id	sid	tid	token	lemma	pos
ajst-26909	1	1	academic	academic	ADJ
ajst-26909	1	2	journal	journal	NOUN
ajst-26909	1	3	of	of	ADP
ajst-26909	1	4	science	science	NOUN
ajst-26909	1	5	and	and	CCONJ
ajst-26909	1	6	technology	technology	NOUN
ajst-26909	1	7	issn	issn	NOUN
ajst-26909	1	8	:	:	PUNCT
ajst-26909	1	9	2771	2771	NUM
ajst-26909	1	10	-	-	SYM
ajst-26909	1	11	3032	3032	NUM
ajst-26909	1	12	|	|	NOUN
ajst-26909	1	13	vol	vol	NOUN
ajst-26909	1	14	.	.	PROPN
ajst-26909	1	15	13	13	NUM
ajst-26909	1	16	,	,	PUNCT
ajst-26909	1	17	no	no	INTJ
ajst-26909	1	18	.	.	NOUN
ajst-26909	1	19	1	1	NUM
ajst-26909	1	20	,	,	PUNCT
ajst-26909	1	21	2024	2024	NUM
ajst-26909	1	22	189	189	NUM
ajst-26909	1	23	application	application	NOUN
ajst-26909	1	24	and	and	CCONJ
ajst-26909	1	25	optimization	optimization	NOUN
ajst-26909	1	26	of	of	ADP
ajst-26909	1	27	lightweight	lightweight	ADJ
ajst-26909	1	28	convolutional	convolutional	ADJ
ajst-26909	1	29	neural	neural	ADJ
ajst-26909	1	30	network	network	NOUN
ajst-26909	1	31	in	in	ADP
ajst-26909	1	32	target	target	NOUN
ajst-26909	1	33	detection	detection	NOUN
ajst-26909	1	34	liangyuan	liangyuan	PROPN
ajst-26909	1	35	li	li	PROPN
ajst-26909	1	36	affiliated	affiliate	VERB
ajst-26909	1	37	middle	middle	ADJ
ajst-26909	1	38	school	school	NOUN
ajst-26909	1	39	of	of	ADP
ajst-26909	1	40	henan	henan	PROPN
ajst-26909	1	41	normal	normal	ADJ
ajst-26909	1	42	university	university	NOUN
ajst-26909	1	43	,	,	PUNCT
ajst-26909	1	44	no	no	NOUN
ajst-26909	1	45	.	.	NOUN
ajst-26909	1	46	85	85	NUM
ajst-26909	1	47	jianshe	jianshe	PROPN
ajst-26909	1	48	east	east	PROPN
ajst-26909	1	49	road	road	PROPN
ajst-26909	1	50	,	,	PUNCT
ajst-26909	1	51	muye	muye	PROPN
ajst-26909	1	52	district	district	PROPN
ajst-26909	1	53	,	,	PUNCT
ajst-26909	1	54	xinxiang	xinxiang	PROPN
ajst-26909	1	55	city	city	PROPN
ajst-26909	1	56	,	,	PUNCT
ajst-26909	1	57	henan	henan	PROPN
ajst-26909	1	58	province	province	PROPN
ajst-26909	1	59	,	,	PUNCT
ajst-26909	1	60	china	china	PROPN
ajst-26909	1	61	abstract	abstract	PROPN
ajst-26909	1	62	:	:	PUNCT
ajst-26909	1	63	due	due	ADP
ajst-26909	1	64	to	to	ADP
ajst-26909	1	65	its	its	PRON
ajst-26909	1	66	low	low	ADJ
ajst-26909	1	67	computational	computational	ADJ
ajst-26909	1	68	complexity	complexity	NOUN
ajst-26909	1	69	,	,	PUNCT
ajst-26909	1	70	minimal	minimal	ADJ
ajst-26909	1	71	storage	storage	NOUN
ajst-26909	1	72	needs	need	NOUN
ajst-26909	1	73	,	,	PUNCT
ajst-26909	1	74	and	and	CCONJ
ajst-26909	1	75	high	high	ADJ
ajst-26909	1	76	real	real	ADJ
ajst-26909	1	77	-	-	PUNCT
ajst-26909	1	78	time	time	NOUN
ajst-26909	1	79	performance	performance	NOUN
ajst-26909	1	80	,	,	PUNCT
ajst-26909	1	81	lightweight	lightweight	ADJ
ajst-26909	1	82	convolutional	convolutional	ADJ
ajst-26909	1	83	neural	neural	ADJ
ajst-26909	1	84	networks	network	NOUN
ajst-26909	1	85	(	(	PUNCT
ajst-26909	1	86	lcnn	lcnn	PROPN
ajst-26909	1	87	)	)	PUNCT
ajst-26909	1	88	have	have	AUX
ajst-26909	1	89	garnered	garner	VERB
ajst-26909	1	90	significant	significant	ADJ
ajst-26909	1	91	attention	attention	NOUN
ajst-26909	1	92	amidst	amidst	ADP
ajst-26909	1	93	the	the	DET
ajst-26909	1	94	swift	swift	ADJ
ajst-26909	1	95	advancement	advancement	NOUN
ajst-26909	1	96	of	of	ADP
ajst-26909	1	97	deep	deep	ADJ
ajst-26909	1	98	learning	learning	NOUN
ajst-26909	1	99	technology	technology	NOUN
ajst-26909	1	100	.	.	PUNCT
ajst-26909	2	1	by	by	ADP
ajst-26909	2	2	automatically	automatically	ADV
ajst-26909	2	3	learning	learn	VERB
ajst-26909	2	4	high	high	ADJ
ajst-26909	2	5	-	-	PUNCT
ajst-26909	2	6	level	level	NOUN
ajst-26909	2	7	feature	feature	NOUN
ajst-26909	2	8	representation	representation	NOUN
ajst-26909	2	9	,	,	PUNCT
ajst-26909	2	10	lcnn	lcnn	PROPN
ajst-26909	2	11	can	can	AUX
ajst-26909	2	12	capture	capture	VERB
ajst-26909	2	13	key	key	ADJ
ajst-26909	2	14	information	information	NOUN
ajst-26909	2	15	in	in	ADP
ajst-26909	2	16	images	image	NOUN
ajst-26909	2	17	more	more	ADV
ajst-26909	2	18	effectively	effectively	ADV
ajst-26909	2	19	.	.	PUNCT
ajst-26909	3	1	this	this	DET
ajst-26909	3	2	paper	paper	NOUN
ajst-26909	3	3	aims	aim	VERB
ajst-26909	3	4	to	to	PART
ajst-26909	3	5	discuss	discuss	VERB
ajst-26909	3	6	the	the	DET
ajst-26909	3	7	application	application	NOUN
ajst-26909	3	8	and	and	CCONJ
ajst-26909	3	9	optimization	optimization	NOUN
ajst-26909	3	10	of	of	ADP
ajst-26909	3	11	lcnn	lcnn	PROPN
ajst-26909	3	12	in	in	ADP
ajst-26909	3	13	target	target	NOUN
ajst-26909	3	14	detection	detection	NOUN
ajst-26909	3	15	task	task	NOUN
ajst-26909	3	16	.	.	PUNCT
ajst-26909	4	1	this	this	DET
ajst-26909	4	2	paper	paper	NOUN
ajst-26909	4	3	discusses	discuss	VERB
ajst-26909	4	4	the	the	DET
ajst-26909	4	5	key	key	ADJ
ajst-26909	4	6	strategies	strategy	NOUN
ajst-26909	4	7	such	such	ADJ
ajst-26909	4	8	as	as	ADP
ajst-26909	4	9	network	network	NOUN
ajst-26909	4	10	structure	structure	NOUN
ajst-26909	4	11	optimization	optimization	NOUN
ajst-26909	4	12	,	,	PUNCT
ajst-26909	4	13	training	training	NOUN
ajst-26909	4	14	method	method	NOUN
ajst-26909	4	15	optimization	optimization	NOUN
ajst-26909	4	16	and	and	CCONJ
ajst-26909	4	17	post	post	ADJ
ajst-26909	4	18	-	-	ADJ
ajst-26909	4	19	processing	processing	ADJ
ajst-26909	4	20	optimization	optimization	NOUN
ajst-26909	4	21	to	to	PART
ajst-26909	4	22	improve	improve	VERB
ajst-26909	4	23	the	the	DET
ajst-26909	4	24	performance	performance	NOUN
ajst-26909	4	25	of	of	ADP
ajst-26909	4	26	lcnn	lcnn	NOUN
ajst-26909	4	27	in	in	ADP
ajst-26909	4	28	target	target	NOUN
ajst-26909	4	29	detection	detection	NOUN
ajst-26909	4	30	.	.	PUNCT
ajst-26909	5	1	the	the	DET
ajst-26909	5	2	experimental	experimental	ADJ
ajst-26909	5	3	results	result	NOUN
ajst-26909	5	4	show	show	VERB
ajst-26909	5	5	that	that	SCONJ
ajst-26909	5	6	compared	compare	VERB
ajst-26909	5	7	with	with	ADP
ajst-26909	5	8	the	the	DET
ajst-26909	5	9	traditional	traditional	ADJ
ajst-26909	5	10	siftbased	siftbase	VERB
ajst-26909	5	11	target	target	NOUN
ajst-26909	5	12	detection	detection	NOUN
ajst-26909	5	13	algorithm	algorithm	NOUN
ajst-26909	5	14	,	,	PUNCT
ajst-26909	5	15	lcnn	lcnn	PROPN
ajst-26909	5	16	has	have	VERB
ajst-26909	5	17	obvious	obvious	ADJ
ajst-26909	5	18	advantages	advantage	NOUN
ajst-26909	5	19	in	in	ADP
ajst-26909	5	20	detection	detection	NOUN
ajst-26909	5	21	success	success	NOUN
ajst-26909	5	22	rate	rate	NOUN
ajst-26909	5	23	,	,	PUNCT
ajst-26909	5	24	time	time	NOUN
ajst-26909	5	25	consumption	consumption	NOUN
ajst-26909	5	26	and	and	CCONJ
ajst-26909	5	27	adaptability	adaptability	NOUN
ajst-26909	5	28	to	to	ADP
ajst-26909	5	29	different	different	ADJ
ajst-26909	5	30	scenes	scene	NOUN
ajst-26909	5	31	.	.	PUNCT
ajst-26909	6	1	in	in	ADP
ajst-26909	6	2	addition	addition	NOUN
ajst-26909	6	3	,	,	PUNCT
ajst-26909	6	4	the	the	DET
ajst-26909	6	5	lightweight	lightweight	ADJ
ajst-26909	6	6	design	design	NOUN
ajst-26909	6	7	of	of	ADP
ajst-26909	6	8	lcnn	lcnn	PROPN
ajst-26909	6	9	makes	make	VERB
ajst-26909	6	10	it	it	PRON
ajst-26909	6	11	easier	easy	ADJ
ajst-26909	6	12	to	to	PART
ajst-26909	6	13	deploy	deploy	VERB
ajst-26909	6	14	on	on	ADP
ajst-26909	6	15	equipment	equipment	NOUN
ajst-26909	6	16	with	with	ADP
ajst-26909	6	17	limited	limited	ADJ
ajst-26909	6	18	resources	resource	NOUN
ajst-26909	6	19	.	.	PUNCT
ajst-26909	7	1	lcnn	lcnn	PROPN
ajst-26909	7	2	shows	show	VERB
ajst-26909	7	3	strong	strong	ADJ
ajst-26909	7	4	performance	performance	NOUN
ajst-26909	7	5	and	and	CCONJ
ajst-26909	7	6	wide	wide	ADJ
ajst-26909	7	7	application	application	NOUN
ajst-26909	7	8	prospect	prospect	NOUN
ajst-26909	7	9	in	in	ADP
ajst-26909	7	10	target	target	NOUN
ajst-26909	7	11	detection	detection	NOUN
ajst-26909	7	12	,	,	PUNCT
ajst-26909	7	13	which	which	PRON
ajst-26909	7	14	is	be	AUX
ajst-26909	7	15	expected	expect	VERB
ajst-26909	7	16	to	to	PART
ajst-26909	7	17	provide	provide	VERB
ajst-26909	7	18	new	new	ADJ
ajst-26909	7	19	impetus	impetus	NOUN
ajst-26909	7	20	for	for	ADP
ajst-26909	7	21	the	the	DET
ajst-26909	7	22	innovation	innovation	NOUN
ajst-26909	7	23	of	of	ADP
ajst-26909	7	24	target	target	NOUN
ajst-26909	7	25	detection	detection	NOUN
ajst-26909	7	26	technology	technology	NOUN
ajst-26909	7	27	.	.	PUNCT
ajst-26909	8	1	keywords	keyword	NOUN
ajst-26909	8	2	:	:	PUNCT
ajst-26909	8	3	lightweight	lightweight	ADJ
ajst-26909	8	4	;	;	PUNCT
ajst-26909	8	5	convolutional	convolutional	ADJ
ajst-26909	8	6	neural	neural	ADJ
ajst-26909	8	7	network	network	NOUN
ajst-26909	8	8	;	;	PUNCT
ajst-26909	8	9	target	target	NOUN
ajst-26909	8	10	detection	detection	NOUN
ajst-26909	8	11	;	;	PUNCT
ajst-26909	8	12	optimization	optimization	NOUN
ajst-26909	8	13	strategy	strategy	NOUN
ajst-26909	8	14	.	.	PUNCT
ajst-26909	9	1	1	1	X
ajst-26909	9	2	.	.	X
ajst-26909	9	3	introduction	introduction	NOUN
ajst-26909	9	4	today	today	NOUN
ajst-26909	9	5	,	,	PUNCT
ajst-26909	9	6	with	with	ADP
ajst-26909	9	7	the	the	DET
ajst-26909	9	8	rapid	rapid	ADJ
ajst-26909	9	9	development	development	NOUN
ajst-26909	9	10	of	of	ADP
ajst-26909	9	11	information	information	NOUN
ajst-26909	9	12	technology	technology	NOUN
ajst-26909	9	13	,	,	PUNCT
ajst-26909	9	14	computer	computer	NOUN
ajst-26909	9	15	vision	vision	NOUN
ajst-26909	9	16	,	,	PUNCT
ajst-26909	9	17	as	as	ADP
ajst-26909	9	18	an	an	DET
ajst-26909	9	19	important	important	ADJ
ajst-26909	9	20	branch	branch	NOUN
ajst-26909	9	21	in	in	ADP
ajst-26909	9	22	the	the	DET
ajst-26909	9	23	field	field	NOUN
ajst-26909	9	24	of	of	ADP
ajst-26909	9	25	artificial	artificial	ADJ
ajst-26909	9	26	intelligence	intelligence	NOUN
ajst-26909	9	27	,	,	PUNCT
ajst-26909	9	28	is	be	AUX
ajst-26909	9	29	promoting	promote	VERB
ajst-26909	9	30	industrial	industrial	ADJ
ajst-26909	9	31	upgrading	upgrading	NOUN
ajst-26909	9	32	at	at	ADP
ajst-26909	9	33	an	an	DET
ajst-26909	9	34	unprecedented	unprecedented	ADJ
ajst-26909	9	35	speed	speed	NOUN
ajst-26909	9	36	.	.	PUNCT
ajst-26909	10	1	as	as	ADP
ajst-26909	10	2	one	one	NUM
ajst-26909	10	3	of	of	ADP
ajst-26909	10	4	the	the	DET
ajst-26909	10	5	core	core	NOUN
ajst-26909	10	6	tasks	task	NOUN
ajst-26909	10	7	of	of	ADP
ajst-26909	10	8	computer	computer	NOUN
ajst-26909	10	9	vision	vision	NOUN
ajst-26909	10	10	,	,	PUNCT
ajst-26909	10	11	target	target	NOUN
ajst-26909	10	12	detection	detection	NOUN
ajst-26909	10	13	aims	aim	VERB
ajst-26909	10	14	to	to	PART
ajst-26909	10	15	accurately	accurately	ADV
ajst-26909	10	16	identify	identify	VERB
ajst-26909	10	17	and	and	CCONJ
ajst-26909	10	18	locate	locate	VERB
ajst-26909	10	19	the	the	DET
ajst-26909	10	20	interested	interested	ADJ
ajst-26909	10	21	target	target	NOUN
ajst-26909	10	22	object	object	NOUN
ajst-26909	10	23	from	from	ADP
ajst-26909	10	24	complex	complex	ADJ
ajst-26909	10	25	images	image	NOUN
ajst-26909	10	26	or	or	CCONJ
ajst-26909	10	27	video	video	NOUN
ajst-26909	10	28	sequences	sequence	NOUN
ajst-26909	11	1	[	[	X
ajst-26909	11	2	1	1	NUM
ajst-26909	11	3	]	]	PUNCT
ajst-26909	11	4	.	.	PUNCT
ajst-26909	12	1	this	this	DET
ajst-26909	12	2	technology	technology	NOUN
ajst-26909	12	3	has	have	AUX
ajst-26909	12	4	shown	show	VERB
ajst-26909	12	5	great	great	ADJ
ajst-26909	12	6	application	application	NOUN
ajst-26909	12	7	potential	potential	NOUN
ajst-26909	12	8	in	in	ADP
ajst-26909	12	9	many	many	ADJ
ajst-26909	12	10	fields	field	NOUN
ajst-26909	12	11	such	such	ADJ
ajst-26909	12	12	as	as	ADP
ajst-26909	12	13	automatic	automatic	ADJ
ajst-26909	12	14	driving	driving	NOUN
ajst-26909	12	15	,	,	PUNCT
ajst-26909	12	16	intelligent	intelligent	ADJ
ajst-26909	12	17	monitoring	monitoring	NOUN
ajst-26909	12	18	,	,	PUNCT
ajst-26909	12	19	medical	medical	ADJ
ajst-26909	12	20	image	image	NOUN
ajst-26909	12	21	analysis	analysis	NOUN
ajst-26909	12	22	and	and	CCONJ
ajst-26909	12	23	so	so	ADV
ajst-26909	12	24	on	on	ADV
ajst-26909	12	25	.	.	PUNCT
ajst-26909	13	1	traditional	traditional	ADJ
ajst-26909	13	2	target	target	NOUN
ajst-26909	13	3	detection	detection	NOUN
ajst-26909	13	4	methods	method	NOUN
ajst-26909	13	5	mainly	mainly	ADV
ajst-26909	13	6	rely	rely	VERB
ajst-26909	13	7	on	on	ADP
ajst-26909	13	8	manually	manually	ADV
ajst-26909	13	9	designed	design	VERB
ajst-26909	13	10	features	feature	NOUN
ajst-26909	13	11	and	and	CCONJ
ajst-26909	13	12	classifiers	classifier	NOUN
ajst-26909	13	13	,	,	PUNCT
ajst-26909	13	14	such	such	ADJ
ajst-26909	13	15	as	as	ADP
ajst-26909	13	16	hog+svm	hog+svm	NOUN
ajst-26909	13	17	,	,	PUNCT
ajst-26909	13	18	haar+adaboost	haar+adaboost	NOUN
ajst-26909	13	19	,	,	PUNCT
ajst-26909	13	20	etc	etc	X
ajst-26909	13	21	[	[	X
ajst-26909	13	22	2	2	NUM
ajst-26909	13	23	]	]	PUNCT
ajst-26909	13	24	.	.	PUNCT
ajst-26909	14	1	although	although	SCONJ
ajst-26909	14	2	these	these	DET
ajst-26909	14	3	methods	method	NOUN
ajst-26909	14	4	can	can	AUX
ajst-26909	14	5	achieve	achieve	VERB
ajst-26909	14	6	certain	certain	ADJ
ajst-26909	14	7	results	result	NOUN
ajst-26909	14	8	in	in	ADP
ajst-26909	14	9	specific	specific	ADJ
ajst-26909	14	10	scenes	scene	NOUN
ajst-26909	14	11	,	,	PUNCT
ajst-26909	14	12	their	their	PRON
ajst-26909	14	13	generalization	generalization	NOUN
ajst-26909	14	14	ability	ability	NOUN
ajst-26909	14	15	and	and	CCONJ
ajst-26909	14	16	robustness	robustness	NOUN
ajst-26909	14	17	are	be	AUX
ajst-26909	14	18	obviously	obviously	ADV
ajst-26909	14	19	insufficient	insufficient	ADJ
ajst-26909	14	20	when	when	SCONJ
ajst-26909	14	21	dealing	deal	VERB
ajst-26909	14	22	with	with	ADP
ajst-26909	14	23	complex	complex	ADJ
ajst-26909	14	24	and	and	CCONJ
ajst-26909	14	25	changeable	changeable	ADJ
ajst-26909	14	26	actual	actual	ADJ
ajst-26909	14	27	environments	environment	NOUN
ajst-26909	14	28	[	[	X
ajst-26909	14	29	3	3	NUM
ajst-26909	14	30	]	]	PUNCT
ajst-26909	14	31	.	.	PUNCT
ajst-26909	15	1	by	by	ADP
ajst-26909	15	2	automatically	automatically	ADV
ajst-26909	15	3	learning	learn	VERB
ajst-26909	15	4	high	high	ADJ
ajst-26909	15	5	-	-	PUNCT
ajst-26909	15	6	level	level	NOUN
ajst-26909	15	7	feature	feature	NOUN
ajst-26909	15	8	representation	representation	NOUN
ajst-26909	15	9	,	,	PUNCT
ajst-26909	15	10	cnn	cnn	PROPN
ajst-26909	15	11	can	can	AUX
ajst-26909	15	12	capture	capture	VERB
ajst-26909	15	13	the	the	DET
ajst-26909	15	14	key	key	ADJ
ajst-26909	15	15	information	information	NOUN
ajst-26909	15	16	in	in	ADP
ajst-26909	15	17	the	the	DET
ajst-26909	15	18	image	image	NOUN
ajst-26909	15	19	more	more	ADV
ajst-26909	15	20	effectively	effectively	ADV
ajst-26909	15	21	,	,	PUNCT
ajst-26909	15	22	thus	thus	ADV
ajst-26909	15	23	achieving	achieve	VERB
ajst-26909	15	24	high	high	ADJ
ajst-26909	15	25	-	-	PUNCT
ajst-26909	15	26	precision	precision	NOUN
ajst-26909	15	27	target	target	NOUN
ajst-26909	15	28	detection	detection	NOUN
ajst-26909	15	29	[	[	X
ajst-26909	15	30	4	4	NUM
ajst-26909	15	31	]	]	PUNCT
ajst-26909	15	32	.	.	PUNCT
ajst-26909	16	1	however	however	ADV
ajst-26909	16	2	,	,	PUNCT
ajst-26909	16	3	high	high	ADJ
ajst-26909	16	4	performance	performance	NOUN
ajst-26909	16	5	is	be	AUX
ajst-26909	16	6	often	often	ADV
ajst-26909	16	7	accompanied	accompany	VERB
ajst-26909	16	8	by	by	ADP
ajst-26909	16	9	high	high	ADJ
ajst-26909	16	10	computing	computing	NOUN
ajst-26909	16	11	cost	cost	NOUN
ajst-26909	16	12	and	and	CCONJ
ajst-26909	16	13	storage	storage	NOUN
ajst-26909	16	14	requirements	requirement	NOUN
ajst-26909	16	15	,	,	PUNCT
ajst-26909	16	16	which	which	PRON
ajst-26909	16	17	limits	limit	VERB
ajst-26909	16	18	the	the	DET
ajst-26909	16	19	wide	wide	ADJ
ajst-26909	16	20	application	application	NOUN
ajst-26909	16	21	of	of	ADP
ajst-26909	16	22	deep	deep	ADJ
ajst-26909	16	23	learning	learning	NOUN
ajst-26909	16	24	model	model	NOUN
ajst-26909	16	25	in	in	ADP
ajst-26909	16	26	resource	resource	NOUN
ajst-26909	16	27	-	-	PUNCT
ajst-26909	16	28	constrained	constrain	VERB
ajst-26909	16	29	devices	device	NOUN
ajst-26909	16	30	.	.	PUNCT
ajst-26909	17	1	the	the	DET
ajst-26909	17	2	appearance	appearance	NOUN
ajst-26909	17	3	of	of	ADP
ajst-26909	17	4	lcnn	lcnn	PROPN
ajst-26909	17	5	makes	make	VERB
ajst-26909	17	6	it	it	PRON
ajst-26909	17	7	possible	possible	ADJ
ajst-26909	17	8	to	to	PART
ajst-26909	17	9	solve	solve	VERB
ajst-26909	17	10	this	this	DET
ajst-26909	17	11	contradiction	contradiction	NOUN
ajst-26909	17	12	.	.	PUNCT
ajst-26909	18	1	lightweight	lightweight	ADJ
ajst-26909	18	2	network	network	NOUN
ajst-26909	18	3	can	can	AUX
ajst-26909	18	4	significantly	significantly	ADV
ajst-26909	18	5	reduce	reduce	VERB
ajst-26909	18	6	the	the	DET
ajst-26909	18	7	parameters	parameter	NOUN
ajst-26909	18	8	and	and	CCONJ
ajst-26909	18	9	computational	computational	ADJ
ajst-26909	18	10	complexity	complexity	NOUN
ajst-26909	18	11	of	of	ADP
ajst-26909	18	12	the	the	DET
ajst-26909	18	13	model	model	NOUN
ajst-26909	18	14	while	while	SCONJ
ajst-26909	18	15	maintaining	maintain	VERB
ajst-26909	18	16	or	or	CCONJ
ajst-26909	18	17	improving	improve	VERB
ajst-26909	18	18	the	the	DET
ajst-26909	18	19	detection	detection	NOUN
ajst-26909	18	20	accuracy	accuracy	NOUN
ajst-26909	18	21	through	through	ADP
ajst-26909	18	22	well	well	ADV
ajst-26909	18	23	-	-	PUNCT
ajst-26909	18	24	designed	design	VERB
ajst-26909	18	25	network	network	NOUN
ajst-26909	18	26	structure	structure	NOUN
ajst-26909	18	27	and	and	CCONJ
ajst-26909	18	28	optimization	optimization	NOUN
ajst-26909	18	29	strategy	strategy	NOUN
ajst-26909	18	30	[	[	X
ajst-26909	18	31	5	5	NUM
ajst-26909	18	32	]	]	PUNCT
ajst-26909	18	33	.	.	PUNCT
ajst-26909	19	1	how	how	SCONJ
ajst-26909	19	2	to	to	PART
ajst-26909	19	3	balance	balance	VERB
ajst-26909	19	4	the	the	DET
ajst-26909	19	5	detection	detection	NOUN
ajst-26909	19	6	speed	speed	NOUN
ajst-26909	19	7	and	and	CCONJ
ajst-26909	19	8	accuracy	accuracy	NOUN
ajst-26909	19	9	with	with	ADP
ajst-26909	19	10	limited	limited	ADJ
ajst-26909	19	11	computing	computing	NOUN
ajst-26909	19	12	resources	resource	NOUN
ajst-26909	19	13	has	have	AUX
ajst-26909	19	14	become	become	VERB
ajst-26909	19	15	a	a	DET
ajst-26909	19	16	key	key	ADJ
ajst-26909	19	17	issue	issue	NOUN
ajst-26909	19	18	in	in	ADP
ajst-26909	19	19	current	current	ADJ
ajst-26909	19	20	research	research	NOUN
ajst-26909	19	21	.	.	PUNCT
ajst-26909	20	1	this	this	DET
ajst-26909	20	2	paper	paper	NOUN
ajst-26909	20	3	aims	aim	VERB
ajst-26909	20	4	at	at	ADP
ajst-26909	20	5	systematically	systematically	ADV
ajst-26909	20	6	discussing	discuss	VERB
ajst-26909	20	7	the	the	DET
ajst-26909	20	8	application	application	NOUN
ajst-26909	20	9	and	and	CCONJ
ajst-26909	20	10	optimization	optimization	NOUN
ajst-26909	20	11	strategy	strategy	NOUN
ajst-26909	20	12	of	of	ADP
ajst-26909	20	13	lcnn	lcnn	PROPN
ajst-26909	20	14	in	in	ADP
ajst-26909	20	15	target	target	NOUN
ajst-26909	20	16	detection	detection	NOUN
ajst-26909	20	17	.	.	PUNCT
ajst-26909	21	1	in	in	ADP
ajst-26909	21	2	order	order	NOUN
ajst-26909	21	3	to	to	PART
ajst-26909	21	4	verify	verify	VERB
ajst-26909	21	5	the	the	DET
ajst-26909	21	6	effectiveness	effectiveness	NOUN
ajst-26909	21	7	of	of	ADP
ajst-26909	21	8	the	the	DET
ajst-26909	21	9	above	above	ADJ
ajst-26909	21	10	research	research	NOUN
ajst-26909	21	11	contents	content	NOUN
ajst-26909	21	12	,	,	PUNCT
ajst-26909	21	13	this	this	DET
ajst-26909	21	14	paper	paper	NOUN
ajst-26909	21	15	will	will	AUX
ajst-26909	21	16	use	use	VERB
ajst-26909	21	17	standard	standard	ADJ
ajst-26909	21	18	data	datum	NOUN
ajst-26909	21	19	sets	set	NOUN
ajst-26909	21	20	and	and	CCONJ
ajst-26909	21	21	evaluation	evaluation	NOUN
ajst-26909	21	22	indicators	indicator	NOUN
ajst-26909	21	23	to	to	PART
ajst-26909	21	24	evaluate	evaluate	VERB
ajst-26909	21	25	the	the	DET
ajst-26909	21	26	performance	performance	NOUN
ajst-26909	21	27	of	of	ADP
ajst-26909	21	28	lightweight	lightweight	ADJ
ajst-26909	21	29	networks	network	NOUN
ajst-26909	21	30	and	and	CCONJ
ajst-26909	21	31	optimization	optimization	NOUN
ajst-26909	21	32	strategies	strategy	NOUN
ajst-26909	21	33	.	.	PUNCT
ajst-26909	22	1	through	through	ADP
ajst-26909	22	2	the	the	DET
ajst-26909	22	3	comparative	comparative	ADJ
ajst-26909	22	4	analysis	analysis	NOUN
ajst-26909	22	5	of	of	ADP
ajst-26909	22	6	experimental	experimental	ADJ
ajst-26909	22	7	results	result	NOUN
ajst-26909	22	8	,	,	PUNCT
ajst-26909	22	9	the	the	DET
ajst-26909	22	10	advantages	advantage	NOUN
ajst-26909	22	11	and	and	CCONJ
ajst-26909	22	12	disadvantages	disadvantage	NOUN
ajst-26909	22	13	of	of	ADP
ajst-26909	22	14	lightweight	lightweight	ADJ
ajst-26909	22	15	network	network	NOUN
ajst-26909	22	16	in	in	ADP
ajst-26909	22	17	target	target	NOUN
ajst-26909	22	18	detection	detection	NOUN
ajst-26909	22	19	and	and	CCONJ
ajst-26909	22	20	the	the	DET
ajst-26909	22	21	actual	actual	ADJ
ajst-26909	22	22	effect	effect	NOUN
ajst-26909	22	23	of	of	ADP
ajst-26909	22	24	optimization	optimization	NOUN
ajst-26909	22	25	strategy	strategy	NOUN
ajst-26909	22	26	are	be	AUX
ajst-26909	22	27	discussed	discuss	VERB
ajst-26909	22	28	.	.	PUNCT
ajst-26909	23	1	2	2	X
ajst-26909	23	2	.	.	X
ajst-26909	23	3	related	relate	VERB
ajst-26909	23	4	theoretical	theoretical	ADJ
ajst-26909	23	5	basis	basis	NOUN
ajst-26909	23	6	2.1	2.1	NUM
ajst-26909	23	7	.	.	PUNCT
ajst-26909	23	8	basic	basic	ADJ
ajst-26909	23	9	principle	principle	NOUN
ajst-26909	23	10	of	of	ADP
ajst-26909	23	11	convolutional	convolutional	ADJ
ajst-26909	23	12	neural	neural	ADJ
ajst-26909	23	13	network	network	NOUN
ajst-26909	23	14	convolutional	convolutional	ADJ
ajst-26909	23	15	neural	neural	ADJ
ajst-26909	23	16	network	network	NOUN
ajst-26909	23	17	(	(	PUNCT
ajst-26909	23	18	cnn	cnn	PROPN
ajst-26909	23	19	)	)	PUNCT
ajst-26909	23	20	is	be	AUX
ajst-26909	23	21	a	a	DET
ajst-26909	23	22	deep	deep	ADJ
ajst-26909	23	23	learning	learning	NOUN
ajst-26909	23	24	model	model	NOUN
ajst-26909	23	25	with	with	ADP
ajst-26909	23	26	grid	grid	NOUN
ajst-26909	23	27	topology	topology	NOUN
ajst-26909	23	28	(	(	PUNCT
ajst-26909	23	29	such	such	ADJ
ajst-26909	23	30	as	as	ADP
ajst-26909	23	31	images	image	NOUN
ajst-26909	23	32	and	and	CCONJ
ajst-26909	23	33	voice	voice	NOUN
ajst-26909	23	34	signals	signal	NOUN
ajst-26909	23	35	)	)	PUNCT
ajst-26909	23	36	specially	specially	ADV
ajst-26909	23	37	used	use	VERB
ajst-26909	23	38	for	for	ADP
ajst-26909	23	39	processing	processing	NOUN
ajst-26909	23	40	data	datum	NOUN
ajst-26909	23	41	.	.	PUNCT
ajst-26909	24	1	its	its	PRON
ajst-26909	24	2	core	core	NOUN
ajst-26909	24	3	idea	idea	NOUN
ajst-26909	24	4	lies	lie	VERB
ajst-26909	24	5	in	in	ADP
ajst-26909	24	6	local	local	ADJ
ajst-26909	24	7	perception	perception	NOUN
ajst-26909	24	8	,	,	PUNCT
ajst-26909	24	9	weight	weight	NOUN
ajst-26909	24	10	sharing	sharing	NOUN
ajst-26909	24	11	and	and	CCONJ
ajst-26909	24	12	pooling	pool	VERB
ajst-26909	24	13	operation	operation	NOUN
ajst-26909	24	14	[	[	X
ajst-26909	24	15	6	6	NUM
ajst-26909	24	16	]	]	PUNCT
ajst-26909	24	17	.	.	PUNCT
ajst-26909	25	1	the	the	DET
ajst-26909	25	2	traditional	traditional	ADJ
ajst-26909	25	3	fully	fully	ADV
ajst-26909	25	4	connected	connect	VERB
ajst-26909	25	5	network	network	NOUN
ajst-26909	25	6	ignores	ignore	VERB
ajst-26909	25	7	the	the	DET
ajst-26909	25	8	spatial	spatial	ADJ
ajst-26909	25	9	structure	structure	NOUN
ajst-26909	25	10	information	information	NOUN
ajst-26909	25	11	of	of	ADP
ajst-26909	25	12	the	the	DET
ajst-26909	25	13	image	image	NOUN
ajst-26909	25	14	when	when	SCONJ
ajst-26909	25	15	processing	process	VERB
ajst-26909	25	16	the	the	DET
ajst-26909	25	17	image	image	NOUN
ajst-26909	25	18	,	,	PUNCT
ajst-26909	25	19	while	while	SCONJ
ajst-26909	25	20	cnn	cnn	PROPN
ajst-26909	25	21	only	only	ADV
ajst-26909	25	22	pays	pay	VERB
ajst-26909	25	23	attention	attention	NOUN
ajst-26909	25	24	to	to	ADP
ajst-26909	25	25	the	the	DET
ajst-26909	25	26	connection	connection	NOUN
ajst-26909	25	27	between	between	ADP
ajst-26909	25	28	each	each	DET
ajst-26909	25	29	neuron	neuron	NOUN
ajst-26909	25	30	and	and	CCONJ
ajst-26909	25	31	a	a	DET
ajst-26909	25	32	local	local	ADJ
ajst-26909	25	33	area	area	NOUN
ajst-26909	25	34	in	in	ADP
ajst-26909	25	35	the	the	DET
ajst-26909	25	36	input	input	NOUN
ajst-26909	25	37	image	image	NOUN
ajst-26909	25	38	through	through	ADP
ajst-26909	25	39	local	local	ADJ
ajst-26909	25	40	connection	connection	NOUN
ajst-26909	25	41	.	.	PUNCT
ajst-26909	26	1	in	in	ADP
ajst-26909	26	2	the	the	DET
ajst-26909	26	3	same	same	ADJ
ajst-26909	26	4	layer	layer	NOUN
ajst-26909	26	5	,	,	PUNCT
ajst-26909	26	6	multiple	multiple	ADJ
ajst-26909	26	7	neurons	neuron	NOUN
ajst-26909	26	8	share	share	VERB
ajst-26909	26	9	the	the	DET
ajst-26909	26	10	same	same	ADJ
ajst-26909	26	11	set	set	NOUN
ajst-26909	26	12	of	of	ADP
ajst-26909	26	13	weights	weight	NOUN
ajst-26909	26	14	,	,	PUNCT
ajst-26909	26	15	which	which	PRON
ajst-26909	26	16	means	mean	VERB
ajst-26909	26	17	that	that	SCONJ
ajst-26909	26	18	in	in	ADP
ajst-26909	26	19	feature	feature	NOUN
ajst-26909	26	20	extraction	extraction	NOUN
ajst-26909	26	21	,	,	PUNCT
ajst-26909	26	22	no	no	ADV
ajst-26909	26	23	matter	matter	ADV
ajst-26909	26	24	where	where	SCONJ
ajst-26909	26	25	the	the	DET
ajst-26909	26	26	feature	feature	NOUN
ajst-26909	26	27	is	be	AUX
ajst-26909	26	28	located	locate	VERB
ajst-26909	26	29	in	in	ADP
ajst-26909	26	30	the	the	DET
ajst-26909	26	31	image	image	NOUN
ajst-26909	26	32	,	,	PUNCT
ajst-26909	26	33	the	the	DET
ajst-26909	26	34	same	same	ADJ
ajst-26909	26	35	convolution	convolution	NOUN
ajst-26909	26	36	kernel	kernel	NOUN
ajst-26909	26	37	is	be	AUX
ajst-26909	26	38	used	use	VERB
ajst-26909	26	39	for	for	ADP
ajst-26909	26	40	operation	operation	NOUN
ajst-26909	26	41	.	.	PUNCT
ajst-26909	27	1	pooling	pool	VERB
ajst-26909	27	2	layer	layer	NOUN
ajst-26909	27	3	(	(	PUNCT
ajst-26909	27	4	such	such	ADJ
ajst-26909	27	5	as	as	ADP
ajst-26909	27	6	maximum	maximum	ADJ
ajst-26909	27	7	pooling	pooling	NOUN
ajst-26909	27	8	and	and	CCONJ
ajst-26909	27	9	average	average	ADJ
ajst-26909	27	10	pooling	pooling	NOUN
ajst-26909	27	11	)	)	PUNCT
ajst-26909	27	12	enhances	enhance	VERB
ajst-26909	27	13	the	the	DET
ajst-26909	27	14	robustness	robustness	NOUN
ajst-26909	27	15	of	of	ADP
ajst-26909	27	16	the	the	DET
ajst-26909	27	17	model	model	NOUN
ajst-26909	27	18	to	to	PART
ajst-26909	27	19	input	input	VERB
ajst-26909	27	20	changes	change	NOUN
ajst-26909	27	21	by	by	ADP
ajst-26909	27	22	downsampling	downsample	VERB
ajst-26909	27	23	the	the	DET
ajst-26909	27	24	feature	feature	NOUN
ajst-26909	27	25	map	map	NOUN
ajst-26909	27	26	.	.	PUNCT
ajst-26909	28	1	2.2	2.2	NUM
ajst-26909	28	2	.	.	PUNCT
ajst-26909	29	1	design	design	NOUN
ajst-26909	29	2	principle	principle	NOUN
ajst-26909	29	3	and	and	CCONJ
ajst-26909	29	4	typical	typical	ADJ
ajst-26909	29	5	model	model	NOUN
ajst-26909	29	6	of	of	ADP
ajst-26909	29	7	lightweight	lightweight	ADJ
ajst-26909	29	8	network	network	NOUN
ajst-26909	29	9	the	the	DET
ajst-26909	29	10	core	core	NOUN
ajst-26909	29	11	of	of	ADP
ajst-26909	29	12	lightweight	lightweight	ADJ
ajst-26909	29	13	network	network	NOUN
ajst-26909	29	14	design	design	NOUN
ajst-26909	29	15	is	be	AUX
ajst-26909	29	16	to	to	PART
ajst-26909	29	17	achieve	achieve	VERB
ajst-26909	29	18	efficient	efficient	ADJ
ajst-26909	29	19	implementation	implementation	NOUN
ajst-26909	29	20	of	of	ADP
ajst-26909	29	21	the	the	DET
ajst-26909	29	22	model	model	NOUN
ajst-26909	29	23	by	by	ADP
ajst-26909	29	24	reducing	reduce	VERB
ajst-26909	29	25	the	the	DET
ajst-26909	29	26	parameters	parameter	NOUN
ajst-26909	29	27	and	and	CCONJ
ajst-26909	29	28	computational	computational	ADJ
ajst-26909	29	29	complexity	complexity	NOUN
ajst-26909	29	30	,	,	PUNCT
ajst-26909	29	31	while	while	SCONJ
ajst-26909	29	32	striving	strive	VERB
ajst-26909	29	33	to	to	PART
ajst-26909	29	34	maintain	maintain	VERB
ajst-26909	29	35	or	or	CCONJ
ajst-26909	29	36	even	even	ADV
ajst-26909	29	37	improve	improve	VERB
ajst-26909	29	38	the	the	DET
ajst-26909	29	39	original	original	ADJ
ajst-26909	29	40	performance	performance	NOUN
ajst-26909	29	41	level	level	NOUN
ajst-26909	29	42	[	[	X
ajst-26909	29	43	7	7	NUM
ajst-26909	29	44	]	]	PUNCT
ajst-26909	29	45	.	.	PUNCT
ajst-26909	30	1	this	this	DET
ajst-26909	30	2	design	design	NOUN
ajst-26909	30	3	follows	follow	VERB
ajst-26909	30	4	several	several	ADJ
ajst-26909	30	5	key	key	ADJ
ajst-26909	30	6	principles	principle	NOUN
ajst-26909	30	7	:	:	PUNCT
ajst-26909	30	8	firstly	firstly	ADV
ajst-26909	30	9	,	,	PUNCT
ajst-26909	30	10	the	the	DET
ajst-26909	30	11	complexity	complexity	NOUN
ajst-26909	30	12	of	of	ADP
ajst-26909	30	13	the	the	DET
ajst-26909	30	14	model	model	NOUN
ajst-26909	30	15	is	be	AUX
ajst-26909	30	16	effectively	effectively	ADV
ajst-26909	30	17	reduced	reduce	VERB
ajst-26909	30	18	by	by	ADP
ajst-26909	30	19	using	use	VERB
ajst-26909	30	20	deep	deep	ADJ
ajst-26909	30	21	separable	separable	ADJ
ajst-26909	30	22	convolution	convolution	NOUN
ajst-26909	30	23	,	,	PUNCT
ajst-26909	30	24	network	network	NOUN
ajst-26909	30	25	pruning	pruning	NOUN
ajst-26909	30	26	,	,	PUNCT
ajst-26909	30	27	weight	weight	NOUN
ajst-26909	30	28	quantization	quantization	NOUN
ajst-26909	30	29	and	and	CCONJ
ajst-26909	30	30	other	other	ADJ
ajst-26909	30	31	technical	technical	ADJ
ajst-26909	30	32	means	mean	NOUN
ajst-26909	30	33	;	;	PUNCT
ajst-26909	30	34	secondly	secondly	ADV
ajst-26909	30	35	,	,	PUNCT
ajst-26909	30	36	an	an	DET
ajst-26909	30	37	efficient	efficient	ADJ
ajst-26909	30	38	network	network	NOUN
ajst-26909	30	39	structure	structure	NOUN
ajst-26909	30	40	is	be	AUX
ajst-26909	30	41	adopted	adopt	VERB
ajst-26909	30	42	to	to	PART
ajst-26909	30	43	enhance	enhance	VERB
ajst-26909	30	44	the	the	DET
ajst-26909	30	45	circulation	circulation	NOUN
ajst-26909	30	46	of	of	ADP
ajst-26909	30	47	information	information	NOUN
ajst-26909	30	48	and	and	CCONJ
ajst-26909	30	49	the	the	DET
ajst-26909	30	50	reuse	reuse	NOUN
ajst-26909	30	51	efficiency	efficiency	NOUN
ajst-26909	30	52	of	of	ADP
ajst-26909	30	53	features	feature	NOUN
ajst-26909	30	54	;	;	PUNCT
ajst-26909	30	55	finally	finally	ADV
ajst-26909	30	56	,	,	PUNCT
ajst-26909	30	57	in	in	ADP
ajst-26909	30	58	the	the	DET
ajst-26909	30	59	process	process	NOUN
ajst-26909	30	60	of	of	ADP
ajst-26909	30	61	pursuing	pursue	VERB
ajst-26909	30	62	lightweight	lightweight	NOUN
ajst-26909	30	63	,	,	PUNCT
ajst-26909	30	64	the	the	DET
ajst-26909	30	65	precision	precision	NOUN
ajst-26909	30	66	and	and	CCONJ
ajst-26909	30	67	running	run	VERB
ajst-26909	30	68	speed	speed	NOUN
ajst-26909	30	69	of	of	ADP
ajst-26909	30	70	the	the	DET
ajst-26909	30	71	model	model	NOUN
ajst-26909	30	72	are	be	AUX
ajst-26909	30	73	carefully	carefully	ADV
ajst-26909	30	74	balanced	balance	VERB
ajst-26909	30	75	.	.	PUNCT
ajst-26909	31	1	under	under	ADP
ajst-26909	31	2	this	this	DET
ajst-26909	31	3	design	design	NOUN
ajst-26909	31	4	concept	concept	NOUN
ajst-26909	31	5	,	,	PUNCT
ajst-26909	31	6	many	many	ADJ
ajst-26909	31	7	typical	typical	ADJ
ajst-26909	31	8	lightweight	lightweight	ADJ
ajst-26909	31	9	models	model	NOUN
ajst-26909	31	10	have	have	AUX
ajst-26909	31	11	emerged	emerge	VERB
ajst-26909	31	12	.	.	PUNCT
ajst-26909	32	1	mobilenetv1	mobilenetv1	PROPN
ajst-26909	32	2	creatively	creatively	ADV
ajst-26909	32	3	proposed	propose	VERB
ajst-26909	32	4	the	the	DET
ajst-26909	32	5	190	190	NUM
ajst-26909	32	6	depth	depth	NOUN
ajst-26909	32	7	separable	separable	NOUN
ajst-26909	32	8	convolution	convolution	NOUN
ajst-26909	32	9	,	,	PUNCT
ajst-26909	32	10	which	which	PRON
ajst-26909	32	11	skillfully	skillfully	ADV
ajst-26909	32	12	decomposed	decompose	VERB
ajst-26909	32	13	the	the	DET
ajst-26909	32	14	standard	standard	ADJ
ajst-26909	32	15	convolution	convolution	NOUN
ajst-26909	32	16	into	into	ADP
ajst-26909	32	17	depth	depth	NOUN
ajst-26909	32	18	convolution	convolution	NOUN
ajst-26909	32	19	and	and	CCONJ
ajst-26909	32	20	point	point	NOUN
ajst-26909	32	21	-	-	PUNCT
ajst-26909	32	22	bypoint	bypoint	NOUN
ajst-26909	32	23	convolution	convolution	NOUN
ajst-26909	32	24	.	.	PUNCT
ajst-26909	33	1	subsequently	subsequently	ADV
ajst-26909	33	2	,	,	PUNCT
ajst-26909	33	3	mobilenetv2	mobilenetv2	PROPN
ajst-26909	33	4	further	far	ADV
ajst-26909	33	5	innovated	innovate	VERB
ajst-26909	33	6	on	on	ADP
ajst-26909	33	7	this	this	DET
ajst-26909	33	8	basis	basis	NOUN
ajst-26909	33	9	,	,	PUNCT
ajst-26909	33	10	and	and	CCONJ
ajst-26909	33	11	introduced	introduce	VERB
ajst-26909	33	12	the	the	DET
ajst-26909	33	13	inverted	inverted	ADJ
ajst-26909	33	14	residual	residual	ADJ
ajst-26909	33	15	structure	structure	NOUN
ajst-26909	33	16	and	and	CCONJ
ajst-26909	33	17	linear	linear	ADJ
ajst-26909	33	18	bottleneck	bottleneck	NOUN
ajst-26909	33	19	layer	layer	NOUN
ajst-26909	33	20	,	,	PUNCT
ajst-26909	33	21	which	which	PRON
ajst-26909	33	22	significantly	significantly	ADV
ajst-26909	33	23	improved	improve	VERB
ajst-26909	33	24	the	the	DET
ajst-26909	33	25	performance	performance	NOUN
ajst-26909	33	26	.	.	PUNCT
ajst-26909	34	1	another	another	DET
ajst-26909	34	2	important	important	ADJ
ajst-26909	34	3	series	series	NOUN
ajst-26909	34	4	is	be	AUX
ajst-26909	34	5	shufflenet	shufflenet	NOUN
ajst-26909	34	6	,	,	PUNCT
ajst-26909	34	7	which	which	PRON
ajst-26909	34	8	strengthens	strengthen	VERB
ajst-26909	34	9	the	the	DET
ajst-26909	34	10	information	information	NOUN
ajst-26909	34	11	exchange	exchange	NOUN
ajst-26909	34	12	between	between	ADP
ajst-26909	34	13	different	different	ADJ
ajst-26909	34	14	channels	channel	NOUN
ajst-26909	34	15	by	by	ADP
ajst-26909	34	16	introducing	introduce	VERB
ajst-26909	34	17	channel	channel	NOUN
ajst-26909	34	18	shuffling	shuffle	VERB
ajst-26909	34	19	operation	operation	NOUN
ajst-26909	34	20	.	.	PUNCT
ajst-26909	35	1	in	in	ADP
ajst-26909	35	2	addition	addition	NOUN
ajst-26909	35	3	,	,	PUNCT
ajst-26909	35	4	efficientnet	efficientnet	ADJ
ajst-26909	35	5	series	series	NOUN
ajst-26909	35	6	is	be	AUX
ajst-26909	35	7	based	base	VERB
ajst-26909	35	8	on	on	ADP
ajst-26909	35	9	a	a	DET
ajst-26909	35	10	compound	compound	NOUN
ajst-26909	35	11	scaling	scaling	NOUN
ajst-26909	35	12	method	method	NOUN
ajst-26909	35	13	,	,	PUNCT
ajst-26909	35	14	which	which	PRON
ajst-26909	35	15	can	can	AUX
ajst-26909	35	16	maximize	maximize	VERB
ajst-26909	35	17	the	the	DET
ajst-26909	35	18	performance	performance	NOUN
ajst-26909	35	19	under	under	ADP
ajst-26909	35	20	the	the	DET
ajst-26909	35	21	condition	condition	NOUN
ajst-26909	35	22	of	of	ADP
ajst-26909	35	23	limited	limited	ADJ
ajst-26909	35	24	resources	resource	NOUN
ajst-26909	35	25	by	by	ADP
ajst-26909	35	26	adjusting	adjust	VERB
ajst-26909	35	27	the	the	DET
ajst-26909	35	28	depth	depth	NOUN
ajst-26909	35	29	,	,	PUNCT
ajst-26909	35	30	width	width	ADJ
ajst-26909	35	31	and	and	CCONJ
ajst-26909	35	32	resolution	resolution	NOUN
ajst-26909	35	33	of	of	ADP
ajst-26909	35	34	the	the	DET
ajst-26909	35	35	network	network	NOUN
ajst-26909	35	36	at	at	ADP
ajst-26909	35	37	the	the	DET
ajst-26909	35	38	same	same	ADJ
ajst-26909	35	39	time	time	NOUN
ajst-26909	35	40	.	.	PUNCT
ajst-26909	36	1	2.3	2.3	NUM
ajst-26909	36	2	.	.	PUNCT
ajst-26909	36	3	overview	overview	NOUN
ajst-26909	36	4	of	of	ADP
ajst-26909	36	5	target	target	NOUN
ajst-26909	36	6	detection	detection	NOUN
ajst-26909	36	7	algorithms	algorithm	VERB
ajst-26909	36	8	traditional	traditional	ADJ
ajst-26909	36	9	target	target	NOUN
ajst-26909	36	10	detection	detection	NOUN
ajst-26909	36	11	methods	method	NOUN
ajst-26909	36	12	mainly	mainly	ADV
ajst-26909	36	13	rely	rely	VERB
ajst-26909	36	14	on	on	ADP
ajst-26909	36	15	manually	manually	ADV
ajst-26909	36	16	designed	design	VERB
ajst-26909	36	17	features	feature	NOUN
ajst-26909	36	18	and	and	CCONJ
ajst-26909	36	19	classifiers	classifier	NOUN
ajst-26909	36	20	.	.	PUNCT
ajst-26909	37	1	for	for	ADP
ajst-26909	37	2	example	example	NOUN
ajst-26909	37	3	,	,	PUNCT
ajst-26909	37	4	the	the	DET
ajst-26909	37	5	pedestrian	pedestrian	NOUN
ajst-26909	37	6	detection	detection	NOUN
ajst-26909	37	7	method	method	NOUN
ajst-26909	37	8	using	use	VERB
ajst-26909	37	9	hog	hog	NOUN
ajst-26909	37	10	features	feature	NOUN
ajst-26909	37	11	combined	combine	VERB
ajst-26909	37	12	with	with	ADP
ajst-26909	37	13	svm	svm	ADJ
ajst-26909	37	14	classifier	classifier	NOUN
ajst-26909	37	15	and	and	CCONJ
ajst-26909	37	16	the	the	DET
ajst-26909	37	17	application	application	NOUN
ajst-26909	37	18	of	of	ADP
ajst-26909	37	19	adaboost	adaboost	ADJ
ajst-26909	37	20	classifier	classifier	NOUN
ajst-26909	37	21	based	base	VERB
ajst-26909	37	22	on	on	ADP
ajst-26909	37	23	haar	haar	PROPN
ajst-26909	37	24	features	feature	NOUN
ajst-26909	37	25	in	in	ADP
ajst-26909	37	26	face	face	NOUN
ajst-26909	37	27	detection	detection	NOUN
ajst-26909	37	28	[	[	X
ajst-26909	37	29	8	8	NUM
ajst-26909	37	30	]	]	PUNCT
ajst-26909	37	31	.	.	PUNCT
ajst-26909	38	1	with	with	ADP
ajst-26909	38	2	the	the	DET
ajst-26909	38	3	rise	rise	NOUN
ajst-26909	38	4	of	of	ADP
ajst-26909	38	5	deep	deep	ADJ
ajst-26909	38	6	learning	learning	NOUN
ajst-26909	38	7	,	,	PUNCT
ajst-26909	38	8	the	the	DET
ajst-26909	38	9	target	target	NOUN
ajst-26909	38	10	detection	detection	NOUN
ajst-26909	38	11	algorithm	algorithm	NOUN
ajst-26909	38	12	has	have	AUX
ajst-26909	38	13	ushered	usher	VERB
ajst-26909	38	14	in	in	ADP
ajst-26909	38	15	a	a	DET
ajst-26909	38	16	new	new	ADJ
ajst-26909	38	17	breakthrough	breakthrough	NOUN
ajst-26909	38	18	.	.	PUNCT
ajst-26909	39	1	among	among	ADP
ajst-26909	39	2	them	they	PRON
ajst-26909	39	3	,	,	PUNCT
ajst-26909	39	4	r	r	X
ajst-26909	39	5	-	-	PUNCT
ajst-26909	39	6	cnn	cnn	PROPN
ajst-26909	39	7	series	series	PROPN
ajst-26909	39	8	algorithm	algorithm	PROPN
ajst-26909	39	9	is	be	AUX
ajst-26909	39	10	the	the	DET
ajst-26909	39	11	first	first	ADJ
ajst-26909	39	12	algorithm	algorithm	NOUN
ajst-26909	39	13	to	to	PART
ajst-26909	39	14	apply	apply	VERB
ajst-26909	39	15	cnn	cnn	PROPN
ajst-26909	39	16	to	to	PART
ajst-26909	39	17	target	target	VERB
ajst-26909	39	18	detection	detection	NOUN
ajst-26909	39	19	.	.	PUNCT
ajst-26909	40	1	by	by	ADP
ajst-26909	40	2	extracting	extract	VERB
ajst-26909	40	3	candidate	candidate	NOUN
ajst-26909	40	4	regions	region	NOUN
ajst-26909	40	5	and	and	CCONJ
ajst-26909	40	6	using	use	VERB
ajst-26909	40	7	cnn	cnn	PROPN
ajst-26909	40	8	for	for	ADP
ajst-26909	40	9	feature	feature	NOUN
ajst-26909	40	10	extraction	extraction	NOUN
ajst-26909	40	11	and	and	CCONJ
ajst-26909	40	12	classification	classification	NOUN
ajst-26909	40	13	,	,	PUNCT
ajst-26909	40	14	r	r	X
ajst-26909	40	15	-	-	PUNCT
ajst-26909	40	16	cnn	cnn	PROPN
ajst-26909	40	17	has	have	AUX
ajst-26909	40	18	achieved	achieve	VERB
ajst-26909	40	19	high	high	ADJ
ajst-26909	40	20	detection	detection	NOUN
ajst-26909	40	21	accuracy	accuracy	NOUN
ajst-26909	40	22	.	.	PUNCT
ajst-26909	41	1	subsequently	subsequently	ADV
ajst-26909	41	2	,	,	PUNCT
ajst-26909	41	3	fast	fast	ADJ
ajst-26909	41	4	r	r	NOUN
ajst-26909	41	5	-	-	PUNCT
ajst-26909	41	6	cnn	cnn	PROPN
ajst-26909	41	7	,	,	PUNCT
ajst-26909	41	8	fast	fast	ADJ
ajst-26909	41	9	rcnn	rcnn	NOUN
ajst-26909	41	10	and	and	CCONJ
ajst-26909	41	11	other	other	ADJ
ajst-26909	41	12	algorithms	algorithm	NOUN
ajst-26909	41	13	further	far	ADV
ajst-26909	41	14	optimized	optimize	VERB
ajst-26909	41	15	the	the	DET
ajst-26909	41	16	detection	detection	NOUN
ajst-26909	41	17	process	process	NOUN
ajst-26909	41	18	and	and	CCONJ
ajst-26909	41	19	speed	speed	NOUN
ajst-26909	41	20	,	,	PUNCT
ajst-26909	41	21	making	make	VERB
ajst-26909	41	22	the	the	DET
ajst-26909	41	23	target	target	NOUN
ajst-26909	41	24	detection	detection	NOUN
ajst-26909	41	25	method	method	NOUN
ajst-26909	41	26	based	base	VERB
ajst-26909	41	27	on	on	ADP
ajst-26909	41	28	deep	deep	ADJ
ajst-26909	41	29	learning	learn	VERB
ajst-26909	41	30	more	more	ADV
ajst-26909	41	31	efficient	efficient	ADJ
ajst-26909	41	32	in	in	ADP
ajst-26909	41	33	practical	practical	ADJ
ajst-26909	41	34	application	application	NOUN
ajst-26909	41	35	.	.	PUNCT
ajst-26909	42	1	in	in	ADP
ajst-26909	42	2	addition	addition	NOUN
ajst-26909	42	3	to	to	ADP
ajst-26909	42	4	r	r	NOUN
ajst-26909	42	5	-	-	PUNCT
ajst-26909	42	6	cnn	cnn	PROPN
ajst-26909	42	7	series	series	NOUN
ajst-26909	42	8	,	,	PUNCT
ajst-26909	42	9	yolo	yolo	ADJ
ajst-26909	42	10	series	series	PROPN
ajst-26909	42	11	algorithms	algorithm	NOUN
ajst-26909	42	12	have	have	AUX
ajst-26909	42	13	also	also	ADV
ajst-26909	42	14	received	receive	VERB
ajst-26909	42	15	extensive	extensive	ADJ
ajst-26909	42	16	attention	attention	NOUN
ajst-26909	42	17	.	.	PUNCT
ajst-26909	43	1	yolo	yolo	PROPN
ajst-26909	43	2	is	be	AUX
ajst-26909	43	3	a	a	DET
ajst-26909	43	4	single	single	ADJ
ajst-26909	43	5	-	-	PUNCT
ajst-26909	43	6	stage	stage	NOUN
ajst-26909	43	7	detection	detection	NOUN
ajst-26909	43	8	algorithm	algorithm	NOUN
ajst-26909	43	9	,	,	PUNCT
ajst-26909	43	10	which	which	PRON
ajst-26909	43	11	transforms	transform	VERB
ajst-26909	43	12	the	the	DET
ajst-26909	43	13	target	target	NOUN
ajst-26909	43	14	detection	detection	NOUN
ajst-26909	43	15	task	task	NOUN
ajst-26909	43	16	into	into	ADP
ajst-26909	43	17	a	a	DET
ajst-26909	43	18	single	single	ADJ
ajst-26909	43	19	forward	forward	ADJ
ajst-26909	43	20	propagation	propagation	NOUN
ajst-26909	43	21	problem	problem	NOUN
ajst-26909	43	22	,	,	PUNCT
ajst-26909	43	23	thus	thus	ADV
ajst-26909	43	24	realizing	realize	VERB
ajst-26909	43	25	real	real	ADJ
ajst-26909	43	26	-	-	PUNCT
ajst-26909	43	27	time	time	NOUN
ajst-26909	43	28	detection	detection	NOUN
ajst-26909	43	29	.	.	PUNCT
ajst-26909	44	1	with	with	ADP
ajst-26909	44	2	the	the	DET
ajst-26909	44	3	introduction	introduction	NOUN
ajst-26909	44	4	of	of	ADP
ajst-26909	44	5	yolov3	yolov3	PROPN
ajst-26909	44	6	,	,	PUNCT
ajst-26909	44	7	yolov4	yolov4	PROPN
ajst-26909	44	8	and	and	CCONJ
ajst-26909	44	9	other	other	ADJ
ajst-26909	44	10	subsequent	subsequent	ADJ
ajst-26909	44	11	versions	version	NOUN
ajst-26909	44	12	,	,	PUNCT
ajst-26909	44	13	the	the	DET
ajst-26909	44	14	detection	detection	NOUN
ajst-26909	44	15	accuracy	accuracy	NOUN
ajst-26909	44	16	and	and	CCONJ
ajst-26909	44	17	speed	speed	NOUN
ajst-26909	44	18	of	of	ADP
ajst-26909	44	19	yolo	yolo	ADJ
ajst-26909	44	20	series	series	NOUN
ajst-26909	44	21	algorithms	algorithm	NOUN
ajst-26909	44	22	have	have	AUX
ajst-26909	44	23	been	be	AUX
ajst-26909	44	24	further	far	ADV
ajst-26909	44	25	improved	improve	VERB
ajst-26909	44	26	by	by	ADP
ajst-26909	44	27	introducing	introduce	VERB
ajst-26909	44	28	more	more	ADV
ajst-26909	44	29	advanced	advanced	ADJ
ajst-26909	44	30	network	network	NOUN
ajst-26909	44	31	structure	structure	NOUN
ajst-26909	44	32	and	and	CCONJ
ajst-26909	44	33	optimization	optimization	NOUN
ajst-26909	44	34	strategy	strategy	NOUN
ajst-26909	44	35	.	.	PUNCT
ajst-26909	45	1	in	in	ADP
ajst-26909	45	2	addition	addition	NOUN
ajst-26909	45	3	,	,	PUNCT
ajst-26909	45	4	ssd(single	ssd(single	NUM
ajst-26909	45	5	shot	shot	NOUN
ajst-26909	45	6	multibox	multibox	NOUN
ajst-26909	45	7	detector	detector	NOUN
ajst-26909	45	8	)	)	PUNCT
ajst-26909	45	9	is	be	AUX
ajst-26909	45	10	also	also	ADV
ajst-26909	45	11	an	an	DET
ajst-26909	45	12	important	important	ADJ
ajst-26909	45	13	single	single	ADJ
ajst-26909	45	14	-	-	PUNCT
ajst-26909	45	15	phase	phase	NOUN
ajst-26909	45	16	detection	detection	NOUN
ajst-26909	45	17	algorithm	algorithm	NOUN
ajst-26909	45	18	.	.	PUNCT
ajst-26909	46	1	it	it	PRON
ajst-26909	46	2	realizes	realize	VERB
ajst-26909	46	3	highprecision	highprecision	NOUN
ajst-26909	46	4	target	target	NOUN
ajst-26909	46	5	detection	detection	NOUN
ajst-26909	46	6	by	by	ADP
ajst-26909	46	7	predicting	predict	VERB
ajst-26909	46	8	the	the	DET
ajst-26909	46	9	position	position	NOUN
ajst-26909	46	10	and	and	CCONJ
ajst-26909	46	11	category	category	NOUN
ajst-26909	46	12	of	of	ADP
ajst-26909	46	13	targets	target	NOUN
ajst-26909	46	14	on	on	ADP
ajst-26909	46	15	feature	feature	NOUN
ajst-26909	46	16	maps	map	NOUN
ajst-26909	46	17	of	of	ADP
ajst-26909	46	18	different	different	ADJ
ajst-26909	46	19	scales	scale	NOUN
ajst-26909	46	20	.	.	PUNCT
ajst-26909	47	1	the	the	DET
ajst-26909	47	2	design	design	NOUN
ajst-26909	47	3	of	of	ADP
ajst-26909	47	4	ssd	ssd	NOUN
ajst-26909	47	5	algorithm	algorithm	NOUN
ajst-26909	47	6	enables	enable	VERB
ajst-26909	47	7	it	it	PRON
ajst-26909	47	8	to	to	PART
ajst-26909	47	9	perform	perform	VERB
ajst-26909	47	10	well	well	ADV
ajst-26909	47	11	in	in	ADP
ajst-26909	47	12	complex	complex	ADJ
ajst-26909	47	13	scenes	scene	NOUN
ajst-26909	47	14	,	,	PUNCT
ajst-26909	47	15	which	which	PRON
ajst-26909	47	16	further	far	ADV
ajst-26909	47	17	promotes	promote	VERB
ajst-26909	47	18	the	the	DET
ajst-26909	47	19	development	development	NOUN
ajst-26909	47	20	of	of	ADP
ajst-26909	47	21	target	target	NOUN
ajst-26909	47	22	detection	detection	NOUN
ajst-26909	47	23	technology	technology	NOUN
ajst-26909	47	24	.	.	PUNCT
ajst-26909	48	1	3	3	X
ajst-26909	48	2	.	.	X
ajst-26909	48	3	application	application	NOUN
ajst-26909	48	4	and	and	CCONJ
ajst-26909	48	5	optimization	optimization	NOUN
ajst-26909	48	6	of	of	ADP
ajst-26909	48	7	lcnn	lcnn	NOUN
ajst-26909	48	8	the	the	DET
ajst-26909	48	9	application	application	NOUN
ajst-26909	48	10	of	of	ADP
ajst-26909	48	11	lightweight	lightweight	ADJ
ajst-26909	48	12	network	network	NOUN
ajst-26909	48	13	in	in	ADP
ajst-26909	48	14	the	the	DET
ajst-26909	48	15	field	field	NOUN
ajst-26909	48	16	of	of	ADP
ajst-26909	48	17	target	target	NOUN
ajst-26909	48	18	detection	detection	NOUN
ajst-26909	48	19	aims	aim	VERB
ajst-26909	48	20	to	to	PART
ajst-26909	48	21	achieve	achieve	VERB
ajst-26909	48	22	a	a	DET
ajst-26909	48	23	key	key	ADJ
ajst-26909	48	24	balance	balance	NOUN
ajst-26909	48	25	by	by	ADP
ajst-26909	48	26	finely	finely	ADV
ajst-26909	48	27	optimizing	optimize	VERB
ajst-26909	48	28	the	the	DET
ajst-26909	48	29	network	network	NOUN
ajst-26909	48	30	structure	structure	NOUN
ajst-26909	48	31	and	and	CCONJ
ajst-26909	48	32	parameter	parameter	NOUN
ajst-26909	48	33	configuration	configuration	NOUN
ajst-26909	48	34	,	,	PUNCT
ajst-26909	48	35	that	that	ADV
ajst-26909	48	36	is	is	ADV
ajst-26909	48	37	,	,	PUNCT
ajst-26909	48	38	to	to	PART
ajst-26909	48	39	greatly	greatly	ADV
ajst-26909	48	40	reduce	reduce	VERB
ajst-26909	48	41	the	the	DET
ajst-26909	48	42	computational	computational	ADJ
ajst-26909	48	43	complexity	complexity	NOUN
ajst-26909	48	44	and	and	CCONJ
ajst-26909	48	45	storage	storage	NOUN
ajst-26909	48	46	requirements	requirement	NOUN
ajst-26909	48	47	while	while	SCONJ
ajst-26909	48	48	maintaining	maintain	VERB
ajst-26909	48	49	a	a	DET
ajst-26909	48	50	high	high	ADJ
ajst-26909	48	51	level	level	NOUN
ajst-26909	48	52	of	of	ADP
ajst-26909	48	53	detection	detection	NOUN
ajst-26909	48	54	accuracy	accuracy	NOUN
ajst-26909	48	55	.	.	PUNCT
ajst-26909	49	1	in	in	ADP
ajst-26909	49	2	view	view	NOUN
ajst-26909	49	3	of	of	ADP
ajst-26909	49	4	the	the	DET
ajst-26909	49	5	particularity	particularity	NOUN
ajst-26909	49	6	of	of	ADP
ajst-26909	49	7	target	target	NOUN
ajst-26909	49	8	detection	detection	NOUN
ajst-26909	49	9	task	task	NOUN
ajst-26909	49	10	,	,	PUNCT
ajst-26909	49	11	designers	designer	NOUN
ajst-26909	49	12	carefully	carefully	ADV
ajst-26909	49	13	construct	construct	VERB
ajst-26909	49	14	an	an	DET
ajst-26909	49	15	efficient	efficient	ADJ
ajst-26909	49	16	network	network	NOUN
ajst-26909	49	17	architecture	architecture	NOUN
ajst-26909	49	18	,	,	PUNCT
ajst-26909	49	19	aiming	aim	VERB
ajst-26909	49	20	at	at	ADP
ajst-26909	49	21	capturing	capture	VERB
ajst-26909	49	22	key	key	ADJ
ajst-26909	49	23	image	image	NOUN
ajst-26909	49	24	features	feature	NOUN
ajst-26909	49	25	with	with	ADP
ajst-26909	49	26	less	less	ADJ
ajst-26909	49	27	computing	compute	VERB
ajst-26909	49	28	resources	resource	NOUN
ajst-26909	49	29	.	.	PUNCT
ajst-26909	50	1	by	by	ADP
ajst-26909	50	2	generating	generate	VERB
ajst-26909	50	3	feature	feature	NOUN
ajst-26909	50	4	maps	map	NOUN
ajst-26909	50	5	at	at	ADP
ajst-26909	50	6	different	different	ADJ
ajst-26909	50	7	levels	level	NOUN
ajst-26909	50	8	of	of	ADP
ajst-26909	50	9	the	the	DET
ajst-26909	50	10	network	network	NOUN
ajst-26909	50	11	and	and	CCONJ
ajst-26909	50	12	predicting	predict	VERB
ajst-26909	50	13	targets	target	NOUN
ajst-26909	50	14	on	on	ADP
ajst-26909	50	15	these	these	DET
ajst-26909	50	16	feature	feature	NOUN
ajst-26909	50	17	maps	map	NOUN
ajst-26909	50	18	respectively	respectively	ADV
ajst-26909	50	19	,	,	PUNCT
ajst-26909	50	20	the	the	DET
ajst-26909	50	21	detection	detection	NOUN
ajst-26909	50	22	ability	ability	NOUN
ajst-26909	50	23	of	of	ADP
ajst-26909	50	24	the	the	DET
ajst-26909	50	25	algorithm	algorithm	NOUN
ajst-26909	50	26	for	for	ADP
ajst-26909	50	27	various	various	ADJ
ajst-26909	50	28	sizes	size	NOUN
ajst-26909	50	29	of	of	ADP
ajst-26909	50	30	targets	target	NOUN
ajst-26909	50	31	can	can	AUX
ajst-26909	50	32	be	be	AUX
ajst-26909	50	33	significantly	significantly	ADV
ajst-26909	50	34	improved	improve	VERB
ajst-26909	50	35	,	,	PUNCT
ajst-26909	50	36	and	and	CCONJ
ajst-26909	50	37	the	the	DET
ajst-26909	50	38	comprehensiveness	comprehensiveness	NOUN
ajst-26909	50	39	and	and	CCONJ
ajst-26909	50	40	accuracy	accuracy	NOUN
ajst-26909	50	41	of	of	ADP
ajst-26909	50	42	detection	detection	NOUN
ajst-26909	50	43	can	can	AUX
ajst-26909	50	44	be	be	AUX
ajst-26909	50	45	ensured	ensure	VERB
ajst-26909	50	46	.	.	PUNCT
ajst-26909	51	1	drawing	draw	VERB
ajst-26909	51	2	lessons	lesson	NOUN
ajst-26909	51	3	from	from	ADP
ajst-26909	51	4	advanced	advanced	ADJ
ajst-26909	51	5	algorithms	algorithm	NOUN
ajst-26909	51	6	such	such	ADJ
ajst-26909	51	7	as	as	ADP
ajst-26909	51	8	faster	fast	ADJ
ajst-26909	51	9	rcnn	rcnn	NOUN
ajst-26909	51	10	,	,	PUNCT
ajst-26909	51	11	a	a	DET
ajst-26909	51	12	group	group	NOUN
ajst-26909	51	13	of	of	ADP
ajst-26909	51	14	anchor	anchor	NOUN
ajst-26909	51	15	frames	frame	NOUN
ajst-26909	51	16	with	with	ADP
ajst-26909	51	17	different	different	ADJ
ajst-26909	51	18	scales	scale	NOUN
ajst-26909	51	19	and	and	CCONJ
ajst-26909	51	20	aspect	aspect	NOUN
ajst-26909	51	21	ratios	ratio	NOUN
ajst-26909	51	22	are	be	AUX
ajst-26909	51	23	preset	preset	ADJ
ajst-26909	51	24	.	.	PUNCT
ajst-26909	52	1	then	then	ADV
ajst-26909	52	2	,	,	PUNCT
ajst-26909	52	3	through	through	ADP
ajst-26909	52	4	fine	fine	ADJ
ajst-26909	52	5	regression	regression	NOUN
ajst-26909	52	6	adjustment	adjustment	NOUN
ajst-26909	52	7	,	,	PUNCT
ajst-26909	52	8	the	the	DET
ajst-26909	52	9	detection	detection	NOUN
ajst-26909	52	10	frame	frame	NOUN
ajst-26909	52	11	fits	fit	VERB
ajst-26909	52	12	the	the	DET
ajst-26909	52	13	actual	actual	ADJ
ajst-26909	52	14	target	target	NOUN
ajst-26909	52	15	contour	contour	NOUN
ajst-26909	52	16	better	well	ADV
ajst-26909	52	17	.	.	PUNCT
ajst-26909	53	1	after	after	SCONJ
ajst-26909	53	2	the	the	DET
ajst-26909	53	3	initial	initial	ADJ
ajst-26909	53	4	detection	detection	NOUN
ajst-26909	53	5	frame	frame	NOUN
ajst-26909	53	6	is	be	AUX
ajst-26909	53	7	obtained	obtain	VERB
ajst-26909	53	8	,	,	PUNCT
ajst-26909	53	9	efficient	efficient	ADJ
ajst-26909	53	10	post	post	ADJ
ajst-26909	53	11	-	-	ADJ
ajst-26909	53	12	processing	processing	ADJ
ajst-26909	53	13	means	mean	NOUN
ajst-26909	53	14	such	such	ADJ
ajst-26909	53	15	as	as	ADP
ajst-26909	53	16	non	non	ADJ
ajst-26909	53	17	-	-	ADJ
ajst-26909	53	18	maximum	maximum	ADJ
ajst-26909	53	19	suppression	suppression	NOUN
ajst-26909	53	20	(	(	PUNCT
ajst-26909	53	21	nms	nms	NOUN
ajst-26909	53	22	)	)	PUNCT
ajst-26909	53	23	can	can	AUX
ajst-26909	53	24	effectively	effectively	ADV
ajst-26909	53	25	eliminate	eliminate	VERB
ajst-26909	53	26	duplicate	duplicate	NOUN
ajst-26909	53	27	and	and	CCONJ
ajst-26909	53	28	redundant	redundant	ADJ
ajst-26909	53	29	detection	detection	NOUN
ajst-26909	53	30	frames	frame	NOUN
ajst-26909	53	31	,	,	PUNCT
ajst-26909	53	32	and	and	CCONJ
ajst-26909	53	33	ensure	ensure	VERB
ajst-26909	53	34	that	that	SCONJ
ajst-26909	53	35	the	the	DET
ajst-26909	53	36	output	output	NOUN
ajst-26909	53	37	results	result	NOUN
ajst-26909	53	38	are	be	AUX
ajst-26909	53	39	concise	concise	ADJ
ajst-26909	53	40	and	and	CCONJ
ajst-26909	53	41	accurate	accurate	ADJ
ajst-26909	53	42	.	.	PUNCT
ajst-26909	54	1	figure	figure	NOUN
ajst-26909	54	2	1	1	NUM
ajst-26909	54	3	shows	show	VERB
ajst-26909	54	4	the	the	DET
ajst-26909	54	5	basic	basic	ADJ
ajst-26909	54	6	structure	structure	NOUN
ajst-26909	54	7	of	of	ADP
ajst-26909	54	8	lcnn	lcnn	PROPN
ajst-26909	54	9	.	.	PUNCT
ajst-26909	55	1	figure	figure	NOUN
ajst-26909	55	2	1	1	NUM
ajst-26909	55	3	.	.	PUNCT
ajst-26909	55	4	lcnn	lcnn	PROPN
ajst-26909	55	5	in	in	ADP
ajst-26909	55	6	cnn	cnn	PROPN
ajst-26909	55	7	architecture	architecture	NOUN
ajst-26909	55	8	,	,	PUNCT
ajst-26909	55	9	neurons	neuron	NOUN
ajst-26909	55	10	serve	serve	VERB
ajst-26909	55	11	as	as	ADP
ajst-26909	55	12	the	the	DET
ajst-26909	55	13	fundamental	fundamental	ADJ
ajst-26909	55	14	processing	processing	NOUN
ajst-26909	55	15	units	unit	NOUN
ajst-26909	55	16	tasked	task	VERB
ajst-26909	55	17	with	with	ADP
ajst-26909	55	18	computation	computation	NOUN
ajst-26909	55	19	.	.	PUNCT
ajst-26909	56	1	for	for	ADP
ajst-26909	56	2	those	those	DET
ajst-26909	56	3	neurons	neuron	NOUN
ajst-26909	56	4	possessing	possess	VERB
ajst-26909	56	5	an	an	DET
ajst-26909	56	6	321	321	NUM
ajst-26909	56	7	,	,	PUNCT
ajst-26909	56	8	,	,	PUNCT
ajst-26909	56	9	xxx	xxx	ADJ
ajst-26909	56	10	input	input	NOUN
ajst-26909	56	11	dimension	dimension	NOUN
ajst-26909	56	12	,	,	PUNCT
ajst-26909	56	13	their	their	PRON
ajst-26909	56	14	output	output	NOUN
ajst-26909	56	15	is	be	AUX
ajst-26909	56	16	determined	determine	VERB
ajst-26909	56	17	through	through	ADP
ajst-26909	56	18	the	the	DET
ajst-26909	56	19	interaction	interaction	NOUN
ajst-26909	56	20	of	of	ADP
ajst-26909	56	21	a	a	DET
ajst-26909	56	22	designated	designate	VERB
ajst-26909	56	23	convolution	convolution	NOUN
ajst-26909	56	24	kernel	kernel	NOUN
ajst-26909	56	25	(	(	PUNCT
ajst-26909	56	26	or	or	CCONJ
ajst-26909	56	27	filter	filter	NOUN
ajst-26909	56	28	)	)	PUNCT
ajst-26909	56	29	with	with	ADP
ajst-26909	56	30	the	the	DET
ajst-26909	56	31	input	input	NOUN
ajst-26909	56	32	data	datum	NOUN
ajst-26909	56	33	.	.	PUNCT
ajst-26909	57	1			NOUN
ajst-26909	58	1			PROPN
ajst-26909	58	2			NOUN
ajst-26909	58	3			PUNCT
ajst-26909	58	4			PROPN
ajst-26909	58	5			NUM
ajst-26909	58	6			PRON
ajst-26909	58	7			PROPN
ajst-26909	58	8			PROPN
ajst-26909	58	9			NOUN
ajst-26909	58	10			NUM
ajst-26909	58	11			X
ajst-26909	58	12			NOUN
ajst-26909	58	13	3	3	NUM
ajst-26909	58	14	1	1	NUM
ajst-26909	58	15	,	,	PUNCT
ajst-26909	58	16	i	i	PRON
ajst-26909	58	17	iii	iii	VERB
ajst-26909	58	18	t	t	NOUN
ajst-26909	58	19	bw	bw	NOUN
ajst-26909	58	20	bxwfxwfxy	bxwfxwfxy	NOUN
ajst-26909	58	21	(	(	PUNCT
ajst-26909	58	22	1	1	X
ajst-26909	58	23	)	)	PUNCT
ajst-26909	58	24	in	in	ADP
ajst-26909	58	25	this	this	DET
ajst-26909	58	26	context	context	NOUN
ajst-26909	58	27	,	,	PUNCT
ajst-26909	58	28	iw	iw	PROPN
ajst-26909	58	29	denotes	denote	VERB
ajst-26909	58	30	the	the	DET
ajst-26909	58	31	weight	weight	NOUN
ajst-26909	58	32	value	value	NOUN
ajst-26909	58	33	assigned	assign	VERB
ajst-26909	58	34	to	to	ADP
ajst-26909	58	35	each	each	DET
ajst-26909	58	36	node	node	NOUN
ajst-26909	58	37	,	,	PUNCT
ajst-26909	58	38	while	while	SCONJ
ajst-26909	58	39	ib	ib	NOUN
ajst-26909	58	40	signifies	signify	VERB
ajst-26909	58	41	the	the	DET
ajst-26909	58	42	bias	bias	NOUN
ajst-26909	58	43	constant	constant	ADJ
ajst-26909	58	44	.	.	PUNCT
ajst-26909	59	1	neurons	neuron	NOUN
ajst-26909	59	2	have	have	VERB
ajst-26909	59	3	the	the	DET
ajst-26909	59	4	capability	capability	NOUN
ajst-26909	59	5	to	to	PART
ajst-26909	59	6	interconnect	interconnect	VERB
ajst-26909	59	7	,	,	PUNCT
ajst-26909	59	8	thereby	thereby	ADV
ajst-26909	59	9	constituting	constitute	VERB
ajst-26909	59	10	a	a	DET
ajst-26909	59	11	neural	neural	ADJ
ajst-26909	59	12	network	network	NOUN
ajst-26909	59	13	.	.	PUNCT
ajst-26909	60	1	aiming	aim	VERB
ajst-26909	60	2	at	at	ADP
ajst-26909	60	3	the	the	DET
ajst-26909	60	4	optimization	optimization	NOUN
ajst-26909	60	5	of	of	ADP
ajst-26909	60	6	network	network	NOUN
ajst-26909	60	7	structure	structure	NOUN
ajst-26909	60	8	,	,	PUNCT
ajst-26909	60	9	the	the	DET
ajst-26909	60	10	introduction	introduction	NOUN
ajst-26909	60	11	of	of	ADP
ajst-26909	60	12	deep	deep	ADJ
ajst-26909	60	13	separable	separable	ADJ
ajst-26909	60	14	convolution	convolution	NOUN
ajst-26909	60	15	can	can	AUX
ajst-26909	60	16	significantly	significantly	ADV
ajst-26909	60	17	reduce	reduce	VERB
ajst-26909	60	18	the	the	DET
ajst-26909	60	19	amount	amount	NOUN
ajst-26909	60	20	of	of	ADP
ajst-26909	60	21	calculation	calculation	NOUN
ajst-26909	60	22	and	and	CCONJ
ajst-26909	60	23	parameters	parameter	NOUN
ajst-26909	60	24	.	.	PUNCT
ajst-26909	61	1	at	at	ADP
ajst-26909	61	2	the	the	DET
ajst-26909	61	3	same	same	ADJ
ajst-26909	61	4	time	time	NOUN
ajst-26909	61	5	,	,	PUNCT
ajst-26909	61	6	feature	feature	NOUN
ajst-26909	61	7	fusion	fusion	NOUN
ajst-26909	61	8	and	and	CCONJ
ajst-26909	61	9	enhancement	enhancement	NOUN
ajst-26909	61	10	strategies	strategy	NOUN
ajst-26909	61	11	,	,	PUNCT
ajst-26909	61	12	such	such	ADJ
ajst-26909	61	13	as	as	ADP
ajst-26909	61	14	splicing	splice	VERB
ajst-26909	61	15	different	different	ADJ
ajst-26909	61	16	levels	level	NOUN
ajst-26909	61	17	of	of	ADP
ajst-26909	61	18	feature	feature	NOUN
ajst-26909	61	19	maps	map	NOUN
ajst-26909	61	20	or	or	CCONJ
ajst-26909	61	21	introducing	introduce	VERB
ajst-26909	61	22	attention	attention	NOUN
ajst-26909	61	23	mechanism	mechanism	NOUN
ajst-26909	61	24	,	,	PUNCT
ajst-26909	61	25	further	far	ADV
ajst-26909	61	26	improve	improve	VERB
ajst-26909	61	27	the	the	DET
ajst-26909	61	28	feature	feature	NOUN
ajst-26909	61	29	expression	expression	NOUN
ajst-26909	61	30	ability	ability	NOUN
ajst-26909	61	31	of	of	ADP
ajst-26909	61	32	lightweight	lightweight	ADJ
ajst-26909	61	33	networks	network	NOUN
ajst-26909	61	34	.	.	PUNCT
ajst-26909	62	1	dynamically	dynamically	ADV
ajst-26909	62	2	adjust	adjust	VERB
ajst-26909	62	3	the	the	DET
ajst-26909	62	4	191	191	NUM
ajst-26909	62	5	network	network	NOUN
ajst-26909	62	6	structure	structure	NOUN
ajst-26909	62	7	according	accord	VERB
ajst-26909	62	8	to	to	ADP
ajst-26909	62	9	the	the	DET
ajst-26909	62	10	complexity	complexity	NOUN
ajst-26909	62	11	of	of	ADP
ajst-26909	62	12	the	the	DET
ajst-26909	62	13	input	input	NOUN
ajst-26909	62	14	image	image	NOUN
ajst-26909	62	15	and	and	CCONJ
ajst-26909	62	16	the	the	DET
ajst-26909	62	17	change	change	NOUN
ajst-26909	62	18	of	of	ADP
ajst-26909	62	19	the	the	DET
ajst-26909	62	20	target	target	NOUN
ajst-26909	62	21	scale	scale	NOUN
ajst-26909	62	22	,	,	PUNCT
ajst-26909	62	23	and	and	CCONJ
ajst-26909	62	24	realize	realize	VERB
ajst-26909	62	25	the	the	DET
ajst-26909	62	26	reasonable	reasonable	ADJ
ajst-26909	62	27	allocation	allocation	NOUN
ajst-26909	62	28	of	of	ADP
ajst-26909	62	29	computing	compute	VERB
ajst-26909	62	30	resources	resource	NOUN
ajst-26909	62	31	.	.	PUNCT
ajst-26909	63	1	this	this	DET
ajst-26909	63	2	study	study	NOUN
ajst-26909	63	3	employs	employ	VERB
ajst-26909	63	4	the	the	DET
ajst-26909	63	5	adam	adam	PROPN
ajst-26909	63	6	optimization	optimization	NOUN
ajst-26909	63	7	algorithm	algorithm	NOUN
ajst-26909	63	8	for	for	ADP
ajst-26909	63	9	updating	update	VERB
ajst-26909	63	10	network	network	NOUN
ajst-26909	63	11	parameters	parameter	NOUN
ajst-26909	63	12	,	,	PUNCT
ajst-26909	63	13	with	with	ADP
ajst-26909	63	14	the	the	DET
ajst-26909	63	15	following	follow	VERB
ajst-26909	63	16	update	update	NOUN
ajst-26909	63	17	rules	rule	NOUN
ajst-26909	63	18	:	:	PUNCT
ajst-26909	63	19			PROPN
ajst-26909	63	20			NOUN
ajst-26909	63	21			X
ajst-26909	63	22	jtt	jtt	PROPN
ajst-26909	63	23			VERB
ajst-26909	63	24	1	1	ADJ
ajst-26909	63	25	(	(	PUNCT
ajst-26909	63	26	2	2	NUM
ajst-26909	63	27	)	)	PUNCT
ajst-26909	63	28	ttt	ttt	NOUN
ajst-26909	63	29			NOUN
ajst-26909	63	30	1	1	NOUN
ajst-26909	63	31	(	(	PUNCT
ajst-26909	63	32	3	3	NUM
ajst-26909	63	33	)	)	PUNCT
ajst-26909	63	34	in	in	ADP
ajst-26909	63	35	this	this	DET
ajst-26909	63	36	context	context	NOUN
ajst-26909	63	37	,	,	PUNCT
ajst-26909	63	38	t	t	NUM
ajst-26909	63	39	represents	represent	VERB
ajst-26909	63	40	the	the	DET
ajst-26909	63	41	speed	speed	NOUN
ajst-26909	63	42	at	at	ADP
ajst-26909	63	43	time	time	NOUN
ajst-26909	63	44	step	step	NOUN
ajst-26909	63	45	t	t	NOUN
ajst-26909	63	46	,	,	PUNCT
ajst-26909	63	47			NOUN
ajst-26909	63	48	denotes	denote	VERB
ajst-26909	63	49	the	the	DET
ajst-26909	63	50	momentum	momentum	NOUN
ajst-26909	63	51	coefficient	coefficient	NOUN
ajst-26909	63	52	,	,	PUNCT
ajst-26909	63	53			PRON
ajst-26909	63	54	signifies	signify	VERB
ajst-26909	63	55	the	the	DET
ajst-26909	63	56	learning	learning	NOUN
ajst-26909	63	57	rate	rate	NOUN
ajst-26909	63	58	,	,	PUNCT
ajst-26909	63	59			PROPN
ajst-26909	63	60			NOUN
ajst-26909	63	61	j	j	PROPN
ajst-26909	63	62	indicates	indicate	VERB
ajst-26909	63	63	the	the	DET
ajst-26909	63	64	gradient	gradient	NOUN
ajst-26909	63	65	of	of	ADP
ajst-26909	63	66	the	the	DET
ajst-26909	63	67	loss	loss	NOUN
ajst-26909	63	68	function	function	NOUN
ajst-26909	63	69			NOUN
ajst-26909	63	70	j	j	PUNCT
ajst-26909	63	71	concerning	concern	VERB
ajst-26909	63	72	model	model	NOUN
ajst-26909	63	73	parameter	parameter	NOUN
ajst-26909	63	74			PROPN
ajst-26909	63	75	,	,	PUNCT
ajst-26909	63	76	and	and	CCONJ
ajst-26909	63	77	t	t	PRON
ajst-26909	63	78	stands	stand	VERB
ajst-26909	63	79	for	for	ADP
ajst-26909	63	80	the	the	DET
ajst-26909	63	81	model	model	NOUN
ajst-26909	63	82	parameter	parameter	NOUN
ajst-26909	63	83	at	at	ADP
ajst-26909	63	84	time	time	NOUN
ajst-26909	63	85	step	step	NOUN
ajst-26909	63	86	t	t	NOUN
ajst-26909	63	87	.	.	PUNCT
ajst-26909	64	1	to	to	PART
ajst-26909	64	2	enhance	enhance	VERB
ajst-26909	64	3	generalization	generalization	NOUN
ajst-26909	64	4	and	and	CCONJ
ajst-26909	64	5	mitigate	mitigate	VERB
ajst-26909	64	6	overfitting	overfitting	NOUN
ajst-26909	64	7	,	,	PUNCT
ajst-26909	64	8	this	this	DET
ajst-26909	64	9	study	study	NOUN
ajst-26909	64	10	employs	employ	VERB
ajst-26909	64	11	l2	l2	NOUN
ajst-26909	64	12	regularization	regularization	NOUN
ajst-26909	64	13	:	:	PUNCT
ajst-26909	65	1			PRON
ajst-26909	65	2			VERB
ajst-26909	66	1	i	i	PRON
ajst-26909	66	2	j	j	PROPN
ajst-26909	67	1	j	j	NOUN
ajst-26909	68	1	i	i	PRON
ajst-26909	68	2	j	j	VERB
ajst-26909	69	1	i	i	PRON
ajst-26909	69	2	yyloss	yyloss	NOUN
ajst-26909	69	3	2	2	NUM
ajst-26909	69	4	ˆlog	ˆlog	VERB
ajst-26909	69	5			PROPN
ajst-26909	69	6	(	(	PUNCT
ajst-26909	69	7	4	4	NUM
ajst-26909	69	8	)	)	PUNCT
ajst-26909	69	9	here	here	ADV
ajst-26909	69	10	,	,	PUNCT
ajst-26909	69	11	y	y	PROPN
ajst-26909	69	12	denotes	denote	VERB
ajst-26909	69	13	the	the	DET
ajst-26909	69	14	expected	expect	VERB
ajst-26909	69	15	value	value	NOUN
ajst-26909	69	16	,	,	PUNCT
ajst-26909	69	17	ŷ	ŷ	NUM
ajst-26909	69	18	the	the	DET
ajst-26909	69	19	predicted	predict	VERB
ajst-26909	69	20	value	value	NOUN
ajst-26909	69	21	,	,	PUNCT
ajst-26909	69	22			X
ajst-26909	69	23	represents	represent	VERB
ajst-26909	69	24	l2	l2	NOUN
ajst-26909	69	25	regularization	regularization	NOUN
ajst-26909	69	26	,	,	PUNCT
ajst-26909	69	27	and	and	CCONJ
ajst-26909	69	28			PROPN
ajst-26909	69	29	signifies	signify	VERB
ajst-26909	69	30	the	the	DET
ajst-26909	69	31	parameter	parameter	NOUN
ajst-26909	69	32	set	set	NOUN
ajst-26909	69	33	of	of	ADP
ajst-26909	69	34	the	the	DET
ajst-26909	69	35	cnn	cnn	PROPN
ajst-26909	69	36	.	.	PUNCT
ajst-26909	70	1	selecting	select	VERB
ajst-26909	70	2	the	the	DET
ajst-26909	70	3	suitable	suitable	ADJ
ajst-26909	70	4	regularization	regularization	NOUN
ajst-26909	70	5	coefficient	coefficient	NOUN
ajst-26909	70	6			ADJ
ajst-26909	70	7	ensures	ensure	VERB
ajst-26909	70	8	model	model	NOUN
ajst-26909	70	9	performance	performance	NOUN
ajst-26909	70	10	while	while	SCONJ
ajst-26909	70	11	mitigating	mitigate	VERB
ajst-26909	70	12	the	the	DET
ajst-26909	70	13	risk	risk	NOUN
ajst-26909	70	14	of	of	ADP
ajst-26909	70	15	over	over	ADV
ajst-26909	70	16	-	-	PUNCT
ajst-26909	70	17	fitting	fitting	NOUN
ajst-26909	70	18	.	.	PUNCT
ajst-26909	71	1	in	in	ADP
ajst-26909	71	2	terms	term	NOUN
ajst-26909	71	3	of	of	ADP
ajst-26909	71	4	training	training	NOUN
ajst-26909	71	5	methods	method	NOUN
ajst-26909	71	6	,	,	PUNCT
ajst-26909	71	7	data	datum	NOUN
ajst-26909	71	8	enhancement	enhancement	NOUN
ajst-26909	71	9	and	and	CCONJ
ajst-26909	71	10	sample	sample	NOUN
ajst-26909	71	11	balance	balance	NOUN
ajst-26909	71	12	techniques	technique	NOUN
ajst-26909	71	13	increase	increase	VERB
ajst-26909	71	14	the	the	DET
ajst-26909	71	15	diversity	diversity	NOUN
ajst-26909	71	16	of	of	ADP
ajst-26909	71	17	training	training	NOUN
ajst-26909	71	18	samples	sample	NOUN
ajst-26909	71	19	and	and	CCONJ
ajst-26909	71	20	improve	improve	VERB
ajst-26909	71	21	the	the	DET
ajst-26909	71	22	generalization	generalization	NOUN
ajst-26909	71	23	ability	ability	NOUN
ajst-26909	71	24	of	of	ADP
ajst-26909	71	25	the	the	DET
ajst-26909	71	26	model	model	NOUN
ajst-26909	71	27	.	.	PUNCT
ajst-26909	72	1	knowledge	knowledge	NOUN
ajst-26909	72	2	distillation	distillation	NOUN
ajst-26909	72	3	and	and	CCONJ
ajst-26909	72	4	transfer	transfer	NOUN
ajst-26909	72	5	learning	learning	NOUN
ajst-26909	72	6	use	use	VERB
ajst-26909	72	7	the	the	DET
ajst-26909	72	8	knowledge	knowledge	NOUN
ajst-26909	72	9	of	of	ADP
ajst-26909	72	10	large	large	ADJ
ajst-26909	72	11	model	model	NOUN
ajst-26909	72	12	to	to	PART
ajst-26909	72	13	guide	guide	VERB
ajst-26909	72	14	the	the	DET
ajst-26909	72	15	training	training	NOUN
ajst-26909	72	16	of	of	ADP
ajst-26909	72	17	lightweight	lightweight	ADJ
ajst-26909	72	18	network	network	NOUN
ajst-26909	72	19	.	.	PUNCT
ajst-26909	73	1	joint	joint	ADJ
ajst-26909	73	2	training	training	NOUN
ajst-26909	73	3	and	and	CCONJ
ajst-26909	73	4	multi	multi	ADJ
ajst-26909	73	5	-	-	NOUN
ajst-26909	73	6	task	task	ADJ
ajst-26909	73	7	learning	learning	NOUN
ajst-26909	73	8	realize	realize	VERB
ajst-26909	73	9	knowledge	knowledge	NOUN
ajst-26909	73	10	sharing	sharing	NOUN
ajst-26909	73	11	among	among	ADP
ajst-26909	73	12	different	different	ADJ
ajst-26909	73	13	tasks	task	NOUN
ajst-26909	73	14	by	by	ADP
ajst-26909	73	15	sharing	share	VERB
ajst-26909	73	16	network	network	NOUN
ajst-26909	73	17	layer	layer	NOUN
ajst-26909	73	18	or	or	CCONJ
ajst-26909	73	19	parameters	parameter	NOUN
ajst-26909	73	20	.	.	PUNCT
ajst-26909	74	1	4	4	X
ajst-26909	74	2	.	.	X
ajst-26909	74	3	experimental	experimental	ADJ
ajst-26909	74	4	results	result	NOUN
ajst-26909	74	5	and	and	CCONJ
ajst-26909	74	6	analysis	analysis	NOUN
ajst-26909	74	7	figure	figure	NOUN
ajst-26909	74	8	2	2	NUM
ajst-26909	74	9	shows	show	VERB
ajst-26909	74	10	the	the	DET
ajst-26909	74	11	comparison	comparison	NOUN
ajst-26909	74	12	between	between	ADP
ajst-26909	74	13	lcnn	lcnn	NOUN
ajst-26909	74	14	and	and	CCONJ
ajst-26909	74	15	siftbased	siftbase	VERB
ajst-26909	74	16	target	target	NOUN
ajst-26909	74	17	detection	detection	NOUN
ajst-26909	74	18	algorithm	algorithm	NOUN
ajst-26909	74	19	in	in	ADP
ajst-26909	74	20	detection	detection	NOUN
ajst-26909	74	21	success	success	NOUN
ajst-26909	74	22	rate	rate	NOUN
ajst-26909	74	23	.	.	PUNCT
ajst-26909	75	1	the	the	DET
ajst-26909	75	2	detection	detection	NOUN
ajst-26909	75	3	success	success	NOUN
ajst-26909	75	4	rate	rate	NOUN
ajst-26909	75	5	of	of	ADP
ajst-26909	75	6	lcnn	lcnn	NOUN
ajst-26909	75	7	on	on	ADP
ajst-26909	75	8	all	all	DET
ajst-26909	75	9	kinds	kind	NOUN
ajst-26909	75	10	of	of	ADP
ajst-26909	75	11	targets	target	NOUN
ajst-26909	75	12	is	be	AUX
ajst-26909	75	13	significantly	significantly	ADV
ajst-26909	75	14	higher	high	ADJ
ajst-26909	75	15	than	than	ADP
ajst-26909	75	16	that	that	PRON
ajst-26909	75	17	of	of	ADP
ajst-26909	75	18	sift	sift	ADJ
ajst-26909	75	19	algorithm	algorithm	NOUN
ajst-26909	75	20	.	.	PUNCT
ajst-26909	76	1	through	through	ADP
ajst-26909	76	2	deep	deep	ADJ
ajst-26909	76	3	learning	learning	NOUN
ajst-26909	76	4	and	and	CCONJ
ajst-26909	76	5	large	large	ADJ
ajst-26909	76	6	-	-	PUNCT
ajst-26909	76	7	scale	scale	NOUN
ajst-26909	76	8	data	datum	NOUN
ajst-26909	76	9	training	training	NOUN
ajst-26909	76	10	,	,	PUNCT
ajst-26909	76	11	lcnn	lcnn	PROPN
ajst-26909	76	12	can	can	AUX
ajst-26909	76	13	capture	capture	VERB
ajst-26909	76	14	more	more	ADV
ajst-26909	76	15	abundant	abundant	ADJ
ajst-26909	76	16	target	target	NOUN
ajst-26909	76	17	features	feature	NOUN
ajst-26909	76	18	and	and	CCONJ
ajst-26909	76	19	maintain	maintain	VERB
ajst-26909	76	20	stable	stable	ADJ
ajst-26909	76	21	detection	detection	NOUN
ajst-26909	76	22	performance	performance	NOUN
ajst-26909	76	23	under	under	ADP
ajst-26909	76	24	various	various	ADJ
ajst-26909	76	25	illumination	illumination	NOUN
ajst-26909	76	26	,	,	PUNCT
ajst-26909	76	27	occlusion	occlusion	NOUN
ajst-26909	76	28	and	and	CCONJ
ajst-26909	76	29	angle	angle	NOUN
ajst-26909	76	30	changes	change	NOUN
ajst-26909	76	31	.	.	PUNCT
ajst-26909	77	1	figure	figure	NOUN
ajst-26909	77	2	2	2	NUM
ajst-26909	77	3	.	.	PUNCT
ajst-26909	77	4	comparison	comparison	NOUN
ajst-26909	77	5	of	of	ADP
ajst-26909	77	6	detection	detection	NOUN
ajst-26909	77	7	success	success	NOUN
ajst-26909	77	8	rate	rate	NOUN
ajst-26909	77	9	figure	figure	NOUN
ajst-26909	77	10	3	3	NUM
ajst-26909	77	11	further	far	ADV
ajst-26909	77	12	reveals	reveal	VERB
ajst-26909	77	13	the	the	DET
ajst-26909	77	14	advantages	advantage	NOUN
ajst-26909	77	15	of	of	ADP
ajst-26909	77	16	lcnn	lcnn	NOUN
ajst-26909	77	17	in	in	ADP
ajst-26909	77	18	time	time	NOUN
ajst-26909	77	19	loss	loss	NOUN
ajst-26909	77	20	of	of	ADP
ajst-26909	77	21	target	target	NOUN
ajst-26909	77	22	detection	detection	NOUN
ajst-26909	77	23	.	.	PUNCT
ajst-26909	78	1	compared	compare	VERB
ajst-26909	78	2	with	with	ADP
ajst-26909	78	3	sift	sift	NOUN
ajst-26909	78	4	-	-	PUNCT
ajst-26909	78	5	based	base	VERB
ajst-26909	78	6	algorithm	algorithm	NOUN
ajst-26909	78	7	,	,	PUNCT
ajst-26909	78	8	lcnn	lcnn	PROPN
ajst-26909	78	9	achieves	achieve	VERB
ajst-26909	78	10	a	a	DET
ajst-26909	78	11	significant	significant	ADJ
ajst-26909	78	12	improvement	improvement	NOUN
ajst-26909	78	13	in	in	ADP
ajst-26909	78	14	detection	detection	NOUN
ajst-26909	78	15	speed	speed	NOUN
ajst-26909	78	16	.	.	PUNCT
ajst-26909	79	1	in	in	ADP
ajst-26909	79	2	practical	practical	ADJ
ajst-26909	79	3	application	application	NOUN
ajst-26909	79	4	,	,	PUNCT
ajst-26909	79	5	this	this	PRON
ajst-26909	79	6	means	mean	VERB
ajst-26909	79	7	that	that	SCONJ
ajst-26909	79	8	lcnn	lcnn	PROPN
ajst-26909	79	9	can	can	AUX
ajst-26909	79	10	complete	complete	VERB
ajst-26909	79	11	the	the	DET
ajst-26909	79	12	target	target	NOUN
ajst-26909	79	13	detection	detection	NOUN
ajst-26909	79	14	task	task	NOUN
ajst-26909	79	15	in	in	ADP
ajst-26909	79	16	a	a	DET
ajst-26909	79	17	shorter	short	ADJ
ajst-26909	79	18	time	time	NOUN
ajst-26909	79	19	and	and	CCONJ
ajst-26909	79	20	meet	meet	VERB
ajst-26909	79	21	the	the	DET
ajst-26909	79	22	requirements	requirement	NOUN
ajst-26909	79	23	of	of	ADP
ajst-26909	79	24	real	real	ADJ
ajst-26909	79	25	-	-	PUNCT
ajst-26909	79	26	time	time	NOUN
ajst-26909	79	27	scenes	scene	NOUN
ajst-26909	79	28	.	.	PUNCT
ajst-26909	80	1	however	however	ADV
ajst-26909	80	2	,	,	PUNCT
ajst-26909	80	3	sift	sift	ADJ
ajst-26909	80	4	algorithm	algorithm	NOUN
ajst-26909	80	5	needs	need	VERB
ajst-26909	80	6	to	to	PART
ajst-26909	80	7	calculate	calculate	VERB
ajst-26909	80	8	a	a	DET
ajst-26909	80	9	large	large	ADJ
ajst-26909	80	10	number	number	NOUN
ajst-26909	80	11	of	of	ADP
ajst-26909	80	12	feature	feature	NOUN
ajst-26909	80	13	points	point	NOUN
ajst-26909	80	14	and	and	CCONJ
ajst-26909	80	15	descriptors	descriptor	NOUN
ajst-26909	80	16	,	,	PUNCT
ajst-26909	80	17	which	which	PRON
ajst-26909	80	18	leads	lead	VERB
ajst-26909	80	19	to	to	ADP
ajst-26909	80	20	a	a	DET
ajst-26909	80	21	large	large	ADJ
ajst-26909	80	22	time	time	NOUN
ajst-26909	80	23	loss	loss	NOUN
ajst-26909	80	24	and	and	CCONJ
ajst-26909	80	25	is	be	AUX
ajst-26909	80	26	difficult	difficult	ADJ
ajst-26909	80	27	to	to	PART
ajst-26909	80	28	meet	meet	VERB
ajst-26909	80	29	the	the	DET
ajst-26909	80	30	real	real	ADJ
ajst-26909	80	31	-	-	PUNCT
ajst-26909	80	32	time	time	NOUN
ajst-26909	80	33	requirements	requirement	NOUN
ajst-26909	80	34	.	.	PUNCT
ajst-26909	81	1	192	192	NUM
ajst-26909	81	2	figure	figure	NOUN
ajst-26909	81	3	3	3	NUM
ajst-26909	81	4	.	.	NOUN
ajst-26909	81	5	comparison	comparison	NOUN
ajst-26909	81	6	of	of	ADP
ajst-26909	81	7	time	time	NOUN
ajst-26909	81	8	loss	loss	NOUN
ajst-26909	81	9	in	in	ADP
ajst-26909	81	10	addition	addition	NOUN
ajst-26909	81	11	to	to	ADP
ajst-26909	81	12	detecting	detect	VERB
ajst-26909	81	13	the	the	DET
ajst-26909	81	14	success	success	NOUN
ajst-26909	81	15	rate	rate	NOUN
ajst-26909	81	16	and	and	CCONJ
ajst-26909	81	17	time	time	NOUN
ajst-26909	81	18	loss	loss	NOUN
ajst-26909	81	19	,	,	PUNCT
ajst-26909	81	20	the	the	DET
ajst-26909	81	21	performance	performance	NOUN
ajst-26909	81	22	of	of	ADP
ajst-26909	81	23	lcnn	lcnn	NOUN
ajst-26909	81	24	in	in	ADP
ajst-26909	81	25	different	different	ADJ
ajst-26909	81	26	scenarios	scenario	NOUN
ajst-26909	81	27	is	be	AUX
ajst-26909	81	28	deeply	deeply	ADV
ajst-26909	81	29	analyzed	analyze	VERB
ajst-26909	81	30	.	.	PUNCT
ajst-26909	82	1	the	the	DET
ajst-26909	82	2	experimental	experimental	ADJ
ajst-26909	82	3	results	result	NOUN
ajst-26909	82	4	show	show	VERB
ajst-26909	82	5	that	that	SCONJ
ajst-26909	82	6	lcnn	lcnn	PROPN
ajst-26909	82	7	performs	perform	VERB
ajst-26909	82	8	well	well	ADV
ajst-26909	82	9	in	in	ADP
ajst-26909	82	10	various	various	ADJ
ajst-26909	82	11	scenes	scene	NOUN
ajst-26909	82	12	,	,	PUNCT
ajst-26909	82	13	and	and	CCONJ
ajst-26909	82	14	can	can	AUX
ajst-26909	82	15	detect	detect	VERB
ajst-26909	82	16	targets	target	NOUN
ajst-26909	82	17	accurately	accurately	ADV
ajst-26909	82	18	and	and	CCONJ
ajst-26909	82	19	quickly	quickly	ADV
ajst-26909	82	20	,	,	PUNCT
ajst-26909	82	21	whether	whether	SCONJ
ajst-26909	82	22	indoors	indoor	NOUN
ajst-26909	82	23	or	or	CCONJ
ajst-26909	82	24	outdoors	outdoor	NOUN
ajst-26909	82	25	,	,	PUNCT
ajst-26909	82	26	day	day	NOUN
ajst-26909	82	27	or	or	CCONJ
ajst-26909	82	28	night	night	NOUN
ajst-26909	82	29	.	.	PUNCT
ajst-26909	83	1	5	5	X
ajst-26909	83	2	.	.	X
ajst-26909	83	3	conclusions	conclusion	NOUN
ajst-26909	83	4	based	base	VERB
ajst-26909	83	5	on	on	ADP
ajst-26909	83	6	the	the	DET
ajst-26909	83	7	in	in	ADP
ajst-26909	83	8	-	-	PUNCT
ajst-26909	83	9	depth	depth	NOUN
ajst-26909	83	10	study	study	NOUN
ajst-26909	83	11	of	of	ADP
ajst-26909	83	12	lcnn	lcnn	PROPN
ajst-26909	83	13	in	in	ADP
ajst-26909	83	14	target	target	NOUN
ajst-26909	83	15	detection	detection	NOUN
ajst-26909	83	16	,	,	PUNCT
ajst-26909	83	17	this	this	DET
ajst-26909	83	18	paper	paper	NOUN
ajst-26909	83	19	discusses	discuss	VERB
ajst-26909	83	20	its	its	PRON
ajst-26909	83	21	design	design	NOUN
ajst-26909	83	22	ideas	idea	NOUN
ajst-26909	83	23	,	,	PUNCT
ajst-26909	83	24	optimization	optimization	NOUN
ajst-26909	83	25	strategies	strategy	NOUN
ajst-26909	83	26	and	and	CCONJ
ajst-26909	83	27	performance	performance	NOUN
ajst-26909	83	28	analysis	analysis	NOUN
ajst-26909	83	29	.	.	PUNCT
ajst-26909	84	1	the	the	DET
ajst-26909	84	2	research	research	NOUN
ajst-26909	84	3	shows	show	VERB
ajst-26909	84	4	that	that	SCONJ
ajst-26909	84	5	lcnn	lcnn	NOUN
ajst-26909	84	6	significantly	significantly	ADV
ajst-26909	84	7	reduces	reduce	VERB
ajst-26909	84	8	the	the	DET
ajst-26909	84	9	computational	computational	ADJ
ajst-26909	84	10	complexity	complexity	NOUN
ajst-26909	84	11	and	and	CCONJ
ajst-26909	84	12	storage	storage	NOUN
ajst-26909	84	13	requirements	requirement	NOUN
ajst-26909	84	14	by	by	ADP
ajst-26909	84	15	optimizing	optimize	VERB
ajst-26909	84	16	the	the	DET
ajst-26909	84	17	network	network	NOUN
ajst-26909	84	18	structure	structure	NOUN
ajst-26909	84	19	and	and	CCONJ
ajst-26909	84	20	parameters	parameter	NOUN
ajst-26909	84	21	,	,	PUNCT
ajst-26909	84	22	while	while	SCONJ
ajst-26909	84	23	maintaining	maintain	VERB
ajst-26909	84	24	high	high	ADJ
ajst-26909	84	25	detection	detection	NOUN
ajst-26909	84	26	accuracy	accuracy	NOUN
ajst-26909	84	27	and	and	CCONJ
ajst-26909	84	28	real	real	ADJ
ajst-26909	84	29	-	-	PUNCT
ajst-26909	84	30	time	time	NOUN
ajst-26909	84	31	.	.	PUNCT
ajst-26909	85	1	in	in	ADP
ajst-26909	85	2	terms	term	NOUN
ajst-26909	85	3	of	of	ADP
ajst-26909	85	4	design	design	NOUN
ajst-26909	85	5	ideas	idea	NOUN
ajst-26909	85	6	,	,	PUNCT
ajst-26909	85	7	lcnn	lcnn	PROPN
ajst-26909	85	8	adopts	adopt	VERB
ajst-26909	85	9	strategies	strategy	NOUN
ajst-26909	85	10	such	such	ADJ
ajst-26909	85	11	as	as	ADP
ajst-26909	85	12	deep	deep	ADJ
ajst-26909	85	13	separable	separable	ADJ
ajst-26909	85	14	convolution	convolution	NOUN
ajst-26909	85	15	,	,	PUNCT
ajst-26909	85	16	feature	feature	NOUN
ajst-26909	85	17	fusion	fusion	NOUN
ajst-26909	85	18	and	and	CCONJ
ajst-26909	85	19	enhancement	enhancement	NOUN
ajst-26909	85	20	,	,	PUNCT
ajst-26909	85	21	which	which	PRON
ajst-26909	85	22	improves	improve	VERB
ajst-26909	85	23	the	the	DET
ajst-26909	85	24	ability	ability	NOUN
ajst-26909	85	25	of	of	ADP
ajst-26909	85	26	feature	feature	NOUN
ajst-26909	85	27	extraction	extraction	NOUN
ajst-26909	85	28	and	and	CCONJ
ajst-26909	85	29	adaptability	adaptability	NOUN
ajst-26909	85	30	to	to	ADP
ajst-26909	85	31	complex	complex	ADJ
ajst-26909	85	32	scenes	scene	NOUN
ajst-26909	85	33	.	.	PUNCT
ajst-26909	86	1	by	by	ADP
ajst-26909	86	2	optimizing	optimize	VERB
ajst-26909	86	3	training	training	NOUN
ajst-26909	86	4	methods	method	NOUN
ajst-26909	86	5	and	and	CCONJ
ajst-26909	86	6	post	post	ADJ
ajst-26909	86	7	-	-	ADJ
ajst-26909	86	8	processing	processing	ADJ
ajst-26909	86	9	means	mean	NOUN
ajst-26909	86	10	,	,	PUNCT
ajst-26909	86	11	the	the	DET
ajst-26909	86	12	performance	performance	NOUN
ajst-26909	86	13	of	of	ADP
ajst-26909	86	14	lcnn	lcnn	NOUN
ajst-26909	86	15	is	be	AUX
ajst-26909	86	16	further	far	ADV
ajst-26909	86	17	improved	improve	VERB
ajst-26909	86	18	.	.	PUNCT
ajst-26909	87	1	the	the	DET
ajst-26909	87	2	results	result	NOUN
ajst-26909	87	3	show	show	VERB
ajst-26909	87	4	that	that	SCONJ
ajst-26909	87	5	lcnn	lcnn	PROPN
ajst-26909	87	6	is	be	AUX
ajst-26909	87	7	superior	superior	ADJ
ajst-26909	87	8	to	to	ADP
ajst-26909	87	9	the	the	DET
ajst-26909	87	10	traditional	traditional	ADJ
ajst-26909	87	11	sift	sift	NOUN
ajst-26909	87	12	-	-	PUNCT
ajst-26909	87	13	based	base	VERB
ajst-26909	87	14	target	target	NOUN
ajst-26909	87	15	detection	detection	NOUN
ajst-26909	87	16	algorithm	algorithm	NOUN
ajst-26909	87	17	in	in	ADP
ajst-26909	87	18	detection	detection	NOUN
ajst-26909	87	19	success	success	NOUN
ajst-26909	87	20	rate	rate	NOUN
ajst-26909	87	21	,	,	PUNCT
ajst-26909	87	22	time	time	NOUN
ajst-26909	87	23	loss	loss	NOUN
ajst-26909	87	24	and	and	CCONJ
ajst-26909	87	25	adaptability	adaptability	NOUN
ajst-26909	87	26	to	to	ADP
ajst-26909	87	27	different	different	ADJ
ajst-26909	87	28	scenes	scene	NOUN
ajst-26909	87	29	.	.	PUNCT
ajst-26909	88	1	the	the	DET
ajst-26909	88	2	lightweight	lightweight	ADJ
ajst-26909	88	3	design	design	NOUN
ajst-26909	88	4	of	of	ADP
ajst-26909	88	5	lcnn	lcnn	PROPN
ajst-26909	88	6	makes	make	VERB
ajst-26909	88	7	it	it	PRON
ajst-26909	88	8	easier	easy	ADJ
ajst-26909	88	9	to	to	PART
ajst-26909	88	10	deploy	deploy	VERB
ajst-26909	88	11	on	on	ADP
ajst-26909	88	12	equipment	equipment	NOUN
ajst-26909	88	13	with	with	ADP
ajst-26909	88	14	limited	limited	ADJ
ajst-26909	88	15	resources	resource	NOUN
ajst-26909	88	16	.	.	PUNCT
ajst-26909	89	1	to	to	PART
ajst-26909	89	2	sum	sum	VERB
ajst-26909	89	3	up	up	ADP
ajst-26909	89	4	,	,	PUNCT
ajst-26909	89	5	lcnn	lcnn	PROPN
ajst-26909	89	6	shows	show	VERB
ajst-26909	89	7	significant	significant	ADJ
ajst-26909	89	8	advantages	advantage	NOUN
ajst-26909	89	9	in	in	ADP
ajst-26909	89	10	target	target	NOUN
ajst-26909	89	11	detection	detection	NOUN
ajst-26909	89	12	.	.	PUNCT
ajst-26909	90	1	in	in	ADP
ajst-26909	90	2	the	the	DET
ajst-26909	90	3	future	future	NOUN
ajst-26909	90	4	,	,	PUNCT
ajst-26909	90	5	with	with	ADP
ajst-26909	90	6	the	the	DET
ajst-26909	90	7	continuous	continuous	ADJ
ajst-26909	90	8	progress	progress	NOUN
ajst-26909	90	9	of	of	ADP
ajst-26909	90	10	deep	deep	ADJ
ajst-26909	90	11	learning	learning	NOUN
ajst-26909	90	12	technology	technology	NOUN
ajst-26909	90	13	and	and	CCONJ
ajst-26909	90	14	the	the	DET
ajst-26909	90	15	emergence	emergence	NOUN
ajst-26909	90	16	of	of	ADP
ajst-26909	90	17	new	new	ADJ
ajst-26909	90	18	hardware	hardware	NOUN
ajst-26909	90	19	platforms	platform	NOUN
ajst-26909	90	20	,	,	PUNCT
ajst-26909	90	21	lcnn	lcnn	PROPN
ajst-26909	90	22	is	be	AUX
ajst-26909	90	23	expected	expect	VERB
ajst-26909	90	24	to	to	PART
ajst-26909	90	25	play	play	VERB
ajst-26909	90	26	an	an	DET
ajst-26909	90	27	important	important	ADJ
ajst-26909	90	28	role	role	NOUN
ajst-26909	90	29	in	in	ADP
ajst-26909	90	30	more	more	ADJ
ajst-26909	90	31	fields	field	NOUN
ajst-26909	90	32	.	.	PUNCT
ajst-26909	91	1	references	reference	NOUN
ajst-26909	91	2	[	[	X
ajst-26909	91	3	1	1	NUM
ajst-26909	91	4	]	]	X
ajst-26909	91	5	payghode	payghode	PROPN
ajst-26909	91	6	v	v	PROPN
ajst-26909	91	7	,	,	PUNCT
ajst-26909	91	8	goyal	goyal	PROPN
ajst-26909	91	9	a	a	X
ajst-26909	91	10	,	,	PUNCT
ajst-26909	91	11	dubey	dubey	PROPN
ajst-26909	91	12	i	i	PRON
ajst-26909	91	13	a	a	DET
ajst-26909	91	14	k.	k.	PROPN
ajst-26909	91	15	object	object	NOUN
ajst-26909	91	16	detection	detection	NOUN
ajst-26909	91	17	and	and	CCONJ
ajst-26909	91	18	activity	activity	NOUN
ajst-26909	91	19	recognition	recognition	NOUN
ajst-26909	91	20	in	in	ADP
ajst-26909	91	21	video	video	NOUN
ajst-26909	91	22	surveillance	surveillance	NOUN
ajst-26909	91	23	using	use	VERB
ajst-26909	91	24	neural	neural	ADJ
ajst-26909	91	25	networks[j	networks[j	PROPN
ajst-26909	91	26	]	]	X
ajst-26909	91	27	.	.	PUNCT
ajst-26909	92	1	international	international	ADJ
ajst-26909	92	2	journal	journal	PROPN
ajst-26909	92	3	of	of	ADP
ajst-26909	92	4	web	web	NOUN
ajst-26909	92	5	information	information	NOUN
ajst-26909	92	6	systems	system	NOUN
ajst-26909	92	7	,	,	PUNCT
ajst-26909	92	8	2023	2023	NUM
ajst-26909	92	9	,	,	PUNCT
ajst-26909	92	10	19(3/4):123	19(3/4):123	NUM
ajst-26909	92	11	-	-	SYM
ajst-26909	92	12	138	138	NUM
ajst-26909	92	13	.	.	PUNCT
ajst-26909	93	1	[	[	X
ajst-26909	93	2	2	2	NUM
ajst-26909	93	3	]	]	PUNCT
ajst-26909	93	4	tang	tang	PROPN
ajst-26909	93	5	j	j	PROPN
ajst-26909	93	6	,	,	PUNCT
ajst-26909	93	7	zhou	zhou	PROPN
ajst-26909	93	8	h	h	PROPN
ajst-26909	93	9	,	,	PUNCT
ajst-26909	93	10	wang	wang	PROPN
ajst-26909	93	11	t	t	PROPN
ajst-26909	93	12	,	,	PUNCT
ajst-26909	93	13	et	et	PROPN
ajst-26909	93	14	al	al	PROPN
ajst-26909	93	15	.	.	PROPN
ajst-26909	93	16	cascaded	cascade	VERB
ajst-26909	93	17	foreign	foreign	ADJ
ajst-26909	93	18	object	object	NOUN
ajst-26909	93	19	detection	detection	NOUN
ajst-26909	93	20	in	in	ADP
ajst-26909	93	21	manufacturing	manufacturing	NOUN
ajst-26909	93	22	processes	process	NOUN
ajst-26909	93	23	using	use	VERB
ajst-26909	93	24	convolutional	convolutional	ADJ
ajst-26909	93	25	neural	neural	ADJ
ajst-26909	93	26	networks	network	NOUN
ajst-26909	93	27	and	and	CCONJ
ajst-26909	93	28	synthetic	synthetic	ADJ
ajst-26909	93	29	data	data	NOUN
ajst-26909	93	30	generation	generation	NOUN
ajst-26909	93	31	methodology[j	methodology[j	PROPN
ajst-26909	93	32	]	]	PUNCT
ajst-26909	93	33	.	.	PUNCT
ajst-26909	94	1	journal	journal	PROPN
ajst-26909	94	2	of	of	ADP
ajst-26909	94	3	intelligent	intelligent	ADJ
ajst-26909	94	4	manufacturing	manufacturing	NOUN
ajst-26909	94	5	,	,	PUNCT
ajst-26909	94	6	2023	2023	NUM
ajst-26909	94	7	,	,	PUNCT
ajst-26909	94	8	34(7):2925	34(7):2925	NUM
ajst-26909	94	9	-	-	SYM
ajst-26909	94	10	2941	2941	NUM
ajst-26909	94	11	.	.	PUNCT
ajst-26909	95	1	[	[	X
ajst-26909	95	2	3	3	NUM
ajst-26909	95	3	]	]	X
ajst-26909	95	4	boisclair	boisclair	ADJ
ajst-26909	95	5	j	j	PROPN
ajst-26909	95	6	,	,	PUNCT
ajst-26909	95	7	kelouwani	kelouwani	PROPN
ajst-26909	95	8	s	s	PROPN
ajst-26909	95	9	,	,	PUNCT
ajst-26909	95	10	ayevide	ayevide	ADJ
ajst-26909	95	11	,	,	PUNCT
ajst-26909	95	12	follivi	follivi	NOUN
ajst-26909	95	13	kloutseamamou	kloutseamamou	PROPN
ajst-26909	95	14	,	,	PUNCT
ajst-26909	95	15	alialam	alialam	PROPN
ajst-26909	95	16	,	,	PUNCT
ajst-26909	95	17	muhammad	muhammad	PROPN
ajst-26909	95	18	zeshanagbossou	zeshanagbossou	PROPN
ajst-26909	95	19	,	,	PUNCT
ajst-26909	95	20	kodjo	kodjo	PROPN
ajst-26909	95	21	.	.	PUNCT
ajst-26909	95	22	attention	attention	NOUN
ajst-26909	95	23	transfer	transfer	NOUN
ajst-26909	95	24	from	from	ADP
ajst-26909	95	25	human	human	ADJ
ajst-26909	95	26	to	to	ADP
ajst-26909	95	27	neural	neural	ADJ
ajst-26909	95	28	networks	network	NOUN
ajst-26909	95	29	for	for	ADP
ajst-26909	95	30	road	road	NOUN
ajst-26909	95	31	object	object	NOUN
ajst-26909	95	32	detection	detection	NOUN
ajst-26909	95	33	in	in	ADP
ajst-26909	95	34	winter[j	winter[j	NOUN
ajst-26909	95	35	]	]	PUNCT
ajst-26909	95	36	.	.	PUNCT
ajst-26909	96	1	iet	iet	PROPN
ajst-26909	96	2	image	image	PROPN
ajst-26909	96	3	processing	processing	NOUN
ajst-26909	96	4	,	,	PUNCT
ajst-26909	96	5	2022	2022	NUM
ajst-26909	96	6	,	,	PUNCT
ajst-26909	96	7	16(13	16(13	NUM
ajst-26909	96	8	):	):	PUNCT
ajst-26909	96	9	3544	3544	NUM
ajst-26909	96	10	-	-	SYM
ajst-26909	96	11	3556	3556	NUM
ajst-26909	96	12	.	.	PUNCT
ajst-26909	97	1	[	[	X
ajst-26909	97	2	4	4	X
ajst-26909	97	3	]	]	X
ajst-26909	97	4	ding	ding	NOUN
ajst-26909	97	5	x	x	X
ajst-26909	97	6	,	,	PUNCT
ajst-26909	97	7	li	li	PROPN
ajst-26909	97	8	b	b	PROPN
ajst-26909	97	9	,	,	PUNCT
ajst-26909	97	10	wang	wang	PROPN
ajst-26909	97	11	j.	j.	PROPN
ajst-26909	97	12	geometric	geometric	PROPN
ajst-26909	97	13	property	property	NOUN
ajst-26909	97	14	-	-	PUNCT
ajst-26909	97	15	based	base	VERB
ajst-26909	97	16	convolutional	convolutional	ADJ
ajst-26909	97	17	neural	neural	ADJ
ajst-26909	97	18	network	network	NOUN
ajst-26909	97	19	for	for	ADP
ajst-26909	97	20	indoor	indoor	ADJ
ajst-26909	97	21	object	object	NOUN
ajst-26909	97	22	detection:[j	detection:[j	NOUN
ajst-26909	97	23	]	]	PUNCT
ajst-26909	97	24	.	.	PUNCT
ajst-26909	97	25	international	international	ADJ
ajst-26909	97	26	journal	journal	PROPN
ajst-26909	97	27	of	of	ADP
ajst-26909	97	28	advanced	advanced	ADJ
ajst-26909	97	29	robotic	robotic	ADJ
ajst-26909	97	30	systems	system	NOUN
ajst-26909	97	31	,	,	PUNCT
ajst-26909	97	32	2021	2021	NUM
ajst-26909	97	33	,	,	PUNCT
ajst-26909	97	34	18(1):261	18(1):261	NUM
ajst-26909	97	35	-	-	SYM
ajst-26909	97	36	318	318	NUM
ajst-26909	97	37	.	.	PUNCT
ajst-26909	98	1	[	[	X
ajst-26909	98	2	5	5	NUM
ajst-26909	98	3	]	]	X
ajst-26909	98	4	zhao	zhao	PROPN
ajst-26909	98	5	z	z	PROPN
ajst-26909	98	6	,	,	PUNCT
ajst-26909	98	7	huang	huang	PROPN
ajst-26909	98	8	z	z	PROPN
ajst-26909	98	9	,	,	PUNCT
ajst-26909	98	10	chai	chai	NOUN
ajst-26909	98	11	x	x	NOUN
ajst-26909	98	12	,	,	PUNCT
ajst-26909	98	13	et	et	PROPN
ajst-26909	98	14	al	al	PROPN
ajst-26909	98	15	.	.	PUNCT
ajst-26909	98	16	depth	depth	NOUN
ajst-26909	98	17	enhanced	enhance	VERB
ajst-26909	98	18	cross	cross	ADJ
ajst-26909	98	19	-	-	ADJ
ajst-26909	98	20	modal	modal	ADJ
ajst-26909	98	21	cascaded	cascade	VERB
ajst-26909	98	22	network	network	NOUN
ajst-26909	98	23	for	for	ADP
ajst-26909	98	24	rgb	rgb	PROPN
ajst-26909	98	25	-	-	PROPN
ajst-26909	98	26	d	d	PROPN
ajst-26909	98	27	salient	salient	NOUN
ajst-26909	98	28	object	object	NOUN
ajst-26909	98	29	detection[j	detection[j	PROPN
ajst-26909	98	30	]	]	PUNCT
ajst-26909	98	31	.	.	PUNCT
ajst-26909	99	1	neural	neural	ADJ
ajst-26909	99	2	processing	processing	NOUN
ajst-26909	99	3	letters	letter	NOUN
ajst-26909	99	4	,	,	PUNCT
ajst-26909	99	5	2023	2023	NUM
ajst-26909	99	6	,	,	PUNCT
ajst-26909	99	7	55(1):361	55(1):361	NOUN
ajst-26909	99	8	-	-	PUNCT
ajst-26909	99	9	384	384	NUM
ajst-26909	99	10	.	.	PUNCT
ajst-26909	100	1	[	[	X
ajst-26909	100	2	6	6	NUM
ajst-26909	100	3	]	]	SYM
ajst-26909	100	4	minor	minor	ADJ
ajst-26909	100	5	e	e	NOUN
ajst-26909	100	6	,	,	PUNCT
ajst-26909	100	7	howard	howard	PROPN
ajst-26909	100	8	s	s	PROPN
ajst-26909	100	9	,	,	PUNCT
ajst-26909	100	10	green	green	PROPN
ajst-26909	100	11	a	a	X
ajst-26909	100	12	,	,	PUNCT
ajst-26909	100	13	et	et	PROPN
ajst-26909	100	14	al	al	PROPN
ajst-26909	100	15	.	.	PROPN
ajst-26909	100	16	end	end	PROPN
ajst-26909	100	17	-	-	PUNCT
ajst-26909	100	18	to	to	ADP
ajst-26909	100	19	-	-	PUNCT
ajst-26909	100	20	end	end	NOUN
ajst-26909	100	21	machine	machine	NOUN
ajst-26909	100	22	learning	learn	VERB
ajst-26909	100	23	for	for	ADP
ajst-26909	100	24	experimental	experimental	ADJ
ajst-26909	100	25	physics	physics	NOUN
ajst-26909	100	26	:	:	PUNCT
ajst-26909	100	27	using	use	VERB
ajst-26909	100	28	simulated	simulated	ADJ
ajst-26909	100	29	data	datum	NOUN
ajst-26909	100	30	to	to	PART
ajst-26909	100	31	train	train	VERB
ajst-26909	100	32	a	a	DET
ajst-26909	100	33	neural	neural	ADJ
ajst-26909	100	34	network	network	NOUN
ajst-26909	100	35	for	for	ADP
ajst-26909	100	36	object	object	NOUN
ajst-26909	100	37	detection	detection	NOUN
ajst-26909	100	38	in	in	ADP
ajst-26909	100	39	video	video	NOUN
ajst-26909	100	40	microscopy	microscopy	NOUN
ajst-26909	100	41	.	.	PUNCT
ajst-26909	101	1	[	[	X
ajst-26909	101	2	j	j	X
ajst-26909	101	3	]	]	X
ajst-26909	101	4	.	.	PUNCT
ajst-26909	101	5	soft	soft	ADJ
ajst-26909	101	6	matter	matter	NOUN
ajst-26909	101	7	,	,	PUNCT
ajst-26909	101	8	2020	2020	NUM
ajst-26909	101	9	,	,	PUNCT
ajst-26909	101	10	16(7):1751	16(7):1751	NUM
ajst-26909	101	11	-	-	SYM
ajst-26909	101	12	1759	1759	NUM
ajst-26909	101	13	.	.	PUNCT
ajst-26909	102	1	[	[	X
ajst-26909	102	2	7	7	X
ajst-26909	102	3	]	]	PUNCT
ajst-26909	102	4	ye	ye	PRON
ajst-26909	102	5	t	t	PROPN
ajst-26909	102	6	,	,	PUNCT
ajst-26909	102	7	zhang	zhang	PROPN
ajst-26909	102	8	x	x	PROPN
ajst-26909	102	9	,	,	PUNCT
ajst-26909	102	10	zhang	zhang	PROPN
ajst-26909	102	11	y	y	PROPN
ajst-26909	102	12	,	,	PUNCT
ajst-26909	102	13	et	et	PROPN
ajst-26909	102	14	al	al	PROPN
ajst-26909	102	15	.	.	PROPN
ajst-26909	102	16	railway	railway	NOUN
ajst-26909	102	17	traffic	traffic	NOUN
ajst-26909	102	18	object	object	NOUN
ajst-26909	102	19	detection	detection	NOUN
ajst-26909	102	20	using	use	VERB
ajst-26909	102	21	differential	differential	ADJ
ajst-26909	102	22	feature	feature	NOUN
ajst-26909	102	23	fusion	fusion	NOUN
ajst-26909	102	24	convolution	convolution	NOUN
ajst-26909	102	25	neural	neural	ADJ
ajst-26909	102	26	network[j	network[j	PROPN
ajst-26909	102	27	]	]	PUNCT
ajst-26909	102	28	.	.	PUNCT
ajst-26909	103	1	ieee	ieee	NOUN
ajst-26909	103	2	transactions	transaction	NOUN
ajst-26909	103	3	on	on	ADP
ajst-26909	103	4	intelligent	intelligent	ADJ
ajst-26909	103	5	transportation	transportation	NOUN
ajst-26909	103	6	systems	system	NOUN
ajst-26909	103	7	,	,	PUNCT
ajst-26909	103	8	2020	2020	NUM
ajst-26909	103	9	,	,	PUNCT
ajst-26909	103	10	22(3):1375	22(3):1375	NUM
ajst-26909	103	11	-	-	SYM
ajst-26909	103	12	1387	1387	NUM
ajst-26909	103	13	.	.	PUNCT
ajst-26909	104	1	[	[	X
ajst-26909	104	2	8	8	NUM
ajst-26909	104	3	]	]	X
ajst-26909	104	4	guo	guo	PROPN
ajst-26909	104	5	h	h	PROPN
ajst-26909	104	6	,	,	PUNCT
ajst-26909	104	7	bai	bai	PROPN
ajst-26909	104	8	h	h	PROPN
ajst-26909	104	9	,	,	PUNCT
ajst-26909	104	10	zhou	zhou	PROPN
ajst-26909	104	11	y	y	PROPN
ajst-26909	104	12	,	,	PUNCT
ajst-26909	104	13	et	et	PROPN
ajst-26909	104	14	al	al	PROPN
ajst-26909	104	15	.	.	PROPN
ajst-26909	104	16	df	df	PROPN
ajst-26909	104	17	-	-	PUNCT
ajst-26909	104	18	ssd	ssd	NOUN
ajst-26909	104	19	:	:	PUNCT
ajst-26909	104	20	a	a	DET
ajst-26909	104	21	deep	deep	ADJ
ajst-26909	104	22	convolutional	convolutional	ADJ
ajst-26909	104	23	neural	neural	ADJ
ajst-26909	104	24	network	network	NOUN
ajst-26909	104	25	-	-	PUNCT
ajst-26909	104	26	based	base	VERB
ajst-26909	104	27	embedded	embed	VERB
ajst-26909	104	28	lightweight	lightweight	ADJ
ajst-26909	104	29	object	object	NOUN
ajst-26909	104	30	detection	detection	NOUN
ajst-26909	104	31	framework	framework	NOUN
ajst-26909	104	32	for	for	ADP
ajst-26909	104	33	remote	remote	ADJ
ajst-26909	104	34	sensing	sense	VERB
ajst-26909	104	35	imagery[j	imagery[j	PROPN
ajst-26909	104	36	]	]	PUNCT
ajst-26909	104	37	.	.	PUNCT
ajst-26909	105	1	journal	journal	PROPN
ajst-26909	105	2	of	of	ADP
ajst-26909	105	3	applied	apply	VERB
ajst-26909	105	4	remote	remote	ADJ
ajst-26909	105	5	sensing	sensing	NOUN
ajst-26909	105	6	,	,	PUNCT
ajst-26909	105	7	2020	2020	NUM
ajst-26909	105	8	,	,	PUNCT
ajst-26909	105	9	14(1):014521	14(1):014521	NUM
ajst-26909	105	10	-	-	SYM
ajst-26909	105	11	014521	014521	NUM
ajst-26909	105	12	.	.	PUNCT