUN
fcis-31244	2	63	value	value	NOUN
fcis-31244	2	64	in	in	ADP
fcis-31244	2	65	human	human	ADJ
fcis-31244	2	66	-	-	PUNCT
fcis-31244	2	67	computer	computer	NOUN
fcis-31244	2	68	interaction	interaction	NOUN
fcis-31244	2	69	of	of	ADP
fcis-31244	2	70	mobile	mobile	ADJ
fcis-31244	2	71	terminal	terminal	NOUN
fcis-31244	2	72	,	,	PUNCT
fcis-31244	2	73	but	but	CCONJ
fcis-31244	2	74	the	the	DET
fcis-31244	2	75	existing	exist	VERB
fcis-31244	2	76	methods	method	NOUN
fcis-31244	2	77	generally	generally	ADV
fcis-31244	2	78	face	face	VERB
fcis-31244	2	79	the	the	DET
fcis-31244	2	80	problems	problem	NOUN
fcis-31244	2	81	of	of	ADP
fcis-31244	2	82	high	high	ADJ
fcis-31244	2	83	computational	computational	ADJ
fcis-31244	2	84	complexity	complexity	NOUN
fcis-31244	2	85	and	and	CCONJ
fcis-31244	2	86	insufficient	insufficient	ADJ
fcis-31244	2	87	time	time	NOUN
fcis-31244	2	88	sequence	sequence	NOUN
fcis-31244	2	89	modeling	modeling	NOUN
fcis-31244	2	90	ability	ability	NOUN
fcis-31244	2	91	.	.	PUNCT
fcis-31244	3	1	therefore	therefore	ADV
fcis-31244	3	2	,	,	PUNCT
fcis-31244	3	3	this	this	DET
fcis-31244	3	4	paper	paper	NOUN
fcis-31244	3	5	proposes	propose	VERB
fcis-31244	3	6	a	a	DET
fcis-31244	3	7	lightweight	lightweight	ADJ
fcis-31244	3	8	dynamic	dynamic	ADJ
fcis-31244	3	9	gesture	gesture	NOUN
fcis-31244	3	10	recognition	recognition	NOUN
fcis-31244	3	11	model	model	NOUN
fcis-31244	3	12	based	base	VERB
fcis-31244	3	13	on	on	ADP
fcis-31244	3	14	shufflenetv2	shufflenetv2	PROPN
fcis-31244	3	15	mamba	mamba	PROPN
fcis-31244	3	16	(	(	PUNCT
fcis-31244	3	17	shuma	shuma	PROPN
fcis-31244	3	18	)	)	PUNCT
fcis-31244	3	19	hybrid	hybrid	ADJ
fcis-31244	3	20	architecture	architecture	NOUN
fcis-31244	3	21	.	.	PUNCT
fcis-31244	4	1	in	in	ADP
fcis-31244	4	2	this	this	DET
fcis-31244	4	3	model	model	NOUN
fcis-31244	4	4	,	,	PUNCT
fcis-31244	4	5	mamba	mamba	PROPN
fcis-31244	4	6	's	's	PART
fcis-31244	4	7	state	state	NOUN
fcis-31244	4	8	space	space	NOUN
fcis-31244	4	9	sequence	sequence	NOUN
fcis-31244	4	10	modeling	modeling	NOUN
fcis-31244	4	11	module	module	NOUN
fcis-31244	4	12	is	be	AUX
fcis-31244	4	13	embedded	embed	VERB
fcis-31244	4	14	into	into	ADP
fcis-31244	4	15	the	the	DET
fcis-31244	4	16	shufflenetv2	shufflenetv2	NOUN
fcis-31244	4	17	backbone	backbone	NOUN
fcis-31244	4	18	network	network	NOUN
fcis-31244	4	19	to	to	PART
fcis-31244	4	20	achieve	achieve	VERB
fcis-31244	4	21	efficient	efficient	ADJ
fcis-31244	4	22	spatio	spatio	ADJ
fcis-31244	4	23	-	-	PUNCT
fcis-31244	4	24	temporal	temporal	ADJ
fcis-31244	4	25	feature	feature	NOUN
fcis-31244	4	26	fusion	fusion	NOUN
fcis-31244	4	27	.	.	PUNCT
fcis-31244	5	1	first	first	ADV
fcis-31244	5	2	,	,	PUNCT
fcis-31244	5	3	part	part	NOUN
fcis-31244	5	4	of	of	ADP
fcis-31244	5	5	the	the	DET
fcis-31244	5	6	convolution	convolution	NOUN
fcis-31244	5	7	operation	operation	NOUN
fcis-31244	5	8	is	be	AUX
fcis-31244	5	9	replaced	replace	VERB
fcis-31244	5	10	in	in	ADP
fcis-31244	5	11	the	the	DET
fcis-31244	5	12	downsampling	downsample	VERB
fcis-31244	5	13	bottleneck	bottleneck	NOUN
fcis-31244	5	14	layer	layer	NOUN
fcis-31244	5	15	of	of	ADP
fcis-31244	5	16	shufflenetv2	shufflenetv2	NOUN
fcis-31244	5	17	,	,	PUNCT
fcis-31244	5	18	and	and	CCONJ
fcis-31244	5	19	mamba	mamba	NOUN
fcis-31244	5	20	's	's	PART
fcis-31244	5	21	linear	linear	ADJ
fcis-31244	5	22	complexity	complexity	NOUN
fcis-31244	5	23	is	be	AUX
fcis-31244	5	24	used	use	VERB
fcis-31244	5	25	to	to	PART
fcis-31244	5	26	capture	capture	VERB
fcis-31244	5	27	the	the	DET
fcis-31244	5	28	long	long	ADJ
fcis-31244	5	29	-	-	PUNCT
fcis-31244	5	30	range	range	NOUN
fcis-31244	5	31	dependence	dependence	NOUN
fcis-31244	5	32	between	between	ADP
fcis-31244	5	33	video	video	NOUN
fcis-31244	5	34	frames	frame	NOUN
fcis-31244	5	35	;	;	PUNCT
fcis-31244	5	36	secondly	secondly	ADV
fcis-31244	5	37	,	,	PUNCT
fcis-31244	5	38	a	a	DET
fcis-31244	5	39	multi	multi	ADJ
fcis-31244	5	40	-	-	ADJ
fcis-31244	5	41	scale	scale	ADJ
fcis-31244	5	42	feature	feature	NOUN
fcis-31244	5	43	dynamic	dynamic	ADJ
fcis-31244	5	44	fusion	fusion	NOUN
fcis-31244	5	45	mechanism	mechanism	NOUN
fcis-31244	5	46	is	be	AUX
fcis-31244	5	47	designed	design	VERB
fcis-31244	5	48	,	,	PUNCT
fcis-31244	5	49	which	which	PRON
fcis-31244	5	50	combines	combine	VERB
fcis-31244	5	51	channel	channel	NOUN
fcis-31244	5	52	shuffle	shuffle	NOUN
fcis-31244	5	53	and	and	CCONJ
fcis-31244	5	54	cross	cross	VERB
fcis-31244	5	55	layer	layer	NOUN
fcis-31244	5	56	feature	feature	NOUN
fcis-31244	5	57	stitching	stitch	VERB
fcis-31244	5	58	to	to	PART
fcis-31244	5	59	enhance	enhance	VERB
fcis-31244	5	60	the	the	DET
fcis-31244	5	61	collaborative	collaborative	ADJ
fcis-31244	5	62	representation	representation	NOUN
fcis-31244	5	63	ability	ability	NOUN
fcis-31244	5	64	of	of	ADP
fcis-31244	5	65	local	local	ADJ
fcis-31244	5	66	details	detail	NOUN
fcis-31244	5	67	and	and	CCONJ
fcis-31244	5	68	global	global	ADJ
fcis-31244	5	69	motion	motion	NOUN
fcis-31244	5	70	patterns	pattern	NOUN
fcis-31244	5	71	of	of	ADP
fcis-31244	5	72	continuous	continuous	ADJ
fcis-31244	5	73	gestures	gesture	NOUN
fcis-31244	5	74	.	.	PUNCT
fcis-31244	6	1	in	in	ADP
fcis-31244	6	2	order	order	NOUN
fcis-31244	6	3	to	to	PART
fcis-31244	6	4	further	far	ADV
fcis-31244	6	5	optimize	optimize	VERB
fcis-31244	6	6	the	the	DET
fcis-31244	6	7	deployment	deployment	NOUN
fcis-31244	6	8	efficiency	efficiency	NOUN
fcis-31244	6	9	,	,	PUNCT
fcis-31244	6	10	layered	layered	ADJ
fcis-31244	6	11	quantization	quantization	NOUN
fcis-31244	6	12	and	and	CCONJ
fcis-31244	6	13	structured	structured	ADJ
fcis-31244	6	14	pruning	pruning	NOUN
fcis-31244	6	15	technology	technology	NOUN
fcis-31244	6	16	are	be	AUX
fcis-31244	6	17	introduced	introduce	VERB
fcis-31244	6	18	to	to	PART
fcis-31244	6	19	compress	compress	VERB
fcis-31244	6	20	the	the	DET
fcis-31244	6	21	model	model	NOUN
fcis-31244	6	22	parameters	parameter	NOUN
fcis-31244	6	23	to	to	ADP
fcis-31244	6	24	2.1	2.1	NUM
fcis-31244	6	25	mb	mb	NOUN
fcis-31244	6	26	.	.	PUNCT
fcis-31244	7	1	experiments	experiment	NOUN
fcis-31244	7	2	on	on	ADP
fcis-31244	7	3	a	a	DET
fcis-31244	7	4	specific	specific	ADJ
fcis-31244	7	5	dynamic	dynamic	ADJ
fcis-31244	7	6	gesture	gesture	NOUN
fcis-31244	7	7	data	datum	NOUN
fcis-31244	7	8	set	set	VERB
fcis-31244	7	9	including	include	VERB
fcis-31244	7	10	first	first	ADJ
fcis-31244	7	11	person	person	NOUN
fcis-31244	7	12	and	and	CCONJ
fcis-31244	7	13	home	home	NOUN
fcis-31244	7	14	monitoring	monitoring	NOUN
fcis-31244	7	15	show	show	VERB
fcis-31244	7	16	that	that	SCONJ
fcis-31244	7	17	the	the	DET
fcis-31244	7	18	accuracy	accuracy	NOUN
fcis-31244	7	19	of	of	ADP
fcis-31244	7	20	gesture	gesture	NOUN
fcis-31244	7	21	classification	classification	NOUN
fcis-31244	7	22	is	be	AUX
fcis-31244	7	23	89.7	89.7	NUM
fcis-31244	7	24	%	%	NOUN
fcis-31244	7	25	,	,	PUNCT
fcis-31244	7	26	which	which	PRON
fcis-31244	7	27	reduces	reduce	VERB
fcis-31244	7	28	the	the	DET
fcis-31244	7	29	computational	computational	ADJ
fcis-31244	7	30	overhead	overhead	NOUN
fcis-31244	7	31	by	by	ADP
fcis-31244	7	32	about	about	ADV
fcis-31244	7	33	43.6	43.6	NUM
fcis-31244	7	34	%	%	NOUN
fcis-31244	7	35	compared	compare	VERB
fcis-31244	7	36	with	with	ADP
fcis-31244	7	37	the	the	DET
fcis-31244	7	38	traditional	traditional	ADJ
fcis-31244	7	39	3d	3d	NUM
fcis-31244	7	40	-	-	PUNCT
fcis-31244	7	41	cnn	cnn	PROPN
fcis-31244	7	42	and	and	CCONJ
fcis-31244	7	43	cnn	cnn	PROPN
fcis-31244	7	44	-	-	PUNCT
fcis-31244	7	45	lstm	lstm	ADJ
fcis-31244	7	46	models	model	NOUN
fcis-31244	7	47	.	.	PUNCT
fcis-31244	8	1	this	this	DET
fcis-31244	8	2	study	study	NOUN
fcis-31244	8	3	provides	provide	VERB
fcis-31244	8	4	an	an	DET
fcis-31244	8	5	efficient	efficient	ADJ
fcis-31244	8	6	solution	solution	NOUN
fcis-31244	8	7	for	for	ADP
fcis-31244	8	8	real	real	ADJ
fcis-31244	8	9	-	-	PUNCT
fcis-31244	8	10	time	time	NOUN
fcis-31244	8	11	dynamic	dynamic	ADJ
fcis-31244	8	12	gesture	gesture	NOUN
fcis-31244	8	13	interaction	interaction	NOUN
fcis-31244	8	14	in	in	ADP
fcis-31244	8	15	resource	resource	NOUN
fcis-31244	8	16	constrained	constrain	VERB
fcis-31244	8	17	scenes	scene	NOUN
fcis-31244	8	18	,	,	PUNCT
fcis-31244	8	19	and	and	CCONJ
fcis-31244	8	20	verifies	verify	VERB
fcis-31244	8	21	the	the	DET
fcis-31244	8	22	effectiveness	effectiveness	NOUN
fcis-31244	8	23	of	of	ADP
fcis-31244	8	24	the	the	DET
fcis-31244	8	25	fusion	fusion	NOUN
fcis-31244	8	26	of	of	ADP
fcis-31244	8	27	lightweight	lightweight	ADJ
fcis-31244	8	28	convolution	convolution	NOUN
fcis-31244	8	29	and	and	CCONJ
fcis-31244	8	30	sequential	sequential	ADJ
fcis-31244	8	31	state	state	NOUN
fcis-31244	8	32	space	space	NOUN
fcis-31244	8	33	model	model	NOUN
fcis-31244	8	34	.	.	PUNCT
fcis-31244	9	1	keywords	keyword	NOUN
fcis-31244	9	2	:	:	PUNCT
fcis-31244	9	3	dynamic	dynamic	ADJ
fcis-31244	9	4	gesture	gesture	NOUN
fcis-31244	9	5	recognition	recognition	NOUN
fcis-31244	9	6	;	;	PUNCT
fcis-31244	9	7	lightweight	lightweight	ADJ
fcis-31244	9	8	model	model	NOUN
fcis-31244	9	9	;	;	PUNCT
fcis-31244	9	10	shufflenetv2	shufflenetv2	NOUN
fcis-31244	9	11	;	;	PUNCT
fcis-31244	9	12	mamba	mamba	PROPN
fcis-31244	9	13	;	;	PUNCT
fcis-31244	9	14	spatio	spatio	PROPN
fcis-31244	9	15	temporal	temporal	ADJ
fcis-31244	9	16	feature	feature	NOUN
fcis-31244	9	17	fusion	fusion	NOUN
fcis-31244	9	18	.	.	PUNCT
fcis-31244	10	1	1	1	X
fcis-31244	10	2	.	.	X
fcis-31244	10	3	introduction	introduction	NOUN
fcis-31244	10	4	in	in	ADP
fcis-31244	10	5	recent	recent	ADJ
fcis-31244	10	6	years	year	NOUN
fcis-31244	10	7	,	,	PUNCT
fcis-31244	10	8	with	with	ADP
fcis-31244	10	9	the	the	DET
fcis-31244	10	10	rapid	rapid	ADJ
fcis-31244	10	11	development	development	NOUN
fcis-31244	10	12	of	of	ADP
fcis-31244	10	13	augmented	augment	VERB
fcis-31244	10	14	reality	reality	NOUN
fcis-31244	10	15	(	(	PUNCT
fcis-31244	10	16	ar	ar	NOUN
fcis-31244	10	17	)	)	PUNCT
fcis-31244	10	18	,	,	PUNCT
fcis-31244	10	19	intelligent	intelligent	ADJ
fcis-31244	10	20	wearable	wearable	ADJ
fcis-31244	10	21	devices	device	NOUN
fcis-31244	10	22	and	and	CCONJ
fcis-31244	10	23	humancomputer	humancomputer	NOUN
fcis-31244	10	24	interaction	interaction	NOUN
fcis-31244	10	25	technology	technology	NOUN
fcis-31244	10	26	,	,	PUNCT
fcis-31244	10	27	dynamic	dynamic	ADJ
fcis-31244	10	28	gesture	gesture	NOUN
fcis-31244	10	29	recognition	recognition	NOUN
fcis-31244	10	30	,	,	PUNCT
fcis-31244	10	31	as	as	ADP
fcis-31244	10	32	one	one	NUM
fcis-31244	10	33	of	of	ADP
fcis-31244	10	34	the	the	DET
fcis-31244	10	35	core	core	NOUN
fcis-31244	10	36	technologies	technology	NOUN
fcis-31244	10	37	of	of	ADP
fcis-31244	10	38	natural	natural	ADJ
fcis-31244	10	39	interaction	interaction	NOUN
fcis-31244	10	40	,	,	PUNCT
fcis-31244	10	41	has	have	AUX
fcis-31244	10	42	gradually	gradually	ADV
fcis-31244	10	43	become	become	VERB
fcis-31244	10	44	a	a	DET
fcis-31244	10	45	research	research	NOUN
fcis-31244	10	46	hotspot	hotspot	NOUN
fcis-31244	10	47	in	in	ADP
fcis-31244	10	48	the	the	DET
fcis-31244	10	49	field	field	NOUN
fcis-31244	10	50	of	of	ADP
fcis-31244	10	51	computer	computer	NOUN
fcis-31244	10	52	vision[1	vision[1	PROPN
fcis-31244	10	53	]	]	PUNCT
fcis-31244	10	54	.	.	PUNCT
fcis-31244	11	1	by	by	ADP
fcis-31244	11	2	recognizing	recognize	VERB
fcis-31244	11	3	the	the	DET
fcis-31244	11	4	trajectory	trajectory	NOUN
fcis-31244	11	5	and	and	CCONJ
fcis-31244	11	6	posture	posture	NOUN
fcis-31244	11	7	changes	change	NOUN
fcis-31244	11	8	of	of	ADP
fcis-31244	11	9	the	the	DET
fcis-31244	11	10	hand	hand	NOUN
fcis-31244	11	11	,	,	PUNCT
fcis-31244	11	12	the	the	DET
fcis-31244	11	13	system	system	NOUN
fcis-31244	11	14	can	can	AUX
fcis-31244	11	15	analyze	analyze	VERB
fcis-31244	11	16	the	the	DET
fcis-31244	11	17	user	user	NOUN
fcis-31244	11	18	's	's	PART
fcis-31244	11	19	intention	intention	NOUN
fcis-31244	11	20	in	in	ADP
fcis-31244	11	21	real	real	ADJ
fcis-31244	11	22	time	time	NOUN
fcis-31244	11	23	,	,	PUNCT
fcis-31244	11	24	and	and	CCONJ
fcis-31244	11	25	plays	play	VERB
fcis-31244	11	26	an	an	DET
fcis-31244	11	27	important	important	ADJ
fcis-31244	11	28	role	role	NOUN
fcis-31244	11	29	in	in	ADP
fcis-31244	11	30	virtual	virtual	ADJ
fcis-31244	11	31	reality	reality	NOUN
fcis-31244	11	32	control	control	NOUN
fcis-31244	11	33	,	,	PUNCT
fcis-31244	11	34	smart	smart	ADJ
fcis-31244	11	35	home	home	NOUN
fcis-31244	11	36	control	control	NOUN
fcis-31244	11	37	,	,	PUNCT
fcis-31244	11	38	barrier	barrier	NOUN
fcis-31244	11	39	free	free	ADJ
fcis-31244	11	40	communication	communication	NOUN
fcis-31244	11	41	and	and	CCONJ
fcis-31244	11	42	other	other	ADJ
fcis-31244	11	43	scenes	scene	NOUN
fcis-31244	11	44	.	.	PUNCT
fcis-31244	12	1	however	however	ADV
fcis-31244	12	2	,	,	PUNCT
fcis-31244	12	3	dynamic	dynamic	ADJ
fcis-31244	12	4	gesture	gesture	NOUN
fcis-31244	12	5	recognition	recognition	NOUN
fcis-31244	12	6	faces	face	VERB
fcis-31244	12	7	two	two	NUM
fcis-31244	12	8	core	core	NOUN
fcis-31244	12	9	challenges	challenge	NOUN
fcis-31244	12	10	:	:	PUNCT
fcis-31244	12	11	first	first	X
fcis-31244	12	12	,	,	PUNCT
fcis-31244	12	13	gesture	gesture	NOUN
fcis-31244	12	14	movements	movement	NOUN
fcis-31244	12	15	are	be	AUX
fcis-31244	12	16	highly	highly	ADV
fcis-31244	12	17	time	time	NOUN
fcis-31244	12	18	-	-	PUNCT
fcis-31244	12	19	space	space	NOUN
fcis-31244	12	20	dependent[2	dependent[2	NOUN
fcis-31244	12	21	]	]	X
fcis-31244	12	22	,	,	PUNCT
fcis-31244	12	23	and	and	CCONJ
fcis-31244	12	24	it	it	PRON
fcis-31244	12	25	is	be	AUX
fcis-31244	12	26	necessary	necessary	ADJ
fcis-31244	12	27	to	to	PART
fcis-31244	12	28	capture	capture	VERB
fcis-31244	12	29	local	local	ADJ
fcis-31244	12	30	details	detail	NOUN
fcis-31244	12	31	(	(	PUNCT
fcis-31244	12	32	such	such	ADJ
fcis-31244	12	33	as	as	ADP
fcis-31244	12	34	finger	finger	NOUN
fcis-31244	12	35	bending	bend	VERB
fcis-31244	12	36	angle	angle	NOUN
fcis-31244	12	37	)	)	PUNCT
fcis-31244	12	38	and	and	CCONJ
fcis-31244	12	39	global	global	ADJ
fcis-31244	12	40	temporal	temporal	ADJ
fcis-31244	12	41	correlation	correlation	NOUN
fcis-31244	12	42	(	(	PUNCT
fcis-31244	12	43	such	such	ADJ
fcis-31244	12	44	as	as	ADP
fcis-31244	12	45	continuous	continuous	ADJ
fcis-31244	12	46	frame	frame	NOUN
fcis-31244	12	47	motion	motion	NOUN
fcis-31244	12	48	trend)[3	trend)[3	ADV
fcis-31244	12	49	]	]	PUNCT
fcis-31244	12	50	.	.	PUNCT
fcis-31244	13	1	traditional	traditional	ADJ
fcis-31244	13	2	3d	3d	NUM
fcis-31244	13	3	convolutional	convolutional	ADJ
fcis-31244	13	4	network	network	NOUN
fcis-31244	13	5	(	(	PUNCT
fcis-31244	13	6	3d	3d	NOUN
fcis-31244	13	7	-	-	PUNCT
fcis-31244	13	8	cnn	cnn	NOUN
fcis-31244	13	9	)	)	PUNCT
fcis-31244	13	10	and	and	CCONJ
fcis-31244	13	11	recurrent	recurrent	ADJ
fcis-31244	13	12	neural	neural	ADJ
fcis-31244	13	13	network	network	NOUN
fcis-31244	13	14	(	(	PUNCT
fcis-31244	13	15	lstm	lstm	PROPN
fcis-31244	13	16	/	/	SYM
fcis-31244	13	17	gru)[4	gru)[4	PROPN
fcis-31244	13	18	]	]	PUNCT
fcis-31244	13	19	are	be	AUX
fcis-31244	13	20	difficult	difficult	ADJ
fcis-31244	13	21	to	to	PART
fcis-31244	13	22	achieve	achieve	VERB
fcis-31244	13	23	efficient	efficient	ADJ
fcis-31244	13	24	reasoning	reasoning	NOUN
fcis-31244	13	25	at	at	ADP
fcis-31244	13	26	the	the	DET
fcis-31244	13	27	mobile	mobile	ADJ
fcis-31244	13	28	terminal	terminal	NOUN
fcis-31244	13	29	due	due	ADP
fcis-31244	13	30	to	to	ADP
fcis-31244	13	31	high	high	ADJ
fcis-31244	13	32	computational	computational	ADJ
fcis-31244	13	33	complexity	complexity	NOUN
fcis-31244	13	34	or	or	CCONJ
fcis-31244	13	35	limited	limited	ADJ
fcis-31244	13	36	long	long	ADJ
fcis-31244	13	37	-	-	PUNCT
fcis-31244	13	38	range	range	NOUN
fcis-31244	13	39	modeling	modeling	NOUN
fcis-31244	13	40	ability	ability	NOUN
fcis-31244	13	41	;	;	PUNCT
fcis-31244	13	42	second	second	X
fcis-31244	13	43	,	,	PUNCT
fcis-31244	13	44	the	the	DET
fcis-31244	13	45	actual	actual	ADJ
fcis-31244	13	46	application	application	NOUN
fcis-31244	13	47	scenario	scenario	NOUN
fcis-31244	13	48	has	have	VERB
fcis-31244	13	49	strict	strict	ADJ
fcis-31244	13	50	requirements	requirement	NOUN
fcis-31244	13	51	on	on	ADP
fcis-31244	13	52	the	the	DET
fcis-31244	13	53	lightweight	lightweight	ADJ
fcis-31244	13	54	and	and	CCONJ
fcis-31244	13	55	deployment	deployment	NOUN
fcis-31244	13	56	efficiency	efficiency	NOUN
fcis-31244	13	57	of	of	ADP
fcis-31244	13	58	the	the	DET
fcis-31244	13	59	model	model	NOUN
fcis-31244	13	60	.	.	PUNCT
fcis-31244	14	1	although	although	SCONJ
fcis-31244	14	2	the	the	DET
fcis-31244	14	3	existing	exist	VERB
fcis-31244	14	4	lightweight	lightweight	ADJ
fcis-31244	14	5	networks	network	NOUN
fcis-31244	14	6	[	[	X
fcis-31244	14	7	5	5	NUM
fcis-31244	14	8	]	]	PUNCT
fcis-31244	14	9	(	(	PUNCT
fcis-31244	14	10	mobilenet	mobilenet	NOUN
fcis-31244	14	11	and	and	CCONJ
fcis-31244	14	12	shufflenetv2	shufflenetv2	NOUN
fcis-31244	14	13	)	)	PUNCT
fcis-31244	14	14	perform	perform	VERB
fcis-31244	14	15	well	well	ADV
fcis-31244	14	16	in	in	ADP
fcis-31244	14	17	still	still	ADV
fcis-31244	14	18	image	image	NOUN
fcis-31244	14	19	classification	classification	NOUN
fcis-31244	14	20	,	,	PUNCT
fcis-31244	14	21	they	they	PRON
fcis-31244	14	22	lack	lack	VERB
fcis-31244	14	23	targeted	target	VERB
fcis-31244	14	24	optimization	optimization	NOUN
fcis-31244	14	25	of	of	ADP
fcis-31244	14	26	temporal	temporal	ADJ
fcis-31244	14	27	dynamic	dynamic	ADJ
fcis-31244	14	28	features	feature	NOUN
fcis-31244	14	29	,	,	PUNCT
fcis-31244	14	30	resulting	result	VERB
fcis-31244	14	31	in	in	ADP
fcis-31244	14	32	insufficient	insufficient	ADJ
fcis-31244	14	33	accuracy	accuracy	NOUN
fcis-31244	14	34	of	of	ADP
fcis-31244	14	35	complex	complex	ADJ
fcis-31244	14	36	gesture	gesture	NOUN
fcis-31244	14	37	recognition	recognition	NOUN
fcis-31244	14	38	.	.	PUNCT
fcis-31244	15	1	to	to	PART
fcis-31244	15	2	solve	solve	VERB
fcis-31244	15	3	the	the	DET
fcis-31244	15	4	above	above	ADJ
fcis-31244	15	5	problems	problem	NOUN
fcis-31244	15	6	,	,	PUNCT
fcis-31244	15	7	researchers	researcher	NOUN
fcis-31244	15	8	have	have	AUX
fcis-31244	15	9	explored	explore	VERB
fcis-31244	15	10	a	a	DET
fcis-31244	15	11	variety	variety	NOUN
fcis-31244	15	12	of	of	ADP
fcis-31244	15	13	improvement	improvement	NOUN
fcis-31244	15	14	directions	direction	NOUN
fcis-31244	15	15	in	in	ADP
fcis-31244	15	16	recent	recent	ADJ
fcis-31244	15	17	years	year	NOUN
fcis-31244	15	18	:	:	PUNCT
fcis-31244	15	19	on	on	ADP
fcis-31244	15	20	the	the	DET
fcis-31244	15	21	one	one	NUM
fcis-31244	15	22	hand	hand	NOUN
fcis-31244	15	23	,	,	PUNCT
fcis-31244	15	24	the	the	DET
fcis-31244	15	25	efficiency	efficiency	NOUN
fcis-31244	15	26	of	of	ADP
fcis-31244	15	27	video	video	NOUN
fcis-31244	15	28	feature	feature	NOUN
fcis-31244	15	29	modeling	modeling	NOUN
fcis-31244	15	30	is	be	AUX
fcis-31244	15	31	optimized	optimize	VERB
fcis-31244	15	32	through	through	ADP
fcis-31244	15	33	spatio	spatio	PROPN
fcis-31244	15	34	-	-	PUNCT
fcis-31244	15	35	temporal	temporal	ADJ
fcis-31244	15	36	separation	separation	NOUN
fcis-31244	15	37	convolution	convolution	NOUN
fcis-31244	15	38	(	(	PUNCT
fcis-31244	15	39	tsm	tsm	NOUN
fcis-31244	15	40	)	)	PUNCT
fcis-31244	16	1	[	[	X
fcis-31244	16	2	5	5	NUM
fcis-31244	16	3	]	]	PUNCT
fcis-31244	16	4	or	or	CCONJ
fcis-31244	16	5	temporal	temporal	ADJ
fcis-31244	16	6	attention	attention	NOUN
fcis-31244	16	7	mechanism	mechanism	NOUN
fcis-31244	16	8	(	(	PUNCT
fcis-31244	16	9	tam	tam	NOUN
fcis-31244	16	10	)	)	PUNCT
fcis-31244	17	1	[	[	X
fcis-31244	17	2	6	6	NUM
fcis-31244	17	3	]	]	PUNCT
fcis-31244	17	4	;	;	PUNCT
fcis-31244	17	5	on	on	ADP
fcis-31244	17	6	the	the	DET
fcis-31244	17	7	other	other	ADJ
fcis-31244	17	8	hand	hand	NOUN
fcis-31244	17	9	,	,	PUNCT
fcis-31244	17	10	with	with	ADP
fcis-31244	17	11	the	the	DET
fcis-31244	17	12	help	help	NOUN
fcis-31244	17	13	of	of	ADP
fcis-31244	17	14	transformer	transformer	NOUN
fcis-31244	17	15	's	's	PART
fcis-31244	17	16	global	global	ADJ
fcis-31244	17	17	self	self	NOUN
fcis-31244	17	18	-	-	PUNCT
fcis-31244	17	19	attention	attention	NOUN
fcis-31244	17	20	,	,	PUNCT
fcis-31244	17	21	the	the	DET
fcis-31244	17	22	ability	ability	NOUN
fcis-31244	17	23	of	of	ADP
fcis-31244	17	24	long	long	ADJ
fcis-31244	17	25	sequence	sequence	NOUN
fcis-31244	17	26	modeling	modeling	NOUN
fcis-31244	17	27	is	be	AUX
fcis-31244	17	28	improved	improve	VERB
fcis-31244	17	29	,	,	PUNCT
fcis-31244	17	30	but	but	CCONJ
fcis-31244	17	31	the	the	DET
fcis-31244	17	32	secondary	secondary	ADJ
fcis-31244	17	33	computational	computational	ADJ
fcis-31244	17	34	complexity	complexity	NOUN
fcis-31244	17	35	still	still	ADV
fcis-31244	17	36	limits	limit	VERB
fcis-31244	17	37	its	its	PRON
fcis-31244	17	38	application	application	NOUN
fcis-31244	17	39	in	in	ADP
fcis-31244	17	40	resource	resource	NOUN
fcis-31244	17	41	constrained	constrain	VERB
fcis-31244	17	42	scenarios	scenario	NOUN
fcis-31244	17	43	.	.	PUNCT
fcis-31244	18	1	at	at	ADP
fcis-31244	18	2	the	the	DET
fcis-31244	18	3	same	same	ADJ
fcis-31244	18	4	time	time	NOUN
fcis-31244	18	5	,	,	PUNCT
fcis-31244	18	6	the	the	DET
fcis-31244	18	7	proposal	proposal	NOUN
fcis-31244	18	8	of	of	ADP
fcis-31244	18	9	state	state	NOUN
fcis-31244	18	10	space	space	NOUN
fcis-31244	18	11	models	model	NOUN
fcis-31244	18	12	(	(	PUNCT
fcis-31244	18	13	ssms	ssm	NOUN
fcis-31244	18	14	)	)	PUNCT
fcis-31244	18	15	,	,	PUNCT
fcis-31244	18	16	especially	especially	ADV
fcis-31244	18	17	mamba	mamba	VERB
fcis-31244	18	18	architecture[8	architecture[8	ADP
fcis-31244	18	19	]	]	X
fcis-31244	18	20	,	,	PUNCT
fcis-31244	18	21	provides	provide	VERB
fcis-31244	18	22	a	a	DET
fcis-31244	18	23	new	new	ADJ
fcis-31244	18	24	idea	idea	NOUN
fcis-31244	18	25	for	for	ADP
fcis-31244	18	26	sequential	sequential	ADJ
fcis-31244	18	27	data	datum	NOUN
fcis-31244	18	28	modeling	modeling	NOUN
fcis-31244	18	29	based	base	VERB
fcis-31244	18	30	on	on	ADP
fcis-31244	18	31	selective	selective	ADJ
fcis-31244	18	32	scanning	scanning	NOUN
fcis-31244	18	33	mechanism	mechanism	NOUN
fcis-31244	18	34	and	and	CCONJ
fcis-31244	18	35	hardware	hardware	NOUN
fcis-31244	18	36	aware	aware	ADJ
fcis-31244	18	37	design	design	NOUN
fcis-31244	18	38	,	,	PUNCT
fcis-31244	18	39	it	it	PRON
fcis-31244	18	40	realizes	realize	VERB
fcis-31244	18	41	long	long	ADJ
fcis-31244	18	42	-	-	PUNCT
fcis-31244	18	43	range	range	NOUN
fcis-31244	18	44	dependent	dependent	ADJ
fcis-31244	18	45	capture	capture	NOUN
fcis-31244	18	46	with	with	ADP
fcis-31244	18	47	linear	linear	PROPN
fcis-31244	18	48	complexity	complexity	NOUN
fcis-31244	18	49	,	,	PUNCT
fcis-31244	18	50	showing	show	VERB
fcis-31244	18	51	significant	significant	ADJ
fcis-31244	18	52	advantages	advantage	NOUN
fcis-31244	18	53	in	in	ADP
fcis-31244	18	54	the	the	DET
fcis-31244	18	55	fields	field	NOUN
fcis-31244	18	56	of	of	ADP
fcis-31244	18	57	language	language	NOUN
fcis-31244	18	58	,	,	PUNCT
fcis-31244	18	59	audio	audio	NOUN
fcis-31244	18	60	and	and	CCONJ
fcis-31244	18	61	so	so	ADV
fcis-31244	18	62	on	on	ADP
fcis-31244	18	63	[	[	PUNCT
fcis-31244	18	64	9	9	NUM
fcis-31244	18	65	]	]	PUNCT
fcis-31244	18	66	.	.	PUNCT
fcis-31244	19	1	however	however	ADV
fcis-31244	19	2	,	,	PUNCT
fcis-31244	19	3	how	how	SCONJ
fcis-31244	19	4	to	to	PART
fcis-31244	19	5	combine	combine	VERB
fcis-31244	19	6	mamba	mamba	PROPN
fcis-31244	19	7	's	's	PART
fcis-31244	19	8	efficient	efficient	ADJ
fcis-31244	19	9	sequence	sequence	NOUN
fcis-31244	19	10	modeling	model	VERB
fcis-31244	19	11	ability	ability	NOUN
fcis-31244	19	12	with	with	ADP
fcis-31244	19	13	lightweight	lightweight	ADJ
fcis-31244	19	14	visual	visual	ADJ
fcis-31244	19	15	network	network	NOUN
fcis-31244	19	16	to	to	PART
fcis-31244	19	17	build	build	VERB
fcis-31244	19	18	a	a	DET
fcis-31244	19	19	dynamic	dynamic	ADJ
fcis-31244	19	20	gesture	gesture	NOUN
fcis-31244	19	21	recognition	recognition	NOUN
fcis-31244	20	1	model[10	model[10	NOUN
fcis-31244	20	2	]	]	PUNCT
fcis-31244	21	1	that	that	PRON
fcis-31244	21	2	takes	take	VERB
fcis-31244	21	3	both	both	DET
fcis-31244	21	4	accuracy	accuracy	NOUN
fcis-31244	21	5	and	and	CCONJ
fcis-31244	21	6	efficiency	efficiency	NOUN
fcis-31244	21	7	into	into	ADP
fcis-31244	21	8	account	account	NOUN
fcis-31244	21	9	is	be	AUX
fcis-31244	21	10	still	still	ADV
fcis-31244	21	11	a	a	DET
fcis-31244	21	12	subject	subject	NOUN
fcis-31244	21	13	to	to	PART
fcis-31244	21	14	be	be	AUX
fcis-31244	21	15	explored	explore	VERB
fcis-31244	21	16	.	.	PUNCT
fcis-31244	22	1	this	this	DET
fcis-31244	22	2	paper	paper	NOUN
fcis-31244	22	3	proposes	propose	VERB
fcis-31244	22	4	a	a	DET
fcis-31244	22	5	lightweight	lightweight	ADJ
fcis-31244	22	6	dynamic	dynamic	ADJ
fcis-31244	22	7	gesture	gesture	NOUN
fcis-31244	22	8	recognition	recognition	NOUN
fcis-31244	22	9	model	model	NOUN
fcis-31244	22	10	based	base	VERB
fcis-31244	22	11	on	on	ADP
fcis-31244	22	12	shufflenetv2	shufflenetv2	PROPN
fcis-31244	22	13	mamba	mamba	PROPN
fcis-31244	22	14	hybrid	hybrid	ADJ
fcis-31244	22	15	architecture	architecture	NOUN
fcis-31244	22	16	.	.	PUNCT
fcis-31244	23	1	the	the	DET
fcis-31244	23	2	core	core	NOUN
fcis-31244	23	3	is	be	AUX
fcis-31244	23	4	to	to	PART
fcis-31244	23	5	propose	propose	VERB
fcis-31244	23	6	a	a	DET
fcis-31244	23	7	modular	modular	ADJ
fcis-31244	23	8	heterogeneous	heterogeneous	ADJ
fcis-31244	23	9	fusion	fusion	NOUN
fcis-31244	23	10	design	design	NOUN
fcis-31244	23	11	:	:	PUNCT
fcis-31244	23	12	embed	embed	VERB
fcis-31244	23	13	mamba	mamba	NOUN
fcis-31244	23	14	blocks	block	NOUN
fcis-31244	23	15	in	in	ADP
fcis-31244	23	16	the	the	DET
fcis-31244	23	17	shufflenetv2	shufflenetv2	NOUN
fcis-31244	23	18	backbone	backbone	NOUN
fcis-31244	23	19	network	network	NOUN
fcis-31244	23	20	,	,	PUNCT
fcis-31244	23	21	use	use	VERB
fcis-31244	23	22	channel	channel	NOUN
fcis-31244	23	23	shuffle	shuffle	NOUN
fcis-31244	23	24	and	and	CCONJ
fcis-31244	23	25	multi	multi	ADJ
fcis-31244	23	26	-	-	ADJ
fcis-31244	23	27	scale	scale	ADJ
fcis-31244	23	28	feature	feature	NOUN
fcis-31244	23	29	fusion	fusion	NOUN
fcis-31244	23	30	mechanism	mechanism	NOUN
fcis-31244	23	31	to	to	PART
fcis-31244	23	32	jointly	jointly	ADV
fcis-31244	23	33	extract	extract	VERB
fcis-31244	23	34	local	local	ADJ
fcis-31244	23	35	spatial	spatial	ADJ
fcis-31244	23	36	features	feature	NOUN
fcis-31244	23	37	and	and	CCONJ
fcis-31244	23	38	global	global	ADJ
fcis-31244	23	39	time	time	NOUN
fcis-31244	23	40	dependence	dependence	NOUN
fcis-31244	23	41	,	,	PUNCT
fcis-31244	23	42	break	break	VERB
fcis-31244	23	43	through	through	ADP
fcis-31244	23	44	the	the	DET
fcis-31244	23	45	modeling	modeling	NOUN
fcis-31244	23	46	bottleneck	bottleneck	NOUN
fcis-31244	23	47	of	of	ADP
fcis-31244	23	48	traditional	traditional	ADJ
fcis-31244	23	49	single	single	ADJ
fcis-31244	23	50	-	-	PUNCT
fcis-31244	23	51	mode	mode	NOUN
fcis-31244	23	52	architecture	architecture	NOUN
fcis-31244	23	53	,	,	PUNCT
fcis-31244	23	54	and	and	CCONJ
fcis-31244	23	55	design	design	NOUN
fcis-31244	23	56	grouped	group	VERB
fcis-31244	23	57	state	state	NOUN
fcis-31244	23	58	space	space	NOUN
fcis-31244	23	59	(	(	PUNCT
fcis-31244	23	60	ssm	ssm	NOUN
fcis-31244	23	61	)	)	PUNCT
fcis-31244	23	62	and	and	CCONJ
fcis-31244	23	63	hierarchical	hierarchical	ADJ
fcis-31244	23	64	quantization	quantization	NOUN
fcis-31244	23	65	strategy[11	strategy[11	NOUN
fcis-31244	23	66	]	]	PUNCT
fcis-31244	23	67	according	accord	VERB
fcis-31244	23	68	to	to	ADP
fcis-31244	23	69	the	the	DET
fcis-31244	23	70	characteristics	characteristic	NOUN
fcis-31244	23	71	of	of	ADP
fcis-31244	23	72	video	video	NOUN
fcis-31244	23	73	frame	frame	NOUN
fcis-31244	23	74	sequence	sequence	NOUN
fcis-31244	23	75	,	,	PUNCT
fcis-31244	23	76	while	while	SCONJ
fcis-31244	23	77	reducing	reduce	VERB
fcis-31244	23	78	the	the	DET
fcis-31244	23	79	memory	memory	NOUN
fcis-31244	23	80	occupation	occupation	NOUN
fcis-31244	23	81	of	of	ADP
fcis-31244	23	82	mamba	mamba	PROPN
fcis-31244	23	83	modules	module	NOUN
fcis-31244	23	84	,	,	PUNCT
fcis-31244	23	85	maintain	maintain	VERB
fcis-31244	23	86	sensitivity	sensitivity	NOUN
fcis-31244	23	87	to	to	ADP
fcis-31244	23	88	complex	complex	ADJ
fcis-31244	23	89	gesture	gesture	NOUN
fcis-31244	23	90	actions	action	NOUN
fcis-31244	23	91	.	.	PUNCT
fcis-31244	24	1	the	the	DET
fcis-31244	24	2	experimental	experimental	ADJ
fcis-31244	24	3	part	part	NOUN
fcis-31244	24	4	is	be	AUX
fcis-31244	24	5	based	base	VERB
fcis-31244	24	6	on	on	ADP
fcis-31244	24	7	the	the	DET
fcis-31244	24	8	fine	fine	ADJ
fcis-31244	24	9	dynamic	dynamic	ADJ
fcis-31244	24	10	gesture	gesture	NOUN
fcis-31244	24	11	recognition	recognition	NOUN
fcis-31244	24	12	data	datum	NOUN
fcis-31244	24	13	set	set	VERB
fcis-31244	24	14	and	and	CCONJ
fcis-31244	24	15	the	the	DET
fcis-31244	24	16	self	self	NOUN
fcis-31244	24	17	built	build	VERB
fcis-31244	24	18	multi	multi	ADJ
fcis-31244	24	19	scene	scene	NOUN
fcis-31244	24	20	gesture	gesture	NOUN
fcis-31244	24	21	video	video	NOUN
fcis-31244	24	22	.	.	PUNCT
fcis-31244	25	1	the	the	DET
fcis-31244	25	2	results	result	NOUN
fcis-31244	25	3	show	show	VERB
fcis-31244	25	4	that	that	SCONJ
fcis-31244	25	5	:	:	PUNCT
fcis-31244	25	6	compared	compare	VERB
fcis-31244	25	7	with	with	ADP
fcis-31244	25	8	the	the	DET
fcis-31244	25	9	mainstream	mainstream	ADJ
fcis-31244	25	10	dynamic	dynamic	ADJ
fcis-31244	25	11	gesture	gesture	NOUN
fcis-31244	25	12	models	model	NOUN
fcis-31244	25	13	(	(	PUNCT
fcis-31244	25	14	cnn	cnn	PROPN
fcis-31244	25	15	-	-	PUNCT
fcis-31244	25	16	lstm	lstm	PROPN
fcis-31244	25	17	,	,	PUNCT
fcis-31244	25	18	dyhand	dyhand	NOUN
fcis-31244	25	19	)	)	PUNCT
fcis-31244	25	20	,	,	PUNCT
fcis-31244	25	21	the	the	DET
fcis-31244	25	22	recognition	recognition	NOUN
fcis-31244	25	23	accuracy	accuracy	NOUN
fcis-31244	25	24	of	of	ADP
fcis-31244	25	25	this	this	DET
fcis-31244	25	26	method	method	NOUN
fcis-31244	25	27	is	be	AUX
fcis-31244	25	28	improved	improve	VERB
fcis-31244	25	29	by	by	ADP
fcis-31244	25	30	1.8	1.8	NUM
fcis-31244	25	31	%	%	NOUN
fcis-31244	25	32	with	with	ADP
fcis-31244	25	33	43.6	43.6	NUM
fcis-31244	25	34	%	%	NOUN
fcis-31244	25	35	parameter	parameter	NOUN
fcis-31244	25	36	reduction	reduction	NOUN
fcis-31244	25	37	(	(	PUNCT
fcis-31244	25	38	2.1	2.1	NUM
fcis-31244	25	39	mb	mb	NOUN
fcis-31244	25	40	)	)	PUNCT
fcis-31244	25	41	,	,	PUNCT
fcis-31244	25	42	which	which	PRON
fcis-31244	25	43	provides	provide	VERB
fcis-31244	25	44	a	a	DET
fcis-31244	25	45	reliable	reliable	ADJ
fcis-31244	25	46	solution	solution	NOUN
fcis-31244	25	47	for	for	ADP
fcis-31244	25	48	real	real	ADJ
fcis-31244	25	49	-	-	PUNCT
fcis-31244	25	50	time	time	NOUN
fcis-31244	25	51	gesture	gesture	NOUN
fcis-31244	25	52	interaction	interaction	NOUN
fcis-31244	25	53	in	in	ADP
fcis-31244	25	54	resource	resource	NOUN
fcis-31244	25	55	74	74	NUM
fcis-31244	25	56	constrained	constrained	ADJ
fcis-31244	25	57	environments	environment	NOUN
fcis-31244	25	58	.	.	PUNCT
fcis-31244	26	1	2	2	X
fcis-31244	26	2	.	.	X
fcis-31244	26	3	related	relate	VERB
fcis-31244	26	4	work	work	NOUN
fcis-31244	26	5	this	this	DET
fcis-31244	26	6	paper	paper	NOUN
fcis-31244	26	7	divides	divide	VERB
fcis-31244	26	8	the	the	DET
fcis-31244	26	9	related	related	ADJ
fcis-31244	26	10	work	work	NOUN
fcis-31244	26	11	into	into	ADP
fcis-31244	26	12	three	three	NUM
fcis-31244	26	13	main	main	ADJ
fcis-31244	26	14	parts	part	NOUN
fcis-31244	26	15	,	,	PUNCT
fcis-31244	26	16	including	include	VERB
fcis-31244	26	17	the	the	DET
fcis-31244	26	18	advantages	advantage	NOUN
fcis-31244	26	19	of	of	ADP
fcis-31244	26	20	shufflenetv2	shufflenetv2	NOUN
fcis-31244	26	21	-	-	PUNCT
fcis-31244	26	22	mamba	mamba	NOUN
fcis-31244	26	23	structure	structure	NOUN
fcis-31244	26	24	;	;	PUNCT
fcis-31244	26	25	the	the	DET
fcis-31244	26	26	comparison	comparison	NOUN
fcis-31244	26	27	between	between	ADP
fcis-31244	26	28	the	the	DET
fcis-31244	26	29	existing	exist	VERB
fcis-31244	26	30	mainstream	mainstream	NOUN
fcis-31244	26	31	model	model	NOUN
fcis-31244	26	32	and	and	CCONJ
fcis-31244	26	33	the	the	DET
fcis-31244	26	34	model	model	NOUN
fcis-31244	26	35	proposed	propose	VERB
fcis-31244	26	36	in	in	ADP
fcis-31244	26	37	this	this	DET
fcis-31244	26	38	paper	paper	NOUN
fcis-31244	26	39	,	,	PUNCT
fcis-31244	26	40	and	and	CCONJ
fcis-31244	26	41	the	the	DET
fcis-31244	26	42	impact	impact	NOUN
fcis-31244	26	43	of	of	ADP
fcis-31244	26	44	each	each	DET
fcis-31244	26	45	part	part	NOUN
fcis-31244	26	46	of	of	ADP
fcis-31244	26	47	the	the	DET
fcis-31244	26	48	model	model	NOUN
fcis-31244	26	49	on	on	ADP
fcis-31244	26	50	the	the	DET
fcis-31244	26	51	model	model	NOUN
fcis-31244	26	52	.	.	PUNCT
fcis-31244	27	1	2.1	2.1	NUM
fcis-31244	27	2	.	.	PUNCT
fcis-31244	28	1	cnn	cnn	PROPN
fcis-31244	28	2	-	-	PUNCT
fcis-31244	28	3	lstm	lstm	PROPN
fcis-31244	28	4	cnn	cnn	PROPN
fcis-31244	28	5	-	-	PUNCT
fcis-31244	28	6	lstm	lstm	PROPN
fcis-31244	28	7	model	model	NOUN
fcis-31244	28	8	combines	combine	VERB
fcis-31244	28	9	convolutional	convolutional	ADJ
fcis-31244	28	10	neural	neural	ADJ
fcis-31244	28	11	network	network	NOUN
fcis-31244	28	12	(	(	PUNCT
fcis-31244	28	13	cnn	cnn	PROPN
fcis-31244	28	14	)	)	PUNCT
fcis-31244	28	15	and	and	CCONJ
fcis-31244	28	16	long	long	ADJ
fcis-31244	28	17	-	-	PUNCT
fcis-31244	28	18	term	term	NOUN
fcis-31244	28	19	and	and	CCONJ
fcis-31244	28	20	short	short	ADJ
fcis-31244	28	21	-	-	PUNCT
fcis-31244	28	22	term	term	NOUN
fcis-31244	28	23	memory	memory	NOUN
fcis-31244	28	24	network	network	NOUN
fcis-31244	28	25	(	(	PUNCT
fcis-31244	28	26	lstm	lstm	PROPN
fcis-31244	28	27	)	)	PUNCT
fcis-31244	28	28	,	,	PUNCT
fcis-31244	28	29	extracts	extract	VERB
fcis-31244	28	30	the	the	DET
fcis-31244	28	31	spatial	spatial	ADJ
fcis-31244	28	32	features	feature	NOUN
fcis-31244	28	33	(	(	PUNCT
fcis-31244	28	34	such	such	ADJ
fcis-31244	28	35	as	as	ADP
fcis-31244	28	36	hand	hand	NOUN
fcis-31244	28	37	shape	shape	NOUN
fcis-31244	28	38	and	and	CCONJ
fcis-31244	28	39	position	position	NOUN
fcis-31244	28	40	)	)	PUNCT
fcis-31244	28	41	in	in	ADP
fcis-31244	28	42	the	the	DET
fcis-31244	28	43	gesture	gesture	NOUN
fcis-31244	28	44	video	video	NOUN
fcis-31244	28	45	frame	frame	NOUN
fcis-31244	28	46	through	through	ADP
fcis-31244	28	47	cnn	cnn	PROPN
fcis-31244	28	48	,	,	PUNCT
fcis-31244	28	49	and	and	CCONJ
fcis-31244	28	50	then	then	ADV
fcis-31244	28	51	uses	use	VERB
fcis-31244	28	52	lstm	lstm	NOUN
fcis-31244	28	53	to	to	PART
fcis-31244	28	54	capture	capture	VERB
fcis-31244	28	55	the	the	DET
fcis-31244	28	56	dynamic	dynamic	ADJ
fcis-31244	28	57	changes	change	NOUN
fcis-31244	28	58	of	of	ADP
fcis-31244	28	59	the	the	DET
fcis-31244	28	60	timing	timing	NOUN
fcis-31244	28	61	of	of	ADP
fcis-31244	28	62	gesture	gesture	NOUN
fcis-31244	28	63	action	action	NOUN
fcis-31244	28	64	.	.	PUNCT
fcis-31244	29	1	this	this	DET
fcis-31244	29	2	architecture	architecture	NOUN
fcis-31244	29	3	can	can	AUX
fcis-31244	29	4	effectively	effectively	ADV
fcis-31244	29	5	integrate	integrate	VERB
fcis-31244	29	6	static	static	ADJ
fcis-31244	29	7	image	image	NOUN
fcis-31244	29	8	features	feature	NOUN
fcis-31244	29	9	and	and	CCONJ
fcis-31244	29	10	context	context	NOUN
fcis-31244	29	11	information	information	NOUN
fcis-31244	29	12	of	of	ADP
fcis-31244	29	13	continuous	continuous	ADJ
fcis-31244	29	14	actions	action	NOUN
fcis-31244	29	15	,	,	PUNCT
fcis-31244	29	16	and	and	CCONJ
fcis-31244	29	17	has	have	VERB
fcis-31244	29	18	excellent	excellent	ADJ
fcis-31244	29	19	performance	performance	NOUN
fcis-31244	29	20	in	in	ADP
fcis-31244	29	21	dynamic	dynamic	ADJ
fcis-31244	29	22	gesture	gesture	NOUN
fcis-31244	29	23	recognition	recognition	NOUN
fcis-31244	29	24	.	.	PUNCT
fcis-31244	30	1	it	it	PRON
fcis-31244	30	2	can	can	AUX
fcis-31244	30	3	achieve	achieve	VERB
fcis-31244	30	4	high	high	ADJ
fcis-31244	30	5	accuracy	accuracy	NOUN
fcis-31244	30	6	and	and	CCONJ
fcis-31244	30	7	support	support	VERB
fcis-31244	30	8	real	real	ADJ
fcis-31244	30	9	-	-	PUNCT
fcis-31244	30	10	time	time	NOUN
fcis-31244	30	11	interaction	interaction	NOUN
fcis-31244	30	12	,	,	PUNCT
fcis-31244	30	13	especially	especially	ADV
fcis-31244	30	14	when	when	SCONJ
fcis-31244	30	15	processing	process	VERB
fcis-31244	30	16	short	short	ADJ
fcis-31244	30	17	-	-	PUNCT
fcis-31244	30	18	term	term	NOUN
fcis-31244	30	19	gesture	gesture	NOUN
fcis-31244	30	20	sequences	sequence	NOUN
fcis-31244	30	21	(	(	PUNCT
fcis-31244	30	22	such	such	ADJ
fcis-31244	30	23	as	as	ADP
fcis-31244	30	24	clicking	click	VERB
fcis-31244	30	25	and	and	CCONJ
fcis-31244	30	26	sliding	sliding	NOUN
fcis-31244	30	27	)	)	PUNCT
fcis-31244	30	28	.	.	PUNCT
fcis-31244	31	1	it	it	PRON
fcis-31244	31	2	is	be	AUX
fcis-31244	31	3	suitable	suitable	ADJ
fcis-31244	31	4	for	for	ADP
fcis-31244	31	5	vr	vr	PROPN
fcis-31244	31	6	/	/	SYM
fcis-31244	31	7	ar	ar	PROPN
fcis-31244	31	8	and	and	CCONJ
fcis-31244	31	9	other	other	ADJ
fcis-31244	31	10	scenes	scene	NOUN
fcis-31244	31	11	requiring	require	VERB
fcis-31244	31	12	low	low	ADJ
fcis-31244	31	13	delay	delay	NOUN
fcis-31244	31	14	response	response	NOUN
fcis-31244	31	15	.	.	PUNCT
fcis-31244	32	1	the	the	DET
fcis-31244	32	2	spatio	spatio	PROPN
fcis-31244	32	3	-	-	PUNCT
fcis-31244	32	4	temporal	temporal	ADJ
fcis-31244	32	5	modeling	modeling	NOUN
fcis-31244	32	6	ability	ability	NOUN
fcis-31244	32	7	of	of	ADP
fcis-31244	32	8	the	the	DET
fcis-31244	32	9	model	model	NOUN
fcis-31244	32	10	can	can	AUX
fcis-31244	32	11	not	not	PART
fcis-31244	32	12	only	only	ADV
fcis-31244	32	13	recognize	recognize	VERB
fcis-31244	32	14	the	the	DET
fcis-31244	32	15	local	local	ADJ
fcis-31244	32	16	details	detail	NOUN
fcis-31244	32	17	of	of	ADP
fcis-31244	32	18	gestures	gesture	NOUN
fcis-31244	32	19	,	,	PUNCT
fcis-31244	32	20	but	but	CCONJ
fcis-31244	32	21	also	also	ADV
fcis-31244	32	22	capture	capture	VERB
fcis-31244	32	23	the	the	DET
fcis-31244	32	24	coherence	coherence	NOUN
fcis-31244	32	25	of	of	ADP
fcis-31244	32	26	actions	action	NOUN
fcis-31244	32	27	,	,	PUNCT
fcis-31244	32	28	and	and	CCONJ
fcis-31244	32	29	has	have	VERB
fcis-31244	32	30	strong	strong	ADJ
fcis-31244	32	31	scalability	scalability	NOUN
fcis-31244	32	32	in	in	ADP
fcis-31244	32	33	multimodal	multimodal	ADJ
fcis-31244	32	34	input	input	NOUN
fcis-31244	32	35	(	(	PUNCT
fcis-31244	32	36	such	such	ADJ
fcis-31244	32	37	as	as	ADP
fcis-31244	32	38	combining	combine	VERB
fcis-31244	32	39	skeleton	skeleton	NOUN
fcis-31244	32	40	data	datum	NOUN
fcis-31244	32	41	)	)	PUNCT
fcis-31244	32	42	.	.	PUNCT
fcis-31244	33	1	however	however	ADV
fcis-31244	33	2	,	,	PUNCT
fcis-31244	33	3	the	the	DET
fcis-31244	33	4	model	model	NOUN
fcis-31244	33	5	has	have	VERB
fcis-31244	33	6	high	high	ADJ
fcis-31244	33	7	computational	computational	ADJ
fcis-31244	33	8	complexity	complexity	NOUN
fcis-31244	33	9	,	,	PUNCT
fcis-31244	33	10	especially	especially	ADV
fcis-31244	33	11	in	in	ADP
fcis-31244	33	12	the	the	DET
fcis-31244	33	13	long	long	ADJ
fcis-31244	33	14	sequence	sequence	NOUN
fcis-31244	33	15	processing	processing	NOUN
fcis-31244	33	16	,	,	PUNCT
fcis-31244	33	17	it	it	PRON
fcis-31244	33	18	is	be	AUX
fcis-31244	33	19	prone	prone	ADJ
fcis-31244	33	20	to	to	ADP
fcis-31244	33	21	efficiency	efficiency	NOUN
fcis-31244	33	22	bottlenecks	bottleneck	NOUN
fcis-31244	33	23	;	;	PUNCT
fcis-31244	33	24	at	at	ADP
fcis-31244	33	25	the	the	DET
fcis-31244	33	26	same	same	ADJ
fcis-31244	33	27	time	time	NOUN
fcis-31244	33	28	,	,	PUNCT
fcis-31244	33	29	the	the	DET
fcis-31244	33	30	model	model	NOUN
fcis-31244	33	31	is	be	AUX
fcis-31244	33	32	highly	highly	ADV
fcis-31244	33	33	dependent	dependent	ADJ
fcis-31244	33	34	on	on	ADP
fcis-31244	33	35	the	the	DET
fcis-31244	33	36	amount	amount	NOUN
fcis-31244	33	37	of	of	ADP
fcis-31244	33	38	training	training	NOUN
fcis-31244	33	39	data	datum	NOUN
fcis-31244	33	40	and	and	CCONJ
fcis-31244	33	41	annotation	annotation	NOUN
fcis-31244	33	42	quality	quality	NOUN
fcis-31244	33	43	,	,	PUNCT
fcis-31244	33	44	and	and	CCONJ
fcis-31244	33	45	its	its	PRON
fcis-31244	33	46	robustness	robustness	NOUN
fcis-31244	33	47	may	may	AUX
fcis-31244	33	48	decline	decline	VERB
fcis-31244	33	49	in	in	ADP
fcis-31244	33	50	complex	complex	ADJ
fcis-31244	33	51	background	background	NOUN
fcis-31244	33	52	or	or	CCONJ
fcis-31244	33	53	occluded	occluded	ADJ
fcis-31244	33	54	scenes	scene	NOUN
fcis-31244	33	55	.	.	PUNCT
fcis-31244	34	1	it	it	PRON
fcis-31244	34	2	needs	need	VERB
fcis-31244	34	3	to	to	PART
fcis-31244	34	4	rely	rely	VERB
fcis-31244	34	5	on	on	ADP
fcis-31244	34	6	data	data	NOUN
fcis-31244	34	7	enhancement	enhancement	NOUN
fcis-31244	34	8	or	or	CCONJ
fcis-31244	34	9	additional	additional	ADJ
fcis-31244	34	10	sensors	sensor	NOUN
fcis-31244	34	11	(	(	PUNCT
fcis-31244	34	12	such	such	ADJ
fcis-31244	34	13	as	as	ADP
fcis-31244	34	14	depth	depth	NOUN
fcis-31244	34	15	camera	camera	NOUN
fcis-31244	34	16	)	)	PUNCT
fcis-31244	34	17	to	to	PART
fcis-31244	34	18	assist	assist	VERB
fcis-31244	34	19	optimization	optimization	NOUN
fcis-31244	34	20	.	.	PUNCT
fcis-31244	35	1	2.2	2.2	NUM
fcis-31244	35	2	.	.	PUNCT
fcis-31244	35	3	transformer	transformer	NOUN
fcis-31244	35	4	.	.	PUNCT
fcis-31244	36	1	the	the	DET
fcis-31244	36	2	transformer	transformer	NOUN
fcis-31244	36	3	model	model	NOUN
fcis-31244	36	4	was	be	AUX
fcis-31244	36	5	proposed	propose	VERB
fcis-31244	36	6	by	by	ADP
fcis-31244	36	7	vaswani	vaswani	PROPN
fcis-31244	36	8	et	et	PROPN
fcis-31244	36	9	al	al	PROPN
fcis-31244	36	10	.	.	PROPN
fcis-31244	37	1	in	in	ADP
fcis-31244	37	2	2017	2017	NUM
fcis-31244	37	3	.	.	PUNCT
fcis-31244	38	1	the	the	DET
fcis-31244	38	2	model	model	NOUN
fcis-31244	38	3	uses	use	VERB
fcis-31244	38	4	a	a	DET
fcis-31244	38	5	codec	codec	NOUN
fcis-31244	38	6	architecture	architecture	NOUN
fcis-31244	38	7	.	.	PUNCT
fcis-31244	39	1	it	it	PRON
fcis-31244	39	2	was	be	AUX
fcis-31244	39	3	first	first	ADV
fcis-31244	39	4	applied	apply	VERB
fcis-31244	39	5	in	in	ADP
fcis-31244	39	6	the	the	DET
fcis-31244	39	7	nlp	nlp	NOUN
fcis-31244	39	8	field	field	NOUN
fcis-31244	39	9	,	,	PUNCT
fcis-31244	39	10	and	and	CCONJ
fcis-31244	39	11	then	then	ADV
fcis-31244	39	12	widely	widely	ADV
fcis-31244	39	13	used	use	VERB
fcis-31244	39	14	in	in	ADP
fcis-31244	39	15	cv	cv	PROPN
fcis-31244	39	16	and	and	CCONJ
fcis-31244	39	17	timing	time	VERB
fcis-31244	39	18	analysis	analysis	NOUN
fcis-31244	39	19	.	.	PUNCT
fcis-31244	40	1	its	its	PRON
fcis-31244	40	2	core	core	NOUN
fcis-31244	40	3	is	be	AUX
fcis-31244	40	4	to	to	PART
fcis-31244	40	5	capture	capture	VERB
fcis-31244	40	6	the	the	DET
fcis-31244	40	7	sequence	sequence	NOUN
fcis-31244	40	8	relationship	relationship	NOUN
fcis-31244	40	9	through	through	ADP
fcis-31244	40	10	multi	multi	ADJ
fcis-31244	40	11	head	head	NOUN
fcis-31244	40	12	attention	attention	NOUN
fcis-31244	40	13	and	and	CCONJ
fcis-31244	40	14	positional	positional	ADJ
fcis-31244	40	15	encoding	encoding	NOUN
fcis-31244	40	16	,	,	PUNCT
fcis-31244	40	17	and	and	CCONJ
fcis-31244	40	18	can	can	AUX
fcis-31244	40	19	still	still	ADV
fcis-31244	40	20	establish	establish	VERB
fcis-31244	40	21	long	long	ADJ
fcis-31244	40	22	-	-	PUNCT
fcis-31244	40	23	distance	distance	NOUN
fcis-31244	40	24	correlation	correlation	NOUN
fcis-31244	40	25	without	without	ADP
fcis-31244	40	26	convolution	convolution	NOUN
fcis-31244	40	27	or	or	CCONJ
fcis-31244	40	28	circulation[12	circulation[12	NOUN
fcis-31244	40	29	]	]	PUNCT
fcis-31244	40	30	.	.	PUNCT
fcis-31244	41	1	in	in	ADP
fcis-31244	41	2	dynamic	dynamic	ADJ
fcis-31244	41	3	gesture	gesture	NOUN
fcis-31244	41	4	recognition	recognition	NOUN
fcis-31244	41	5	,	,	PUNCT
fcis-31244	41	6	transformer	transformer	NOUN
fcis-31244	41	7	can	can	AUX
fcis-31244	41	8	process	process	VERB
fcis-31244	41	9	the	the	DET
fcis-31244	41	10	sequence	sequence	NOUN
fcis-31244	41	11	of	of	ADP
fcis-31244	41	12	video	video	NOUN
fcis-31244	41	13	frames	frame	NOUN
fcis-31244	41	14	and	and	CCONJ
fcis-31244	41	15	analyze	analyze	VERB
fcis-31244	41	16	the	the	DET
fcis-31244	41	17	continuity	continuity	NOUN
fcis-31244	41	18	and	and	CCONJ
fcis-31244	41	19	local	local	ADJ
fcis-31244	41	20	details	detail	NOUN
fcis-31244	41	21	of	of	ADP
fcis-31244	41	22	gesture	gesture	NOUN
fcis-31244	41	23	actions	action	NOUN
fcis-31244	41	24	through	through	ADP
fcis-31244	41	25	attention	attention	NOUN
fcis-31244	41	26	mechanism	mechanism	NOUN
fcis-31244	41	27	.	.	PUNCT
fcis-31244	42	1	however	however	ADV
fcis-31244	42	2	,	,	PUNCT
fcis-31244	42	3	due	due	ADP
fcis-31244	42	4	to	to	ADP
fcis-31244	42	5	the	the	DET
fcis-31244	42	6	limitations	limitation	NOUN
fcis-31244	42	7	of	of	ADP
fcis-31244	42	8	transformer	transformer	NOUN
fcis-31244	42	9	's	's	PART
fcis-31244	42	10	structure	structure	NOUN
fcis-31244	42	11	,	,	PUNCT
fcis-31244	42	12	the	the	DET
fcis-31244	42	13	model	model	NOUN
fcis-31244	42	14	relies	rely	VERB
fcis-31244	42	15	heavily	heavily	ADV
fcis-31244	42	16	on	on	ADP
fcis-31244	42	17	high	high	ADJ
fcis-31244	42	18	computing	computing	NOUN
fcis-31244	42	19	resources	resource	NOUN
fcis-31244	42	20	and	and	CCONJ
fcis-31244	42	21	data	datum	NOUN
fcis-31244	42	22	sets	set	NOUN
fcis-31244	42	23	,	,	PUNCT
fcis-31244	42	24	which	which	PRON
fcis-31244	42	25	limits	limit	VERB
fcis-31244	42	26	the	the	DET
fcis-31244	42	27	computational	computational	ADJ
fcis-31244	42	28	efficiency	efficiency	NOUN
fcis-31244	42	29	of	of	ADP
fcis-31244	42	30	the	the	DET
fcis-31244	42	31	model	model	NOUN
fcis-31244	42	32	and	and	CCONJ
fcis-31244	42	33	affects	affect	VERB
fcis-31244	42	34	the	the	DET
fcis-31244	42	35	ability	ability	NOUN
fcis-31244	42	36	to	to	PART
fcis-31244	42	37	handle	handle	VERB
fcis-31244	42	38	complex	complex	ADJ
fcis-31244	42	39	sequential	sequential	ADJ
fcis-31244	42	40	tasks	task	NOUN
fcis-31244	42	41	.	.	PUNCT
fcis-31244	43	1	2.3	2.3	NUM
fcis-31244	43	2	.	.	PUNCT
fcis-31244	44	1	mamba	mamba	PROPN
fcis-31244	44	2	mamba	mamba	PROPN
fcis-31244	44	3	is	be	AUX
fcis-31244	44	4	a	a	DET
fcis-31244	44	5	new	new	ADJ
fcis-31244	44	6	type	type	NOUN
fcis-31244	44	7	of	of	ADP
fcis-31244	44	8	deep	deep	ADJ
fcis-31244	44	9	learning	learning	NOUN
fcis-31244	44	10	architecture	architecture	NOUN
fcis-31244	44	11	based	base	VERB
fcis-31244	44	12	on	on	ADP
fcis-31244	44	13	the	the	DET
fcis-31244	44	14	selective	selective	ADJ
fcis-31244	44	15	state	state	NOUN
fcis-31244	44	16	space	space	NOUN
fcis-31244	44	17	model	model	NOUN
fcis-31244	44	18	,	,	PUNCT
fcis-31244	44	19	which	which	PRON
fcis-31244	44	20	aims	aim	VERB
fcis-31244	44	21	to	to	PART
fcis-31244	44	22	solve	solve	VERB
fcis-31244	44	23	the	the	DET
fcis-31244	44	24	efficiency	efficiency	NOUN
fcis-31244	44	25	bottleneck	bottleneck	NOUN
fcis-31244	44	26	problem	problem	NOUN
fcis-31244	44	27	caused	cause	VERB
fcis-31244	44	28	by	by	ADP
fcis-31244	44	29	the	the	DET
fcis-31244	44	30	complexity	complexity	NOUN
fcis-31244	44	31	of	of	ADP
fcis-31244	44	32	secondary	secondary	ADJ
fcis-31244	44	33	calculation	calculation	NOUN
fcis-31244	44	34	when	when	SCONJ
fcis-31244	44	35	the	the	DET
fcis-31244	44	36	transformer	transformer	NOUN
fcis-31244	44	37	processes	process	VERB
fcis-31244	44	38	sequential	sequential	ADJ
fcis-31244	44	39	tasks	task	NOUN
fcis-31244	44	40	.	.	PUNCT
fcis-31244	45	1	the	the	DET
fcis-31244	45	2	selectivity	selectivity	NOUN
fcis-31244	45	3	mechanism	mechanism	NOUN
fcis-31244	45	4	and	and	CCONJ
fcis-31244	45	5	hardware	hardware	NOUN
fcis-31244	45	6	aware	aware	ADJ
fcis-31244	45	7	algorithm	algorithm	NOUN
fcis-31244	45	8	enable	enable	VERB
fcis-31244	45	9	it	it	PRON
fcis-31244	45	10	to	to	PART
fcis-31244	45	11	show	show	VERB
fcis-31244	45	12	the	the	DET
fcis-31244	45	13	same	same	ADJ
fcis-31244	45	14	performance	performance	NOUN
fcis-31244	45	15	as	as	ADP
fcis-31244	45	16	transformer	transformer	NOUN
fcis-31244	45	17	in	in	ADP
fcis-31244	45	18	audio	audio	ADJ
fcis-31244	45	19	and	and	CCONJ
fcis-31244	45	20	video	video	NOUN
fcis-31244	45	21	tasks	task	NOUN
fcis-31244	45	22	.	.	PUNCT
fcis-31244	46	1	the	the	DET
fcis-31244	46	2	model	model	NOUN
fcis-31244	46	3	uses	use	VERB
fcis-31244	46	4	the	the	DET
fcis-31244	46	5	scan	scan	ADJ
fcis-31244	46	6	mechanism	mechanism	NOUN
fcis-31244	46	7	to	to	PART
fcis-31244	46	8	replace	replace	VERB
fcis-31244	46	9	the	the	DET
fcis-31244	46	10	traditional	traditional	ADJ
fcis-31244	46	11	convolution	convolution	NOUN
fcis-31244	46	12	or	or	CCONJ
fcis-31244	46	13	attention	attention	NOUN
fcis-31244	46	14	calculation	calculation	NOUN
fcis-31244	46	15	,	,	PUNCT
fcis-31244	46	16	and	and	CCONJ
fcis-31244	46	17	combines	combine	VERB
fcis-31244	46	18	the	the	DET
fcis-31244	46	19	gpu	gpu	NOUN
fcis-31244	46	20	memory	memory	NOUN
fcis-31244	46	21	hierarchy	hierarchy	NOUN
fcis-31244	46	22	(	(	PUNCT
fcis-31244	46	23	sram	sram	PROPN
fcis-31244	46	24	and	and	CCONJ
fcis-31244	46	25	hbm	hbm	PROPN
fcis-31244	46	26	)	)	PUNCT
fcis-31244	46	27	to	to	PART
fcis-31244	46	28	reduce	reduce	VERB
fcis-31244	46	29	the	the	DET
fcis-31244	46	30	read	read	NOUN
fcis-31244	46	31	and	and	CCONJ
fcis-31244	46	32	write	write	VERB
fcis-31244	46	33	overhead	overhead	NOUN
fcis-31244	46	34	of	of	ADP
fcis-31244	46	35	the	the	DET
fcis-31244	46	36	video	video	NOUN
fcis-31244	46	37	memory	memory	NOUN
fcis-31244	46	38	,	,	PUNCT
fcis-31244	46	39	and	and	CCONJ
fcis-31244	46	40	removes	remove	VERB
fcis-31244	46	41	the	the	DET
fcis-31244	46	42	attention	attention	NOUN
fcis-31244	46	43	module	module	NOUN
fcis-31244	46	44	and	and	CCONJ
fcis-31244	46	45	mlp	mlp	NOUN
fcis-31244	46	46	in	in	ADP
fcis-31244	46	47	the	the	DET
fcis-31244	46	48	transformer	transformer	NOUN
fcis-31244	46	49	,	,	PUNCT
fcis-31244	46	50	which	which	PRON
fcis-31244	46	51	is	be	AUX
fcis-31244	46	52	only	only	ADV
fcis-31244	46	53	realized	realize	VERB
fcis-31244	46	54	by	by	ADP
fcis-31244	46	55	the	the	DET
fcis-31244	46	56	mamba	mamba	PROPN
fcis-31244	46	57	block	block	NOUN
fcis-31244	46	58	(	(	PUNCT
fcis-31244	46	59	ssm+mlp	ssm+mlp	NOUN
fcis-31244	46	60	)	)	PUNCT
fcis-31244	46	61	stack	stack	NOUN
fcis-31244	46	62	,	,	PUNCT
fcis-31244	46	63	with	with	ADP
fcis-31244	46	64	a	a	DET
fcis-31244	46	65	more	more	ADV
fcis-31244	46	66	compact	compact	ADJ
fcis-31244	46	67	structure	structure	NOUN
fcis-31244	46	68	and	and	CCONJ
fcis-31244	46	69	higher	high	ADJ
fcis-31244	46	70	parameter	parameter	NOUN
fcis-31244	46	71	utilization	utilization	NOUN
fcis-31244	46	72	.	.	PUNCT
fcis-31244	47	1	the	the	DET
fcis-31244	47	2	computational	computational	ADJ
fcis-31244	47	3	complexity	complexity	NOUN
fcis-31244	47	4	also	also	ADV
fcis-31244	47	5	shows	show	VERB
fcis-31244	47	6	linear	linear	ADJ
fcis-31244	47	7	scaling	scale	VERB
fcis-31244	47	8	effect	effect	NOUN
fcis-31244	47	9	when	when	SCONJ
fcis-31244	47	10	the	the	DET
fcis-31244	47	11	sequence	sequence	NOUN
fcis-31244	47	12	length	length	NOUN
fcis-31244	47	13	is	be	AUX
fcis-31244	47	14	extended	extend	VERB
fcis-31244	47	15	,	,	PUNCT
fcis-31244	47	16	which	which	PRON
fcis-31244	47	17	ensures	ensure	VERB
fcis-31244	47	18	the	the	DET
fcis-31244	47	19	excellent	excellent	ADJ
fcis-31244	47	20	performance	performance	NOUN
fcis-31244	47	21	of	of	ADP
fcis-31244	47	22	the	the	DET
fcis-31244	47	23	model	model	NOUN
fcis-31244	47	24	in	in	ADP
fcis-31244	47	25	long	long	ADJ
fcis-31244	47	26	sequence	sequence	NOUN
fcis-31244	47	27	tasks	task	NOUN
fcis-31244	47	28	.	.	PUNCT
fcis-31244	48	1	3	3	X
fcis-31244	48	2	.	.	X
fcis-31244	48	3	network	network	NOUN
fcis-31244	48	4	design	design	NOUN
fcis-31244	48	5	this	this	DET
fcis-31244	48	6	paper	paper	NOUN
fcis-31244	48	7	uses	use	VERB
fcis-31244	48	8	shufflenetv2	shufflenetv2	PROPN
fcis-31244	48	9	as	as	ADP
fcis-31244	48	10	the	the	DET
fcis-31244	48	11	backbone	backbone	NOUN
fcis-31244	48	12	network	network	NOUN
fcis-31244	48	13	,	,	PUNCT
fcis-31244	48	14	its	its	PRON
fcis-31244	48	15	core	core	NOUN
fcis-31244	48	16	is	be	AUX
fcis-31244	48	17	the	the	DET
fcis-31244	48	18	channel	channel	NOUN
fcis-31244	48	19	split	split	NOUN
fcis-31244	48	20	and	and	CCONJ
fcis-31244	48	21	channel	channel	NOUN
fcis-31244	48	22	shuffle	shuffle	NOUN
fcis-31244	48	23	mechanism	mechanism	NOUN
fcis-31244	48	24	,	,	PUNCT
fcis-31244	48	25	and	and	CCONJ
fcis-31244	48	26	integrates	integrate	VERB
fcis-31244	48	27	mamba	mamba	NOUN
fcis-31244	48	28	block	block	NOUN
fcis-31244	48	29	to	to	PART
fcis-31244	48	30	innovatively	innovatively	ADV
fcis-31244	48	31	propose	propose	VERB
fcis-31244	48	32	an	an	DET
fcis-31244	48	33	efficient	efficient	ADJ
fcis-31244	48	34	gesture	gesture	NOUN
fcis-31244	48	35	recognition	recognition	NOUN
fcis-31244	48	36	method	method	NOUN
fcis-31244	48	37	.	.	PUNCT
fcis-31244	49	1	its	its	PRON
fcis-31244	49	2	core	core	ADJ
fcis-31244	49	3	highlights	highlight	NOUN
fcis-31244	49	4	are	be	AUX
fcis-31244	49	5	the	the	DET
fcis-31244	49	6	introduction	introduction	NOUN
fcis-31244	49	7	of	of	ADP
fcis-31244	49	8	mamba	mamba	PROPN
fcis-31244	49	9	block	block	NOUN
fcis-31244	49	10	and	and	CCONJ
fcis-31244	49	11	the	the	DET
fcis-31244	49	12	low	low	ADJ
fcis-31244	49	13	parameter	parameter	NOUN
fcis-31244	49	14	of	of	ADP
fcis-31244	49	15	the	the	DET
fcis-31244	49	16	network	network	NOUN
fcis-31244	49	17	.	.	PUNCT
fcis-31244	50	1	smf	smf	PROPN
fcis-31244	50	2	embeds	embed	VERB
fcis-31244	50	3	mamba	mamba	NOUN
fcis-31244	50	4	blocks	block	NOUN
fcis-31244	50	5	in	in	ADP
fcis-31244	50	6	the	the	DET
fcis-31244	50	7	bottleneck	bottleneck	NOUN
fcis-31244	50	8	block	block	NOUN
fcis-31244	50	9	of	of	ADP
fcis-31244	50	10	the	the	DET
fcis-31244	50	11	traditional	traditional	ADJ
fcis-31244	50	12	shufflenetv2	shufflenetv2	NOUN
fcis-31244	50	13	network	network	NOUN
fcis-31244	50	14	to	to	PART
fcis-31244	50	15	replace	replace	VERB
fcis-31244	50	16	part	part	NOUN
fcis-31244	50	17	of	of	ADP
fcis-31244	50	18	the	the	DET
fcis-31244	50	19	convolution	convolution	NOUN
fcis-31244	50	20	operation	operation	NOUN
fcis-31244	50	21	.	.	PUNCT
fcis-31244	51	1	its	its	PRON
fcis-31244	51	2	key	key	ADJ
fcis-31244	51	3	design	design	NOUN
fcis-31244	51	4	is	be	AUX
fcis-31244	51	5	through	through	ADP
fcis-31244	51	6	the	the	DET
fcis-31244	51	7	hidden	hidden	ADJ
fcis-31244	51	8	state	state	NOUN
fcis-31244	51	9	in	in	ADP
fcis-31244	51	10	the	the	DET
fcis-31244	51	11	state	state	NOUN
fcis-31244	51	12	space	space	NOUN
fcis-31244	51	13	model	model	NOUN
fcis-31244	51	14	(	(	PUNCT
fcis-31244	51	15	ssm	ssm	PROPN
fcis-31244	51	16	):	):	PUNCT
fcis-31244	51	17	1	1	NUM
fcis-31244	51	18	where	where	SCONJ
fcis-31244	51	19	is	be	AUX
fcis-31244	51	20	the	the	DET
fcis-31244	51	21	hidden	hidden	ADJ
fcis-31244	51	22	state	state	NOUN
fcis-31244	51	23	at	at	ADP
fcis-31244	51	24	time	time	NOUN
fcis-31244	51	25	t	t	PROPN
fcis-31244	51	26	,	,	PUNCT
fcis-31244	51	27	is	be	AUX
fcis-31244	51	28	the	the	DET
fcis-31244	51	29	t	t	PROPN
fcis-31244	51	30	vector	vector	NOUN
fcis-31244	51	31	of	of	ADP
fcis-31244	51	32	the	the	DET
fcis-31244	51	33	input	input	NOUN
fcis-31244	51	34	sequence	sequence	NOUN
fcis-31244	51	35	,	,	PUNCT
fcis-31244	51	36	a	a	PRON
fcis-31244	51	37	and	and	CCONJ
fcis-31244	51	38	b	b	NOUN
fcis-31244	51	39	are	be	AUX
fcis-31244	51	40	the	the	DET
fcis-31244	51	41	state	state	NOUN
fcis-31244	51	42	transition	transition	NOUN
fcis-31244	51	43	matrix	matrix	NOUN
fcis-31244	51	44	and	and	CCONJ
fcis-31244	51	45	input	input	NOUN
fcis-31244	51	46	projection	projection	NOUN
fcis-31244	51	47	matrix	matrix	NOUN
fcis-31244	51	48	,	,	PUNCT
fcis-31244	51	49	and	and	CCONJ
fcis-31244	51	50	their	their	PRON
fcis-31244	51	51	outputs	output	NOUN
fcis-31244	51	52	:	:	PUNCT
fcis-31244	51	53	where	where	SCONJ
fcis-31244	51	54	is	be	AUX
fcis-31244	51	55	the	the	DET
fcis-31244	51	56	hidden	hidden	ADJ
fcis-31244	51	57	state	state	NOUN
fcis-31244	51	58	at	at	ADP
fcis-31244	51	59	time	time	NOUN
fcis-31244	51	60	t	t	PROPN
fcis-31244	51	61	,	,	PUNCT
fcis-31244	51	62	is	be	AUX
fcis-31244	51	63	the	the	DET
fcis-31244	51	64	t	t	PROPN
fcis-31244	51	65	vector	vector	NOUN
fcis-31244	51	66	of	of	ADP
fcis-31244	51	67	the	the	DET
fcis-31244	51	68	input	input	NOUN
fcis-31244	51	69	sequence	sequence	NOUN
fcis-31244	51	70	,	,	PUNCT
fcis-31244	51	71	a	a	PRON
fcis-31244	51	72	and	and	CCONJ
fcis-31244	51	73	b	b	NOUN
fcis-31244	51	74	are	be	AUX
fcis-31244	51	75	the	the	DET
fcis-31244	51	76	state	state	NOUN
fcis-31244	51	77	transition	transition	NOUN
fcis-31244	51	78	matrix	matrix	NOUN
fcis-31244	51	79	and	and	CCONJ
fcis-31244	51	80	input	input	NOUN
fcis-31244	51	81	projection	projection	NOUN
fcis-31244	51	82	matrix	matrix	NOUN
fcis-31244	51	83	,	,	PUNCT
fcis-31244	51	84	and	and	CCONJ
fcis-31244	51	85	their	their	PRON
fcis-31244	51	86	outputs	output	NOUN
fcis-31244	51	87	are	be	AUX
fcis-31244	51	88	:	:	PUNCT
fcis-31244	51	89	2	2	NUM
fcis-31244	51	90	is	be	AUX
fcis-31244	51	91	the	the	DET
fcis-31244	51	92	output	output	NOUN
fcis-31244	51	93	projection	projection	NOUN
fcis-31244	51	94	matrix	matrix	NOUN
fcis-31244	51	95	and	and	CCONJ
fcis-31244	51	96	is	be	AUX
fcis-31244	51	97	the	the	DET
fcis-31244	51	98	connection	connection	NOUN
fcis-31244	51	99	matrix	matrix	NOUN
fcis-31244	51	100	.	.	PUNCT
fcis-31244	52	1	this	this	DET
fcis-31244	52	2	improvement	improvement	NOUN
fcis-31244	52	3	enhances	enhance	VERB
fcis-31244	52	4	the	the	DET
fcis-31244	52	5	ability	ability	NOUN
fcis-31244	52	6	of	of	ADP
fcis-31244	52	7	the	the	DET
fcis-31244	52	8	model	model	NOUN
fcis-31244	52	9	to	to	PART
fcis-31244	52	10	deal	deal	VERB
fcis-31244	52	11	with	with	ADP
fcis-31244	52	12	complex	complex	ADJ
fcis-31244	52	13	feature	feature	NOUN
fcis-31244	52	14	sequences	sequence	NOUN
fcis-31244	52	15	,	,	PUNCT
fcis-31244	52	16	and	and	CCONJ
fcis-31244	52	17	the	the	DET
fcis-31244	52	18	design	design	NOUN
fcis-31244	52	19	of	of	ADP
fcis-31244	52	20	selective	selective	ADJ
fcis-31244	52	21	scanning	scanning	NOUN
fcis-31244	52	22	mechanism	mechanism	NOUN
fcis-31244	52	23	in	in	ADP
fcis-31244	52	24	smf	smf	PROPN
fcis-31244	52	25	enables	enable	VERB
fcis-31244	52	26	it	it	PRON
fcis-31244	52	27	to	to	PART
fcis-31244	52	28	dynamically	dynamically	ADV
fcis-31244	52	29	adjust	adjust	VERB
fcis-31244	52	30	ssm	ssm	PROPN
fcis-31244	52	31	parameters[13	parameters[13	NOUN
fcis-31244	52	32	]	]	X
fcis-31244	52	33	,	,	PUNCT
fcis-31244	52	34	which	which	PRON
fcis-31244	52	35	is	be	AUX
fcis-31244	52	36	that	that	SCONJ
fcis-31244	52	37	the	the	DET
fcis-31244	52	38	model	model	NOUN
fcis-31244	52	39	can	can	AUX
fcis-31244	52	40	adaptively	adaptively	ADV
fcis-31244	52	41	focus	focus	VERB
fcis-31244	52	42	on	on	ADP
fcis-31244	52	43	key	key	ADJ
fcis-31244	52	44	temporal	temporal	ADJ
fcis-31244	52	45	features	feature	NOUN
fcis-31244	52	46	according	accord	VERB
fcis-31244	52	47	to	to	ADP
fcis-31244	52	48	the	the	DET
fcis-31244	52	49	gesture	gesture	NOUN
fcis-31244	52	50	trajectory	trajectory	NOUN
fcis-31244	52	51	.	.	PUNCT
fcis-31244	53	1	the	the	DET
fcis-31244	53	2	ssm	ssm	PROPN
fcis-31244	53	3	discretization	discretization	NOUN
fcis-31244	53	4	process	process	NOUN
fcis-31244	53	5	is	be	AUX
fcis-31244	53	6	to	to	PART
fcis-31244	53	7	convert	convert	VERB
fcis-31244	53	8	the	the	DET
fcis-31244	53	9	state	state	NOUN
fcis-31244	53	10	transition	transition	NOUN
fcis-31244	53	11	matrix	matrix	NOUN
fcis-31244	53	12	and	and	CCONJ
fcis-31244	53	13	input	input	NOUN
fcis-31244	53	14	projection	projection	NOUN
fcis-31244	53	15	matrix	matrix	NOUN
fcis-31244	53	16	into	into	ADP
fcis-31244	53	17	discrete	discrete	ADJ
fcis-31244	53	18	parameters	parameter	NOUN
fcis-31244	53	19	through	through	ADP
fcis-31244	53	20	zero	zero	NUM
fcis-31244	53	21	order	order	NOUN
fcis-31244	53	22	hold	hold	NOUN
fcis-31244	53	23	(	(	PUNCT
fcis-31244	53	24	zoh	zoh	NOUN
fcis-31244	53	25	):	):	PUNCT
fcis-31244	54	1	∆	∆	PROPN
fcis-31244	54	2	∆	∆	NOUN
fcis-31244	54	3	∆	∆	X
fcis-31244	54	4	∆	∆	X
fcis-31244	54	5	3	3	NUM
fcis-31244	54	6	∆	∆	X
fcis-31244	54	7	is	be	AUX
fcis-31244	54	8	a	a	DET
fcis-31244	54	9	learnable	learnable	ADJ
fcis-31244	54	10	time	time	NOUN
fcis-31244	54	11	step	step	NOUN
fcis-31244	54	12	parameter	parameter	NOUN
fcis-31244	54	13	.	.	PUNCT
fcis-31244	55	1	3.1	3.1	NUM
fcis-31244	55	2	.	.	PUNCT
fcis-31244	56	1	network	network	NOUN
fcis-31244	56	2	model	model	NOUN
fcis-31244	56	3	structure	structure	NOUN
fcis-31244	56	4	the	the	DET
fcis-31244	56	5	data	data	NOUN
fcis-31244	56	6	flow	flow	NOUN
fcis-31244	56	7	dependency	dependency	NOUN
fcis-31244	56	8	of	of	ADP
fcis-31244	56	9	this	this	DET
fcis-31244	56	10	study	study	NOUN
fcis-31244	56	11	is	be	AUX
fcis-31244	56	12	shown	show	VERB
fcis-31244	56	13	in	in	ADP
fcis-31244	56	14	figure	figure	NOUN
fcis-31244	56	15	1	1	NUM
fcis-31244	56	16	.	.	PUNCT
fcis-31244	57	1	the	the	DET
fcis-31244	57	2	model	model	NOUN
fcis-31244	57	3	provides	provide	VERB
fcis-31244	57	4	dynamic	dynamic	ADJ
fcis-31244	57	5	scalability	scalability	NOUN
fcis-31244	57	6	while	while	SCONJ
fcis-31244	57	7	taking	take	VERB
fcis-31244	57	8	into	into	ADP
fcis-31244	57	9	account	account	NOUN
fcis-31244	57	10	the	the	DET
fcis-31244	57	11	efficiency	efficiency	NOUN
fcis-31244	57	12	performance	performance	NOUN
fcis-31244	57	13	balance	balance	NOUN
fcis-31244	57	14	,	,	PUNCT
fcis-31244	57	15	and	and	CCONJ
fcis-31244	57	16	can	can	AUX
fcis-31244	57	17	dynamically	dynamically	ADV
fcis-31244	57	18	adjust	adjust	VERB
fcis-31244	57	19	the	the	DET
fcis-31244	57	20	channel	channel	NOUN
fcis-31244	57	21	division	division	NOUN
fcis-31244	57	22	ratio	ratio	NOUN
fcis-31244	57	23	to	to	PART
fcis-31244	57	24	adapt	adapt	VERB
fcis-31244	57	25	to	to	ADP
fcis-31244	57	26	the	the	DET
fcis-31244	57	27	constraints	constraint	NOUN
fcis-31244	57	28	of	of	ADP
fcis-31244	57	29	different	different	ADJ
fcis-31244	57	30	hardware	hardware	NOUN
fcis-31244	57	31	resources	resource	NOUN
fcis-31244	57	32	.	.	PUNCT
fcis-31244	58	1	local	local	ADJ
fcis-31244	58	2	convolution	convolution	NOUN
fcis-31244	58	3	flow	flow	NOUN
fcis-31244	58	4	ensures	ensure	VERB
fcis-31244	58	5	the	the	DET
fcis-31244	58	6	real	real	ADJ
fcis-31244	58	7	-	-	PUNCT
fcis-31244	58	8	time	time	NOUN
fcis-31244	58	9	performance	performance	NOUN
fcis-31244	58	10	of	of	ADP
fcis-31244	58	11	high	high	ADJ
fcis-31244	58	12	-	-	PUNCT
fcis-31244	58	13	resolution	resolution	NOUN
fcis-31244	58	14	feature	feature	NOUN
fcis-31244	58	15	extraction	extraction	NOUN
fcis-31244	58	16	.	.	PUNCT
fcis-31244	59	1	through	through	ADP
fcis-31244	59	2	the	the	DET
fcis-31244	59	3	shallow	shallow	ADJ
fcis-31244	59	4	feature	feature	NOUN
fcis-31244	59	5	extraction	extraction	NOUN
fcis-31244	59	6	module	module	NOUN
fcis-31244	59	7	,	,	PUNCT
fcis-31244	59	8	the	the	DET
fcis-31244	59	9	forward	forward	ADJ
fcis-31244	59	10	flow	flow	NOUN
fcis-31244	59	11	of	of	ADP
fcis-31244	59	12	the	the	DET
fcis-31244	59	13	model	model	NOUN
fcis-31244	59	14	realizes	realize	VERB
fcis-31244	59	15	the	the	DET
fcis-31244	59	16	collaboration	collaboration	NOUN
fcis-31244	59	17	of	of	ADP
fcis-31244	59	18	local	local	ADJ
fcis-31244	59	19	perception	perception	NOUN
fcis-31244	59	20	and	and	CCONJ
fcis-31244	59	21	global	global	ADJ
fcis-31244	59	22	sequence	sequence	NOUN
fcis-31244	59	23	modeling	model	VERB
fcis-31244	59	24	through	through	ADP
fcis-31244	59	25	the	the	DET
fcis-31244	59	26	shuffle	shuffle	NOUN
fcis-31244	59	27	-	-	PUNCT
fcis-31244	59	28	mamba	mamba	NOUN
fcis-31244	59	29	block	block	NOUN
fcis-31244	59	30	stacked	stack	VERB
fcis-31244	59	31	in	in	ADP
fcis-31244	59	32	the	the	DET
fcis-31244	59	33	multi	multi	ADJ
fcis-31244	59	34	-	-	ADJ
fcis-31244	59	35	stage	stage	ADJ
fcis-31244	59	36	feature	feature	NOUN
fcis-31244	59	37	fusion	fusion	NOUN
fcis-31244	59	38	,	,	PUNCT
fcis-31244	59	39	uses	use	VERB
fcis-31244	59	40	attention	attention	NOUN
fcis-31244	59	41	pooling	pool	VERB
fcis-31244	59	42	to	to	PART
fcis-31244	59	43	compress	compress	VERB
fcis-31244	59	44	the	the	DET
fcis-31244	59	45	space	space	NOUN
fcis-31244	59	46	-	-	PUNCT
fcis-31244	59	47	time	time	NOUN
fcis-31244	59	48	dimension	dimension	NOUN
fcis-31244	59	49	,	,	PUNCT
fcis-31244	59	50	and	and	CCONJ
fcis-31244	59	51	outputs	output	VERB
fcis-31244	59	52	the	the	DET
fcis-31244	59	53	gesture	gesture	NOUN
fcis-31244	59	54	category	category	NOUN
fcis-31244	59	55	probability	probability	NOUN
fcis-31244	59	56	through	through	ADP
fcis-31244	59	57	the	the	DET
fcis-31244	59	58	full	full	ADJ
fcis-31244	59	59	connection	connection	NOUN
fcis-31244	59	60	layer	layer	NOUN
fcis-31244	59	61	and	and	CCONJ
fcis-31244	59	62	softmax	softmax	NOUN
fcis-31244	59	63	layer	layer	NOUN
fcis-31244	59	64	after	after	ADP
fcis-31244	59	65	retaining	retain	VERB
fcis-31244	59	66	the	the	DET
fcis-31244	59	67	discriminative	discriminative	NOUN
fcis-31244	59	68	features	feature	NOUN
fcis-31244	59	69	.	.	PUNCT
fcis-31244	60	1	in	in	ADP
fcis-31244	60	2	the	the	DET
fcis-31244	60	3	module	module	NOUN
fcis-31244	60	4	level	level	NOUN
fcis-31244	60	5	dependency	dependency	NOUN
fcis-31244	60	6	,	,	PUNCT
fcis-31244	60	7	the	the	DET
fcis-31244	60	8	input	input	NOUN
fcis-31244	60	9	characteristic	characteristic	ADJ
fcis-31244	60	10	graph	graph	NOUN
fcis-31244	60	11	is	be	AUX
fcis-31244	60	12	divided	divide	VERB
fcis-31244	60	13	into	into	ADP
fcis-31244	60	14	two	two	NUM
fcis-31244	60	15	channels	channel	NOUN
fcis-31244	60	16	and	and	CCONJ
fcis-31244	60	17	sent	send	VERB
fcis-31244	60	18	to	to	ADP
fcis-31244	60	19	the	the	DET
fcis-31244	60	20	local	local	ADJ
fcis-31244	60	21	and	and	CCONJ
fcis-31244	60	22	global	global	ADJ
fcis-31244	60	23	information	information	NOUN
fcis-31244	60	24	processing	processing	NOUN
fcis-31244	60	25	flows	flow	VERB
fcis-31244	60	26	respectively	respectively	ADV
fcis-31244	60	27	.	.	PUNCT
fcis-31244	61	1	the	the	DET
fcis-31244	61	2	local	local	ADJ
fcis-31244	61	3	convolution	convolution	NOUN
fcis-31244	61	4	flow	flow	NOUN
fcis-31244	61	5	adopts	adopt	VERB
fcis-31244	61	6	the	the	DET
fcis-31244	61	7	mechanism	mechanism	NOUN
fcis-31244	61	8	of	of	ADP
fcis-31244	61	9	grouping	group	VERB
fcis-31244	61	10	convolution	convolution	NOUN
fcis-31244	61	11	and	and	CCONJ
fcis-31244	61	12	channel	channel	NOUN
fcis-31244	61	13	shuffling	shuffle	VERB
fcis-31244	61	14	to	to	PART
fcis-31244	61	15	extract	extract	VERB
fcis-31244	61	16	spatial	spatial	ADJ
fcis-31244	61	17	details	detail	NOUN
fcis-31244	61	18	and	and	CCONJ
fcis-31244	61	19	reduce	reduce	VERB
fcis-31244	61	20	the	the	DET
fcis-31244	61	21	computational	computational	ADJ
fcis-31244	61	22	complexity	complexity	NOUN
fcis-31244	61	23	.	.	PUNCT
fcis-31244	62	1	the	the	DET
fcis-31244	62	2	global	global	ADJ
fcis-31244	62	3	sequence	sequence	NOUN
fcis-31244	62	4	flow	flow	NOUN
fcis-31244	62	5	paves	pave	VERB
fcis-31244	62	6	the	the	DET
fcis-31244	62	7	feature	feature	NOUN
fcis-31244	62	8	map	map	NOUN
fcis-31244	62	9	into	into	ADP
fcis-31244	62	10	a	a	DET
fcis-31244	62	11	sequence	sequence	NOUN
fcis-31244	62	12	,	,	PUNCT
fcis-31244	62	13	and	and	CCONJ
fcis-31244	62	14	75	75	NUM
fcis-31244	62	15	uses	use	VERB
fcis-31244	62	16	ssm	ssm	PROPN
fcis-31244	62	17	to	to	PART
fcis-31244	62	18	model	model	VERB
fcis-31244	62	19	the	the	DET
fcis-31244	62	20	long	long	ADJ
fcis-31244	62	21	-	-	PUNCT
fcis-31244	62	22	distance	distance	NOUN
fcis-31244	62	23	spatio	spatio	NOUN
fcis-31244	62	24	-	-	PUNCT
fcis-31244	62	25	temporal	temporal	ADJ
fcis-31244	62	26	dependence	dependence	NOUN
fcis-31244	62	27	to	to	PART
fcis-31244	62	28	capture	capture	VERB
fcis-31244	62	29	the	the	DET
fcis-31244	62	30	dynamic	dynamic	ADJ
fcis-31244	62	31	continuity	continuity	NOUN
fcis-31244	62	32	of	of	ADP
fcis-31244	62	33	gestures	gesture	NOUN
fcis-31244	62	34	.	.	PUNCT
fcis-31244	63	1	finally	finally	ADV
fcis-31244	63	2	,	,	PUNCT
fcis-31244	63	3	the	the	DET
fcis-31244	63	4	learnable	learnable	ADJ
fcis-31244	63	5	weight	weight	NOUN
fcis-31244	63	6	is	be	AUX
fcis-31244	63	7	used	use	VERB
fcis-31244	63	8	to	to	PART
fcis-31244	63	9	fuse	fuse	VERB
fcis-31244	63	10	the	the	DET
fcis-31244	63	11	two	two	NUM
fcis-31244	63	12	stream	stream	NOUN
fcis-31244	63	13	features	feature	NOUN
fcis-31244	63	14	to	to	PART
fcis-31244	63	15	balance	balance	VERB
fcis-31244	63	16	the	the	DET
fcis-31244	63	17	local	local	ADJ
fcis-31244	63	18	details	detail	NOUN
fcis-31244	63	19	and	and	CCONJ
fcis-31244	63	20	global	global	ADJ
fcis-31244	63	21	features	feature	NOUN
fcis-31244	63	22	.	.	PUNCT
fcis-31244	64	1	fig	fig	NOUN
fcis-31244	64	2	1	1	NUM
fcis-31244	64	3	.	.	PUNCT
fcis-31244	65	1	overall	overall	ADJ
fcis-31244	65	2	network	network	NOUN
fcis-31244	65	3	process	process	NOUN
fcis-31244	65	4	at	at	ADP
fcis-31244	65	5	the	the	DET
fcis-31244	65	6	hardware	hardware	NOUN
fcis-31244	65	7	level	level	NOUN
fcis-31244	65	8	,	,	PUNCT
fcis-31244	65	9	the	the	DET
fcis-31244	65	10	pytoch	pytoch	ADJ
fcis-31244	65	11	model	model	NOUN
fcis-31244	65	12	is	be	AUX
fcis-31244	65	13	converted	convert	VERB
fcis-31244	65	14	to	to	ADP
fcis-31244	65	15	onnx	onnx	NOUN
fcis-31244	65	16	format	format	NOUN
fcis-31244	65	17	to	to	PART
fcis-31244	65	18	adapt	adapt	VERB
fcis-31244	65	19	to	to	ADP
fcis-31244	65	20	the	the	DET
fcis-31244	65	21	mainstream	mainstream	NOUN
fcis-31244	65	22	device	device	NOUN
fcis-31244	65	23	architecture	architecture	NOUN
fcis-31244	65	24	,	,	PUNCT
fcis-31244	65	25	and	and	CCONJ
fcis-31244	65	26	the	the	DET
fcis-31244	65	27	model	model	NOUN
fcis-31244	65	28	is	be	AUX
fcis-31244	65	29	quantified	quantify	VERB
fcis-31244	65	30	to	to	PART
fcis-31244	65	31	reduce	reduce	VERB
fcis-31244	65	32	the	the	DET
fcis-31244	65	33	model	model	NOUN
fcis-31244	65	34	volume	volume	NOUN
fcis-31244	65	35	.	.	PUNCT
fcis-31244	66	1	combined	combine	VERB
fcis-31244	66	2	with	with	ADP
fcis-31244	66	3	gradient	gradient	NOUN
fcis-31244	66	4	based	base	VERB
fcis-31244	66	5	unstructured	unstructured	ADJ
fcis-31244	66	6	pruning	pruning	NOUN
fcis-31244	66	7	,	,	PUNCT
fcis-31244	66	8	the	the	DET
fcis-31244	66	9	calculation	calculation	NOUN
fcis-31244	66	10	is	be	AUX
fcis-31244	66	11	further	far	ADV
fcis-31244	66	12	compressed	compress	VERB
fcis-31244	66	13	to	to	PART
fcis-31244	66	14	enable	enable	VERB
fcis-31244	66	15	it	it	PRON
fcis-31244	66	16	to	to	PART
fcis-31244	66	17	run	run	VERB
fcis-31244	66	18	on	on	ADP
fcis-31244	66	19	edge	edge	NOUN
fcis-31244	66	20	devices	device	NOUN
fcis-31244	66	21	.	.	PUNCT
fcis-31244	67	1	3.2	3.2	NUM
fcis-31244	67	2	.	.	PUNCT
fcis-31244	68	1	backbone	backbone	NOUN
fcis-31244	68	2	network	network	NOUN
fcis-31244	68	3	shufflenetv2	shufflenetv2	PROPN
fcis-31244	68	4	3.2.1	3.2.1	NUM
fcis-31244	68	5	.	.	PUNCT
fcis-31244	69	1	core	core	NOUN
fcis-31244	69	2	design	design	NOUN
fcis-31244	69	3	principles	principle	NOUN
fcis-31244	69	4	the	the	DET
fcis-31244	69	5	design	design	NOUN
fcis-31244	69	6	goal	goal	NOUN
fcis-31244	69	7	of	of	ADP
fcis-31244	69	8	shufflenetv2	shufflenetv2	NOUN
fcis-31244	69	9	is	be	AUX
fcis-31244	69	10	to	to	PART
fcis-31244	69	11	optimize	optimize	VERB
fcis-31244	69	12	the	the	DET
fcis-31244	69	13	reasoning	reasoning	NOUN
fcis-31244	69	14	efficiency	efficiency	NOUN
fcis-31244	69	15	of	of	ADP
fcis-31244	69	16	mobile	mobile	ADJ
fcis-31244	69	17	terminals	terminal	NOUN
fcis-31244	69	18	and	and	CCONJ
fcis-31244	69	19	embedded	embed	VERB
fcis-31244	69	20	edge	edge	NOUN
fcis-31244	69	21	devices	device	NOUN
fcis-31244	69	22	.	.	PUNCT
fcis-31244	70	1	its	its	PRON
fcis-31244	70	2	network	network	NOUN
fcis-31244	70	3	design	design	NOUN
fcis-31244	70	4	focuses	focus	VERB
fcis-31244	70	5	not	not	PART
fcis-31244	70	6	only	only	ADV
fcis-31244	70	7	on	on	ADP
fcis-31244	70	8	the	the	DET
fcis-31244	70	9	theoretical	theoretical	ADJ
fcis-31244	70	10	amount	amount	NOUN
fcis-31244	70	11	of	of	ADP
fcis-31244	70	12	computation	computation	NOUN
fcis-31244	70	13	(	(	PUNCT
fcis-31244	70	14	flops	flop	NOUN
fcis-31244	70	15	)	)	PUNCT
fcis-31244	70	16	,	,	PUNCT
fcis-31244	70	17	but	but	CCONJ
fcis-31244	70	18	also	also	ADV
fcis-31244	70	19	on	on	ADP
fcis-31244	70	20	the	the	DET
fcis-31244	70	21	actual	actual	ADJ
fcis-31244	70	22	running	running	NOUN
fcis-31244	70	23	speed	speed	NOUN
fcis-31244	70	24	and	and	CCONJ
fcis-31244	70	25	memory	memory	NOUN
fcis-31244	70	26	access	access	NOUN
fcis-31244	70	27	cost	cost	NOUN
fcis-31244	70	28	(	(	PUNCT
fcis-31244	70	29	mac	mac	PROPN
fcis-31244	70	30	)	)	PUNCT
fcis-31244	70	31	.	.	PUNCT
fcis-31244	71	1	according	accord	VERB
fcis-31244	71	2	to	to	ADP
fcis-31244	71	3	the	the	DET
fcis-31244	71	4	network	network	NOUN
fcis-31244	71	5	structure	structure	NOUN
fcis-31244	71	6	,	,	PUNCT
fcis-31244	71	7	when	when	SCONJ
fcis-31244	71	8	the	the	DET
fcis-31244	71	9	input	input	NOUN
fcis-31244	71	10	and	and	CCONJ
fcis-31244	71	11	output	output	NOUN
fcis-31244	71	12	channels	channel	NOUN
fcis-31244	71	13	are	be	AUX
fcis-31244	71	14	equal	equal	ADJ
fcis-31244	71	15	,	,	PUNCT
fcis-31244	71	16	the	the	DET
fcis-31244	71	17	memory	memory	NOUN
fcis-31244	71	18	access	access	NOUN
fcis-31244	71	19	cost	cost	NOUN
fcis-31244	71	20	(	(	PUNCT
fcis-31244	71	21	mac	mac	PROPN
fcis-31244	71	22	)	)	PUNCT
fcis-31244	71	23	is	be	AUX
fcis-31244	71	24	the	the	DET
fcis-31244	71	25	minimum	minimum	NOUN
fcis-31244	71	26	.	.	PUNCT
fcis-31244	72	1	in	in	ADP
fcis-31244	72	2	order	order	NOUN
fcis-31244	72	3	to	to	PART
fcis-31244	72	4	ensure	ensure	VERB
fcis-31244	72	5	the	the	DET
fcis-31244	72	6	memory	memory	NOUN
fcis-31244	72	7	exchange	exchange	NOUN
fcis-31244	72	8	efficiency	efficiency	NOUN
fcis-31244	72	9	,	,	PUNCT
fcis-31244	72	10	the	the	DET
fcis-31244	72	11	backbone	backbone	NOUN
fcis-31244	72	12	network	network	NOUN
fcis-31244	72	13	needs	need	VERB
fcis-31244	72	14	to	to	PART
fcis-31244	72	15	balance	balance	VERB
fcis-31244	72	16	the	the	DET
fcis-31244	72	17	channels	channel	NOUN
fcis-31244	72	18	.	.	PUNCT
fcis-31244	73	1	in	in	ADP
fcis-31244	73	2	the	the	DET
fcis-31244	73	3	optimized	optimize	VERB
fcis-31244	73	4	computational	computational	ADJ
fcis-31244	73	5	efficiency	efficiency	NOUN
fcis-31244	73	6	,	,	PUNCT
fcis-31244	73	7	deep	deep	ADJ
fcis-31244	73	8	convolution	convolution	NOUN
fcis-31244	73	9	:	:	PUNCT
fcis-31244	73	10	flops	flop	VERB
fcis-31244	73	11	⋅	⋅	PROPN
fcis-31244	73	12	⋅	⋅	PROPN
fcis-31244	73	13	⋅	⋅	PROPN
fcis-31244	73	14	4	4	NUM
fcis-31244	73	15	pointwise	pointwise	NOUN
fcis-31244	73	16	convolution	convolution	NOUN
fcis-31244	73	17	:	:	PUNCT
fcis-31244	73	18	flop	flop	VERB
fcis-31244	73	19	1	1	NUM
fcis-31244	73	20	⋅	⋅	PROPN
fcis-31244	73	21	⋅	⋅	PROPN
fcis-31244	73	22	⋅	⋅	PROPN
fcis-31244	73	23	⋅	⋅	PROPN
fcis-31244	73	24	5	5	NUM
fcis-31244	73	25	the	the	DET
fcis-31244	73	26	total	total	ADJ
fcis-31244	73	27	amount	amount	NOUN
fcis-31244	73	28	of	of	ADP
fcis-31244	73	29	calculation	calculation	NOUN
fcis-31244	73	30	is	be	AUX
fcis-31244	73	31	the	the	DET
fcis-31244	73	32	sum	sum	NOUN
fcis-31244	73	33	of	of	ADP
fcis-31244	73	34	the	the	DET
fcis-31244	73	35	above	above	ADJ
fcis-31244	73	36	two	two	NUM
fcis-31244	73	37	,	,	PUNCT
fcis-31244	73	38	compared	compare	VERB
fcis-31244	73	39	with	with	ADP
fcis-31244	73	40	the	the	DET
fcis-31244	73	41	standard	standard	ADJ
fcis-31244	73	42	convolution	convolution	NOUN
fcis-31244	73	43	calculation	calculation	NOUN
fcis-31244	73	44	,	,	PUNCT
fcis-31244	73	45	can	can	AUX
fcis-31244	73	46	reduce	reduce	VERB
fcis-31244	73	47	the	the	DET
fcis-31244	73	48	amount	amount	NOUN
fcis-31244	73	49	of	of	ADP
fcis-31244	73	50	calculation	calculation	NOUN
fcis-31244	73	51	by	by	ADP
fcis-31244	73	52	1/	1/	NUM
fcis-31244	73	53	1/	1/	NUM
fcis-31244	73	54	times	time	NOUN
fcis-31244	73	55	.	.	PUNCT
fcis-31244	74	1	the	the	DET
fcis-31244	74	2	two	two	NUM
fcis-31244	74	3	main	main	ADJ
fcis-31244	74	4	technical	technical	ADJ
fcis-31244	74	5	features	feature	NOUN
fcis-31244	74	6	of	of	ADP
fcis-31244	74	7	backbone	backbone	NOUN
fcis-31244	74	8	network	network	NOUN
fcis-31244	74	9	:	:	PUNCT
fcis-31244	74	10	packet	packet	NOUN
fcis-31244	74	11	convolution	convolution	NOUN
fcis-31244	74	12	and	and	CCONJ
fcis-31244	74	13	channel	channel	NOUN
fcis-31244	74	14	shuffling	shuffling	NOUN
fcis-31244	74	15	will	will	AUX
fcis-31244	74	16	also	also	ADV
fcis-31244	74	17	affect	affect	VERB
fcis-31244	74	18	the	the	DET
fcis-31244	74	19	overall	overall	ADJ
fcis-31244	74	20	reasoning	reasoning	NOUN
fcis-31244	74	21	speed	speed	NOUN
fcis-31244	74	22	.	.	PUNCT
fcis-31244	75	1	although	although	SCONJ
fcis-31244	75	2	packet	packet	NOUN
fcis-31244	75	3	convolution	convolution	NOUN
fcis-31244	75	4	will	will	AUX
fcis-31244	75	5	reduce	reduce	VERB
fcis-31244	75	6	flops	flop	NOUN
fcis-31244	75	7	,	,	PUNCT
fcis-31244	75	8	it	it	PRON
fcis-31244	75	9	will	will	AUX
fcis-31244	75	10	increase	increase	VERB
fcis-31244	75	11	mac	mac	PROPN
fcis-31244	75	12	.	.	PUNCT
fcis-31244	76	1	according	accord	VERB
fcis-31244	76	2	to	to	ADP
fcis-31244	76	3	the	the	DET
fcis-31244	76	4	experiment	experiment	NOUN
fcis-31244	76	5	,	,	PUNCT
fcis-31244	76	6	the	the	PRON
fcis-31244	76	7	larger	large	ADJ
fcis-31244	76	8	the	the	DET
fcis-31244	76	9	packet	packet	NOUN
fcis-31244	76	10	is	be	AUX
fcis-31244	76	11	,	,	PUNCT
fcis-31244	76	12	the	the	PRON
fcis-31244	76	13	slower	slow	ADJ
fcis-31244	76	14	the	the	DET
fcis-31244	76	15	reasoning	reasoning	NOUN
fcis-31244	76	16	speed	speed	NOUN
fcis-31244	76	17	is	be	AUX
fcis-31244	76	18	.	.	PUNCT
fcis-31244	77	1	when	when	SCONJ
fcis-31244	77	2	the	the	DET
fcis-31244	77	3	number	number	NOUN
fcis-31244	77	4	of	of	ADP
fcis-31244	77	5	packets	packet	NOUN
fcis-31244	77	6	increases	increase	NOUN
fcis-31244	77	7	from	from	ADP
fcis-31244	77	8	1	1	NUM
fcis-31244	77	9	to	to	ADP
fcis-31244	77	10	8	8	NUM
fcis-31244	77	11	,	,	PUNCT
fcis-31244	77	12	the	the	DET
fcis-31244	77	13	gpu	gpu	NOUN
fcis-31244	77	14	reasoning	reasoning	NOUN
fcis-31244	77	15	speed	speed	NOUN
fcis-31244	77	16	decreases	decrease	VERB
fcis-31244	77	17	to	to	ADP
fcis-31244	77	18	1/4	1/4	NUM
fcis-31244	77	19	.	.	PUNCT
fcis-31244	78	1	in	in	ADP
fcis-31244	78	2	dealing	deal	VERB
fcis-31244	78	3	with	with	ADP
fcis-31244	78	4	network	network	NOUN
fcis-31244	78	5	fragmentation	fragmentation	NOUN
fcis-31244	78	6	,	,	PUNCT
fcis-31244	78	7	the	the	DET
fcis-31244	78	8	concept	concept	NOUN
fcis-31244	78	9	structure	structure	NOUN
fcis-31244	78	10	will	will	AUX
fcis-31244	78	11	reduce	reduce	VERB
fcis-31244	78	12	the	the	DET
fcis-31244	78	13	parallelism	parallelism	NOUN
fcis-31244	78	14	and	and	CCONJ
fcis-31244	78	15	increase	increase	VERB
fcis-31244	78	16	the	the	DET
fcis-31244	78	17	synchronization	synchronization	NOUN
fcis-31244	78	18	overhead	overhead	ADV
fcis-31244	78	19	,	,	PUNCT
fcis-31244	78	20	so	so	ADV
fcis-31244	78	21	the	the	DET
fcis-31244	78	22	network	network	NOUN
fcis-31244	78	23	structure	structure	NOUN
fcis-31244	78	24	adopts	adopt	VERB
fcis-31244	78	25	a	a	DET
fcis-31244	78	26	simple	simple	ADJ
fcis-31244	78	27	single	single	ADJ
fcis-31244	78	28	branch	branch	NOUN
fcis-31244	78	29	structure	structure	NOUN
fcis-31244	78	30	to	to	PART
fcis-31244	78	31	improve	improve	VERB
fcis-31244	78	32	the	the	DET
fcis-31244	78	33	efficiency	efficiency	NOUN
fcis-31244	78	34	of	of	ADP
fcis-31244	78	35	parallel	parallel	ADJ
fcis-31244	78	36	devices	device	NOUN
fcis-31244	78	37	.	.	PUNCT
fcis-31244	79	1	3.2.2	3.2.2	NUM
fcis-31244	79	2	.	.	PUNCT
fcis-31244	79	3	structural	structural	ADJ
fcis-31244	79	4	features	feature	VERB
fcis-31244	79	5	the	the	DET
fcis-31244	79	6	input	input	NOUN
fcis-31244	79	7	channel	channel	NOUN
fcis-31244	79	8	of	of	ADP
fcis-31244	79	9	the	the	DET
fcis-31244	79	10	common	common	ADJ
fcis-31244	79	11	unit	unit	NOUN
fcis-31244	79	12	in	in	ADP
fcis-31244	79	13	the	the	DET
fcis-31244	79	14	shufflenetv2	shufflenetv2	NOUN
fcis-31244	79	15	structure	structure	NOUN
fcis-31244	79	16	is	be	AUX
fcis-31244	79	17	divided	divide	VERB
fcis-31244	79	18	into	into	ADP
fcis-31244	79	19	two	two	NUM
fcis-31244	79	20	parts	part	NOUN
fcis-31244	79	21	.	.	PUNCT
fcis-31244	80	1	one	one	NUM
fcis-31244	80	2	part	part	NOUN
fcis-31244	80	3	is	be	AUX
fcis-31244	80	4	processed	process	VERB
fcis-31244	80	5	by	by	ADP
fcis-31244	80	6	deep	deep	ADJ
fcis-31244	80	7	separable	separable	ADJ
fcis-31244	80	8	convolution	convolution	NOUN
fcis-31244	80	9	and	and	CCONJ
fcis-31244	80	10	1x1	1x1	NUM
fcis-31244	80	11	convolution	convolution	NOUN
fcis-31244	80	12	.	.	PUNCT
fcis-31244	81	1	the	the	DET
fcis-31244	81	2	other	other	ADJ
fcis-31244	81	3	part	part	NOUN
fcis-31244	81	4	is	be	AUX
fcis-31244	81	5	direct	direct	ADJ
fcis-31244	81	6	identity	identity	NOUN
fcis-31244	81	7	mapping	mapping	NOUN
fcis-31244	81	8	.	.	PUNCT
fcis-31244	82	1	finally	finally	ADV
fcis-31244	82	2	,	,	PUNCT
fcis-31244	82	3	the	the	DET
fcis-31244	82	4	stitching	stitching	NOUN
fcis-31244	82	5	is	be	AUX
fcis-31244	82	6	through	through	ADP
fcis-31244	82	7	channel	channel	NOUN
fcis-31244	82	8	shuffle	shuffle	NOUN
fcis-31244	82	9	to	to	PART
fcis-31244	82	10	enhance	enhance	VERB
fcis-31244	82	11	the	the	DET
fcis-31244	82	12	interaction	interaction	NOUN
fcis-31244	82	13	of	of	ADP
fcis-31244	82	14	information	information	NOUN
fcis-31244	82	15	.	.	PUNCT
fcis-31244	83	1	at	at	ADP
fcis-31244	83	2	the	the	DET
fcis-31244	83	3	same	same	ADJ
fcis-31244	83	4	time	time	NOUN
fcis-31244	83	5	,	,	PUNCT
fcis-31244	83	6	the	the	DET
fcis-31244	83	7	channel	channel	NOUN
fcis-31244	83	8	segmentation	segmentation	NOUN
fcis-31244	83	9	is	be	AUX
fcis-31244	83	10	canceled	cancel	VERB
fcis-31244	83	11	,	,	PUNCT
fcis-31244	83	12	and	and	CCONJ
fcis-31244	83	13	the	the	DET
fcis-31244	83	14	spatial	spatial	ADJ
fcis-31244	83	15	down	down	ADV
fcis-31244	83	16	sampling	sample	VERB
fcis-31244	83	17	and	and	CCONJ
fcis-31244	83	18	channel	channel	NOUN
fcis-31244	83	19	expansion	expansion	NOUN
fcis-31244	83	20	are	be	AUX
fcis-31244	83	21	directly	directly	ADV
fcis-31244	83	22	realized	realize	VERB
fcis-31244	83	23	through	through	ADP
fcis-31244	83	24	the	the	DET
fcis-31244	83	25	convolution	convolution	NOUN
fcis-31244	83	26	with	with	ADP
fcis-31244	83	27	step	step	NOUN
fcis-31244	83	28	size	size	NOUN
fcis-31244	83	29	of	of	ADP
fcis-31244	83	30	2	2	NUM
fcis-31244	83	31	to	to	PART
fcis-31244	83	32	maintain	maintain	VERB
fcis-31244	83	33	low	low	ADJ
fcis-31244	83	34	mac	mac	PROPN
fcis-31244	83	35	.	.	PUNCT
fcis-31244	84	1	the	the	DET
fcis-31244	84	2	channel	channel	NOUN
fcis-31244	84	3	shuffling	shuffling	NOUN
fcis-31244	84	4	mechanism	mechanism	NOUN
fcis-31244	84	5	can	can	AUX
fcis-31244	84	6	improve	improve	VERB
fcis-31244	84	7	the	the	DET
fcis-31244	84	8	expression	expression	NOUN
fcis-31244	84	9	ability	ability	NOUN
fcis-31244	84	10	of	of	ADP
fcis-31244	84	11	the	the	DET
fcis-31244	84	12	model	model	NOUN
fcis-31244	84	13	and	and	CCONJ
fcis-31244	84	14	reduce	reduce	VERB
fcis-31244	84	15	the	the	DET
fcis-31244	84	16	computational	computational	ADJ
fcis-31244	84	17	fragmentation	fragmentation	NOUN
fcis-31244	84	18	.	.	PUNCT
fcis-31244	85	1	usually	usually	ADV
fcis-31244	85	2	,	,	PUNCT
fcis-31244	85	3	the	the	DET
fcis-31244	85	4	shuffling	shuffle	VERB
fcis-31244	85	5	operation	operation	NOUN
fcis-31244	85	6	is	be	AUX
fcis-31244	85	7	performed	perform	VERB
fcis-31244	85	8	after	after	ADP
fcis-31244	85	9	splicing	splicing	NOUN
fcis-31244	85	10	,	,	PUNCT
fcis-31244	85	11	combined	combine	VERB
fcis-31244	85	12	with	with	ADP
fcis-31244	85	13	convolution	convolution	NOUN
fcis-31244	85	14	operation	operation	NOUN
fcis-31244	85	15	to	to	PART
fcis-31244	85	16	achieve	achieve	VERB
fcis-31244	85	17	efficient	efficient	ADJ
fcis-31244	85	18	feature	feature	NOUN
fcis-31244	85	19	fusion	fusion	NOUN
fcis-31244	85	20	.	.	PUNCT
fcis-31244	86	1	the	the	DET
fcis-31244	86	2	deep	deep	ADJ
fcis-31244	86	3	separable	separable	ADJ
fcis-31244	86	4	convolution	convolution	NOUN
fcis-31244	86	5	is	be	AUX
fcis-31244	86	6	adopted	adopt	VERB
fcis-31244	86	7	to	to	PART
fcis-31244	86	8	replace	replace	VERB
fcis-31244	86	9	the	the	DET
fcis-31244	86	10	standard	standard	ADJ
fcis-31244	86	11	convolution	convolution	NOUN
fcis-31244	86	12	,	,	PUNCT
fcis-31244	86	13	which	which	PRON
fcis-31244	86	14	reduces	reduce	VERB
fcis-31244	86	15	the	the	DET
fcis-31244	86	16	parameters	parameter	NOUN
fcis-31244	86	17	and	and	CCONJ
fcis-31244	86	18	the	the	DET
fcis-31244	86	19	amount	amount	NOUN
fcis-31244	86	20	of	of	ADP
fcis-31244	86	21	calculation	calculation	NOUN
fcis-31244	86	22	,	,	PUNCT
fcis-31244	86	23	and	and	CCONJ
fcis-31244	86	24	has	have	VERB
fcis-31244	86	25	different	different	ADJ
fcis-31244	86	26	network	network	NOUN
fcis-31244	86	27	widths	width	NOUN
fcis-31244	86	28	to	to	PART
fcis-31244	86	29	adapt	adapt	VERB
fcis-31244	86	30	to	to	ADP
fcis-31244	86	31	the	the	DET
fcis-31244	86	32	equipment	equipment	NOUN
fcis-31244	86	33	with	with	ADP
fcis-31244	86	34	different	different	ADJ
fcis-31244	86	35	resource	resource	NOUN
fcis-31244	86	36	constraints	constraint	NOUN
fcis-31244	86	37	.	.	PUNCT
fcis-31244	87	1	76	76	NUM
fcis-31244	87	2	3.2.3	3.2.3	NUM
fcis-31244	87	3	.	.	PUNCT
fcis-31244	87	4	shufflenetv2	shufflenetv2	NOUN
fcis-31244	87	5	structure	structure	NOUN
fcis-31244	87	6	integrated	integrate	VERB
fcis-31244	87	7	with	with	ADP
fcis-31244	87	8	mamba	mamba	PROPN
fcis-31244	87	9	block	block	PROPN
fcis-31244	87	10	the	the	DET
fcis-31244	87	11	purpose	purpose	NOUN
fcis-31244	87	12	of	of	ADP
fcis-31244	87	13	fusing	fuse	VERB
fcis-31244	87	14	the	the	DET
fcis-31244	87	15	shufflenetv2	shufflenetv2	NOUN
fcis-31244	87	16	structure	structure	NOUN
fcis-31244	87	17	of	of	ADP
fcis-31244	87	18	mamba	mamba	PROPN
fcis-31244	87	19	block	block	NOUN
fcis-31244	87	20	is	be	AUX
fcis-31244	87	21	to	to	PART
fcis-31244	87	22	solve	solve	VERB
fcis-31244	87	23	the	the	DET
fcis-31244	87	24	balance	balance	NOUN
fcis-31244	87	25	problem	problem	NOUN
fcis-31244	87	26	between	between	ADP
fcis-31244	87	27	computational	computational	ADJ
fcis-31244	87	28	efficiency	efficiency	NOUN
fcis-31244	87	29	and	and	CCONJ
fcis-31244	87	30	temporal	temporal	ADJ
fcis-31244	87	31	modeling	modeling	NOUN
fcis-31244	87	32	ability	ability	NOUN
fcis-31244	87	33	in	in	ADP
fcis-31244	87	34	dynamic	dynamic	ADJ
fcis-31244	87	35	gesture	gesture	NOUN
fcis-31244	87	36	recognition	recognition	NOUN
fcis-31244	87	37	by	by	ADP
fcis-31244	87	38	combining	combine	VERB
fcis-31244	87	39	the	the	DET
fcis-31244	87	40	efficient	efficient	ADJ
fcis-31244	87	41	spatial	spatial	ADJ
fcis-31244	87	42	feature	feature	NOUN
fcis-31244	87	43	extraction	extraction	NOUN
fcis-31244	87	44	ability	ability	NOUN
fcis-31244	87	45	of	of	ADP
fcis-31244	87	46	lightweight	lightweight	ADJ
fcis-31244	87	47	convolutional	convolutional	ADJ
fcis-31244	87	48	network	network	NOUN
fcis-31244	87	49	and	and	CCONJ
fcis-31244	87	50	mamba	mamba	NOUN
fcis-31244	87	51	's	's	PART
fcis-31244	87	52	long	long	ADJ
fcis-31244	87	53	sequence	sequence	NOUN
fcis-31244	87	54	modeling	model	VERB
fcis-31244	87	55	advantage	advantage	NOUN
fcis-31244	87	56	.	.	PUNCT
fcis-31244	88	1	its	its	PRON
fcis-31244	88	2	core	core	NOUN
fcis-31244	88	3	structure	structure	NOUN
fcis-31244	88	4	is	be	AUX
fcis-31244	88	5	shown	show	VERB
fcis-31244	88	6	in	in	ADP
fcis-31244	88	7	figure	figure	NOUN
fcis-31244	88	8	2	2	NUM
fcis-31244	88	9	.	.	PUNCT
fcis-31244	88	10	fig	fig	NOUN
fcis-31244	88	11	2	2	NUM
fcis-31244	88	12	.	.	PUNCT
fcis-31244	88	13	fusion	fusion	NOUN
fcis-31244	88	14	model	model	NOUN
fcis-31244	88	15	structure	structure	NOUN
fcis-31244	88	16	after	after	ADP
fcis-31244	88	17	inputting	inputte	VERB
fcis-31244	88	18	the	the	DET
fcis-31244	88	19	dynamic	dynamic	ADJ
fcis-31244	88	20	gesture	gesture	NOUN
fcis-31244	88	21	video	video	NOUN
fcis-31244	88	22	sequence	sequence	NOUN
fcis-31244	88	23	,	,	PUNCT
fcis-31244	88	24	it	it	PRON
fcis-31244	88	25	is	be	AUX
fcis-31244	88	26	divided	divide	VERB
fcis-31244	88	27	into	into	ADP
fcis-31244	88	28	three	three	NUM
fcis-31244	88	29	parts	part	NOUN
fcis-31244	88	30	through	through	ADP
fcis-31244	88	31	channel	channel	NOUN
fcis-31244	88	32	segmentation	segmentation	NOUN
fcis-31244	88	33	.	.	PUNCT
fcis-31244	89	1	the	the	DET
fcis-31244	89	2	first	first	ADJ
fcis-31244	89	3	part	part	NOUN
fcis-31244	89	4	extracts	extract	VERB
fcis-31244	89	5	the	the	DET
fcis-31244	89	6	low	low	ADJ
fcis-31244	89	7	-	-	PUNCT
fcis-31244	89	8	order	order	NOUN
fcis-31244	89	9	local	local	ADJ
fcis-31244	89	10	spatial	spatial	ADJ
fcis-31244	89	11	details	detail	NOUN
fcis-31244	89	12	of	of	ADP
fcis-31244	89	13	finger	finger	NOUN
fcis-31244	89	14	posture	posture	NOUN
fcis-31244	89	15	through	through	ADP
fcis-31244	89	16	a	a	DET
fcis-31244	89	17	series	series	NOUN
fcis-31244	89	18	of	of	ADP
fcis-31244	89	19	calculations	calculation	NOUN
fcis-31244	89	20	such	such	ADJ
fcis-31244	89	21	as	as	ADP
fcis-31244	89	22	the	the	DET
fcis-31244	89	23	initial	initial	ADJ
fcis-31244	89	24	convolution	convolution	NOUN
fcis-31244	89	25	layer	layer	NOUN
fcis-31244	89	26	of	of	ADP
fcis-31244	89	27	shufflenet	shufflenet	NOUN
fcis-31244	89	28	module	module	NOUN
fcis-31244	89	29	,	,	PUNCT
fcis-31244	89	30	the	the	DET
fcis-31244	89	31	depth	depth	NOUN
fcis-31244	89	32	separable	separable	ADJ
fcis-31244	89	33	convolution	convolution	NOUN
fcis-31244	89	34	layer	layer	NOUN
fcis-31244	89	35	and	and	CCONJ
fcis-31244	89	36	point	point	NOUN
fcis-31244	89	37	-	-	PUNCT
fcis-31244	89	38	by	by	ADP
fcis-31244	89	39	-	-	PUNCT
fcis-31244	89	40	point	point	NOUN
fcis-31244	89	41	convolution	convolution	NOUN
fcis-31244	89	42	.	.	PUNCT
fcis-31244	90	1	in	in	ADP
fcis-31244	90	2	the	the	DET
fcis-31244	90	3	second	second	ADJ
fcis-31244	90	4	part	part	NOUN
fcis-31244	90	5	,	,	PUNCT
fcis-31244	90	6	the	the	DET
fcis-31244	90	7	feature	feature	NOUN
fcis-31244	90	8	map	map	NOUN
fcis-31244	90	9	is	be	AUX
fcis-31244	90	10	rearranged	rearrange	VERB
fcis-31244	90	11	into	into	ADP
fcis-31244	90	12	sequences	sequence	NOUN
fcis-31244	90	13	and	and	CCONJ
fcis-31244	90	14	input	input	NOUN
fcis-31244	90	15	into	into	ADP
fcis-31244	90	16	mamba	mamba	PROPN
fcis-31244	90	17	's	's	PART
fcis-31244	90	18	state	state	NOUN
fcis-31244	90	19	space	space	NOUN
fcis-31244	90	20	model	model	NOUN
fcis-31244	90	21	(	(	PUNCT
fcis-31244	90	22	ssm	ssm	PROPN
fcis-31244	90	23	)	)	PUNCT
fcis-31244	90	24	to	to	PART
fcis-31244	90	25	capture	capture	VERB
fcis-31244	90	26	the	the	DET
fcis-31244	90	27	motion	motion	NOUN
fcis-31244	90	28	dependence	dependence	NOUN
fcis-31244	90	29	between	between	ADP
fcis-31244	90	30	frames	frame	NOUN
fcis-31244	90	31	,	,	PUNCT
fcis-31244	90	32	such	such	ADJ
fcis-31244	90	33	as	as	ADP
fcis-31244	90	34	the	the	DET
fcis-31244	90	35	waving	wave	VERB
fcis-31244	90	36	trajectory	trajectory	NOUN
fcis-31244	90	37	,	,	PUNCT
fcis-31244	90	38	and	and	CCONJ
fcis-31244	90	39	then	then	ADV
fcis-31244	90	40	the	the	DET
fcis-31244	90	41	spatial	spatial	ADJ
fcis-31244	90	42	dimension	dimension	NOUN
fcis-31244	90	43	is	be	AUX
fcis-31244	90	44	restored	restore	VERB
fcis-31244	90	45	by	by	ADP
fcis-31244	90	46	reverse	reverse	ADJ
fcis-31244	90	47	rearrangement	rearrangement	NOUN
fcis-31244	90	48	.	.	PUNCT
fcis-31244	91	1	the	the	DET
fcis-31244	91	2	last	last	ADJ
fcis-31244	91	3	part	part	NOUN
fcis-31244	91	4	is	be	AUX
fcis-31244	91	5	the	the	DET
fcis-31244	91	6	feature	feature	NOUN
fcis-31244	91	7	fusion	fusion	NOUN
fcis-31244	91	8	of	of	ADP
fcis-31244	91	9	the	the	DET
fcis-31244	91	10	residual	residual	ADJ
fcis-31244	91	11	layer	layer	NOUN
fcis-31244	91	12	and	and	CCONJ
fcis-31244	91	13	the	the	DET
fcis-31244	91	14	two	two	NUM
fcis-31244	91	15	layers	layer	NOUN
fcis-31244	91	16	after	after	ADP
fcis-31244	91	17	the	the	DET
fcis-31244	91	18	simple	simple	ADJ
fcis-31244	91	19	shallow	shallow	ADJ
fcis-31244	91	20	feature	feature	NOUN
fcis-31244	91	21	extraction	extraction	NOUN
fcis-31244	91	22	,	,	PUNCT
fcis-31244	91	23	and	and	CCONJ
fcis-31244	91	24	the	the	DET
fcis-31244	91	25	three	three	NUM
fcis-31244	91	26	parts	part	NOUN
fcis-31244	91	27	are	be	AUX
fcis-31244	91	28	output	output	NOUN
fcis-31244	91	29	and	and	CCONJ
fcis-31244	91	30	spliced	splice	VERB
fcis-31244	91	31	to	to	PART
fcis-31244	91	32	perform	perform	VERB
fcis-31244	91	33	the	the	DET
fcis-31244	91	34	channel	channel	NOUN
fcis-31244	91	35	shuffling	shuffle	VERB
fcis-31244	91	36	operation	operation	NOUN
fcis-31244	91	37	.	.	PUNCT
fcis-31244	92	1	after	after	SCONJ
fcis-31244	92	2	the	the	DET
fcis-31244	92	3	final	final	ADJ
fcis-31244	92	4	feature	feature	NOUN
fcis-31244	92	5	is	be	AUX
fcis-31244	92	6	pooled	pool	VERB
fcis-31244	92	7	by	by	ADP
fcis-31244	92	8	the	the	DET
fcis-31244	92	9	global	global	ADJ
fcis-31244	92	10	average	average	NOUN
fcis-31244	92	11	,	,	PUNCT
fcis-31244	92	12	the	the	DET
fcis-31244	92	13	gesture	gesture	NOUN
fcis-31244	92	14	category	category	NOUN
fcis-31244	92	15	probability	probability	NOUN
fcis-31244	92	16	is	be	AUX
fcis-31244	92	17	output	output	NOUN
fcis-31244	92	18	through	through	ADP
fcis-31244	92	19	the	the	DET
fcis-31244	92	20	classification	classification	NOUN
fcis-31244	92	21	layer	layer	NOUN
fcis-31244	92	22	.	.	PUNCT
fcis-31244	93	1	4	4	X
fcis-31244	93	2	.	.	X
fcis-31244	93	3	experiment	experiment	NOUN
fcis-31244	93	4	in	in	ADP
fcis-31244	93	5	this	this	DET
fcis-31244	93	6	paper	paper	NOUN
fcis-31244	93	7	,	,	PUNCT
fcis-31244	93	8	shufflenetv2	shufflenetv2	NOUN
fcis-31244	93	9	-	-	PUNCT
fcis-31244	93	10	mamba	mamba	PROPN
fcis-31244	93	11	is	be	AUX
fcis-31244	93	12	compared	compare	VERB
fcis-31244	93	13	with	with	ADP
fcis-31244	93	14	the	the	DET
fcis-31244	93	15	existing	exist	VERB
fcis-31244	93	16	popular	popular	ADJ
fcis-31244	93	17	model	model	NOUN
fcis-31244	93	18	to	to	PART
fcis-31244	93	19	evaluate	evaluate	VERB
fcis-31244	93	20	the	the	DET
fcis-31244	93	21	performance	performance	NOUN
fcis-31244	93	22	of	of	ADP
fcis-31244	93	23	the	the	DET
fcis-31244	93	24	model	model	NOUN
fcis-31244	93	25	.	.	PUNCT
fcis-31244	94	1	the	the	DET
fcis-31244	94	2	evaluation	evaluation	NOUN
fcis-31244	94	3	results	result	VERB
fcis-31244	94	4	on	on	ADP
fcis-31244	94	5	the	the	DET
fcis-31244	94	6	above	above	ADJ
fcis-31244	94	7	data	data	NOUN
fcis-31244	94	8	sets	set	NOUN
fcis-31244	94	9	show	show	VERB
fcis-31244	94	10	that	that	SCONJ
fcis-31244	94	11	the	the	DET
fcis-31244	94	12	overall	overall	ADJ
fcis-31244	94	13	performance	performance	NOUN
fcis-31244	94	14	of	of	ADP
fcis-31244	94	15	the	the	DET
fcis-31244	94	16	model	model	NOUN
fcis-31244	94	17	proposed	propose	VERB
fcis-31244	94	18	in	in	ADP
fcis-31244	94	19	this	this	DET
fcis-31244	94	20	paper	paper	NOUN
fcis-31244	94	21	is	be	AUX
fcis-31244	94	22	excellent	excellent	ADJ
fcis-31244	94	23	.	.	PUNCT
fcis-31244	95	1	4.1	4.1	NUM
fcis-31244	95	2	.	.	PUNCT
fcis-31244	95	3	experimental	experimental	ADJ
fcis-31244	95	4	data	datum	NOUN
fcis-31244	95	5	and	and	CCONJ
fcis-31244	95	6	evaluation	evaluation	NOUN
fcis-31244	95	7	criteria	criterion	NOUN
fcis-31244	95	8	the	the	DET
fcis-31244	95	9	data	datum	NOUN
fcis-31244	95	10	set	set	VERB
fcis-31244	95	11	used	use	VERB
fcis-31244	95	12	in	in	ADP
fcis-31244	95	13	this	this	DET
fcis-31244	95	14	experiment	experiment	NOUN
fcis-31244	95	15	contains	contain	VERB
fcis-31244	95	16	the	the	DET
fcis-31244	95	17	specific	specific	ADJ
fcis-31244	95	18	dynamic	dynamic	ADJ
fcis-31244	95	19	gestures	gesture	NOUN
fcis-31244	95	20	in	in	ADP
fcis-31244	95	21	the	the	DET
fcis-31244	95	22	first	first	ADJ
fcis-31244	95	23	person	person	NOUN
fcis-31244	95	24	and	and	CCONJ
fcis-31244	95	25	home	home	NOUN
fcis-31244	95	26	monitoring	monitoring	NOUN
fcis-31244	95	27	.	.	PUNCT
fcis-31244	96	1	in	in	ADP
fcis-31244	96	2	these	these	DET
fcis-31244	96	3	dynamic	dynamic	ADJ
fcis-31244	96	4	data	datum	NOUN
fcis-31244	96	5	sets	set	NOUN
fcis-31244	96	6	,	,	PUNCT
fcis-31244	96	7	including	include	VERB
fcis-31244	96	8	seven	seven	NUM
fcis-31244	96	9	kinds	kind	NOUN
fcis-31244	96	10	of	of	ADP
fcis-31244	96	11	dynamic	dynamic	ADJ
fcis-31244	96	12	gestures	gesture	NOUN
fcis-31244	96	13	such	such	ADJ
fcis-31244	96	14	as	as	ADP
fcis-31244	96	15	sliding	slide	VERB
fcis-31244	96	16	up	up	ADP
fcis-31244	96	17	and	and	CCONJ
fcis-31244	96	18	sliding	slide	VERB
fcis-31244	96	19	down	down	ADP
fcis-31244	96	20	under	under	ADP
fcis-31244	96	21	different	different	ADJ
fcis-31244	96	22	lighting	lighting	NOUN
fcis-31244	96	23	conditions	condition	NOUN
fcis-31244	96	24	and	and	CCONJ
fcis-31244	96	25	different	different	ADJ
fcis-31244	96	26	viewing	viewing	NOUN
fcis-31244	96	27	angles	angle	NOUN
fcis-31244	96	28	.	.	PUNCT
fcis-31244	97	1	in	in	ADP
fcis-31244	97	2	these	these	DET
fcis-31244	97	3	different	different	ADJ
fcis-31244	97	4	types	type	NOUN
fcis-31244	97	5	of	of	ADP
fcis-31244	97	6	data	datum	NOUN
fcis-31244	97	7	sets	set	NOUN
fcis-31244	97	8	,	,	PUNCT
fcis-31244	97	9	the	the	DET
fcis-31244	97	10	number	number	NOUN
fcis-31244	97	11	of	of	ADP
fcis-31244	97	12	single	single	ADJ
fcis-31244	97	13	categories	category	NOUN
fcis-31244	97	14	of	of	ADP
fcis-31244	97	15	all	all	DET
fcis-31244	97	16	gestures	gesture	NOUN
fcis-31244	97	17	is	be	AUX
fcis-31244	97	18	the	the	DET
fcis-31244	97	19	same	same	ADJ
fcis-31244	97	20	.	.	PUNCT
fcis-31244	98	1	due	due	ADP
fcis-31244	98	2	to	to	ADP
fcis-31244	98	3	the	the	DET
fcis-31244	98	4	influence	influence	NOUN
fcis-31244	98	5	of	of	ADP
fcis-31244	98	6	illumination	illumination	NOUN
fcis-31244	98	7	,	,	PUNCT
fcis-31244	98	8	the	the	DET
fcis-31244	98	9	model	model	NOUN
fcis-31244	98	10	needs	need	VERB
fcis-31244	98	11	to	to	PART
fcis-31244	98	12	have	have	VERB
fcis-31244	98	13	strong	strong	ADJ
fcis-31244	98	14	detail	detail	NOUN
fcis-31244	98	15	extraction	extraction	NOUN
fcis-31244	98	16	ability	ability	NOUN
fcis-31244	98	17	and	and	CCONJ
fcis-31244	98	18	noise	noise	NOUN
fcis-31244	98	19	tolerance[14	tolerance[14	PROPN
fcis-31244	98	20	]	]	PUNCT
fcis-31244	98	21	.	.	PUNCT
fcis-31244	99	1	on	on	ADP
fcis-31244	99	2	the	the	DET
fcis-31244	99	3	data	datum	NOUN
fcis-31244	99	4	set	set	VERB
fcis-31244	99	5	of	of	ADP
fcis-31244	99	6	partial	partial	ADJ
fcis-31244	99	7	gesture	gesture	NOUN
fcis-31244	99	8	inching	inch	VERB
fcis-31244	99	9	,	,	PUNCT
fcis-31244	99	10	the	the	DET
fcis-31244	99	11	model	model	NOUN
fcis-31244	99	12	must	must	AUX
fcis-31244	99	13	be	be	AUX
fcis-31244	99	14	able	able	ADJ
fcis-31244	99	15	to	to	PART
fcis-31244	99	16	capture	capture	VERB
fcis-31244	99	17	small	small	ADJ
fcis-31244	99	18	details	detail	NOUN
fcis-31244	99	19	and	and	CCONJ
fcis-31244	99	20	aggregate	aggregate	VERB
fcis-31244	99	21	local	local	ADJ
fcis-31244	99	22	information	information	NOUN
fcis-31244	99	23	.	.	PUNCT
fcis-31244	100	1	through	through	ADP
fcis-31244	100	2	the	the	DET
fcis-31244	100	3	classification	classification	NOUN
fcis-31244	100	4	task	task	NOUN
fcis-31244	100	5	on	on	ADP
fcis-31244	100	6	these	these	DET
fcis-31244	100	7	data	datum	NOUN
fcis-31244	100	8	sets	set	NOUN
fcis-31244	100	9	,	,	PUNCT
fcis-31244	100	10	it	it	PRON
fcis-31244	100	11	is	be	AUX
fcis-31244	100	12	proved	prove	VERB
fcis-31244	100	13	that	that	SCONJ
fcis-31244	100	14	the	the	DET
fcis-31244	100	15	model	model	NOUN
fcis-31244	100	16	can	can	AUX
fcis-31244	100	17	face	face	VERB
fcis-31244	100	18	the	the	DET
fcis-31244	100	19	gesture	gesture	NOUN
fcis-31244	100	20	control	control	NOUN
fcis-31244	100	21	of	of	ADP
fcis-31244	100	22	diverse	diverse	ADJ
fcis-31244	100	23	scenes	scene	NOUN
fcis-31244	100	24	such	such	ADJ
fcis-31244	100	25	as	as	ADP
fcis-31244	100	26	smart	smart	ADJ
fcis-31244	100	27	home	home	NOUN
fcis-31244	100	28	.	.	PUNCT
fcis-31244	101	1	the	the	DET
fcis-31244	101	2	table	table	NOUN
fcis-31244	101	3	1	1	NUM
fcis-31244	101	4	for	for	ADP
fcis-31244	101	5	details	detail	NOUN
fcis-31244	101	6	of	of	ADP
fcis-31244	101	7	datasets	dataset	NOUN
fcis-31244	101	8	.	.	PUNCT
fcis-31244	102	1	table	table	NOUN
fcis-31244	102	2	1	1	NUM
fcis-31244	102	3	.	.	PUNCT
fcis-31244	102	4	dataset	dataset	NOUN
fcis-31244	102	5	details	detail	NOUN
fcis-31244	102	6	dataset	dataset	VERB
fcis-31244	102	7	task	task	NOUN
fcis-31244	102	8	number	number	NOUN
fcis-31244	102	9	of	of	ADP
fcis-31244	102	10	samples	sample	NOUN
fcis-31244	102	11	training	training	NOUN
fcis-31244	102	12	/	/	SYM
fcis-31244	102	13	validation	validation	NOUN
fcis-31244	102	14	/	/	SYM
fcis-31244	102	15	testing	testing	NOUN
fcis-31244	102	16	fine	fine	ADJ
fcis-31244	102	17	dynamic	dynamic	ADJ
fcis-31244	102	18	multi	multi	ADJ
fcis-31244	102	19	classification	classification	NOUN
fcis-31244	102	20	350	350	NUM
fcis-31244	102	21	280/35/35	280/35/35	NUM
fcis-31244	102	22	first	first	ADJ
fcis-31244	102	23	person	person	NOUN
fcis-31244	102	24	multi	multi	VERB
fcis-31244	102	25	classification	classification	NOUN
fcis-31244	102	26	700	700	NUM
fcis-31244	102	27	560/70/70	560/70/70	NUM
fcis-31244	102	28	oblique	oblique	ADJ
fcis-31244	102	29	top	top	ADJ
fcis-31244	102	30	multi	multi	ADJ
fcis-31244	102	31	classification	classification	NOUN
fcis-31244	102	32	700	700	NUM
fcis-31244	102	33	560/70/70	560/70/70	NUM
fcis-31244	102	34	opposite	opposite	ADJ
fcis-31244	102	35	multi	multi	ADJ
fcis-31244	102	36	classification	classification	NOUN
fcis-31244	102	37	420	420	NUM
fcis-31244	102	38	336/42/42	336/42/42	NUM
fcis-31244	102	39	on	on	ADP
fcis-31244	102	40	the	the	DET
fcis-31244	102	41	above	above	ADJ
fcis-31244	102	42	data	data	NOUN
fcis-31244	102	43	sets	set	NOUN
fcis-31244	102	44	,	,	PUNCT
fcis-31244	102	45	acc	acc	PROPN
fcis-31244	102	46	and	and	CCONJ
fcis-31244	102	47	macro	macro	ADJ
fcis-31244	102	48	average	average	NOUN
fcis-31244	102	49	are	be	AUX
fcis-31244	102	50	used	use	VERB
fcis-31244	102	51	to	to	PART
fcis-31244	102	52	evaluate	evaluate	VERB
fcis-31244	102	53	the	the	DET
fcis-31244	102	54	model	model	NOUN
fcis-31244	102	55	,	,	PUNCT
fcis-31244	102	56	where	where	SCONJ
fcis-31244	102	57	acc	acc	PROPN
fcis-31244	102	58	represents	represent	VERB
fcis-31244	102	59	the	the	DET
fcis-31244	102	60	proportion	proportion	NOUN
fcis-31244	102	61	of	of	ADP
fcis-31244	102	62	all	all	DET
fcis-31244	102	63	samples	sample	NOUN
fcis-31244	102	64	correctly	correctly	ADV
fcis-31244	102	65	classified	classify	VERB
fcis-31244	102	66	.	.	PUNCT
fcis-31244	103	1	accuracy	accuracy	NOUN
fcis-31244	103	2	1	1	NUM
fcis-31244	103	3	  	  	SPACE
fcis-31244	103	4	6	6	NUM
fcis-31244	103	5	macro	macro	NOUN
fcis-31244	103	6	average	average	NOUN
fcis-31244	103	7	is	be	AUX
fcis-31244	103	8	to	to	PART
fcis-31244	103	9	directly	directly	ADV
fcis-31244	103	10	average	average	VERB
fcis-31244	103	11	the	the	DET
fcis-31244	103	12	indicators	indicator	NOUN
fcis-31244	103	13	of	of	ADP
fcis-31244	103	14	all	all	DET
fcis-31244	103	15	categories	category	NOUN
fcis-31244	103	16	,	,	PUNCT
fcis-31244	103	17	focusing	focus	VERB
fcis-31244	103	18	on	on	ADP
fcis-31244	103	19	the	the	DET
fcis-31244	103	20	performance	performance	NOUN
fcis-31244	103	21	of	of	ADP
fcis-31244	103	22	small	small	ADJ
fcis-31244	103	23	categories	category	NOUN
fcis-31244	103	24	.	.	PUNCT
fcis-31244	104	1	macro	macro	ADJ
fcis-31244	104	2	-	-	NOUN
fcis-31244	104	3	precision	precision	NOUN
fcis-31244	104	4	1	1	NUM
fcis-31244	104	5	  	  	SPACE
fcis-31244	104	6	tp	tp	NOUN
fcis-31244	104	7	tp	tp	ADP
fcis-31244	104	8	fp	fp	PROPN
fcis-31244	104	9	7	7	NUM
fcis-31244	104	10	4.2	4.2	NUM
fcis-31244	104	11	.	.	PUNCT
fcis-31244	105	1	experimental	experimental	ADJ
fcis-31244	105	2	details	detail	NOUN
fcis-31244	105	3	this	this	DET
fcis-31244	105	4	model	model	NOUN
fcis-31244	105	5	is	be	AUX
fcis-31244	105	6	trained	train	VERB
fcis-31244	105	7	and	and	CCONJ
fcis-31244	105	8	reasoned	reason	VERB
fcis-31244	105	9	on	on	ADP
fcis-31244	105	10	the	the	DET
fcis-31244	105	11	above	above	ADJ
fcis-31244	105	12	data	data	NOUN
fcis-31244	105	13	sets	set	NOUN
fcis-31244	105	14	,	,	PUNCT
fcis-31244	105	15	and	and	CCONJ
fcis-31244	105	16	compared	compare	VERB
fcis-31244	105	17	with	with	ADP
fcis-31244	105	18	the	the	DET
fcis-31244	105	19	mainstream	mainstream	NOUN
fcis-31244	105	20	models	model	NOUN
fcis-31244	105	21	(	(	PUNCT
fcis-31244	105	22	mobilenet	mobilenet	NOUN
fcis-31244	105	23	,	,	PUNCT
fcis-31244	105	24	vim	vim	NOUN
fcis-31244	105	25	)	)	PUNCT
fcis-31244	105	26	,	,	PUNCT
fcis-31244	105	27	etc	etc	X
fcis-31244	105	28	.	.	X
fcis-31244	106	1	the	the	DET
fcis-31244	106	2	experiment	experiment	NOUN
fcis-31244	106	3	was	be	AUX
fcis-31244	106	4	carried	carry	VERB
fcis-31244	106	5	out	out	ADP
fcis-31244	106	6	on	on	ADP
fcis-31244	106	7	two	two	NUM
fcis-31244	106	8	24	24	NUM
fcis-31244	106	9	gb	gb	PROPN
fcis-31244	106	10	nvidia	nvidia	PROPN
fcis-31244	106	11	geforce	geforce	NOUN
fcis-31244	106	12	rtx	rtx	PROPN
fcis-31244	106	13	3090ti	3090ti	PROPN
fcis-31244	106	14	using	use	VERB
fcis-31244	106	15	python3.8	python3.8	ADV
fcis-31244	106	16	and	and	CCONJ
fcis-31244	106	17	pytorch2.4.0	pytorch2.4.0	NOUN
fcis-31244	106	18	.	.	PUNCT
fcis-31244	107	1	after	after	ADP
fcis-31244	107	2	initial	initial	ADJ
fcis-31244	107	3	parameter	parameter	NOUN
fcis-31244	107	4	adjustment	adjustment	NOUN
fcis-31244	107	5	,	,	PUNCT
fcis-31244	107	6	the	the	DET
fcis-31244	107	7	training	training	NOUN
fcis-31244	107	8	superparameter	superparameter	NOUN
fcis-31244	107	9	is	be	AUX
fcis-31244	107	10	selected	select	VERB
fcis-31244	107	11	as	as	ADP
fcis-31244	107	12	epoch	epoch	NOUN
fcis-31244	107	13	200	200	NUM
fcis-31244	107	14	and	and	CCONJ
fcis-31244	107	15	batch	batch	VERB
fcis-31244	107	16	size	size	NOUN
fcis-31244	107	17	16	16	NUM
fcis-31244	107	18	.	.	PUNCT
fcis-31244	108	1	for	for	ADP
fcis-31244	108	2	all	all	DET
fcis-31244	108	3	data	datum	NOUN
fcis-31244	108	4	sets	set	NOUN
fcis-31244	108	5	,	,	PUNCT
fcis-31244	108	6	the	the	DET
fcis-31244	108	7	optimizer	optimizer	NOUN
fcis-31244	108	8	uses	use	VERB
fcis-31244	108	9	adam	adam	PROPN
fcis-31244	108	10	,	,	PUNCT
fcis-31244	108	11	and	and	CCONJ
fcis-31244	108	12	the	the	DET
fcis-31244	108	13	learning	learning	NOUN
fcis-31244	108	14	rate	rate	NOUN
fcis-31244	108	15	is	be	AUX
fcis-31244	108	16	dynamically	dynamically	ADV
fcis-31244	108	17	adjusted	adjust	VERB
fcis-31244	108	18	from	from	ADP
fcis-31244	108	19	1e-3	1e-3	PROPN
fcis-31244	108	20	to	to	ADP
fcis-31244	108	21	1e-5	1e-5	NUM
fcis-31244	108	22	.	.	PUNCT
fcis-31244	109	1	77	77	NUM
fcis-31244	109	2	4.3	4.3	NUM
fcis-31244	109	3	.	.	PUNCT
fcis-31244	109	4	result	result	VERB
fcis-31244	109	5	analysis	analysis	NOUN
fcis-31244	109	6	the	the	DET
fcis-31244	109	7	results	result	NOUN
fcis-31244	109	8	of	of	ADP
fcis-31244	109	9	the	the	DET
fcis-31244	109	10	comparative	comparative	ADJ
fcis-31244	109	11	experiment	experiment	NOUN
fcis-31244	109	12	are	be	AUX
fcis-31244	109	13	shown	show	VERB
fcis-31244	109	14	in	in	ADP
fcis-31244	109	15	table	table	NOUN
fcis-31244	109	16	2	2	NUM
fcis-31244	109	17	,	,	PUNCT
fcis-31244	109	18	and	and	CCONJ
fcis-31244	109	19	the	the	DET
fcis-31244	109	20	data	datum	NOUN
fcis-31244	109	21	adopts	adopt	VERB
fcis-31244	109	22	the	the	DET
fcis-31244	109	23	percentage	percentage	NOUN
fcis-31244	109	24	system	system	NOUN
fcis-31244	109	25	.	.	PUNCT
fcis-31244	110	1	the	the	DET
fcis-31244	110	2	results	result	NOUN
fcis-31244	110	3	show	show	VERB
fcis-31244	110	4	that	that	SCONJ
fcis-31244	110	5	in	in	ADP
fcis-31244	110	6	some	some	DET
fcis-31244	110	7	scenarios	scenario	NOUN
fcis-31244	110	8	,	,	PUNCT
fcis-31244	110	9	the	the	DET
fcis-31244	110	10	model	model	NOUN
fcis-31244	110	11	proposed	propose	VERB
fcis-31244	110	12	in	in	ADP
fcis-31244	110	13	this	this	DET
fcis-31244	110	14	paper	paper	NOUN
fcis-31244	110	15	is	be	AUX
fcis-31244	110	16	superior	superior	ADJ
fcis-31244	110	17	to	to	ADP
fcis-31244	110	18	the	the	DET
fcis-31244	110	19	existing	exist	VERB
fcis-31244	110	20	mainstream	mainstream	NOUN
fcis-31244	110	21	models	model	NOUN
fcis-31244	110	22	.	.	PUNCT
fcis-31244	111	1	compared	compare	VERB
fcis-31244	111	2	with	with	ADP
fcis-31244	111	3	the	the	DET
fcis-31244	111	4	same	same	ADJ
fcis-31244	111	5	mobile	mobile	ADJ
fcis-31244	111	6	terminal	terminal	PROPN
fcis-31244	111	7	model	model	NOUN
fcis-31244	111	8	mobilenet	mobilenet	PROPN
fcis-31244	111	9	,	,	PUNCT
fcis-31244	111	10	shuma	shuma	PROPN
fcis-31244	111	11	's	's	PART
fcis-31244	111	12	acc	acc	PROPN
fcis-31244	111	13	is	be	AUX
fcis-31244	111	14	improved	improve	VERB
fcis-31244	111	15	by	by	ADP
fcis-31244	111	16	3	3	NUM
fcis-31244	111	17	%	%	NOUN
fcis-31244	111	18	on	on	ADP
fcis-31244	111	19	average	average	ADJ
fcis-31244	111	20	.	.	PUNCT
fcis-31244	112	1	in	in	ADP
fcis-31244	112	2	the	the	DET
fcis-31244	112	3	data	datum	NOUN
fcis-31244	112	4	set	set	VERB
fcis-31244	112	5	of	of	ADP
fcis-31244	112	6	dynamic	dynamic	ADJ
fcis-31244	112	7	gesture	gesture	NOUN
fcis-31244	112	8	smart	smart	ADJ
fcis-31244	112	9	home	home	NOUN
fcis-31244	112	10	application	application	NOUN
fcis-31244	112	11	scenarios	scenario	NOUN
fcis-31244	112	12	above	above	ADP
fcis-31244	112	13	the	the	DET
fcis-31244	112	14	slope	slope	NOUN
fcis-31244	112	15	,	,	PUNCT
fcis-31244	112	16	the	the	DET
fcis-31244	112	17	acc	acc	PROPN
fcis-31244	112	18	is	be	AUX
fcis-31244	112	19	improved	improve	VERB
fcis-31244	112	20	by	by	ADP
fcis-31244	112	21	4.8	4.8	NUM
fcis-31244	112	22	%	%	NOUN
fcis-31244	112	23	compared	compare	VERB
fcis-31244	112	24	with	with	ADP
fcis-31244	112	25	3dresnet	3dresnet	NUM
fcis-31244	112	26	.	.	PUNCT
fcis-31244	113	1	similarly	similarly	ADV
fcis-31244	113	2	,	,	PUNCT
fcis-31244	113	3	shuma	shuma	PROPN
fcis-31244	113	4	also	also	ADV
fcis-31244	113	5	performs	perform	VERB
fcis-31244	113	6	well	well	ADV
fcis-31244	113	7	in	in	ADP
fcis-31244	113	8	other	other	ADJ
fcis-31244	113	9	data	data	NOUN
fcis-31244	113	10	sets	set	NOUN
fcis-31244	113	11	.	.	PUNCT
fcis-31244	114	1	table	table	NOUN
fcis-31244	114	2	2	2	NUM
fcis-31244	114	3	.	.	PUNCT
fcis-31244	114	4	performance	performance	NOUN
fcis-31244	114	5	comparison	comparison	NOUN
fcis-31244	114	6	between	between	ADP
fcis-31244	114	7	shuma	shuma	PROPN
fcis-31244	114	8	and	and	CCONJ
fcis-31244	114	9	other	other	ADJ
fcis-31244	114	10	models	model	NOUN
fcis-31244	114	11	model	model	VERB
fcis-31244	114	12	fine	fine	ADJ
fcis-31244	114	13	dynamic	dynamic	ADJ
fcis-31244	114	14	first	first	ADJ
fcis-31244	114	15	person	person	NOUN
fcis-31244	114	16	oblique	oblique	ADJ
fcis-31244	114	17	top	top	NOUN
fcis-31244	114	18	opposite	opposite	ADJ
fcis-31244	114	19	acc	acc	PROPN
fcis-31244	114	20	mp	mp	PROPN
fcis-31244	114	21	acc	acc	PROPN
fcis-31244	114	22	mp	mp	PROPN
fcis-31244	114	23	acc	acc	PROPN
fcis-31244	114	24	mp	mp	PROPN
fcis-31244	114	25	acc	acc	PROPN
fcis-31244	114	26	mp	mp	PROPN
fcis-31244	114	27	mobilenetxt+ca[15	mobilenetxt+ca[15	PROPN
fcis-31244	114	28	]	]	X
fcis-31244	114	29	73.2	73.2	NUM
fcis-31244	114	30	61.7	61.7	NUM
fcis-31244	114	31	81.1	81.1	NUM
fcis-31244	114	32	73.2	73.2	NUM
fcis-31244	114	33	64.4	64.4	NUM
fcis-31244	114	34	51.3	51.3	NUM
fcis-31244	114	35	85.6	85.6	NUM
fcis-31244	114	36	72.6	72.6	NUM
fcis-31244	114	37	vim[16	vim[16	NOUN
fcis-31244	114	38	]	]	PUNCT
fcis-31244	114	39	84.1	84.1	NUM
fcis-31244	114	40	64.2	64.2	NUM
fcis-31244	114	41	86.5	86.5	NUM
fcis-31244	114	42	74.6	74.6	NUM
fcis-31244	114	43	70.2	70.2	NUM
fcis-31244	114	44	53.1	53.1	NUM
fcis-31244	114	45	89.6	89.6	NUM
fcis-31244	114	46	74.1	74.1	NUM
fcis-31244	114	47	3d	3d	NUM
fcis-31244	114	48	-	-	PUNCT
fcis-31244	114	49	lstm[17	lstm[17	VERB
fcis-31244	114	50	]	]	PUNCT
fcis-31244	114	51	81.9	81.9	NUM
fcis-31244	114	52	63.0	63.0	NUM
fcis-31244	114	53	83.3	83.3	NUM
fcis-31244	114	54	73.5	73.5	NUM
fcis-31244	114	55	69.3	69.3	NUM
fcis-31244	114	56	51.7	51.7	NUM
fcis-31244	114	57	87.4	87.4	NUM
fcis-31244	114	58	74.8	74.8	NUM
fcis-31244	114	59	3d	3d	NUM
fcis-31244	114	60	-	-	PUNCT
fcis-31244	114	61	resnet[18	resnet[18	PROPN
fcis-31244	114	62	]	]	X
fcis-31244	114	63	80.4	80.4	NUM
fcis-31244	114	64	61.1	61.1	NUM
fcis-31244	114	65	84.2	84.2	NUM
fcis-31244	114	66	71.5	71.5	NUM
fcis-31244	114	67	65.2	65.2	NUM
fcis-31244	114	68	51.4	51.4	NUM
fcis-31244	114	69	84.8	84.8	NUM
fcis-31244	114	70	73.1	73.1	NUM
fcis-31244	114	71	posenet[19	posenet[19	NOUN
fcis-31244	114	72	]	]	PUNCT
fcis-31244	114	73	84.2	84.2	NUM
fcis-31244	114	74	63.3	63.3	NUM
fcis-31244	114	75	86.2	86.2	NUM
fcis-31244	114	76	75.1	75.1	NUM
fcis-31244	114	77	70.9	70.9	NUM
fcis-31244	114	78	54.0	54.0	NUM
fcis-31244	114	79	89.1	89.1	NUM
fcis-31244	114	80	75.3	75.3	NUM
fcis-31244	114	81	inception	inception	NOUN
fcis-31244	114	82	-	-	PUNCT
fcis-31244	114	83	lstm[20	lstm[20	NOUN
fcis-31244	114	84	]	]	X
fcis-31244	114	85	80.2	80.2	NUM
fcis-31244	114	86	61.1	61.1	NUM
fcis-31244	114	87	81.6	81.6	NUM
fcis-31244	114	88	73.3	73.3	NUM
fcis-31244	114	89	69.5	69.5	NUM
fcis-31244	114	90	53.0	53.0	NUM
fcis-31244	114	91	86.3	86.3	NUM
fcis-31244	114	92	73.4	73.4	NUM
fcis-31244	114	93	shuma	shuma	NOUN
fcis-31244	114	94	81.7	81.7	NUM
fcis-31244	114	95	62.9	62.9	NUM
fcis-31244	114	96	87.7	87.7	NUM
fcis-31244	114	97	76.2	76.2	NUM
fcis-31244	114	98	70.0	70.0	NUM
fcis-31244	114	99	53.7	53.7	NUM
fcis-31244	114	100	89.7	89.7	NUM
fcis-31244	114	101	75.4	75.4	NUM
fcis-31244	114	102	in	in	ADP
fcis-31244	114	103	order	order	NOUN
fcis-31244	114	104	to	to	PART
fcis-31244	114	105	verify	verify	VERB
fcis-31244	114	106	the	the	DET
fcis-31244	114	107	generalization	generalization	NOUN
fcis-31244	114	108	ability	ability	NOUN
fcis-31244	114	109	of	of	ADP
fcis-31244	114	110	the	the	DET
fcis-31244	114	111	model	model	NOUN
fcis-31244	114	112	in	in	ADP
fcis-31244	114	113	this	this	DET
fcis-31244	114	114	paper	paper	NOUN
fcis-31244	114	115	,	,	PUNCT
fcis-31244	114	116	data	datum	NOUN
fcis-31244	114	117	enhancement	enhancement	NOUN
fcis-31244	114	118	is	be	AUX
fcis-31244	114	119	carried	carry	VERB
fcis-31244	114	120	out	out	ADP
fcis-31244	114	121	on	on	ADP
fcis-31244	114	122	the	the	DET
fcis-31244	114	123	proposed	propose	VERB
fcis-31244	114	124	dataset[22	dataset[22	NOUN
fcis-31244	114	125	]	]	PUNCT
fcis-31244	114	126	to	to	PART
fcis-31244	114	127	verify	verify	VERB
fcis-31244	114	128	the	the	DET
fcis-31244	114	129	ability	ability	NOUN
fcis-31244	114	130	of	of	ADP
fcis-31244	114	131	the	the	DET
fcis-31244	114	132	model	model	NOUN
fcis-31244	114	133	to	to	PART
fcis-31244	114	134	process	process	VERB
fcis-31244	114	135	noisy	noisy	ADJ
fcis-31244	114	136	data	datum	NOUN
fcis-31244	114	137	.	.	PUNCT
fcis-31244	115	1	the	the	DET
fcis-31244	115	2	accuracy	accuracy	NOUN
fcis-31244	115	3	of	of	ADP
fcis-31244	115	4	all	all	DET
fcis-31244	115	5	data	datum	NOUN
fcis-31244	115	6	sets	set	NOUN
fcis-31244	115	7	is	be	AUX
fcis-31244	115	8	averaged	average	VERB
fcis-31244	115	9	,	,	PUNCT
fcis-31244	115	10	and	and	CCONJ
fcis-31244	115	11	five	five	NUM
fcis-31244	115	12	experiments	experiment	NOUN
fcis-31244	115	13	are	be	AUX
fcis-31244	115	14	carried	carry	VERB
fcis-31244	115	15	out	out	ADP
fcis-31244	115	16	on	on	ADP
fcis-31244	115	17	each	each	DET
fcis-31244	115	18	model	model	NOUN
fcis-31244	115	19	to	to	PART
fcis-31244	115	20	eliminate	eliminate	VERB
fcis-31244	115	21	the	the	DET
fcis-31244	115	22	interference	interference	NOUN
fcis-31244	115	23	of	of	ADP
fcis-31244	115	24	special	special	ADJ
fcis-31244	115	25	case	case	NOUN
fcis-31244	115	26	data	datum	NOUN
fcis-31244	115	27	on	on	ADP
fcis-31244	115	28	the	the	DET
fcis-31244	115	29	experimental	experimental	ADJ
fcis-31244	115	30	results	result	NOUN
fcis-31244	115	31	.	.	PUNCT
fcis-31244	116	1	the	the	DET
fcis-31244	116	2	experimental	experimental	ADJ
fcis-31244	116	3	results	result	NOUN
fcis-31244	116	4	take	take	VERB
fcis-31244	116	5	the	the	DET
fcis-31244	116	6	noise	noise	NOUN
fcis-31244	116	7	adding	add	VERB
fcis-31244	116	8	ratio	ratio	NOUN
fcis-31244	116	9	of	of	ADP
fcis-31244	116	10	0.2	0.2	NUM
fcis-31244	116	11	,	,	PUNCT
fcis-31244	116	12	as	as	SCONJ
fcis-31244	116	13	shown	show	VERB
fcis-31244	116	14	in	in	ADP
fcis-31244	116	15	figure	figure	NOUN
fcis-31244	116	16	3	3	NUM
fcis-31244	116	17	.	.	PUNCT
fcis-31244	116	18	fig	fig	PROPN
fcis-31244	116	19	3	3	NUM
fcis-31244	116	20	.	.	PUNCT
fcis-31244	116	21	comparison	comparison	NOUN
fcis-31244	116	22	of	of	ADP
fcis-31244	116	23	average	average	ADJ
fcis-31244	116	24	accuracy	accuracy	NOUN
fcis-31244	116	25	of	of	ADP
fcis-31244	116	26	model	model	NOUN
fcis-31244	116	27	denoising	denoise	VERB
fcis-31244	116	28	the	the	DET
fcis-31244	116	29	results	result	NOUN
fcis-31244	116	30	show	show	VERB
fcis-31244	116	31	that	that	SCONJ
fcis-31244	116	32	the	the	DET
fcis-31244	116	33	average	average	ADJ
fcis-31244	116	34	accuracy	accuracy	NOUN
fcis-31244	116	35	of	of	ADP
fcis-31244	116	36	shuma	shuma	PROPN
fcis-31244	116	37	is	be	AUX
fcis-31244	116	38	also	also	ADV
fcis-31244	116	39	better	well	ADJ
fcis-31244	116	40	than	than	ADP
fcis-31244	116	41	most	most	ADJ
fcis-31244	116	42	models	model	NOUN
fcis-31244	116	43	when	when	SCONJ
fcis-31244	116	44	the	the	DET
fcis-31244	116	45	data	datum	NOUN
fcis-31244	116	46	set	set	VERB
fcis-31244	116	47	is	be	AUX
fcis-31244	116	48	added	add	VERB
fcis-31244	116	49	with	with	ADP
fcis-31244	116	50	noise[21	noise[21	PROPN
fcis-31244	116	51	]	]	PUNCT
fcis-31244	116	52	,	,	PUNCT
fcis-31244	116	53	which	which	PRON
fcis-31244	116	54	further	far	ADV
fcis-31244	116	55	proves	prove	VERB
fcis-31244	116	56	its	its	PRON
fcis-31244	116	57	excellent	excellent	ADJ
fcis-31244	116	58	performance	performance	NOUN
fcis-31244	116	59	in	in	ADP
fcis-31244	116	60	dynamic	dynamic	ADJ
fcis-31244	116	61	gesture	gesture	NOUN
fcis-31244	116	62	recognition	recognition	NOUN
fcis-31244	116	63	.	.	PUNCT
fcis-31244	117	1	5	5	X
fcis-31244	117	2	.	.	X
fcis-31244	117	3	conclusion	conclusion	NOUN
fcis-31244	117	4	the	the	DET
fcis-31244	117	5	shuma	shuma	PROPN
fcis-31244	117	6	model	model	NOUN
fcis-31244	117	7	proposed	propose	VERB
fcis-31244	117	8	in	in	ADP
fcis-31244	117	9	this	this	DET
fcis-31244	117	10	paper	paper	NOUN
fcis-31244	117	11	is	be	AUX
fcis-31244	117	12	a	a	DET
fcis-31244	117	13	dynamic	dynamic	ADJ
fcis-31244	117	14	gesture	gesture	NOUN
fcis-31244	117	15	recognition	recognition	NOUN
fcis-31244	117	16	model	model	NOUN
fcis-31244	117	17	based	base	VERB
fcis-31244	117	18	on	on	ADP
fcis-31244	117	19	improved	improved	ADJ
fcis-31244	117	20	shufflenetv2	shufflenetv2	NOUN
fcis-31244	117	21	and	and	CCONJ
fcis-31244	117	22	mamba	mamba	NOUN
fcis-31244	117	23	.	.	PUNCT
fcis-31244	118	1	combining	combine	VERB
fcis-31244	118	2	the	the	DET
fcis-31244	118	3	lightweight	lightweight	ADJ
fcis-31244	118	4	architecture	architecture	NOUN
fcis-31244	118	5	of	of	ADP
fcis-31244	118	6	shufflenetv2	shufflenetv2	PROPN
fcis-31244	118	7	model	model	NOUN
fcis-31244	118	8	with	with	ADP
fcis-31244	118	9	the	the	DET
fcis-31244	118	10	long	long	ADJ
fcis-31244	118	11	time	time	NOUN
fcis-31244	118	12	-	-	PUNCT
fcis-31244	118	13	series	series	NOUN
fcis-31244	118	14	dependence	dependence	NOUN
fcis-31244	118	15	of	of	ADP
fcis-31244	118	16	mamba	mamba	PROPN
fcis-31244	118	17	results	result	NOUN
fcis-31244	118	18	,	,	PUNCT
fcis-31244	118	19	the	the	DET
fcis-31244	118	20	model	model	NOUN
fcis-31244	118	21	has	have	VERB
fcis-31244	118	22	unique	unique	ADJ
fcis-31244	118	23	advantages	advantage	NOUN
fcis-31244	118	24	in	in	ADP
fcis-31244	118	25	the	the	DET
fcis-31244	118	26	deployment	deployment	NOUN
fcis-31244	118	27	and	and	CCONJ
fcis-31244	118	28	recognition	recognition	NOUN
fcis-31244	118	29	accuracy	accuracy	NOUN
fcis-31244	118	30	of	of	ADP
fcis-31244	118	31	marginalized	marginalize	VERB
fcis-31244	118	32	devices	device	NOUN
fcis-31244	118	33	.	.	PUNCT
fcis-31244	119	1	combining	combine	VERB
fcis-31244	119	2	with	with	ADP
fcis-31244	119	3	the	the	DET
fcis-31244	119	4	different	different	ADJ
fcis-31244	119	5	widths	width	NOUN
fcis-31244	119	6	of	of	ADP
fcis-31244	119	7	the	the	DET
fcis-31244	119	8	backbone	backbone	NOUN
fcis-31244	119	9	network	network	NOUN
fcis-31244	119	10	,	,	PUNCT
fcis-31244	119	11	it	it	PRON
fcis-31244	119	12	can	can	AUX
fcis-31244	119	13	take	take	VERB
fcis-31244	119	14	into	into	ADP
fcis-31244	119	15	account	account	NOUN
fcis-31244	119	16	different	different	ADJ
fcis-31244	119	17	computing	computing	NOUN
fcis-31244	119	18	devices	device	NOUN
fcis-31244	119	19	,	,	PUNCT
fcis-31244	119	20	and	and	CCONJ
fcis-31244	119	21	significantly	significantly	ADV
fcis-31244	119	22	improves	improve	VERB
fcis-31244	119	23	the	the	DET
fcis-31244	119	24	scalability	scalability	NOUN
fcis-31244	119	25	of	of	ADP
fcis-31244	119	26	the	the	DET
fcis-31244	119	27	model	model	NOUN
fcis-31244	119	28	.	.	PUNCT
fcis-31244	120	1	in	in	ADP
fcis-31244	120	2	the	the	DET
fcis-31244	120	3	case	case	NOUN
fcis-31244	120	4	of	of	ADP
fcis-31244	120	5	noise	noise	NOUN
fcis-31244	120	6	interference	interference	NOUN
fcis-31244	120	7	in	in	ADP
fcis-31244	120	8	the	the	DET
fcis-31244	120	9	scene	scene	NOUN
fcis-31244	120	10	,	,	PUNCT
fcis-31244	120	11	shuma	shuma	NOUN
fcis-31244	120	12	model	model	NOUN
fcis-31244	120	13	can	can	AUX
fcis-31244	120	14	still	still	ADV
fcis-31244	120	15	maintain	maintain	VERB
fcis-31244	120	16	the	the	DET
fcis-31244	120	17	performance	performance	NOUN
fcis-31244	120	18	superior	superior	ADJ
fcis-31244	120	19	to	to	ADP
fcis-31244	120	20	other	other	ADJ
fcis-31244	120	21	models	model	NOUN
fcis-31244	120	22	,	,	PUNCT
fcis-31244	120	23	highlighting	highlight	VERB
fcis-31244	120	24	its	its	PRON
fcis-31244	120	25	ability	ability	NOUN
fcis-31244	120	26	to	to	PART
fcis-31244	120	27	effectively	effectively	ADV
fcis-31244	120	28	deal	deal	VERB
fcis-31244	120	29	with	with	ADP
fcis-31244	120	30	gesture	gesture	NOUN
fcis-31244	120	31	recognition	recognition	NOUN
fcis-31244	120	32	in	in	ADP
fcis-31244	120	33	complex	complex	ADJ
fcis-31244	120	34	scenes	scene	NOUN
fcis-31244	120	35	.	.	PUNCT
fcis-31244	121	1	in	in	ADP
fcis-31244	121	2	the	the	DET
fcis-31244	121	3	future	future	NOUN
fcis-31244	121	4	,	,	PUNCT
fcis-31244	121	5	we	we	PRON
fcis-31244	121	6	will	will	AUX
fcis-31244	121	7	continue	continue	VERB
fcis-31244	121	8	to	to	PART
fcis-31244	121	9	explore	explore	VERB
fcis-31244	121	10	the	the	DET
fcis-31244	121	11	application	application	NOUN
fcis-31244	121	12	of	of	ADP
fcis-31244	121	13	shuma	shuma	PROPN
fcis-31244	121	14	model	model	NOUN
fcis-31244	121	15	and	and	CCONJ
fcis-31244	121	16	other	other	ADJ
fcis-31244	121	17	lightweight	lightweight	ADJ
fcis-31244	121	18	models	model	NOUN
fcis-31244	121	19	in	in	ADP
fcis-31244	121	20	gesture	gesture	NOUN
fcis-31244	121	21	control	control	NOUN
fcis-31244	121	22	tasks	task	NOUN
fcis-31244	121	23	,	,	PUNCT
fcis-31244	121	24	and	and	CCONJ
fcis-31244	121	25	further	far	ADV
fcis-31244	121	26	optimize	optimize	VERB
fcis-31244	121	27	the	the	DET
fcis-31244	121	28	structure	structure	NOUN
fcis-31244	121	29	and	and	CCONJ
fcis-31244	121	30	parameters	parameter	NOUN
fcis-31244	121	31	of	of	ADP
fcis-31244	121	32	the	the	DET
fcis-31244	121	33	model	model	NOUN
fcis-31244	121	34	to	to	PART
fcis-31244	121	35	achieve	achieve	VERB
fcis-31244	121	36	better	well	ADJ
fcis-31244	121	37	performance	performance	NOUN
fcis-31244	121	38	and	and	CCONJ
fcis-31244	121	39	be	be	AUX
fcis-31244	121	40	competent	competent	ADJ
fcis-31244	121	41	for	for	ADP
fcis-31244	121	42	more	more	ADJ
fcis-31244	121	43	complex	complex	ADJ
fcis-31244	121	44	scenes	scene	NOUN
fcis-31244	121	45	.	.	PUNCT
fcis-31244	122	1	references	reference	NOUN
fcis-31244	122	2	[	[	X
fcis-31244	122	3	1	1	NUM
fcis-31244	122	4	]	]	SYM
fcis-31244	122	5	hu	hu	PROPN
fcis-31244	122	6	j	j	PROPN
fcis-31244	122	7	,	,	PUNCT
fcis-31244	122	8	liu	liu	PROPN
fcis-31244	122	9	s	s	PROPN
fcis-31244	122	10	,	,	PUNCT
fcis-31244	122	11	liu	liu	PROPN
fcis-31244	122	12	m	m	PROPN
fcis-31244	122	13	,	,	PUNCT
fcis-31244	122	14	et	et	NOUN
fcis-31244	122	15	al.st	al.st	ADJ
fcis-31244	122	16	-	-	PUNCT
fcis-31244	122	17	cgnet	cgnet	NOUN
fcis-31244	122	18	:	:	PUNCT
fcis-31244	122	19	a	a	DET
fcis-31244	122	20	spatiotemporal	spatiotemporal	ADJ
fcis-31244	122	21	gesture	gesture	NOUN
fcis-31244	122	22	recognition	recognition	NOUN
fcis-31244	122	23	network	network	NOUN
fcis-31244	122	24	with	with	ADP
fcis-31244	122	25	triplet	triplet	NOUN
fcis-31244	122	26	attention	attention	NOUN
fcis-31244	122	27	and	and	CCONJ
fcis-31244	122	28	dual	dual	ADJ
fcis-31244	122	29	feature	feature	NOUN
fcis-31244	122	30	fusion[j	fusion[j	PROPN
fcis-31244	122	31	]	]	PUNCT
fcis-31244	122	32	.	.	PUNCT
fcis-31244	123	1	pattern	pattern	NOUN
fcis-31244	123	2	recognition,2025,167111767	recognition,2025,167111767	NOUN
fcis-31244	123	3	-	-	PUNCT
fcis-31244	123	4	111767	111767	NUM
fcis-31244	123	5	.	.	PUNCT
fcis-31244	124	1	[	[	X
fcis-31244	124	2	2	2	X
fcis-31244	124	3	]	]	X
fcis-31244	124	4	shaopeng	shaopeng	PROPN
fcis-31244	124	5	c	c	PROPN
fcis-31244	124	6	,	,	PUNCT
fcis-31244	124	7	xueyu	xueyu	PROPN
fcis-31244	124	8	h	h	NOUN
fcis-31244	124	9	.lm	.lm	PUNCT
fcis-31244	124	10	-	-	PUNCT
fcis-31244	124	11	net	net	NOUN
fcis-31244	124	12	:	:	PUNCT
fcis-31244	124	13	a	a	DET
fcis-31244	124	14	dynamic	dynamic	ADJ
fcis-31244	124	15	gesture	gesture	NOUN
fcis-31244	124	16	recognition	recognition	NOUN
fcis-31244	124	17	network	network	NOUN
fcis-31244	124	18	with	with	ADP
fcis-31244	124	19	long	long	ADJ
fcis-31244	124	20	-	-	PUNCT
fcis-31244	124	21	term	term	NOUN
fcis-31244	124	22	aggregation	aggregation	NOUN
fcis-31244	124	23	and	and	CCONJ
fcis-31244	124	24	motion	motion	NOUN
fcis-31244	124	25	excitation[j	excitation[j	PROPN
fcis-31244	124	26	]	]	PUNCT
fcis-31244	124	27	.	.	PUNCT
fcis-31244	125	1	international	international	ADJ
fcis-31244	125	2	journal	journal	PROPN
fcis-31244	125	3	of	of	ADP
fcis-31244	125	4	machine	machine	NOUN
fcis-31244	125	5	learning	learning	NOUN
fcis-31244	125	6	and	and	CCONJ
fcis-31244	125	7	cybernetics	cybernetic	NOUN
fcis-31244	125	8	,	,	PUNCT
fcis-31244	125	9	2023	2023	NUM
fcis-31244	125	10	,	,	PUNCT
fcis-31244	125	11	15(4):1633	15(4):1633	NUM
fcis-31244	125	12	-	-	SYM
fcis-31244	125	13	1645	1645	NUM
fcis-31244	125	14	.	.	PUNCT
fcis-31244	126	1	[	[	X
fcis-31244	126	2	3	3	X
fcis-31244	126	3	]	]	PUNCT
fcis-31244	126	4	m.	m.	NOUN
fcis-31244	126	5	sandler	sandler	PROPN
fcis-31244	126	6	,	,	PUNCT
fcis-31244	126	7	a.	a.	PROPN
fcis-31244	126	8	howard	howard	PROPN
fcis-31244	126	9	,	,	PUNCT
fcis-31244	126	10	m.	m.	PROPN
fcis-31244	126	11	zhu	zhu	PROPN
fcis-31244	126	12	,	,	PUNCT
fcis-31244	126	13	a.	a.	NOUN
fcis-31244	126	14	zhmoginov	zhmoginov	PROPN
fcis-31244	126	15	and	and	CCONJ
fcis-31244	126	16	l.	l.	PROPN
fcis-31244	126	17	-c	-c	PROPN
fcis-31244	126	18	.	.	PUNCT
fcis-31244	126	19	chen	chen	PROPN
fcis-31244	126	20	,	,	PUNCT
fcis-31244	126	21	"	"	PUNCT
fcis-31244	126	22	mobilenetv2	mobilenetv2	NOUN
fcis-31244	126	23	:	:	PUNCT
fcis-31244	126	24	inverted	inverted	ADJ
fcis-31244	126	25	residuals	residual	NOUN
fcis-31244	126	26	and	and	CCONJ
fcis-31244	126	27	linear	linear	ADJ
fcis-31244	126	28	bottlenecks	bottleneck	NOUN
fcis-31244	126	29	,	,	PUNCT
fcis-31244	126	30	"	"	PUNCT
fcis-31244	126	31	2018	2018	NUM
fcis-31244	126	32	ieee	ieee	NOUN
fcis-31244	126	33	/	/	SYM
fcis-31244	126	34	cvf	cvf	NOUN
fcis-31244	126	35	conference	conference	NOUN
fcis-31244	126	36	on	on	ADP
fcis-31244	126	37	computer	computer	NOUN
fcis-31244	126	38	vision	vision	NOUN
fcis-31244	126	39	and	and	CCONJ
fcis-31244	126	40	pattern	pattern	NOUN
fcis-31244	126	41	recognition	recognition	NOUN
fcis-31244	126	42	,	,	PUNCT
fcis-31244	126	43	salt	salt	NOUN
fcis-31244	126	44	lake	lake	PROPN
fcis-31244	126	45	city	city	PROPN
fcis-31244	126	46	,	,	PUNCT
fcis-31244	126	47	ut	ut	PROPN
fcis-31244	126	48	,	,	PUNCT
fcis-31244	126	49	usa	usa	PROPN
fcis-31244	126	50	,	,	PUNCT
fcis-31244	126	51	2018	2018	NUM
fcis-31244	126	52	.	.	PUNCT
fcis-31244	127	1	78	78	NUM
fcis-31244	128	1	[	[	SYM
fcis-31244	128	2	4	4	NUM
fcis-31244	128	3	]	]	PUNCT
fcis-31244	128	4	x.	x.	NOUN
fcis-31244	128	5	zhang	zhang	PROPN
fcis-31244	128	6	,	,	PUNCT
fcis-31244	128	7	x.	x.	PROPN
fcis-31244	128	8	zhou	zhou	PROPN
fcis-31244	128	9	,	,	PUNCT
fcis-31244	128	10	m.	m.	NOUN
fcis-31244	128	11	lin	lin	PROPN
fcis-31244	128	12	and	and	CCONJ
fcis-31244	128	13	j.	j.	PROPN
fcis-31244	128	14	sun	sun	PROPN
fcis-31244	128	15	,	,	PUNCT
fcis-31244	128	16	"	"	PUNCT
fcis-31244	128	17	shufflenet	shufflenet	NOUN
fcis-31244	128	18	:	:	PUNCT
fcis-31244	128	19	an	an	DET
fcis-31244	128	20	extremely	extremely	ADV
fcis-31244	128	21	efficient	efficient	ADJ
fcis-31244	128	22	convolutional	convolutional	ADJ
fcis-31244	128	23	neural	neural	ADJ
fcis-31244	128	24	network	network	NOUN
fcis-31244	128	25	for	for	ADP
fcis-31244	128	26	mobile	mobile	ADJ
fcis-31244	128	27	devices	device	NOUN
fcis-31244	128	28	,	,	PUNCT
fcis-31244	128	29	"	"	PUNCT
fcis-31244	128	30	2018	2018	NUM
fcis-31244	128	31	ieee	ieee	NOUN
fcis-31244	128	32	/	/	SYM
fcis-31244	128	33	cvf	cvf	NOUN
fcis-31244	128	34	conference	conference	NOUN
fcis-31244	128	35	on	on	ADP
fcis-31244	128	36	computer	computer	NOUN
fcis-31244	128	37	vision	vision	NOUN
fcis-31244	128	38	and	and	CCONJ
fcis-31244	128	39	pattern	pattern	NOUN
fcis-31244	128	40	recognition	recognition	NOUN
fcis-31244	128	41	,	,	PUNCT
fcis-31244	128	42	salt	salt	NOUN
fcis-31244	128	43	lake	lake	PROPN
fcis-31244	128	44	city	city	PROPN
fcis-31244	128	45	,	,	PUNCT
fcis-31244	128	46	ut	ut	PROPN
fcis-31244	128	47	,	,	PUNCT
fcis-31244	128	48	usa	usa	PROPN
fcis-31244	128	49	,	,	PUNCT
fcis-31244	128	50	2018	2018	NUM
fcis-31244	128	51	.	.	PUNCT
fcis-31244	129	1	[	[	X
fcis-31244	129	2	5	5	NUM
fcis-31244	129	3	]	]	X
fcis-31244	129	4	tsm	tsm	NOUN
fcis-31244	129	5	:	:	PUNCT
fcis-31244	129	6	temporal	temporal	ADJ
fcis-31244	129	7	shift	shift	NOUN
fcis-31244	129	8	module	module	NOUN
fcis-31244	129	9	for	for	ADP
fcis-31244	129	10	efficient	efficient	ADJ
fcis-31244	129	11	video	video	NOUN
fcis-31244	129	12	understanding	understanding	NOUN
fcis-31244	129	13	.	.	PUNCT
fcis-31244	130	1	[	[	X
fcis-31244	130	2	j].ieee	j].ieee	NOUN
fcis-31244	130	3	transactions	transaction	NOUN
fcis-31244	130	4	on	on	ADP
fcis-31244	130	5	pattern	pattern	NOUN
fcis-31244	130	6	analysis	analysis	NOUN
fcis-31244	130	7	and	and	CCONJ
fcis-31244	130	8	machine	machine	NOUN
fcis-31244	130	9	intelligence,2020	intelligence,2020	NOUN
fcis-31244	130	10	,	,	PUNCT
fcis-31244	130	11	pp	pp	ADV
fcis-31244	130	12	.	.	PUNCT
fcis-31244	131	1	[	[	X
fcis-31244	131	2	6	6	NUM
fcis-31244	131	3	]	]	PUNCT
fcis-31244	131	4	z.	z.	PROPN
fcis-31244	131	5	liu	liu	PROPN
fcis-31244	131	6	,	,	PUNCT
fcis-31244	131	7	l.	l.	PROPN
fcis-31244	131	8	wang	wang	PROPN
fcis-31244	131	9	,	,	PUNCT
fcis-31244	131	10	w.	w.	PROPN
fcis-31244	131	11	wu	wu	PROPN
fcis-31244	131	12	,	,	PUNCT
fcis-31244	131	13	c.	c.	PROPN
fcis-31244	131	14	qian	qian	PROPN
fcis-31244	131	15	and	and	CCONJ
fcis-31244	131	16	t.	t.	PROPN
fcis-31244	131	17	lu	lu	PROPN
fcis-31244	131	18	,	,	PUNCT
fcis-31244	131	19	"	"	PUNCT
fcis-31244	131	20	tam	tam	PROPN
fcis-31244	131	21	:	:	PUNCT
fcis-31244	131	22	temporal	temporal	ADJ
fcis-31244	131	23	adaptive	adaptive	ADJ
fcis-31244	131	24	module	module	NOUN
fcis-31244	131	25	for	for	ADP
fcis-31244	131	26	video	video	NOUN
fcis-31244	131	27	recognition	recognition	NOUN
fcis-31244	131	28	,	,	PUNCT
fcis-31244	131	29	"	"	PUNCT
fcis-31244	131	30	2021	2021	NUM
fcis-31244	131	31	ieee	ieee	NOUN
fcis-31244	131	32	/	/	SYM
fcis-31244	131	33	cvf	cvf	NOUN
fcis-31244	131	34	international	international	ADJ
fcis-31244	131	35	conference	conference	NOUN
fcis-31244	131	36	on	on	ADP
fcis-31244	131	37	computer	computer	NOUN
fcis-31244	131	38	vision	vision	NOUN
fcis-31244	131	39	(	(	PUNCT
fcis-31244	131	40	iccv	iccv	PROPN
fcis-31244	131	41	)	)	PUNCT
fcis-31244	131	42	,	,	PUNCT
fcis-31244	131	43	montreal	montreal	PROPN
fcis-31244	131	44	,	,	PUNCT
fcis-31244	131	45	qc	qc	PROPN
fcis-31244	131	46	,	,	PUNCT
fcis-31244	131	47	canada	canada	PROPN
fcis-31244	131	48	,	,	PUNCT
fcis-31244	131	49	2021	2021	NUM
fcis-31244	131	50	,	,	PUNCT
fcis-31244	131	51	pp	pp	ADV
fcis-31244	131	52	.	.	PUNCT
fcis-31244	132	1	[	[	X
fcis-31244	132	2	7	7	X
fcis-31244	132	3	]	]	X
fcis-31244	132	4	gunawardane	gunawardane	NOUN
fcis-31244	132	5	h	h	NOUN
fcis-31244	132	6	s	s	PART
fcis-31244	132	7	d	d	X
fcis-31244	132	8	p	p	PROPN
fcis-31244	132	9	,	,	PUNCT
fcis-31244	132	10	macneil	macneil	NOUN
fcis-31244	132	11	r	r	NOUN
fcis-31244	132	12	r	r	NOUN
fcis-31244	132	13	,	,	PUNCT
fcis-31244	132	14	zhao	zhao	PROPN
fcis-31244	132	15	l	l	PROPN
fcis-31244	132	16	,	,	PUNCT
fcis-31244	132	17	et	et	NOUN
fcis-31244	132	18	al.a	al.a	ADJ
fcis-31244	132	19	fusion	fusion	NOUN
fcis-31244	132	20	algorithm	algorithm	NOUN
fcis-31244	132	21	based	base	VERB
fcis-31244	132	22	on	on	ADP
fcis-31244	132	23	a	a	DET
fcis-31244	132	24	constant	constant	ADJ
fcis-31244	132	25	velocity	velocity	NOUN
fcis-31244	132	26	model	model	NOUN
fcis-31244	132	27	for	for	ADP
fcis-31244	132	28	improving	improve	VERB
fcis-31244	132	29	the	the	DET
fcis-31244	132	30	measurement	measurement	NOUN
fcis-31244	132	31	of	of	ADP
fcis-31244	132	32	saccade	saccade	NOUN
fcis-31244	132	33	parameters	parameter	NOUN
fcis-31244	132	34	with	with	ADP
fcis-31244	132	35	electrooculography	electrooculography	NOUN
fcis-31244	132	36	[	[	X
fcis-31244	132	37	j].sensors,2024,24(2	j].sensors,2024,24(2	NOUN
fcis-31244	132	38	)	)	PUNCT
fcis-31244	132	39	.	.	PUNCT
fcis-31244	133	1	[	[	X
fcis-31244	133	2	8	8	NUM
fcis-31244	133	3	]	]	X
fcis-31244	133	4	gu	gu	NOUN
fcis-31244	133	5	a	a	PROPN
fcis-31244	133	6	,	,	PUNCT
fcis-31244	133	7	dao	dao	PROPN
fcis-31244	133	8	t.	t.	PROPN
fcis-31244	133	9	mamba	mamba	PROPN
fcis-31244	133	10	:	:	PUNCT
fcis-31244	133	11	linear	linear	ADJ
fcis-31244	133	12	-	-	PUNCT
fcis-31244	133	13	time	time	NOUN
fcis-31244	133	14	sequence	sequence	NOUN
fcis-31244	133	15	modeling	modeling	NOUN
fcis-31244	133	16	with	with	ADP
fcis-31244	133	17	selective	selective	ADJ
fcis-31244	133	18	state	state	NOUN
fcis-31244	133	19	spaces[j	spaces[j	NOUN
fcis-31244	133	20	]	]	PUNCT
fcis-31244	133	21	.	.	PUNCT
fcis-31244	134	1	arxiv	arxiv	PROPN
fcis-31244	134	2	preprint	preprint	PROPN
fcis-31244	134	3	arxiv:2312.00752	arxiv:2312.00752	ADV
fcis-31244	134	4	,	,	PUNCT
fcis-31244	134	5	2023	2023	NUM
fcis-31244	134	6	.	.	PUNCT
fcis-31244	135	1	[	[	X
fcis-31244	135	2	9	9	NUM
fcis-31244	135	3	]	]	PUNCT
fcis-31244	135	4	tu	tu	PROPN
fcis-31244	135	5	c	c	PROPN
fcis-31244	135	6	j	j	PROPN
fcis-31244	135	7	,	,	PUNCT
fcis-31244	135	8	chuang	chuang	PROPN
fcis-31244	135	9	l	l	PROPN
fcis-31244	135	10	y	y	PROPN
fcis-31244	135	11	,	,	PUNCT
fcis-31244	135	12	chang	chang	PROPN
fcis-31244	135	13	j	j	PROPN
fcis-31244	135	14	y	y	PROPN
fcis-31244	135	15	,	,	PUNCT
fcis-31244	135	16	et	et	PROPN
fcis-31244	135	17	al	al	PROPN
fcis-31244	135	18	.	.	PROPN
fcis-31244	135	19	feature	feature	NOUN
fcis-31244	135	20	selection	selection	NOUN
fcis-31244	135	21	using	use	VERB
fcis-31244	135	22	pso	pso	NOUN
fcis-31244	135	23	-	-	PUNCT
fcis-31244	135	24	svm	svm	PROPN
fcis-31244	136	1	[	[	X
fcis-31244	136	2	j	j	X
fcis-31244	136	3	]	]	X
fcis-31244	136	4	.	.	PUNCT
fcis-31244	137	1	iaeng	iaeng	PROPN
fcis-31244	137	2	international	international	PROPN
fcis-31244	137	3	journal	journal	PROPN
fcis-31244	137	4	of	of	ADP
fcis-31244	137	5	computer	computer	NOUN
fcis-31244	137	6	science	science	NOUN
fcis-31244	137	7	,	,	PUNCT
fcis-31244	137	8	2007	2007	NUM
fcis-31244	137	9	,	,	PUNCT
fcis-31244	137	10	33(1	33(1	NUM
fcis-31244	137	11	)	)	PUNCT
fcis-31244	137	12	.	.	PUNCT
fcis-31244	138	1	[	[	X
fcis-31244	138	2	10	10	NUM
fcis-31244	138	3	]	]	X
fcis-31244	138	4	gao	gao	PROPN
fcis-31244	138	5	q	q	PROPN
fcis-31244	138	6	,	,	PUNCT
fcis-31244	138	7	chen	chen	PROPN
fcis-31244	138	8	y	y	PROPN
fcis-31244	138	9	,	,	PUNCT
fcis-31244	138	10	ju	ju	PROPN
fcis-31244	138	11	z	z	PROPN
fcis-31244	138	12	,	,	PUNCT
fcis-31244	138	13	et	et	PROPN
fcis-31244	138	14	al	al	PROPN
fcis-31244	138	15	.	.	PUNCT
fcis-31244	138	16	dynamic	dynamic	ADJ
fcis-31244	138	17	hand	hand	NOUN
fcis-31244	138	18	gesture	gesture	NOUN
fcis-31244	138	19	recognition	recognition	NOUN
fcis-31244	138	20	based	base	VERB
fcis-31244	138	21	on	on	ADP
fcis-31244	138	22	3d	3d	NUM
fcis-31244	138	23	hand	hand	NOUN
fcis-31244	138	24	pose	pose	NOUN
fcis-31244	138	25	estimation	estimation	NOUN
fcis-31244	138	26	for	for	ADP
fcis-31244	138	27	human	human	ADJ
fcis-31244	138	28	–	–	PUNCT
fcis-31244	138	29	robot	robot	NOUN
fcis-31244	138	30	interaction[j	interaction[j	NOUN
fcis-31244	138	31	]	]	PUNCT
fcis-31244	138	32	.	.	PUNCT
fcis-31244	139	1	ieee	ieee	PROPN
fcis-31244	139	2	sensors	sensor	NOUN
fcis-31244	139	3	journal	journal	NOUN
fcis-31244	139	4	,	,	PUNCT
fcis-31244	139	5	2021	2021	NUM
fcis-31244	139	6	,	,	PUNCT
fcis-31244	139	7	22(18	22(18	NUM
fcis-31244	139	8	):	):	PUNCT
fcis-31244	139	9	1742117430	1742117430	NUM
fcis-31244	139	10	.	.	PUNCT
fcis-31244	140	1	[	[	X
fcis-31244	140	2	11	11	NUM
fcis-31244	140	3	]	]	X
fcis-31244	140	4	zhang	zhang	PROPN
fcis-31244	140	5	w	w	PROPN
fcis-31244	140	6	,	,	PUNCT
fcis-31244	140	7	wang	wang	PROPN
fcis-31244	140	8	j	j	PROPN
fcis-31244	140	9	,	,	PUNCT
fcis-31244	140	10	lan	lan	PROPN
fcis-31244	140	11	f.	f.	PROPN
fcis-31244	140	12	dynamic	dynamic	ADJ
fcis-31244	140	13	hand	hand	NOUN
fcis-31244	140	14	gesture	gesture	NOUN
fcis-31244	140	15	recognition	recognition	NOUN
fcis-31244	140	16	based	base	VERB
fcis-31244	140	17	on	on	ADP
fcis-31244	140	18	short	short	ADJ
fcis-31244	140	19	-	-	PUNCT
fcis-31244	140	20	term	term	NOUN
fcis-31244	140	21	sampling	sample	VERB
fcis-31244	140	22	neural	neural	ADJ
fcis-31244	140	23	networks[j	networks[j	PROPN
fcis-31244	140	24	]	]	X
fcis-31244	140	25	.	.	PUNCT
fcis-31244	140	26	ieee	ieee	PROPN
fcis-31244	140	27	/	/	SYM
fcis-31244	140	28	caa	caa	PROPN
fcis-31244	140	29	journal	journal	PROPN
fcis-31244	140	30	of	of	ADP
fcis-31244	140	31	automatica	automatica	PROPN
fcis-31244	140	32	sinica	sinica	PROPN
fcis-31244	140	33	,	,	PUNCT
fcis-31244	140	34	2020	2020	NUM
fcis-31244	140	35	,	,	PUNCT
fcis-31244	140	36	8(1	8(1	NOUN
fcis-31244	140	37	):	):	PUNCT
fcis-31244	140	38	110	110	NUM
fcis-31244	140	39	-	-	SYM
fcis-31244	140	40	120	120	NUM
fcis-31244	140	41	.	.	PUNCT
fcis-31244	141	1	[	[	X
fcis-31244	141	2	12	12	NUM
fcis-31244	141	3	]	]	X
fcis-31244	141	4	de	de	X
fcis-31244	141	5	smedt	smedt	PROPN
fcis-31244	141	6	q	q	PROPN
fcis-31244	141	7	,	,	PUNCT
fcis-31244	141	8	wannous	wannous	ADJ
fcis-31244	141	9	h	h	NOUN
fcis-31244	141	10	,	,	PUNCT
fcis-31244	141	11	vandeborre	vandeborre	PROPN
fcis-31244	141	12	j	j	PROPN
fcis-31244	142	1	p.	p.	PROPN
fcis-31244	142	2	skeleton	skeleton	PROPN
fcis-31244	142	3	-	-	PUNCT
fcis-31244	142	4	based	base	VERB
fcis-31244	142	5	dynamic	dynamic	ADJ
fcis-31244	142	6	hand	hand	NOUN
fcis-31244	142	7	gesture	gesture	NOUN
fcis-31244	142	8	recognition[c]//proceedings	recognition[c]//proceeding	NOUN
fcis-31244	142	9	of	of	ADP
fcis-31244	142	10	the	the	DET
fcis-31244	142	11	ieee	ieee	NOUN
fcis-31244	142	12	conference	conference	NOUN
fcis-31244	142	13	on	on	ADP
fcis-31244	142	14	computer	computer	NOUN
fcis-31244	142	15	vision	vision	NOUN
fcis-31244	142	16	and	and	CCONJ
fcis-31244	142	17	pattern	pattern	NOUN
fcis-31244	142	18	recognition	recognition	NOUN
fcis-31244	142	19	workshops	workshop	NOUN
fcis-31244	142	20	.	.	PUNCT
fcis-31244	143	1	2016	2016	NUM
fcis-31244	143	2	:	:	PUNCT
fcis-31244	143	3	1	1	NUM
fcis-31244	143	4	-	-	SYM
fcis-31244	143	5	9	9	NUM
fcis-31244	143	6	.	.	PUNCT
fcis-31244	144	1	[	[	X
fcis-31244	144	2	13	13	NUM
fcis-31244	144	3	]	]	X
fcis-31244	144	4	prakash	prakash	PROPN
fcis-31244	144	5	k	k	PROPN
fcis-31244	144	6	s	s	PROPN
fcis-31244	144	7	,	,	PUNCT
fcis-31244	144	8	kunju	kunju	PROPN
fcis-31244	144	9	n.	n.	NOUN
fcis-31244	144	10	an	an	DET
fcis-31244	144	11	optimized	optimize	VERB
fcis-31244	144	12	electrode	electrode	NOUN
fcis-31244	144	13	configuration	configuration	NOUN
fcis-31244	144	14	for	for	ADP
fcis-31244	144	15	wrist	wrist	NOUN
fcis-31244	144	16	wearable	wearable	ADJ
fcis-31244	144	17	emg	emg	NOUN
fcis-31244	144	18	-	-	PUNCT
fcis-31244	144	19	based	base	VERB
fcis-31244	144	20	hand	hand	NOUN
fcis-31244	144	21	gesture	gesture	NOUN
fcis-31244	144	22	recognition	recognition	NOUN
fcis-31244	144	23	using	use	VERB
fcis-31244	144	24	machine	machine	NOUN
fcis-31244	144	25	learning[j	learning[j	NOUN
fcis-31244	144	26	]	]	PUNCT
fcis-31244	144	27	.	.	PUNCT
fcis-31244	145	1	expert	expert	NOUN
fcis-31244	145	2	systems	system	NOUN
fcis-31244	145	3	with	with	ADP
fcis-31244	145	4	applications	application	NOUN
fcis-31244	145	5	,	,	PUNCT
fcis-31244	145	6	2025	2025	NUM
fcis-31244	145	7	,	,	PUNCT
fcis-31244	145	8	274	274	NUM
fcis-31244	145	9	:	:	SYM
fcis-31244	145	10	127040	127040	NUM
fcis-31244	145	11	.	.	PUNCT
fcis-31244	146	1	[	[	X
fcis-31244	146	2	14	14	NUM
fcis-31244	146	3	]	]	X
fcis-31244	146	4	ma	ma	PROPN
fcis-31244	146	5	q	q	PROPN
fcis-31244	146	6	,	,	PUNCT
fcis-31244	146	7	gu	gu	PROPN
fcis-31244	146	8	z	z	PROPN
fcis-31244	146	9	,	,	PUNCT
fcis-31244	146	10	gao	gao	PROPN
fcis-31244	146	11	x	x	PROPN
fcis-31244	146	12	,	,	PUNCT
fcis-31244	146	13	et	et	PROPN
fcis-31244	146	14	al	al	PROPN
fcis-31244	146	15	.	.	PROPN
fcis-31244	146	16	intelligent	intelligent	ADJ
fcis-31244	146	17	hand‐gesture	hand‐gesture	NOUN
fcis-31244	146	18	recognition	recognition	NOUN
fcis-31244	146	19	based	base	VERB
fcis-31244	146	20	on	on	ADP
fcis-31244	146	21	programmable	programmable	ADJ
fcis-31244	146	22	topological	topological	ADJ
fcis-31244	146	23	metasurfaces	metasurface	NOUN
fcis-31244	147	1	[	[	X
fcis-31244	147	2	j	j	X
fcis-31244	147	3	]	]	X
fcis-31244	147	4	.	.	PUNCT
fcis-31244	148	1	advanced	advanced	ADJ
fcis-31244	148	2	functional	functional	ADJ
fcis-31244	148	3	materials	material	NOUN
fcis-31244	148	4	,	,	PUNCT
fcis-31244	148	5	2025	2025	NUM
fcis-31244	148	6	,	,	PUNCT
fcis-31244	148	7	35(1	35(1	NUM
fcis-31244	148	8	):	):	PUNCT
fcis-31244	148	9	2411667	2411667	NUM
fcis-31244	148	10	.	.	PUNCT
fcis-31244	149	1	[	[	X
fcis-31244	149	2	15	15	NUM
fcis-31244	149	3	]	]	X
fcis-31244	149	4	pintelas	pintela	NOUN
fcis-31244	149	5	e	e	NOUN
fcis-31244	149	6	,	,	PUNCT
fcis-31244	149	7	livieris	livieri	VERB
fcis-31244	149	8	i	i	PRON
fcis-31244	149	9	e	e	PROPN
fcis-31244	149	10	,	,	PUNCT
fcis-31244	149	11	tampakas	tampakas	PROPN
fcis-31244	149	12	v	v	NOUN
fcis-31244	149	13	,	,	PUNCT
fcis-31244	149	14	et	et	PROPN
fcis-31244	149	15	al	al	PROPN
fcis-31244	149	16	.	.	PUNCT
fcis-31244	149	17	mobilenet	mobilenet	PROPN
fcis-31244	149	18	-	-	PUNCT
fcis-31244	149	19	hex	hex	PROPN
fcis-31244	149	20	:	:	PUNCT
fcis-31244	149	21	heterogeneous	heterogeneous	ADJ
fcis-31244	149	22	ensemble	ensemble	ADJ
fcis-31244	149	23	of	of	ADP
fcis-31244	149	24	mobilenet	mobilenet	NOUN
fcis-31244	149	25	experts	expert	NOUN
fcis-31244	149	26	for	for	ADP
fcis-31244	149	27	efficient	efficient	ADJ
fcis-31244	149	28	and	and	CCONJ
fcis-31244	149	29	scalable	scalable	ADJ
fcis-31244	149	30	vision	vision	NOUN
fcis-31244	149	31	model	model	NOUN
fcis-31244	149	32	optimization[j	optimization[j	PROPN
fcis-31244	149	33	]	]	X
fcis-31244	149	34	.	.	PUNCT
fcis-31244	150	1	big	big	ADJ
fcis-31244	150	2	data	datum	NOUN
fcis-31244	150	3	and	and	CCONJ
fcis-31244	150	4	cognitive	cognitive	ADJ
fcis-31244	150	5	computing	computing	NOUN
fcis-31244	150	6	,	,	PUNCT
fcis-31244	150	7	2025	2025	NUM
fcis-31244	150	8	,	,	PUNCT
fcis-31244	150	9	9(1	9(1	NUM
fcis-31244	150	10	):	):	PUNCT
fcis-31244	150	11	2	2	NUM
fcis-31244	150	12	.	.	PUNCT
fcis-31244	151	1	[	[	X
fcis-31244	151	2	16	16	NUM
fcis-31244	151	3	]	]	X
fcis-31244	151	4	wu	wu	PROPN
fcis-31244	151	5	r	r	PROPN
fcis-31244	151	6	,	,	PUNCT
fcis-31244	151	7	liu	liu	PROPN
fcis-31244	151	8	y	y	PROPN
fcis-31244	151	9	,	,	PUNCT
fcis-31244	151	10	liang	liang	PROPN
fcis-31244	151	11	p	p	PROPN
fcis-31244	151	12	,	,	PUNCT
fcis-31244	151	13	et	et	PROPN
fcis-31244	151	14	al	al	PROPN
fcis-31244	151	15	.	.	PROPN
fcis-31244	152	1	h	h	NOUN
fcis-31244	152	2	-	-	PUNCT
fcis-31244	152	3	vmunet	vmunet	ADJ
fcis-31244	152	4	:	:	PUNCT
fcis-31244	152	5	high	high	ADJ
fcis-31244	152	6	-	-	PUNCT
fcis-31244	152	7	order	order	NOUN
fcis-31244	152	8	vision	vision	NOUN
fcis-31244	152	9	mamba	mamba	PROPN
fcis-31244	152	10	unet	unet	PROPN
fcis-31244	152	11	for	for	ADP
fcis-31244	152	12	medical	medical	ADJ
fcis-31244	152	13	image	image	NOUN
fcis-31244	152	14	segmentation[j	segmentation[j	PROPN
fcis-31244	152	15	]	]	PUNCT
fcis-31244	152	16	.	.	PUNCT
fcis-31244	153	1	neurocomputing	neurocomputing	NOUN
fcis-31244	153	2	,	,	PUNCT
fcis-31244	153	3	2025	2025	NUM
fcis-31244	153	4	:	:	PUNCT
fcis-31244	153	5	129447	129447	NUM
fcis-31244	153	6	.	.	PUNCT
fcis-31244	154	1	[	[	X
fcis-31244	154	2	17	17	NUM
fcis-31244	154	3	]	]	X
fcis-31244	154	4	de	de	X
fcis-31244	154	5	jesus	jesus	PROPN
fcis-31244	154	6	n	n	PROPN
fcis-31244	154	7	m	m	PROPN
fcis-31244	154	8	,	,	PUNCT
fcis-31244	154	9	festijo	festijo	PROPN
fcis-31244	154	10	e	e	PROPN
fcis-31244	154	11	d	d	PROPN
fcis-31244	154	12	,	,	PUNCT
fcis-31244	154	13	apolinario	apolinario	ADJ
fcis-31244	154	14	g	g	PROPN
fcis-31244	154	15	f	f	PROPN
fcis-31244	154	16	d	d	PROPN
fcis-31244	154	17	g	g	PROPN
fcis-31244	154	18	,	,	PUNCT
fcis-31244	154	19	et	et	PROPN
fcis-31244	154	20	al	al	PROPN
fcis-31244	154	21	.	.	PROPN
fcis-31244	154	22	multilocation	multilocation	PROPN
fcis-31244	154	23	and	and	CCONJ
fcis-31244	154	24	multi	multi	ADJ
fcis-31244	154	25	-	-	ADJ
fcis-31244	154	26	feature	feature	ADJ
fcis-31244	154	27	lmp	lmp	NOUN
fcis-31244	154	28	forecasting	forecasting	NOUN
fcis-31244	154	29	:	:	PUNCT
fcis-31244	154	30	a	a	DET
fcis-31244	154	31	2d	2d	NUM
fcis-31244	154	32	spatiotemporal	spatiotemporal	ADJ
fcis-31244	154	33	lstm	lstm	PROPN
fcis-31244	154	34	-	-	PUNCT
fcis-31244	154	35	cnn	cnn	PROPN
fcis-31244	154	36	approach[c]//2025	approach[c]//2025	PROPN
fcis-31244	154	37	15th	15th	ADJ
fcis-31244	154	38	international	international	ADJ
fcis-31244	154	39	conference	conference	NOUN
fcis-31244	154	40	on	on	ADP
fcis-31244	154	41	power	power	NOUN
fcis-31244	154	42	,	,	PUNCT
fcis-31244	154	43	energy	energy	NOUN
fcis-31244	154	44	,	,	PUNCT
fcis-31244	154	45	and	and	CCONJ
fcis-31244	154	46	electrical	electrical	ADJ
fcis-31244	154	47	engineering	engineering	NOUN
fcis-31244	154	48	(	(	PUNCT
fcis-31244	154	49	cpeee	cpeee	NOUN
fcis-31244	154	50	)	)	PUNCT
fcis-31244	154	51	.	.	PUNCT
fcis-31244	155	1	ieee	ieee	NOUN
fcis-31244	155	2	,	,	PUNCT
fcis-31244	155	3	2025	2025	NUM
fcis-31244	155	4	:	:	PUNCT
fcis-31244	155	5	207	207	NUM
fcis-31244	155	6	-	-	SYM
fcis-31244	155	7	214	214	NUM
fcis-31244	155	8	.	.	PUNCT
fcis-31244	156	1	[	[	X
fcis-31244	156	2	18	18	NUM
fcis-31244	156	3	]	]	PUNCT
fcis-31244	156	4	boitel	boitel	NOUN
fcis-31244	156	5	e	e	NOUN
fcis-31244	156	6	,	,	PUNCT
fcis-31244	156	7	mohasseb	mohasseb	NOUN
fcis-31244	156	8	a	a	PROPN
fcis-31244	156	9	,	,	PUNCT
fcis-31244	156	10	haig	haig	PROPN
fcis-31244	156	11	e.	e.	PROPN
fcis-31244	156	12	mist	mist	PROPN
fcis-31244	156	13	:	:	PUNCT
fcis-31244	156	14	multimodal	multimodal	NOUN
fcis-31244	156	15	emotion	emotion	NOUN
fcis-31244	156	16	recognition	recognition	NOUN
fcis-31244	156	17	using	use	VERB
fcis-31244	156	18	deberta	deberta	NOUN
fcis-31244	156	19	for	for	ADP
fcis-31244	156	20	text	text	NOUN
fcis-31244	156	21	,	,	PUNCT
fcis-31244	156	22	semi	semi	ADJ
fcis-31244	156	23	-	-	VERB
fcis-31244	156	24	cnn	cnn	NOUN
fcis-31244	156	25	for	for	ADP
fcis-31244	156	26	speech	speech	NOUN
fcis-31244	156	27	,	,	PUNCT
fcis-31244	156	28	resnet-50	resnet-50	PROPN
fcis-31244	156	29	for	for	ADP
fcis-31244	156	30	facial	facial	ADJ
fcis-31244	156	31	,	,	PUNCT
fcis-31244	156	32	and	and	CCONJ
fcis-31244	156	33	3d	3d	X
fcis-31244	156	34	-	-	PUNCT
fcis-31244	156	35	cnn	cnn	PROPN
fcis-31244	156	36	for	for	ADP
fcis-31244	156	37	motion	motion	NOUN
fcis-31244	156	38	analysis[j	analysis[j	PROPN
fcis-31244	156	39	]	]	PUNCT
fcis-31244	156	40	.	.	PUNCT
fcis-31244	157	1	expert	expert	NOUN
fcis-31244	157	2	systems	system	NOUN
fcis-31244	157	3	with	with	ADP
fcis-31244	157	4	applications	application	NOUN
fcis-31244	157	5	,	,	PUNCT
fcis-31244	157	6	2025	2025	NUM
fcis-31244	157	7	,	,	PUNCT
fcis-31244	157	8	270	270	NUM
fcis-31244	157	9	:	:	SYM
fcis-31244	157	10	126236	126236	NUM
fcis-31244	157	11	.	.	PUNCT
fcis-31244	158	1	[	[	X
fcis-31244	158	2	19	19	NUM
fcis-31244	158	3	]	]	X
fcis-31244	158	4	shahid	shahid	PROPN
fcis-31244	158	5	m	m	VERB
fcis-31244	158	6	a	a	PRON
fcis-31244	158	7	,	,	PUNCT
fcis-31244	158	8	raza	raza	PROPN
fcis-31244	158	9	m	m	PROPN
fcis-31244	158	10	,	,	PUNCT
fcis-31244	158	11	sharif	sharif	PROPN
fcis-31244	158	12	m	m	PROPN
fcis-31244	158	13	,	,	PUNCT
fcis-31244	158	14	et	et	PROPN
fcis-31244	158	15	al	al	PROPN
fcis-31244	158	16	.	.	PROPN
fcis-31244	158	17	pedestrian	pedestrian	PROPN
fcis-31244	158	18	pose	pose	NOUN
fcis-31244	158	19	estimation	estimation	NOUN
fcis-31244	158	20	using	use	VERB
fcis-31244	158	21	multi	multi	ADJ
fcis-31244	158	22	-	-	ADJ
fcis-31244	158	23	branched	branched	ADJ
fcis-31244	158	24	deep	deep	ADJ
fcis-31244	158	25	learning	learning	NOUN
fcis-31244	158	26	pose	pose	VERB
fcis-31244	158	27	net[j	net[j	ADV
fcis-31244	158	28	]	]	PUNCT
fcis-31244	158	29	.	.	PUNCT
fcis-31244	159	1	plos	plos	PROPN
fcis-31244	159	2	one	one	NUM
fcis-31244	159	3	,	,	PUNCT
fcis-31244	159	4	2025	2025	NUM
fcis-31244	159	5	,	,	PUNCT
fcis-31244	159	6	20(1	20(1	NUM
fcis-31244	159	7	):	):	PUNCT
fcis-31244	159	8	e0312177	e0312177	PROPN
fcis-31244	159	9	.	.	PUNCT
fcis-31244	160	1	[	[	X
fcis-31244	160	2	20	20	NUM
fcis-31244	160	3	]	]	X
fcis-31244	160	4	zhang	zhang	PROPN
fcis-31244	160	5	w.	w.	PROPN
fcis-31244	160	6	dynamic	dynamic	PROPN
fcis-31244	160	7	pose	pose	NOUN
fcis-31244	160	8	recognition	recognition	NOUN
fcis-31244	160	9	based	base	VERB
fcis-31244	160	10	on	on	ADP
fcis-31244	160	11	deep	deep	ADJ
fcis-31244	160	12	learning	learning	NOUN
fcis-31244	160	13	:	:	PUNCT
fcis-31244	160	14	developing	develop	VERB
fcis-31244	160	15	a	a	DET
fcis-31244	160	16	cnn	cnn	PROPN
fcis-31244	160	17	model	model	NOUN
fcis-31244	160	18	for	for	ADP
fcis-31244	160	19	choral	choral	ADJ
fcis-31244	160	20	conductor	conductor	NOUN
fcis-31244	160	21	pose	pose	VERB
fcis-31244	160	22	recognition	recognition	NOUN
fcis-31244	161	1	[	[	X
fcis-31244	161	2	j	j	X
fcis-31244	161	3	]	]	X
fcis-31244	161	4	.	.	PUNCT
fcis-31244	162	1	journal	journal	PROPN
fcis-31244	162	2	of	of	ADP
fcis-31244	162	3	computational	computational	ADJ
fcis-31244	162	4	methods	method	NOUN
fcis-31244	162	5	in	in	ADP
fcis-31244	162	6	sciences	science	NOUN
fcis-31244	162	7	and	and	CCONJ
fcis-31244	162	8	engineering	engineering	NOUN
fcis-31244	162	9	,	,	PUNCT
fcis-31244	162	10	2025	2025	NUM
fcis-31244	162	11	:	:	PUNCT
fcis-31244	162	12	14727978251323068	14727978251323068	NUM
fcis-31244	162	13	.	.	PUNCT
fcis-31244	163	1	[	[	X
fcis-31244	163	2	21	21	NUM
fcis-31244	163	3	]	]	X
fcis-31244	163	4	huang	huang	PROPN
fcis-31244	163	5	s	s	PROPN
fcis-31244	163	6	,	,	PUNCT
fcis-31244	163	7	zhang	zhang	PROPN
fcis-31244	163	8	h	h	PROPN
fcis-31244	163	9	,	,	PUNCT
fcis-31244	163	10	li	li	PROPN
fcis-31244	163	11	x.	x.	PROPN
fcis-31244	163	12	enhance	enhance	VERB
fcis-31244	163	13	vision	vision	NOUN
fcis-31244	163	14	-	-	PUNCT
fcis-31244	163	15	language	language	NOUN
fcis-31244	163	16	alignment	alignment	NOUN
fcis-31244	163	17	with	with	ADP
fcis-31244	163	18	noise	noise	NOUN
fcis-31244	163	19	[	[	X
fcis-31244	163	20	c]//proceedings	c]//proceeding	NOUN
fcis-31244	163	21	of	of	ADP
fcis-31244	163	22	the	the	DET
fcis-31244	163	23	aaai	aaai	PROPN
fcis-31244	163	24	conference	conference	NOUN
fcis-31244	163	25	on	on	ADP
fcis-31244	163	26	artificial	artificial	ADJ
fcis-31244	163	27	intelligence	intelligence	NOUN
fcis-31244	163	28	.	.	PUNCT
fcis-31244	164	1	2025	2025	NUM
fcis-31244	164	2	,	,	PUNCT
fcis-31244	164	3	39(16	39(16	NUM
fcis-31244	164	4	):	):	PUNCT
fcis-31244	164	5	17449	17449	NUM
fcis-31244	164	6	-	-	SYM
fcis-31244	164	7	17457	17457	NUM
fcis-31244	164	8	.	.	PUNCT
fcis-31244	165	1	[	[	X
fcis-31244	165	2	22	22	NUM
fcis-31244	165	3	]	]	X
fcis-31244	165	4	falisse	falisse	NOUN
fcis-31244	165	5	a	a	PRON
fcis-31244	165	6	,	,	PUNCT
fcis-31244	165	7	uhlrich	uhlrich	PROPN
fcis-31244	165	8	s	s	PROPN
fcis-31244	165	9	d	d	PROPN
fcis-31244	165	10	,	,	PUNCT
fcis-31244	165	11	chaudhari	chaudhari	PRON
fcis-31244	165	12	a	a	DET
fcis-31244	165	13	s	s	PROPN
fcis-31244	165	14	,	,	PUNCT
fcis-31244	165	15	et	et	PROPN
fcis-31244	165	16	al	al	PROPN
fcis-31244	165	17	.	.	PROPN
fcis-31244	166	1	marker	marker	NOUN
fcis-31244	166	2	data	datum	NOUN
fcis-31244	166	3	enhancement	enhancement	NOUN
fcis-31244	166	4	for	for	ADP
fcis-31244	166	5	markerless	markerless	ADJ
fcis-31244	166	6	motion	motion	NOUN
fcis-31244	166	7	capture[j	capture[j	NOUN
fcis-31244	166	8	]	]	PUNCT
fcis-31244	166	9	.	.	PUNCT
fcis-31244	167	1	ieee	ieee	NOUN
fcis-31244	167	2	transactions	transaction	NOUN
fcis-31244	167	3	on	on	ADP
fcis-31244	167	4	biomedical	biomedical	ADJ
fcis-31244	167	5	engineering	engineering	NOUN
fcis-31244	167	6	,	,	PUNCT
fcis-31244	167	7	2025	2025	NUM
fcis-31244	167	8	.	.	PUNCT