id	sid	tid	token	lemma	pos
ajst-20214	1	1	academic	academic	ADJ
ajst-20214	1	2	journal	journal	NOUN
ajst-20214	1	3	of	of	ADP
ajst-20214	1	4	science	science	NOUN
ajst-20214	1	5	and	and	CCONJ
ajst-20214	1	6	technology	technology	NOUN
ajst-20214	1	7	issn	issn	NOUN
ajst-20214	1	8	:	:	PUNCT
ajst-20214	1	9	2771	2771	NUM
ajst-20214	1	10	-	-	SYM
ajst-20214	1	11	3032	3032	NUM
ajst-20214	1	12	|	|	NOUN
ajst-20214	1	13	vol	vol	NOUN
ajst-20214	1	14	.	.	PROPN
ajst-20214	2	1	10	10	NUM
ajst-20214	2	2	,	,	PUNCT
ajst-20214	2	3	no	no	INTJ
ajst-20214	2	4	.	.	NOUN
ajst-20214	2	5	2	2	NUM
ajst-20214	2	6	,	,	PUNCT
ajst-20214	2	7	2024	2024	NUM
ajst-20214	2	8	181	181	NUM
ajst-20214	2	9	a	a	DET
ajst-20214	2	10	design	design	NOUN
ajst-20214	2	11	of	of	ADP
ajst-20214	2	12	model	model	NOUN
ajst-20214	2	13	compression	compression	NOUN
ajst-20214	2	14	method	method	NOUN
ajst-20214	2	15	based	base	VERB
ajst-20214	2	16	on	on	ADP
ajst-20214	2	17	yolov5	yolov5	NOUN
ajst-20214	2	18	zeyang	zeyang	PROPN
ajst-20214	2	19	wang1	wang1	PROPN
ajst-20214	2	20	,	,	PUNCT
ajst-20214	2	21	huawei	huawei	PROPN
ajst-20214	2	22	mei1	mei1	PROPN
ajst-20214	2	23	,	,	PUNCT
ajst-20214	2	24	*	*	PUNCT
ajst-20214	2	25	and	and	CCONJ
ajst-20214	2	26	yi	yi	PROPN
ajst-20214	2	27	fang1	fang1	NOUN
ajst-20214	3	1	1school	1school	NUM
ajst-20214	3	2	of	of	ADP
ajst-20214	3	3	control	control	NOUN
ajst-20214	3	4	and	and	CCONJ
ajst-20214	3	5	computer	computer	NOUN
ajst-20214	3	6	engineering	engineering	NOUN
ajst-20214	3	7	,	,	PUNCT
ajst-20214	4	1	north	north	PROPN
ajst-20214	4	2	china	china	PROPN
ajst-20214	4	3	electric	electric	PROPN
ajst-20214	4	4	power	power	PROPN
ajst-20214	4	5	university	university	PROPN
ajst-20214	4	6	,	,	PUNCT
ajst-20214	4	7	baoding	baoding	PROPN
ajst-20214	4	8	071003	071003	NUM
ajst-20214	4	9	,	,	PUNCT
ajst-20214	4	10	china	china	PROPN
ajst-20214	4	11	*	*	PUNCT
ajst-20214	4	12	corresponding	correspond	VERB
ajst-20214	4	13	author	author	NOUN
ajst-20214	4	14	email	email	NOUN
ajst-20214	4	15	:	:	PUNCT
ajst-20214	4	16	fn123@ncepu.edu.cn	fn123@ncepu.edu.cn	NOUN
ajst-20214	4	17	abstract	abstract	NOUN
ajst-20214	4	18	:	:	PUNCT
ajst-20214	4	19	in	in	ADP
ajst-20214	4	20	response	response	NOUN
ajst-20214	4	21	to	to	ADP
ajst-20214	4	22	the	the	DET
ajst-20214	4	23	requirements	requirement	NOUN
ajst-20214	4	24	for	for	ADP
ajst-20214	4	25	detection	detection	NOUN
ajst-20214	4	26	accuracy	accuracy	NOUN
ajst-20214	4	27	and	and	CCONJ
ajst-20214	4	28	speed	speed	NOUN
ajst-20214	4	29	in	in	ADP
ajst-20214	4	30	security	security	NOUN
ajst-20214	4	31	detection	detection	NOUN
ajst-20214	4	32	technology	technology	NOUN
ajst-20214	4	33	in	in	ADP
ajst-20214	4	34	current	current	ADJ
ajst-20214	4	35	smart	smart	ADJ
ajst-20214	4	36	city	city	NOUN
ajst-20214	4	37	construction	construction	NOUN
ajst-20214	4	38	,	,	PUNCT
ajst-20214	4	39	a	a	DET
ajst-20214	4	40	model	model	NOUN
ajst-20214	4	41	compression	compression	NOUN
ajst-20214	4	42	method	method	NOUN
ajst-20214	4	43	based	base	VERB
ajst-20214	4	44	on	on	ADP
ajst-20214	4	45	yolov5s	yolov5s	PROPN
ajst-20214	4	46	is	be	AUX
ajst-20214	4	47	proposed	propose	VERB
ajst-20214	4	48	,	,	PUNCT
ajst-20214	4	49	aiming	aim	VERB
ajst-20214	4	50	to	to	PART
ajst-20214	4	51	lighten	lighten	VERB
ajst-20214	4	52	the	the	DET
ajst-20214	4	53	original	original	ADJ
ajst-20214	4	54	model	model	NOUN
ajst-20214	4	55	and	and	CCONJ
ajst-20214	4	56	detect	detect	VERB
ajst-20214	4	57	the	the	DET
ajst-20214	4	58	opening	opening	NOUN
ajst-20214	4	59	and	and	CCONJ
ajst-20214	4	60	closing	closing	NOUN
ajst-20214	4	61	states	state	NOUN
ajst-20214	4	62	of	of	ADP
ajst-20214	4	63	car	car	NOUN
ajst-20214	4	64	windows	window	NOUN
ajst-20214	4	65	.	.	PUNCT
ajst-20214	5	1	firstly	firstly	ADV
ajst-20214	5	2	,	,	PUNCT
ajst-20214	5	3	a	a	DET
ajst-20214	5	4	structured	structured	ADJ
ajst-20214	5	5	pruning	pruning	NOUN
ajst-20214	5	6	method	method	NOUN
ajst-20214	5	7	based	base	VERB
ajst-20214	5	8	on	on	ADP
ajst-20214	5	9	channel	channel	NOUN
ajst-20214	5	10	weights	weight	NOUN
ajst-20214	5	11	is	be	AUX
ajst-20214	5	12	employed	employ	VERB
ajst-20214	5	13	to	to	PART
ajst-20214	5	14	perform	perform	VERB
ajst-20214	5	15	channel	channel	NOUN
ajst-20214	5	16	pruning	pruning	NOUN
ajst-20214	5	17	.	.	PUNCT
ajst-20214	6	1	then	then	ADV
ajst-20214	6	2	,	,	PUNCT
ajst-20214	6	3	a	a	DET
ajst-20214	6	4	fine	fine	ADV
ajst-20214	6	5	-	-	PUNCT
ajst-20214	6	6	tuning	tune	VERB
ajst-20214	6	7	training	training	NOUN
ajst-20214	6	8	method	method	NOUN
ajst-20214	6	9	based	base	VERB
ajst-20214	6	10	on	on	ADP
ajst-20214	6	11	logical	logical	ADJ
ajst-20214	6	12	distillation	distillation	NOUN
ajst-20214	6	13	is	be	AUX
ajst-20214	6	14	adopted	adopt	VERB
ajst-20214	6	15	to	to	PART
ajst-20214	6	16	restore	restore	VERB
ajst-20214	6	17	the	the	DET
ajst-20214	6	18	network	network	NOUN
ajst-20214	6	19	detection	detection	NOUN
ajst-20214	6	20	accuracy	accuracy	NOUN
ajst-20214	6	21	.	.	PUNCT
ajst-20214	7	1	experimental	experimental	ADJ
ajst-20214	7	2	results	result	NOUN
ajst-20214	7	3	on	on	ADP
ajst-20214	7	4	the	the	DET
ajst-20214	7	5	car	car	NOUN
ajst-20214	7	6	window	window	NOUN
ajst-20214	7	7	dataset	dataset	NOUN
ajst-20214	7	8	show	show	NOUN
ajst-20214	7	9	that	that	SCONJ
ajst-20214	7	10	compared	compare	VERB
ajst-20214	7	11	with	with	ADP
ajst-20214	7	12	the	the	DET
ajst-20214	7	13	original	original	ADJ
ajst-20214	7	14	algorithm	algorithm	NOUN
ajst-20214	7	15	,	,	PUNCT
ajst-20214	7	16	the	the	DET
ajst-20214	7	17	improved	improved	ADJ
ajst-20214	7	18	algorithm	algorithm	NOUN
ajst-20214	7	19	only	only	ADV
ajst-20214	7	20	loses	lose	VERB
ajst-20214	7	21	0.3	0.3	NUM
ajst-20214	7	22	%	%	NOUN
ajst-20214	7	23	in	in	ADP
ajst-20214	7	24	detection	detection	NOUN
ajst-20214	7	25	accuracy	accuracy	NOUN
ajst-20214	7	26	while	while	SCONJ
ajst-20214	7	27	reducing	reduce	VERB
ajst-20214	7	28	the	the	DET
ajst-20214	7	29	number	number	NOUN
ajst-20214	7	30	of	of	ADP
ajst-20214	7	31	parameters	parameter	NOUN
ajst-20214	7	32	and	and	CCONJ
ajst-20214	7	33	computations	computation	NOUN
ajst-20214	7	34	to	to	ADP
ajst-20214	7	35	41.5	41.5	NUM
ajst-20214	7	36	%	%	NOUN
ajst-20214	7	37	and	and	CCONJ
ajst-20214	7	38	44.3	44.3	NUM
ajst-20214	7	39	%	%	NOUN
ajst-20214	7	40	of	of	ADP
ajst-20214	7	41	the	the	DET
ajst-20214	7	42	original	original	ADJ
ajst-20214	7	43	model	model	NOUN
ajst-20214	7	44	,	,	PUNCT
ajst-20214	7	45	respectively	respectively	ADV
ajst-20214	7	46	.	.	PUNCT
ajst-20214	8	1	this	this	PRON
ajst-20214	8	2	significantly	significantly	ADV
ajst-20214	8	3	reduces	reduce	VERB
ajst-20214	8	4	the	the	DET
ajst-20214	8	5	model	model	NOUN
ajst-20214	8	6	complexity	complexity	NOUN
ajst-20214	8	7	and	and	CCONJ
ajst-20214	8	8	achieves	achieve	VERB
ajst-20214	8	9	model	model	NOUN
ajst-20214	8	10	lightweighting	lightweighting	NOUN
ajst-20214	8	11	.	.	PUNCT
ajst-20214	9	1	keywords	keyword	NOUN
ajst-20214	9	2	:	:	PUNCT
ajst-20214	9	3	object	object	VERB
ajst-20214	9	4	detection	detection	NOUN
ajst-20214	9	5	,	,	PUNCT
ajst-20214	9	6	model	model	NOUN
ajst-20214	9	7	compression	compression	NOUN
ajst-20214	9	8	,	,	PUNCT
ajst-20214	9	9	pruning	prune	VERB
ajst-20214	9	10	,	,	PUNCT
ajst-20214	9	11	logical	logical	ADJ
ajst-20214	9	12	distillation	distillation	NOUN
ajst-20214	9	13	.	.	PUNCT
ajst-20214	10	1	1	1	X
ajst-20214	10	2	.	.	X
ajst-20214	10	3	introduction	introduction	NOUN
ajst-20214	10	4	with	with	ADP
ajst-20214	10	5	the	the	DET
ajst-20214	10	6	continuous	continuous	ADJ
ajst-20214	10	7	advancement	advancement	NOUN
ajst-20214	10	8	of	of	ADP
ajst-20214	10	9	smart	smart	ADJ
ajst-20214	10	10	city	city	NOUN
ajst-20214	10	11	construction	construction	NOUN
ajst-20214	10	12	and	and	CCONJ
ajst-20214	10	13	the	the	DET
ajst-20214	10	14	rapid	rapid	ADJ
ajst-20214	10	15	development	development	NOUN
ajst-20214	10	16	of	of	ADP
ajst-20214	10	17	artificial	artificial	ADJ
ajst-20214	10	18	intelligence	intelligence	NOUN
ajst-20214	10	19	technology	technology	NOUN
ajst-20214	10	20	,	,	PUNCT
ajst-20214	10	21	intelligent	intelligent	ADJ
ajst-20214	10	22	security	security	NOUN
ajst-20214	10	23	and	and	CCONJ
ajst-20214	10	24	personnel	personnel	NOUN
ajst-20214	10	25	intelligent	intelligent	ADJ
ajst-20214	10	26	management	management	NOUN
ajst-20214	10	27	have	have	AUX
ajst-20214	10	28	gradually	gradually	ADV
ajst-20214	10	29	become	become	VERB
ajst-20214	10	30	the	the	DET
ajst-20214	10	31	focus	focus	NOUN
ajst-20214	10	32	of	of	ADP
ajst-20214	10	33	social	social	ADJ
ajst-20214	10	34	attention	attention	NOUN
ajst-20214	10	35	.	.	PUNCT
ajst-20214	11	1	smart	smart	ADJ
ajst-20214	11	2	cities	city	NOUN
ajst-20214	11	3	have	have	AUX
ajst-20214	11	4	installed	instal	VERB
ajst-20214	11	5	numerous	numerous	ADJ
ajst-20214	11	6	sensors	sensor	NOUN
ajst-20214	11	7	to	to	PART
ajst-20214	11	8	capture	capture	VERB
ajst-20214	11	9	vast	vast	ADJ
ajst-20214	11	10	amounts	amount	NOUN
ajst-20214	11	11	of	of	ADP
ajst-20214	11	12	data	datum	NOUN
ajst-20214	11	13	,	,	PUNCT
ajst-20214	11	14	such	such	ADJ
ajst-20214	11	15	as	as	ADP
ajst-20214	11	16	surveillance	surveillance	NOUN
ajst-20214	11	17	videos	video	NOUN
ajst-20214	11	18	,	,	PUNCT
ajst-20214	11	19	environmental	environmental	ADJ
ajst-20214	11	20	,	,	PUNCT
ajst-20214	11	21	and	and	CCONJ
ajst-20214	11	22	transportation	transportation	NOUN
ajst-20214	11	23	data	datum	NOUN
ajst-20214	11	24	.	.	PUNCT
ajst-20214	12	1	facing	face	VERB
ajst-20214	12	2	the	the	DET
ajst-20214	12	3	massive	massive	ADJ
ajst-20214	12	4	volume	volume	NOUN
ajst-20214	12	5	of	of	ADP
ajst-20214	12	6	video	video	NOUN
ajst-20214	12	7	surveillance	surveillance	NOUN
ajst-20214	12	8	data	datum	NOUN
ajst-20214	12	9	,	,	PUNCT
ajst-20214	12	10	diverse	diverse	ADJ
ajst-20214	12	11	personalized	personalized	ADJ
ajst-20214	12	12	security	security	NOUN
ajst-20214	12	13	task	task	NOUN
ajst-20214	12	14	requirements	requirement	NOUN
ajst-20214	12	15	in	in	ADP
ajst-20214	12	16	various	various	ADJ
ajst-20214	12	17	scenarios	scenario	NOUN
ajst-20214	12	18	,	,	PUNCT
ajst-20214	12	19	and	and	CCONJ
ajst-20214	12	20	the	the	DET
ajst-20214	12	21	performance	performance	NOUN
ajst-20214	12	22	demands	demand	NOUN
ajst-20214	12	23	of	of	ADP
ajst-20214	12	24	industrialized	industrialized	ADJ
ajst-20214	12	25	applications	application	NOUN
ajst-20214	12	26	,	,	PUNCT
ajst-20214	12	27	traditional	traditional	ADJ
ajst-20214	12	28	security	security	NOUN
ajst-20214	12	29	technologies	technology	NOUN
ajst-20214	12	30	can	can	AUX
ajst-20214	12	31	no	no	ADV
ajst-20214	12	32	longer	long	ADV
ajst-20214	12	33	meet	meet	VERB
ajst-20214	12	34	current	current	ADJ
ajst-20214	12	35	market	market	NOUN
ajst-20214	12	36	needs	need	NOUN
ajst-20214	12	37	.	.	PUNCT
ajst-20214	13	1	compared	compare	VERB
ajst-20214	13	2	to	to	ADP
ajst-20214	13	3	traditional	traditional	ADJ
ajst-20214	13	4	security	security	NOUN
ajst-20214	13	5	technologies	technology	NOUN
ajst-20214	13	6	,	,	PUNCT
ajst-20214	13	7	deep	deep	ADJ
ajst-20214	13	8	learning	learning	NOUN
ajst-20214	13	9	-	-	PUNCT
ajst-20214	13	10	based	base	VERB
ajst-20214	13	11	visual	visual	ADJ
ajst-20214	13	12	algorithms	algorithm	NOUN
ajst-20214	13	13	exhibit	exhibit	VERB
ajst-20214	13	14	significant	significant	ADJ
ajst-20214	13	15	advantages	advantage	NOUN
ajst-20214	13	16	in	in	ADP
ajst-20214	13	17	network	network	NOUN
ajst-20214	13	18	recognition	recognition	NOUN
ajst-20214	13	19	accuracy	accuracy	NOUN
ajst-20214	13	20	,	,	PUNCT
ajst-20214	13	21	efficiency	efficiency	NOUN
ajst-20214	13	22	,	,	PUNCT
ajst-20214	13	23	and	and	CCONJ
ajst-20214	13	24	model	model	NOUN
ajst-20214	13	25	generalization	generalization	NOUN
ajst-20214	13	26	capabilities	capability	NOUN
ajst-20214	13	27	,	,	PUNCT
ajst-20214	13	28	making	make	VERB
ajst-20214	13	29	them	they	PRON
ajst-20214	13	30	crucial	crucial	ADJ
ajst-20214	13	31	for	for	ADP
ajst-20214	13	32	obtaining	obtain	VERB
ajst-20214	13	33	the	the	DET
ajst-20214	13	34	most	most	ADV
ajst-20214	13	35	useful	useful	ADJ
ajst-20214	13	36	information	information	NOUN
ajst-20214	13	37	from	from	ADP
ajst-20214	13	38	massive	massive	ADJ
ajst-20214	13	39	datasets	dataset	NOUN
ajst-20214	13	40	.	.	PUNCT
ajst-20214	14	1	target	target	NOUN
ajst-20214	14	2	detection	detection	NOUN
ajst-20214	14	3	technology	technology	NOUN
ajst-20214	14	4	plays	play	VERB
ajst-20214	14	5	a	a	DET
ajst-20214	14	6	vital	vital	ADJ
ajst-20214	14	7	role	role	NOUN
ajst-20214	14	8	in	in	ADP
ajst-20214	14	9	the	the	DET
ajst-20214	14	10	field	field	NOUN
ajst-20214	14	11	of	of	ADP
ajst-20214	14	12	intelligent	intelligent	ADJ
ajst-20214	14	13	security	security	NOUN
ajst-20214	14	14	.	.	PUNCT
ajst-20214	15	1	moreover	moreover	ADV
ajst-20214	15	2	,	,	PUNCT
ajst-20214	15	3	as	as	ADP
ajst-20214	15	4	edge	edge	NOUN
ajst-20214	15	5	devices	device	NOUN
ajst-20214	15	6	(	(	PUNCT
ajst-20214	15	7	such	such	ADJ
ajst-20214	15	8	as	as	ADP
ajst-20214	15	9	smartphones	smartphone	NOUN
ajst-20214	15	10	and	and	CCONJ
ajst-20214	15	11	embedded	embed	VERB
ajst-20214	15	12	systems	system	NOUN
ajst-20214	15	13	)	)	PUNCT
ajst-20214	15	14	become	become	VERB
ajst-20214	15	15	increasingly	increasingly	ADV
ajst-20214	15	16	popular	popular	ADJ
ajst-20214	15	17	due	due	ADP
ajst-20214	15	18	to	to	ADP
ajst-20214	15	19	their	their	PRON
ajst-20214	15	20	small	small	ADJ
ajst-20214	15	21	size	size	NOUN
ajst-20214	15	22	,	,	PUNCT
ajst-20214	15	23	high	high	ADJ
ajst-20214	15	24	cost	cost	NOUN
ajst-20214	15	25	-	-	PUNCT
ajst-20214	15	26	effectiveness	effectiveness	NOUN
ajst-20214	15	27	,	,	PUNCT
ajst-20214	15	28	and	and	CCONJ
ajst-20214	15	29	low	low	ADJ
ajst-20214	15	30	power	power	NOUN
ajst-20214	15	31	consumption	consumption	NOUN
ajst-20214	15	32	,	,	PUNCT
ajst-20214	15	33	more	more	ADJ
ajst-20214	15	34	researchers	researcher	NOUN
ajst-20214	15	35	are	be	AUX
ajst-20214	15	36	exploring	explore	VERB
ajst-20214	15	37	their	their	PRON
ajst-20214	15	38	computing	computing	NOUN
ajst-20214	15	39	capabilities	capability	NOUN
ajst-20214	15	40	.	.	PUNCT
ajst-20214	16	1	target	target	NOUN
ajst-20214	16	2	detection	detection	NOUN
ajst-20214	16	3	algorithms	algorithm	NOUN
ajst-20214	16	4	can	can	AUX
ajst-20214	16	5	also	also	ADV
ajst-20214	16	6	leverage	leverage	VERB
ajst-20214	16	7	the	the	DET
ajst-20214	16	8	advantages	advantage	NOUN
ajst-20214	16	9	of	of	ADP
ajst-20214	16	10	edge	edge	NOUN
ajst-20214	16	11	computing	compute	VERB
ajst-20214	16	12	to	to	PART
ajst-20214	16	13	enhance	enhance	VERB
ajst-20214	16	14	the	the	DET
ajst-20214	16	15	real	real	ADJ
ajst-20214	16	16	-	-	PUNCT
ajst-20214	16	17	time	time	NOUN
ajst-20214	16	18	responsiveness	responsiveness	NOUN
ajst-20214	16	19	of	of	ADP
ajst-20214	16	20	systems	system	NOUN
ajst-20214	16	21	and	and	CCONJ
ajst-20214	16	22	be	be	AUX
ajst-20214	16	23	applied	apply	VERB
ajst-20214	16	24	in	in	ADP
ajst-20214	16	25	areas	area	NOUN
ajst-20214	16	26	such	such	ADJ
ajst-20214	16	27	as	as	ADP
ajst-20214	16	28	autonomous	autonomous	ADJ
ajst-20214	16	29	driving	driving	NOUN
ajst-20214	16	30	,	,	PUNCT
ajst-20214	16	31	unmanned	unmanned	ADJ
ajst-20214	16	32	aerial	aerial	ADJ
ajst-20214	16	33	vehicle	vehicle	NOUN
ajst-20214	16	34	(	(	PUNCT
ajst-20214	16	35	uav	uav	PROPN
ajst-20214	16	36	)	)	PUNCT
ajst-20214	16	37	automatic	automatic	ADJ
ajst-20214	16	38	inspection	inspection	NOUN
ajst-20214	16	39	,	,	PUNCT
ajst-20214	16	40	and	and	CCONJ
ajst-20214	16	41	face	face	NOUN
ajst-20214	16	42	recognition	recognition	NOUN
ajst-20214	16	43	.	.	PUNCT
ajst-20214	17	1	however	however	ADV
ajst-20214	17	2	,	,	PUNCT
ajst-20214	17	3	as	as	SCONJ
ajst-20214	17	4	the	the	DET
ajst-20214	17	5	pursuit	pursuit	NOUN
ajst-20214	17	6	of	of	ADP
ajst-20214	17	7	detection	detection	NOUN
ajst-20214	17	8	accuracy	accuracy	NOUN
ajst-20214	17	9	continues	continue	VERB
ajst-20214	17	10	to	to	PART
ajst-20214	17	11	increase	increase	VERB
ajst-20214	17	12	,	,	PUNCT
ajst-20214	17	13	the	the	DET
ajst-20214	17	14	network	network	NOUN
ajst-20214	17	15	structures	structure	NOUN
ajst-20214	17	16	of	of	ADP
ajst-20214	17	17	target	target	NOUN
ajst-20214	17	18	detection	detection	NOUN
ajst-20214	17	19	algorithms	algorithm	NOUN
ajst-20214	17	20	have	have	AUX
ajst-20214	17	21	become	become	VERB
ajst-20214	17	22	increasingly	increasingly	ADV
ajst-20214	17	23	complex	complex	ADJ
ajst-20214	17	24	,	,	PUNCT
ajst-20214	17	25	with	with	ADP
ajst-20214	17	26	deeper	deep	ADJ
ajst-20214	17	27	network	network	NOUN
ajst-20214	17	28	layers	layer	NOUN
ajst-20214	17	29	,	,	PUNCT
ajst-20214	17	30	leading	lead	VERB
ajst-20214	17	31	to	to	ADP
ajst-20214	17	32	a	a	DET
ajst-20214	17	33	sharp	sharp	ADJ
ajst-20214	17	34	increase	increase	NOUN
ajst-20214	17	35	in	in	ADP
ajst-20214	17	36	model	model	NOUN
ajst-20214	17	37	parameters	parameter	NOUN
ajst-20214	17	38	and	and	CCONJ
ajst-20214	17	39	computations	computation	NOUN
ajst-20214	17	40	.	.	PUNCT
ajst-20214	18	1	this	this	PRON
ajst-20214	18	2	poses	pose	VERB
ajst-20214	18	3	higher	high	ADJ
ajst-20214	18	4	requirements	requirement	NOUN
ajst-20214	18	5	for	for	ADP
ajst-20214	18	6	devices	device	NOUN
ajst-20214	18	7	and	and	CCONJ
ajst-20214	18	8	makes	make	VERB
ajst-20214	18	9	it	it	PRON
ajst-20214	18	10	difficult	difficult	ADJ
ajst-20214	18	11	to	to	PART
ajst-20214	18	12	deploy	deploy	VERB
ajst-20214	18	13	and	and	CCONJ
ajst-20214	18	14	apply	apply	VERB
ajst-20214	18	15	them	they	PRON
ajst-20214	18	16	on	on	ADP
ajst-20214	18	17	edge	edge	NOUN
ajst-20214	18	18	computing	computing	NOUN
ajst-20214	18	19	devices	device	NOUN
ajst-20214	18	20	with	with	ADP
ajst-20214	18	21	limited	limited	ADJ
ajst-20214	18	22	computing	computing	NOUN
ajst-20214	18	23	power	power	NOUN
ajst-20214	18	24	and	and	CCONJ
ajst-20214	18	25	storage	storage	NOUN
ajst-20214	18	26	,	,	PUNCT
ajst-20214	18	27	such	such	ADJ
ajst-20214	18	28	as	as	ADP
ajst-20214	18	29	smartphones	smartphone	NOUN
ajst-20214	18	30	and	and	CCONJ
ajst-20214	18	31	embedded	embed	VERB
ajst-20214	18	32	systems	system	NOUN
ajst-20214	18	33	.	.	PUNCT
ajst-20214	19	1	therefore	therefore	ADV
ajst-20214	19	2	,	,	PUNCT
ajst-20214	19	3	many	many	ADJ
ajst-20214	19	4	experts	expert	NOUN
ajst-20214	19	5	and	and	CCONJ
ajst-20214	19	6	scholars	scholar	NOUN
ajst-20214	19	7	have	have	AUX
ajst-20214	19	8	begun	begin	VERB
ajst-20214	19	9	to	to	PART
ajst-20214	19	10	investigate	investigate	VERB
ajst-20214	19	11	methods	method	NOUN
ajst-20214	19	12	for	for	ADP
ajst-20214	19	13	lightweighting	lightweighte	VERB
ajst-20214	19	14	deep	deep	ADJ
ajst-20214	19	15	learning	learning	NOUN
ajst-20214	19	16	models	model	NOUN
ajst-20214	19	17	and	and	CCONJ
ajst-20214	19	18	deploying	deploy	VERB
ajst-20214	19	19	lightweight	lightweight	ADJ
ajst-20214	19	20	target	target	NOUN
ajst-20214	19	21	detection	detection	NOUN
ajst-20214	19	22	models	model	NOUN
ajst-20214	19	23	on	on	ADP
ajst-20214	19	24	edge	edge	NOUN
ajst-20214	19	25	devices	device	NOUN
ajst-20214	19	26	to	to	PART
ajst-20214	19	27	enable	enable	VERB
ajst-20214	19	28	real	real	ADJ
ajst-20214	19	29	-	-	PUNCT
ajst-20214	19	30	time	time	NOUN
ajst-20214	19	31	detection	detection	NOUN
ajst-20214	19	32	tasks	task	NOUN
ajst-20214	19	33	.	.	PUNCT
ajst-20214	20	1	to	to	PART
ajst-20214	20	2	achieve	achieve	VERB
ajst-20214	20	3	this	this	DET
ajst-20214	20	4	goal	goal	NOUN
ajst-20214	20	5	,	,	PUNCT
ajst-20214	20	6	this	this	DET
ajst-20214	20	7	article	article	NOUN
ajst-20214	20	8	proposes	propose	VERB
ajst-20214	20	9	a	a	DET
ajst-20214	20	10	model	model	NOUN
ajst-20214	20	11	compression	compression	NOUN
ajst-20214	20	12	design	design	NOUN
ajst-20214	20	13	method	method	NOUN
ajst-20214	20	14	based	base	VERB
ajst-20214	20	15	on	on	ADP
ajst-20214	20	16	yolov5	yolov5	NOUN
ajst-20214	20	17	,	,	PUNCT
ajst-20214	20	18	aiming	aim	VERB
ajst-20214	20	19	to	to	PART
ajst-20214	20	20	lighten	lighten	VERB
ajst-20214	20	21	the	the	DET
ajst-20214	20	22	yolov5	yolov5	NOUN
ajst-20214	20	23	target	target	NOUN
ajst-20214	20	24	detection	detection	NOUN
ajst-20214	20	25	model	model	NOUN
ajst-20214	20	26	without	without	ADP
ajst-20214	20	27	compromising	compromise	VERB
ajst-20214	20	28	detection	detection	NOUN
ajst-20214	20	29	accuracy	accuracy	NOUN
ajst-20214	20	30	.	.	PUNCT
ajst-20214	21	1	the	the	DET
ajst-20214	21	2	following	follow	VERB
ajst-20214	21	3	innovations	innovation	NOUN
ajst-20214	21	4	are	be	AUX
ajst-20214	21	5	made	make	VERB
ajst-20214	21	6	in	in	ADP
ajst-20214	21	7	this	this	DET
ajst-20214	21	8	article	article	NOUN
ajst-20214	21	9	:	:	PUNCT
ajst-20214	21	10	1	1	X
ajst-20214	21	11	)	)	PUNCT
ajst-20214	21	12	adopting	adopt	VERB
ajst-20214	21	13	a	a	DET
ajst-20214	21	14	structured	structured	ADJ
ajst-20214	21	15	pruning	pruning	NOUN
ajst-20214	21	16	method	method	NOUN
ajst-20214	21	17	based	base	VERB
ajst-20214	21	18	on	on	ADP
ajst-20214	21	19	channel	channel	NOUN
ajst-20214	21	20	weights	weight	NOUN
ajst-20214	21	21	to	to	PART
ajst-20214	21	22	prune	prune	NOUN
ajst-20214	21	23	channels	channel	NOUN
ajst-20214	21	24	with	with	ADP
ajst-20214	21	25	lower	low	ADJ
ajst-20214	21	26	weights	weight	NOUN
ajst-20214	21	27	and	and	CCONJ
ajst-20214	21	28	minimal	minimal	ADJ
ajst-20214	21	29	impact	impact	NOUN
ajst-20214	21	30	on	on	ADP
ajst-20214	21	31	the	the	DET
ajst-20214	21	32	network	network	NOUN
ajst-20214	21	33	model	model	NOUN
ajst-20214	21	34	,	,	PUNCT
ajst-20214	21	35	achieving	achieve	VERB
ajst-20214	21	36	effective	effective	ADJ
ajst-20214	21	37	model	model	NOUN
ajst-20214	21	38	compression	compression	NOUN
ajst-20214	21	39	;	;	PUNCT
ajst-20214	21	40	2	2	X
ajst-20214	21	41	)	)	PUNCT
ajst-20214	21	42	employing	employ	VERB
ajst-20214	21	43	a	a	DET
ajst-20214	21	44	fine	fine	ADV
ajst-20214	21	45	-	-	PUNCT
ajst-20214	21	46	tuning	tune	VERB
ajst-20214	21	47	training	training	NOUN
ajst-20214	21	48	method	method	NOUN
ajst-20214	21	49	based	base	VERB
ajst-20214	21	50	on	on	ADP
ajst-20214	21	51	logical	logical	ADJ
ajst-20214	21	52	distillation	distillation	NOUN
ajst-20214	21	53	to	to	PART
ajst-20214	21	54	restore	restore	VERB
ajst-20214	21	55	the	the	DET
ajst-20214	21	56	detection	detection	NOUN
ajst-20214	21	57	accuracy	accuracy	NOUN
ajst-20214	21	58	reduced	reduce	VERB
ajst-20214	21	59	by	by	ADP
ajst-20214	21	60	pruning	prune	VERB
ajst-20214	21	61	operations	operation	NOUN
ajst-20214	21	62	.	.	PUNCT
ajst-20214	22	1	finally	finally	ADV
ajst-20214	22	2	,	,	PUNCT
ajst-20214	22	3	experiments	experiment	NOUN
ajst-20214	22	4	demonstrate	demonstrate	VERB
ajst-20214	22	5	the	the	DET
ajst-20214	22	6	effectiveness	effectiveness	NOUN
ajst-20214	22	7	of	of	ADP
ajst-20214	22	8	the	the	DET
ajst-20214	22	9	proposed	propose	VERB
ajst-20214	22	10	model	model	NOUN
ajst-20214	22	11	compression	compression	NOUN
ajst-20214	22	12	method	method	NOUN
ajst-20214	22	13	.	.	PUNCT
ajst-20214	23	1	2	2	X
ajst-20214	23	2	.	.	X
ajst-20214	23	3	related	relate	VERB
ajst-20214	23	4	work	work	NOUN
ajst-20214	23	5	2.1	2.1	NUM
ajst-20214	23	6	.	.	PUNCT
ajst-20214	24	1	deep	deep	ADJ
ajst-20214	24	2	learning	learning	NOUN
ajst-20214	24	3	-	-	PUNCT
ajst-20214	24	4	based	base	VERB
ajst-20214	24	5	object	object	NOUN
ajst-20214	24	6	detection	detection	NOUN
ajst-20214	24	7	technique	technique	NOUN
ajst-20214	24	8	.	.	PUNCT
ajst-20214	25	1	deep	deep	ADJ
ajst-20214	25	2	learning	learning	NOUN
ajst-20214	25	3	-	-	PUNCT
ajst-20214	25	4	based	base	VERB
ajst-20214	25	5	object	object	NOUN
ajst-20214	25	6	detection	detection	NOUN
ajst-20214	25	7	algorithms	algorithm	NOUN
ajst-20214	25	8	can	can	AUX
ajst-20214	25	9	be	be	AUX
ajst-20214	25	10	roughly	roughly	ADV
ajst-20214	25	11	categorized	categorize	VERB
ajst-20214	25	12	into	into	ADP
ajst-20214	25	13	two	two	NUM
ajst-20214	25	14	main	main	ADJ
ajst-20214	25	15	types	type	NOUN
ajst-20214	25	16	:	:	PUNCT
ajst-20214	25	17	1	1	X
ajst-20214	25	18	)	)	PUNCT
ajst-20214	25	19	two	two	NUM
ajst-20214	25	20	-	-	PUNCT
ajst-20214	25	21	stage	stage	NOUN
ajst-20214	25	22	object	object	NOUN
ajst-20214	25	23	detection	detection	NOUN
ajst-20214	25	24	,	,	PUNCT
ajst-20214	25	25	such	such	ADJ
ajst-20214	25	26	as	as	ADP
ajst-20214	25	27	r	r	NOUN
ajst-20214	25	28	-	-	PUNCT
ajst-20214	25	29	cnn[1	cnn[1	NOUN
ajst-20214	25	30	]	]	X
ajst-20214	25	31	,	,	PUNCT
ajst-20214	25	32	fast	fast	ADJ
ajst-20214	25	33	r	r	NOUN
ajst-20214	25	34	-	-	PUNCT
ajst-20214	25	35	cnn[2	cnn[2	NOUN
ajst-20214	25	36	]	]	PUNCT
ajst-20214	25	37	,	,	PUNCT
ajst-20214	25	38	faster	fast	ADV
ajst-20214	25	39	rcnn[3	rcnn[3	PROPN
ajst-20214	25	40	]	]	PUNCT
ajst-20214	25	41	,	,	PUNCT
ajst-20214	25	42	and	and	CCONJ
ajst-20214	25	43	so	so	ADV
ajst-20214	25	44	on	on	ADV
ajst-20214	25	45	;	;	PUNCT
ajst-20214	25	46	and	and	CCONJ
ajst-20214	25	47	2	2	X
ajst-20214	25	48	)	)	PUNCT
ajst-20214	25	49	one	one	NUM
ajst-20214	25	50	-	-	PUNCT
ajst-20214	25	51	stage	stage	NOUN
ajst-20214	25	52	object	object	NOUN
ajst-20214	25	53	detection	detection	NOUN
ajst-20214	25	54	,	,	PUNCT
ajst-20214	25	55	represented	represent	VERB
ajst-20214	25	56	by	by	ADP
ajst-20214	25	57	the	the	DET
ajst-20214	25	58	yolo	yolo	ADJ
ajst-20214	25	59	series[4	series[4	NOUN
ajst-20214	25	60	-	-	PUNCT
ajst-20214	25	61	7	7	NUM
ajst-20214	25	62	]	]	PUNCT
ajst-20214	25	63	.	.	PUNCT
ajst-20214	26	1	in	in	ADP
ajst-20214	26	2	two	two	NUM
ajst-20214	26	3	-	-	PUNCT
ajst-20214	26	4	stage	stage	NOUN
ajst-20214	26	5	object	object	NOUN
ajst-20214	26	6	detection	detection	NOUN
ajst-20214	26	7	,	,	PUNCT
ajst-20214	26	8	candidate	candidate	NOUN
ajst-20214	26	9	regions	region	NOUN
ajst-20214	26	10	are	be	AUX
ajst-20214	26	11	typically	typically	ADV
ajst-20214	26	12	generated	generate	VERB
ajst-20214	26	13	first	first	ADV
ajst-20214	26	14	,	,	PUNCT
ajst-20214	26	15	followed	follow	VERB
ajst-20214	26	16	by	by	ADP
ajst-20214	26	17	extracting	extract	VERB
ajst-20214	26	18	and	and	CCONJ
ajst-20214	26	19	encoding	encode	VERB
ajst-20214	26	20	feature	feature	NOUN
ajst-20214	26	21	vectors	vector	NOUN
ajst-20214	26	22	using	use	VERB
ajst-20214	26	23	deep	deep	ADJ
ajst-20214	26	24	convolutional	convolutional	ADJ
ajst-20214	26	25	networks	network	NOUN
ajst-20214	26	26	.	.	PUNCT
ajst-20214	27	1	then	then	ADV
ajst-20214	27	2	,	,	PUNCT
ajst-20214	27	3	the	the	DET
ajst-20214	27	4	categories	category	NOUN
ajst-20214	27	5	and	and	CCONJ
ajst-20214	27	6	locations	location	NOUN
ajst-20214	27	7	of	of	ADP
ajst-20214	27	8	objects	object	NOUN
ajst-20214	27	9	within	within	ADP
ajst-20214	27	10	the	the	DET
ajst-20214	27	11	candidate	candidate	NOUN
ajst-20214	27	12	regions	region	NOUN
ajst-20214	27	13	are	be	AUX
ajst-20214	27	14	detected	detect	VERB
ajst-20214	27	15	.	.	PUNCT
ajst-20214	28	1	in	in	ADP
ajst-20214	28	2	contrast	contrast	NOUN
ajst-20214	28	3	,	,	PUNCT
ajst-20214	28	4	one	one	NUM
ajst-20214	28	5	-	-	PUNCT
ajst-20214	28	6	stage	stage	NOUN
ajst-20214	28	7	object	object	NOUN
ajst-20214	28	8	detection	detection	NOUN
ajst-20214	28	9	models	model	NOUN
ajst-20214	28	10	eliminate	eliminate	VERB
ajst-20214	28	11	the	the	DET
ajst-20214	28	12	candidate	candidate	NOUN
ajst-20214	28	13	region	region	NOUN
ajst-20214	28	14	generation	generation	NOUN
ajst-20214	28	15	stage	stage	NOUN
ajst-20214	28	16	,	,	PUNCT
ajst-20214	28	17	directly	directly	ADV
ajst-20214	28	18	classifying	classify	VERB
ajst-20214	28	19	each	each	DET
ajst-20214	28	20	region	region	NOUN
ajst-20214	28	21	of	of	ADP
ajst-20214	28	22	interest	interest	NOUN
ajst-20214	28	23	as	as	ADP
ajst-20214	28	24	background	background	NOUN
ajst-20214	28	25	or	or	CCONJ
ajst-20214	28	26	a	a	DET
ajst-20214	28	27	target	target	NOUN
ajst-20214	28	28	object	object	NOUN
ajst-20214	28	29	.	.	PUNCT
ajst-20214	29	1	as	as	ADP
ajst-20214	29	2	a	a	DET
ajst-20214	29	3	result	result	NOUN
ajst-20214	29	4	,	,	PUNCT
ajst-20214	29	5	they	they	PRON
ajst-20214	29	6	offer	offer	VERB
ajst-20214	29	7	faster	fast	ADJ
ajst-20214	29	8	inference	inference	NOUN
ajst-20214	29	9	speeds	speed	NOUN
ajst-20214	29	10	and	and	CCONJ
ajst-20214	29	11	are	be	AUX
ajst-20214	29	12	more	more	ADV
ajst-20214	29	13	suitable	suitable	ADJ
ajst-20214	29	14	for	for	ADP
ajst-20214	29	15	real	real	ADJ
ajst-20214	29	16	-	-	PUNCT
ajst-20214	29	17	time	time	NOUN
ajst-20214	29	18	object	object	NOUN
ajst-20214	29	19	detection	detection	NOUN
ajst-20214	29	20	scenarios	scenario	NOUN
ajst-20214	29	21	,	,	PUNCT
ajst-20214	29	22	albeit	albeit	SCONJ
ajst-20214	29	23	with	with	ADP
ajst-20214	29	24	slightly	slightly	ADV
ajst-20214	29	25	lower	low	ADJ
ajst-20214	29	26	accuracy	accuracy	NOUN
ajst-20214	29	27	compared	compare	VERB
ajst-20214	29	28	to	to	ADP
ajst-20214	29	29	two	two	NUM
ajst-20214	29	30	-	-	PUNCT
ajst-20214	29	31	stage	stage	NOUN
ajst-20214	29	32	methods	method	NOUN
ajst-20214	29	33	.	.	PUNCT
ajst-20214	30	1	in	in	ADP
ajst-20214	30	2	applications	application	NOUN
ajst-20214	30	3	requiring	require	VERB
ajst-20214	30	4	real	real	ADJ
ajst-20214	30	5	-	-	PUNCT
ajst-20214	30	6	time	time	NOUN
ajst-20214	30	7	and	and	CCONJ
ajst-20214	30	8	rapid	rapid	ADJ
ajst-20214	30	9	responses	response	NOUN
ajst-20214	30	10	,	,	PUNCT
ajst-20214	30	11	one	one	NUM
ajst-20214	30	12	-	-	PUNCT
ajst-20214	30	13	stage	stage	NOUN
ajst-20214	30	14	object	object	NOUN
ajst-20214	30	15	detection	detection	NOUN
ajst-20214	30	16	algorithms	algorithm	NOUN
ajst-20214	30	17	are	be	AUX
ajst-20214	30	18	generally	generally	ADV
ajst-20214	30	19	preferred	prefer	VERB
ajst-20214	30	20	.	.	PUNCT
ajst-20214	31	1	in	in	ADP
ajst-20214	31	2	this	this	DET
ajst-20214	31	3	paper	paper	NOUN
ajst-20214	31	4	,	,	PUNCT
ajst-20214	31	5	we	we	PRON
ajst-20214	31	6	focus	focus	VERB
ajst-20214	31	7	on	on	ADP
ajst-20214	31	8	improving	improve	VERB
ajst-20214	31	9	the	the	DET
ajst-20214	31	10	single	single	ADJ
ajst-20214	31	11	-	-	PUNCT
ajst-20214	31	12	stage	stage	NOUN
ajst-20214	31	13	object	object	NOUN
ajst-20214	31	14	detection	detection	NOUN
ajst-20214	31	15	algorithm	algorithm	NOUN
ajst-20214	31	16	yolov5	yolov5	NOUN
ajst-20214	31	17	to	to	PART
ajst-20214	31	18	strike	strike	VERB
ajst-20214	31	19	a	a	DET
ajst-20214	31	20	balance	balance	NOUN
ajst-20214	31	21	between	between	ADP
ajst-20214	31	22	accuracy	accuracy	NOUN
ajst-20214	31	23	and	and	CCONJ
ajst-20214	31	24	detection	detection	NOUN
ajst-20214	31	25	speed	speed	NOUN
ajst-20214	31	26	.	.	PUNCT
ajst-20214	32	1	2.2	2.2	NUM
ajst-20214	32	2	.	.	PUNCT
ajst-20214	32	3	model	model	NOUN
ajst-20214	32	4	compression	compression	NOUN
ajst-20214	32	5	technique	technique	NOUN
ajst-20214	32	6	.	.	PUNCT
ajst-20214	33	1	due	due	ADP
ajst-20214	33	2	to	to	ADP
ajst-20214	33	3	the	the	DET
ajst-20214	33	4	vast	vast	ADJ
ajst-20214	33	5	number	number	NOUN
ajst-20214	33	6	of	of	ADP
ajst-20214	33	7	parameters	parameter	NOUN
ajst-20214	33	8	and	and	CCONJ
ajst-20214	33	9	complex	complex	ADJ
ajst-20214	33	10	computational	computational	ADJ
ajst-20214	33	11	processes	process	NOUN
ajst-20214	33	12	inherent	inherent	ADJ
ajst-20214	33	13	in	in	ADP
ajst-20214	33	14	deep	deep	ADJ
ajst-20214	33	15	learning	learning	NOUN
ajst-20214	33	16	models	model	NOUN
ajst-20214	33	17	for	for	ADP
ajst-20214	33	18	182	182	NUM
ajst-20214	33	19	object	object	NOUN
ajst-20214	33	20	detection	detection	NOUN
ajst-20214	33	21	,	,	PUNCT
ajst-20214	33	22	their	their	PRON
ajst-20214	33	23	deployment	deployment	NOUN
ajst-20214	33	24	on	on	ADP
ajst-20214	33	25	resource	resource	NOUN
ajst-20214	33	26	-	-	PUNCT
ajst-20214	33	27	limited	limit	VERB
ajst-20214	33	28	hardware	hardware	NOUN
ajst-20214	33	29	platforms	platform	NOUN
ajst-20214	33	30	is	be	AUX
ajst-20214	33	31	often	often	ADV
ajst-20214	33	32	constrained	constrain	VERB
ajst-20214	33	33	.	.	PUNCT
ajst-20214	34	1	to	to	PART
ajst-20214	34	2	address	address	VERB
ajst-20214	34	3	this	this	DET
ajst-20214	34	4	challenge	challenge	NOUN
ajst-20214	34	5	,	,	PUNCT
ajst-20214	34	6	it	it	PRON
ajst-20214	34	7	is	be	AUX
ajst-20214	34	8	necessary	necessary	ADJ
ajst-20214	34	9	to	to	PART
ajst-20214	34	10	compress	compress	VERB
ajst-20214	34	11	the	the	DET
ajst-20214	34	12	storage	storage	NOUN
ajst-20214	34	13	space	space	NOUN
ajst-20214	34	14	and	and	CCONJ
ajst-20214	34	15	accelerate	accelerate	VERB
ajst-20214	34	16	the	the	DET
ajst-20214	34	17	computational	computational	ADJ
ajst-20214	34	18	processes	process	NOUN
ajst-20214	34	19	of	of	ADP
ajst-20214	34	20	deep	deep	ADJ
ajst-20214	34	21	models	model	NOUN
ajst-20214	34	22	.	.	PUNCT
ajst-20214	35	1	to	to	PART
ajst-20214	35	2	achieve	achieve	VERB
ajst-20214	35	3	these	these	DET
ajst-20214	35	4	goals	goal	NOUN
ajst-20214	35	5	,	,	PUNCT
ajst-20214	35	6	common	common	ADJ
ajst-20214	35	7	methods	method	NOUN
ajst-20214	35	8	include	include	VERB
ajst-20214	35	9	knowledge	knowledge	NOUN
ajst-20214	35	10	distillation	distillation	NOUN
ajst-20214	35	11	[	[	X
ajst-20214	35	12	8	8	NUM
ajst-20214	35	13	]	]	PUNCT
ajst-20214	35	14	,	,	PUNCT
ajst-20214	35	15	network	network	NOUN
ajst-20214	35	16	pruning	prune	VERB
ajst-20214	35	17	[	[	X
ajst-20214	35	18	9	9	NUM
ajst-20214	35	19	,	,	PUNCT
ajst-20214	35	20	10	10	NUM
ajst-20214	35	21	]	]	PUNCT
ajst-20214	35	22	,	,	PUNCT
ajst-20214	35	23	model	model	NOUN
ajst-20214	35	24	quantization	quantization	NOUN
ajst-20214	35	25	[	[	X
ajst-20214	35	26	11	11	NUM
ajst-20214	35	27	,	,	PUNCT
ajst-20214	35	28	12	12	NUM
ajst-20214	35	29	]	]	PUNCT
ajst-20214	35	30	,	,	PUNCT
ajst-20214	35	31	and	and	CCONJ
ajst-20214	35	32	low	low	ADJ
ajst-20214	35	33	-	-	PUNCT
ajst-20214	35	34	rank	rank	NOUN
ajst-20214	35	35	decomposition	decomposition	NOUN
ajst-20214	35	36	[	[	X
ajst-20214	35	37	13	13	NUM
ajst-20214	35	38	,	,	PUNCT
ajst-20214	35	39	14	14	NUM
ajst-20214	35	40	]	]	PUNCT
ajst-20214	35	41	.	.	PUNCT
ajst-20214	36	1	3	3	X
ajst-20214	36	2	.	.	X
ajst-20214	36	3	a	a	DET
ajst-20214	36	4	design	design	NOUN
ajst-20214	36	5	of	of	ADP
ajst-20214	36	6	model	model	NOUN
ajst-20214	36	7	compression	compression	NOUN
ajst-20214	36	8	method	method	NOUN
ajst-20214	36	9	based	base	VERB
ajst-20214	36	10	on	on	ADP
ajst-20214	36	11	yolov5	yolov5	NOUN
ajst-20214	36	12	3.1	3.1	NUM
ajst-20214	36	13	.	.	PUNCT
ajst-20214	37	1	yolov5	yolov5	NOUN
ajst-20214	37	2	.	.	PUNCT
ajst-20214	38	1	the	the	DET
ajst-20214	38	2	yolov5	yolov5	NOUN
ajst-20214	38	3	algorithm	algorithm	NOUN
ajst-20214	38	4	shares	share	VERB
ajst-20214	38	5	a	a	DET
ajst-20214	38	6	similar	similar	ADJ
ajst-20214	38	7	network	network	NOUN
ajst-20214	38	8	structure	structure	NOUN
ajst-20214	38	9	with	with	ADP
ajst-20214	38	10	the	the	DET
ajst-20214	38	11	yolo	yolo	ADJ
ajst-20214	38	12	series	series	NOUN
ajst-20214	38	13	,	,	PUNCT
ajst-20214	38	14	consisting	consist	VERB
ajst-20214	38	15	primarily	primarily	ADV
ajst-20214	38	16	of	of	ADP
ajst-20214	38	17	four	four	NUM
ajst-20214	38	18	components	component	NOUN
ajst-20214	38	19	:	:	PUNCT
ajst-20214	38	20	input	input	NOUN
ajst-20214	38	21	,	,	PUNCT
ajst-20214	38	22	backbone	backbone	NOUN
ajst-20214	38	23	,	,	PUNCT
ajst-20214	38	24	neck	neck	NOUN
ajst-20214	38	25	,	,	PUNCT
ajst-20214	38	26	and	and	CCONJ
ajst-20214	38	27	head	head	NOUN
ajst-20214	38	28	.	.	PUNCT
ajst-20214	39	1	due	due	ADP
ajst-20214	39	2	to	to	ADP
ajst-20214	39	3	its	its	PRON
ajst-20214	39	4	smaller	small	ADJ
ajst-20214	39	5	model	model	NOUN
ajst-20214	39	6	size	size	NOUN
ajst-20214	39	7	,	,	PUNCT
ajst-20214	39	8	yolov5s	yolov5s	PROPN
ajst-20214	39	9	is	be	AUX
ajst-20214	39	10	widely	widely	ADV
ajst-20214	39	11	used	use	VERB
ajst-20214	39	12	in	in	ADP
ajst-20214	39	13	scenarios	scenario	NOUN
ajst-20214	39	14	that	that	PRON
ajst-20214	39	15	require	require	VERB
ajst-20214	39	16	lightweight	lightweight	ADJ
ajst-20214	39	17	solutions	solution	NOUN
ajst-20214	39	18	.	.	PUNCT
ajst-20214	40	1	the	the	DET
ajst-20214	40	2	structure	structure	NOUN
ajst-20214	40	3	of	of	ADP
ajst-20214	40	4	the	the	DET
ajst-20214	40	5	yolov5	yolov5	NOUN
ajst-20214	40	6	algorithm	algorithm	NOUN
ajst-20214	40	7	is	be	AUX
ajst-20214	40	8	illustrated	illustrate	VERB
ajst-20214	40	9	in	in	ADP
ajst-20214	40	10	fig	fig	NOUN
ajst-20214	40	11	.	.	PUNCT
ajst-20214	41	1	1	1	X
ajst-20214	41	2	.	.	X
ajst-20214	41	3	conv	conv	PROPN
ajst-20214	41	4	conv	conv	PROPN
ajst-20214	41	5	c3	c3	PROPN
ajst-20214	41	6	conv	conv	PROPN
ajst-20214	41	7	c3	c3	PROPN
ajst-20214	41	8	conv	conv	PROPN
ajst-20214	41	9	c3	c3	PROPN
ajst-20214	41	10	conv	conv	PROPN
ajst-20214	41	11	c3	c3	PROPN
ajst-20214	41	12	sppf	sppf	PROPN
ajst-20214	41	13	concat	concat	PROPN
ajst-20214	41	14	upsample	upsample	PROPN
ajst-20214	41	15	conv	conv	PROPN
ajst-20214	41	16	c3	c3	PROPN
ajst-20214	41	17	concat	concat	PROPN
ajst-20214	41	18	upsample	upsample	PROPN
ajst-20214	41	19	conv	conv	PROPN
ajst-20214	41	20	c3	c3	PROPN
ajst-20214	41	21	conv	conv	PROPN
ajst-20214	41	22	concat	concat	PROPN
ajst-20214	41	23	c3	c3	PROPN
ajst-20214	41	24	conv	conv	PROPN
ajst-20214	41	25	concat	concat	PROPN
ajst-20214	41	26	c3	c3	PROPN
ajst-20214	41	27	detect	detect	PROPN
ajst-20214	41	28	backbone	backbone	NOUN
ajst-20214	41	29	neck	neck	NOUN
ajst-20214	41	30	head	head	NOUN
ajst-20214	41	31	input	input	NOUN
ajst-20214	41	32	detect	detect	NOUN
ajst-20214	41	33	detect	detect	NOUN
ajst-20214	41	34	figure	figure	NOUN
ajst-20214	41	35	1	1	NUM
ajst-20214	41	36	.	.	PUNCT
ajst-20214	42	1	the	the	DET
ajst-20214	42	2	network	network	NOUN
ajst-20214	42	3	structure	structure	NOUN
ajst-20214	42	4	of	of	ADP
ajst-20214	42	5	yolov5	yolov5	NOUN
ajst-20214	42	6	the	the	DET
ajst-20214	42	7	input	input	NOUN
ajst-20214	42	8	section	section	NOUN
ajst-20214	42	9	of	of	ADP
ajst-20214	42	10	the	the	DET
ajst-20214	42	11	yolov5	yolov5	NOUN
ajst-20214	42	12	network	network	NOUN
ajst-20214	42	13	handles	handle	VERB
ajst-20214	42	14	the	the	DET
ajst-20214	42	15	input	input	NOUN
ajst-20214	42	16	of	of	ADP
ajst-20214	42	17	three	three	NUM
ajst-20214	42	18	-	-	PUNCT
ajst-20214	42	19	channel	channel	NOUN
ajst-20214	42	20	rgb	rgb	PROPN
ajst-20214	42	21	images	image	NOUN
ajst-20214	42	22	.	.	PUNCT
ajst-20214	43	1	it	it	PRON
ajst-20214	43	2	performs	perform	VERB
ajst-20214	43	3	mosaic	mosaic	ADJ
ajst-20214	43	4	data	datum	NOUN
ajst-20214	43	5	augmentation	augmentation	NOUN
ajst-20214	43	6	,	,	PUNCT
ajst-20214	43	7	adaptive	adaptive	ADJ
ajst-20214	43	8	processing	processing	NOUN
ajst-20214	43	9	of	of	ADP
ajst-20214	43	10	image	image	NOUN
ajst-20214	43	11	sizes	size	NOUN
ajst-20214	43	12	,	,	PUNCT
ajst-20214	43	13	and	and	CCONJ
ajst-20214	43	14	optimization	optimization	NOUN
ajst-20214	43	15	of	of	ADP
ajst-20214	43	16	anchor	anchor	PROPN
ajst-20214	43	17	box	box	NOUN
ajst-20214	43	18	calculations	calculation	NOUN
ajst-20214	43	19	.	.	PUNCT
ajst-20214	44	1	mosaic	mosaic	ADJ
ajst-20214	44	2	data	datum	NOUN
ajst-20214	44	3	augmentation	augmentation	NOUN
ajst-20214	44	4	enriches	enrich	VERB
ajst-20214	44	5	image	image	NOUN
ajst-20214	44	6	information	information	NOUN
ajst-20214	44	7	by	by	ADP
ajst-20214	44	8	combining	combine	VERB
ajst-20214	44	9	four	four	NUM
ajst-20214	44	10	images	image	NOUN
ajst-20214	44	11	into	into	ADP
ajst-20214	44	12	one	one	NUM
ajst-20214	44	13	,	,	PUNCT
ajst-20214	44	14	scaling	scale	VERB
ajst-20214	44	15	the	the	DET
ajst-20214	44	16	resulting	result	VERB
ajst-20214	44	17	image	image	NOUN
ajst-20214	44	18	to	to	ADP
ajst-20214	44	19	a	a	DET
ajst-20214	44	20	standard	standard	ADJ
ajst-20214	44	21	size	size	NOUN
ajst-20214	44	22	for	for	ADP
ajst-20214	44	23	training	training	NOUN
ajst-20214	44	24	.	.	PUNCT
ajst-20214	45	1	this	this	PRON
ajst-20214	45	2	reduces	reduce	VERB
ajst-20214	45	3	the	the	DET
ajst-20214	45	4	model	model	NOUN
ajst-20214	45	5	's	's	PART
ajst-20214	45	6	dependency	dependency	NOUN
ajst-20214	45	7	on	on	ADP
ajst-20214	45	8	batch	batch	NOUN
ajst-20214	45	9	size	size	NOUN
ajst-20214	45	10	and	and	CCONJ
ajst-20214	45	11	effectively	effectively	ADV
ajst-20214	45	12	improves	improve	VERB
ajst-20214	45	13	detection	detection	NOUN
ajst-20214	45	14	accuracy	accuracy	NOUN
ajst-20214	45	15	.	.	PUNCT
ajst-20214	46	1	anchor	anchor	PROPN
ajst-20214	46	2	box	box	PROPN
ajst-20214	46	3	calculations	calculation	NOUN
ajst-20214	46	4	compare	compare	AUX
ajst-20214	46	5	predicted	predict	VERB
ajst-20214	46	6	bounding	bounding	NOUN
ajst-20214	46	7	boxes	box	NOUN
ajst-20214	46	8	with	with	ADP
ajst-20214	46	9	ground	ground	NOUN
ajst-20214	46	10	truth	truth	NOUN
ajst-20214	46	11	boxes	box	NOUN
ajst-20214	46	12	,	,	PUNCT
ajst-20214	46	13	obtaining	obtain	VERB
ajst-20214	46	14	the	the	DET
ajst-20214	46	15	differences	difference	NOUN
ajst-20214	46	16	and	and	CCONJ
ajst-20214	46	17	then	then	ADV
ajst-20214	46	18	updating	update	VERB
ajst-20214	46	19	them	they	PRON
ajst-20214	46	20	in	in	ADP
ajst-20214	46	21	reverse	reverse	NOUN
ajst-20214	46	22	to	to	PART
ajst-20214	46	23	iteratively	iteratively	ADV
ajst-20214	46	24	optimize	optimize	VERB
ajst-20214	46	25	parameters	parameter	NOUN
ajst-20214	46	26	and	and	CCONJ
ajst-20214	46	27	approximate	approximate	VERB
ajst-20214	46	28	the	the	DET
ajst-20214	46	29	optimal	optimal	ADJ
ajst-20214	46	30	anchor	anchor	NOUN
ajst-20214	46	31	box	box	NOUN
ajst-20214	46	32	values	value	NOUN
ajst-20214	46	33	.	.	PUNCT
ajst-20214	47	1	the	the	DET
ajst-20214	47	2	backbone	backbone	NOUN
ajst-20214	47	3	,	,	PUNCT
ajst-20214	47	4	consisting	consist	VERB
ajst-20214	47	5	of	of	ADP
ajst-20214	47	6	csp	csp	PROPN
ajst-20214	47	7	and	and	CCONJ
ajst-20214	47	8	spatial	spatial	ADJ
ajst-20214	47	9	pyramid	pyramid	NOUN
ajst-20214	47	10	pooling	pool	VERB
ajst-20214	47	11	fast	fast	ADJ
ajst-20214	47	12	(	(	PUNCT
ajst-20214	47	13	sppf	sppf	ADJ
ajst-20214	47	14	)	)	PUNCT
ajst-20214	47	15	structures	structure	NOUN
ajst-20214	47	16	,	,	PUNCT
ajst-20214	47	17	is	be	AUX
ajst-20214	47	18	primarily	primarily	ADV
ajst-20214	47	19	responsible	responsible	ADJ
ajst-20214	47	20	for	for	ADP
ajst-20214	47	21	feature	feature	NOUN
ajst-20214	47	22	extraction	extraction	NOUN
ajst-20214	47	23	in	in	ADP
ajst-20214	47	24	object	object	NOUN
ajst-20214	47	25	detection	detection	NOUN
ajst-20214	47	26	.	.	PUNCT
ajst-20214	48	1	the	the	DET
ajst-20214	48	2	csp	csp	PROPN
ajst-20214	48	3	module	module	NOUN
ajst-20214	48	4	reduces	reduce	VERB
ajst-20214	48	5	computational	computational	ADJ
ajst-20214	48	6	complexity	complexity	NOUN
ajst-20214	48	7	and	and	CCONJ
ajst-20214	48	8	enhances	enhance	VERB
ajst-20214	48	9	the	the	DET
ajst-20214	48	10	network	network	NOUN
ajst-20214	48	11	's	's	PART
ajst-20214	48	12	learning	learning	NOUN
ajst-20214	48	13	performance	performance	NOUN
ajst-20214	48	14	,	,	PUNCT
ajst-20214	48	15	having	having	AUX
ajst-20214	48	16	been	be	AUX
ajst-20214	48	17	upgraded	upgrade	VERB
ajst-20214	48	18	to	to	ADP
ajst-20214	48	19	the	the	DET
ajst-20214	48	20	c3	c3	PROPN
ajst-20214	48	21	module	module	NOUN
ajst-20214	48	22	in	in	ADP
ajst-20214	48	23	the	the	DET
ajst-20214	48	24	6.0	6.0	NUM
ajst-20214	48	25	version	version	NOUN
ajst-20214	48	26	of	of	ADP
ajst-20214	48	27	yolov5	yolov5	NOUN
ajst-20214	48	28	.	.	PUNCT
ajst-20214	49	1	sppf	sppf	ADJ
ajst-20214	49	2	integrates	integrate	NOUN
ajst-20214	49	3	deep	deep	ADJ
ajst-20214	49	4	semantic	semantic	ADJ
ajst-20214	49	5	information	information	NOUN
ajst-20214	49	6	with	with	ADP
ajst-20214	49	7	shallow	shallow	ADJ
ajst-20214	49	8	semantic	semantic	ADJ
ajst-20214	49	9	information	information	NOUN
ajst-20214	49	10	,	,	PUNCT
ajst-20214	49	11	further	far	ADV
ajst-20214	49	12	improving	improve	VERB
ajst-20214	49	13	the	the	DET
ajst-20214	49	14	network	network	NOUN
ajst-20214	49	15	's	's	PART
ajst-20214	49	16	detection	detection	NOUN
ajst-20214	49	17	accuracy	accuracy	NOUN
ajst-20214	49	18	.	.	PUNCT
ajst-20214	50	1	the	the	DET
ajst-20214	50	2	neck	neck	NOUN
ajst-20214	50	3	,	,	PUNCT
ajst-20214	50	4	the	the	DET
ajst-20214	50	5	feature	feature	NOUN
ajst-20214	50	6	fusion	fusion	NOUN
ajst-20214	50	7	layer	layer	NOUN
ajst-20214	50	8	,	,	PUNCT
ajst-20214	50	9	employs	employ	VERB
ajst-20214	50	10	a	a	DET
ajst-20214	50	11	path	path	NOUN
ajst-20214	50	12	aggregation	aggregation	NOUN
ajst-20214	50	13	network	network	NOUN
ajst-20214	50	14	(	(	PUNCT
ajst-20214	50	15	panet	panet	PROPN
ajst-20214	50	16	)	)	PUNCT
ajst-20214	50	17	that	that	PRON
ajst-20214	50	18	combines	combine	VERB
ajst-20214	50	19	the	the	DET
ajst-20214	50	20	fpn	fpn	ADJ
ajst-20214	50	21	layer	layer	NOUN
ajst-20214	50	22	,	,	PUNCT
ajst-20214	50	23	which	which	PRON
ajst-20214	50	24	merges	merge	VERB
ajst-20214	50	25	deep	deep	ADJ
ajst-20214	50	26	and	and	CCONJ
ajst-20214	50	27	shallow	shallow	ADJ
ajst-20214	50	28	features	feature	NOUN
ajst-20214	50	29	,	,	PUNCT
ajst-20214	50	30	with	with	ADP
ajst-20214	50	31	a	a	DET
ajst-20214	50	32	feature	feature	NOUN
ajst-20214	50	33	pyramid	pyramid	NOUN
ajst-20214	50	34	that	that	PRON
ajst-20214	50	35	merges	merge	VERB
ajst-20214	50	36	shallow	shallow	ADJ
ajst-20214	50	37	features	feature	NOUN
ajst-20214	50	38	with	with	ADP
ajst-20214	50	39	deep	deep	ADJ
ajst-20214	50	40	ones	one	NOUN
ajst-20214	50	41	.	.	PUNCT
ajst-20214	51	1	this	this	DET
ajst-20214	51	2	fusion	fusion	NOUN
ajst-20214	51	3	enhances	enhance	VERB
ajst-20214	51	4	the	the	DET
ajst-20214	51	5	model	model	NOUN
ajst-20214	51	6	's	's	PART
ajst-20214	51	7	feature	feature	NOUN
ajst-20214	51	8	extraction	extraction	NOUN
ajst-20214	51	9	by	by	ADP
ajst-20214	51	10	integrating	integrate	VERB
ajst-20214	51	11	information	information	NOUN
ajst-20214	51	12	from	from	ADP
ajst-20214	51	13	different	different	ADJ
ajst-20214	51	14	network	network	NOUN
ajst-20214	51	15	layers	layer	NOUN
ajst-20214	51	16	in	in	ADP
ajst-20214	51	17	the	the	DET
ajst-20214	51	18	backbone	backbone	NOUN
ajst-20214	51	19	and	and	CCONJ
ajst-20214	51	20	achieving	achieve	VERB
ajst-20214	51	21	a	a	DET
ajst-20214	51	22	blend	blend	NOUN
ajst-20214	51	23	of	of	ADP
ajst-20214	51	24	information	information	NOUN
ajst-20214	51	25	from	from	ADP
ajst-20214	51	26	different	different	ADJ
ajst-20214	51	27	feature	feature	NOUN
ajst-20214	51	28	levels	level	NOUN
ajst-20214	51	29	.	.	PUNCT
ajst-20214	52	1	the	the	DET
ajst-20214	52	2	head	head	NOUN
ajst-20214	52	3	,	,	PUNCT
ajst-20214	52	4	the	the	DET
ajst-20214	52	5	output	output	NOUN
ajst-20214	52	6	section	section	NOUN
ajst-20214	52	7	,	,	PUNCT
ajst-20214	52	8	generates	generate	VERB
ajst-20214	52	9	a	a	DET
ajst-20214	52	10	vector	vector	NOUN
ajst-20214	52	11	that	that	PRON
ajst-20214	52	12	describes	describe	VERB
ajst-20214	52	13	the	the	DET
ajst-20214	52	14	target	target	NOUN
ajst-20214	52	15	's	's	PART
ajst-20214	52	16	category	category	NOUN
ajst-20214	52	17	probability	probability	NOUN
ajst-20214	52	18	,	,	PUNCT
ajst-20214	52	19	score	score	NOUN
ajst-20214	52	20	,	,	PUNCT
ajst-20214	52	21	and	and	CCONJ
ajst-20214	52	22	the	the	DET
ajst-20214	52	23	location	location	NOUN
ajst-20214	52	24	of	of	ADP
ajst-20214	52	25	the	the	DET
ajst-20214	52	26	predicted	predict	VERB
ajst-20214	52	27	bounding	bounding	NOUN
ajst-20214	52	28	box	box	NOUN
ajst-20214	52	29	.	.	PUNCT
ajst-20214	53	1	there	there	PRON
ajst-20214	53	2	are	be	VERB
ajst-20214	53	3	three	three	NUM
ajst-20214	53	4	yolo	yolo	ADJ
ajst-20214	53	5	head	head	NOUN
ajst-20214	53	6	detectors	detector	NOUN
ajst-20214	53	7	that	that	PRON
ajst-20214	53	8	output	output	VERB
ajst-20214	53	9	feature	feature	NOUN
ajst-20214	53	10	maps	map	NOUN
ajst-20214	53	11	of	of	ADP
ajst-20214	53	12	different	different	ADJ
ajst-20214	53	13	scales	scale	NOUN
ajst-20214	53	14	for	for	ADP
ajst-20214	53	15	object	object	NOUN
ajst-20214	53	16	prediction	prediction	NOUN
ajst-20214	53	17	,	,	PUNCT
ajst-20214	53	18	detecting	detect	VERB
ajst-20214	53	19	targets	target	NOUN
ajst-20214	53	20	of	of	ADP
ajst-20214	53	21	varying	vary	VERB
ajst-20214	53	22	sizes	size	NOUN
ajst-20214	53	23	.	.	PUNCT
ajst-20214	54	1	each	each	DET
ajst-20214	54	2	detection	detection	NOUN
ajst-20214	54	3	head	head	NOUN
ajst-20214	54	4	obtains	obtain	VERB
ajst-20214	54	5	a	a	DET
ajst-20214	54	6	different	different	ADJ
ajst-20214	54	7	vector	vector	NOUN
ajst-20214	54	8	,	,	PUNCT
ajst-20214	54	9	which	which	PRON
ajst-20214	54	10	is	be	AUX
ajst-20214	54	11	used	use	VERB
ajst-20214	54	12	to	to	PART
ajst-20214	54	13	determine	determine	VERB
ajst-20214	54	14	the	the	DET
ajst-20214	54	15	predicted	predict	VERB
ajst-20214	54	16	bounding	bounding	NOUN
ajst-20214	54	17	box	box	NOUN
ajst-20214	54	18	location	location	NOUN
ajst-20214	54	19	and	and	CCONJ
ajst-20214	54	20	category	category	NOUN
ajst-20214	54	21	information	information	NOUN
ajst-20214	54	22	of	of	ADP
ajst-20214	54	23	the	the	DET
ajst-20214	54	24	target	target	NOUN
ajst-20214	54	25	in	in	ADP
ajst-20214	54	26	the	the	DET
ajst-20214	54	27	original	original	ADJ
ajst-20214	54	28	image	image	NOUN
ajst-20214	54	29	.	.	PUNCT
ajst-20214	55	1	while	while	SCONJ
ajst-20214	55	2	yolov5	yolov5	NOUN
ajst-20214	55	3	has	have	AUX
ajst-20214	55	4	achieved	achieve	VERB
ajst-20214	55	5	impressive	impressive	ADJ
ajst-20214	55	6	results	result	NOUN
ajst-20214	55	7	,	,	PUNCT
ajst-20214	55	8	it	it	PRON
ajst-20214	55	9	still	still	ADV
ajst-20214	55	10	has	have	VERB
ajst-20214	55	11	some	some	DET
ajst-20214	55	12	limitations	limitation	NOUN
ajst-20214	55	13	,	,	PUNCT
ajst-20214	55	14	particularly	particularly	ADV
ajst-20214	55	15	its	its	PRON
ajst-20214	55	16	high	high	ADJ
ajst-20214	55	17	computational	computational	ADJ
ajst-20214	55	18	demand	demand	NOUN
ajst-20214	55	19	,	,	PUNCT
ajst-20214	55	20	which	which	PRON
ajst-20214	55	21	makes	make	VERB
ajst-20214	55	22	it	it	PRON
ajst-20214	55	23	difficult	difficult	ADJ
ajst-20214	55	24	to	to	PART
ajst-20214	55	25	deploy	deploy	VERB
ajst-20214	55	26	on	on	ADP
ajst-20214	55	27	small	small	ADJ
ajst-20214	55	28	embedded	embed	VERB
ajst-20214	55	29	devices	device	NOUN
ajst-20214	55	30	or	or	CCONJ
ajst-20214	55	31	mobile	mobile	ADJ
ajst-20214	55	32	devices	device	NOUN
ajst-20214	55	33	,	,	PUNCT
ajst-20214	55	34	resulting	result	VERB
ajst-20214	55	35	in	in	ADP
ajst-20214	55	36	high	high	ADJ
ajst-20214	55	37	overall	overall	ADJ
ajst-20214	55	38	system	system	NOUN
ajst-20214	55	39	hardware	hardware	NOUN
ajst-20214	55	40	costs	cost	NOUN
ajst-20214	55	41	.	.	PUNCT
ajst-20214	56	1	to	to	PART
ajst-20214	56	2	make	make	VERB
ajst-20214	56	3	it	it	PRON
ajst-20214	56	4	suitable	suitable	ADJ
ajst-20214	56	5	for	for	ADP
ajst-20214	56	6	edge	edge	NOUN
ajst-20214	56	7	computing	computing	NOUN
ajst-20214	56	8	devices	device	NOUN
ajst-20214	56	9	,	,	PUNCT
ajst-20214	56	10	this	this	DET
ajst-20214	56	11	paper	paper	NOUN
ajst-20214	56	12	compresses	compress	VERB
ajst-20214	56	13	the	the	DET
ajst-20214	56	14	yolov5	yolov5	NOUN
ajst-20214	56	15	model	model	NOUN
ajst-20214	56	16	to	to	PART
ajst-20214	56	17	reduce	reduce	VERB
ajst-20214	56	18	its	its	PRON
ajst-20214	56	19	complexity	complexity	NOUN
ajst-20214	56	20	and	and	CCONJ
ajst-20214	56	21	computational	computational	ADJ
ajst-20214	56	22	requirements	requirement	NOUN
ajst-20214	56	23	while	while	SCONJ
ajst-20214	56	24	minimizing	minimize	VERB
ajst-20214	56	25	precision	precision	NOUN
ajst-20214	56	26	loss	loss	NOUN
ajst-20214	56	27	.	.	PUNCT
ajst-20214	57	1	3.2	3.2	NUM
ajst-20214	57	2	.	.	PUNCT
ajst-20214	58	1	structured	structure	VERB
ajst-20214	58	2	pruning	pruning	NOUN
ajst-20214	58	3	based	base	VERB
ajst-20214	58	4	on	on	ADP
ajst-20214	58	5	model	model	NOUN
ajst-20214	58	6	channel	channel	PROPN
ajst-20214	58	7	weights	weight	NOUN
ajst-20214	58	8	.	.	PUNCT
ajst-20214	59	1	in	in	ADP
ajst-20214	59	2	neural	neural	ADJ
ajst-20214	59	3	networks	network	NOUN
ajst-20214	59	4	,	,	PUNCT
ajst-20214	59	5	due	due	ADP
ajst-20214	59	6	to	to	ADP
ajst-20214	59	7	the	the	DET
ajst-20214	59	8	vast	vast	ADJ
ajst-20214	59	9	number	number	NOUN
ajst-20214	59	10	of	of	ADP
ajst-20214	59	11	parameters	parameter	NOUN
ajst-20214	59	12	,	,	PUNCT
ajst-20214	59	13	there	there	PRON
ajst-20214	59	14	often	often	ADV
ajst-20214	59	15	exist	exist	VERB
ajst-20214	59	16	a	a	DET
ajst-20214	59	17	significant	significant	ADJ
ajst-20214	59	18	amount	amount	NOUN
ajst-20214	59	19	of	of	ADP
ajst-20214	59	20	redundant	redundant	ADJ
ajst-20214	59	21	connections	connection	NOUN
ajst-20214	59	22	and	and	CCONJ
ajst-20214	59	23	parameters	parameter	NOUN
ajst-20214	59	24	.	.	PUNCT
ajst-20214	60	1	these	these	DET
ajst-20214	60	2	redundant	redundant	ADJ
ajst-20214	60	3	parts	part	NOUN
ajst-20214	60	4	contribute	contribute	VERB
ajst-20214	60	5	little	little	ADJ
ajst-20214	60	6	to	to	ADP
ajst-20214	60	7	the	the	DET
ajst-20214	60	8	model	model	NOUN
ajst-20214	60	9	's	's	PART
ajst-20214	60	10	performance	performance	NOUN
ajst-20214	60	11	and	and	CCONJ
ajst-20214	60	12	may	may	AUX
ajst-20214	60	13	even	even	ADV
ajst-20214	60	14	introduce	introduce	VERB
ajst-20214	60	15	noise	noise	NOUN
ajst-20214	60	16	and	and	CCONJ
ajst-20214	60	17	interference	interference	NOUN
ajst-20214	60	18	.	.	PUNCT
ajst-20214	61	1	pruning	prune	VERB
ajst-20214	61	2	operations	operation	NOUN
ajst-20214	61	3	aim	aim	VERB
ajst-20214	61	4	to	to	PART
ajst-20214	61	5	reduce	reduce	VERB
ajst-20214	61	6	the	the	DET
ajst-20214	61	7	complexity	complexity	NOUN
ajst-20214	61	8	and	and	CCONJ
ajst-20214	61	9	computational	computational	ADJ
ajst-20214	61	10	cost	cost	NOUN
ajst-20214	61	11	of	of	ADP
ajst-20214	61	12	the	the	DET
ajst-20214	61	13	model	model	NOUN
ajst-20214	61	14	by	by	ADP
ajst-20214	61	15	eliminating	eliminate	VERB
ajst-20214	61	16	these	these	DET
ajst-20214	61	17	redundant	redundant	ADJ
ajst-20214	61	18	parts	part	NOUN
ajst-20214	61	19	while	while	SCONJ
ajst-20214	61	20	minimizing	minimize	VERB
ajst-20214	61	21	the	the	DET
ajst-20214	61	22	impact	impact	NOUN
ajst-20214	61	23	on	on	ADP
ajst-20214	61	24	performance	performance	NOUN
ajst-20214	61	25	.	.	PUNCT
ajst-20214	62	1	since	since	SCONJ
ajst-20214	62	2	unstructured	unstructured	ADJ
ajst-20214	62	3	pruning	pruning	NOUN
ajst-20214	62	4	can	can	AUX
ajst-20214	62	5	disrupt	disrupt	VERB
ajst-20214	62	6	the	the	DET
ajst-20214	62	7	network	network	NOUN
ajst-20214	62	8	structure	structure	NOUN
ajst-20214	62	9	and	and	CCONJ
ajst-20214	62	10	is	be	AUX
ajst-20214	62	11	not	not	PART
ajst-20214	62	12	hardware	hardware	NOUN
ajst-20214	62	13	-	-	PUNCT
ajst-20214	62	14	friendly	friendly	ADJ
ajst-20214	62	15	,	,	PUNCT
ajst-20214	62	16	this	this	DET
ajst-20214	62	17	paper	paper	NOUN
ajst-20214	62	18	adopts	adopt	VERB
ajst-20214	62	19	structured	structure	VERB
ajst-20214	62	20	pruning	prune	VERB
ajst-20214	62	21	to	to	PART
ajst-20214	62	22	preserve	preserve	VERB
ajst-20214	62	23	the	the	DET
ajst-20214	62	24	integrity	integrity	NOUN
ajst-20214	62	25	of	of	ADP
ajst-20214	62	26	the	the	DET
ajst-20214	62	27	network	network	NOUN
ajst-20214	62	28	structure	structure	NOUN
ajst-20214	62	29	.	.	PUNCT
ajst-20214	63	1	channel	channel	NOUN
ajst-20214	63	2	pruning	pruning	NOUN
ajst-20214	63	3	is	be	AUX
ajst-20214	63	4	performed	perform	VERB
ajst-20214	63	5	based	base	VERB
ajst-20214	63	6	on	on	ADP
ajst-20214	63	7	the	the	DET
ajst-20214	63	8	weights	weight	NOUN
ajst-20214	63	9	of	of	ADP
ajst-20214	63	10	each	each	DET
ajst-20214	63	11	channel	channel	NOUN
ajst-20214	63	12	.	.	PUNCT
ajst-20214	64	1	batch	batch	NOUN
ajst-20214	64	2	normalization	normalization	NOUN
ajst-20214	64	3	(	(	PUNCT
ajst-20214	64	4	bn	bn	NOUN
ajst-20214	64	5	)	)	PUNCT
ajst-20214	64	6	is	be	AUX
ajst-20214	64	7	a	a	DET
ajst-20214	64	8	commonly	commonly	ADV
ajst-20214	64	9	used	use	VERB
ajst-20214	64	10	technique	technique	NOUN
ajst-20214	64	11	in	in	ADP
ajst-20214	64	12	deep	deep	ADJ
ajst-20214	64	13	learning	learning	NOUN
ajst-20214	64	14	that	that	PRON
ajst-20214	64	15	addresses	address	VERB
ajst-20214	64	16	the	the	DET
ajst-20214	64	17	issue	issue	NOUN
ajst-20214	64	18	of	of	ADP
ajst-20214	64	19	internal	internal	ADJ
ajst-20214	64	20	covariate	covariate	ADJ
ajst-20214	64	21	shift	shift	NOUN
ajst-20214	64	22	.	.	PUNCT
ajst-20214	65	1	it	it	PRON
ajst-20214	65	2	normalizes	normalize	VERB
ajst-20214	65	3	the	the	DET
ajst-20214	65	4	input	input	NOUN
ajst-20214	65	5	data	datum	NOUN
ajst-20214	65	6	to	to	PART
ajst-20214	65	7	accelerate	accelerate	VERB
ajst-20214	65	8	the	the	DET
ajst-20214	65	9	convergence	convergence	NOUN
ajst-20214	65	10	of	of	ADP
ajst-20214	65	11	the	the	DET
ajst-20214	65	12	network	network	NOUN
ajst-20214	65	13	and	and	CCONJ
ajst-20214	65	14	improve	improve	VERB
ajst-20214	65	15	training	train	VERB
ajst-20214	65	16	stability	stability	NOUN
ajst-20214	65	17	.	.	PUNCT
ajst-20214	66	1	specifically	specifically	ADV
ajst-20214	66	2	,	,	PUNCT
ajst-20214	66	3	bn	bn	ADP
ajst-20214	66	4	layers	layer	NOUN
ajst-20214	66	5	normalize	normalize	VERB
ajst-20214	66	6	the	the	DET
ajst-20214	66	7	distribution	distribution	NOUN
ajst-20214	66	8	of	of	ADP
ajst-20214	66	9	input	input	NOUN
ajst-20214	66	10	data	datum	NOUN
ajst-20214	66	11	by	by	ADP
ajst-20214	66	12	standardizing	standardize	VERB
ajst-20214	66	13	each	each	DET
ajst-20214	66	14	feature	feature	NOUN
ajst-20214	66	15	dimension	dimension	NOUN
ajst-20214	66	16	to	to	PART
ajst-20214	66	17	have	have	VERB
ajst-20214	66	18	a	a	DET
ajst-20214	66	19	mean	mean	NOUN
ajst-20214	66	20	of	of	ADP
ajst-20214	66	21	0	0	NUM
ajst-20214	66	22	and	and	CCONJ
ajst-20214	66	23	a	a	DET
ajst-20214	66	24	variance	variance	NOUN
ajst-20214	66	25	of	of	ADP
ajst-20214	66	26	1	1	NUM
ajst-20214	66	27	,	,	PUNCT
ajst-20214	66	28	thus	thus	ADV
ajst-20214	66	29	avoiding	avoid	VERB
ajst-20214	66	30	gradient	gradient	ADJ
ajst-20214	66	31	vanishing	vanish	VERB
ajst-20214	66	32	issues	issue	NOUN
ajst-20214	66	33	caused	cause	VERB
ajst-20214	66	34	by	by	ADP
ajst-20214	66	35	deeper	deep	ADJ
ajst-20214	66	36	network	network	NOUN
ajst-20214	66	37	layers	layer	NOUN
ajst-20214	66	38	and	and	CCONJ
ajst-20214	66	39	speeding	speed	VERB
ajst-20214	66	40	up	up	ADP
ajst-20214	66	41	the	the	DET
ajst-20214	66	42	convergence	convergence	NOUN
ajst-20214	66	43	of	of	ADP
ajst-20214	66	44	model	model	NOUN
ajst-20214	66	45	training	training	NOUN
ajst-20214	66	46	.	.	PUNCT
ajst-20214	67	1	in	in	ADP
ajst-20214	67	2	yolov5	yolov5	PROPN
ajst-20214	67	3	,	,	PUNCT
ajst-20214	67	4	bn	bn	NUM
ajst-20214	67	5	layers	layer	NOUN
ajst-20214	67	6	are	be	AUX
ajst-20214	67	7	typically	typically	ADV
ajst-20214	67	8	placed	place	VERB
ajst-20214	67	9	after	after	ADP
ajst-20214	67	10	convolutional	convolutional	ADJ
ajst-20214	67	11	layers	layer	NOUN
ajst-20214	67	12	.	.	PUNCT
ajst-20214	68	1	each	each	DET
ajst-20214	68	2	bn	bn	NOUN
ajst-20214	68	3	layer	layer	NOUN
ajst-20214	68	4	contains	contain	VERB
ajst-20214	68	5	four	four	NUM
ajst-20214	68	6	learnable	learnable	ADJ
ajst-20214	68	7	parameters	parameter	NOUN
ajst-20214	68	8	:	:	PUNCT
ajst-20214	68	9	shift	shift	NOUN
ajst-20214	68	10	parameters	parameter	NOUN
ajst-20214	68	11			PROPN
ajst-20214	68	12	,	,	PUNCT
ajst-20214	68	13	scale	scale	NOUN
ajst-20214	68	14	parameters	parameter	NOUN
ajst-20214	68	15			VERB
ajst-20214	68	16	,	,	PUNCT
ajst-20214	68	17	mean	mean	VERB
ajst-20214	68	18	,	,	PUNCT
ajst-20214	68	19	and	and	CCONJ
ajst-20214	68	20	variance	variance	NOUN
ajst-20214	68	21	statistics	statistic	NOUN
ajst-20214	68	22	.	.	PUNCT
ajst-20214	69	1	the	the	DET
ajst-20214	69	2	shift	shift	NOUN
ajst-20214	69	3	parameters	parameter	NOUN
ajst-20214	69	4			NOUN
ajst-20214	69	5	and	and	CCONJ
ajst-20214	69	6	scale	scale	NOUN
ajst-20214	69	7	parameters	parameter	NOUN
ajst-20214	69	8			NOUN
ajst-20214	69	9	are	be	AUX
ajst-20214	69	10	used	use	VERB
ajst-20214	69	11	to	to	PART
ajst-20214	69	12	shift	shift	VERB
ajst-20214	69	13	and	and	CCONJ
ajst-20214	69	14	scale	scale	VERB
ajst-20214	69	15	the	the	DET
ajst-20214	69	16	bn	bn	NOUN
ajst-20214	69	17	layer	layer	NOUN
ajst-20214	69	18	,	,	PUNCT
ajst-20214	69	19	normalizing	normalize	VERB
ajst-20214	69	20	the	the	DET
ajst-20214	69	21	distribution	distribution	NOUN
ajst-20214	69	22	of	of	ADP
ajst-20214	69	23	the	the	DET
ajst-20214	69	24	input	input	NOUN
ajst-20214	69	25	data	datum	NOUN
ajst-20214	69	26	.	.	PUNCT
ajst-20214	70	1	the	the	DET
ajst-20214	70	2	mean	mean	ADJ
ajst-20214	70	3	and	and	CCONJ
ajst-20214	70	4	variance	variance	NOUN
ajst-20214	70	5	information	information	NOUN
ajst-20214	70	6	are	be	AUX
ajst-20214	70	7	used	use	VERB
ajst-20214	70	8	to	to	PART
ajst-20214	70	9	record	record	VERB
ajst-20214	70	10	the	the	DET
ajst-20214	70	11	statistical	statistical	ADJ
ajst-20214	70	12	information	information	NOUN
ajst-20214	70	13	of	of	ADP
ajst-20214	70	14	the	the	DET
ajst-20214	70	15	input	input	NOUN
ajst-20214	70	16	data	datum	NOUN
ajst-20214	70	17	for	for	ADP
ajst-20214	70	18	normalization	normalization	NOUN
ajst-20214	70	19	during	during	ADP
ajst-20214	70	20	the	the	DET
ajst-20214	70	21	testing	testing	NOUN
ajst-20214	70	22	phase	phase	NOUN
ajst-20214	70	23	.	.	PUNCT
ajst-20214	71	1	the	the	DET
ajst-20214	71	2	scale	scale	NOUN
ajst-20214	71	3	parameters	parameter	NOUN
ajst-20214	71	4			NUM
ajst-20214	71	5	of	of	ADP
ajst-20214	71	6	the	the	DET
ajst-20214	71	7	bn	bn	NOUN
ajst-20214	71	8	layer	layer	NOUN
ajst-20214	71	9	's	's	PART
ajst-20214	71	10	parameters	parameter	NOUN
ajst-20214	71	11	directly	directly	ADV
ajst-20214	71	12	affects	affect	VERB
ajst-20214	71	13	the	the	DET
ajst-20214	71	14	output	output	NOUN
ajst-20214	71	15	feature	feature	NOUN
ajst-20214	71	16	vector	vector	NOUN
ajst-20214	71	17	of	of	ADP
ajst-20214	71	18	the	the	DET
ajst-20214	71	19	current	current	ADJ
ajst-20214	71	20	channel	channel	NOUN
ajst-20214	71	21	.	.	PUNCT
ajst-20214	72	1	when	when	SCONJ
ajst-20214	72	2	the	the	DET
ajst-20214	72	3	value	value	NOUN
ajst-20214	72	4	of	of	ADP
ajst-20214	72	5			NUM
ajst-20214	72	6	approaches	approach	NOUN
ajst-20214	72	7	0	0	NUM
ajst-20214	72	8	,	,	PUNCT
ajst-20214	72	9	it	it	PRON
ajst-20214	72	10	indicates	indicate	VERB
ajst-20214	72	11	that	that	SCONJ
ajst-20214	72	12	the	the	DET
ajst-20214	72	13	183	183	NUM
ajst-20214	72	14	current	current	ADJ
ajst-20214	72	15	channel	channel	NOUN
ajst-20214	72	16	has	have	VERB
ajst-20214	72	17	a	a	DET
ajst-20214	72	18	minimal	minimal	ADJ
ajst-20214	72	19	impact	impact	NOUN
ajst-20214	72	20	on	on	ADP
ajst-20214	72	21	the	the	DET
ajst-20214	72	22	network	network	NOUN
ajst-20214	72	23	and	and	CCONJ
ajst-20214	72	24	a	a	DET
ajst-20214	72	25	low	low	ADJ
ajst-20214	72	26	weight	weight	NOUN
ajst-20214	72	27	.	.	PUNCT
ajst-20214	73	1	therefore	therefore	ADV
ajst-20214	73	2	,	,	PUNCT
ajst-20214	73	3	the	the	DET
ajst-20214	73	4			NUM
ajst-20214	73	5	of	of	ADP
ajst-20214	73	6	the	the	DET
ajst-20214	73	7	bn	bn	NOUN
ajst-20214	73	8	layer	layer	NOUN
ajst-20214	73	9	can	can	AUX
ajst-20214	73	10	be	be	AUX
ajst-20214	73	11	used	use	VERB
ajst-20214	73	12	as	as	ADP
ajst-20214	73	13	influencing	influence	VERB
ajst-20214	73	14	factors	factor	NOUN
ajst-20214	73	15	for	for	ADP
ajst-20214	73	16	channel	channel	NOUN
ajst-20214	73	17	pruning	prune	VERB
ajst-20214	73	18	to	to	PART
ajst-20214	73	19	measure	measure	VERB
ajst-20214	73	20	the	the	DET
ajst-20214	73	21	importance	importance	NOUN
ajst-20214	73	22	of	of	ADP
ajst-20214	73	23	each	each	DET
ajst-20214	73	24	channel	channel	NOUN
ajst-20214	73	25	.	.	PUNCT
ajst-20214	74	1	for	for	ADP
ajst-20214	74	2	the	the	DET
ajst-20214	74	3	set	set	NOUN
ajst-20214	74	4	of	of	ADP
ajst-20214	74	5			VERB
ajst-20214	74	6	corresponding	correspond	VERB
ajst-20214	74	7	to	to	ADP
ajst-20214	74	8	each	each	DET
ajst-20214	74	9	channel	channel	NOUN
ajst-20214	74	10			NUM
ajst-20214	74	11	in	in	ADP
ajst-20214	74	12	the	the	DET
ajst-20214	74	13	bn	bn	NOUN
ajst-20214	74	14	layer	layer	NOUN
ajst-20214	74	15	,	,	PUNCT
ajst-20214	74	16	l1	l1	PROPN
ajst-20214	74	17	regularization	regularization	NOUN
ajst-20214	74	18	is	be	AUX
ajst-20214	74	19	employed	employ	VERB
ajst-20214	74	20	to	to	PART
ajst-20214	74	21	achieve	achieve	VERB
ajst-20214	74	22	sparse	sparse	ADJ
ajst-20214	74	23	expression	expression	NOUN
ajst-20214	74	24	.	.	PUNCT
ajst-20214	75	1	by	by	ADP
ajst-20214	75	2	introducing	introduce	VERB
ajst-20214	75	3	sparse	sparse	ADJ
ajst-20214	75	4	expression	expression	NOUN
ajst-20214	75	5	into	into	ADP
ajst-20214	75	6	the	the	DET
ajst-20214	75	7	network	network	NOUN
ajst-20214	75	8	's	's	PART
ajst-20214	75	9	loss	loss	NOUN
ajst-20214	75	10	function	function	NOUN
ajst-20214	75	11	l	l	NOUN
ajst-20214	75	12	for	for	ADP
ajst-20214	75	13	sparse	sparse	ADJ
ajst-20214	75	14	training	training	NOUN
ajst-20214	75	15	,	,	PUNCT
ajst-20214	75	16	the	the	DET
ajst-20214	75	17	formula	formula	NOUN
ajst-20214	75	18	is	be	AUX
ajst-20214	75	19	as	as	SCONJ
ajst-20214	75	20	follows	follow	VERB
ajst-20214	75	21	:	:	PUNCT
ajst-20214	75	22	(	(	PUNCT
ajst-20214	75	23	,	,	PUNCT
ajst-20214	75	24	)	)	PUNCT
ajst-20214	75	25	(	(	PUNCT
ajst-20214	75	26	(	(	PUNCT
ajst-20214	75	27	,	,	PUNCT
ajst-20214	75	28	)	)	PUNCT
ajst-20214	75	29	,	,	PUNCT
ajst-20214	75	30	)	)	PUNCT
ajst-20214	75	31	(	(	PUNCT
ajst-20214	75	32	)	)	PUNCT
ajst-20214	75	33	x	x	PUNCT
ajst-20214	76	1	y	y	NOUN
ajst-20214	76	2	y	y	PROPN
ajst-20214	76	3	l	l	NOUN
ajst-20214	76	4	l	l	NOUN
ajst-20214	77	1	f	f	X
ajst-20214	77	2	x	x	X
ajst-20214	77	3	w	w	PROPN
ajst-20214	77	4	y	y	PROPN
ajst-20214	77	5	g	g	PROPN
ajst-20214	77	6			PROPN
ajst-20214	77	7			NOUN
ajst-20214	77	8			NUM
ajst-20214	77	9			NOUN
ajst-20214	77	10			X
ajst-20214	77	11	(	(	PUNCT
ajst-20214	77	12	1	1	X
ajst-20214	77	13	)	)	PUNCT
ajst-20214	77	14	where	where	SCONJ
ajst-20214	77	15	,	,	PUNCT
ajst-20214	77	16	x	x	PRON
ajst-20214	77	17	and	and	CCONJ
ajst-20214	77	18	y	y	PROPN
ajst-20214	77	19	represent	represent	VERB
ajst-20214	77	20	the	the	DET
ajst-20214	77	21	input	input	NOUN
ajst-20214	77	22	and	and	CCONJ
ajst-20214	77	23	target	target	NOUN
ajst-20214	77	24	of	of	ADP
ajst-20214	77	25	the	the	DET
ajst-20214	77	26	network	network	NOUN
ajst-20214	77	27	,	,	PUNCT
ajst-20214	77	28	respectively	respectively	ADV
ajst-20214	77	29	,	,	PUNCT
ajst-20214	77	30	w	w	PROPN
ajst-20214	77	31	represents	represent	VERB
ajst-20214	77	32	the	the	DET
ajst-20214	77	33	trainable	trainable	ADJ
ajst-20214	77	34	weights	weight	NOUN
ajst-20214	77	35	of	of	ADP
ajst-20214	77	36	the	the	DET
ajst-20214	77	37	network	network	NOUN
ajst-20214	77	38	,	,	PUNCT
ajst-20214	77	39	(	(	PUNCT
ajst-20214	77	40	,	,	PUNCT
ajst-20214	77	41	)	)	PUNCT
ajst-20214	77	42	(	(	PUNCT
ajst-20214	77	43	(	(	PUNCT
ajst-20214	77	44	,	,	PUNCT
ajst-20214	77	45	)	)	PUNCT
ajst-20214	77	46	,	,	PUNCT
ajst-20214	77	47	)	)	PUNCT
ajst-20214	78	1	x	x	PUNCT
ajst-20214	79	1	y	y	NOUN
ajst-20214	79	2	l	l	NOUN
ajst-20214	79	3	f	f	X
ajst-20214	79	4	x	x	X
ajst-20214	79	5	w	w	PROPN
ajst-20214	79	6	y	y	PROPN
ajst-20214	79	7	represents	represent	VERB
ajst-20214	79	8	the	the	DET
ajst-20214	79	9	original	original	ADJ
ajst-20214	79	10	loss	loss	NOUN
ajst-20214	79	11	function	function	NOUN
ajst-20214	79	12	,	,	PUNCT
ajst-20214	79	13			X
ajst-20214	79	14	is	be	AUX
ajst-20214	79	15	the	the	DET
ajst-20214	79	16	balancing	balancing	NOUN
ajst-20214	79	17	factor	factor	NOUN
ajst-20214	79	18	,	,	PUNCT
ajst-20214	79	19	and	and	CCONJ
ajst-20214	79	20	(	(	PUNCT
ajst-20214	79	21	)	)	PUNCT
ajst-20214	79	22	g	g	PROPN
ajst-20214	79	23			PROPN
ajst-20214	79	24	is	be	AUX
ajst-20214	79	25	the	the	DET
ajst-20214	79	26	loss	loss	NOUN
ajst-20214	79	27	for	for	ADP
ajst-20214	79	28	sparse	sparse	ADJ
ajst-20214	79	29	training	training	NOUN
ajst-20214	79	30	of	of	ADP
ajst-20214	79	31	the	the	DET
ajst-20214	79	32	scaling	scale	VERB
ajst-20214	79	33	parameter	parameter	NOUN
ajst-20214	79	34			PROPN
ajst-20214	79	35	,	,	PUNCT
ajst-20214	79	36	which	which	PRON
ajst-20214	79	37	is	be	AUX
ajst-20214	79	38	implemented	implement	VERB
ajst-20214	79	39	using	use	VERB
ajst-20214	79	40	l1	l1	PROPN
ajst-20214	79	41	regularization	regularization	NOUN
ajst-20214	79	42	,	,	PUNCT
ajst-20214	79	43	i.e.	i.e.	X
ajst-20214	79	44	,	,	PUNCT
ajst-20214	79	45	(	(	PUNCT
ajst-20214	79	46	)	)	PUNCT
ajst-20214	79	47	g	g	PROPN
ajst-20214	79	48			NUM
ajst-20214	79	49			PROPN
ajst-20214	79	50	.	.	PUNCT
ajst-20214	80	1	during	during	ADP
ajst-20214	80	2	sparse	sparse	ADJ
ajst-20214	80	3	training	training	NOUN
ajst-20214	80	4	,	,	PUNCT
ajst-20214	80	5	keeping	keep	VERB
ajst-20214	80	6	the	the	DET
ajst-20214	80	7	balancing	balancing	NOUN
ajst-20214	80	8	factor	factor	NOUN
ajst-20214	80	9			ADJ
ajst-20214	80	10	constant	constant	ADJ
ajst-20214	80	11	is	be	AUX
ajst-20214	80	12	a	a	DET
ajst-20214	80	13	commonly	commonly	ADV
ajst-20214	80	14	used	use	VERB
ajst-20214	80	15	approach	approach	NOUN
ajst-20214	80	16	.	.	PUNCT
ajst-20214	81	1	although	although	SCONJ
ajst-20214	81	2	it	it	PRON
ajst-20214	81	3	can	can	AUX
ajst-20214	81	4	achieve	achieve	VERB
ajst-20214	81	5	good	good	ADJ
ajst-20214	81	6	sparsity	sparsity	NOUN
ajst-20214	81	7	results	result	NOUN
ajst-20214	81	8	for	for	ADP
ajst-20214	81	9			NUM
ajst-20214	81	10	,	,	PUNCT
ajst-20214	81	11	it	it	PRON
ajst-20214	81	12	requires	require	VERB
ajst-20214	81	13	a	a	DET
ajst-20214	81	14	significant	significant	ADJ
ajst-20214	81	15	amount	amount	NOUN
ajst-20214	81	16	of	of	ADP
ajst-20214	81	17	time	time	NOUN
ajst-20214	81	18	to	to	PART
ajst-20214	81	19	find	find	VERB
ajst-20214	81	20	the	the	DET
ajst-20214	81	21	appropriate	appropriate	ADJ
ajst-20214	81	22	value	value	NOUN
ajst-20214	81	23	of	of	ADP
ajst-20214	81	24			NOUN
ajst-20214	81	25	.	.	PUNCT
ajst-20214	82	1	therefore	therefore	ADV
ajst-20214	82	2	,	,	PUNCT
ajst-20214	82	3	a	a	DET
ajst-20214	82	4	subgradient	subgradient	ADJ
ajst-20214	82	5	descent	descent	NOUN
ajst-20214	82	6	optimization	optimization	NOUN
ajst-20214	82	7	method	method	NOUN
ajst-20214	82	8	is	be	AUX
ajst-20214	82	9	adopted	adopt	VERB
ajst-20214	82	10	to	to	PART
ajst-20214	82	11	continuously	continuously	ADV
ajst-20214	82	12	decrease	decrease	VERB
ajst-20214	82	13	the	the	DET
ajst-20214	82	14	value	value	NOUN
ajst-20214	82	15	of	of	ADP
ajst-20214	82	16			ADJ
ajst-20214	82	17	during	during	ADP
ajst-20214	82	18	training	training	NOUN
ajst-20214	82	19	,	,	PUNCT
ajst-20214	82	20	allowing	allow	VERB
ajst-20214	82	21			NOUN
ajst-20214	82	22	to	to	PART
ajst-20214	82	23	gradually	gradually	ADV
ajst-20214	82	24	approach	approach	VERB
ajst-20214	82	25	0	0	PUNCT
ajst-20214	82	26	and	and	CCONJ
ajst-20214	82	27	achieve	achieve	VERB
ajst-20214	82	28	sparsity	sparsity	NOUN
ajst-20214	82	29	.	.	PUNCT
ajst-20214	83	1	after	after	ADP
ajst-20214	83	2	sparse	sparse	ADJ
ajst-20214	83	3	training	training	NOUN
ajst-20214	83	4	,	,	PUNCT
ajst-20214	83	5	the	the	DET
ajst-20214	83	6	obtained	obtain	VERB
ajst-20214	83	7	scaling	scale	VERB
ajst-20214	83	8	factors	factor	NOUN
ajst-20214	83	9			NUM
ajst-20214	83	10	are	be	AUX
ajst-20214	83	11	sorted	sort	VERB
ajst-20214	83	12	.	.	PUNCT
ajst-20214	84	1	based	base	VERB
ajst-20214	84	2	on	on	ADP
ajst-20214	84	3	the	the	DET
ajst-20214	84	4	set	set	NOUN
ajst-20214	84	5	pruning	pruning	NOUN
ajst-20214	84	6	ratio	ratio	NOUN
ajst-20214	84	7	,	,	PUNCT
ajst-20214	84	8	a	a	DET
ajst-20214	84	9	pruning	prune	VERB
ajst-20214	84	10	threshold	threshold	NOUN
ajst-20214	84	11	is	be	AUX
ajst-20214	84	12	determined	determine	VERB
ajst-20214	84	13	.	.	PUNCT
ajst-20214	85	1	if	if	SCONJ
ajst-20214	85	2	the	the	DET
ajst-20214	85	3	value	value	NOUN
ajst-20214	85	4	of	of	ADP
ajst-20214	85	5	a	a	DET
ajst-20214	85	6	scaling	scale	VERB
ajst-20214	85	7	factor	factor	NOUN
ajst-20214	85	8			NUM
ajst-20214	85	9	is	be	AUX
ajst-20214	85	10	below	below	ADP
ajst-20214	85	11	this	this	DET
ajst-20214	85	12	threshold	threshold	NOUN
ajst-20214	85	13	,	,	PUNCT
ajst-20214	85	14	it	it	PRON
ajst-20214	85	15	is	be	AUX
ajst-20214	85	16	considered	consider	VERB
ajst-20214	85	17	a	a	DET
ajst-20214	85	18	less	less	ADV
ajst-20214	85	19	important	important	ADJ
ajst-20214	85	20	channel	channel	NOUN
ajst-20214	85	21	and	and	CCONJ
ajst-20214	85	22	will	will	AUX
ajst-20214	85	23	be	be	AUX
ajst-20214	85	24	pruned	prune	VERB
ajst-20214	85	25	.	.	PUNCT
ajst-20214	86	1	the	the	DET
ajst-20214	86	2	specific	specific	ADJ
ajst-20214	86	3	process	process	NOUN
ajst-20214	86	4	of	of	ADP
ajst-20214	86	5	channel	channel	NOUN
ajst-20214	86	6	pruning	pruning	NOUN
ajst-20214	86	7	is	be	AUX
ajst-20214	86	8	illustrated	illustrate	VERB
ajst-20214	86	9	in	in	ADP
ajst-20214	86	10	fig	fig	NOUN
ajst-20214	86	11	.	.	PUNCT
ajst-20214	87	1	2	2	X
ajst-20214	87	2	.	.	X
ajst-20214	87	3	in	in	ADP
ajst-20214	87	4	the	the	DET
ajst-20214	87	5	i	i	NOUN
ajst-20214	87	6	-	-	PUNCT
ajst-20214	87	7	th	th	X
ajst-20214	87	8	convolutional	convolutional	ADJ
ajst-20214	87	9	layer	layer	NOUN
ajst-20214	87	10	of	of	ADP
ajst-20214	87	11	the	the	DET
ajst-20214	87	12	original	original	ADJ
ajst-20214	87	13	network	network	NOUN
ajst-20214	87	14	,	,	PUNCT
ajst-20214	87	15	each	each	DET
ajst-20214	87	16	feature	feature	NOUN
ajst-20214	87	17	channel	channel	NOUN
ajst-20214	87	18	is	be	AUX
ajst-20214	87	19	connected	connect	VERB
ajst-20214	87	20	to	to	ADP
ajst-20214	87	21	a	a	DET
ajst-20214	87	22	scaling	scale	VERB
ajst-20214	87	23	factor	factor	NOUN
ajst-20214	87	24			NOUN
ajst-20214	87	25	that	that	PRON
ajst-20214	87	26	has	have	AUX
ajst-20214	87	27	undergone	undergo	VERB
ajst-20214	87	28	sparse	sparse	ADJ
ajst-20214	87	29	processing	processing	NOUN
ajst-20214	87	30	.	.	PUNCT
ajst-20214	88	1	if	if	SCONJ
ajst-20214	88	2	the	the	DET
ajst-20214	88	3	values	value	NOUN
ajst-20214	88	4	of	of	ADP
ajst-20214	88	5	scaling	scale	VERB
ajst-20214	88	6	factors	factor	NOUN
ajst-20214	88	7			NUM
ajst-20214	88	8	corresponding	correspond	VERB
ajst-20214	88	9	to	to	AUX
ajst-20214	88	10	feature	feature	VERB
ajst-20214	88	11	channels	channel	NOUN
ajst-20214	88	12	ci2	ci2	PROPN
ajst-20214	88	13	and	and	CCONJ
ajst-20214	88	14	ci3	ci3	NOUN
ajst-20214	88	15	are	be	AUX
ajst-20214	88	16	below	below	ADP
ajst-20214	88	17	the	the	DET
ajst-20214	88	18	preset	preset	ADJ
ajst-20214	88	19	threshold	threshold	NOUN
ajst-20214	88	20	,	,	PUNCT
ajst-20214	88	21	the	the	DET
ajst-20214	88	22	convolutional	convolutional	ADJ
ajst-20214	88	23	kernels	kernel	NOUN
ajst-20214	88	24	and	and	CCONJ
ajst-20214	88	25	feature	feature	NOUN
ajst-20214	88	26	channels	channel	NOUN
ajst-20214	88	27	associated	associate	VERB
ajst-20214	88	28	with	with	ADP
ajst-20214	88	29	these	these	DET
ajst-20214	88	30	channels	channel	NOUN
ajst-20214	88	31	will	will	AUX
ajst-20214	88	32	be	be	AUX
ajst-20214	88	33	removed	remove	VERB
ajst-20214	88	34	,	,	PUNCT
ajst-20214	88	35	effectively	effectively	ADV
ajst-20214	88	36	compressing	compress	VERB
ajst-20214	88	37	the	the	DET
ajst-20214	88	38	model	model	NOUN
ajst-20214	88	39	size	size	NOUN
ajst-20214	88	40	.	.	PUNCT
ajst-20214	89	1	…	…	PUNCT
ajst-20214	89	2	…	…	PUNCT
ajst-20214	89	3	0.955	0.955	NUM
ajst-20214	89	4	0.005	0.005	NUM
ajst-20214	89	5	0.006	0.006	NUM
ajst-20214	89	6	0.873	0.873	NUM
ajst-20214	89	7	(	(	PUNCT
ajst-20214	89	8	j	j	NOUN
ajst-20214	89	9	=	=	NOUN
ajst-20214	89	10	i+1	i+1	ADV
ajst-20214	89	11	)	)	PUNCT
ajst-20214	89	12	pruning	prune	VERB
ajst-20214	89	13	0.912	0.912	NUM
ajst-20214	89	14	…	…	PUNCT
ajst-20214	89	15	…	…	PUNCT
ajst-20214	89	16	0.955	0.955	NUM
ajst-20214	89	17	0.873	0.873	NUM
ajst-20214	89	18	(	(	PUNCT
ajst-20214	89	19	j	j	X
ajst-20214	89	20	=	=	NOUN
ajst-20214	89	21	i+1	i+1	NOUN
ajst-20214	89	22	)	)	PUNCT
ajst-20214	89	23	0.912	0.912	NUM
ajst-20214	89	24	…	…	SYM
ajst-20214	89	25	…	…	PUNCT
ajst-20214	89	26	…	…	PUNCT
ajst-20214	89	27	…	…	PUNCT
ajst-20214	89	28	feature	feature	NOUN
ajst-20214	89	29	map	map	NOUN
ajst-20214	89	30	of	of	ADP
ajst-20214	89	31	the	the	DET
ajst-20214	89	32	i	i	NOUN
ajst-20214	89	33	-	-	PUNCT
ajst-20214	89	34	th	th	X
ajst-20214	89	35	convolutional	convolutional	ADJ
ajst-20214	89	36	layer	layer	NOUN
ajst-20214	89	37	feature	feature	NOUN
ajst-20214	89	38	map	map	NOUN
ajst-20214	89	39	of	of	ADP
ajst-20214	89	40	the	the	DET
ajst-20214	89	41	j	j	PROPN
ajst-20214	89	42	-	-	PUNCT
ajst-20214	89	43	th	th	VERB
ajst-20214	89	44	convolutional	convolutional	ADJ
ajst-20214	89	45	layer	layer	NOUN
ajst-20214	89	46	the	the	DET
ajst-20214	89	47	scaling	scaling	ADJ
ajst-20214	89	48	factor	factor	NOUN
ajst-20214	89	49	of	of	ADP
ajst-20214	89	50	the	the	DET
ajst-20214	89	51	batch	batch	NOUN
ajst-20214	89	52	normalization	normalization	NOUN
ajst-20214	89	53	(	(	PUNCT
ajst-20214	89	54	bn	bn	NOUN
ajst-20214	89	55	)	)	PUNCT
ajst-20214	89	56	layer	layer	NOUN
ajst-20214	89	57	feature	feature	NOUN
ajst-20214	89	58	map	map	NOUN
ajst-20214	89	59	of	of	ADP
ajst-20214	89	60	the	the	DET
ajst-20214	89	61	i	i	NOUN
ajst-20214	89	62	-	-	PUNCT
ajst-20214	89	63	th	th	X
ajst-20214	89	64	convolutional	convolutional	ADJ
ajst-20214	89	65	layer	layer	NOUN
ajst-20214	89	66	the	the	DET
ajst-20214	89	67	scaling	scaling	ADJ
ajst-20214	89	68	factor	factor	NOUN
ajst-20214	89	69	of	of	ADP
ajst-20214	89	70	the	the	DET
ajst-20214	89	71	batch	batch	NOUN
ajst-20214	89	72	normalization	normalization	NOUN
ajst-20214	89	73	(	(	PUNCT
ajst-20214	89	74	bn	bn	NOUN
ajst-20214	89	75	)	)	PUNCT
ajst-20214	89	76	layer	layer	NOUN
ajst-20214	89	77	feature	feature	NOUN
ajst-20214	89	78	map	map	NOUN
ajst-20214	89	79	of	of	ADP
ajst-20214	89	80	the	the	DET
ajst-20214	89	81	j	j	PROPN
ajst-20214	89	82	-	-	PUNCT
ajst-20214	89	83	th	th	VERB
ajst-20214	89	84	convolutional	convolutional	ADJ
ajst-20214	89	85	layer	layer	NOUN
ajst-20214	89	86	figure	figure	NOUN
ajst-20214	89	87	2	2	NUM
ajst-20214	89	88	.	.	PUNCT
ajst-20214	90	1	the	the	DET
ajst-20214	90	2	process	process	NOUN
ajst-20214	90	3	of	of	ADP
ajst-20214	90	4	channel	channel	NOUN
ajst-20214	90	5	pruning	prune	VERB
ajst-20214	90	6	3.3	3.3	NUM
ajst-20214	90	7	.	.	PUNCT
ajst-20214	91	1	the	the	DET
ajst-20214	91	2	design	design	NOUN
ajst-20214	91	3	of	of	ADP
ajst-20214	91	4	fine	fine	ADJ
ajst-20214	91	5	-	-	PUNCT
ajst-20214	91	6	tuning	tune	VERB
ajst-20214	91	7	training	training	NOUN
ajst-20214	91	8	method	method	NOUN
ajst-20214	91	9	based	base	VERB
ajst-20214	91	10	on	on	ADP
ajst-20214	91	11	logic	logic	NOUN
ajst-20214	91	12	distillation	distillation	NOUN
ajst-20214	91	13	.	.	PUNCT
ajst-20214	92	1	after	after	ADP
ajst-20214	92	2	pruning	prune	VERB
ajst-20214	92	3	and	and	CCONJ
ajst-20214	92	4	compressing	compress	VERB
ajst-20214	92	5	the	the	DET
ajst-20214	92	6	model	model	NOUN
ajst-20214	92	7	in	in	ADP
ajst-20214	92	8	section	section	NOUN
ajst-20214	92	9	3.2	3.2	NUM
ajst-20214	92	10	,	,	PUNCT
ajst-20214	92	11	the	the	DET
ajst-20214	92	12	number	number	NOUN
ajst-20214	92	13	of	of	ADP
ajst-20214	92	14	parameters	parameter	NOUN
ajst-20214	92	15	and	and	CCONJ
ajst-20214	92	16	computational	computational	ADJ
ajst-20214	92	17	complexity	complexity	NOUN
ajst-20214	92	18	of	of	ADP
ajst-20214	92	19	the	the	DET
ajst-20214	92	20	model	model	NOUN
ajst-20214	92	21	decrease	decrease	NOUN
ajst-20214	92	22	significantly	significantly	ADV
ajst-20214	92	23	,	,	PUNCT
ajst-20214	92	24	but	but	CCONJ
ajst-20214	92	25	there	there	PRON
ajst-20214	92	26	is	be	VERB
ajst-20214	92	27	also	also	ADV
ajst-20214	92	28	a	a	DET
ajst-20214	92	29	certain	certain	ADJ
ajst-20214	92	30	loss	loss	NOUN
ajst-20214	92	31	in	in	ADP
ajst-20214	92	32	model	model	NOUN
ajst-20214	92	33	accuracy	accuracy	NOUN
ajst-20214	92	34	.	.	PUNCT
ajst-20214	93	1	at	at	ADP
ajst-20214	93	2	this	this	DET
ajst-20214	93	3	point	point	NOUN
ajst-20214	93	4	,	,	PUNCT
ajst-20214	93	5	fine	fine	ADV
ajst-20214	93	6	-	-	PUNCT
ajst-20214	93	7	tuning	tuning	NOUN
ajst-20214	93	8	training	training	NOUN
ajst-20214	93	9	is	be	AUX
ajst-20214	93	10	needed	need	VERB
ajst-20214	93	11	to	to	PART
ajst-20214	93	12	restore	restore	VERB
ajst-20214	93	13	the	the	DET
ajst-20214	93	14	accuracy	accuracy	NOUN
ajst-20214	93	15	.	.	PUNCT
ajst-20214	94	1	the	the	DET
ajst-20214	94	2	commonly	commonly	ADV
ajst-20214	94	3	used	use	VERB
ajst-20214	94	4	finetuning	finetune	VERB
ajst-20214	94	5	training	training	NOUN
ajst-20214	94	6	method	method	NOUN
ajst-20214	94	7	is	be	AUX
ajst-20214	94	8	to	to	PART
ajst-20214	94	9	directly	directly	ADV
ajst-20214	94	10	retrain	retrain	VERB
ajst-20214	94	11	the	the	DET
ajst-20214	94	12	pruned	prune	VERB
ajst-20214	94	13	network	network	NOUN
ajst-20214	94	14	to	to	PART
ajst-20214	94	15	restore	restore	VERB
ajst-20214	94	16	its	its	PRON
ajst-20214	94	17	detection	detection	NOUN
ajst-20214	94	18	accuracy	accuracy	NOUN
ajst-20214	94	19	.	.	PUNCT
ajst-20214	95	1	in	in	ADP
ajst-20214	95	2	this	this	DET
ajst-20214	95	3	paper	paper	NOUN
ajst-20214	95	4	,	,	PUNCT
ajst-20214	95	5	a	a	DET
ajst-20214	95	6	finetuning	finetune	VERB
ajst-20214	95	7	training	training	NOUN
ajst-20214	95	8	method	method	NOUN
ajst-20214	95	9	based	base	VERB
ajst-20214	95	10	on	on	ADP
ajst-20214	95	11	logic	logic	NOUN
ajst-20214	95	12	distillation	distillation	NOUN
ajst-20214	95	13	is	be	AUX
ajst-20214	95	14	designed	design	VERB
ajst-20214	95	15	,	,	PUNCT
ajst-20214	95	16	where	where	SCONJ
ajst-20214	95	17	the	the	DET
ajst-20214	95	18	unpruned	unpruned	ADJ
ajst-20214	95	19	network	network	NOUN
ajst-20214	95	20	serves	serve	VERB
ajst-20214	95	21	as	as	SCONJ
ajst-20214	95	22	the	the	DET
ajst-20214	95	23	teacher	teacher	NOUN
ajst-20214	95	24	network	network	NOUN
ajst-20214	95	25	and	and	CCONJ
ajst-20214	95	26	the	the	DET
ajst-20214	95	27	pruned	prune	VERB
ajst-20214	95	28	network	network	NOUN
ajst-20214	95	29	serves	serve	VERB
ajst-20214	95	30	as	as	ADP
ajst-20214	95	31	the	the	DET
ajst-20214	95	32	student	student	NOUN
ajst-20214	95	33	network	network	NOUN
ajst-20214	95	34	.	.	PUNCT
ajst-20214	96	1	by	by	ADP
ajst-20214	96	2	transferring	transfer	VERB
ajst-20214	96	3	the	the	DET
ajst-20214	96	4	logit	logit	NOUN
ajst-20214	96	5	information	information	NOUN
ajst-20214	96	6	from	from	ADP
ajst-20214	96	7	the	the	DET
ajst-20214	96	8	large	large	ADJ
ajst-20214	96	9	neural	neural	ADJ
ajst-20214	96	10	network	network	NOUN
ajst-20214	96	11	to	to	ADP
ajst-20214	96	12	the	the	DET
ajst-20214	96	13	small	small	ADJ
ajst-20214	96	14	neural	neural	ADJ
ajst-20214	96	15	network	network	NOUN
ajst-20214	96	16	,	,	PUNCT
ajst-20214	96	17	knowledge	knowledge	NOUN
ajst-20214	96	18	transfer	transfer	NOUN
ajst-20214	96	19	between	between	ADP
ajst-20214	96	20	the	the	DET
ajst-20214	96	21	two	two	NUM
ajst-20214	96	22	models	model	NOUN
ajst-20214	96	23	is	be	AUX
ajst-20214	96	24	achieved	achieve	VERB
ajst-20214	96	25	.	.	PUNCT
ajst-20214	97	1	by	by	ADP
ajst-20214	97	2	adopting	adopt	VERB
ajst-20214	97	3	the	the	DET
ajst-20214	97	4	logic	logic	NOUN
ajst-20214	97	5	distillation	distillation	NOUN
ajst-20214	97	6	method	method	NOUN
ajst-20214	97	7	,	,	PUNCT
ajst-20214	97	8	an	an	DET
ajst-20214	97	9	auxiliary	auxiliary	ADJ
ajst-20214	97	10	network	network	NOUN
ajst-20214	97	11	is	be	AUX
ajst-20214	97	12	introduced	introduce	VERB
ajst-20214	97	13	to	to	PART
ajst-20214	97	14	supervise	supervise	VERB
ajst-20214	97	15	and	and	CCONJ
ajst-20214	97	16	assist	assist	VERB
ajst-20214	97	17	the	the	DET
ajst-20214	97	18	fine	fine	ADV
ajst-20214	97	19	-	-	PUNCT
ajst-20214	97	20	tuning	tune	VERB
ajst-20214	97	21	training	training	NOUN
ajst-20214	97	22	process	process	NOUN
ajst-20214	97	23	of	of	ADP
ajst-20214	97	24	the	the	DET
ajst-20214	97	25	pruned	prune	VERB
ajst-20214	97	26	network	network	NOUN
ajst-20214	97	27	,	,	PUNCT
ajst-20214	97	28	thereby	thereby	ADV
ajst-20214	97	29	fully	fully	ADV
ajst-20214	97	30	utilizing	utilize	VERB
ajst-20214	97	31	richer	rich	ADJ
ajst-20214	97	32	sample	sample	NOUN
ajst-20214	97	33	information	information	NOUN
ajst-20214	97	34	and	and	CCONJ
ajst-20214	97	35	ultimately	ultimately	ADV
ajst-20214	97	36	obtaining	obtain	VERB
ajst-20214	97	37	better	well	ADJ
ajst-20214	97	38	detection	detection	NOUN
ajst-20214	97	39	performance	performance	NOUN
ajst-20214	97	40	.	.	PUNCT
ajst-20214	98	1	this	this	DET
ajst-20214	98	2	method	method	NOUN
ajst-20214	98	3	can	can	AUX
ajst-20214	98	4	effectively	effectively	ADV
ajst-20214	98	5	improve	improve	VERB
ajst-20214	98	6	the	the	DET
ajst-20214	98	7	performance	performance	NOUN
ajst-20214	98	8	of	of	ADP
ajst-20214	98	9	the	the	DET
ajst-20214	98	10	pruned	prune	VERB
ajst-20214	98	11	network	network	NOUN
ajst-20214	98	12	while	while	SCONJ
ajst-20214	98	13	ensuring	ensure	VERB
ajst-20214	98	14	the	the	DET
ajst-20214	98	15	accuracy	accuracy	NOUN
ajst-20214	98	16	and	and	CCONJ
ajst-20214	98	17	generalization	generalization	NOUN
ajst-20214	98	18	ability	ability	NOUN
ajst-20214	98	19	of	of	ADP
ajst-20214	98	20	the	the	DET
ajst-20214	98	21	model	model	NOUN
ajst-20214	98	22	.	.	PUNCT
ajst-20214	99	1	in	in	ADP
ajst-20214	99	2	this	this	DET
ajst-20214	99	3	paper	paper	NOUN
ajst-20214	99	4	,	,	PUNCT
ajst-20214	99	5	logic	logic	ADJ
ajst-20214	99	6	distillation	distillation	NOUN
ajst-20214	99	7	is	be	AUX
ajst-20214	99	8	used	use	VERB
ajst-20214	99	9	for	for	ADP
ajst-20214	99	10	fine	fine	ADV
ajst-20214	99	11	-	-	PUNCT
ajst-20214	99	12	tuning	tuning	NOUN
ajst-20214	99	13	training	training	NOUN
ajst-20214	99	14	after	after	ADP
ajst-20214	99	15	pruning	prune	VERB
ajst-20214	99	16	.	.	PUNCT
ajst-20214	100	1	the	the	DET
ajst-20214	100	2	algorithm	algorithm	NOUN
ajst-20214	100	3	framework	framework	NOUN
ajst-20214	100	4	is	be	AUX
ajst-20214	100	5	shown	show	VERB
ajst-20214	100	6	in	in	ADP
ajst-20214	100	7	fig	fig	NOUN
ajst-20214	100	8	.	.	PUNCT
ajst-20214	101	1	3	3	X
ajst-20214	101	2	.	.	X
ajst-20214	101	3	the	the	DET
ajst-20214	101	4	algorithm	algorithm	NOUN
ajst-20214	101	5	consists	consist	VERB
ajst-20214	101	6	of	of	ADP
ajst-20214	101	7	two	two	NUM
ajst-20214	101	8	branches	branch	NOUN
ajst-20214	101	9	,	,	PUNCT
ajst-20214	101	10	namely	namely	ADV
ajst-20214	101	11	the	the	DET
ajst-20214	101	12	teacher	teacher	NOUN
ajst-20214	101	13	network	network	NOUN
ajst-20214	101	14	branch	branch	NOUN
ajst-20214	101	15	and	and	CCONJ
ajst-20214	101	16	the	the	DET
ajst-20214	101	17	student	student	NOUN
ajst-20214	101	18	network	network	NOUN
ajst-20214	101	19	branch	branch	NOUN
ajst-20214	101	20	.	.	PUNCT
ajst-20214	102	1	the	the	DET
ajst-20214	102	2	teacher	teacher	NOUN
ajst-20214	102	3	network	network	NOUN
ajst-20214	102	4	branch	branch	NOUN
ajst-20214	102	5	is	be	AUX
ajst-20214	102	6	the	the	DET
ajst-20214	102	7	original	original	ADJ
ajst-20214	102	8	unpruned	unpruned	ADJ
ajst-20214	102	9	yolov5	yolov5	NOUN
ajst-20214	102	10	object	object	NOUN
ajst-20214	102	11	detection	detection	NOUN
ajst-20214	102	12	algorithm	algorithm	NOUN
ajst-20214	102	13	,	,	PUNCT
ajst-20214	102	14	while	while	SCONJ
ajst-20214	102	15	the	the	DET
ajst-20214	102	16	student	student	NOUN
ajst-20214	102	17	network	network	NOUN
ajst-20214	102	18	branch	branch	NOUN
ajst-20214	102	19	is	be	AUX
ajst-20214	102	20	the	the	DET
ajst-20214	102	21	yolov5	yolov5	NOUN
ajst-20214	102	22	object	object	NOUN
ajst-20214	102	23	detection	detection	NOUN
ajst-20214	102	24	algorithm	algorithm	NOUN
ajst-20214	102	25	after	after	ADP
ajst-20214	102	26	network	network	NOUN
ajst-20214	102	27	pruning	prune	VERB
ajst-20214	102	28	in	in	ADP
ajst-20214	102	29	section	section	NOUN
ajst-20214	102	30	3.2	3.2	NUM
ajst-20214	102	31	.	.	PUNCT
ajst-20214	103	1	after	after	ADP
ajst-20214	103	2	inputting	inputte	VERB
ajst-20214	103	3	the	the	DET
ajst-20214	103	4	detection	detection	NOUN
ajst-20214	103	5	image	image	NOUN
ajst-20214	103	6	,	,	PUNCT
ajst-20214	103	7	it	it	PRON
ajst-20214	103	8	undergoes	undergo	VERB
ajst-20214	103	9	feature	feature	NOUN
ajst-20214	103	10	extraction	extraction	NOUN
ajst-20214	103	11	through	through	ADP
ajst-20214	103	12	both	both	CCONJ
ajst-20214	103	13	the	the	DET
ajst-20214	103	14	teacher	teacher	NOUN
ajst-20214	103	15	network	network	NOUN
ajst-20214	103	16	and	and	CCONJ
ajst-20214	103	17	the	the	DET
ajst-20214	103	18	student	student	NOUN
ajst-20214	103	19	network	network	NOUN
ajst-20214	103	20	,	,	PUNCT
ajst-20214	103	21	and	and	CCONJ
ajst-20214	103	22	finally	finally	ADV
ajst-20214	103	23	outputs	output	VERB
ajst-20214	103	24	the	the	DET
ajst-20214	103	25	image	image	NOUN
ajst-20214	103	26	position	position	NOUN
ajst-20214	103	27	,	,	PUNCT
ajst-20214	103	28	category	category	NOUN
ajst-20214	103	29	probability	probability	NOUN
ajst-20214	103	30	,	,	PUNCT
ajst-20214	103	31	and	and	CCONJ
ajst-20214	103	32	confidence	confidence	NOUN
ajst-20214	103	33	level	level	NOUN
ajst-20214	103	34	of	of	ADP
ajst-20214	103	35	the	the	DET
ajst-20214	103	36	student	student	NOUN
ajst-20214	103	37	network	network	NOUN
ajst-20214	103	38	.	.	PUNCT
ajst-20214	104	1	in	in	ADP
ajst-20214	104	2	the	the	DET
ajst-20214	104	3	process	process	NOUN
ajst-20214	104	4	of	of	ADP
ajst-20214	104	5	logic	logic	NOUN
ajst-20214	104	6	distillation	distillation	NOUN
ajst-20214	104	7	,	,	PUNCT
ajst-20214	104	8	the	the	DET
ajst-20214	104	9	loss	loss	NOUN
ajst-20214	104	10	function	function	NOUN
ajst-20214	104	11	consists	consist	VERB
ajst-20214	104	12	of	of	ADP
ajst-20214	104	13	the	the	DET
ajst-20214	104	14	bounding	bounding	NOUN
ajst-20214	104	15	box	box	NOUN
ajst-20214	104	16	loss	loss	NOUN
ajst-20214	104	17	,	,	PUNCT
ajst-20214	104	18	category	category	NOUN
ajst-20214	104	19	loss	loss	NOUN
ajst-20214	104	20	,	,	PUNCT
ajst-20214	104	21	and	and	CCONJ
ajst-20214	104	22	confidence	confidence	NOUN
ajst-20214	104	23	loss	loss	NOUN
ajst-20214	104	24	of	of	ADP
ajst-20214	104	25	the	the	DET
ajst-20214	104	26	student	student	NOUN
ajst-20214	104	27	network	network	NOUN
ajst-20214	104	28	,	,	PUNCT
ajst-20214	104	29	as	as	ADV
ajst-20214	104	30	well	well	ADV
ajst-20214	104	31	as	as	ADP
ajst-20214	104	32	the	the	DET
ajst-20214	104	33	distillation	distillation	NOUN
ajst-20214	104	34	output	output	NOUN
ajst-20214	104	35	loss	loss	NOUN
ajst-20214	104	36	.	.	PUNCT
ajst-20214	105	1	using	use	VERB
ajst-20214	105	2	the	the	DET
ajst-20214	105	3	offline	offline	ADJ
ajst-20214	105	4	distillation	distillation	NOUN
ajst-20214	105	5	method	method	NOUN
ajst-20214	105	6	of	of	ADP
ajst-20214	105	7	the	the	DET
ajst-20214	105	8	pre	pre	ADJ
ajst-20214	105	9	-	-	ADJ
ajst-20214	105	10	trained	trained	ADJ
ajst-20214	105	11	teacher	teacher	NOUN
ajst-20214	105	12	network	network	NOUN
ajst-20214	105	13	,	,	PUNCT
ajst-20214	105	14	only	only	ADV
ajst-20214	105	15	the	the	DET
ajst-20214	105	16	parameters	parameter	NOUN
ajst-20214	105	17	of	of	ADP
ajst-20214	105	18	the	the	DET
ajst-20214	105	19	student	student	NOUN
ajst-20214	105	20	network	network	NOUN
ajst-20214	105	21	are	be	AUX
ajst-20214	105	22	updated	update	VERB
ajst-20214	105	23	.	.	PUNCT
ajst-20214	106	1	184	184	NUM
ajst-20214	106	2	teacher	teacher	NOUN
ajst-20214	106	3	network	network	NOUN
ajst-20214	106	4	student	student	NOUN
ajst-20214	106	5	network	network	NOUN
ajst-20214	106	6	knowledge	knowledge	NOUN
ajst-20214	106	7	distillation	distillation	NOUN
ajst-20214	106	8	ls	ls	PROPN
ajst-20214	106	9	ld_output	ld_output	PROPN
ajst-20214	106	10	box	box	PROPN
ajst-20214	106	11	obj	obj	PROPN
ajst-20214	106	12	cls	cls	PROPN
ajst-20214	106	13	box	box	PROPN
ajst-20214	106	14	obj	obj	PROPN
ajst-20214	106	15	cls	cls	PROPN
ajst-20214	106	16	student	student	NOUN
ajst-20214	106	17	prediction	prediction	NOUN
ajst-20214	106	18	teacher	teacher	NOUN
ajst-20214	106	19	prediction	prediction	NOUN
ajst-20214	106	20	figure	figure	NOUN
ajst-20214	106	21	3	3	NUM
ajst-20214	106	22	.	.	PUNCT
ajst-20214	107	1	the	the	DET
ajst-20214	107	2	framework	framework	NOUN
ajst-20214	107	3	of	of	ADP
ajst-20214	107	4	knowledge	knowledge	NOUN
ajst-20214	107	5	distillation	distillation	NOUN
ajst-20214	107	6	algorithm	algorithm	NOUN
ajst-20214	107	7	as	as	SCONJ
ajst-20214	107	8	can	can	AUX
ajst-20214	107	9	be	be	AUX
ajst-20214	107	10	seen	see	VERB
ajst-20214	107	11	from	from	ADP
ajst-20214	107	12	fig	fig	NOUN
ajst-20214	107	13	.	.	PUNCT
ajst-20214	108	1	3	3	NUM
ajst-20214	108	2	,	,	PUNCT
ajst-20214	108	3	the	the	DET
ajst-20214	108	4	distillation	distillation	NOUN
ajst-20214	108	5	loss	loss	NOUN
ajst-20214	108	6	function	function	NOUN
ajst-20214	108	7	consists	consist	VERB
ajst-20214	108	8	of	of	ADP
ajst-20214	108	9	the	the	DET
ajst-20214	108	10	loss	loss	NOUN
ajst-20214	108	11	function	function	NOUN
ajst-20214	108	12	of	of	ADP
ajst-20214	108	13	the	the	DET
ajst-20214	108	14	student	student	NOUN
ajst-20214	108	15	network	network	NOUN
ajst-20214	108	16	model	model	NOUN
ajst-20214	108	17	and	and	CCONJ
ajst-20214	108	18	the	the	DET
ajst-20214	108	19	distillation	distillation	NOUN
ajst-20214	108	20	output	output	NOUN
ajst-20214	108	21	loss	loss	NOUN
ajst-20214	108	22	.	.	PUNCT
ajst-20214	109	1	the	the	DET
ajst-20214	109	2	formula	formula	NOUN
ajst-20214	109	3	is	be	AUX
ajst-20214	109	4	as	as	SCONJ
ajst-20214	109	5	follows	follow	VERB
ajst-20214	109	6	:	:	PUNCT
ajst-20214	109	7	_	_	PRON
ajst-20214	109	8	s	s	X
ajst-20214	109	9	d	d	X
ajst-20214	109	10	outputl	outputl	ADJ
ajst-20214	109	11	l	l	NOUN
ajst-20214	109	12	l	l	NUM
ajst-20214	110	1			PUNCT
ajst-20214	110	2	(	(	PUNCT
ajst-20214	110	3	2	2	NUM
ajst-20214	110	4	)	)	PUNCT
ajst-20214	110	5	where	where	SCONJ
ajst-20214	110	6	,	,	PUNCT
ajst-20214	110	7	sl	sl	PRON
ajst-20214	110	8	represents	represent	VERB
ajst-20214	110	9	the	the	DET
ajst-20214	110	10	loss	loss	NOUN
ajst-20214	110	11	function	function	NOUN
ajst-20214	110	12	of	of	ADP
ajst-20214	110	13	the	the	DET
ajst-20214	110	14	student	student	NOUN
ajst-20214	110	15	network	network	NOUN
ajst-20214	110	16	model	model	NOUN
ajst-20214	110	17	,	,	PUNCT
ajst-20214	110	18	_	_	PUNCT
ajst-20214	110	19	d	d	PROPN
ajst-20214	111	1	outputl	outputl	ADJ
ajst-20214	111	2	denotes	denote	VERB
ajst-20214	111	3	the	the	DET
ajst-20214	111	4	distillation	distillation	NOUN
ajst-20214	111	5	output	output	NOUN
ajst-20214	111	6	loss	loss	NOUN
ajst-20214	111	7	,	,	PUNCT
ajst-20214	111	8	and	and	CCONJ
ajst-20214	111	9			NOUN
ajst-20214	111	10	is	be	AUX
ajst-20214	111	11	the	the	DET
ajst-20214	111	12	weight	weight	NOUN
ajst-20214	111	13	parameter	parameter	NOUN
ajst-20214	111	14	that	that	PRON
ajst-20214	111	15	adjusts	adjust	VERB
ajst-20214	111	16	the	the	DET
ajst-20214	111	17	influence	influence	NOUN
ajst-20214	111	18	of	of	ADP
ajst-20214	111	19	distillation	distillation	NOUN
ajst-20214	111	20	loss	loss	NOUN
ajst-20214	111	21	within	within	ADP
ajst-20214	111	22	the	the	DET
ajst-20214	111	23	total	total	ADJ
ajst-20214	111	24	loss	loss	NOUN
ajst-20214	111	25	.	.	PUNCT
ajst-20214	112	1	the	the	DET
ajst-20214	112	2	value	value	NOUN
ajst-20214	112	3	of	of	ADP
ajst-20214	112	4			NOUN
ajst-20214	112	5	affects	affect	VERB
ajst-20214	112	6	the	the	DET
ajst-20214	112	7	student	student	NOUN
ajst-20214	112	8	's	's	PART
ajst-20214	112	9	tendency	tendency	NOUN
ajst-20214	112	10	to	to	PART
ajst-20214	112	11	learn	learn	VERB
ajst-20214	112	12	from	from	ADP
ajst-20214	112	13	the	the	DET
ajst-20214	112	14	teacher	teacher	NOUN
ajst-20214	112	15	network	network	NOUN
ajst-20214	112	16	,	,	PUNCT
ajst-20214	112	17	determining	determine	VERB
ajst-20214	112	18	whether	whether	SCONJ
ajst-20214	112	19	it	it	PRON
ajst-20214	112	20	prefers	prefer	VERB
ajst-20214	112	21	to	to	PART
ajst-20214	112	22	acquire	acquire	VERB
ajst-20214	112	23	knowledge	knowledge	NOUN
ajst-20214	112	24	from	from	ADP
ajst-20214	112	25	the	the	DET
ajst-20214	112	26	teacher	teacher	NOUN
ajst-20214	112	27	's	's	PART
ajst-20214	112	28	predictions	prediction	NOUN
ajst-20214	112	29	or	or	CCONJ
ajst-20214	112	30	directly	directly	ADV
ajst-20214	112	31	from	from	ADP
ajst-20214	112	32	the	the	DET
ajst-20214	112	33	true	true	ADJ
ajst-20214	112	34	labels	label	NOUN
ajst-20214	112	35	.	.	PUNCT
ajst-20214	113	1	in	in	ADP
ajst-20214	113	2	this	this	DET
ajst-20214	113	3	paper	paper	NOUN
ajst-20214	113	4	,	,	PUNCT
ajst-20214	113	5			NOUN
ajst-20214	113	6	is	be	AUX
ajst-20214	113	7	set	set	VERB
ajst-20214	113	8	to	to	ADP
ajst-20214	113	9	10	10	NUM
ajst-20214	113	10	,	,	PUNCT
ajst-20214	113	11	indicating	indicate	VERB
ajst-20214	113	12	that	that	SCONJ
ajst-20214	113	13	the	the	DET
ajst-20214	113	14	distillation	distillation	NOUN
ajst-20214	113	15	loss	loss	NOUN
ajst-20214	113	16	will	will	AUX
ajst-20214	113	17	be	be	AUX
ajst-20214	113	18	amplified	amplify	VERB
ajst-20214	113	19	by	by	ADP
ajst-20214	113	20	a	a	DET
ajst-20214	113	21	factor	factor	NOUN
ajst-20214	113	22	of	of	ADP
ajst-20214	113	23	10	10	NUM
ajst-20214	113	24	.	.	PUNCT
ajst-20214	114	1	sl	sl	PROPN
ajst-20214	114	2	represents	represent	VERB
ajst-20214	114	3	the	the	DET
ajst-20214	114	4	hard	hard	ADJ
ajst-20214	114	5	loss	loss	NOUN
ajst-20214	114	6	of	of	ADP
ajst-20214	114	7	the	the	DET
ajst-20214	114	8	student	student	NOUN
ajst-20214	114	9	model	model	NOUN
ajst-20214	114	10	,	,	PUNCT
ajst-20214	114	11	reflecting	reflect	VERB
ajst-20214	114	12	the	the	DET
ajst-20214	114	13	discrepancy	discrepancy	NOUN
ajst-20214	114	14	between	between	ADP
ajst-20214	114	15	the	the	DET
ajst-20214	114	16	student	student	NOUN
ajst-20214	114	17	's	's	PART
ajst-20214	114	18	predictions	prediction	NOUN
ajst-20214	114	19	and	and	CCONJ
ajst-20214	114	20	the	the	DET
ajst-20214	114	21	true	true	ADJ
ajst-20214	114	22	labels	label	NOUN
ajst-20214	114	23	.	.	PUNCT
ajst-20214	115	1	its	its	PRON
ajst-20214	115	2	numerical	numerical	ADJ
ajst-20214	115	3	value	value	NOUN
ajst-20214	115	4	corresponds	correspond	VERB
ajst-20214	115	5	to	to	ADP
ajst-20214	115	6	the	the	DET
ajst-20214	115	7	loss	loss	NOUN
ajst-20214	115	8	function	function	NOUN
ajst-20214	115	9	of	of	ADP
ajst-20214	115	10	the	the	DET
ajst-20214	115	11	original	original	ADJ
ajst-20214	115	12	yolov5	yolov5	NOUN
ajst-20214	115	13	.	.	PUNCT
ajst-20214	116	1	_	_	PUNCT
ajst-20214	117	1	d	d	PUNCT
ajst-20214	117	2	outputl	outputl	INTJ
ajst-20214	117	3	,	,	PUNCT
ajst-20214	117	4	as	as	SCONJ
ajst-20214	117	5	the	the	DET
ajst-20214	117	6	core	core	NOUN
ajst-20214	117	7	component	component	NOUN
ajst-20214	117	8	of	of	ADP
ajst-20214	117	9	logic	logic	NOUN
ajst-20214	117	10	distillation	distillation	NOUN
ajst-20214	117	11	,	,	PUNCT
ajst-20214	117	12	calculates	calculate	VERB
ajst-20214	117	13	the	the	DET
ajst-20214	117	14	difference	difference	NOUN
ajst-20214	117	15	between	between	ADP
ajst-20214	117	16	the	the	DET
ajst-20214	117	17	predictions	prediction	NOUN
ajst-20214	117	18	made	make	VERB
ajst-20214	117	19	by	by	ADP
ajst-20214	117	20	the	the	DET
ajst-20214	117	21	student	student	NOUN
ajst-20214	117	22	model	model	NOUN
ajst-20214	117	23	and	and	CCONJ
ajst-20214	117	24	those	those	PRON
ajst-20214	117	25	made	make	VERB
ajst-20214	117	26	by	by	ADP
ajst-20214	117	27	the	the	DET
ajst-20214	117	28	teacher	teacher	NOUN
ajst-20214	117	29	model	model	NOUN
ajst-20214	117	30	.	.	PUNCT
ajst-20214	118	1	the	the	DET
ajst-20214	118	2	formula	formula	NOUN
ajst-20214	118	3	for	for	ADP
ajst-20214	118	4	_	_	PROPN
ajst-20214	118	5	d	d	PROPN
ajst-20214	118	6	outputl	outputl	PROPN
ajst-20214	118	7	is	be	AUX
ajst-20214	118	8	as	as	SCONJ
ajst-20214	118	9	follows	follow	VERB
ajst-20214	118	10	:	:	PUNCT
ajst-20214	119	1	_	_	PUNCT
ajst-20214	119	2	d	d	PROPN
ajst-20214	120	1	output	output	PROPN
ajst-20214	120	2	b	b	PROPN
ajst-20214	120	3	b	b	PROPN
ajst-20214	120	4	c	c	NOUN
ajst-20214	120	5	c	c	NOUN
ajst-20214	120	6	o	o	NOUN
ajst-20214	120	7	ol	ol	ADJ
ajst-20214	120	8	h	h	NOUN
ajst-20214	120	9	l	l	NOUN
ajst-20214	120	10	h	h	NOUN
ajst-20214	121	1	l	l	NOUN
ajst-20214	121	2	h	h	NOUN
ajst-20214	121	3	l	l	NOUN
ajst-20214	121	4			VERB
ajst-20214	121	5			X
ajst-20214	121	6	(	(	PUNCT
ajst-20214	121	7	3	3	X
ajst-20214	121	8	)	)	PUNCT
ajst-20214	121	9	where	where	SCONJ
ajst-20214	121	10	,	,	PUNCT
ajst-20214	121	11	bh	bh	NOUN
ajst-20214	121	12	,	,	PUNCT
ajst-20214	121	13	ch	ch	NOUN
ajst-20214	121	14	,	,	PUNCT
ajst-20214	121	15	and	and	CCONJ
ajst-20214	121	16	oh	oh	INTJ
ajst-20214	121	17	represent	represent	VERB
ajst-20214	121	18	the	the	DET
ajst-20214	121	19	hyperparameter	hyperparameter	NOUN
ajst-20214	121	20	weight	weight	NOUN
ajst-20214	121	21	coefficients	coefficient	NOUN
ajst-20214	121	22	for	for	ADP
ajst-20214	121	23	the	the	DET
ajst-20214	121	24	bounding	bounding	NOUN
ajst-20214	121	25	box	box	NOUN
ajst-20214	121	26	loss	loss	NOUN
ajst-20214	121	27	,	,	PUNCT
ajst-20214	121	28	class	class	NOUN
ajst-20214	121	29	loss	loss	NOUN
ajst-20214	121	30	,	,	PUNCT
ajst-20214	121	31	and	and	CCONJ
ajst-20214	121	32	confidence	confidence	NOUN
ajst-20214	121	33	loss	loss	NOUN
ajst-20214	121	34	,	,	PUNCT
ajst-20214	121	35	respectively	respectively	ADV
ajst-20214	121	36	.	.	PUNCT
ajst-20214	122	1	for	for	ADP
ajst-20214	122	2	the	the	DET
ajst-20214	122	3	calculation	calculation	NOUN
ajst-20214	122	4	of	of	ADP
ajst-20214	122	5	these	these	DET
ajst-20214	122	6	three	three	NUM
ajst-20214	122	7	types	type	NOUN
ajst-20214	122	8	of	of	ADP
ajst-20214	122	9	losses	loss	NOUN
ajst-20214	122	10	,	,	PUNCT
ajst-20214	122	11	the	the	DET
ajst-20214	122	12	mean	mean	NOUN
ajst-20214	122	13	squared	square	VERB
ajst-20214	122	14	error	error	NOUN
ajst-20214	122	15	(	(	PUNCT
ajst-20214	122	16	mse	mse	NOUN
ajst-20214	122	17	)	)	PUNCT
ajst-20214	122	18	loss	loss	NOUN
ajst-20214	122	19	function	function	NOUN
ajst-20214	122	20	is	be	AUX
ajst-20214	122	21	employed	employ	VERB
ajst-20214	122	22	to	to	PART
ajst-20214	122	23	measure	measure	VERB
ajst-20214	122	24	the	the	DET
ajst-20214	122	25	differences	difference	NOUN
ajst-20214	122	26	between	between	ADP
ajst-20214	122	27	the	the	DET
ajst-20214	122	28	student	student	NOUN
ajst-20214	122	29	model	model	NOUN
ajst-20214	122	30	and	and	CCONJ
ajst-20214	122	31	the	the	DET
ajst-20214	122	32	teacher	teacher	NOUN
ajst-20214	122	33	model	model	NOUN
ajst-20214	122	34	in	in	ADP
ajst-20214	122	35	terms	term	NOUN
ajst-20214	122	36	of	of	ADP
ajst-20214	122	37	the	the	DET
ajst-20214	122	38	bounding	bounding	NOUN
ajst-20214	122	39	box	box	NOUN
ajst-20214	122	40	,	,	PUNCT
ajst-20214	122	41	class	class	NOUN
ajst-20214	122	42	,	,	PUNCT
ajst-20214	122	43	and	and	CCONJ
ajst-20214	122	44	confidence	confidence	NOUN
ajst-20214	122	45	.	.	PUNCT
ajst-20214	123	1	the	the	DET
ajst-20214	123	2	formula	formula	NOUN
ajst-20214	123	3	is	be	AUX
ajst-20214	123	4	as	as	SCONJ
ajst-20214	123	5	follows	follow	VERB
ajst-20214	123	6	:	:	PUNCT
ajst-20214	123	7	21	21	NUM
ajst-20214	123	8	(	(	PUNCT
ajst-20214	123	9	)	)	PUNCT
ajst-20214	123	10	(	(	PUNCT
ajst-20214	123	11	)	)	PUNCT
ajst-20214	124	1	i	i	PRON
ajst-20214	124	2	i	i	PRON
ajst-20214	125	1	t	t	VERB
ajst-20214	126	1	smse	smse	PROPN
ajst-20214	126	2	y	y	PROPN
ajst-20214	126	3	y	y	PROPN
ajst-20214	126	4	m	m	VERB
ajst-20214	126	5			VERB
ajst-20214	126	6			X
ajst-20214	126	7	(	(	PUNCT
ajst-20214	126	8	4	4	NUM
ajst-20214	126	9	)	)	PUNCT
ajst-20214	126	10	where	where	SCONJ
ajst-20214	126	11	,	,	PUNCT
ajst-20214	126	12	m	m	VERB
ajst-20214	126	13	represents	represent	VERB
ajst-20214	126	14	the	the	DET
ajst-20214	126	15	number	number	NOUN
ajst-20214	126	16	of	of	ADP
ajst-20214	126	17	samples	sample	NOUN
ajst-20214	126	18	,	,	PUNCT
ajst-20214	126	19	i	i	PRON
ajst-20214	126	20	ty	ty	INTJ
ajst-20214	127	1	and	and	CCONJ
ajst-20214	128	1	i	i	PRON
ajst-20214	128	2	sy	sy	INTJ
ajst-20214	128	3	denote	denote	VERB
ajst-20214	128	4	the	the	DET
ajst-20214	128	5	predicted	predict	VERB
ajst-20214	128	6	values	value	NOUN
ajst-20214	128	7	of	of	ADP
ajst-20214	128	8	the	the	DET
ajst-20214	128	9	teacher	teacher	NOUN
ajst-20214	128	10	network	network	NOUN
ajst-20214	128	11	and	and	CCONJ
ajst-20214	128	12	the	the	DET
ajst-20214	128	13	student	student	NOUN
ajst-20214	128	14	network	network	NOUN
ajst-20214	128	15	,	,	PUNCT
ajst-20214	128	16	respectively	respectively	ADV
ajst-20214	128	17	.	.	PUNCT
ajst-20214	129	1	therefore	therefore	ADV
ajst-20214	129	2	,	,	PUNCT
ajst-20214	129	3	the	the	DET
ajst-20214	129	4	formulas	formula	NOUN
ajst-20214	129	5	for	for	ADP
ajst-20214	129	6	calculating	calculate	VERB
ajst-20214	129	7	bl	bl	INTJ
ajst-20214	129	8	,	,	PUNCT
ajst-20214	129	9	cl	cl	INTJ
ajst-20214	129	10	,	,	PUNCT
ajst-20214	129	11	and	and	CCONJ
ajst-20214	129	12	tl	tl	PROPN
ajst-20214	129	13	are	be	AUX
ajst-20214	129	14	as	as	SCONJ
ajst-20214	129	15	follows	follow	VERB
ajst-20214	129	16	:	:	PUNCT
ajst-20214	129	17	_	_	PUNCT
ajst-20214	130	1	_	_	PUNCT
ajst-20214	130	2	(	(	PUNCT
ajst-20214	130	3	)	)	PUNCT
ajst-20214	130	4	b	b	PROPN
ajst-20214	130	5	b	b	PROPN
ajst-20214	130	6	t	t	PROPN
ajst-20214	130	7	b	b	X
ajst-20214	130	8	s	s	X
ajst-20214	130	9	bl	bl	PROPN
ajst-20214	130	10	w	w	PROPN
ajst-20214	130	11	mse	mse	PROPN
ajst-20214	130	12	y	y	PROPN
ajst-20214	130	13	y	y	PROPN
ajst-20214	130	14			PROPN
ajst-20214	130	15	(	(	PUNCT
ajst-20214	130	16	5	5	NUM
ajst-20214	130	17	)	)	PUNCT
ajst-20214	130	18	_	_	PUNCT
ajst-20214	131	1	_	_	PUNCT
ajst-20214	131	2	(	(	PUNCT
ajst-20214	131	3	)	)	PUNCT
ajst-20214	131	4	c	c	NOUN
ajst-20214	131	5	c	c	NOUN
ajst-20214	131	6	t	t	PROPN
ajst-20214	131	7	c	c	NOUN
ajst-20214	131	8	s	s	X
ajst-20214	131	9	cl	cl	NOUN
ajst-20214	131	10	w	w	PROPN
ajst-20214	131	11	mse	mse	PROPN
ajst-20214	131	12	y	y	PROPN
ajst-20214	131	13	y	y	PROPN
ajst-20214	131	14			PROPN
ajst-20214	131	15	(	(	PUNCT
ajst-20214	131	16	6	6	NUM
ajst-20214	131	17	)	)	PUNCT
ajst-20214	131	18	_	_	PUNCT
ajst-20214	132	1	_	_	PUNCT
ajst-20214	132	2	(	(	PUNCT
ajst-20214	132	3	)	)	PUNCT
ajst-20214	133	1	o	o	NOUN
ajst-20214	134	1	o	o	NOUN
ajst-20214	134	2	t	t	X
ajst-20214	134	3	o	o	X
ajst-20214	134	4	s	s	AUX
ajst-20214	134	5	ol	ol	PROPN
ajst-20214	134	6	w	w	PROPN
ajst-20214	134	7	mse	mse	PROPN
ajst-20214	134	8	y	y	PROPN
ajst-20214	134	9	y	y	PROPN
ajst-20214	134	10			PROPN
ajst-20214	134	11	(	(	PUNCT
ajst-20214	134	12	7	7	NUM
ajst-20214	134	13	)	)	PUNCT
ajst-20214	134	14	where	where	SCONJ
ajst-20214	134	15	,	,	PUNCT
ajst-20214	134	16	bw	bw	PROPN
ajst-20214	134	17	,	,	PUNCT
ajst-20214	134	18	cw	cw	NOUN
ajst-20214	134	19	,	,	PUNCT
ajst-20214	134	20	and	and	CCONJ
ajst-20214	134	21	ow	ow	INTJ
ajst-20214	134	22	represent	represent	VERB
ajst-20214	134	23	the	the	DET
ajst-20214	134	24	scaling	scaling	NOUN
ajst-20214	134	25	weights	weight	NOUN
ajst-20214	134	26	for	for	ADP
ajst-20214	134	27	the	the	DET
ajst-20214	134	28	bounding	bounding	NOUN
ajst-20214	134	29	box	box	NOUN
ajst-20214	134	30	loss	loss	NOUN
ajst-20214	134	31	,	,	PUNCT
ajst-20214	134	32	the	the	DET
ajst-20214	134	33	scaling	scale	VERB
ajst-20214	134	34	weight	weight	NOUN
ajst-20214	134	35	for	for	ADP
ajst-20214	134	36	the	the	DET
ajst-20214	134	37	category	category	NOUN
ajst-20214	134	38	loss	loss	NOUN
ajst-20214	134	39	,	,	PUNCT
ajst-20214	134	40	and	and	CCONJ
ajst-20214	134	41	the	the	DET
ajst-20214	134	42	confidence	confidence	NOUN
ajst-20214	134	43	score	score	NOUN
ajst-20214	134	44	output	output	NOUN
ajst-20214	134	45	by	by	ADP
ajst-20214	134	46	the	the	DET
ajst-20214	134	47	teacher	teacher	NOUN
ajst-20214	134	48	model	model	NOUN
ajst-20214	134	49	,	,	PUNCT
ajst-20214	134	50	respectively	respectively	ADV
ajst-20214	134	51	.	.	PUNCT
ajst-20214	135	1	the	the	DET
ajst-20214	135	2	values	value	NOUN
ajst-20214	135	3	of	of	ADP
ajst-20214	135	4	bw	bw	PROPN
ajst-20214	135	5	and	and	CCONJ
ajst-20214	135	6	cw	cw	NOUN
ajst-20214	135	7	are	be	AUX
ajst-20214	135	8	obtained	obtain	VERB
ajst-20214	135	9	by	by	ADP
ajst-20214	135	10	expanding	expand	VERB
ajst-20214	135	11	ow	ow	INTJ
ajst-20214	135	12	to	to	ADP
ajst-20214	135	13	the	the	DET
ajst-20214	135	14	same	same	ADJ
ajst-20214	135	15	shape	shape	NOUN
ajst-20214	135	16	as	as	ADP
ajst-20214	135	17	the	the	DET
ajst-20214	135	18	bounding	bounding	NOUN
ajst-20214	135	19	box	box	NOUN
ajst-20214	135	20	and	and	CCONJ
ajst-20214	135	21	prediction	prediction	NOUN
ajst-20214	135	22	box	box	NOUN
ajst-20214	135	23	coordinates	coordinate	NOUN
ajst-20214	135	24	,	,	PUNCT
ajst-20214	135	25	ensuring	ensure	VERB
ajst-20214	135	26	that	that	SCONJ
ajst-20214	135	27	prediction	prediction	NOUN
ajst-20214	135	28	boxes	box	NOUN
ajst-20214	135	29	with	with	ADP
ajst-20214	135	30	higher	high	ADJ
ajst-20214	135	31	confidence	confidence	NOUN
ajst-20214	135	32	scores	score	NOUN
ajst-20214	135	33	carry	carry	VERB
ajst-20214	135	34	greater	great	ADJ
ajst-20214	135	35	weight	weight	NOUN
ajst-20214	135	36	in	in	ADP
ajst-20214	135	37	the	the	DET
ajst-20214	135	38	calculation	calculation	NOUN
ajst-20214	135	39	of	of	ADP
ajst-20214	135	40	bounding	bound	VERB
ajst-20214	135	41	box	box	NOUN
ajst-20214	135	42	loss	loss	NOUN
ajst-20214	135	43	and	and	CCONJ
ajst-20214	135	44	category	category	NOUN
ajst-20214	135	45	loss	loss	NOUN
ajst-20214	135	46	.	.	PUNCT
ajst-20214	136	1	through	through	ADP
ajst-20214	136	2	the	the	DET
ajst-20214	136	3	above	above	ADJ
ajst-20214	136	4	formulas	formula	NOUN
ajst-20214	136	5	,	,	PUNCT
ajst-20214	136	6	the	the	DET
ajst-20214	136	7	final	final	ADJ
ajst-20214	136	8	distillation	distillation	NOUN
ajst-20214	136	9	loss	loss	NOUN
ajst-20214	136	10	function	function	NOUN
ajst-20214	136	11	l	l	NOUN
ajst-20214	136	12	is	be	AUX
ajst-20214	136	13	derived	derive	VERB
ajst-20214	136	14	.	.	PUNCT
ajst-20214	137	1	4	4	X
ajst-20214	137	2	.	.	X
ajst-20214	137	3	experiment	experiment	NOUN
ajst-20214	137	4	4.1	4.1	NUM
ajst-20214	137	5	.	.	PUNCT
ajst-20214	138	1	experimental	experimental	ADJ
ajst-20214	138	2	environment	environment	NOUN
ajst-20214	138	3	and	and	CCONJ
ajst-20214	138	4	dataset	dataset	NOUN
ajst-20214	138	5	sources	source	NOUN
ajst-20214	138	6	.	.	PUNCT
ajst-20214	139	1	the	the	DET
ajst-20214	139	2	model	model	NOUN
ajst-20214	139	3	training	training	NOUN
ajst-20214	139	4	and	and	CCONJ
ajst-20214	139	5	testing	testing	NOUN
ajst-20214	139	6	in	in	ADP
ajst-20214	139	7	this	this	DET
ajst-20214	139	8	paper	paper	NOUN
ajst-20214	139	9	were	be	AUX
ajst-20214	139	10	conducted	conduct	VERB
ajst-20214	139	11	on	on	ADP
ajst-20214	139	12	an	an	DET
ajst-20214	139	13	nvidia	nvidia	PROPN
ajst-20214	139	14	geforce	geforce	NOUN
ajst-20214	139	15	rtx	rtx	PROPN
ajst-20214	139	16	3080	3080	NUM
ajst-20214	139	17	ti	ti	NOUN
ajst-20214	139	18	with	with	ADP
ajst-20214	139	19	12	12	NUM
ajst-20214	139	20	gb	gb	NOUN
ajst-20214	139	21	of	of	ADP
ajst-20214	139	22	video	video	NOUN
ajst-20214	139	23	memory	memory	NOUN
ajst-20214	139	24	,	,	PUNCT
ajst-20214	139	25	using	use	VERB
ajst-20214	139	26	the	the	DET
ajst-20214	139	27	deep	deep	ADJ
ajst-20214	139	28	learning	learning	NOUN
ajst-20214	139	29	framework	framework	NOUN
ajst-20214	139	30	pytorch	pytorch	NOUN
ajst-20214	139	31	1.10	1.10	NUM
ajst-20214	139	32	.	.	PUNCT
ajst-20214	140	1	for	for	ADP
ajst-20214	140	2	the	the	DET
ajst-20214	140	3	experiments	experiment	NOUN
ajst-20214	140	4	,	,	PUNCT
ajst-20214	140	5	yolov5s	yolov5s	PROPN
ajst-20214	140	6	was	be	AUX
ajst-20214	140	7	used	use	VERB
ajst-20214	140	8	as	as	ADP
ajst-20214	140	9	the	the	DET
ajst-20214	140	10	baseline	baseline	NOUN
ajst-20214	140	11	model	model	NOUN
ajst-20214	140	12	.	.	PUNCT
ajst-20214	141	1	the	the	DET
ajst-20214	141	2	network	network	NOUN
ajst-20214	141	3	parameters	parameter	NOUN
ajst-20214	141	4	were	be	AUX
ajst-20214	141	5	iteratively	iteratively	ADV
ajst-20214	141	6	updated	update	VERB
ajst-20214	141	7	using	use	VERB
ajst-20214	141	8	the	the	DET
ajst-20214	141	9	sgd	sgd	PROPN
ajst-20214	141	10	method	method	NOUN
ajst-20214	141	11	,	,	PUNCT
ajst-20214	141	12	with	with	SCONJ
ajst-20214	141	13	the	the	DET
ajst-20214	141	14	momentum	momentum	NOUN
ajst-20214	141	15	parameter	parameter	NOUN
ajst-20214	141	16	set	set	VERB
ajst-20214	141	17	to	to	ADP
ajst-20214	141	18	0.937	0.937	NUM
ajst-20214	141	19	.	.	PUNCT
ajst-20214	142	1	the	the	DET
ajst-20214	142	2	initial	initial	ADJ
ajst-20214	142	3	learning	learning	NOUN
ajst-20214	142	4	rate	rate	NOUN
ajst-20214	142	5	(	(	PUNCT
ajst-20214	142	6	lr	lr	NOUN
ajst-20214	142	7	)	)	PUNCT
ajst-20214	142	8	was	be	AUX
ajst-20214	142	9	set	set	VERB
ajst-20214	142	10	to	to	ADP
ajst-20214	142	11	0.1	0.1	NUM
ajst-20214	142	12	,	,	PUNCT
ajst-20214	142	13	the	the	DET
ajst-20214	142	14	batch	batch	NOUN
ajst-20214	142	15	size	size	NOUN
ajst-20214	142	16	was	be	AUX
ajst-20214	142	17	32	32	NUM
ajst-20214	142	18	,	,	PUNCT
ajst-20214	142	19	the	the	DET
ajst-20214	142	20	input	input	NOUN
ajst-20214	142	21	image	image	NOUN
ajst-20214	142	22	size	size	NOUN
ajst-20214	142	23	was	be	AUX
ajst-20214	142	24	640	640	NUM
ajst-20214	142	25	*	*	NUM
ajst-20214	142	26	640	640	NUM
ajst-20214	142	27	,	,	PUNCT
ajst-20214	142	28	and	and	CCONJ
ajst-20214	142	29	the	the	DET
ajst-20214	142	30	number	number	NOUN
ajst-20214	142	31	of	of	ADP
ajst-20214	142	32	training	training	NOUN
ajst-20214	142	33	epochs	epoch	NOUN
ajst-20214	142	34	was	be	AUX
ajst-20214	142	35	300	300	NUM
ajst-20214	142	36	.	.	PUNCT
ajst-20214	143	1	to	to	PART
ajst-20214	143	2	achieve	achieve	VERB
ajst-20214	143	3	the	the	DET
ajst-20214	143	4	detection	detection	NOUN
ajst-20214	143	5	of	of	ADP
ajst-20214	143	6	open	open	ADJ
ajst-20214	143	7	and	and	CCONJ
ajst-20214	143	8	closed	closed	ADJ
ajst-20214	143	9	car	car	NOUN
ajst-20214	143	10	windows	window	NOUN
ajst-20214	143	11	in	in	ADP
ajst-20214	143	12	smart	smart	ADJ
ajst-20214	143	13	city	city	NOUN
ajst-20214	143	14	construction	construction	NOUN
ajst-20214	143	15	,	,	PUNCT
ajst-20214	143	16	a	a	DET
ajst-20214	143	17	custom	custom	ADV
ajst-20214	143	18	-	-	PUNCT
ajst-20214	143	19	made	make	VERB
ajst-20214	143	20	car	car	NOUN
ajst-20214	143	21	window	window	NOUN
ajst-20214	143	22	dataset	dataset	NOUN
ajst-20214	143	23	was	be	AUX
ajst-20214	143	24	created	create	VERB
ajst-20214	143	25	.	.	PUNCT
ajst-20214	144	1	this	this	DET
ajst-20214	144	2	dataset	dataset	NOUN
ajst-20214	144	3	consists	consist	VERB
ajst-20214	144	4	of	of	ADP
ajst-20214	144	5	four	four	NUM
ajst-20214	144	6	categories	category	NOUN
ajst-20214	144	7	:	:	PUNCT
ajst-20214	144	8	open	open	ADJ
ajst-20214	144	9	front	front	ADJ
ajst-20214	144	10	window	window	NOUN
ajst-20214	144	11	,	,	PUNCT
ajst-20214	144	12	closed	close	VERB
ajst-20214	144	13	front	front	ADJ
ajst-20214	144	14	window	window	NOUN
ajst-20214	144	15	,	,	PUNCT
ajst-20214	144	16	open	open	ADJ
ajst-20214	144	17	rear	rear	ADJ
ajst-20214	144	18	window	window	NOUN
ajst-20214	144	19	,	,	PUNCT
ajst-20214	144	20	and	and	CCONJ
ajst-20214	144	21	closed	close	VERB
ajst-20214	144	22	rear	rear	ADJ
ajst-20214	144	23	window	window	NOUN
ajst-20214	144	24	.	.	PUNCT
ajst-20214	145	1	the	the	DET
ajst-20214	145	2	dataset	dataset	NOUN
ajst-20214	145	3	contains	contain	VERB
ajst-20214	145	4	a	a	DET
ajst-20214	145	5	total	total	NOUN
ajst-20214	145	6	of	of	ADP
ajst-20214	145	7	10,869	10,869	NUM
ajst-20214	145	8	images	image	NOUN
ajst-20214	145	9	,	,	PUNCT
ajst-20214	145	10	with	with	ADP
ajst-20214	145	11	7,608	7,608	NUM
ajst-20214	145	12	images	image	NOUN
ajst-20214	145	13	in	in	ADP
ajst-20214	145	14	the	the	DET
ajst-20214	145	15	training	training	NOUN
ajst-20214	145	16	set	set	NOUN
ajst-20214	145	17	and	and	CCONJ
ajst-20214	145	18	3,261	3,261	NUM
ajst-20214	145	19	images	image	NOUN
ajst-20214	145	20	in	in	ADP
ajst-20214	145	21	the	the	DET
ajst-20214	145	22	test	test	NOUN
ajst-20214	145	23	set	set	VERB
ajst-20214	145	24	.	.	PUNCT
ajst-20214	146	1	185	185	NUM
ajst-20214	146	2	4.2	4.2	NUM
ajst-20214	146	3	.	.	PUNCT
ajst-20214	146	4	results	result	NOUN
ajst-20214	146	5	of	of	ADP
ajst-20214	146	6	channel	channel	NOUN
ajst-20214	146	7	pruning	prune	VERB
ajst-20214	146	8	experiments	experiment	NOUN
ajst-20214	146	9	.	.	PUNCT
ajst-20214	147	1	based	base	VERB
ajst-20214	147	2	on	on	ADP
ajst-20214	147	3	the	the	DET
ajst-20214	147	4	structured	structured	ADJ
ajst-20214	147	5	pruning	prune	VERB
ajst-20214	147	6	algorithm	algorithm	NOUN
ajst-20214	147	7	utilizing	utilize	VERB
ajst-20214	147	8	model	model	NOUN
ajst-20214	147	9	channel	channel	PROPN
ajst-20214	147	10	weights	weight	NOUN
ajst-20214	147	11	described	describe	VERB
ajst-20214	147	12	in	in	ADP
ajst-20214	147	13	section	section	NOUN
ajst-20214	147	14	3.2	3.2	NUM
ajst-20214	147	15	,	,	PUNCT
ajst-20214	147	16	channel	channel	NOUN
ajst-20214	147	17	pruning	pruning	NOUN
ajst-20214	147	18	was	be	AUX
ajst-20214	147	19	implemented	implement	VERB
ajst-20214	147	20	for	for	ADP
ajst-20214	147	21	the	the	DET
ajst-20214	147	22	yolov5	yolov5	NOUN
ajst-20214	147	23	object	object	NOUN
ajst-20214	147	24	detection	detection	NOUN
ajst-20214	147	25	model	model	NOUN
ajst-20214	147	26	.	.	PUNCT
ajst-20214	148	1	fig	fig	NOUN
ajst-20214	148	2	.	.	PUNCT
ajst-20214	149	1	4	4	NUM
ajst-20214	149	2	illustrates	illustrate	VERB
ajst-20214	149	3	the	the	DET
ajst-20214	149	4	impact	impact	NOUN
ajst-20214	149	5	of	of	ADP
ajst-20214	149	6	using	use	VERB
ajst-20214	149	7	different	different	ADJ
ajst-20214	149	8	pruning	pruning	NOUN
ajst-20214	149	9	rates	rate	NOUN
ajst-20214	149	10	on	on	ADP
ajst-20214	149	11	the	the	DET
ajst-20214	149	12	number	number	NOUN
ajst-20214	149	13	of	of	ADP
ajst-20214	149	14	parameters	parameter	NOUN
ajst-20214	149	15	,	,	PUNCT
ajst-20214	149	16	computational	computational	ADJ
ajst-20214	149	17	complexity	complexity	NOUN
ajst-20214	149	18	,	,	PUNCT
ajst-20214	149	19	and	and	CCONJ
ajst-20214	149	20	detection	detection	NOUN
ajst-20214	149	21	accuracy	accuracy	NOUN
ajst-20214	149	22	of	of	ADP
ajst-20214	149	23	the	the	DET
ajst-20214	149	24	yolov5	yolov5	NOUN
ajst-20214	149	25	model	model	NOUN
ajst-20214	149	26	.	.	PUNCT
ajst-20214	150	1	(	(	PUNCT
ajst-20214	150	2	a	a	X
ajst-20214	150	3	)	)	PUNCT
ajst-20214	150	4	trend	trend	NOUN
ajst-20214	150	5	of	of	ADP
ajst-20214	150	6	parameter	parameter	NOUN
ajst-20214	150	7	quantity	quantity	NOUN
ajst-20214	150	8	change	change	NOUN
ajst-20214	150	9	(	(	PUNCT
ajst-20214	150	10	b	b	NOUN
ajst-20214	150	11	)	)	PUNCT
ajst-20214	150	12	trend	trend	NOUN
ajst-20214	150	13	of	of	ADP
ajst-20214	150	14	computational	computational	ADJ
ajst-20214	150	15	complexity	complexity	NOUN
ajst-20214	150	16	change	change	NOUN
ajst-20214	150	17	(	(	PUNCT
ajst-20214	150	18	c	c	NOUN
ajst-20214	150	19	)	)	PUNCT
ajst-20214	150	20	trend	trend	NOUN
ajst-20214	150	21	of	of	ADP
ajst-20214	150	22	detection	detection	NOUN
ajst-20214	150	23	accuracy	accuracy	NOUN
ajst-20214	150	24	change	change	NOUN
ajst-20214	150	25	figure	figure	NOUN
ajst-20214	150	26	4	4	NUM
ajst-20214	150	27	.	.	PUNCT
ajst-20214	151	1	the	the	DET
ajst-20214	151	2	framework	framework	NOUN
ajst-20214	151	3	of	of	ADP
ajst-20214	151	4	knowledge	knowledge	NOUN
ajst-20214	151	5	distillation	distillation	NOUN
ajst-20214	151	6	algorithm	algorithm	NOUN
ajst-20214	151	7	as	as	SCONJ
ajst-20214	151	8	shown	show	VERB
ajst-20214	151	9	in	in	ADP
ajst-20214	151	10	fig	fig	NOUN
ajst-20214	151	11	.	.	PUNCT
ajst-20214	152	1	4	4	NUM
ajst-20214	152	2	,	,	PUNCT
ajst-20214	152	3	as	as	SCONJ
ajst-20214	152	4	the	the	DET
ajst-20214	152	5	pruning	prune	VERB
ajst-20214	152	6	rate	rate	NOUN
ajst-20214	152	7	continues	continue	VERB
ajst-20214	152	8	to	to	PART
ajst-20214	152	9	increase	increase	VERB
ajst-20214	152	10	,	,	PUNCT
ajst-20214	152	11	the	the	DET
ajst-20214	152	12	number	number	NOUN
ajst-20214	152	13	of	of	ADP
ajst-20214	152	14	parameters	parameter	NOUN
ajst-20214	152	15	and	and	CCONJ
ajst-20214	152	16	computational	computational	ADJ
ajst-20214	152	17	complexity	complexity	NOUN
ajst-20214	152	18	of	of	ADP
ajst-20214	152	19	the	the	DET
ajst-20214	152	20	yolov5	yolov5	NOUN
ajst-20214	152	21	model	model	NOUN
ajst-20214	152	22	decrease	decrease	NOUN
ajst-20214	152	23	accordingly	accordingly	ADV
ajst-20214	152	24	.	.	PUNCT
ajst-20214	153	1	when	when	SCONJ
ajst-20214	153	2	the	the	DET
ajst-20214	153	3	channel	channel	NOUN
ajst-20214	153	4	pruning	pruning	NOUN
ajst-20214	153	5	rate	rate	NOUN
ajst-20214	153	6	is	be	AUX
ajst-20214	153	7	less	less	ADJ
ajst-20214	153	8	than	than	ADP
ajst-20214	153	9	50	50	NUM
ajst-20214	153	10	%	%	NOUN
ajst-20214	153	11	,	,	PUNCT
ajst-20214	153	12	the	the	DET
ajst-20214	153	13	decrease	decrease	NOUN
ajst-20214	153	14	in	in	ADP
ajst-20214	153	15	detection	detection	NOUN
ajst-20214	153	16	accuracy	accuracy	NOUN
ajst-20214	153	17	is	be	AUX
ajst-20214	153	18	relatively	relatively	ADV
ajst-20214	153	19	small	small	ADJ
ajst-20214	153	20	.	.	PUNCT
ajst-20214	154	1	however	however	ADV
ajst-20214	154	2	,	,	PUNCT
ajst-20214	154	3	when	when	SCONJ
ajst-20214	154	4	the	the	DET
ajst-20214	154	5	channel	channel	NOUN
ajst-20214	154	6	pruning	prune	VERB
ajst-20214	154	7	rate	rate	NOUN
ajst-20214	154	8	exceeds	exceed	VERB
ajst-20214	154	9	50	50	NUM
ajst-20214	154	10	%	%	NOUN
ajst-20214	154	11	,	,	PUNCT
ajst-20214	154	12	the	the	DET
ajst-20214	154	13	detection	detection	NOUN
ajst-20214	154	14	accuracy	accuracy	NOUN
ajst-20214	154	15	begins	begin	VERB
ajst-20214	154	16	to	to	PART
ajst-20214	154	17	decline	decline	VERB
ajst-20214	154	18	rapidly	rapidly	ADV
ajst-20214	154	19	,	,	PUNCT
ajst-20214	154	20	and	and	CCONJ
ajst-20214	154	21	even	even	ADV
ajst-20214	154	22	after	after	ADP
ajst-20214	154	23	retraining	retrain	VERB
ajst-20214	154	24	and	and	CCONJ
ajst-20214	154	25	finetuning	finetuning	NOUN
ajst-20214	154	26	,	,	PUNCT
ajst-20214	154	27	the	the	DET
ajst-20214	154	28	accuracy	accuracy	NOUN
ajst-20214	154	29	can	can	AUX
ajst-20214	154	30	not	not	PART
ajst-20214	154	31	be	be	AUX
ajst-20214	154	32	restored	restore	VERB
ajst-20214	154	33	.	.	PUNCT
ajst-20214	155	1	therefore	therefore	ADV
ajst-20214	155	2	,	,	PUNCT
ajst-20214	155	3	in	in	ADP
ajst-20214	155	4	this	this	DET
ajst-20214	155	5	paper	paper	NOUN
ajst-20214	155	6	,	,	PUNCT
ajst-20214	155	7	a	a	DET
ajst-20214	155	8	pruning	prune	VERB
ajst-20214	155	9	rate	rate	NOUN
ajst-20214	155	10	of	of	ADP
ajst-20214	155	11	50	50	NUM
ajst-20214	155	12	%	%	NOUN
ajst-20214	155	13	is	be	AUX
ajst-20214	155	14	adopted	adopt	VERB
ajst-20214	155	15	for	for	ADP
ajst-20214	155	16	subsequent	subsequent	ADJ
ajst-20214	155	17	experiments	experiment	NOUN
ajst-20214	155	18	related	relate	VERB
ajst-20214	155	19	to	to	ADP
ajst-20214	155	20	knowledge	knowledge	NOUN
ajst-20214	155	21	distillation	distillation	NOUN
ajst-20214	155	22	.	.	PUNCT
ajst-20214	156	1	table	table	NOUN
ajst-20214	156	2	1	1	NUM
ajst-20214	156	3	compares	compare	VERB
ajst-20214	156	4	the	the	DET
ajst-20214	156	5	performance	performance	NOUN
ajst-20214	156	6	of	of	ADP
ajst-20214	156	7	the	the	DET
ajst-20214	156	8	yolov5s	yolov5s	PROPN
ajst-20214	156	9	model	model	NOUN
ajst-20214	156	10	before	before	ADV
ajst-20214	156	11	and	and	CCONJ
ajst-20214	156	12	after	after	ADP
ajst-20214	156	13	pruning	prune	VERB
ajst-20214	156	14	on	on	ADP
ajst-20214	156	15	the	the	DET
ajst-20214	156	16	custom	custom	ADV
ajst-20214	156	17	-	-	PUNCT
ajst-20214	156	18	made	make	VERB
ajst-20214	156	19	car	car	NOUN
ajst-20214	156	20	window	window	NOUN
ajst-20214	156	21	state	state	NOUN
ajst-20214	156	22	dataset	dataset	NOUN
ajst-20214	156	23	.	.	PUNCT
ajst-20214	157	1	table	table	NOUN
ajst-20214	157	2	1	1	NUM
ajst-20214	157	3	.	.	PUNCT
ajst-20214	157	4	comparison	comparison	NOUN
ajst-20214	157	5	of	of	ADP
ajst-20214	157	6	yolov5	yolov5	NOUN
ajst-20214	157	7	model	model	NOUN
ajst-20214	157	8	pruning	prune	VERB
ajst-20214	157	9	performance	performance	NOUN
ajst-20214	157	10	model	model	NOUN
ajst-20214	157	11	map50	map50	PROPN
ajst-20214	157	12	gflops	gflop	NOUN
ajst-20214	157	13	params	param	VERB
ajst-20214	157	14	/	/	SYM
ajst-20214	157	15	m	m	VERB
ajst-20214	157	16	yolov5	yolov5	NOUN
ajst-20214	157	17	0.953	0.953	NUM
ajst-20214	157	18	15.8	15.8	NUM
ajst-20214	157	19	7.02	7.02	NUM
ajst-20214	157	20	50	50	NUM
ajst-20214	157	21	%	%	NOUN
ajst-20214	157	22	channel	channel	NOUN
ajst-20214	157	23	pruning	prune	VERB
ajst-20214	157	24	0.899	0.899	NUM
ajst-20214	157	25	8.8	8.8	NUM
ajst-20214	157	26	4.11	4.11	NUM
ajst-20214	157	27	according	accord	VERB
ajst-20214	157	28	to	to	ADP
ajst-20214	157	29	table	table	NOUN
ajst-20214	157	30	1	1	NUM
ajst-20214	157	31	,	,	PUNCT
ajst-20214	157	32	after	after	ADP
ajst-20214	157	33	applying	apply	VERB
ajst-20214	157	34	channel	channel	NOUN
ajst-20214	157	35	pruning	prune	VERB
ajst-20214	157	36	to	to	ADP
ajst-20214	157	37	the	the	DET
ajst-20214	157	38	yolov5	yolov5	NOUN
ajst-20214	157	39	model	model	NOUN
ajst-20214	157	40	,	,	PUNCT
ajst-20214	157	41	the	the	DET
ajst-20214	157	42	map50	map50	PROPN
ajst-20214	157	43	decreased	decrease	VERB
ajst-20214	157	44	by	by	ADP
ajst-20214	157	45	0.053	0.053	NUM
ajst-20214	157	46	,	,	PUNCT
ajst-20214	157	47	while	while	SCONJ
ajst-20214	157	48	the	the	DET
ajst-20214	157	49	number	number	NOUN
ajst-20214	157	50	of	of	ADP
ajst-20214	157	51	parameters	parameter	NOUN
ajst-20214	157	52	and	and	CCONJ
ajst-20214	157	53	computational	computational	ADJ
ajst-20214	157	54	complexity	complexity	NOUN
ajst-20214	157	55	decreased	decrease	VERB
ajst-20214	157	56	by	by	ADP
ajst-20214	157	57	41.5	41.5	NUM
ajst-20214	157	58	%	%	NOUN
ajst-20214	157	59	and	and	CCONJ
ajst-20214	157	60	44.3	44.3	NUM
ajst-20214	157	61	%	%	NOUN
ajst-20214	157	62	,	,	PUNCT
ajst-20214	157	63	respectively	respectively	ADV
ajst-20214	157	64	.	.	PUNCT
ajst-20214	158	1	4.3	4.3	NUM
ajst-20214	158	2	.	.	PUNCT
ajst-20214	158	3	results	result	NOUN
ajst-20214	158	4	and	and	CCONJ
ajst-20214	158	5	analysis	analysis	NOUN
ajst-20214	158	6	of	of	ADP
ajst-20214	158	7	logical	logical	ADJ
ajst-20214	158	8	distillation	distillation	NOUN
ajst-20214	158	9	experiments	experiment	NOUN
ajst-20214	158	10	.	.	PUNCT
ajst-20214	159	1	the	the	DET
ajst-20214	159	2	results	result	NOUN
ajst-20214	159	3	of	of	ADP
ajst-20214	159	4	fine	fine	ADV
ajst-20214	159	5	-	-	PUNCT
ajst-20214	159	6	tuning	tune	VERB
ajst-20214	159	7	the	the	DET
ajst-20214	159	8	pruned	pruned	ADJ
ajst-20214	159	9	yolov5	yolov5	NOUN
ajst-20214	159	10	model	model	NOUN
ajst-20214	159	11	through	through	ADP
ajst-20214	159	12	retraining	retrain	VERB
ajst-20214	159	13	and	and	CCONJ
ajst-20214	159	14	logical	logical	ADJ
ajst-20214	159	15	distillation	distillation	NOUN
ajst-20214	159	16	-	-	PUNCT
ajst-20214	159	17	based	base	VERB
ajst-20214	159	18	fine	fine	ADV
ajst-20214	159	19	-	-	PUNCT
ajst-20214	159	20	tuning	tuning	NOUN
ajst-20214	159	21	are	be	AUX
ajst-20214	159	22	presented	present	VERB
ajst-20214	159	23	in	in	ADP
ajst-20214	159	24	table	table	NOUN
ajst-20214	159	25	2	2	NUM
ajst-20214	159	26	.	.	PUNCT
ajst-20214	159	27	table	table	NOUN
ajst-20214	159	28	2	2	NUM
ajst-20214	159	29	.	.	PUNCT
ajst-20214	159	30	comparison	comparison	NOUN
ajst-20214	159	31	of	of	ADP
ajst-20214	159	32	fine	fine	ADV
ajst-20214	159	33	-	-	PUNCT
ajst-20214	159	34	tuning	tune	VERB
ajst-20214	159	35	performance	performance	NOUN
ajst-20214	159	36	for	for	ADP
ajst-20214	159	37	pruned	prune	VERB
ajst-20214	159	38	models	model	NOUN
ajst-20214	159	39	model	model	VERB
ajst-20214	159	40	map50	map50	PROPN
ajst-20214	159	41	gflops	gflop	NOUN
ajst-20214	159	42	params	param	VERB
ajst-20214	159	43	/	/	SYM
ajst-20214	159	44	m	m	VERB
ajst-20214	159	45	50	50	NUM
ajst-20214	159	46	%	%	NOUN
ajst-20214	159	47	channel	channel	NOUN
ajst-20214	159	48	pruning	prune	VERB
ajst-20214	159	49	for	for	ADP
ajst-20214	159	50	yolov5	yolov5	NOUN
ajst-20214	159	51	0.901	0.901	NUM
ajst-20214	159	52	8.8	8.8	NUM
ajst-20214	159	53	4.11	4.11	NUM
ajst-20214	159	54	retraining	retrain	VERB
ajst-20214	159	55	fine	fine	ADV
ajst-20214	159	56	-	-	PUNCT
ajst-20214	159	57	tuning	tune	VERB
ajst-20214	159	58	0.945	0.945	NUM
ajst-20214	159	59	8.8	8.8	NUM
ajst-20214	159	60	4.11	4.11	NUM
ajst-20214	159	61	logical	logical	ADJ
ajst-20214	159	62	distillation	distillation	NOUN
ajst-20214	159	63	fine	fine	ADV
ajst-20214	159	64	-	-	PUNCT
ajst-20214	159	65	tuning	tune	VERB
ajst-20214	159	66	0.950	0.950	NUM
ajst-20214	159	67	8.8	8.8	NUM
ajst-20214	159	68	4.11	4.11	NUM
ajst-20214	159	69	according	accord	VERB
ajst-20214	159	70	to	to	ADP
ajst-20214	159	71	table	table	NOUN
ajst-20214	159	72	2	2	NUM
ajst-20214	159	73	,	,	PUNCT
ajst-20214	159	74	after	after	ADP
ajst-20214	159	75	fine	fine	ADV
ajst-20214	159	76	-	-	PUNCT
ajst-20214	159	77	tuning	tuning	NOUN
ajst-20214	159	78	through	through	ADP
ajst-20214	159	79	retraining	retrain	VERB
ajst-20214	159	80	,	,	PUNCT
ajst-20214	159	81	the	the	DET
ajst-20214	159	82	detection	detection	NOUN
ajst-20214	159	83	accuracy	accuracy	NOUN
ajst-20214	159	84	of	of	ADP
ajst-20214	159	85	the	the	DET
ajst-20214	159	86	model	model	NOUN
ajst-20214	159	87	improved	improve	VERB
ajst-20214	159	88	by	by	ADP
ajst-20214	159	89	0.044	0.044	NUM
ajst-20214	159	90	.	.	PUNCT
ajst-20214	160	1	when	when	SCONJ
ajst-20214	160	2	using	use	VERB
ajst-20214	160	3	logical	logical	ADJ
ajst-20214	160	4	distillation	distillation	NOUN
ajst-20214	160	5	for	for	ADP
ajst-20214	160	6	fine	fine	ADV
ajst-20214	160	7	-	-	PUNCT
ajst-20214	160	8	tuning	tuning	NOUN
ajst-20214	160	9	,	,	PUNCT
ajst-20214	160	10	the	the	DET
ajst-20214	160	11	detection	detection	NOUN
ajst-20214	160	12	accuracy	accuracy	NOUN
ajst-20214	160	13	increased	increase	VERB
ajst-20214	160	14	by	by	ADP
ajst-20214	160	15	0.049	0.049	NUM
ajst-20214	160	16	.	.	PUNCT
ajst-20214	161	1	compared	compare	VERB
ajst-20214	161	2	to	to	ADP
ajst-20214	161	3	the	the	DET
ajst-20214	161	4	ordinary	ordinary	ADJ
ajst-20214	161	5	fine	fine	ADJ
ajst-20214	161	6	186	186	NUM
ajst-20214	161	7	tuning	tuning	NOUN
ajst-20214	161	8	method	method	NOUN
ajst-20214	161	9	,	,	PUNCT
ajst-20214	161	10	the	the	DET
ajst-20214	161	11	yolov5	yolov5	NOUN
ajst-20214	161	12	model	model	NOUN
ajst-20214	161	13	achieved	achieve	VERB
ajst-20214	161	14	a	a	DET
ajst-20214	161	15	0.5	0.5	NUM
ajst-20214	161	16	%	%	NOUN
ajst-20214	161	17	increase	increase	NOUN
ajst-20214	161	18	in	in	ADP
ajst-20214	161	19	accuracy	accuracy	NOUN
ajst-20214	161	20	when	when	SCONJ
ajst-20214	161	21	fine	fine	ADV
ajst-20214	161	22	-	-	PUNCT
ajst-20214	161	23	tuned	tune	VERB
ajst-20214	161	24	using	use	VERB
ajst-20214	161	25	logical	logical	ADJ
ajst-20214	161	26	distillation	distillation	NOUN
ajst-20214	161	27	.	.	PUNCT
ajst-20214	162	1	compared	compare	VERB
ajst-20214	162	2	to	to	ADP
ajst-20214	162	3	the	the	DET
ajst-20214	162	4	unpruned	unpruned	ADJ
ajst-20214	162	5	yolov5	yolov5	NOUN
ajst-20214	162	6	model	model	NOUN
ajst-20214	162	7	,	,	PUNCT
ajst-20214	162	8	the	the	DET
ajst-20214	162	9	pruned	prune	VERB
ajst-20214	162	10	model	model	NOUN
ajst-20214	162	11	significantly	significantly	ADV
ajst-20214	162	12	reduces	reduce	VERB
ajst-20214	162	13	the	the	DET
ajst-20214	162	14	number	number	NOUN
ajst-20214	162	15	of	of	ADP
ajst-20214	162	16	parameters	parameter	NOUN
ajst-20214	162	17	while	while	SCONJ
ajst-20214	162	18	only	only	ADV
ajst-20214	162	19	sacrificing	sacrifice	VERB
ajst-20214	162	20	0.3	0.3	NUM
ajst-20214	162	21	%	%	NOUN
ajst-20214	162	22	of	of	ADP
ajst-20214	162	23	detection	detection	NOUN
ajst-20214	162	24	accuracy	accuracy	NOUN
ajst-20214	162	25	,	,	PUNCT
ajst-20214	162	26	making	make	VERB
ajst-20214	162	27	it	it	PRON
ajst-20214	162	28	lighter	light	ADJ
ajst-20214	162	29	and	and	CCONJ
ajst-20214	162	30	reducing	reduce	VERB
ajst-20214	162	31	the	the	DET
ajst-20214	162	32	storage	storage	NOUN
ajst-20214	162	33	space	space	NOUN
ajst-20214	162	34	requirements	requirement	NOUN
ajst-20214	162	35	.	.	PUNCT
ajst-20214	163	1	fig	fig	NOUN
ajst-20214	163	2	.	.	PUNCT
ajst-20214	164	1	5	5	NUM
ajst-20214	164	2	demonstrates	demonstrate	VERB
ajst-20214	164	3	the	the	DET
ajst-20214	164	4	detection	detection	NOUN
ajst-20214	164	5	results	result	NOUN
ajst-20214	164	6	of	of	ADP
ajst-20214	164	7	the	the	DET
ajst-20214	164	8	optimized	optimize	VERB
ajst-20214	164	9	model	model	NOUN
ajst-20214	164	10	.	.	PUNCT
ajst-20214	165	1	figure	figure	NOUN
ajst-20214	165	2	5	5	NUM
ajst-20214	165	3	.	.	PUNCT
ajst-20214	165	4	model	model	NOUN
ajst-20214	165	5	detection	detection	NOUN
ajst-20214	165	6	results	result	VERB
ajst-20214	165	7	5	5	NUM
ajst-20214	165	8	.	.	X
ajst-20214	166	1	summary	summary	NOUN
ajst-20214	166	2	to	to	PART
ajst-20214	166	3	reduce	reduce	VERB
ajst-20214	166	4	model	model	NOUN
ajst-20214	166	5	complexity	complexity	NOUN
ajst-20214	166	6	and	and	CCONJ
ajst-20214	166	7	improve	improve	VERB
ajst-20214	166	8	inference	inference	NOUN
ajst-20214	166	9	speed	speed	NOUN
ajst-20214	166	10	,	,	PUNCT
ajst-20214	166	11	this	this	DET
ajst-20214	166	12	paper	paper	NOUN
ajst-20214	166	13	proposes	propose	VERB
ajst-20214	166	14	a	a	DET
ajst-20214	166	15	lightweight	lightweight	ADJ
ajst-20214	166	16	object	object	NOUN
ajst-20214	166	17	detection	detection	NOUN
ajst-20214	166	18	compression	compression	NOUN
ajst-20214	166	19	method	method	NOUN
ajst-20214	166	20	.	.	PUNCT
ajst-20214	167	1	first	first	ADV
ajst-20214	167	2	,	,	PUNCT
ajst-20214	167	3	a	a	DET
ajst-20214	167	4	structured	structured	ADJ
ajst-20214	167	5	pruning	pruning	NOUN
ajst-20214	167	6	approach	approach	NOUN
ajst-20214	167	7	based	base	VERB
ajst-20214	167	8	on	on	ADP
ajst-20214	167	9	channel	channel	NOUN
ajst-20214	167	10	weights	weight	NOUN
ajst-20214	167	11	is	be	AUX
ajst-20214	167	12	employed	employ	VERB
ajst-20214	167	13	to	to	ADP
ajst-20214	167	14	prune	prune	NOUN
ajst-20214	167	15	channels	channel	NOUN
ajst-20214	167	16	with	with	ADP
ajst-20214	167	17	lower	low	ADJ
ajst-20214	167	18	weights	weight	NOUN
ajst-20214	167	19	and	and	CCONJ
ajst-20214	167	20	minimal	minimal	ADJ
ajst-20214	167	21	impact	impact	NOUN
ajst-20214	167	22	on	on	ADP
ajst-20214	167	23	the	the	DET
ajst-20214	167	24	network	network	NOUN
ajst-20214	167	25	model	model	NOUN
ajst-20214	167	26	in	in	ADP
ajst-20214	167	27	the	the	DET
ajst-20214	167	28	yolov5	yolov5	NOUN
ajst-20214	167	29	model	model	NOUN
ajst-20214	167	30	,	,	PUNCT
ajst-20214	167	31	thereby	thereby	ADV
ajst-20214	167	32	reducing	reduce	VERB
ajst-20214	167	33	the	the	DET
ajst-20214	167	34	number	number	NOUN
ajst-20214	167	35	of	of	ADP
ajst-20214	167	36	parameters	parameter	NOUN
ajst-20214	167	37	and	and	CCONJ
ajst-20214	167	38	computational	computational	ADJ
ajst-20214	167	39	complexity	complexity	NOUN
ajst-20214	167	40	.	.	PUNCT
ajst-20214	168	1	although	although	SCONJ
ajst-20214	168	2	the	the	DET
ajst-20214	168	3	detection	detection	NOUN
ajst-20214	168	4	accuracy	accuracy	NOUN
ajst-20214	168	5	of	of	ADP
ajst-20214	168	6	the	the	DET
ajst-20214	168	7	model	model	NOUN
ajst-20214	168	8	slightly	slightly	ADV
ajst-20214	168	9	decreases	decrease	VERB
ajst-20214	168	10	after	after	ADP
ajst-20214	168	11	channel	channel	NOUN
ajst-20214	168	12	pruning	pruning	NOUN
ajst-20214	168	13	,	,	PUNCT
ajst-20214	168	14	fine	fine	ADV
ajst-20214	168	15	-	-	PUNCT
ajst-20214	168	16	tuning	tuning	NOUN
ajst-20214	168	17	based	base	VERB
ajst-20214	168	18	on	on	ADP
ajst-20214	168	19	logical	logical	ADJ
ajst-20214	168	20	distillation	distillation	NOUN
ajst-20214	168	21	is	be	AUX
ajst-20214	168	22	then	then	ADV
ajst-20214	168	23	adopted	adopt	VERB
ajst-20214	168	24	to	to	PART
ajst-20214	168	25	recover	recover	VERB
ajst-20214	168	26	the	the	DET
ajst-20214	168	27	detection	detection	NOUN
ajst-20214	168	28	accuracy	accuracy	NOUN
ajst-20214	168	29	lost	lose	VERB
ajst-20214	168	30	due	due	ADJ
ajst-20214	168	31	to	to	ADP
ajst-20214	168	32	pruning	prune	VERB
ajst-20214	168	33	.	.	PUNCT
ajst-20214	169	1	in	in	ADP
ajst-20214	169	2	this	this	DET
ajst-20214	169	3	process	process	NOUN
ajst-20214	169	4	,	,	PUNCT
ajst-20214	169	5	the	the	DET
ajst-20214	169	6	unpruned	unpruned	ADJ
ajst-20214	169	7	yolov5	yolov5	NOUN
ajst-20214	169	8	model	model	NOUN
ajst-20214	169	9	serves	serve	VERB
ajst-20214	169	10	as	as	ADP
ajst-20214	169	11	the	the	DET
ajst-20214	169	12	teacher	teacher	NOUN
ajst-20214	169	13	model	model	NOUN
ajst-20214	169	14	,	,	PUNCT
ajst-20214	169	15	while	while	SCONJ
ajst-20214	169	16	the	the	DET
ajst-20214	169	17	pruned	pruned	ADJ
ajst-20214	169	18	yolov5	yolov5	NOUN
ajst-20214	169	19	model	model	NOUN
ajst-20214	169	20	serves	serve	VERB
ajst-20214	169	21	as	as	ADP
ajst-20214	169	22	the	the	DET
ajst-20214	169	23	student	student	NOUN
ajst-20214	169	24	model	model	NOUN
ajst-20214	169	25	.	.	PUNCT
ajst-20214	170	1	experimental	experimental	ADJ
ajst-20214	170	2	results	result	NOUN
ajst-20214	170	3	show	show	VERB
ajst-20214	170	4	that	that	SCONJ
ajst-20214	170	5	the	the	DET
ajst-20214	170	6	pruned	pruned	ADJ
ajst-20214	170	7	yolov5	yolov5	NOUN
ajst-20214	170	8	model	model	NOUN
ajst-20214	170	9	achieves	achieve	VERB
ajst-20214	170	10	a	a	DET
ajst-20214	170	11	41.5	41.5	NUM
ajst-20214	170	12	%	%	NOUN
ajst-20214	170	13	reduction	reduction	NOUN
ajst-20214	170	14	in	in	ADP
ajst-20214	170	15	the	the	DET
ajst-20214	170	16	number	number	NOUN
ajst-20214	170	17	of	of	ADP
ajst-20214	170	18	parameters	parameter	NOUN
ajst-20214	170	19	and	and	CCONJ
ajst-20214	170	20	a	a	DET
ajst-20214	170	21	44.3	44.3	NUM
ajst-20214	170	22	%	%	NOUN
ajst-20214	170	23	reduction	reduction	NOUN
ajst-20214	170	24	in	in	ADP
ajst-20214	170	25	computational	computational	ADJ
ajst-20214	170	26	complexity	complexity	NOUN
ajst-20214	170	27	compared	compare	VERB
ajst-20214	170	28	to	to	ADP
ajst-20214	170	29	the	the	DET
ajst-20214	170	30	unpruned	unpruned	ADJ
ajst-20214	170	31	model	model	NOUN
ajst-20214	170	32	.	.	PUNCT
ajst-20214	171	1	after	after	ADP
ajst-20214	171	2	fine	fine	ADV
ajst-20214	171	3	-	-	PUNCT
ajst-20214	171	4	tuning	tuning	NOUN
ajst-20214	171	5	,	,	PUNCT
ajst-20214	171	6	the	the	DET
ajst-20214	171	7	detection	detection	NOUN
ajst-20214	171	8	accuracy	accuracy	NOUN
ajst-20214	171	9	of	of	ADP
ajst-20214	171	10	the	the	DET
ajst-20214	171	11	pruned	prune	VERB
ajst-20214	171	12	model	model	NOUN
ajst-20214	171	13	is	be	AUX
ajst-20214	171	14	comparable	comparable	ADJ
ajst-20214	171	15	to	to	ADP
ajst-20214	171	16	that	that	PRON
ajst-20214	171	17	of	of	ADP
ajst-20214	171	18	the	the	DET
ajst-20214	171	19	unpruned	unpruned	ADJ
ajst-20214	171	20	model	model	NOUN
ajst-20214	171	21	.	.	PUNCT
ajst-20214	172	1	in	in	ADP
ajst-20214	172	2	future	future	ADJ
ajst-20214	172	3	work	work	NOUN
ajst-20214	172	4	,	,	PUNCT
ajst-20214	172	5	we	we	PRON
ajst-20214	172	6	will	will	AUX
ajst-20214	172	7	also	also	ADV
ajst-20214	172	8	consider	consider	VERB
ajst-20214	172	9	the	the	DET
ajst-20214	172	10	differences	difference	NOUN
ajst-20214	172	11	in	in	ADP
ajst-20214	172	12	feature	feature	NOUN
ajst-20214	172	13	representations	representation	NOUN
ajst-20214	172	14	between	between	ADP
ajst-20214	172	15	the	the	DET
ajst-20214	172	16	intermediate	intermediate	ADJ
ajst-20214	172	17	layers	layer	NOUN
ajst-20214	172	18	of	of	ADP
ajst-20214	172	19	the	the	DET
ajst-20214	172	20	student	student	NOUN
ajst-20214	172	21	and	and	CCONJ
ajst-20214	172	22	teacher	teacher	NOUN
ajst-20214	172	23	models	model	NOUN
ajst-20214	172	24	to	to	PART
ajst-20214	172	25	further	far	ADV
ajst-20214	172	26	improve	improve	VERB
ajst-20214	172	27	the	the	DET
ajst-20214	172	28	knowledge	knowledge	NOUN
ajst-20214	172	29	distillation	distillation	NOUN
ajst-20214	172	30	algorithm	algorithm	NOUN
ajst-20214	172	31	framework	framework	NOUN
ajst-20214	172	32	.	.	PUNCT
ajst-20214	173	1	references	reference	NOUN
ajst-20214	173	2	[	[	X
ajst-20214	173	3	1	1	NUM
ajst-20214	173	4	]	]	X
ajst-20214	173	5	girshick	girshick	PROPN
ajst-20214	173	6	,	,	PUNCT
ajst-20214	173	7	r.	r.	PROPN
ajst-20214	173	8	,	,	PUNCT
ajst-20214	173	9	donahue	donahue	PROPN
ajst-20214	173	10	,	,	PUNCT
ajst-20214	173	11	j.	j.	PROPN
ajst-20214	173	12	,	,	PUNCT
ajst-20214	173	13	darrell	darrell	PROPN
ajst-20214	173	14	,	,	PUNCT
ajst-20214	173	15	t.	t.	PROPN
ajst-20214	173	16	,	,	PUNCT
ajst-20214	173	17	&	&	CCONJ
ajst-20214	173	18	malik	malik	PROPN
ajst-20214	173	19	,	,	PUNCT
ajst-20214	173	20	j.	j.	PROPN
ajst-20214	173	21	(	(	PUNCT
ajst-20214	173	22	2014	2014	NUM
ajst-20214	173	23	)	)	PUNCT
ajst-20214	173	24	.	.	PUNCT
ajst-20214	174	1	rich	rich	ADJ
ajst-20214	174	2	feature	feature	NOUN
ajst-20214	174	3	hierarchies	hierarchy	NOUN
ajst-20214	174	4	for	for	ADP
ajst-20214	174	5	accurate	accurate	ADJ
ajst-20214	174	6	object	object	NOUN
ajst-20214	174	7	detection	detection	NOUN
ajst-20214	174	8	and	and	CCONJ
ajst-20214	174	9	semantic	semantic	ADJ
ajst-20214	174	10	segmentation	segmentation	NOUN
ajst-20214	174	11	.	.	PUNCT
ajst-20214	175	1	in	in	ADP
ajst-20214	175	2	proceedings	proceeding	NOUN
ajst-20214	175	3	of	of	ADP
ajst-20214	175	4	the	the	DET
ajst-20214	175	5	ieee	ieee	NOUN
ajst-20214	175	6	conference	conference	NOUN
ajst-20214	175	7	on	on	ADP
ajst-20214	175	8	computer	computer	NOUN
ajst-20214	175	9	vision	vision	NOUN
ajst-20214	175	10	and	and	CCONJ
ajst-20214	175	11	pattern	pattern	NOUN
ajst-20214	175	12	recognition	recognition	NOUN
ajst-20214	175	13	(	(	PUNCT
ajst-20214	175	14	pp	pp	ADJ
ajst-20214	175	15	.	.	PUNCT
ajst-20214	176	1	580	580	NUM
ajst-20214	176	2	-	-	SYM
ajst-20214	176	3	587	587	NUM
ajst-20214	176	4	)	)	PUNCT
ajst-20214	176	5	.	.	PUNCT
ajst-20214	177	1	[	[	X
ajst-20214	177	2	2	2	NUM
ajst-20214	177	3	]	]	X
ajst-20214	177	4	girshick	girshick	PROPN
ajst-20214	177	5	,	,	PUNCT
ajst-20214	177	6	r.	r.	PROPN
ajst-20214	177	7	(	(	PUNCT
ajst-20214	177	8	2015	2015	NUM
ajst-20214	177	9	)	)	PUNCT
ajst-20214	177	10	.	.	PUNCT
ajst-20214	178	1	fast	fast	ADJ
ajst-20214	178	2	r	r	NOUN
ajst-20214	178	3	-	-	PUNCT
ajst-20214	178	4	cnn	cnn	NOUN
ajst-20214	178	5	.	.	PUNCT
ajst-20214	179	1	in	in	ADP
ajst-20214	179	2	proceedings	proceeding	NOUN
ajst-20214	179	3	of	of	ADP
ajst-20214	179	4	the	the	DET
ajst-20214	179	5	ieee	ieee	NOUN
ajst-20214	179	6	international	international	PROPN
ajst-20214	179	7	conference	conference	NOUN
ajst-20214	179	8	on	on	ADP
ajst-20214	179	9	computer	computer	NOUN
ajst-20214	179	10	vision	vision	NOUN
ajst-20214	179	11	(	(	PUNCT
ajst-20214	179	12	pp	pp	ADJ
ajst-20214	179	13	.	.	PUNCT
ajst-20214	179	14	1440	1440	NUM
ajst-20214	179	15	-	-	SYM
ajst-20214	179	16	1448	1448	NUM
ajst-20214	179	17	)	)	PUNCT
ajst-20214	179	18	.	.	PUNCT
ajst-20214	180	1	[	[	X
ajst-20214	180	2	3	3	X
ajst-20214	180	3	]	]	X
ajst-20214	180	4	ren	ren	PROPN
ajst-20214	180	5	,	,	PUNCT
ajst-20214	180	6	s.	s.	PROPN
ajst-20214	180	7	,	,	PUNCT
ajst-20214	180	8	he	he	PRON
ajst-20214	180	9	,	,	PUNCT
ajst-20214	180	10	k.	k.	PROPN
ajst-20214	180	11	,	,	PUNCT
ajst-20214	180	12	girshick	girshick	PROPN
ajst-20214	180	13	,	,	PUNCT
ajst-20214	180	14	r.	r.	PROPN
ajst-20214	180	15	,	,	PUNCT
ajst-20214	180	16	&	&	CCONJ
ajst-20214	180	17	sun	sun	PROPN
ajst-20214	180	18	,	,	PUNCT
ajst-20214	180	19	j.	j.	PROPN
ajst-20214	180	20	(	(	PUNCT
ajst-20214	180	21	2015	2015	NUM
ajst-20214	180	22	)	)	PUNCT
ajst-20214	180	23	.	.	PUNCT
ajst-20214	181	1	faster	fast	ADV
ajst-20214	181	2	r	r	X
ajst-20214	181	3	-	-	PUNCT
ajst-20214	181	4	cnn	cnn	NOUN
ajst-20214	181	5	:	:	PUNCT
ajst-20214	181	6	towards	towards	ADP
ajst-20214	181	7	real	real	ADJ
ajst-20214	181	8	-	-	PUNCT
ajst-20214	181	9	time	time	NOUN
ajst-20214	181	10	object	object	NOUN
ajst-20214	181	11	detection	detection	NOUN
ajst-20214	181	12	with	with	ADP
ajst-20214	181	13	region	region	NOUN
ajst-20214	181	14	proposal	proposal	NOUN
ajst-20214	181	15	networks	network	NOUN
ajst-20214	181	16	.	.	PUNCT
ajst-20214	182	1	advances	advance	NOUN
ajst-20214	182	2	in	in	ADP
ajst-20214	182	3	neural	neural	ADJ
ajst-20214	182	4	information	information	NOUN
ajst-20214	182	5	processing	processing	NOUN
ajst-20214	182	6	systems	system	NOUN
ajst-20214	182	7	,	,	PUNCT
ajst-20214	182	8	28	28	NUM
ajst-20214	182	9	.	.	PUNCT
ajst-20214	183	1	[	[	X
ajst-20214	183	2	4	4	NUM
ajst-20214	183	3	]	]	X
ajst-20214	183	4	redmon	redmon	PROPN
ajst-20214	183	5	,	,	PUNCT
ajst-20214	183	6	j.	j.	PROPN
ajst-20214	183	7	,	,	PUNCT
ajst-20214	183	8	divvala	divvala	PROPN
ajst-20214	183	9	,	,	PUNCT
ajst-20214	183	10	s.	s.	PROPN
ajst-20214	183	11	,	,	PUNCT
ajst-20214	183	12	girshick	girshick	PROPN
ajst-20214	183	13	,	,	PUNCT
ajst-20214	183	14	r.	r.	PROPN
ajst-20214	183	15	,	,	PUNCT
ajst-20214	183	16	&	&	CCONJ
ajst-20214	183	17	farhadi	farhadi	PROPN
ajst-20214	183	18	,	,	PUNCT
ajst-20214	183	19	a.	a.	NOUN
ajst-20214	183	20	(	(	PUNCT
ajst-20214	183	21	2016	2016	NUM
ajst-20214	183	22	)	)	PUNCT
ajst-20214	183	23	.	.	PUNCT
ajst-20214	184	1	you	you	PRON
ajst-20214	184	2	only	only	ADV
ajst-20214	184	3	look	look	VERB
ajst-20214	184	4	once	once	ADV
ajst-20214	184	5	:	:	PUNCT
ajst-20214	184	6	unified	unified	ADJ
ajst-20214	184	7	,	,	PUNCT
ajst-20214	184	8	real	real	ADJ
ajst-20214	184	9	-	-	PUNCT
ajst-20214	184	10	time	time	NOUN
ajst-20214	184	11	object	object	NOUN
ajst-20214	184	12	detection	detection	NOUN
ajst-20214	184	13	.	.	PUNCT
ajst-20214	185	1	in	in	ADP
ajst-20214	185	2	proceedings	proceeding	NOUN
ajst-20214	185	3	of	of	ADP
ajst-20214	185	4	the	the	DET
ajst-20214	185	5	ieee	ieee	NOUN
ajst-20214	185	6	conference	conference	NOUN
ajst-20214	185	7	on	on	ADP
ajst-20214	185	8	computer	computer	NOUN
ajst-20214	185	9	vision	vision	NOUN
ajst-20214	185	10	and	and	CCONJ
ajst-20214	185	11	pattern	pattern	NOUN
ajst-20214	185	12	recognition	recognition	NOUN
ajst-20214	185	13	(	(	PUNCT
ajst-20214	185	14	pp	pp	ADJ
ajst-20214	185	15	.	.	PUNCT
ajst-20214	186	1	779	779	NUM
ajst-20214	186	2	-	-	SYM
ajst-20214	186	3	788	788	NUM
ajst-20214	186	4	)	)	PUNCT
ajst-20214	186	5	.	.	PUNCT
ajst-20214	187	1	[	[	X
ajst-20214	187	2	5	5	NUM
ajst-20214	187	3	]	]	X
ajst-20214	187	4	redmon	redmon	PROPN
ajst-20214	187	5	,	,	PUNCT
ajst-20214	187	6	j.	j.	PROPN
ajst-20214	187	7	,	,	PUNCT
ajst-20214	187	8	&	&	CCONJ
ajst-20214	187	9	farhadi	farhadi	PROPN
ajst-20214	187	10	,	,	PUNCT
ajst-20214	187	11	a.	a.	NOUN
ajst-20214	187	12	(	(	PUNCT
ajst-20214	187	13	2017	2017	NUM
ajst-20214	187	14	)	)	PUNCT
ajst-20214	187	15	.	.	PUNCT
ajst-20214	188	1	yolo9000	yolo9000	PROPN
ajst-20214	188	2	:	:	PUNCT
ajst-20214	188	3	better	well	ADJ
ajst-20214	188	4	,	,	PUNCT
ajst-20214	188	5	faster	fast	ADJ
ajst-20214	188	6	,	,	PUNCT
ajst-20214	188	7	stronger	strong	ADJ
ajst-20214	188	8	.	.	PUNCT
ajst-20214	189	1	in	in	ADP
ajst-20214	189	2	proceedings	proceeding	NOUN
ajst-20214	189	3	of	of	ADP
ajst-20214	189	4	the	the	DET
ajst-20214	189	5	ieee	ieee	NOUN
ajst-20214	189	6	conference	conference	NOUN
ajst-20214	189	7	on	on	ADP
ajst-20214	189	8	computer	computer	NOUN
ajst-20214	189	9	vision	vision	NOUN
ajst-20214	189	10	and	and	CCONJ
ajst-20214	189	11	pattern	pattern	NOUN
ajst-20214	189	12	recognition	recognition	NOUN
ajst-20214	189	13	(	(	PUNCT
ajst-20214	189	14	pp	pp	ADJ
ajst-20214	189	15	.	.	PUNCT
ajst-20214	190	1	7263	7263	NUM
ajst-20214	190	2	-	-	SYM
ajst-20214	190	3	7271	7271	NUM
ajst-20214	190	4	)	)	PUNCT
ajst-20214	190	5	.	.	PUNCT
ajst-20214	191	1	[	[	X
ajst-20214	191	2	6	6	NUM
ajst-20214	191	3	]	]	X
ajst-20214	191	4	redmon	redmon	PROPN
ajst-20214	191	5	,	,	PUNCT
ajst-20214	191	6	j.	j.	PROPN
ajst-20214	191	7	,	,	PUNCT
ajst-20214	191	8	&	&	CCONJ
ajst-20214	191	9	farhadi	farhadi	PROPN
ajst-20214	191	10	,	,	PUNCT
ajst-20214	191	11	a.	a.	NOUN
ajst-20214	191	12	(	(	PUNCT
ajst-20214	191	13	2018	2018	NUM
ajst-20214	191	14	)	)	PUNCT
ajst-20214	191	15	.	.	PUNCT
ajst-20214	192	1	yolov3	yolov3	PROPN
ajst-20214	192	2	:	:	PUNCT
ajst-20214	193	1	an	an	DET
ajst-20214	193	2	incremental	incremental	ADJ
ajst-20214	193	3	improvement	improvement	NOUN
ajst-20214	193	4	.	.	PUNCT
ajst-20214	194	1	arxiv	arxiv	PROPN
ajst-20214	194	2	preprint	preprint	VERB
ajst-20214	194	3	arxiv:1804.02767	arxiv:1804.02767	PROPN
ajst-20214	194	4	.	.	PUNCT
ajst-20214	195	1	[	[	X
ajst-20214	195	2	7	7	NUM
ajst-20214	195	3	]	]	X
ajst-20214	195	4	bochkovskiy	bochkovskiy	NOUN
ajst-20214	195	5	,	,	PUNCT
ajst-20214	195	6	a.	a.	PROPN
ajst-20214	195	7	,	,	PUNCT
ajst-20214	195	8	wang	wang	PROPN
ajst-20214	195	9	,	,	PUNCT
ajst-20214	195	10	c.	c.	PROPN
ajst-20214	195	11	y.	y.	PROPN
ajst-20214	195	12	,	,	PUNCT
ajst-20214	195	13	&	&	CCONJ
ajst-20214	195	14	liao	liao	PROPN
ajst-20214	195	15	,	,	PUNCT
ajst-20214	195	16	h.	h.	PROPN
ajst-20214	195	17	y.	y.	PROPN
ajst-20214	195	18	m.	m.	PROPN
ajst-20214	195	19	(	(	PUNCT
ajst-20214	195	20	2020	2020	NUM
ajst-20214	195	21	)	)	PUNCT
ajst-20214	195	22	.	.	PUNCT
ajst-20214	196	1	yolov4	yolov4	NOUN
ajst-20214	196	2	:	:	PUNCT
ajst-20214	196	3	optimal	optimal	ADJ
ajst-20214	196	4	speed	speed	NOUN
ajst-20214	196	5	and	and	CCONJ
ajst-20214	196	6	accuracy	accuracy	NOUN
ajst-20214	196	7	of	of	ADP
ajst-20214	196	8	object	object	NOUN
ajst-20214	196	9	detection	detection	NOUN
ajst-20214	196	10	.	.	PUNCT
ajst-20214	197	1	arxiv	arxiv	PROPN
ajst-20214	197	2	preprint	preprint	NOUN
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ajst-20214	197	4	.	.	PUNCT
ajst-20214	198	1	[	[	X
ajst-20214	198	2	8	8	NUM
ajst-20214	198	3	]	]	X
ajst-20214	198	4	hinton	hinton	PROPN
ajst-20214	198	5	,	,	PUNCT
ajst-20214	198	6	g.	g.	PROPN
ajst-20214	198	7	,	,	PUNCT
ajst-20214	198	8	vinyals	vinyal	NOUN
ajst-20214	198	9	,	,	PUNCT
ajst-20214	198	10	o.	o.	NOUN
ajst-20214	198	11	,	,	PUNCT
ajst-20214	198	12	&	&	CCONJ
ajst-20214	198	13	dean	dean	PROPN
ajst-20214	198	14	,	,	PUNCT
ajst-20214	198	15	j.	j.	PROPN
ajst-20214	198	16	(	(	PUNCT
ajst-20214	198	17	2015	2015	NUM
ajst-20214	198	18	)	)	PUNCT
ajst-20214	198	19	.	.	PUNCT
ajst-20214	199	1	distilling	distil	VERB
ajst-20214	199	2	the	the	DET
ajst-20214	199	3	knowledge	knowledge	NOUN
ajst-20214	199	4	in	in	ADP
ajst-20214	199	5	a	a	DET
ajst-20214	199	6	neural	neural	ADJ
ajst-20214	199	7	network	network	NOUN
ajst-20214	199	8	.	.	PUNCT
ajst-20214	200	1	arxiv	arxiv	PROPN
ajst-20214	200	2	preprint	preprint	VERB
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ajst-20214	200	4	.	.	PUNCT
ajst-20214	201	1	[	[	X
ajst-20214	201	2	9	9	NUM
ajst-20214	201	3	]	]	SYM
ajst-20214	201	4	luo	luo	PROPN
ajst-20214	201	5	,	,	PUNCT
ajst-20214	201	6	j.	j.	PROPN
ajst-20214	201	7	h.	h.	PROPN
ajst-20214	201	8	,	,	PUNCT
ajst-20214	201	9	wu	wu	PROPN
ajst-20214	201	10	,	,	PUNCT
ajst-20214	201	11	j.	j.	PROPN
ajst-20214	201	12	,	,	PUNCT
ajst-20214	201	13	&	&	CCONJ
ajst-20214	201	14	lin	lin	PROPN
ajst-20214	201	15	,	,	PUNCT
ajst-20214	201	16	w.	w.	PROPN
ajst-20214	201	17	(	(	PUNCT
ajst-20214	201	18	2017	2017	NUM
ajst-20214	201	19	)	)	PUNCT
ajst-20214	201	20	.	.	PUNCT
ajst-20214	202	1	thinet	thinet	ADJ
ajst-20214	202	2	:	:	PUNCT
ajst-20214	202	3	a	a	DET
ajst-20214	202	4	filter	filter	NOUN
ajst-20214	202	5	level	level	NOUN
ajst-20214	202	6	pruning	pruning	NOUN
ajst-20214	202	7	method	method	NOUN
ajst-20214	202	8	for	for	ADP
ajst-20214	202	9	deep	deep	ADJ
ajst-20214	202	10	neural	neural	ADJ
ajst-20214	202	11	network	network	NOUN
ajst-20214	202	12	compression	compression	NOUN
ajst-20214	202	13	.	.	PUNCT
ajst-20214	203	1	in	in	ADP
ajst-20214	203	2	proceedings	proceeding	NOUN
ajst-20214	203	3	of	of	ADP
ajst-20214	203	4	the	the	DET
ajst-20214	203	5	ieee	ieee	NOUN
ajst-20214	203	6	international	international	PROPN
ajst-20214	203	7	conference	conference	NOUN
ajst-20214	203	8	on	on	ADP
ajst-20214	203	9	computer	computer	NOUN
ajst-20214	203	10	vision	vision	NOUN
ajst-20214	203	11	(	(	PUNCT
ajst-20214	203	12	pp	pp	ADJ
ajst-20214	203	13	.	.	PUNCT
ajst-20214	203	14	5058	5058	NUM
ajst-20214	203	15	-	-	SYM
ajst-20214	203	16	5066	5066	NUM
ajst-20214	203	17	)	)	PUNCT
ajst-20214	203	18	.	.	PUNCT
ajst-20214	204	1	[	[	X
ajst-20214	204	2	10	10	NUM
ajst-20214	204	3	]	]	X
ajst-20214	204	4	he	he	PRON
ajst-20214	204	5	,	,	PUNCT
ajst-20214	204	6	y.	y.	PROPN
ajst-20214	204	7	,	,	PUNCT
ajst-20214	204	8	zhang	zhang	PROPN
ajst-20214	204	9	,	,	PUNCT
ajst-20214	204	10	x.	x.	PROPN
ajst-20214	204	11	,	,	PUNCT
ajst-20214	204	12	&	&	CCONJ
ajst-20214	204	13	sun	sun	PROPN
ajst-20214	204	14	,	,	PUNCT
ajst-20214	204	15	j.	j.	PROPN
ajst-20214	204	16	(	(	PUNCT
ajst-20214	204	17	2017	2017	NUM
ajst-20214	204	18	)	)	PUNCT
ajst-20214	204	19	.	.	PUNCT
ajst-20214	205	1	channel	channel	NOUN
ajst-20214	205	2	pruning	prune	VERB
ajst-20214	205	3	for	for	ADP
ajst-20214	205	4	accelerating	accelerate	VERB
ajst-20214	205	5	very	very	ADV
ajst-20214	205	6	deep	deep	ADJ
ajst-20214	205	7	neural	neural	ADJ
ajst-20214	205	8	networks	network	NOUN
ajst-20214	205	9	.	.	PUNCT
ajst-20214	206	1	in	in	ADP
ajst-20214	206	2	proceedings	proceeding	NOUN
ajst-20214	206	3	of	of	ADP
ajst-20214	206	4	the	the	DET
ajst-20214	206	5	ieee	ieee	NOUN
ajst-20214	206	6	international	international	PROPN
ajst-20214	206	7	conference	conference	NOUN
ajst-20214	206	8	on	on	ADP
ajst-20214	206	9	computer	computer	NOUN
ajst-20214	206	10	vision	vision	NOUN
ajst-20214	206	11	(	(	PUNCT
ajst-20214	206	12	pp	pp	ADP
ajst-20214	206	13	.	.	PUNCT
ajst-20214	206	14	13891397	13891397	NUM
ajst-20214	206	15	)	)	PUNCT
ajst-20214	206	16	.	.	PUNCT
ajst-20214	207	1	[	[	X
ajst-20214	207	2	11	11	NUM
ajst-20214	207	3	]	]	X
ajst-20214	207	4	hubara	hubara	PROPN
ajst-20214	207	5	,	,	PUNCT
ajst-20214	207	6	i.	i.	PROPN
ajst-20214	207	7	,	,	PUNCT
ajst-20214	207	8	courbariaux	courbariaux	ADV
ajst-20214	207	9	,	,	PUNCT
ajst-20214	207	10	m.	m.	NOUN
ajst-20214	207	11	,	,	PUNCT
ajst-20214	207	12	soudry	soudry	ADJ
ajst-20214	207	13	,	,	PUNCT
ajst-20214	207	14	d.	d.	PROPN
ajst-20214	207	15	,	,	PUNCT
ajst-20214	207	16	el	el	PROPN
ajst-20214	207	17	-	-	PUNCT
ajst-20214	207	18	yaniv	yaniv	PROPN
ajst-20214	207	19	,	,	PUNCT
ajst-20214	207	20	r.	r.	PROPN
ajst-20214	207	21	,	,	PUNCT
ajst-20214	207	22	&	&	CCONJ
ajst-20214	207	23	bengio	bengio	PROPN
ajst-20214	207	24	,	,	PUNCT
ajst-20214	207	25	y.	y.	PROPN
ajst-20214	207	26	(	(	PUNCT
ajst-20214	207	27	2018	2018	NUM
ajst-20214	207	28	)	)	PUNCT
ajst-20214	207	29	.	.	PUNCT
ajst-20214	208	1	quantized	quantize	VERB
ajst-20214	208	2	neural	neural	ADJ
ajst-20214	208	3	networks	network	NOUN
ajst-20214	208	4	:	:	PUNCT
ajst-20214	208	5	training	train	VERB
ajst-20214	208	6	neural	neural	ADJ
ajst-20214	208	7	networks	network	NOUN
ajst-20214	208	8	with	with	ADP
ajst-20214	208	9	low	low	ADJ
ajst-20214	208	10	precision	precision	NOUN
ajst-20214	208	11	weights	weight	NOUN
ajst-20214	208	12	and	and	CCONJ
ajst-20214	208	13	activations	activation	NOUN
ajst-20214	208	14	.	.	PUNCT
ajst-20214	209	1	journal	journal	NOUN
ajst-20214	209	2	of	of	ADP
ajst-20214	209	3	machine	machine	NOUN
ajst-20214	209	4	learning	learn	VERB
ajst-20214	209	5	research	research	NOUN
ajst-20214	209	6	,	,	PUNCT
ajst-20214	209	7	18(187	18(187	NOUN
ajst-20214	209	8	)	)	PUNCT
ajst-20214	209	9	,	,	PUNCT
ajst-20214	209	10	1	1	NUM
ajst-20214	209	11	-	-	SYM
ajst-20214	209	12	30	30	NUM
ajst-20214	209	13	.	.	PUNCT
ajst-20214	210	1	[	[	X
ajst-20214	210	2	12	12	NUM
ajst-20214	210	3	]	]	X
ajst-20214	210	4	jacob	jacob	PROPN
ajst-20214	210	5	,	,	PUNCT
ajst-20214	210	6	b.	b.	PROPN
ajst-20214	210	7	,	,	PUNCT
ajst-20214	210	8	kligys	kligys	PROPN
ajst-20214	210	9	,	,	PUNCT
ajst-20214	210	10	s.	s.	PROPN
ajst-20214	210	11	,	,	PUNCT
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ajst-20214	210	13	,	,	PUNCT
ajst-20214	210	14	b.	b.	PROPN
ajst-20214	210	15	,	,	PUNCT
ajst-20214	210	16	zhu	zhu	PROPN
ajst-20214	210	17	,	,	PUNCT
ajst-20214	210	18	m.	m.	NOUN
ajst-20214	210	19	,	,	PUNCT
ajst-20214	210	20	tang	tang	PROPN
ajst-20214	210	21	,	,	PUNCT
ajst-20214	210	22	m.	m.	NOUN
ajst-20214	210	23	,	,	PUNCT
ajst-20214	210	24	howard	howard	PROPN
ajst-20214	210	25	,	,	PUNCT
ajst-20214	210	26	a.	a.	PROPN
ajst-20214	210	27	,	,	PUNCT
ajst-20214	210	28	...	...	PUNCT
ajst-20214	210	29	&	&	CCONJ
ajst-20214	210	30	kalenichenko	kalenichenko	PROPN
ajst-20214	210	31	,	,	PUNCT
ajst-20214	210	32	d.	d.	PROPN
ajst-20214	210	33	(	(	PUNCT
ajst-20214	210	34	2018	2018	NUM
ajst-20214	210	35	)	)	PUNCT
ajst-20214	210	36	.	.	PUNCT
ajst-20214	211	1	quantization	quantization	NOUN
ajst-20214	211	2	and	and	CCONJ
ajst-20214	211	3	training	training	NOUN
ajst-20214	211	4	of	of	ADP
ajst-20214	211	5	neural	neural	ADJ
ajst-20214	211	6	networks	network	NOUN
ajst-20214	211	7	for	for	ADP
ajst-20214	211	8	efficient	efficient	ADJ
ajst-20214	211	9	integer	integer	NOUN
ajst-20214	211	10	-	-	PUNCT
ajst-20214	211	11	arithmetic	arithmetic	ADJ
ajst-20214	211	12	-	-	PUNCT
ajst-20214	211	13	only	only	ADJ
ajst-20214	211	14	inference	inference	NOUN
ajst-20214	211	15	.	.	PUNCT
ajst-20214	212	1	in	in	ADP
ajst-20214	212	2	proceedings	proceeding	NOUN
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ajst-20214	212	4	the	the	DET
ajst-20214	212	5	ieee	ieee	NOUN
ajst-20214	212	6	conference	conference	NOUN
ajst-20214	212	7	on	on	ADP
ajst-20214	212	8	computer	computer	NOUN
ajst-20214	212	9	vision	vision	NOUN
ajst-20214	212	10	and	and	CCONJ
ajst-20214	212	11	pattern	pattern	NOUN
ajst-20214	212	12	recognition	recognition	NOUN
ajst-20214	212	13	(	(	PUNCT
ajst-20214	212	14	pp	pp	ADJ
ajst-20214	212	15	.	.	PUNCT
ajst-20214	212	16	2704	2704	NUM
ajst-20214	212	17	-	-	SYM
ajst-20214	212	18	2713	2713	NUM
ajst-20214	212	19	)	)	PUNCT
ajst-20214	212	20	.	.	PUNCT
ajst-20214	213	1	[	[	X
ajst-20214	213	2	13	13	NUM
ajst-20214	213	3	]	]	X
ajst-20214	213	4	zhang	zhang	PROPN
ajst-20214	213	5	,	,	PUNCT
ajst-20214	213	6	x.	x.	PROPN
ajst-20214	213	7	,	,	PUNCT
ajst-20214	213	8	zou	zou	PROPN
ajst-20214	213	9	,	,	PUNCT
ajst-20214	213	10	j.	j.	PROPN
ajst-20214	213	11	,	,	PUNCT
ajst-20214	213	12	he	he	PRON
ajst-20214	213	13	,	,	PUNCT
ajst-20214	213	14	k.	k.	PROPN
ajst-20214	213	15	,	,	PUNCT
ajst-20214	213	16	&	&	CCONJ
ajst-20214	213	17	sun	sun	PROPN
ajst-20214	213	18	,	,	PUNCT
ajst-20214	213	19	j.	j.	PROPN
ajst-20214	213	20	(	(	PUNCT
ajst-20214	213	21	2015	2015	NUM
ajst-20214	213	22	)	)	PUNCT
ajst-20214	213	23	.	.	PUNCT
ajst-20214	214	1	accelerating	accelerate	VERB
ajst-20214	214	2	very	very	ADV
ajst-20214	214	3	deep	deep	ADJ
ajst-20214	214	4	convolutional	convolutional	ADJ
ajst-20214	214	5	networks	network	NOUN
ajst-20214	214	6	for	for	ADP
ajst-20214	214	7	classification	classification	NOUN
ajst-20214	214	8	and	and	CCONJ
ajst-20214	214	9	detection	detection	NOUN
ajst-20214	214	10	.	.	PUNCT
ajst-20214	215	1	ieee	ieee	NOUN
ajst-20214	215	2	transactions	transaction	NOUN
ajst-20214	215	3	on	on	ADP
ajst-20214	215	4	pattern	pattern	NOUN
ajst-20214	215	5	analysis	analysis	NOUN
ajst-20214	215	6	and	and	CCONJ
ajst-20214	215	7	machine	machine	NOUN
ajst-20214	215	8	intelligence	intelligence	NOUN
ajst-20214	215	9	,	,	PUNCT
ajst-20214	215	10	38(10	38(10	PROPN
ajst-20214	215	11	)	)	PUNCT
ajst-20214	215	12	,	,	PUNCT
ajst-20214	215	13	1943	1943	NUM
ajst-20214	215	14	-	-	SYM
ajst-20214	215	15	1955	1955	NUM
ajst-20214	215	16	.	.	PUNCT
ajst-20214	216	1	[	[	X
ajst-20214	216	2	14	14	NUM
ajst-20214	216	3	]	]	X
ajst-20214	216	4	lebedev	lebedev	PROPN
ajst-20214	216	5	,	,	PUNCT
ajst-20214	216	6	v.	v.	PROPN
ajst-20214	216	7	,	,	PUNCT
ajst-20214	216	8	ganin	ganin	PROPN
ajst-20214	216	9	,	,	PUNCT
ajst-20214	216	10	y.	y.	PROPN
ajst-20214	216	11	,	,	PUNCT
ajst-20214	216	12	rakhuba	rakhuba	VERB
ajst-20214	216	13	,	,	PUNCT
ajst-20214	216	14	m.	m.	NOUN
ajst-20214	216	15	,	,	PUNCT
ajst-20214	216	16	oseledets	oseledet	NOUN
ajst-20214	216	17	,	,	PUNCT
ajst-20214	216	18	i.	i.	NOUN
ajst-20214	216	19	,	,	PUNCT
ajst-20214	216	20	&	&	CCONJ
ajst-20214	216	21	lempitsky	lempitsky	PROPN
ajst-20214	216	22	,	,	PUNCT
ajst-20214	216	23	v.	v.	PROPN
ajst-20214	216	24	(	(	PUNCT
ajst-20214	216	25	2014	2014	NUM
ajst-20214	216	26	)	)	PUNCT
ajst-20214	216	27	.	.	PUNCT
ajst-20214	217	1	speeding	speed	VERB
ajst-20214	217	2	-	-	PUNCT
ajst-20214	217	3	up	up	ADP
ajst-20214	217	4	convolutional	convolutional	ADJ
ajst-20214	217	5	neural	neural	ADJ
ajst-20214	217	6	networks	network	NOUN
ajst-20214	217	7	using	use	VERB
ajst-20214	217	8	fine	fine	ADV
ajst-20214	217	9	-	-	PUNCT
ajst-20214	217	10	tuned	tune	VERB
ajst-20214	217	11	cp	cp	NOUN
ajst-20214	217	12	-	-	NOUN
ajst-20214	217	13	decomposition	decomposition	NOUN
ajst-20214	217	14	.	.	PUNCT
ajst-20214	218	1	arxiv	arxiv	PROPN
ajst-20214	218	2	preprint	preprint	VERB
ajst-20214	218	3	arxiv:1412.6553	arxiv:1412.6553	PROPN
ajst-20214	218	4	.	.	PUNCT