id	sid	tid	token	lemma	pos
ajst-24867	1	1	academic	academic	ADJ
ajst-24867	1	2	journal	journal	NOUN
ajst-24867	1	3	of	of	ADP
ajst-24867	1	4	science	science	NOUN
ajst-24867	1	5	and	and	CCONJ
ajst-24867	1	6	technology	technology	NOUN
ajst-24867	1	7	issn	issn	NOUN
ajst-24867	1	8	:	:	PUNCT
ajst-24867	1	9	2771	2771	NUM
ajst-24867	1	10	-	-	SYM
ajst-24867	1	11	3032	3032	NUM
ajst-24867	1	12	|	|	NOUN
ajst-24867	1	13	vol	vol	NOUN
ajst-24867	1	14	.	.	PROPN
ajst-24867	2	1	12	12	NUM
ajst-24867	2	2	,	,	PUNCT
ajst-24867	2	3	no	no	INTJ
ajst-24867	2	4	.	.	NOUN
ajst-24867	2	5	1	1	NUM
ajst-24867	2	6	,	,	PUNCT
ajst-24867	2	7	2024	2024	NUM
ajst-24867	2	8	80	80	NUM
ajst-24867	2	9	an	an	DET
ajst-24867	2	10	infrared	infrared	ADJ
ajst-24867	2	11	ship	ship	NOUN
ajst-24867	2	12	detection	detection	NOUN
ajst-24867	2	13	algorithm	algorithm	NOUN
ajst-24867	2	14	based	base	VERB
ajst-24867	2	15	on	on	ADP
ajst-24867	2	16	yolov8n	yolov8n	PROPN
ajst-24867	2	17	haiyang	haiyang	PROPN
ajst-24867	2	18	qin	qin	PROPN
ajst-24867	2	19	1	1	NUM
ajst-24867	2	20	,	,	PUNCT
ajst-24867	2	21	2	2	NUM
ajst-24867	2	22	,	,	PUNCT
ajst-24867	2	23	gongquan	gongquan	NOUN
ajst-24867	2	24	tan	tan	PROPN
ajst-24867	2	25	1	1	NUM
ajst-24867	2	26	,	,	PUNCT
ajst-24867	2	27	2	2	NUM
ajst-24867	2	28	,	,	PUNCT
ajst-24867	2	29	hao	hao	PROPN
ajst-24867	2	30	deng	deng	PROPN
ajst-24867	2	31	1	1	NUM
ajst-24867	2	32	,	,	PUNCT
ajst-24867	2	33	2	2	NUM
ajst-24867	2	34	,	,	PUNCT
ajst-24867	2	35	dayang	dayang	PROPN
ajst-24867	2	36	cai	cai	PROPN
ajst-24867	2	37	1	1	NUM
ajst-24867	2	38	,	,	PUNCT
ajst-24867	2	39	2	2	NUM
ajst-24867	2	40	,	,	PUNCT
ajst-24867	2	41	yao	yao	PROPN
ajst-24867	2	42	wang	wang	PROPN
ajst-24867	2	43	1	1	NUM
ajst-24867	2	44	,	,	PUNCT
ajst-24867	2	45	2	2	NUM
ajst-24867	2	46	,	,	PUNCT
ajst-24867	2	47	guobin	guobin	NOUN
ajst-24867	2	48	mao	mao	PROPN
ajst-24867	2	49	1	1	NUM
ajst-24867	2	50	,	,	PUNCT
ajst-24867	2	51	2	2	NUM
ajst-24867	2	52	,	,	PUNCT
ajst-24867	2	53	teng	teng	PROPN
ajst-24867	2	54	hu	hu	PROPN
ajst-24867	2	55	1	1	NUM
ajst-24867	2	56	,	,	PUNCT
ajst-24867	2	57	2	2	NUM
ajst-24867	2	58	1	1	NUM
ajst-24867	2	59	school	school	NOUN
ajst-24867	2	60	of	of	ADP
ajst-24867	2	61	automation	automation	NOUN
ajst-24867	2	62	and	and	CCONJ
ajst-24867	2	63	information	information	NOUN
ajst-24867	2	64	engineering	engineering	NOUN
ajst-24867	2	65	,	,	PUNCT
ajst-24867	2	66	sichuan	sichuan	PROPN
ajst-24867	2	67	university	university	PROPN
ajst-24867	2	68	of	of	ADP
ajst-24867	2	69	science	science	PROPN
ajst-24867	2	70	&	&	CCONJ
ajst-24867	2	71	engineering	engineering	PROPN
ajst-24867	2	72	,	,	PUNCT
ajst-24867	2	73	yibin	yibin	PROPN
ajst-24867	2	74	644000	644000	NUM
ajst-24867	2	75	,	,	PUNCT
ajst-24867	2	76	china	china	PROPN
ajst-24867	2	77	2	2	NUM
ajst-24867	2	78	artificial	artificial	ADJ
ajst-24867	2	79	intelligence	intelligence	NOUN
ajst-24867	2	80	key	key	NOUN
ajst-24867	2	81	laboratory	laboratory	NOUN
ajst-24867	2	82	of	of	ADP
ajst-24867	2	83	sichuan	sichuan	PROPN
ajst-24867	2	84	province	province	PROPN
ajst-24867	2	85	,	,	PUNCT
ajst-24867	2	86	sichuan	sichuan	PROPN
ajst-24867	2	87	university	university	PROPN
ajst-24867	2	88	of	of	ADP
ajst-24867	2	89	science	science	PROPN
ajst-24867	2	90	&	&	CCONJ
ajst-24867	2	91	engineering	engineering	PROPN
ajst-24867	2	92	,	,	PUNCT
ajst-24867	2	93	yibin	yibin	PROPN
ajst-24867	2	94	644000	644000	NUM
ajst-24867	2	95	,	,	PUNCT
ajst-24867	2	96	china	china	PROPN
ajst-24867	2	97	abstract	abstract	NOUN
ajst-24867	2	98	:	:	PUNCT
ajst-24867	2	99	with	with	ADP
ajst-24867	2	100	the	the	DET
ajst-24867	2	101	development	development	NOUN
ajst-24867	2	102	of	of	ADP
ajst-24867	2	103	infrared	infrared	ADJ
ajst-24867	2	104	technology	technology	NOUN
ajst-24867	2	105	,	,	PUNCT
ajst-24867	2	106	infrared	infrared	ADJ
ajst-24867	2	107	imaging	imaging	NOUN
ajst-24867	2	108	technology	technology	NOUN
ajst-24867	2	109	has	have	AUX
ajst-24867	2	110	also	also	ADV
ajst-24867	2	111	been	be	AUX
ajst-24867	2	112	widely	widely	ADV
ajst-24867	2	113	used	use	VERB
ajst-24867	2	114	in	in	ADP
ajst-24867	2	115	marine	marine	ADJ
ajst-24867	2	116	ship	ship	NOUN
ajst-24867	2	117	detection	detection	NOUN
ajst-24867	2	118	.	.	PUNCT
ajst-24867	3	1	however	however	ADV
ajst-24867	3	2	,	,	PUNCT
ajst-24867	3	3	factors	factor	NOUN
ajst-24867	3	4	such	such	ADJ
ajst-24867	3	5	as	as	ADP
ajst-24867	3	6	low	low	ADJ
ajst-24867	3	7	contrast	contrast	NOUN
ajst-24867	3	8	and	and	CCONJ
ajst-24867	3	9	high	high	ADJ
ajst-24867	3	10	noise	noise	NOUN
ajst-24867	3	11	in	in	ADP
ajst-24867	3	12	infrared	infrared	ADJ
ajst-24867	3	13	images	image	NOUN
ajst-24867	3	14	result	result	VERB
ajst-24867	3	15	in	in	ADP
ajst-24867	3	16	poor	poor	ADJ
ajst-24867	3	17	detection	detection	NOUN
ajst-24867	3	18	performance	performance	NOUN
ajst-24867	3	19	.	.	PUNCT
ajst-24867	4	1	this	this	DET
ajst-24867	4	2	article	article	NOUN
ajst-24867	4	3	proposes	propose	VERB
ajst-24867	4	4	an	an	DET
ajst-24867	4	5	infrared	infrared	ADJ
ajst-24867	4	6	ship	ship	NOUN
ajst-24867	4	7	detection	detection	NOUN
ajst-24867	4	8	algorithm	algorithm	NOUN
ajst-24867	4	9	based	base	VERB
ajst-24867	4	10	on	on	ADP
ajst-24867	4	11	yolov8n	yolov8n	NOUN
ajst-24867	4	12	to	to	PART
ajst-24867	4	13	address	address	VERB
ajst-24867	4	14	this	this	DET
ajst-24867	4	15	issue	issue	NOUN
ajst-24867	4	16	.	.	PUNCT
ajst-24867	5	1	firstly	firstly	ADV
ajst-24867	5	2	,	,	PUNCT
ajst-24867	5	3	by	by	ADP
ajst-24867	5	4	adding	add	VERB
ajst-24867	5	5	a	a	DET
ajst-24867	5	6	small	small	ADJ
ajst-24867	5	7	target	target	NOUN
ajst-24867	5	8	detection	detection	NOUN
ajst-24867	5	9	layer	layer	NOUN
ajst-24867	5	10	,	,	PUNCT
ajst-24867	5	11	the	the	DET
ajst-24867	5	12	detection	detection	NOUN
ajst-24867	5	13	accuracy	accuracy	NOUN
ajst-24867	5	14	of	of	ADP
ajst-24867	5	15	small	small	ADJ
ajst-24867	5	16	target	target	NOUN
ajst-24867	5	17	ships	ship	NOUN
ajst-24867	5	18	has	have	AUX
ajst-24867	5	19	been	be	AUX
ajst-24867	5	20	significantly	significantly	ADV
ajst-24867	5	21	improved	improve	VERB
ajst-24867	5	22	.	.	PUNCT
ajst-24867	6	1	secondly	secondly	ADV
ajst-24867	6	2	,	,	PUNCT
ajst-24867	6	3	a	a	DET
ajst-24867	6	4	focaler	focaler	NOUN
ajst-24867	6	5	mpdiou	mpdiou	NOUN
ajst-24867	6	6	loss	loss	NOUN
ajst-24867	6	7	function	function	NOUN
ajst-24867	6	8	was	be	AUX
ajst-24867	6	9	designed	design	VERB
ajst-24867	6	10	to	to	PART
ajst-24867	6	11	address	address	VERB
ajst-24867	6	12	the	the	DET
ajst-24867	6	13	issue	issue	NOUN
ajst-24867	6	14	of	of	ADP
ajst-24867	6	15	imbalanced	imbalanced	ADJ
ajst-24867	6	16	sample	sample	NOUN
ajst-24867	6	17	categories	category	NOUN
ajst-24867	6	18	and	and	CCONJ
ajst-24867	6	19	reduce	reduce	VERB
ajst-24867	6	20	excessive	excessive	ADJ
ajst-24867	6	21	attention	attention	NOUN
ajst-24867	6	22	to	to	ADP
ajst-24867	6	23	easily	easily	ADV
ajst-24867	6	24	classified	classified	ADJ
ajst-24867	6	25	samples	sample	NOUN
ajst-24867	6	26	.	.	PUNCT
ajst-24867	7	1	finally	finally	ADV
ajst-24867	7	2	,	,	PUNCT
ajst-24867	7	3	the	the	DET
ajst-24867	7	4	introduction	introduction	NOUN
ajst-24867	7	5	of	of	ADP
ajst-24867	7	6	a	a	DET
ajst-24867	7	7	lightweight	lightweight	ADJ
ajst-24867	7	8	v7downsampling	v7downsample	VERB
ajst-24867	7	9	downsampling	downsampling	NOUN
ajst-24867	7	10	module	module	NOUN
ajst-24867	7	11	further	far	ADV
ajst-24867	7	12	improves	improve	VERB
ajst-24867	7	13	detection	detection	NOUN
ajst-24867	7	14	accuracy	accuracy	NOUN
ajst-24867	7	15	and	and	CCONJ
ajst-24867	7	16	reduces	reduce	VERB
ajst-24867	7	17	the	the	DET
ajst-24867	7	18	number	number	NOUN
ajst-24867	7	19	of	of	ADP
ajst-24867	7	20	model	model	NOUN
ajst-24867	7	21	parameters	parameter	NOUN
ajst-24867	7	22	and	and	CCONJ
ajst-24867	7	23	model	model	NOUN
ajst-24867	7	24	size	size	NOUN
ajst-24867	7	25	.	.	PUNCT
ajst-24867	8	1	the	the	DET
ajst-24867	8	2	experimental	experimental	ADJ
ajst-24867	8	3	results	result	NOUN
ajst-24867	8	4	show	show	VERB
ajst-24867	8	5	that	that	SCONJ
ajst-24867	8	6	the	the	DET
ajst-24867	8	7	improved	improved	ADJ
ajst-24867	8	8	algorithm	algorithm	NOUN
ajst-24867	8	9	has	have	AUX
ajst-24867	8	10	improved	improve	VERB
ajst-24867	8	11	the	the	DET
ajst-24867	8	12	average	average	ADJ
ajst-24867	8	13	accuracy	accuracy	NOUN
ajst-24867	8	14	on	on	ADP
ajst-24867	8	15	the	the	DET
ajst-24867	8	16	publicly	publicly	ADV
ajst-24867	8	17	available	available	ADJ
ajst-24867	8	18	infiray	infiray	NOUN
ajst-24867	8	19	infrared	infrared	ADJ
ajst-24867	8	20	ship	ship	NOUN
ajst-24867	8	21	dataset	dataset	VERB
ajst-24867	8	22	by	by	ADP
ajst-24867	8	23	3.4	3.4	NUM
ajst-24867	8	24	percentage	percentage	NOUN
ajst-24867	8	25	points	point	NOUN
ajst-24867	8	26	compared	compare	VERB
ajst-24867	8	27	to	to	ADP
ajst-24867	8	28	the	the	DET
ajst-24867	8	29	original	original	ADJ
ajst-24867	8	30	yolov8n	yolov8n	NOUN
ajst-24867	8	31	,	,	PUNCT
ajst-24867	8	32	while	while	SCONJ
ajst-24867	8	33	reducing	reduce	VERB
ajst-24867	8	34	the	the	DET
ajst-24867	8	35	number	number	NOUN
ajst-24867	8	36	of	of	ADP
ajst-24867	8	37	parameters	parameter	NOUN
ajst-24867	8	38	by	by	ADP
ajst-24867	8	39	11.8	11.8	NUM
ajst-24867	8	40	%	%	NOUN
ajst-24867	8	41	and	and	CCONJ
ajst-24867	8	42	the	the	DET
ajst-24867	8	43	model	model	NOUN
ajst-24867	8	44	size	size	NOUN
ajst-24867	8	45	by	by	ADP
ajst-24867	8	46	8	8	NUM
ajst-24867	8	47	%	%	NOUN
ajst-24867	8	48	,	,	PUNCT
ajst-24867	8	49	significantly	significantly	ADV
ajst-24867	8	50	improving	improve	VERB
ajst-24867	8	51	detection	detection	NOUN
ajst-24867	8	52	accuracy	accuracy	NOUN
ajst-24867	8	53	and	and	CCONJ
ajst-24867	8	54	making	make	VERB
ajst-24867	8	55	it	it	PRON
ajst-24867	8	56	easy	easy	ADJ
ajst-24867	8	57	to	to	PART
ajst-24867	8	58	deploy	deploy	VERB
ajst-24867	8	59	on	on	ADP
ajst-24867	8	60	resource	resource	NOUN
ajst-24867	8	61	limited	limit	VERB
ajst-24867	8	62	platforms	platform	NOUN
ajst-24867	8	63	.	.	PUNCT
ajst-24867	9	1	keywords	keyword	NOUN
ajst-24867	9	2	:	:	PUNCT
ajst-24867	9	3	infrared	infrared	ADJ
ajst-24867	9	4	ship	ship	NOUN
ajst-24867	9	5	detection	detection	NOUN
ajst-24867	9	6	;	;	PUNCT
ajst-24867	9	7	yolov8n	yolov8n	NOUN
ajst-24867	9	8	;	;	PUNCT
ajst-24867	9	9	v7downsampling	v7downsample	VERB
ajst-24867	9	10	;	;	PUNCT
ajst-24867	9	11	loss	loss	NOUN
ajst-24867	9	12	function	function	NOUN
ajst-24867	9	13	.	.	PUNCT
ajst-24867	10	1	1	1	X
ajst-24867	10	2	.	.	X
ajst-24867	10	3	introduction	introduction	NOUN
ajst-24867	10	4	ship	ship	NOUN
ajst-24867	10	5	detection	detection	NOUN
ajst-24867	10	6	technology	technology	NOUN
ajst-24867	10	7	plays	play	VERB
ajst-24867	10	8	a	a	DET
ajst-24867	10	9	crucial	crucial	ADJ
ajst-24867	10	10	role	role	NOUN
ajst-24867	10	11	in	in	ADP
ajst-24867	10	12	modern	modern	ADJ
ajst-24867	10	13	ocean	ocean	NOUN
ajst-24867	10	14	monitoring	monitoring	NOUN
ajst-24867	10	15	and	and	CCONJ
ajst-24867	10	16	maritime	maritime	ADJ
ajst-24867	10	17	safety	safety	NOUN
ajst-24867	10	18	.	.	PUNCT
ajst-24867	11	1	especially	especially	ADV
ajst-24867	11	2	in	in	ADP
ajst-24867	11	3	the	the	DET
ajst-24867	11	4	context	context	NOUN
ajst-24867	11	5	of	of	ADP
ajst-24867	11	6	the	the	DET
ajst-24867	11	7	gradual	gradual	ADJ
ajst-24867	11	8	maturity	maturity	NOUN
ajst-24867	11	9	and	and	CCONJ
ajst-24867	11	10	widespread	widespread	ADJ
ajst-24867	11	11	application	application	NOUN
ajst-24867	11	12	of	of	ADP
ajst-24867	11	13	infrared	infrared	ADJ
ajst-24867	11	14	imaging	imaging	NOUN
ajst-24867	11	15	technology	technology	NOUN
ajst-24867	11	16	,	,	PUNCT
ajst-24867	11	17	it	it	PRON
ajst-24867	11	18	is	be	AUX
ajst-24867	11	19	of	of	ADP
ajst-24867	11	20	great	great	ADJ
ajst-24867	11	21	practical	practical	ADJ
ajst-24867	11	22	significance	significance	NOUN
ajst-24867	11	23	to	to	AUX
ajst-24867	11	24	efficiently	efficiently	ADV
ajst-24867	11	25	and	and	CCONJ
ajst-24867	11	26	accurately	accurately	ADV
ajst-24867	11	27	detect	detect	VERB
ajst-24867	11	28	ships	ship	NOUN
ajst-24867	11	29	at	at	ADP
ajst-24867	11	30	sea	sea	NOUN
ajst-24867	11	31	using	use	VERB
ajst-24867	11	32	infrared	infrared	ADJ
ajst-24867	11	33	images	image	NOUN
ajst-24867	11	34	.	.	PUNCT
ajst-24867	12	1	infrared	infrared	ADJ
ajst-24867	12	2	imaging	imaging	NOUN
ajst-24867	12	3	technology	technology	NOUN
ajst-24867	12	4	has	have	VERB
ajst-24867	12	5	the	the	DET
ajst-24867	12	6	unique	unique	ADJ
ajst-24867	12	7	advantage	advantage	NOUN
ajst-24867	12	8	of	of	ADP
ajst-24867	12	9	being	be	AUX
ajst-24867	12	10	able	able	ADJ
ajst-24867	12	11	to	to	PART
ajst-24867	12	12	work	work	VERB
ajst-24867	12	13	at	at	ADP
ajst-24867	12	14	night	night	NOUN
ajst-24867	12	15	and	and	CCONJ
ajst-24867	12	16	in	in	ADP
ajst-24867	12	17	harsh	harsh	ADJ
ajst-24867	12	18	weather	weather	NOUN
ajst-24867	12	19	conditions	condition	NOUN
ajst-24867	12	20	,	,	PUNCT
ajst-24867	12	21	which	which	PRON
ajst-24867	12	22	makes	make	VERB
ajst-24867	12	23	it	it	PRON
ajst-24867	12	24	play	play	VERB
ajst-24867	12	25	an	an	DET
ajst-24867	12	26	important	important	ADJ
ajst-24867	12	27	role	role	NOUN
ajst-24867	12	28	in	in	ADP
ajst-24867	12	29	maritime	maritime	ADJ
ajst-24867	12	30	monitoring	monitoring	NOUN
ajst-24867	12	31	and	and	CCONJ
ajst-24867	12	32	search	search	NOUN
ajst-24867	12	33	and	and	CCONJ
ajst-24867	12	34	rescue	rescue	NOUN
ajst-24867	12	35	operations	operation	NOUN
ajst-24867	12	36	.	.	PUNCT
ajst-24867	13	1	however	however	ADV
ajst-24867	13	2	,	,	PUNCT
ajst-24867	13	3	infrared	infrared	ADJ
ajst-24867	13	4	images	image	NOUN
ajst-24867	13	5	also	also	ADV
ajst-24867	13	6	have	have	VERB
ajst-24867	13	7	problems	problem	NOUN
ajst-24867	13	8	such	such	ADJ
ajst-24867	13	9	as	as	ADP
ajst-24867	13	10	low	low	ADJ
ajst-24867	13	11	contrast	contrast	NOUN
ajst-24867	13	12	,	,	PUNCT
ajst-24867	13	13	high	high	ADJ
ajst-24867	13	14	noise	noise	NOUN
ajst-24867	13	15	,	,	PUNCT
ajst-24867	13	16	and	and	CCONJ
ajst-24867	13	17	small	small	ADJ
ajst-24867	13	18	differences	difference	NOUN
ajst-24867	13	19	between	between	ADP
ajst-24867	13	20	targets	target	NOUN
ajst-24867	13	21	and	and	CCONJ
ajst-24867	13	22	backgrounds	background	NOUN
ajst-24867	13	23	,	,	PUNCT
ajst-24867	13	24	which	which	PRON
ajst-24867	13	25	pose	pose	VERB
ajst-24867	13	26	great	great	ADJ
ajst-24867	13	27	challenges	challenge	NOUN
ajst-24867	13	28	to	to	PART
ajst-24867	13	29	ship	ship	NOUN
ajst-24867	13	30	detection	detection	NOUN
ajst-24867	13	31	.	.	PUNCT
ajst-24867	14	1	traditional	traditional	ADJ
ajst-24867	14	2	infrared	infrared	ADJ
ajst-24867	14	3	ship	ship	NOUN
ajst-24867	14	4	detection	detection	NOUN
ajst-24867	14	5	in	in	ADP
ajst-24867	14	6	the	the	DET
ajst-24867	14	7	past	past	NOUN
ajst-24867	14	8	mainly	mainly	ADV
ajst-24867	14	9	relied	rely	VERB
ajst-24867	14	10	on	on	ADP
ajst-24867	14	11	traditional	traditional	ADJ
ajst-24867	14	12	image	image	NOUN
ajst-24867	14	13	processing	processing	NOUN
ajst-24867	14	14	techniques	technique	NOUN
ajst-24867	14	15	.	.	PUNCT
ajst-24867	15	1	technologies	technology	NOUN
ajst-24867	15	2	such	such	ADJ
ajst-24867	15	3	as	as	ADP
ajst-24867	15	4	background	background	NOUN
ajst-24867	15	5	modeling	modeling	NOUN
ajst-24867	15	6	[	[	X
ajst-24867	15	7	3	3	NUM
ajst-24867	15	8	]	]	PUNCT
ajst-24867	15	9	,	,	PUNCT
ajst-24867	15	10	image	image	NOUN
ajst-24867	15	11	enhancement	enhancement	NOUN
ajst-24867	15	12	[	[	X
ajst-24867	15	13	4	4	NUM
ajst-24867	15	14	]	]	PUNCT
ajst-24867	15	15	,	,	PUNCT
ajst-24867	15	16	edge	edge	NOUN
ajst-24867	15	17	detection	detection	NOUN
ajst-24867	15	18	[	[	X
ajst-24867	15	19	5	5	NUM
ajst-24867	15	20	]	]	PUNCT
ajst-24867	15	21	,	,	PUNCT
ajst-24867	15	22	etc	etc	X
ajst-24867	15	23	.	.	X
ajst-24867	15	24	have	have	AUX
ajst-24867	15	25	to	to	ADP
ajst-24867	15	26	some	some	DET
ajst-24867	15	27	extent	extent	NOUN
ajst-24867	15	28	solved	solve	VERB
ajst-24867	15	29	the	the	DET
ajst-24867	15	30	detection	detection	NOUN
ajst-24867	15	31	problem	problem	NOUN
ajst-24867	15	32	in	in	ADP
ajst-24867	15	33	specific	specific	ADJ
ajst-24867	15	34	environments	environment	NOUN
ajst-24867	15	35	.	.	PUNCT
ajst-24867	16	1	however	however	ADV
ajst-24867	16	2	,	,	PUNCT
ajst-24867	16	3	due	due	ADP
ajst-24867	16	4	to	to	ADP
ajst-24867	16	5	their	their	PRON
ajst-24867	16	6	reliance	reliance	NOUN
ajst-24867	16	7	on	on	ADP
ajst-24867	16	8	manually	manually	ADV
ajst-24867	16	9	designed	design	VERB
ajst-24867	16	10	features	feature	NOUN
ajst-24867	16	11	and	and	CCONJ
ajst-24867	16	12	fixed	fix	VERB
ajst-24867	16	13	rules	rule	NOUN
ajst-24867	16	14	,	,	PUNCT
ajst-24867	16	15	it	it	PRON
ajst-24867	16	16	is	be	AUX
ajst-24867	16	17	difficult	difficult	ADJ
ajst-24867	16	18	to	to	PART
ajst-24867	16	19	capture	capture	VERB
ajst-24867	16	20	the	the	DET
ajst-24867	16	21	complex	complex	ADJ
ajst-24867	16	22	features	feature	NOUN
ajst-24867	16	23	of	of	ADP
ajst-24867	16	24	targets	target	NOUN
ajst-24867	16	25	in	in	ADP
ajst-24867	16	26	infrared	infrared	ADJ
ajst-24867	16	27	images	image	NOUN
ajst-24867	16	28	,	,	PUNCT
ajst-24867	16	29	resulting	result	VERB
ajst-24867	16	30	in	in	ADP
ajst-24867	16	31	high	high	ADJ
ajst-24867	16	32	rates	rate	NOUN
ajst-24867	16	33	of	of	ADP
ajst-24867	16	34	false	false	ADJ
ajst-24867	16	35	positives	positive	NOUN
ajst-24867	16	36	and	and	CCONJ
ajst-24867	16	37	missed	miss	VERB
ajst-24867	16	38	detections	detection	NOUN
ajst-24867	16	39	.	.	PUNCT
ajst-24867	17	1	with	with	ADP
ajst-24867	17	2	the	the	DET
ajst-24867	17	3	development	development	NOUN
ajst-24867	17	4	of	of	ADP
ajst-24867	17	5	deep	deep	ADJ
ajst-24867	17	6	learning	learning	NOUN
ajst-24867	17	7	technology	technology	NOUN
ajst-24867	17	8	,	,	PUNCT
ajst-24867	17	9	infrared	infrared	ADJ
ajst-24867	17	10	ship	ship	NOUN
ajst-24867	17	11	detection	detection	NOUN
ajst-24867	17	12	methods	method	NOUN
ajst-24867	17	13	based	base	VERB
ajst-24867	17	14	on	on	ADP
ajst-24867	17	15	deep	deep	ADJ
ajst-24867	17	16	learning	learning	NOUN
ajst-24867	17	17	have	have	AUX
ajst-24867	17	18	become	become	VERB
ajst-24867	17	19	an	an	DET
ajst-24867	17	20	effective	effective	ADJ
ajst-24867	17	21	technical	technical	ADJ
ajst-24867	17	22	means	mean	NOUN
ajst-24867	17	23	.	.	PUNCT
ajst-24867	18	1	especially	especially	ADV
ajst-24867	18	2	for	for	ADP
ajst-24867	18	3	object	object	NOUN
ajst-24867	18	4	detection	detection	NOUN
ajst-24867	18	5	algorithms	algorithm	NOUN
ajst-24867	18	6	based	base	VERB
ajst-24867	18	7	on	on	ADP
ajst-24867	18	8	convolutional	convolutional	ADJ
ajst-24867	18	9	neural	neural	ADJ
ajst-24867	18	10	networks	network	NOUN
ajst-24867	18	11	(	(	PUNCT
ajst-24867	18	12	cnn	cnn	PROPN
ajst-24867	18	13	)	)	PUNCT
ajst-24867	18	14	,	,	PUNCT
ajst-24867	18	15	such	such	ADJ
ajst-24867	18	16	as	as	ADP
ajst-24867	18	17	the	the	DET
ajst-24867	18	18	yolo	yolo	NOUN
ajst-24867	19	1	[	[	X
ajst-24867	19	2	6	6	NUM
ajst-24867	19	3	-	-	SYM
ajst-24867	19	4	8	8	NUM
ajst-24867	19	5	]	]	PUNCT
ajst-24867	19	6	(	(	PUNCT
ajst-24867	19	7	you	you	PRON
ajst-24867	19	8	only	only	ADV
ajst-24867	19	9	look	look	VERB
ajst-24867	19	10	once	once	ADV
ajst-24867	19	11	)	)	PUNCT
ajst-24867	19	12	series	series	NOUN
ajst-24867	19	13	,	,	PUNCT
ajst-24867	19	14	they	they	PRON
ajst-24867	19	15	achieve	achieve	VERB
ajst-24867	19	16	end	end	NOUN
ajst-24867	19	17	-	-	PUNCT
ajst-24867	19	18	to	to	ADP
ajst-24867	19	19	-	-	PUNCT
ajst-24867	19	20	end	end	NOUN
ajst-24867	19	21	object	object	NOUN
ajst-24867	19	22	detection	detection	NOUN
ajst-24867	19	23	through	through	ADP
ajst-24867	19	24	a	a	DET
ajst-24867	19	25	single	single	ADJ
ajst-24867	19	26	-	-	PUNCT
ajst-24867	19	27	stage	stage	NOUN
ajst-24867	19	28	detection	detection	NOUN
ajst-24867	19	29	framework	framework	NOUN
ajst-24867	19	30	,	,	PUNCT
ajst-24867	19	31	greatly	greatly	ADV
ajst-24867	19	32	improving	improve	VERB
ajst-24867	19	33	detection	detection	NOUN
ajst-24867	19	34	speed	speed	NOUN
ajst-24867	19	35	while	while	SCONJ
ajst-24867	19	36	maintaining	maintain	VERB
ajst-24867	19	37	high	high	ADJ
ajst-24867	19	38	accuracy	accuracy	NOUN
ajst-24867	19	39	.	.	PUNCT
ajst-24867	20	1	zhang	zhang	PROPN
ajst-24867	20	2	et	et	PROPN
ajst-24867	20	3	al	al	PROPN
ajst-24867	20	4	.	.	PROPN
ajst-24867	20	5	proposed	propose	VERB
ajst-24867	20	6	an	an	DET
ajst-24867	20	7	egisd	egisd	NOUN
ajst-24867	20	8	-	-	PUNCT
ajst-24867	20	9	yolo	yolo	PROPN
ajst-24867	20	10	and	and	CCONJ
ajst-24867	20	11	designed	design	VERB
ajst-24867	20	12	a	a	DET
ajst-24867	20	13	deconvolution	deconvolution	NOUN
ajst-24867	20	14	channel	channel	NOUN
ajst-24867	20	15	attention	attention	NOUN
ajst-24867	20	16	module	module	NOUN
ajst-24867	20	17	(	(	PUNCT
ajst-24867	20	18	dca	dca	PROPN
ajst-24867	20	19	)	)	PUNCT
ajst-24867	20	20	by	by	ADP
ajst-24867	20	21	improving	improve	VERB
ajst-24867	20	22	the	the	DET
ajst-24867	20	23	csp	csp	PROPN
ajst-24867	20	24	module	module	NOUN
ajst-24867	20	25	of	of	ADP
ajst-24867	20	26	yolo	yolo	PROPN
ajst-24867	20	27	,	,	PUNCT
ajst-24867	20	28	effectively	effectively	ADV
ajst-24867	20	29	reducing	reduce	VERB
ajst-24867	20	30	missed	miss	VERB
ajst-24867	20	31	detections	detection	NOUN
ajst-24867	20	32	of	of	ADP
ajst-24867	20	33	ships	ship	NOUN
ajst-24867	20	34	.	.	PUNCT
ajst-24867	21	1	however	however	ADV
ajst-24867	21	2	,	,	PUNCT
ajst-24867	21	3	its	its	PRON
ajst-24867	21	4	model	model	NOUN
ajst-24867	21	5	is	be	AUX
ajst-24867	21	6	large	large	ADJ
ajst-24867	21	7	and	and	CCONJ
ajst-24867	21	8	not	not	PART
ajst-24867	21	9	suitable	suitable	ADJ
ajst-24867	21	10	for	for	ADP
ajst-24867	21	11	deployment	deployment	NOUN
ajst-24867	21	12	on	on	ADP
ajst-24867	21	13	platforms	platform	NOUN
ajst-24867	21	14	with	with	ADP
ajst-24867	21	15	limited	limited	ADJ
ajst-24867	21	16	computing	compute	VERB
ajst-24867	21	17	resources	resource	NOUN
ajst-24867	21	18	;	;	PUNCT
ajst-24867	21	19	gu	gu	NOUN
ajst-24867	21	20	jiaojiao	jiaojiao	VERB
ajst-24867	21	21	et	et	PROPN
ajst-24867	21	22	al	al	PROPN
ajst-24867	21	23	.	.	PROPN
ajst-24867	21	24	proposed	propose	VERB
ajst-24867	21	25	an	an	DET
ajst-24867	21	26	infrared	infrared	ADJ
ajst-24867	21	27	ship	ship	NOUN
ajst-24867	21	28	target	target	NOUN
ajst-24867	21	29	detection	detection	NOUN
ajst-24867	21	30	algorithm	algorithm	NOUN
ajst-24867	21	31	based	base	VERB
ajst-24867	21	32	on	on	ADP
ajst-24867	21	33	improved	improved	ADJ
ajst-24867	21	34	faster	fast	ADV
ajst-24867	21	35	r	r	NOUN
ajst-24867	21	36	-	-	PUNCT
ajst-24867	21	37	cnn	cnn	NOUN
ajst-24867	21	38	.	.	PUNCT
ajst-24867	22	1	by	by	ADP
ajst-24867	22	2	modifying	modify	VERB
ajst-24867	22	3	the	the	DET
ajst-24867	22	4	backbone	backbone	NOUN
ajst-24867	22	5	network	network	NOUN
ajst-24867	22	6	and	and	CCONJ
ajst-24867	22	7	optimizing	optimize	VERB
ajst-24867	22	8	the	the	DET
ajst-24867	22	9	number	number	NOUN
ajst-24867	22	10	and	and	CCONJ
ajst-24867	22	11	size	size	NOUN
ajst-24867	22	12	of	of	ADP
ajst-24867	22	13	anchor	anchor	NOUN
ajst-24867	22	14	boxes	box	NOUN
ajst-24867	22	15	,	,	PUNCT
ajst-24867	22	16	the	the	DET
ajst-24867	22	17	accuracy	accuracy	NOUN
ajst-24867	22	18	has	have	AUX
ajst-24867	22	19	been	be	AUX
ajst-24867	22	20	improved	improve	VERB
ajst-24867	22	21	to	to	ADP
ajst-24867	22	22	some	some	DET
ajst-24867	22	23	extent	extent	NOUN
ajst-24867	22	24	,	,	PUNCT
ajst-24867	22	25	but	but	CCONJ
ajst-24867	22	26	there	there	PRON
ajst-24867	22	27	is	be	VERB
ajst-24867	22	28	still	still	ADV
ajst-24867	22	29	a	a	DET
ajst-24867	22	30	lot	lot	NOUN
ajst-24867	22	31	of	of	ADP
ajst-24867	22	32	room	room	NOUN
ajst-24867	22	33	for	for	ADP
ajst-24867	22	34	improvement	improvement	NOUN
ajst-24867	22	35	in	in	ADP
ajst-24867	22	36	terms	term	NOUN
ajst-24867	22	37	of	of	ADP
ajst-24867	22	38	accuracy	accuracy	NOUN
ajst-24867	22	39	;	;	PUNCT
ajst-24867	22	40	miao	miao	NOUN
ajst-24867	22	41	et	et	PROPN
ajst-24867	22	42	al	al	PROPN
ajst-24867	22	43	.	.	PROPN
ajst-24867	22	44	proposed	propose	VERB
ajst-24867	22	45	a	a	DET
ajst-24867	22	46	robust	robust	ADJ
ajst-24867	22	47	method	method	NOUN
ajst-24867	22	48	for	for	ADP
ajst-24867	22	49	detecting	detect	VERB
ajst-24867	22	50	ships	ship	NOUN
ajst-24867	22	51	in	in	ADP
ajst-24867	22	52	infrared	infrared	ADJ
ajst-24867	22	53	images	image	NOUN
ajst-24867	22	54	using	use	VERB
ajst-24867	22	55	multi	multi	ADJ
ajst-24867	22	56	-	-	ADJ
ajst-24867	22	57	scale	scale	ADJ
ajst-24867	22	58	feature	feature	NOUN
ajst-24867	22	59	extraction	extraction	NOUN
ajst-24867	22	60	and	and	CCONJ
ajst-24867	22	61	convolutional	convolutional	ADJ
ajst-24867	22	62	neural	neural	ADJ
ajst-24867	22	63	networks	network	NOUN
ajst-24867	22	64	(	(	PUNCT
ajst-24867	22	65	cnn	cnn	PROPN
ajst-24867	22	66	)	)	PUNCT
ajst-24867	22	67	.	.	PUNCT
ajst-24867	23	1	the	the	DET
ajst-24867	23	2	effectiveness	effectiveness	NOUN
ajst-24867	23	3	of	of	ADP
ajst-24867	23	4	this	this	DET
ajst-24867	23	5	method	method	NOUN
ajst-24867	23	6	largely	largely	ADV
ajst-24867	23	7	depends	depend	VERB
ajst-24867	23	8	on	on	ADP
ajst-24867	23	9	the	the	DET
ajst-24867	23	10	quality	quality	NOUN
ajst-24867	23	11	of	of	ADP
ajst-24867	23	12	the	the	DET
ajst-24867	23	13	infrared	infrared	ADJ
ajst-24867	23	14	images	image	NOUN
ajst-24867	23	15	,	,	PUNCT
ajst-24867	23	16	which	which	PRON
ajst-24867	23	17	can	can	AUX
ajst-24867	23	18	lead	lead	VERB
ajst-24867	23	19	to	to	ADP
ajst-24867	23	20	a	a	DET
ajst-24867	23	21	decrease	decrease	NOUN
ajst-24867	23	22	in	in	ADP
ajst-24867	23	23	detection	detection	NOUN
ajst-24867	23	24	performance	performance	NOUN
ajst-24867	23	25	when	when	SCONJ
ajst-24867	23	26	the	the	DET
ajst-24867	23	27	image	image	NOUN
ajst-24867	23	28	quality	quality	NOUN
ajst-24867	23	29	is	be	AUX
ajst-24867	23	30	compromised	compromise	VERB
ajst-24867	23	31	;	;	PUNCT
ajst-24867	23	32	zhang	zhang	PROPN
ajst-24867	23	33	shen	shen	PROPN
ajst-24867	23	34	et	et	PROPN
ajst-24867	23	35	al	al	PROPN
ajst-24867	23	36	.	.	PROPN
ajst-24867	23	37	embedded	embed	VERB
ajst-24867	23	38	the	the	DET
ajst-24867	23	39	mobilenetv3	mobilenetv3	PROPN
ajst-24867	23	40	network	network	NOUN
ajst-24867	23	41	into	into	ADP
ajst-24867	23	42	the	the	DET
ajst-24867	23	43	yolov7	yolov7	NOUN
ajst-24867	23	44	backbone	backbone	NOUN
ajst-24867	23	45	network	network	NOUN
ajst-24867	23	46	and	and	CCONJ
ajst-24867	23	47	introduced	introduce	VERB
ajst-24867	23	48	se	se	PROPN
ajst-24867	23	49	attention	attention	NOUN
ajst-24867	23	50	mechanism	mechanism	NOUN
ajst-24867	23	51	,	,	PUNCT
ajst-24867	23	52	wise	wise	ADJ
ajst-24867	23	53	iou	iou	NOUN
ajst-24867	23	54	loss	loss	NOUN
ajst-24867	23	55	function	function	NOUN
ajst-24867	23	56	,	,	PUNCT
ajst-24867	23	57	and	and	CCONJ
ajst-24867	23	58	bipfn	bipfn	PROPN
ajst-24867	23	59	feature	feature	NOUN
ajst-24867	23	60	pyramid	pyramid	NOUN
ajst-24867	23	61	,	,	PUNCT
ajst-24867	23	62	effectively	effectively	ADV
ajst-24867	23	63	achieving	achieve	VERB
ajst-24867	23	64	high	high	ADJ
ajst-24867	23	65	-	-	PUNCT
ajst-24867	23	66	speed	speed	NOUN
ajst-24867	23	67	and	and	CCONJ
ajst-24867	23	68	highprecision	highprecision	NOUN
ajst-24867	23	69	ship	ship	NOUN
ajst-24867	23	70	detection	detection	NOUN
ajst-24867	23	71	.	.	PUNCT
ajst-24867	24	1	however	however	ADV
ajst-24867	24	2	,	,	PUNCT
ajst-24867	24	3	its	its	PRON
ajst-24867	24	4	computational	computational	ADJ
ajst-24867	24	5	and	and	CCONJ
ajst-24867	24	6	parameter	parameter	NOUN
ajst-24867	24	7	requirements	requirement	NOUN
ajst-24867	24	8	are	be	AUX
ajst-24867	24	9	still	still	ADV
ajst-24867	24	10	relatively	relatively	ADV
ajst-24867	24	11	large	large	ADJ
ajst-24867	24	12	.	.	PUNCT
ajst-24867	25	1	in	in	ADP
ajst-24867	25	2	summary	summary	NOUN
ajst-24867	25	3	,	,	PUNCT
ajst-24867	25	4	although	although	SCONJ
ajst-24867	25	5	some	some	DET
ajst-24867	25	6	progress	progress	NOUN
ajst-24867	25	7	has	have	AUX
ajst-24867	25	8	been	be	AUX
ajst-24867	25	9	made	make	VERB
ajst-24867	25	10	in	in	ADP
ajst-24867	25	11	the	the	DET
ajst-24867	25	12	current	current	ADJ
ajst-24867	25	13	field	field	NOUN
ajst-24867	25	14	of	of	ADP
ajst-24867	25	15	infrared	infrared	ADJ
ajst-24867	25	16	ship	ship	NOUN
ajst-24867	25	17	detection	detection	NOUN
ajst-24867	25	18	,	,	PUNCT
ajst-24867	25	19	there	there	PRON
ajst-24867	25	20	are	be	VERB
ajst-24867	25	21	still	still	ADV
ajst-24867	25	22	problems	problem	NOUN
ajst-24867	25	23	such	such	ADJ
ajst-24867	25	24	as	as	ADP
ajst-24867	25	25	missed	miss	VERB
ajst-24867	25	26	detection	detection	NOUN
ajst-24867	25	27	,	,	PUNCT
ajst-24867	25	28	false	false	ADJ
ajst-24867	25	29	detection	detection	NOUN
ajst-24867	25	30	,	,	PUNCT
ajst-24867	25	31	and	and	CCONJ
ajst-24867	25	32	large	large	ADJ
ajst-24867	25	33	model	model	NOUN
ajst-24867	25	34	size	size	NOUN
ajst-24867	25	35	.	.	PUNCT
ajst-24867	26	1	therefore	therefore	ADV
ajst-24867	26	2	,	,	PUNCT
ajst-24867	26	3	this	this	DET
ajst-24867	26	4	article	article	NOUN
ajst-24867	26	5	proposes	propose	VERB
ajst-24867	26	6	an	an	DET
ajst-24867	26	7	infrared	infrared	ADJ
ajst-24867	26	8	ship	ship	NOUN
ajst-24867	26	9	detection	detection	NOUN
ajst-24867	26	10	model	model	NOUN
ajst-24867	26	11	based	base	VERB
ajst-24867	26	12	on	on	ADP
ajst-24867	26	13	yolov8n	yolov8n	NOUN
ajst-24867	26	14	by	by	ADP
ajst-24867	26	15	adding	add	VERB
ajst-24867	26	16	a	a	DET
ajst-24867	26	17	small	small	ADJ
ajst-24867	26	18	target	target	NOUN
ajst-24867	26	19	layer	layer	NOUN
ajst-24867	26	20	,	,	PUNCT
ajst-24867	26	21	improving	improve	VERB
ajst-24867	26	22	the	the	DET
ajst-24867	26	23	backbone	backbone	NOUN
ajst-24867	26	24	downsampling	downsampling	NOUN
ajst-24867	26	25	and	and	CCONJ
ajst-24867	26	26	loss	loss	NOUN
ajst-24867	26	27	function	function	NOUN
ajst-24867	26	28	,	,	PUNCT
ajst-24867	26	29	which	which	PRON
ajst-24867	26	30	effectively	effectively	ADV
ajst-24867	26	31	improves	improve	VERB
ajst-24867	26	32	detection	detection	NOUN
ajst-24867	26	33	performance	performance	NOUN
ajst-24867	26	34	and	and	CCONJ
ajst-24867	26	35	is	be	AUX
ajst-24867	26	36	easy	easy	ADJ
ajst-24867	26	37	to	to	PART
ajst-24867	26	38	deploy	deploy	VERB
ajst-24867	26	39	on	on	ADP
ajst-24867	26	40	devices	device	NOUN
ajst-24867	26	41	with	with	ADP
ajst-24867	26	42	limited	limited	ADJ
ajst-24867	26	43	computing	computing	NOUN
ajst-24867	26	44	resources	resource	NOUN
ajst-24867	26	45	.	.	PUNCT
ajst-24867	27	1	2	2	X
ajst-24867	27	2	.	.	X
ajst-24867	27	3	introduction	introduction	NOUN
ajst-24867	27	4	to	to	ADP
ajst-24867	27	5	yolov8n	yolov8n	PROPN
ajst-24867	27	6	algorithm	algorithm	NOUN
ajst-24867	27	7	yolov8	yolov8	NOUN
ajst-24867	27	8	is	be	AUX
ajst-24867	27	9	a	a	DET
ajst-24867	27	10	new	new	ADJ
ajst-24867	27	11	generation	generation	NOUN
ajst-24867	27	12	sota	sota	NOUN
ajst-24867	27	13	model	model	NOUN
ajst-24867	27	14	released	release	VERB
ajst-24867	27	15	by	by	ADP
ajst-24867	27	16	ultralytics	ultralytic	NOUN
ajst-24867	27	17	.	.	PUNCT
ajst-24867	28	1	it	it	PRON
ajst-24867	28	2	refers	refer	VERB
ajst-24867	28	3	to	to	ADP
ajst-24867	28	4	the	the	DET
ajst-24867	28	5	elan	elan	PROPN
ajst-24867	28	6	design	design	NOUN
ajst-24867	28	7	concept	concept	NOUN
ajst-24867	28	8	of	of	ADP
ajst-24867	28	9	yolov7	yolov7	NOUN
ajst-24867	28	10	,	,	PUNCT
ajst-24867	28	11	replaces	replace	VERB
ajst-24867	28	12	the	the	DET
ajst-24867	28	13	c3	c3	NOUN
ajst-24867	28	14	structure	structure	NOUN
ajst-24867	28	15	of	of	ADP
ajst-24867	28	16	yolov5	yolov5	NOUN
ajst-24867	28	17	with	with	ADP
ajst-24867	28	18	c2f	c2f	NOUN
ajst-24867	28	19	structure	structure	NOUN
ajst-24867	28	20	,	,	PUNCT
ajst-24867	28	21	adopts	adopt	VERB
ajst-24867	28	22	anchor	anchor	NOUN
ajst-24867	28	23	free	free	ADJ
ajst-24867	28	24	detection	detection	NOUN
ajst-24867	28	25	head	head	NOUN
ajst-24867	28	26	,	,	PUNCT
ajst-24867	28	27	and	and	CCONJ
ajst-24867	28	28	the	the	DET
ajst-24867	28	29	loss	loss	NOUN
ajst-24867	28	30	calculation	calculation	NOUN
ajst-24867	28	31	includes	include	VERB
ajst-24867	28	32	two	two	NUM
ajst-24867	28	33	parts	part	NOUN
ajst-24867	28	34	:	:	PUNCT
ajst-24867	28	35	classification	classification	NOUN
ajst-24867	28	36	and	and	CCONJ
ajst-24867	28	37	regression	regression	NOUN
ajst-24867	28	38	,	,	PUNCT
ajst-24867	28	39	excluding	exclude	VERB
ajst-24867	28	40	objective	objective	ADJ
ajst-24867	28	41	branches	branch	NOUN
ajst-24867	28	42	.	.	PUNCT
ajst-24867	29	1	the	the	DET
ajst-24867	29	2	classification	classification	NOUN
ajst-24867	29	3	branch	branch	NOUN
ajst-24867	29	4	uses	use	VERB
ajst-24867	29	5	binary	binary	PROPN
ajst-24867	29	6	81	81	NUM
ajst-24867	29	7	cross	cross	NOUN
ajst-24867	29	8	entropy	entropy	PROPN
ajst-24867	29	9	(	(	PUNCT
ajst-24867	29	10	bce	bce	NOUN
ajst-24867	29	11	)	)	PUNCT
ajst-24867	29	12	loss	loss	NOUN
ajst-24867	29	13	,	,	PUNCT
ajst-24867	29	14	while	while	SCONJ
ajst-24867	29	15	the	the	DET
ajst-24867	29	16	regression	regression	NOUN
ajst-24867	29	17	branch	branch	NOUN
ajst-24867	29	18	uses	use	VERB
ajst-24867	29	19	distribution	distribution	NOUN
ajst-24867	29	20	focus	focus	NOUN
ajst-24867	29	21	loss	loss	NOUN
ajst-24867	29	22	(	(	PUNCT
ajst-24867	29	23	dfl	dfl	PROPN
ajst-24867	29	24	)	)	PUNCT
ajst-24867	29	25	and	and	CCONJ
ajst-24867	29	26	ciou	ciou	NOUN
ajst-24867	29	27	loss	loss	NOUN
ajst-24867	29	28	functions	function	NOUN
ajst-24867	29	29	.	.	PUNCT
ajst-24867	30	1	the	the	DET
ajst-24867	30	2	network	network	NOUN
ajst-24867	30	3	structure	structure	NOUN
ajst-24867	30	4	of	of	ADP
ajst-24867	30	5	yolov8	yolov8	NOUN
ajst-24867	30	6	includes	include	VERB
ajst-24867	30	7	an	an	DET
ajst-24867	30	8	input	input	NOUN
ajst-24867	30	9	part	part	NOUN
ajst-24867	30	10	,	,	PUNCT
ajst-24867	30	11	a	a	DET
ajst-24867	30	12	backbone	backbone	NOUN
ajst-24867	30	13	network	network	NOUN
ajst-24867	30	14	,	,	PUNCT
ajst-24867	30	15	a	a	DET
ajst-24867	30	16	neck	neck	NOUN
ajst-24867	30	17	module	module	NOUN
ajst-24867	30	18	,	,	PUNCT
ajst-24867	30	19	and	and	CCONJ
ajst-24867	30	20	an	an	DET
ajst-24867	30	21	output	output	NOUN
ajst-24867	30	22	part	part	NOUN
ajst-24867	30	23	.	.	PUNCT
ajst-24867	31	1	the	the	DET
ajst-24867	31	2	input	input	NOUN
ajst-24867	31	3	part	part	NOUN
ajst-24867	31	4	performs	perform	VERB
ajst-24867	31	5	mosaic	mosaic	ADJ
ajst-24867	31	6	data	datum	NOUN
ajst-24867	31	7	enhancement	enhancement	NOUN
ajst-24867	31	8	,	,	PUNCT
ajst-24867	31	9	adaptive	adaptive	ADJ
ajst-24867	31	10	anchor	anchor	NOUN
ajst-24867	31	11	point	point	NOUN
ajst-24867	31	12	calculation	calculation	NOUN
ajst-24867	31	13	,	,	PUNCT
ajst-24867	31	14	and	and	CCONJ
ajst-24867	31	15	adaptive	adaptive	ADJ
ajst-24867	31	16	grayscale	grayscale	NOUN
ajst-24867	31	17	filling	fill	VERB
ajst-24867	31	18	on	on	ADP
ajst-24867	31	19	the	the	DET
ajst-24867	31	20	input	input	NOUN
ajst-24867	31	21	image	image	NOUN
ajst-24867	31	22	.	.	PUNCT
ajst-24867	32	1	the	the	DET
ajst-24867	32	2	neck	neck	NOUN
ajst-24867	32	3	module	module	NOUN
ajst-24867	32	4	adopts	adopt	VERB
ajst-24867	32	5	fpn+pan	fpn+pan	PROPN
ajst-24867	32	6	structure	structure	NOUN
ajst-24867	32	7	to	to	PART
ajst-24867	32	8	enhance	enhance	VERB
ajst-24867	32	9	the	the	DET
ajst-24867	32	10	feature	feature	NOUN
ajst-24867	32	11	fusion	fusion	NOUN
ajst-24867	32	12	ability	ability	NOUN
ajst-24867	32	13	of	of	ADP
ajst-24867	32	14	the	the	DET
ajst-24867	32	15	model	model	NOUN
ajst-24867	32	16	,	,	PUNCT
ajst-24867	32	17	and	and	CCONJ
ajst-24867	32	18	combines	combine	VERB
ajst-24867	32	19	up	up	ADP
ajst-24867	32	20	sampling	sample	VERB
ajst-24867	32	21	and	and	CCONJ
ajst-24867	32	22	down	down	ADV
ajst-24867	32	23	sampling	sample	VERB
ajst-24867	32	24	techniques	technique	NOUN
ajst-24867	32	25	with	with	ADP
ajst-24867	32	26	high	high	ADJ
ajst-24867	32	27	-	-	PUNCT
ajst-24867	32	28	level	level	NOUN
ajst-24867	32	29	and	and	CCONJ
ajst-24867	32	30	low	low	ADJ
ajst-24867	32	31	-	-	PUNCT
ajst-24867	32	32	level	level	NOUN
ajst-24867	32	33	feature	feature	NOUN
ajst-24867	32	34	maps	map	NOUN
ajst-24867	32	35	to	to	PART
ajst-24867	32	36	improve	improve	VERB
ajst-24867	32	37	the	the	DET
ajst-24867	32	38	detection	detection	NOUN
ajst-24867	32	39	performance	performance	NOUN
ajst-24867	32	40	of	of	ADP
ajst-24867	32	41	objects	object	NOUN
ajst-24867	32	42	of	of	ADP
ajst-24867	32	43	different	different	ADJ
ajst-24867	32	44	scales	scale	NOUN
ajst-24867	32	45	.	.	PUNCT
ajst-24867	33	1	it	it	PRON
ajst-24867	33	2	provides	provide	VERB
ajst-24867	33	3	five	five	NUM
ajst-24867	33	4	scaled	scale	VERB
ajst-24867	33	5	versions	version	NOUN
ajst-24867	33	6	(	(	PUNCT
ajst-24867	33	7	n	n	CCONJ
ajst-24867	33	8	/	/	SYM
ajst-24867	33	9	s	s	NOUN
ajst-24867	33	10	/	/	SYM
ajst-24867	33	11	m	m	NOUN
ajst-24867	33	12	/	/	SYM
ajst-24867	33	13	l	l	NOUN
ajst-24867	33	14	/	/	SYM
ajst-24867	33	15	x	x	NOUN
ajst-24867	33	16	)	)	PUNCT
ajst-24867	33	17	to	to	PART
ajst-24867	33	18	meet	meet	VERB
ajst-24867	33	19	the	the	DET
ajst-24867	33	20	needs	need	NOUN
ajst-24867	33	21	of	of	ADP
ajst-24867	33	22	different	different	ADJ
ajst-24867	33	23	computing	computing	NOUN
ajst-24867	33	24	capabilities	capability	NOUN
ajst-24867	33	25	and	and	CCONJ
ajst-24867	33	26	application	application	NOUN
ajst-24867	33	27	scenarios	scenario	NOUN
ajst-24867	33	28	.	.	PUNCT
ajst-24867	34	1	taking	take	VERB
ajst-24867	34	2	into	into	ADP
ajst-24867	34	3	account	account	NOUN
ajst-24867	34	4	all	all	DET
ajst-24867	34	5	factors	factor	NOUN
ajst-24867	34	6	,	,	PUNCT
ajst-24867	34	7	this	this	DET
ajst-24867	34	8	article	article	NOUN
ajst-24867	34	9	improves	improve	VERB
ajst-24867	34	10	yolov8n	yolov8n	NOUN
ajst-24867	34	11	,	,	PUNCT
ajst-24867	34	12	and	and	CCONJ
ajst-24867	34	13	the	the	DET
ajst-24867	34	14	yolov8	yolov8	NOUN
ajst-24867	34	15	structure	structure	NOUN
ajst-24867	34	16	diagram	diagram	NOUN
ajst-24867	34	17	is	be	AUX
ajst-24867	34	18	shown	show	VERB
ajst-24867	34	19	in	in	ADP
ajst-24867	34	20	figure	figure	NOUN
ajst-24867	34	21	1	1	NUM
ajst-24867	34	22	.	.	PUNCT
ajst-24867	35	1	conv	conv	PROPN
ajst-24867	35	2	c2f	c2f	PROPN
ajst-24867	35	3	conv	conv	PROPN
ajst-24867	35	4	c2f	c2f	PROPN
ajst-24867	35	5	conv	conv	PROPN
ajst-24867	35	6	c2f	c2f	PROPN
ajst-24867	35	7	conv	conv	PROPN
ajst-24867	35	8	c2f	c2f	PROPN
ajst-24867	35	9	conv	conv	PROPN
ajst-24867	35	10	c2f	c2f	PROPN
ajst-24867	35	11	upsample	upsample	PROPN
ajst-24867	35	12	upsample	upsample	PROPN
ajst-24867	35	13	c2f	c2f	PROPN
ajst-24867	35	14	conv	conv	PROPN
ajst-24867	35	15	c2f	c2f	PROPN
ajst-24867	35	16	conv	conv	PROPN
ajst-24867	35	17	c2f	c2f	PROPN
ajst-24867	35	18	backbone	backbone	PROPN
ajst-24867	35	19	neck	neck	PROPN
ajst-24867	35	20	head	head	NOUN
ajst-24867	35	21	concat	concat	PROPN
ajst-24867	35	22	concat	concat	PROPN
ajst-24867	35	23	concat	concat	PROPN
ajst-24867	35	24	concat	concat	NOUN
ajst-24867	35	25	detect	detect	VERB
ajst-24867	35	26	detect	detect	NOUN
ajst-24867	35	27	detectsppf	detectsppf	NOUN
ajst-24867	35	28	input	input	NOUN
ajst-24867	35	29	640x640	640x640	NUM
ajst-24867	35	30	figure	figure	NOUN
ajst-24867	35	31	1	1	NUM
ajst-24867	35	32	.	.	PUNCT
ajst-24867	36	1	yolov8	yolov8	NOUN
ajst-24867	36	2	structure	structure	PROPN
ajst-24867	36	3	diagram	diagram	PROPN
ajst-24867	36	4	3	3	NUM
ajst-24867	36	5	.	.	PUNCT
ajst-24867	36	6	improved	improve	VERB
ajst-24867	36	7	yolov8n	yolov8n	PROPN
ajst-24867	36	8	models	model	NOUN
ajst-24867	36	9	conv	conv	PROPN
ajst-24867	36	10	c2f	c2f	PROPN
ajst-24867	36	11	conv	conv	PROPN
ajst-24867	36	12	c2f	c2f	PROPN
ajst-24867	36	13	v7ds	v7ds	X
ajst-24867	37	1	c2f	c2f	VERB
ajst-24867	37	2	v7ds	v7ds	X
ajst-24867	37	3	v7ds	v7ds	X
ajst-24867	38	1	c2f	c2f	PROPN
ajst-24867	38	2	concat	concat	PROPN
ajst-24867	38	3	upsample	upsample	PROPN
ajst-24867	38	4	upsample	upsample	PROPN
ajst-24867	38	5	concat	concat	PROPN
ajst-24867	38	6	v7ds	v7ds	PUNCT
ajst-24867	38	7	c2f	c2f	PROPN
ajst-24867	38	8	c2f	c2f	PROPN
ajst-24867	38	9	v7ds	v7ds	X
ajst-24867	39	1	concat	concat	X
ajst-24867	39	2	backbone	backbone	NOUN
ajst-24867	39	3	neck	neck	PROPN
ajst-24867	39	4	head	head	NOUN
ajst-24867	39	5	c2f	c2f	PROPN
ajst-24867	39	6	concat	concat	PROPN
ajst-24867	39	7	upsample	upsample	VERB
ajst-24867	39	8	v7ds	v7ds	X
ajst-24867	39	9	concat	concat	PROPN
ajst-24867	39	10	c2f	c2f	PROPN
ajst-24867	39	11	c2f	c2f	PROPN
ajst-24867	39	12	c2f	c2f	NOUN
ajst-24867	39	13	c2fsppf	c2fsppf	NOUN
ajst-24867	39	14	detect	detect	VERB
ajst-24867	39	15	detect	detect	NOUN
ajst-24867	39	16	detect	detect	NOUN
ajst-24867	39	17	detect	detect	NOUN
ajst-24867	39	18	input	input	NOUN
ajst-24867	39	19	640x640	640x640	NUM
ajst-24867	39	20	figure	figure	NOUN
ajst-24867	39	21	2	2	NUM
ajst-24867	39	22	.	.	PUNCT
ajst-24867	39	23	improved	improve	VERB
ajst-24867	39	24	model	model	NOUN
ajst-24867	39	25	structure	structure	NOUN
ajst-24867	39	26	diagram	diagram	NOUN
ajst-24867	39	27	the	the	DET
ajst-24867	39	28	improved	improved	ADJ
ajst-24867	39	29	model	model	NOUN
ajst-24867	39	30	structure	structure	NOUN
ajst-24867	39	31	is	be	AUX
ajst-24867	39	32	shown	show	VERB
ajst-24867	39	33	in	in	ADP
ajst-24867	39	34	figure	figure	NOUN
ajst-24867	39	35	2	2	NUM
ajst-24867	39	36	.	.	PUNCT
ajst-24867	39	37	firstly	firstly	ADV
ajst-24867	39	38	,	,	PUNCT
ajst-24867	39	39	adding	add	VERB
ajst-24867	39	40	a	a	DET
ajst-24867	39	41	small	small	ADJ
ajst-24867	39	42	target	target	NOUN
ajst-24867	39	43	detection	detection	NOUN
ajst-24867	39	44	layer	layer	NOUN
ajst-24867	39	45	at	at	ADP
ajst-24867	39	46	the	the	DET
ajst-24867	39	47	head	head	NOUN
ajst-24867	39	48	enhances	enhance	VERB
ajst-24867	39	49	the	the	DET
ajst-24867	39	50	ability	ability	NOUN
ajst-24867	39	51	to	to	PART
ajst-24867	39	52	extract	extract	VERB
ajst-24867	39	53	small	small	ADJ
ajst-24867	39	54	target	target	NOUN
ajst-24867	39	55	features	feature	NOUN
ajst-24867	39	56	,	,	PUNCT
ajst-24867	39	57	thereby	thereby	ADV
ajst-24867	39	58	improving	improve	VERB
ajst-24867	39	59	the	the	DET
ajst-24867	39	60	detection	detection	NOUN
ajst-24867	39	61	accuracy	accuracy	NOUN
ajst-24867	39	62	of	of	ADP
ajst-24867	39	63	small	small	ADJ
ajst-24867	39	64	ship	ship	NOUN
ajst-24867	39	65	targets	target	NOUN
ajst-24867	39	66	.	.	PUNCT
ajst-24867	40	1	secondly	secondly	ADV
ajst-24867	40	2	,	,	PUNCT
ajst-24867	40	3	the	the	DET
ajst-24867	40	4	focaler	focaler	NOUN
ajst-24867	40	5	mpdiou	mpdiou	NOUN
ajst-24867	40	6	loss	loss	NOUN
ajst-24867	40	7	function	function	NOUN
ajst-24867	40	8	is	be	AUX
ajst-24867	40	9	used	use	VERB
ajst-24867	40	10	to	to	PART
ajst-24867	40	11	replace	replace	VERB
ajst-24867	40	12	the	the	DET
ajst-24867	40	13	default	default	NOUN
ajst-24867	40	14	ciou	ciou	NOUN
ajst-24867	40	15	loss	loss	NOUN
ajst-24867	40	16	function	function	NOUN
ajst-24867	40	17	,	,	PUNCT
ajst-24867	40	18	improving	improve	VERB
ajst-24867	40	19	the	the	DET
ajst-24867	40	20	performance	performance	NOUN
ajst-24867	40	21	and	and	CCONJ
ajst-24867	40	22	convergence	convergence	NOUN
ajst-24867	40	23	speed	speed	NOUN
ajst-24867	40	24	of	of	ADP
ajst-24867	40	25	the	the	DET
ajst-24867	40	26	model	model	NOUN
ajst-24867	40	27	on	on	ADP
ajst-24867	40	28	small	small	ADJ
ajst-24867	40	29	or	or	CCONJ
ajst-24867	40	30	severely	severely	ADV
ajst-24867	40	31	occluded	occluded	ADJ
ajst-24867	40	32	objects	object	NOUN
ajst-24867	40	33	.	.	PUNCT
ajst-24867	41	1	finally	finally	ADV
ajst-24867	41	2	,	,	PUNCT
ajst-24867	41	3	the	the	DET
ajst-24867	41	4	v8	v8	PROPN
ajst-24867	41	5	downsampling	downsampling	NOUN
ajst-24867	41	6	is	be	AUX
ajst-24867	41	7	improved	improve	VERB
ajst-24867	41	8	to	to	ADP
ajst-24867	41	9	v7ds	v7d	NOUN
ajst-24867	41	10	,	,	PUNCT
ajst-24867	41	11	which	which	PRON
ajst-24867	41	12	improves	improve	VERB
ajst-24867	41	13	the	the	DET
ajst-24867	41	14	accuracy	accuracy	NOUN
ajst-24867	41	15	of	of	ADP
ajst-24867	41	16	ship	ship	NOUN
ajst-24867	41	17	detection	detection	NOUN
ajst-24867	41	18	and	and	CCONJ
ajst-24867	41	19	reduces	reduce	VERB
ajst-24867	41	20	the	the	DET
ajst-24867	41	21	number	number	NOUN
ajst-24867	41	22	of	of	ADP
ajst-24867	41	23	model	model	NOUN
ajst-24867	41	24	parameters	parameter	NOUN
ajst-24867	41	25	and	and	CCONJ
ajst-24867	41	26	computational	computational	ADJ
ajst-24867	41	27	complexity	complexity	NOUN
ajst-24867	41	28	of	of	ADP
ajst-24867	41	29	the	the	DET
ajst-24867	41	30	small	small	ADJ
ajst-24867	41	31	target	target	NOUN
ajst-24867	41	32	detection	detection	NOUN
ajst-24867	41	33	layer	layer	NOUN
ajst-24867	41	34	to	to	ADP
ajst-24867	41	35	a	a	DET
ajst-24867	41	36	certain	certain	ADJ
ajst-24867	41	37	extent	extent	NOUN
ajst-24867	41	38	.	.	PUNCT
ajst-24867	42	1	3.1	3.1	NUM
ajst-24867	42	2	.	.	PUNCT
ajst-24867	42	3	adding	add	VERB
ajst-24867	42	4	a	a	DET
ajst-24867	42	5	small	small	ADJ
ajst-24867	42	6	object	object	NOUN
ajst-24867	42	7	detection	detection	NOUN
ajst-24867	42	8	layer	layer	NOUN
ajst-24867	42	9	in	in	ADP
ajst-24867	42	10	many	many	ADJ
ajst-24867	42	11	ship	ship	NOUN
ajst-24867	42	12	images	image	NOUN
ajst-24867	42	13	or	or	CCONJ
ajst-24867	42	14	videos	video	NOUN
ajst-24867	42	15	,	,	PUNCT
ajst-24867	42	16	the	the	DET
ajst-24867	42	17	target	target	NOUN
ajst-24867	42	18	appears	appear	VERB
ajst-24867	42	19	smaller	small	ADJ
ajst-24867	42	20	in	in	ADP
ajst-24867	42	21	proportion	proportion	NOUN
ajst-24867	42	22	due	due	ADP
ajst-24867	42	23	to	to	ADP
ajst-24867	42	24	its	its	PRON
ajst-24867	42	25	distance	distance	NOUN
ajst-24867	42	26	.	.	PUNCT
ajst-24867	43	1	due	due	ADP
ajst-24867	43	2	to	to	ADP
ajst-24867	43	3	the	the	DET
ajst-24867	43	4	limitation	limitation	NOUN
ajst-24867	43	5	of	of	ADP
ajst-24867	43	6	receptive	receptive	ADJ
ajst-24867	43	7	field	field	NOUN
ajst-24867	43	8	,	,	PUNCT
ajst-24867	43	9	the	the	DET
ajst-24867	43	10	80	80	NUM
ajst-24867	43	11	×	×	NOUN
ajst-24867	43	12	80	80	NUM
ajst-24867	43	13	maximum	maximum	ADJ
ajst-24867	43	14	feature	feature	NOUN
ajst-24867	43	15	layer	layer	NOUN
ajst-24867	43	16	used	use	VERB
ajst-24867	43	17	in	in	ADP
ajst-24867	43	18	the	the	DET
ajst-24867	43	19	original	original	ADJ
ajst-24867	43	20	yolov8	yolov8	NOUN
ajst-24867	43	21	often	often	ADV
ajst-24867	43	22	misses	miss	VERB
ajst-24867	43	23	some	some	DET
ajst-24867	43	24	targets	target	NOUN
ajst-24867	43	25	with	with	ADP
ajst-24867	43	26	fewer	few	ADJ
ajst-24867	43	27	pixels	pixel	NOUN
ajst-24867	43	28	.	.	PUNCT
ajst-24867	44	1	to	to	PART
ajst-24867	44	2	address	address	VERB
ajst-24867	44	3	this	this	DET
ajst-24867	44	4	issue	issue	NOUN
ajst-24867	44	5	,	,	PUNCT
ajst-24867	44	6	we	we	PRON
ajst-24867	44	7	have	have	AUX
ajst-24867	44	8	added	add	VERB
ajst-24867	44	9	a	a	DET
ajst-24867	44	10	160	160	NUM
ajst-24867	44	11	×	×	NOUN
ajst-24867	44	12	160	160	NUM
ajst-24867	44	13	extra	extra	ADJ
ajst-24867	44	14	large	large	ADJ
ajst-24867	44	15	feature	feature	NOUN
ajst-24867	44	16	layer	layer	NOUN
ajst-24867	44	17	specifically	specifically	ADV
ajst-24867	44	18	designed	design	VERB
ajst-24867	44	19	for	for	ADP
ajst-24867	44	20	detecting	detect	VERB
ajst-24867	44	21	smaller	small	ADJ
ajst-24867	44	22	targets	target	NOUN
ajst-24867	44	23	.	.	PUNCT
ajst-24867	45	1	this	this	DET
ajst-24867	45	2	improvement	improvement	NOUN
ajst-24867	45	3	addresses	address	VERB
ajst-24867	45	4	the	the	DET
ajst-24867	45	5	shortcomings	shortcoming	NOUN
ajst-24867	45	6	of	of	ADP
ajst-24867	45	7	the	the	DET
ajst-24867	45	8	original	original	ADJ
ajst-24867	45	9	algorithm	algorithm	NOUN
ajst-24867	45	10	in	in	ADP
ajst-24867	45	11	small	small	ADJ
ajst-24867	45	12	object	object	NOUN
ajst-24867	45	13	detection	detection	NOUN
ajst-24867	45	14	.	.	PUNCT
ajst-24867	46	1	although	although	SCONJ
ajst-24867	46	2	adding	add	VERB
ajst-24867	46	3	this	this	DET
ajst-24867	46	4	detection	detection	NOUN
ajst-24867	46	5	head	head	NOUN
ajst-24867	46	6	increases	increase	VERB
ajst-24867	46	7	the	the	DET
ajst-24867	46	8	computational	computational	ADJ
ajst-24867	46	9	and	and	CCONJ
ajst-24867	46	10	memory	memory	NOUN
ajst-24867	46	11	overhead	overhead	NOUN
ajst-24867	46	12	of	of	ADP
ajst-24867	46	13	the	the	DET
ajst-24867	46	14	model	model	NOUN
ajst-24867	46	15	,	,	PUNCT
ajst-24867	46	16	it	it	PRON
ajst-24867	46	17	significantly	significantly	ADV
ajst-24867	46	18	improves	improve	VERB
ajst-24867	46	19	the	the	DET
ajst-24867	46	20	accuracy	accuracy	NOUN
ajst-24867	46	21	of	of	ADP
ajst-24867	46	22	small	small	ADJ
ajst-24867	46	23	object	object	NOUN
ajst-24867	46	24	detection	detection	NOUN
ajst-24867	46	25	from	from	ADP
ajst-24867	46	26	ships	ship	NOUN
ajst-24867	46	27	and	and	CCONJ
ajst-24867	46	28	greatly	greatly	ADV
ajst-24867	46	29	reduces	reduce	VERB
ajst-24867	46	30	the	the	DET
ajst-24867	46	31	missed	miss	VERB
ajst-24867	46	32	detection	detection	NOUN
ajst-24867	46	33	rate	rate	NOUN
ajst-24867	46	34	of	of	ADP
ajst-24867	46	35	small	small	ADJ
ajst-24867	46	36	object	object	NOUN
ajst-24867	46	37	ships	ship	NOUN
ajst-24867	46	38	.	.	PUNCT
ajst-24867	47	1	the	the	DET
ajst-24867	47	2	improved	improved	ADJ
ajst-24867	47	3	head	head	NOUN
ajst-24867	47	4	is	be	AUX
ajst-24867	47	5	shown	show	VERB
ajst-24867	47	6	in	in	ADP
ajst-24867	47	7	figure	figure	NOUN
ajst-24867	47	8	3	3	NUM
ajst-24867	47	9	below	below	ADV
ajst-24867	47	10	.	.	PUNCT
ajst-24867	48	1	p1	p1	NOUN
ajst-24867	48	2	p2	p2	PROPN
ajst-24867	48	3	p3	p3	PROPN
ajst-24867	48	4	p4	p4	ADJ
ajst-24867	48	5	p5	p5	PROPN
ajst-24867	48	6	fpn	fpn	VERB
ajst-24867	48	7	pan	pan	NOUN
ajst-24867	48	8	input	input	NOUN
ajst-24867	48	9	640x640	640x640	NUM
ajst-24867	48	10	tiny	tiny	ADJ
ajst-24867	48	11	head	head	NOUN
ajst-24867	48	12	small	small	ADJ
ajst-24867	48	13	head	head	NOUN
ajst-24867	48	14	backbone	backbone	NOUN
ajst-24867	48	15	large	large	ADJ
ajst-24867	48	16	head	head	NOUN
ajst-24867	48	17	mid	mid	ADJ
ajst-24867	48	18	head	head	NOUN
ajst-24867	48	19	neck	neck	NOUN
ajst-24867	48	20	160x160	160x160	PROPN
ajst-24867	48	21	20x20	20x20	NUM
ajst-24867	48	22	40x40	40x40	NUM
ajst-24867	48	23	80x80	80x80	NUM
ajst-24867	48	24	head	head	NOUN
ajst-24867	48	25	figure	figure	NOUN
ajst-24867	48	26	3	3	NUM
ajst-24867	48	27	.	.	PUNCT
ajst-24867	48	28	improved	improve	VERB
ajst-24867	48	29	head	head	NOUN
ajst-24867	48	30	structure	structure	NOUN
ajst-24867	48	31	diagram	diagram	NOUN
ajst-24867	48	32	3.2	3.2	NUM
ajst-24867	48	33	.	.	PUNCT
ajst-24867	49	1	new	new	ADJ
ajst-24867	49	2	loss	loss	NOUN
ajst-24867	49	3	function	function	NOUN
ajst-24867	49	4	-	-	PUNCT
ajst-24867	49	5	focal	focal	ADJ
ajst-24867	49	6	mpdiou	mpdiou	NOUN
ajst-24867	49	7	in	in	ADP
ajst-24867	49	8	object	object	NOUN
ajst-24867	49	9	detection	detection	NOUN
ajst-24867	49	10	,	,	PUNCT
ajst-24867	49	11	iou	iou	PROPN
ajst-24867	49	12	is	be	AUX
ajst-24867	49	13	a	a	DET
ajst-24867	49	14	very	very	ADV
ajst-24867	49	15	important	important	ADJ
ajst-24867	49	16	metric	metric	NOUN
ajst-24867	49	17	used	use	VERB
ajst-24867	49	18	to	to	PART
ajst-24867	49	19	evaluate	evaluate	VERB
ajst-24867	49	20	the	the	DET
ajst-24867	49	21	degree	degree	NOUN
ajst-24867	49	22	of	of	ADP
ajst-24867	49	23	overlap	overlap	NOUN
ajst-24867	49	24	between	between	ADP
ajst-24867	49	25	predicted	predict	VERB
ajst-24867	49	26	bounding	bounding	NOUN
ajst-24867	49	27	boxes	box	NOUN
ajst-24867	49	28	and	and	CCONJ
ajst-24867	49	29	real	real	ADJ
ajst-24867	49	30	bounding	bounding	NOUN
ajst-24867	49	31	boxes	box	NOUN
ajst-24867	49	32	.	.	PUNCT
ajst-24867	50	1	iou	iou	NOUN
ajst-24867	50	2	values	value	NOUN
ajst-24867	50	3	range	range	VERB
ajst-24867	50	4	from	from	ADP
ajst-24867	50	5	0	0	NUM
ajst-24867	50	6	to	to	ADP
ajst-24867	50	7	1	1	NUM
ajst-24867	50	8	,	,	PUNCT
ajst-24867	50	9	with	with	ADP
ajst-24867	50	10	higher	high	ADJ
ajst-24867	50	11	values	value	NOUN
ajst-24867	50	12	indicating	indicate	VERB
ajst-24867	50	13	greater	great	ADJ
ajst-24867	50	14	overlap	overlap	NOUN
ajst-24867	50	15	between	between	ADP
ajst-24867	50	16	predicted	predict	VERB
ajst-24867	50	17	and	and	CCONJ
ajst-24867	50	18	real	real	ADJ
ajst-24867	50	19	bounding	bounding	NOUN
ajst-24867	50	20	boxes	box	NOUN
ajst-24867	50	21	,	,	PUNCT
ajst-24867	50	22	resulting	result	VERB
ajst-24867	50	23	in	in	ADP
ajst-24867	50	24	higher	high	ADJ
ajst-24867	50	25	accuracy	accuracy	NOUN
ajst-24867	50	26	in	in	ADP
ajst-24867	50	27	object	object	NOUN
ajst-24867	50	28	detection	detection	NOUN
ajst-24867	50	29	.	.	PUNCT
ajst-24867	51	1	the	the	DET
ajst-24867	51	2	calculation	calculation	NOUN
ajst-24867	51	3	formula	formula	NOUN
ajst-24867	51	4	is	be	AUX
ajst-24867	51	5	as	as	SCONJ
ajst-24867	51	6	follows	follow	VERB
ajst-24867	51	7	:	:	PUNCT
ajst-24867	51	8	pred	pre	VERB
ajst-24867	51	9	gt	gt	PROPN
ajst-24867	51	10	pred	pre	VERB
ajst-24867	51	11	gt	gt	PROPN
ajst-24867	51	12	b	b	PROPN
ajst-24867	51	13	b	b	PROPN
ajst-24867	51	14	iou	iou	PROPN
ajst-24867	51	15	b	b	PROPN
ajst-24867	51	16	b	b	PROPN
ajst-24867	51	17			PUNCT
ajst-24867	51	18			PROPN
ajst-24867	51	19			NOUN
ajst-24867	51	20	(	(	PUNCT
ajst-24867	51	21	1	1	NUM
ajst-24867	51	22	)	)	PUNCT
ajst-24867	51	23	among	among	ADP
ajst-24867	51	24	them	they	PRON
ajst-24867	51	25	,	,	PUNCT
ajst-24867	51	26	predb	predb	PROPN
ajst-24867	51	27	is	be	AUX
ajst-24867	51	28	the	the	DET
ajst-24867	51	29	predicted	predict	VERB
ajst-24867	51	30	bounding	bounding	NOUN
ajst-24867	51	31	box	box	NOUN
ajst-24867	51	32	and	and	CCONJ
ajst-24867	51	33	gtb	gtb	NOUN
ajst-24867	51	34	is	be	AUX
ajst-24867	51	35	the	the	DET
ajst-24867	51	36	real	real	ADJ
ajst-24867	51	37	bounding	bounding	NOUN
ajst-24867	51	38	box	box	NOUN
ajst-24867	51	39	.	.	PUNCT
ajst-24867	52	1	focaler	focaler	PROPN
ajst-24867	52	2	iou	iou	PROPN
ajst-24867	53	1	[	[	PUNCT
ajst-24867	53	2	13	13	NUM
ajst-24867	53	3	]	]	PUNCT
ajst-24867	53	4	is	be	AUX
ajst-24867	53	5	a	a	DET
ajst-24867	53	6	loss	loss	NOUN
ajst-24867	53	7	function	function	NOUN
ajst-24867	53	8	that	that	PRON
ajst-24867	53	9	focuses	focus	VERB
ajst-24867	53	10	on	on	ADP
ajst-24867	53	11	samples	sample	NOUN
ajst-24867	53	12	of	of	ADP
ajst-24867	53	13	different	different	ADJ
ajst-24867	53	14	difficulty	difficulty	NOUN
ajst-24867	53	15	levels	level	NOUN
ajst-24867	53	16	.	.	PUNCT
ajst-24867	54	1	it	it	PRON
ajst-24867	54	2	is	be	AUX
ajst-24867	54	3	based	base	VERB
ajst-24867	54	4	on	on	ADP
ajst-24867	54	5	the	the	DET
ajst-24867	54	6	iou	iou	NOUN
ajst-24867	54	7	loss	loss	NOUN
ajst-24867	54	8	function	function	NOUN
ajst-24867	54	9	and	and	CCONJ
ajst-24867	54	10	adjusts	adjust	VERB
ajst-24867	54	11	the	the	DET
ajst-24867	54	12	loss	loss	NOUN
ajst-24867	54	13	value	value	NOUN
ajst-24867	54	14	through	through	ADP
ajst-24867	54	15	linear	linear	ADJ
ajst-24867	54	16	interval	interval	NOUN
ajst-24867	54	17	mapping	mapping	NOUN
ajst-24867	54	18	method	method	NOUN
ajst-24867	54	19	,	,	PUNCT
ajst-24867	54	20	making	make	VERB
ajst-24867	54	21	the	the	DET
ajst-24867	54	22	model	model	NOUN
ajst-24867	54	23	pay	pay	VERB
ajst-24867	54	24	more	more	ADJ
ajst-24867	54	25	attention	attention	NOUN
ajst-24867	54	26	to	to	ADP
ajst-24867	54	27	difficult	difficult	ADJ
ajst-24867	54	28	to	to	PART
ajst-24867	54	29	detect	detect	VERB
ajst-24867	54	30	samples	sample	NOUN
ajst-24867	54	31	(	(	PUNCT
ajst-24867	54	32	such	such	ADJ
ajst-24867	54	33	as	as	ADP
ajst-24867	54	34	small	small	ADJ
ajst-24867	54	35	targets	target	NOUN
ajst-24867	54	36	or	or	CCONJ
ajst-24867	54	37	occluded	occluded	ADJ
ajst-24867	54	38	targets	target	NOUN
ajst-24867	54	39	)	)	PUNCT
ajst-24867	54	40	during	during	ADP
ajst-24867	54	41	the	the	DET
ajst-24867	54	42	training	training	NOUN
ajst-24867	54	43	process	process	NOUN
ajst-24867	54	44	,	,	PUNCT
ajst-24867	54	45	while	while	SCONJ
ajst-24867	54	46	reducing	reduce	VERB
ajst-24867	54	47	the	the	DET
ajst-24867	54	48	focus	focus	NOUN
ajst-24867	54	49	on	on	ADP
ajst-24867	54	50	easy	easy	ADJ
ajst-24867	54	51	to	to	PART
ajst-24867	54	52	detect	detect	VERB
ajst-24867	54	53	samples	sample	NOUN
ajst-24867	54	54	.	.	PUNCT
ajst-24867	55	1	focaler	focaler	NOUN
ajst-24867	55	2	-	-	PUNCT
ajst-24867	55	3	iou	iou	NOUN
ajst-24867	55	4	,	,	PUNCT
ajst-24867	55	5	the	the	DET
ajst-24867	55	6	calculation	calculation	NOUN
ajst-24867	55	7	formula	formula	NOUN
ajst-24867	55	8	is	be	AUX
ajst-24867	55	9	as	as	SCONJ
ajst-24867	55	10	follows	follow	VERB
ajst-24867	55	11	:	:	PUNCT
ajst-24867	55	12	f	f	PROPN
ajst-24867	55	13	0	0	NUM
ajst-24867	55	14	,	,	PUNCT
ajst-24867	55	15	o	o	INTJ
ajst-24867	55	16	,	,	PUNCT
ajst-24867	55	17	1	1	NUM
ajst-24867	55	18	,	,	PUNCT
ajst-24867	55	19	ocaler	ocaler	NOUN
ajst-24867	55	20	iou	iou	NOUN
ajst-24867	55	21	i	i	PRON
ajst-24867	55	22	u	u	NOUN
ajst-24867	55	23	iou	iou	NOUN
ajst-24867	55	24	iou	iou	PROPN
ajst-24867	55	25	iou	iou	PROPN
ajst-24867	55	26			X
ajst-24867	55	27			X
ajst-24867	55	28			NUM
ajst-24867	55	29			PROPN
ajst-24867	55	30			PROPN
ajst-24867	55	31			X
ajst-24867	55	32			PROPN
ajst-24867	55	33			ADJ
ajst-24867	55	34			PROPN
ajst-24867	55	35			NUM
ajst-24867	55	36			PROPN
ajst-24867	55	37			NOUN
ajst-24867	55	38			VERB
ajst-24867	55	39			NOUN
ajst-24867	55	40			PRON
ajst-24867	55	41			NOUN
ajst-24867	55	42	(	(	PUNCT
ajst-24867	55	43	2	2	NUM
ajst-24867	55	44	)	)	PUNCT
ajst-24867	55	45	f1	f1	NOUN
ajst-24867	55	46	ocaler	ocaler	NOUN
ajst-24867	55	47	focaler	focaler	NOUN
ajst-24867	55	48	ioul	ioul	PROPN
ajst-24867	56	1	iou	iou	AUX
ajst-24867	56	2			PROPN
ajst-24867	56	3			NOUN
ajst-24867	56	4	(	(	PUNCT
ajst-24867	56	5	3	3	NUM
ajst-24867	56	6	)	)	PUNCT
ajst-24867	56	7	among	among	ADP
ajst-24867	56	8	them	they	PRON
ajst-24867	56	9	,	,	PUNCT
ajst-24867	56	10	α	α	PRON
ajst-24867	56	11	,	,	PUNCT
ajst-24867	56	12	β	β	X
ajst-24867	56	13	are	be	AUX
ajst-24867	56	14	hyperparameters	hyperparameter	NOUN
ajst-24867	56	15	,	,	PUNCT
ajst-24867	56	16	[	[	X
ajst-24867	56	17	α	α	NOUN
ajst-24867	56	18	,	,	PUNCT
ajst-24867	56	19	β	β	X
ajst-24867	56	20	]	]	X
ajst-24867	56	21			NOUN
ajst-24867	57	1	[	[	X
ajst-24867	57	2	0,1	0,1	NUM
ajst-24867	57	3	]	]	PUNCT
ajst-24867	57	4	,	,	PUNCT
ajst-24867	57	5	in	in	ADP
ajst-24867	57	6	this	this	DET
ajst-24867	57	7	paper	paper	NOUN
ajst-24867	57	8	β=0	β=0	ADP
ajst-24867	57	9	,	,	PUNCT
ajst-24867	57	10	β=0.95	β=0.95	NOUN
ajst-24867	57	11	mpdiou	mpdiou	NOUN
ajst-24867	57	12	[	[	X
ajst-24867	57	13	14	14	NUM
ajst-24867	57	14	]	]	PUNCT
ajst-24867	57	15	is	be	AUX
ajst-24867	57	16	a	a	DET
ajst-24867	57	17	bounding	bounding	NOUN
ajst-24867	57	18	box	box	NOUN
ajst-24867	57	19	regression	regression	NOUN
ajst-24867	57	20	loss	loss	NOUN
ajst-24867	57	21	function	function	NOUN
ajst-24867	57	22	that	that	PRON
ajst-24867	57	23	optimizes	optimize	VERB
ajst-24867	57	24	the	the	DET
ajst-24867	57	25	regression	regression	NOUN
ajst-24867	57	26	of	of	ADP
ajst-24867	57	27	bounding	bound	VERB
ajst-24867	57	28	boxes	box	NOUN
ajst-24867	57	29	by	by	ADP
ajst-24867	57	30	minimizing	minimize	VERB
ajst-24867	57	31	the	the	DET
ajst-24867	57	32	distance	distance	NOUN
ajst-24867	57	33	between	between	ADP
ajst-24867	57	34	the	the	DET
ajst-24867	57	35	top	top	NOUN
ajst-24867	57	36	left	left	ADJ
ajst-24867	57	37	and	and	CCONJ
ajst-24867	57	38	bottom	bottom	ADJ
ajst-24867	57	39	right	right	ADJ
ajst-24867	57	40	points	point	NOUN
ajst-24867	57	41	of	of	ADP
ajst-24867	57	42	the	the	DET
ajst-24867	57	43	predicted	predict	VERB
ajst-24867	57	44	and	and	CCONJ
ajst-24867	57	45	real	real	ADJ
ajst-24867	57	46	boxes	box	NOUN
ajst-24867	57	47	.	.	PUNCT
ajst-24867	58	1	mpdiou	mpdiou	NOUN
ajst-24867	58	2	also	also	ADV
ajst-24867	58	3	considers	consider	VERB
ajst-24867	58	4	the	the	DET
ajst-24867	58	5	distance	distance	NOUN
ajst-24867	58	6	between	between	ADP
ajst-24867	58	7	the	the	DET
ajst-24867	58	8	center	center	NOUN
ajst-24867	58	9	82	82	NUM
ajst-24867	58	10	points	point	NOUN
ajst-24867	58	11	of	of	ADP
ajst-24867	58	12	two	two	NUM
ajst-24867	58	13	bounding	bounding	NOUN
ajst-24867	58	14	boxes	box	NOUN
ajst-24867	58	15	,	,	PUNCT
ajst-24867	58	16	which	which	PRON
ajst-24867	58	17	helps	help	VERB
ajst-24867	58	18	to	to	PART
ajst-24867	58	19	further	far	ADV
ajst-24867	58	20	optimize	optimize	VERB
ajst-24867	58	21	the	the	DET
ajst-24867	58	22	position	position	NOUN
ajst-24867	58	23	of	of	ADP
ajst-24867	58	24	the	the	DET
ajst-24867	58	25	bounding	bounding	NOUN
ajst-24867	58	26	boxes	box	NOUN
ajst-24867	58	27	.	.	PUNCT
ajst-24867	59	1	the	the	DET
ajst-24867	59	2	calculation	calculation	NOUN
ajst-24867	59	3	formula	formula	NOUN
ajst-24867	59	4	is	be	AUX
ajst-24867	59	5	as	as	SCONJ
ajst-24867	59	6	follows	follow	VERB
ajst-24867	59	7	:	:	PUNCT
ajst-24867	59	8	2	2	NUM
ajst-24867	59	9	2	2	NUM
ajst-24867	59	10	1	1	NUM
ajst-24867	59	11	2	2	NUM
ajst-24867	59	12	2	2	NUM
ajst-24867	59	13	2	2	NUM
ajst-24867	59	14	2	2	NUM
ajst-24867	59	15	2	2	NUM
ajst-24867	59	16	d	d	NOUN
ajst-24867	59	17	d	d	NOUN
ajst-24867	59	18	mpdiou	mpdiou	NOUN
ajst-24867	59	19	iou	iou	PROPN
ajst-24867	59	20	w	w	PROPN
ajst-24867	59	21	h	h	PROPN
ajst-24867	59	22	w	w	PROPN
ajst-24867	59	23	h	h	PROPN
ajst-24867	60	1			PROPN
ajst-24867	60	2			PROPN
ajst-24867	60	3			PROPN
ajst-24867	60	4			PUNCT
ajst-24867	60	5			X
ajst-24867	60	6	(	(	PUNCT
ajst-24867	60	7	4	4	NUM
ajst-24867	60	8	)	)	SYM
ajst-24867	60	9	2	2	NUM
ajst-24867	60	10	2	2	NUM
ajst-24867	60	11	1	1	NUM
ajst-24867	60	12	1	1	NUM
ajst-24867	60	13	1	1	NUM
ajst-24867	60	14	1	1	NUM
ajst-24867	60	15	1	1	NUM
ajst-24867	60	16	(	(	PUNCT
ajst-24867	60	17	)	)	PUNCT
ajst-24867	60	18	(	(	PUNCT
ajst-24867	60	19	)	)	PUNCT
ajst-24867	60	20	bprd	bprd	NOUN
ajst-24867	60	21	gt	gt	PROPN
ajst-24867	60	22	bprd	bprd	NOUN
ajst-24867	60	23	gtd	gtd	NOUN
ajst-24867	60	24	x	x	PUNCT
ajst-24867	60	25	x	x	PUNCT
ajst-24867	60	26	y	y	PROPN
ajst-24867	60	27	y	y	PROPN
ajst-24867	60	28			PROPN
ajst-24867	60	29			VERB
ajst-24867	60	30			NOUN
ajst-24867	60	31	(	(	PUNCT
ajst-24867	60	32	5	5	NUM
ajst-24867	60	33	)	)	SYM
ajst-24867	60	34	2	2	NUM
ajst-24867	60	35	2	2	NUM
ajst-24867	60	36	2	2	NUM
ajst-24867	60	37	2	2	NUM
ajst-24867	60	38	2	2	NUM
ajst-24867	60	39	2	2	NUM
ajst-24867	60	40	2	2	NUM
ajst-24867	60	41	(	(	PUNCT
ajst-24867	60	42	)	)	PUNCT
ajst-24867	60	43	(	(	PUNCT
ajst-24867	60	44	)	)	PUNCT
ajst-24867	60	45	bprd	bprd	NOUN
ajst-24867	60	46	gt	gt	PROPN
ajst-24867	60	47	bprd	bprd	NOUN
ajst-24867	60	48	gtd	gtd	NOUN
ajst-24867	60	49	x	x	PUNCT
ajst-24867	60	50	x	x	PUNCT
ajst-24867	60	51	y	y	PROPN
ajst-24867	60	52	y	y	PROPN
ajst-24867	60	53			PROPN
ajst-24867	60	54			VERB
ajst-24867	60	55			NOUN
ajst-24867	60	56	(	(	PUNCT
ajst-24867	60	57	6	6	NUM
ajst-24867	60	58	)	)	PUNCT
ajst-24867	60	59	in	in	ADP
ajst-24867	60	60	the	the	DET
ajst-24867	60	61	formula	formula	NOUN
ajst-24867	60	62	,	,	PUNCT
ajst-24867	60	63	,	,	PUNCT
ajst-24867	60	64	w	w	PROPN
ajst-24867	60	65	h	h	NOUN
ajst-24867	60	66	are	be	AUX
ajst-24867	60	67	the	the	DET
ajst-24867	60	68	length	length	NOUN
ajst-24867	60	69	and	and	CCONJ
ajst-24867	60	70	width	width	NOUN
ajst-24867	60	71	of	of	ADP
ajst-24867	60	72	the	the	DET
ajst-24867	60	73	input	input	NOUN
ajst-24867	60	74	image	image	NOUN
ajst-24867	60	75	,	,	PUNCT
ajst-24867	60	76			PROPN
ajst-24867	60	77			SYM
ajst-24867	60	78			NOUN
ajst-24867	60	79	1	1	VERB
ajst-24867	60	80	1	1	NUM
ajst-24867	60	81	2	2	NUM
ajst-24867	60	82	2	2	NUM
ajst-24867	60	83	,	,	PUNCT
ajst-24867	60	84	,	,	PUNCT
ajst-24867	60	85	bprd	bprd	NOUN
ajst-24867	60	86	bprd	bprd	NOUN
ajst-24867	60	87	bprd	bprd	NOUN
ajst-24867	60	88	bprdx	bprdx	NOUN
ajst-24867	60	89	y	y	PROPN
ajst-24867	61	1	x	x	PROPN
ajst-24867	61	2	y	y	PROPN
ajst-24867	61	3	，	，	ADJ
ajst-24867	61	4	are	be	AUX
ajst-24867	61	5	the	the	DET
ajst-24867	61	6	coordinates	coordinate	NOUN
ajst-24867	61	7	of	of	ADP
ajst-24867	61	8	the	the	DET
ajst-24867	61	9	predicted	predict	VERB
ajst-24867	61	10	box	box	NOUN
ajst-24867	61	11	and	and	CCONJ
ajst-24867	61	12	the	the	DET
ajst-24867	61	13	real	real	ADJ
ajst-24867	61	14	box	box	NOUN
ajst-24867	61	15	at	at	ADP
ajst-24867	61	16	the	the	DET
ajst-24867	61	17	top	top	ADJ
ajst-24867	61	18	left	left	ADJ
ajst-24867	61	19	corner	corner	NOUN
ajst-24867	61	20	,	,	PUNCT
ajst-24867	61	21	and	and	CCONJ
ajst-24867	61	22			NOUN
ajst-24867	61	23			SYM
ajst-24867	61	24			PROPN
ajst-24867	61	25	gt	gt	VERB
ajst-24867	62	1	gt	gt	INTJ
ajst-24867	62	2	gt	gt	INTJ
ajst-24867	62	3	gt	gt	PROPN
ajst-24867	62	4	1	1	NUM
ajst-24867	62	5	1	1	NUM
ajst-24867	62	6	2	2	NUM
ajst-24867	62	7	2	2	NUM
ajst-24867	62	8	,	,	PUNCT
ajst-24867	62	9	,	,	PUNCT
ajst-24867	62	10	b	b	PROPN
ajst-24867	62	11	b	b	X
ajst-24867	62	12	b	b	PROPN
ajst-24867	62	13	bx	bx	NOUN
ajst-24867	62	14	y	y	PROPN
ajst-24867	62	15	x	x	PROPN
ajst-24867	62	16	y	y	PROPN
ajst-24867	62	17	，	，	ADJ
ajst-24867	62	18	are	be	AUX
ajst-24867	62	19	the	the	DET
ajst-24867	62	20	coordinates	coordinate	NOUN
ajst-24867	62	21	of	of	ADP
ajst-24867	62	22	the	the	DET
ajst-24867	62	23	predicted	predict	VERB
ajst-24867	62	24	box	box	NOUN
ajst-24867	62	25	and	and	CCONJ
ajst-24867	62	26	the	the	DET
ajst-24867	62	27	real	real	ADJ
ajst-24867	62	28	box	box	NOUN
ajst-24867	62	29	at	at	ADP
ajst-24867	62	30	the	the	DET
ajst-24867	62	31	bottom	bottom	ADJ
ajst-24867	62	32	right	right	ADJ
ajst-24867	62	33	corner	corner	NOUN
ajst-24867	62	34	,	,	PUNCT
ajst-24867	62	35	representing	represent	VERB
ajst-24867	62	36	the	the	DET
ajst-24867	62	37	euclidean	euclidean	ADJ
ajst-24867	62	38	distance	distance	NOUN
ajst-24867	62	39	between	between	ADP
ajst-24867	62	40	the	the	DET
ajst-24867	62	41	real	real	ADJ
ajst-24867	62	42	box	box	NOUN
ajst-24867	62	43	and	and	CCONJ
ajst-24867	62	44	the	the	DET
ajst-24867	62	45	predicted	predict	VERB
ajst-24867	62	46	box	box	NOUN
ajst-24867	62	47	at	at	ADP
ajst-24867	62	48	the	the	DET
ajst-24867	62	49	top	top	NOUN
ajst-24867	62	50	left	left	ADJ
ajst-24867	62	51	and	and	CCONJ
ajst-24867	62	52	bottom	bottom	ADJ
ajst-24867	62	53	right	right	ADJ
ajst-24867	62	54	corners	corner	NOUN
ajst-24867	62	55	,	,	PUNCT
ajst-24867	62	56	respectively	respectively	ADV
ajst-24867	62	57	.	.	PUNCT
ajst-24867	63	1	this	this	DET
ajst-24867	63	2	article	article	NOUN
ajst-24867	63	3	combines	combine	VERB
ajst-24867	63	4	the	the	DET
ajst-24867	63	5	advantages	advantage	NOUN
ajst-24867	63	6	of	of	ADP
ajst-24867	63	7	focaler	focaler	NOUN
ajst-24867	63	8	iou	iou	NOUN
ajst-24867	63	9	and	and	CCONJ
ajst-24867	63	10	mpdiou	mpdiou	NOUN
ajst-24867	63	11	to	to	PART
ajst-24867	63	12	design	design	VERB
ajst-24867	63	13	the	the	DET
ajst-24867	63	14	focaler	focaler	NOUN
ajst-24867	63	15	mpdiou	mpdiou	NOUN
ajst-24867	63	16	loss	loss	NOUN
ajst-24867	63	17	function	function	NOUN
ajst-24867	63	18	calculation	calculation	NOUN
ajst-24867	63	19	formula	formula	NOUN
ajst-24867	63	20	as	as	SCONJ
ajst-24867	63	21	follows	follow	VERB
ajst-24867	63	22	f	f	PROPN
ajst-24867	63	23	0	0	NUM
ajst-24867	63	24	,	,	PUNCT
ajst-24867	63	25	,	,	PUNCT
ajst-24867	63	26	1	1	NUM
ajst-24867	63	27	,	,	PUNCT
ajst-24867	63	28	ocaler	ocaler	NOUN
ajst-24867	63	29	mpdiou	mpdiou	NOUN
ajst-24867	63	30	mpdiou	mpdiou	NOUN
ajst-24867	63	31	mpdiou	mpdiou	NOUN
ajst-24867	63	32	iou	iou	NOUN
ajst-24867	63	33	mpdiou	mpdiou	NOUN
ajst-24867	63	34			NOUN
ajst-24867	63	35			X
ajst-24867	63	36			NUM
ajst-24867	63	37			PROPN
ajst-24867	63	38			PROPN
ajst-24867	63	39			X
ajst-24867	63	40			PROPN
ajst-24867	63	41			ADJ
ajst-24867	63	42			PROPN
ajst-24867	63	43			NUM
ajst-24867	63	44			PROPN
ajst-24867	63	45			NOUN
ajst-24867	63	46			AUX
ajst-24867	63	47			NOUN
ajst-24867	63	48			PRON
ajst-24867	63	49			NOUN
ajst-24867	63	50	(	(	PUNCT
ajst-24867	63	51	7	7	NUM
ajst-24867	63	52	)	)	PUNCT
ajst-24867	63	53	f1	f1	NOUN
ajst-24867	63	54	ocaler	ocaler	NOUN
ajst-24867	63	55	focaler	focaler	NOUN
ajst-24867	63	56	mpdioul	mpdioul	ADJ
ajst-24867	63	57	mpdiou	mpdiou	PROPN
ajst-24867	63	58			PROPN
ajst-24867	63	59			NOUN
ajst-24867	63	60	(	(	PUNCT
ajst-24867	63	61	8)	8)	NUM
ajst-24867	63	62	by	by	ADP
ajst-24867	63	63	combining	combine	VERB
ajst-24867	63	64	the	the	DET
ajst-24867	63	65	characteristics	characteristic	NOUN
ajst-24867	63	66	of	of	ADP
ajst-24867	63	67	difficult	difficult	ADJ
ajst-24867	63	68	and	and	CCONJ
ajst-24867	63	69	easy	easy	ADJ
ajst-24867	63	70	samples	sample	NOUN
ajst-24867	63	71	of	of	ADP
ajst-24867	63	72	focaler	focaler	NOUN
ajst-24867	63	73	iou	iou	NOUN
ajst-24867	63	74	with	with	ADP
ajst-24867	63	75	the	the	DET
ajst-24867	63	76	minimum	minimum	ADJ
ajst-24867	63	77	point	point	NOUN
ajst-24867	63	78	distance	distance	NOUN
ajst-24867	63	79	metric	metric	NOUN
ajst-24867	63	80	of	of	ADP
ajst-24867	63	81	mpdiou	mpdiou	NOUN
ajst-24867	63	82	,	,	PUNCT
ajst-24867	63	83	the	the	DET
ajst-24867	63	84	detection	detection	NOUN
ajst-24867	63	85	accuracy	accuracy	NOUN
ajst-24867	63	86	is	be	AUX
ajst-24867	63	87	further	far	ADV
ajst-24867	63	88	improved	improve	VERB
ajst-24867	63	89	,	,	PUNCT
ajst-24867	63	90	especially	especially	ADV
ajst-24867	63	91	for	for	ADP
ajst-24867	63	92	small	small	ADJ
ajst-24867	63	93	targets	target	NOUN
ajst-24867	63	94	,	,	PUNCT
ajst-24867	63	95	and	and	CCONJ
ajst-24867	63	96	the	the	DET
ajst-24867	63	97	convergence	convergence	NOUN
ajst-24867	63	98	of	of	ADP
ajst-24867	63	99	the	the	DET
ajst-24867	63	100	model	model	NOUN
ajst-24867	63	101	is	be	AUX
ajst-24867	63	102	accelerated	accelerate	VERB
ajst-24867	63	103	,	,	PUNCT
ajst-24867	63	104	thereby	thereby	ADV
ajst-24867	63	105	improving	improve	VERB
ajst-24867	63	106	the	the	DET
ajst-24867	63	107	positioning	positioning	NOUN
ajst-24867	63	108	and	and	CCONJ
ajst-24867	63	109	boundary	boundary	ADJ
ajst-24867	63	110	accuracy	accuracy	NOUN
ajst-24867	63	111	of	of	ADP
ajst-24867	63	112	sea	sea	NOUN
ajst-24867	63	113	surface	surface	NOUN
ajst-24867	63	114	ship	ship	NOUN
ajst-24867	63	115	detection	detection	NOUN
ajst-24867	63	116	.	.	PUNCT
ajst-24867	64	1	3.3	3.3	NUM
ajst-24867	64	2	.	.	PUNCT
ajst-24867	65	1	lightweight	lightweight	ADJ
ajst-24867	65	2	v7downsampling	v7downsample	VERB
ajst-24867	65	3	module	module	NOUN
ajst-24867	65	4	infrared	infrare	VERB
ajst-24867	65	5	images	image	NOUN
ajst-24867	65	6	usually	usually	ADV
ajst-24867	65	7	have	have	VERB
ajst-24867	65	8	low	low	ADJ
ajst-24867	65	9	resolution	resolution	NOUN
ajst-24867	65	10	and	and	CCONJ
ajst-24867	65	11	contrast	contrast	NOUN
ajst-24867	65	12	.	.	PUNCT
ajst-24867	66	1	in	in	ADP
ajst-24867	66	2	the	the	DET
ajst-24867	66	3	original	original	ADJ
ajst-24867	66	4	yolov8	yolov8	NOUN
ajst-24867	66	5	,	,	PUNCT
ajst-24867	66	6	downsampling	downsample	VERB
ajst-24867	66	7	is	be	AUX
ajst-24867	66	8	mainly	mainly	ADV
ajst-24867	66	9	achieved	achieve	VERB
ajst-24867	66	10	using	use	VERB
ajst-24867	66	11	convolution	convolution	NOUN
ajst-24867	66	12	with	with	ADP
ajst-24867	66	13	a	a	DET
ajst-24867	66	14	stride	stride	NOUN
ajst-24867	66	15	of	of	ADP
ajst-24867	66	16	2	2	NUM
ajst-24867	66	17	,	,	PUNCT
ajst-24867	66	18	which	which	PRON
ajst-24867	66	19	may	may	AUX
ajst-24867	66	20	lead	lead	VERB
ajst-24867	66	21	to	to	ADP
ajst-24867	66	22	the	the	DET
ajst-24867	66	23	loss	loss	NOUN
ajst-24867	66	24	of	of	ADP
ajst-24867	66	25	fine	fine	ADV
ajst-24867	66	26	-	-	PUNCT
ajst-24867	66	27	grained	grain	VERB
ajst-24867	66	28	information	information	NOUN
ajst-24867	66	29	,	,	PUNCT
ajst-24867	66	30	thereby	thereby	ADV
ajst-24867	66	31	affecting	affect	VERB
ajst-24867	66	32	the	the	DET
ajst-24867	66	33	detection	detection	NOUN
ajst-24867	66	34	standards	standard	NOUN
ajst-24867	66	35	for	for	ADP
ajst-24867	66	36	small	small	ADJ
ajst-24867	66	37	or	or	CCONJ
ajst-24867	66	38	low	low	ADJ
ajst-24867	66	39	contrast	contrast	NOUN
ajst-24867	66	40	objects	object	NOUN
ajst-24867	66	41	(	(	PUNCT
ajst-24867	66	42	such	such	ADJ
ajst-24867	66	43	as	as	ADP
ajst-24867	66	44	ships	ship	NOUN
ajst-24867	66	45	)	)	PUNCT
ajst-24867	66	46	in	in	ADP
ajst-24867	66	47	infrared	infrared	ADJ
ajst-24867	66	48	images	image	NOUN
ajst-24867	66	49	.	.	PUNCT
ajst-24867	67	1	the	the	DET
ajst-24867	67	2	convolution	convolution	NOUN
ajst-24867	67	3	layer	layer	NOUN
ajst-24867	67	4	contains	contain	VERB
ajst-24867	67	5	more	more	ADJ
ajst-24867	67	6	parameters	parameter	NOUN
ajst-24867	67	7	and	and	CCONJ
ajst-24867	67	8	computational	computational	ADJ
ajst-24867	67	9	complexity	complexity	NOUN
ajst-24867	67	10	,	,	PUNCT
ajst-24867	67	11	and	and	CCONJ
ajst-24867	67	12	is	be	AUX
ajst-24867	67	13	prone	prone	ADJ
ajst-24867	67	14	to	to	ADP
ajst-24867	67	15	losing	lose	VERB
ajst-24867	67	16	fine	fine	ADV
ajst-24867	67	17	-	-	PUNCT
ajst-24867	67	18	grained	grain	VERB
ajst-24867	67	19	information	information	NOUN
ajst-24867	67	20	,	,	PUNCT
ajst-24867	67	21	resulting	result	VERB
ajst-24867	67	22	in	in	ADP
ajst-24867	67	23	poor	poor	ADJ
ajst-24867	67	24	detection	detection	NOUN
ajst-24867	67	25	of	of	ADP
ajst-24867	67	26	small	small	ADJ
ajst-24867	67	27	ship	ship	NOUN
ajst-24867	67	28	targets	target	NOUN
ajst-24867	67	29	.	.	PUNCT
ajst-24867	68	1	to	to	PART
ajst-24867	68	2	solve	solve	VERB
ajst-24867	68	3	this	this	DET
ajst-24867	68	4	problem	problem	NOUN
ajst-24867	68	5	,	,	PUNCT
ajst-24867	68	6	the	the	DET
ajst-24867	68	7	v7downsampling	v7downsample	VERB
ajst-24867	68	8	module	module	NOUN
ajst-24867	68	9	in	in	ADP
ajst-24867	68	10	yolov7	yolov7	NOUN
ajst-24867	68	11	[	[	X
ajst-24867	68	12	8	8	NUM
ajst-24867	68	13	]	]	PUNCT
ajst-24867	68	14	is	be	AUX
ajst-24867	68	15	introduced	introduce	VERB
ajst-24867	68	16	.	.	PUNCT
ajst-24867	69	1	the	the	DET
ajst-24867	69	2	steps	step	NOUN
ajst-24867	69	3	are	be	AUX
ajst-24867	69	4	as	as	SCONJ
ajst-24867	69	5	follows	follow	VERB
ajst-24867	69	6	:	:	PUNCT
ajst-24867	69	7	the	the	DET
ajst-24867	69	8	input	input	NOUN
ajst-24867	69	9	feature	feature	NOUN
ajst-24867	69	10	map	map	NOUN
ajst-24867	69	11	x	x	VERB
ajst-24867	69	12	is	be	AUX
ajst-24867	69	13	first	first	ADV
ajst-24867	69	14	fed	feed	VERB
ajst-24867	69	15	into	into	ADP
ajst-24867	69	16	a	a	DET
ajst-24867	69	17	max	max	PROPN
ajst-24867	69	18	pooling	pooling	NOUN
ajst-24867	69	19	sequence	sequence	NOUN
ajst-24867	69	20	,	,	PUNCT
ajst-24867	69	21	which	which	PRON
ajst-24867	69	22	includes	include	VERB
ajst-24867	69	23	a	a	DET
ajst-24867	69	24	max	max	PROPN
ajst-24867	69	25	pooling	pooling	NOUN
ajst-24867	69	26	layer	layer	NOUN
ajst-24867	69	27	and	and	CCONJ
ajst-24867	69	28	a	a	DET
ajst-24867	69	29	1x1	1x1	NUM
ajst-24867	69	30	convolutional	convolutional	ADJ
ajst-24867	69	31	layer	layer	NOUN
ajst-24867	69	32	conv	conv	NOUN
ajst-24867	69	33	(	(	PUNCT
ajst-24867	69	34	k=1	k=1	NOUN
ajst-24867	69	35	)	)	PUNCT
ajst-24867	69	36	.	.	PUNCT
ajst-24867	70	1	the	the	DET
ajst-24867	70	2	max	max	PROPN
ajst-24867	70	3	pooling	pool	VERB
ajst-24867	70	4	layer	layer	NOUN
ajst-24867	70	5	halves	halve	VERB
ajst-24867	70	6	the	the	DET
ajst-24867	70	7	width	width	NOUN
ajst-24867	70	8	and	and	CCONJ
ajst-24867	70	9	height	height	NOUN
ajst-24867	70	10	of	of	ADP
ajst-24867	70	11	the	the	DET
ajst-24867	70	12	feature	feature	NOUN
ajst-24867	70	13	map	map	NOUN
ajst-24867	70	14	,	,	PUNCT
ajst-24867	70	15	while	while	SCONJ
ajst-24867	70	16	the	the	DET
ajst-24867	70	17	1x1	1x1	NUM
ajst-24867	70	18	convolutional	convolutional	ADJ
ajst-24867	70	19	layer	layer	NOUN
ajst-24867	70	20	converts	convert	VERB
ajst-24867	70	21	the	the	DET
ajst-24867	70	22	number	number	NOUN
ajst-24867	70	23	of	of	ADP
ajst-24867	70	24	input	input	NOUN
ajst-24867	70	25	channels	channel	NOUN
ajst-24867	70	26	to	to	ADP
ajst-24867	70	27	half	half	DET
ajst-24867	70	28	the	the	DET
ajst-24867	70	29	number	number	NOUN
ajst-24867	70	30	of	of	ADP
ajst-24867	70	31	output	output	NOUN
ajst-24867	70	32	channels	channel	NOUN
ajst-24867	70	33	.	.	PUNCT
ajst-24867	71	1	next	next	ADV
ajst-24867	71	2	,	,	PUNCT
ajst-24867	71	3	the	the	DET
ajst-24867	71	4	input	input	NOUN
ajst-24867	71	5	feature	feature	NOUN
ajst-24867	71	6	map	map	NOUN
ajst-24867	71	7	x	x	VERB
ajst-24867	71	8	is	be	AUX
ajst-24867	71	9	also	also	ADV
ajst-24867	71	10	fed	feed	VERB
ajst-24867	71	11	into	into	ADP
ajst-24867	71	12	a	a	DET
ajst-24867	71	13	convolutional	convolutional	ADJ
ajst-24867	71	14	sequence	sequence	NOUN
ajst-24867	71	15	,	,	PUNCT
ajst-24867	71	16	which	which	PRON
ajst-24867	71	17	includes	include	VERB
ajst-24867	71	18	a	a	DET
ajst-24867	71	19	1x1	1x1	NUM
ajst-24867	71	20	convolutional	convolutional	ADJ
ajst-24867	71	21	layer	layer	NOUN
ajst-24867	71	22	conv	conv	NOUN
ajst-24867	71	23	(	(	PUNCT
ajst-24867	71	24	k=1	k=1	NOUN
ajst-24867	71	25	)	)	PUNCT
ajst-24867	71	26	and	and	CCONJ
ajst-24867	71	27	a	a	DET
ajst-24867	71	28	3x3	3x3	NUM
ajst-24867	71	29	convolutional	convolutional	ADJ
ajst-24867	71	30	layer	layer	NOUN
ajst-24867	71	31	conv	conv	NOUN
ajst-24867	71	32	(	(	PUNCT
ajst-24867	71	33	k=3	k=3	PROPN
ajst-24867	71	34	,	,	PUNCT
ajst-24867	71	35	s=2	s=2	NOUN
ajst-24867	71	36	)	)	PUNCT
ajst-24867	71	37	,	,	PUNCT
ajst-24867	71	38	further	far	ADV
ajst-24867	71	39	halving	halve	VERB
ajst-24867	71	40	the	the	DET
ajst-24867	71	41	width	width	NOUN
ajst-24867	71	42	and	and	CCONJ
ajst-24867	71	43	height	height	NOUN
ajst-24867	71	44	of	of	ADP
ajst-24867	71	45	the	the	DET
ajst-24867	71	46	feature	feature	NOUN
ajst-24867	71	47	map	map	NOUN
ajst-24867	71	48	.	.	PUNCT
ajst-24867	72	1	this	this	PRON
ajst-24867	72	2	is	be	AUX
ajst-24867	72	3	equivalent	equivalent	ADJ
ajst-24867	72	4	to	to	ADP
ajst-24867	72	5	a	a	DET
ajst-24867	72	6	lightweight	lightweight	ADJ
ajst-24867	72	7	depthwise	depthwise	NOUN
ajst-24867	72	8	separable	separable	ADJ
ajst-24867	72	9	convolution	convolution	NOUN
ajst-24867	72	10	,	,	PUNCT
ajst-24867	72	11	which	which	PRON
ajst-24867	72	12	helps	help	VERB
ajst-24867	72	13	reduce	reduce	VERB
ajst-24867	72	14	computational	computational	ADJ
ajst-24867	72	15	and	and	CCONJ
ajst-24867	72	16	parameter	parameter	NOUN
ajst-24867	72	17	complexity	complexity	NOUN
ajst-24867	72	18	,	,	PUNCT
ajst-24867	72	19	making	make	VERB
ajst-24867	72	20	the	the	DET
ajst-24867	72	21	network	network	NOUN
ajst-24867	72	22	more	more	ADV
ajst-24867	72	23	efficient	efficient	ADJ
ajst-24867	72	24	.	.	PUNCT
ajst-24867	73	1	finally	finally	ADV
ajst-24867	73	2	,	,	PUNCT
ajst-24867	73	3	the	the	DET
ajst-24867	73	4	output	output	NOUN
ajst-24867	73	5	maxpool	maxpool	NOUN
ajst-24867	73	6	(	(	PUNCT
ajst-24867	73	7	x	x	X
ajst-24867	73	8	)	)	PUNCT
ajst-24867	73	9	of	of	ADP
ajst-24867	73	10	the	the	DET
ajst-24867	73	11	max	max	PROPN
ajst-24867	73	12	pooling	pool	VERB
ajst-24867	73	13	sequence	sequence	NOUN
ajst-24867	73	14	and	and	CCONJ
ajst-24867	73	15	the	the	DET
ajst-24867	73	16	output	output	NOUN
ajst-24867	73	17	conv	conv	NOUN
ajst-24867	73	18	(	(	PUNCT
ajst-24867	73	19	x	x	NOUN
ajst-24867	73	20	)	)	PUNCT
ajst-24867	73	21	of	of	ADP
ajst-24867	73	22	the	the	DET
ajst-24867	73	23	convolutional	convolutional	ADJ
ajst-24867	73	24	sequence	sequence	NOUN
ajst-24867	73	25	are	be	AUX
ajst-24867	73	26	concatenated	concatenate	VERB
ajst-24867	73	27	in	in	ADP
ajst-24867	73	28	the	the	DET
ajst-24867	73	29	channel	channel	NOUN
ajst-24867	73	30	dimension	dimension	NOUN
ajst-24867	73	31	to	to	PART
ajst-24867	73	32	form	form	VERB
ajst-24867	73	33	the	the	DET
ajst-24867	73	34	final	final	ADJ
ajst-24867	73	35	output	output	NOUN
ajst-24867	73	36	feature	feature	NOUN
ajst-24867	73	37	map	map	NOUN
ajst-24867	73	38	.	.	PUNCT
ajst-24867	74	1	compared	compare	VERB
ajst-24867	74	2	to	to	ADP
ajst-24867	74	3	a	a	DET
ajst-24867	74	4	single	single	ADJ
ajst-24867	74	5	convolution	convolution	NOUN
ajst-24867	74	6	with	with	ADP
ajst-24867	74	7	a	a	DET
ajst-24867	74	8	stride	stride	NOUN
ajst-24867	74	9	of	of	ADP
ajst-24867	74	10	2	2	NUM
ajst-24867	74	11	,	,	PUNCT
ajst-24867	74	12	the	the	DET
ajst-24867	74	13	v7downsampling	v7downsample	VERB
ajst-24867	74	14	module	module	NOUN
ajst-24867	74	15	helps	helps	AUX
ajst-24867	74	16	preserve	preserve	VERB
ajst-24867	74	17	more	more	ADJ
ajst-24867	74	18	spatial	spatial	ADJ
ajst-24867	74	19	information	information	NOUN
ajst-24867	74	20	.	.	PUNCT
ajst-24867	75	1	the	the	DET
ajst-24867	75	2	v7downsampling	v7downsample	VERB
ajst-24867	75	3	structure	structure	NOUN
ajst-24867	75	4	is	be	AUX
ajst-24867	75	5	shown	show	VERB
ajst-24867	75	6	in	in	ADP
ajst-24867	75	7	figure	figure	NOUN
ajst-24867	75	8	4	4	NUM
ajst-24867	75	9	.	.	PUNCT
ajst-24867	75	10	max	max	PROPN
ajst-24867	75	11	pooling(2x2	pooling(2x2	PROPN
ajst-24867	75	12	,	,	PUNCT
ajst-24867	75	13	stride=2	stride=2	NOUN
ajst-24867	75	14	)	)	PUNCT
ajst-24867	75	15	input	input	NOUN
ajst-24867	75	16	feature	feature	NOUN
ajst-24867	75	17	map	map	NOUN
ajst-24867	75	18	x	x	NOUN
ajst-24867	75	19	conv	conv	X
ajst-24867	75	20	(	(	PUNCT
ajst-24867	75	21	3x3	3x3	NUM
ajst-24867	75	22	,	,	PUNCT
ajst-24867	75	23	stride=2	stride=2	NOUN
ajst-24867	75	24	)	)	PUNCT
ajst-24867	75	25	conv	conv	NOUN
ajst-24867	75	26	(	(	PUNCT
ajst-24867	75	27	1x1	1x1	NUM
ajst-24867	75	28	,	,	PUNCT
ajst-24867	75	29	stride=1	stride=1	PROPN
ajst-24867	75	30	)	)	PUNCT
ajst-24867	75	31	conv	conv	NOUN
ajst-24867	75	32	(	(	PUNCT
ajst-24867	75	33	1x1	1x1	NUM
ajst-24867	75	34	,	,	PUNCT
ajst-24867	75	35	stride=1	stride=1	PROPN
ajst-24867	75	36	)	)	PUNCT
ajst-24867	75	37	concat	concat	NOUN
ajst-24867	75	38	figure	figure	VERB
ajst-24867	75	39	4	4	NUM
ajst-24867	75	40	.	.	PUNCT
ajst-24867	76	1	v7downsampling	v7downsample	VERB
ajst-24867	76	2	module	module	NOUN
ajst-24867	76	3	structure	structure	NOUN
ajst-24867	76	4	4	4	NUM
ajst-24867	76	5	.	.	PUNCT
ajst-24867	76	6	experimental	experimental	ADJ
ajst-24867	76	7	results	result	NOUN
ajst-24867	76	8	and	and	CCONJ
ajst-24867	76	9	analysis	analysis	NOUN
ajst-24867	76	10	4.1	4.1	NUM
ajst-24867	76	11	.	.	PUNCT
ajst-24867	77	1	experimental	experimental	ADJ
ajst-24867	77	2	environment	environment	NOUN
ajst-24867	77	3	this	this	DET
ajst-24867	77	4	article	article	NOUN
ajst-24867	77	5	uses	use	VERB
ajst-24867	77	6	the	the	DET
ajst-24867	77	7	64	64	NUM
ajst-24867	77	8	bit	bit	NOUN
ajst-24867	77	9	windows	window	NOUN
ajst-24867	77	10	11	11	NUM
ajst-24867	77	11	operating	operating	NOUN
ajst-24867	77	12	system	system	NOUN
ajst-24867	77	13	,	,	PUNCT
ajst-24867	77	14	cuda	cuda	NOUN
ajst-24867	77	15	version	version	NOUN
ajst-24867	77	16	10.2	10.2	NUM
ajst-24867	77	17	,	,	PUNCT
ajst-24867	77	18	programming	programming	NOUN
ajst-24867	77	19	language	language	NOUN
ajst-24867	77	20	python	python	NOUN
ajst-24867	77	21	3.8	3.8	NUM
ajst-24867	77	22	,	,	PUNCT
ajst-24867	77	23	deep	deep	ADJ
ajst-24867	77	24	learning	learning	NOUN
ajst-24867	77	25	framework	framework	NOUN
ajst-24867	77	26	pytorch	pytorch	NOUN
ajst-24867	77	27	1.12.1	1.12.1	NUM
ajst-24867	77	28	,	,	PUNCT
ajst-24867	77	29	and	and	CCONJ
ajst-24867	77	30	graphics	graphic	NOUN
ajst-24867	77	31	card	card	NOUN
ajst-24867	77	32	rtx6000	rtx6000	PROPN
ajst-24867	77	33	.	.	PUNCT
ajst-24867	78	1	the	the	DET
ajst-24867	78	2	experimental	experimental	ADJ
ajst-24867	78	3	parameters	parameter	NOUN
ajst-24867	78	4	are	be	AUX
ajst-24867	78	5	shown	show	VERB
ajst-24867	78	6	in	in	ADP
ajst-24867	78	7	table	table	NOUN
ajst-24867	78	8	1	1	NUM
ajst-24867	78	9	below	below	ADV
ajst-24867	78	10	.	.	PUNCT
ajst-24867	79	1	table	table	NOUN
ajst-24867	79	2	1	1	NUM
ajst-24867	79	3	.	.	PUNCT
ajst-24867	79	4	experimental	experimental	ADJ
ajst-24867	79	5	parameter	parameter	NOUN
ajst-24867	79	6	settings	setting	NOUN
ajst-24867	79	7	parameters	parameter	NOUN
ajst-24867	79	8	setup	setup	VERB
ajst-24867	79	9	input	input	NOUN
ajst-24867	79	10	image	image	NOUN
ajst-24867	79	11	size	size	NOUN
ajst-24867	79	12	640×640	640×640	NUM
ajst-24867	79	13	initial	initial	ADJ
ajst-24867	79	14	learning	learning	NOUN
ajst-24867	79	15	rate	rate	NOUN
ajst-24867	79	16	0.01	0.01	NUM
ajst-24867	79	17	epochs	epoch	NOUN
ajst-24867	79	18	200	200	NUM
ajst-24867	79	19	batch	batch	NOUN
ajst-24867	79	20	size	size	NOUN
ajst-24867	79	21	16	16	NUM
ajst-24867	79	22	optimizer	optimizer	NOUN
ajst-24867	79	23	sgd	sgd	NOUN
ajst-24867	79	24	momentum	momentum	NOUN
ajst-24867	79	25	0.937	0.937	NUM
ajst-24867	79	26	weight	weight	NOUN
ajst-24867	79	27	decay	decay	NOUN
ajst-24867	79	28	0.0005	0.0005	NUM
ajst-24867	79	29	4.2	4.2	NUM
ajst-24867	79	30	.	.	PUNCT
ajst-24867	80	1	dataset	dataset	NOUN
ajst-24867	80	2	and	and	CCONJ
ajst-24867	80	3	evaluation	evaluation	NOUN
ajst-24867	80	4	indicators	indicator	NOUN
ajst-24867	80	5	this	this	DET
ajst-24867	80	6	article	article	NOUN
ajst-24867	80	7	uses	use	VERB
ajst-24867	80	8	a	a	DET
ajst-24867	80	9	publicly	publicly	ADV
ajst-24867	80	10	available	available	ADJ
ajst-24867	80	11	infrared	infrared	ADJ
ajst-24867	80	12	ship	ship	NOUN
ajst-24867	80	13	dataset	dataset	VERB
ajst-24867	80	14	created	create	VERB
ajst-24867	80	15	by	by	ADP
ajst-24867	80	16	infiray	infiray	NOUN
ajst-24867	80	17	,	,	PUNCT
ajst-24867	80	18	which	which	PRON
ajst-24867	80	19	includes	include	VERB
ajst-24867	80	20	8402	8402	NUM
ajst-24867	80	21	images	image	NOUN
ajst-24867	80	22	of	of	ADP
ajst-24867	80	23	infrared	infrared	ADJ
ajst-24867	80	24	ships	ship	NOUN
ajst-24867	80	25	in	in	ADP
ajst-24867	80	26	7	7	NUM
ajst-24867	80	27	categories	category	NOUN
ajst-24867	80	28	:	:	PUNCT
ajst-24867	80	29	liner	liner	NOUN
ajst-24867	80	30	,	,	PUNCT
ajst-24867	80	31	bulk	bulk	ADJ
ajst-24867	80	32	carrier	carrier	NOUN
ajst-24867	80	33	,	,	PUNCT
ajst-24867	80	34	warship	warship	NOUN
ajst-24867	80	35	,	,	PUNCT
ajst-24867	80	36	sailboat	sailboat	NOUN
ajst-24867	80	37	,	,	PUNCT
ajst-24867	80	38	canoe	canoe	NOUN
ajst-24867	80	39	,	,	PUNCT
ajst-24867	80	40	container	container	NOUN
ajst-24867	80	41	ship	ship	NOUN
ajst-24867	80	42	,	,	PUNCT
ajst-24867	80	43	and	and	CCONJ
ajst-24867	80	44	fishing	fishing	NOUN
ajst-24867	80	45	boat	boat	NOUN
ajst-24867	80	46	.	.	PUNCT
ajst-24867	81	1	this	this	DET
ajst-24867	81	2	article	article	NOUN
ajst-24867	81	3	randomly	randomly	ADV
ajst-24867	81	4	divides	divide	VERB
ajst-24867	81	5	the	the	DET
ajst-24867	81	6	dataset	dataset	NOUN
ajst-24867	81	7	into	into	ADP
ajst-24867	81	8	training	training	NOUN
ajst-24867	81	9	,	,	PUNCT
ajst-24867	81	10	validation	validation	NOUN
ajst-24867	81	11	,	,	PUNCT
ajst-24867	81	12	and	and	CCONJ
ajst-24867	81	13	testing	testing	NOUN
ajst-24867	81	14	sets	set	NOUN
ajst-24867	81	15	in	in	ADP
ajst-24867	81	16	a	a	DET
ajst-24867	81	17	ratio	ratio	NOUN
ajst-24867	81	18	of	of	ADP
ajst-24867	81	19	7:2:1	7:2:1	PROPN
ajst-24867	81	20	.	.	PUNCT
ajst-24867	82	1	figures	figure	NOUN
ajst-24867	82	2	5	5	NUM
ajst-24867	82	3	and	and	CCONJ
ajst-24867	82	4	6	6	NUM
ajst-24867	82	5	show	show	VERB
ajst-24867	82	6	the	the	DET
ajst-24867	82	7	distribution	distribution	NOUN
ajst-24867	82	8	of	of	ADP
ajst-24867	82	9	the	the	DET
ajst-24867	82	10	number	number	NOUN
ajst-24867	82	11	of	of	ADP
ajst-24867	82	12	category	category	NOUN
ajst-24867	82	13	labels	label	NOUN
ajst-24867	82	14	and	and	CCONJ
ajst-24867	82	15	the	the	DET
ajst-24867	82	16	size	size	NOUN
ajst-24867	82	17	of	of	ADP
ajst-24867	82	18	label	label	NOUN
ajst-24867	82	19	bounding	bounding	NOUN
ajst-24867	82	20	boxes	box	NOUN
ajst-24867	82	21	,	,	PUNCT
ajst-24867	82	22	respectively	respectively	ADV
ajst-24867	82	23	.	.	PUNCT
ajst-24867	83	1	liner	liner	PROPN
ajst-24867	83	2	sailboat	sailboat	PROPN
ajst-24867	83	3	warship	warship	PROPN
ajst-24867	83	4	canoe	canoe	NOUN
ajst-24867	83	5	bulk	bulk	ADJ
ajst-24867	83	6	carrier	carrier	NOUN
ajst-24867	83	7	container	container	NOUN
ajst-24867	83	8	ship	ship	NOUN
ajst-24867	83	9	fishing	fishing	NOUN
ajst-24867	83	10	boat	boat	NOUN
ajst-24867	83	11	0	0	NUM
ajst-24867	83	12	1000	1000	NUM
ajst-24867	83	13	2000	2000	NUM
ajst-24867	83	14	3000	3000	NUM
ajst-24867	83	15	4000	4000	NUM
ajst-24867	83	16	5000	5000	NUM
ajst-24867	83	17	6000	6000	NUM
ajst-24867	83	18	in	in	ADP
ajst-24867	83	19	st	st	PROPN
ajst-24867	83	20	an	an	DET
ajst-24867	83	21	ce	ce	PROPN
ajst-24867	83	22	s	s	PART
ajst-24867	83	23	figure	figure	NOUN
ajst-24867	83	24	5	5	NUM
ajst-24867	83	25	.	.	PUNCT
ajst-24867	84	1	quantity	quantity	NOUN
ajst-24867	84	2	of	of	ADP
ajst-24867	84	3	various	various	ADJ
ajst-24867	84	4	labels	label	NOUN
ajst-24867	84	5	0.0	0.0	NUM
ajst-24867	84	6	0.2	0.2	NUM
ajst-24867	84	7	0.4	0.4	NUM
ajst-24867	84	8	0.6	0.6	NUM
ajst-24867	84	9	0.8	0.8	NUM
ajst-24867	84	10	1.0	1.0	NUM
ajst-24867	84	11	0.0	0.0	NUM
ajst-24867	84	12	0.2	0.2	NUM
ajst-24867	84	13	0.4	0.4	NUM
ajst-24867	84	14	0.6	0.6	NUM
ajst-24867	84	15	0.8	0.8	NUM
ajst-24867	84	16	1.0	1.0	NUM
ajst-24867	84	17	height	height	NOUN
ajst-24867	84	18	width	width	ADJ
ajst-24867	84	19	figure	figure	NOUN
ajst-24867	84	20	6	6	NUM
ajst-24867	84	21	.	.	PUNCT
ajst-24867	85	1	distribution	distribution	NOUN
ajst-24867	85	2	of	of	ADP
ajst-24867	85	3	label	label	NOUN
ajst-24867	85	4	bounding	bounding	NOUN
ajst-24867	85	5	box	box	NOUN
ajst-24867	85	6	sizes	size	NOUN
ajst-24867	85	7	83	83	NUM
ajst-24867	85	8	in	in	ADP
ajst-24867	85	9	order	order	NOUN
ajst-24867	85	10	to	to	PART
ajst-24867	85	11	accurately	accurately	ADV
ajst-24867	85	12	evaluate	evaluate	VERB
ajst-24867	85	13	the	the	DET
ajst-24867	85	14	performance	performance	NOUN
ajst-24867	85	15	of	of	ADP
ajst-24867	85	16	the	the	DET
ajst-24867	85	17	proposed	propose	VERB
ajst-24867	85	18	detection	detection	NOUN
ajst-24867	85	19	method	method	NOUN
ajst-24867	85	20	,	,	PUNCT
ajst-24867	85	21	precision	precision	NOUN
ajst-24867	85	22	(	(	PUNCT
ajst-24867	85	23	p	p	NOUN
ajst-24867	85	24	)	)	PUNCT
ajst-24867	85	25	,	,	PUNCT
ajst-24867	85	26	recall	recall	INTJ
ajst-24867	85	27	(	(	PUNCT
ajst-24867	85	28	r	r	NOUN
ajst-24867	85	29	)	)	PUNCT
ajst-24867	85	30	,	,	PUNCT
ajst-24867	85	31	and	and	CCONJ
ajst-24867	85	32	average	average	ADJ
ajst-24867	85	33	precision	precision	NOUN
ajst-24867	85	34	(	(	PUNCT
ajst-24867	85	35	map50	map50	PROPN
ajst-24867	85	36	)	)	PUNCT
ajst-24867	85	37	were	be	AUX
ajst-24867	85	38	used	use	VERB
ajst-24867	85	39	.	.	PUNCT
ajst-24867	86	1	the	the	PRON
ajst-24867	86	2	higher	high	ADJ
ajst-24867	86	3	the	the	DET
ajst-24867	86	4	p	p	X
ajst-24867	86	5	,	,	PUNCT
ajst-24867	86	6	r	r	NOUN
ajst-24867	86	7	,	,	PUNCT
ajst-24867	86	8	and	and	CCONJ
ajst-24867	86	9	map	map	NOUN
ajst-24867	86	10	,	,	PUNCT
ajst-24867	86	11	the	the	DET
ajst-24867	86	12	more	more	ADV
ajst-24867	86	13	accurate	accurate	ADJ
ajst-24867	86	14	the	the	DET
ajst-24867	86	15	object	object	NOUN
ajst-24867	86	16	detection	detection	NOUN
ajst-24867	86	17	.	.	PUNCT
ajst-24867	87	1	to	to	PART
ajst-24867	87	2	comprehensively	comprehensively	ADV
ajst-24867	87	3	evaluate	evaluate	VERB
ajst-24867	87	4	efficiency	efficiency	NOUN
ajst-24867	87	5	and	and	CCONJ
ajst-24867	87	6	performance	performance	NOUN
ajst-24867	87	7	,	,	PUNCT
ajst-24867	87	8	this	this	DET
ajst-24867	87	9	study	study	NOUN
ajst-24867	87	10	also	also	ADV
ajst-24867	87	11	considered	consider	VERB
ajst-24867	87	12	the	the	DET
ajst-24867	87	13	model	model	NOUN
ajst-24867	87	14	's	's	PART
ajst-24867	87	15	parameter	parameter	NOUN
ajst-24867	87	16	count	count	NOUN
ajst-24867	87	17	,	,	PUNCT
ajst-24867	87	18	computational	computational	ADJ
ajst-24867	87	19	complexity	complexity	NOUN
ajst-24867	87	20	,	,	PUNCT
ajst-24867	87	21	and	and	CCONJ
ajst-24867	87	22	model	model	NOUN
ajst-24867	87	23	size	size	NOUN
ajst-24867	87	24	.	.	PUNCT
ajst-24867	88	1	among	among	ADP
ajst-24867	88	2	them	they	PRON
ajst-24867	88	3	,	,	PUNCT
ajst-24867	88	4	map0.5	map0.5	PROPN
ajst-24867	88	5	represents	represent	VERB
ajst-24867	88	6	the	the	DET
ajst-24867	88	7	average	average	ADJ
ajst-24867	88	8	detection	detection	NOUN
ajst-24867	88	9	accuracy	accuracy	NOUN
ajst-24867	88	10	of	of	ADP
ajst-24867	88	11	all	all	DET
ajst-24867	88	12	target	target	NOUN
ajst-24867	88	13	categories	category	NOUN
ajst-24867	88	14	when	when	SCONJ
ajst-24867	88	15	the	the	DET
ajst-24867	88	16	iou	iou	NOUN
ajst-24867	88	17	threshold	threshold	NOUN
ajst-24867	88	18	is	be	AUX
ajst-24867	88	19	0.5	0.5	NUM
ajst-24867	88	20	.	.	PUNCT
ajst-24867	89	1	the	the	DET
ajst-24867	89	2	calculation	calculation	NOUN
ajst-24867	89	3	formulas	formula	VERB
ajst-24867	89	4	for	for	ADP
ajst-24867	89	5	p	p	NOUN
ajst-24867	89	6	,	,	PUNCT
ajst-24867	89	7	r	r	NOUN
ajst-24867	89	8	,	,	PUNCT
ajst-24867	89	9	ap	ap	PROPN
ajst-24867	89	10	(	(	PUNCT
ajst-24867	89	11	the	the	DET
ajst-24867	89	12	area	area	NOUN
ajst-24867	89	13	enclosed	enclose	VERB
ajst-24867	89	14	by	by	ADP
ajst-24867	89	15	the	the	DET
ajst-24867	89	16	pr	pr	NOUN
ajst-24867	89	17	curve	curve	NOUN
ajst-24867	89	18	)	)	PUNCT
ajst-24867	89	19	,	,	PUNCT
ajst-24867	89	20	and	and	CCONJ
ajst-24867	89	21	map	map	NOUN
ajst-24867	89	22	are	be	AUX
ajst-24867	89	23	as	as	SCONJ
ajst-24867	89	24	follows	follow	VERB
ajst-24867	89	25	.	.	PUNCT
ajst-24867	90	1	p	p	NOUN
ajst-24867	90	2	precision	precision	NOUN
ajst-24867	90	3	tp	tp	NOUN
ajst-24867	90	4	tp	tp	ADP
ajst-24867	90	5	f	f	PROPN
ajst-24867	91	1			PROPN
ajst-24867	91	2			PUNCT
ajst-24867	91	3	(	(	PUNCT
ajst-24867	91	4	9	9	NUM
ajst-24867	91	5	)	)	PUNCT
ajst-24867	91	6	tp	tp	NOUN
ajst-24867	91	7	tp	tp	ADP
ajst-24867	91	8	fn	fn	PROPN
ajst-24867	91	9	recall	recall	PROPN
ajst-24867	91	10			PROPN
ajst-24867	91	11			PUNCT
ajst-24867	91	12	(	(	PUNCT
ajst-24867	91	13	10	10	NUM
ajst-24867	91	14	)	)	PUNCT
ajst-24867	91	15	1	1	NUM
ajst-24867	91	16	0	0	NUM
ajst-24867	91	17	(	(	PUNCT
ajst-24867	91	18	)	)	PUNCT
ajst-24867	91	19	ap	ap	PROPN
ajst-24867	92	1	p	p	NOUN
ajst-24867	92	2	r	r	NOUN
ajst-24867	92	3	dr	dr	NOUN
ajst-24867	92	4			PUNCT
ajst-24867	92	5	(	(	PUNCT
ajst-24867	92	6	11	11	NUM
ajst-24867	92	7	)	)	PUNCT
ajst-24867	92	8	0	0	NUM
ajst-24867	93	1	1	1	NUM
ajst-24867	94	1	k	k	NOUN
ajst-24867	94	2	i	i	PRON
ajst-24867	95	1	i	i	PRON
ajst-24867	95	2	map	map	VERB
ajst-24867	96	1	ap	ap	PROPN
ajst-24867	97	1	k	k	PROPN
ajst-24867	98	1			PROPN
ajst-24867	98	2			ADJ
ajst-24867	98	3			X
ajst-24867	98	4	(	(	PUNCT
ajst-24867	98	5	12	12	NUM
ajst-24867	98	6	)	)	PUNCT
ajst-24867	98	7	1	1	NUM
ajst-24867	98	8	0	0	NUM
ajst-24867	98	9	(	(	PUNCT
ajst-24867	98	10	)	)	PUNCT
ajst-24867	98	11	ap	ap	PROPN
ajst-24867	99	1	p	p	NOUN
ajst-24867	99	2	r	r	NOUN
ajst-24867	99	3	dr	dr	NOUN
ajst-24867	99	4			PUNCT
ajst-24867	99	5	(	(	PUNCT
ajst-24867	99	6	13	13	NUM
ajst-24867	99	7	)	)	PUNCT
ajst-24867	99	8	among	among	ADP
ajst-24867	99	9	them	they	PRON
ajst-24867	99	10	:	:	PUNCT
ajst-24867	99	11	represents	represent	VERB
ajst-24867	99	12	the	the	DET
ajst-24867	99	13	number	number	NOUN
ajst-24867	99	14	of	of	ADP
ajst-24867	99	15	correctly	correctly	ADV
ajst-24867	99	16	predicted	predict	VERB
ajst-24867	99	17	positive	positive	ADJ
ajst-24867	99	18	classes	class	NOUN
ajst-24867	99	19	,	,	PUNCT
ajst-24867	99	20	represents	represent	VERB
ajst-24867	99	21	the	the	DET
ajst-24867	99	22	number	number	NOUN
ajst-24867	99	23	of	of	ADP
ajst-24867	99	24	incorrectly	incorrectly	ADV
ajst-24867	99	25	predicted	predict	VERB
ajst-24867	99	26	negative	negative	ADJ
ajst-24867	99	27	classes	class	NOUN
ajst-24867	99	28	,	,	PUNCT
ajst-24867	99	29	represents	represent	VERB
ajst-24867	99	30	the	the	DET
ajst-24867	99	31	number	number	NOUN
ajst-24867	99	32	of	of	ADP
ajst-24867	99	33	incorrectly	incorrectly	ADV
ajst-24867	99	34	predicted	predict	VERB
ajst-24867	99	35	positive	positive	ADJ
ajst-24867	99	36	classes	class	NOUN
ajst-24867	99	37	.	.	PUNCT
ajst-24867	100	1	figures	figure	NOUN
ajst-24867	100	2	7	7	NUM
ajst-24867	100	3	(	(	PUNCT
ajst-24867	100	4	a	a	NOUN
ajst-24867	100	5	)	)	PUNCT
ajst-24867	100	6	and	and	CCONJ
ajst-24867	100	7	(	(	PUNCT
ajst-24867	100	8	b	b	X
ajst-24867	100	9	)	)	PUNCT
ajst-24867	100	10	represent	represent	VERB
ajst-24867	100	11	the	the	DET
ajst-24867	100	12	pr	pr	NOUN
ajst-24867	100	13	curves	curve	NOUN
ajst-24867	100	14	before	before	ADV
ajst-24867	100	15	and	and	CCONJ
ajst-24867	100	16	after	after	ADP
ajst-24867	100	17	the	the	DET
ajst-24867	100	18	improvement	improvement	NOUN
ajst-24867	100	19	,	,	PUNCT
ajst-24867	100	20	respectively	respectively	ADV
ajst-24867	100	21	.	.	PUNCT
ajst-24867	101	1	from	from	ADP
ajst-24867	101	2	the	the	DET
ajst-24867	101	3	figures	figure	NOUN
ajst-24867	101	4	,	,	PUNCT
ajst-24867	101	5	it	it	PRON
ajst-24867	101	6	can	can	AUX
ajst-24867	101	7	be	be	AUX
ajst-24867	101	8	seen	see	VERB
ajst-24867	101	9	that	that	SCONJ
ajst-24867	101	10	the	the	DET
ajst-24867	101	11	improved	improved	ADJ
ajst-24867	101	12	algorithm	algorithm	NOUN
ajst-24867	101	13	has	have	VERB
ajst-24867	101	14	varying	vary	VERB
ajst-24867	101	15	degrees	degree	NOUN
ajst-24867	101	16	of	of	ADP
ajst-24867	101	17	detection	detection	NOUN
ajst-24867	101	18	accuracy	accuracy	NOUN
ajst-24867	101	19	on	on	ADP
ajst-24867	101	20	seven	seven	NUM
ajst-24867	101	21	types	type	NOUN
ajst-24867	101	22	of	of	ADP
ajst-24867	101	23	ships	ship	NOUN
ajst-24867	101	24	,	,	PUNCT
ajst-24867	101	25	includifng	includifng	ADJ
ajst-24867	101	26	liners	liner	NOUN
ajst-24867	101	27	map@0.5	map@0.5	NOUN
ajst-24867	101	28	improved	improve	VERB
ajst-24867	101	29	from	from	ADP
ajst-24867	101	30	0.889	0.889	NUM
ajst-24867	101	31	to	to	ADP
ajst-24867	101	32	0.923	0.923	NUM
ajst-24867	101	33	,	,	PUNCT
ajst-24867	101	34	overall	overall	ADJ
ajst-24867	101	35	,	,	PUNCT
ajst-24867	101	36	the	the	DET
ajst-24867	101	37	improved	improve	VERB
ajst-24867	101	38	yolo	yolo	ADJ
ajst-24867	101	39	model	model	NOUN
ajst-24867	101	40	has	have	VERB
ajst-24867	101	41	an	an	DET
ajst-24867	101	42	average	average	ADJ
ajst-24867	101	43	precision	precision	NOUN
ajst-24867	101	44	mean	mean	VERB
ajst-24867	101	45	across	across	ADP
ajst-24867	101	46	all	all	DET
ajst-24867	101	47	categories	category	NOUN
ajst-24867	101	48	(	(	PUNCT
ajst-24867	101	49	map@0.5	map@0.5	PROPN
ajst-24867	101	50	)	)	PUNCT
ajst-24867	101	51	the	the	DET
ajst-24867	101	52	improvement	improvement	NOUN
ajst-24867	101	53	from	from	ADP
ajst-24867	101	54	0.889	0.889	NUM
ajst-24867	101	55	to	to	ADP
ajst-24867	101	56	0.923	0.923	NUM
ajst-24867	101	57	indicates	indicate	VERB
ajst-24867	101	58	that	that	SCONJ
ajst-24867	101	59	the	the	DET
ajst-24867	101	60	improved	improved	ADJ
ajst-24867	101	61	model	model	NOUN
ajst-24867	101	62	performs	perform	VERB
ajst-24867	101	63	better	well	ADV
ajst-24867	101	64	in	in	ADP
ajst-24867	101	65	infrared	infrared	ADJ
ajst-24867	101	66	ship	ship	NOUN
ajst-24867	101	67	detection	detection	NOUN
ajst-24867	101	68	and	and	CCONJ
ajst-24867	101	69	can	can	AUX
ajst-24867	101	70	more	more	ADV
ajst-24867	101	71	accurately	accurately	ADV
ajst-24867	101	72	detect	detect	VERB
ajst-24867	101	73	and	and	CCONJ
ajst-24867	101	74	identify	identify	VERB
ajst-24867	101	75	different	different	ADJ
ajst-24867	101	76	types	type	NOUN
ajst-24867	101	77	of	of	ADP
ajst-24867	101	78	ships	ship	NOUN
ajst-24867	101	79	figure	figure	VERB
ajst-24867	101	80	7	7	NUM
ajst-24867	101	81	.	.	PUNCT
ajst-24867	102	1	(	(	PUNCT
ajst-24867	102	2	a	a	X
ajst-24867	102	3	)	)	PUNCT
ajst-24867	102	4	pr	pr	NOUN
ajst-24867	102	5	curve	curve	NOUN
ajst-24867	102	6	before	before	ADP
ajst-24867	102	7	improvement	improvement	NOUN
ajst-24867	102	8	figure	figure	NOUN
ajst-24867	102	9	figure	figure	NOUN
ajst-24867	102	10	7	7	NUM
ajst-24867	102	11	.	.	PUNCT
ajst-24867	103	1	(	(	PUNCT
ajst-24867	103	2	b	b	X
ajst-24867	103	3	)	)	PUNCT
ajst-24867	103	4	pr	pr	NOUN
ajst-24867	103	5	curve	curve	NOUN
ajst-24867	103	6	after	after	ADP
ajst-24867	103	7	improvement	improvement	NOUN
ajst-24867	103	8	4.3	4.3	NUM
ajst-24867	103	9	.	.	PUNCT
ajst-24867	103	10	module	module	NOUN
ajst-24867	103	11	ablation	ablation	NOUN
ajst-24867	103	12	experiment	experiment	NOUN
ajst-24867	103	13	in	in	ADP
ajst-24867	103	14	order	order	NOUN
ajst-24867	103	15	to	to	PART
ajst-24867	103	16	verify	verify	VERB
ajst-24867	103	17	the	the	DET
ajst-24867	103	18	effectiveness	effectiveness	NOUN
ajst-24867	103	19	of	of	ADP
ajst-24867	103	20	the	the	DET
ajst-24867	103	21	small	small	ADJ
ajst-24867	103	22	target	target	NOUN
ajst-24867	103	23	detection	detection	NOUN
ajst-24867	103	24	layer	layer	NOUN
ajst-24867	103	25	,	,	PUNCT
ajst-24867	103	26	focaler	focaler	NOUN
ajst-24867	103	27	mpdiou	mpdiou	NOUN
ajst-24867	103	28	loss	loss	NOUN
ajst-24867	103	29	function	function	NOUN
ajst-24867	103	30	,	,	PUNCT
ajst-24867	103	31	and	and	CCONJ
ajst-24867	103	32	yolov5	yolov5	NOUN
ajst-24867	103	33	downsampling	downsample	VERB
ajst-24867	103	34	module	module	NOUN
ajst-24867	103	35	,	,	PUNCT
ajst-24867	103	36	the	the	DET
ajst-24867	103	37	following	follow	VERB
ajst-24867	103	38	ablation	ablation	NOUN
ajst-24867	103	39	experiments	experiment	NOUN
ajst-24867	103	40	were	be	AUX
ajst-24867	103	41	conducted	conduct	VERB
ajst-24867	103	42	using	use	VERB
ajst-24867	103	43	yolo	yolo	ADJ
ajst-24867	103	44	v8n	v8n	PROPN
ajst-24867	103	45	as	as	ADP
ajst-24867	103	46	the	the	DET
ajst-24867	103	47	baseline	baseline	NOUN
ajst-24867	103	48	model	model	NOUN
ajst-24867	103	49	.	.	PUNCT
ajst-24867	104	1	the	the	DET
ajst-24867	104	2	experimental	experimental	ADJ
ajst-24867	104	3	results	result	NOUN
ajst-24867	104	4	are	be	AUX
ajst-24867	104	5	shown	show	VERB
ajst-24867	104	6	in	in	ADP
ajst-24867	104	7	table	table	NOUN
ajst-24867	104	8	2	2	NUM
ajst-24867	104	9	(	(	PUNCT
ajst-24867	104	10	where	where	SCONJ
ajst-24867	104	11	p2	p2	NOUN
ajst-24867	104	12	,	,	PUNCT
ajst-24867	104	13	f	f	X
ajst-24867	104	14	,	,	PUNCT
ajst-24867	104	15	and	and	CCONJ
ajst-24867	104	16	v	v	AUX
ajst-24867	104	17	represent	represent	VERB
ajst-24867	104	18	the	the	DET
ajst-24867	104	19	p2	p2	PROPN
ajst-24867	104	20	small	small	ADJ
ajst-24867	104	21	target	target	NOUN
ajst-24867	104	22	detection	detection	NOUN
ajst-24867	104	23	layer	layer	NOUN
ajst-24867	104	24	,	,	PUNCT
ajst-24867	104	25	focaler	focaler	NOUN
ajst-24867	104	26	mpdiou	mpdiou	NOUN
ajst-24867	104	27	loss	loss	NOUN
ajst-24867	104	28	function	function	NOUN
ajst-24867	104	29	,	,	PUNCT
ajst-24867	104	30	v7	v7	VERB
ajst-24867	104	31	downsampling	downsampling	NOUN
ajst-24867	104	32	,	,	PUNCT
ajst-24867	104	33	and	and	CCONJ
ajst-24867	104	34	'	'	PUNCT
ajst-24867	104	35	√	√	VERB
ajst-24867	104	36	'	'	PUNCT
ajst-24867	104	37	represents	represent	VERB
ajst-24867	104	38	the	the	DET
ajst-24867	104	39	use	use	NOUN
ajst-24867	104	40	of	of	ADP
ajst-24867	104	41	this	this	DET
ajst-24867	104	42	module	module	NOUN
ajst-24867	104	43	in	in	ADP
ajst-24867	104	44	this	this	DET
ajst-24867	104	45	set	set	NOUN
ajst-24867	104	46	of	of	ADP
ajst-24867	104	47	experiments	experiment	NOUN
ajst-24867	104	48	)	)	PUNCT
ajst-24867	104	49	.	.	PUNCT
ajst-24867	105	1	in	in	ADP
ajst-24867	105	2	experiments	experiment	NOUN
ajst-24867	105	3	a	a	DET
ajst-24867	105	4	,	,	PUNCT
ajst-24867	105	5	b	b	NOUN
ajst-24867	105	6	,	,	PUNCT
ajst-24867	105	7	and	and	CCONJ
ajst-24867	105	8	c	c	X
ajst-24867	105	9	,	,	PUNCT
ajst-24867	105	10	the	the	DET
ajst-24867	105	11	addition	addition	NOUN
ajst-24867	105	12	of	of	ADP
ajst-24867	105	13	p2	p2	PROPN
ajst-24867	105	14	,	,	PUNCT
ajst-24867	105	15	f	f	X
ajst-24867	105	16	,	,	PUNCT
ajst-24867	105	17	and	and	CCONJ
ajst-24867	105	18	v	v	ADP
ajst-24867	105	19	modules	module	NOUN
ajst-24867	105	20	to	to	ADP
ajst-24867	105	21	yolo	yolo	ADJ
ajst-24867	105	22	v8n	v8n	PROPN
ajst-24867	105	23	resulted	result	VERB
ajst-24867	105	24	in	in	ADP
ajst-24867	105	25	varying	vary	VERB
ajst-24867	105	26	degrees	degree	NOUN
ajst-24867	105	27	of	of	ADP
ajst-24867	105	28	improvement	improvement	NOUN
ajst-24867	105	29	in	in	ADP
ajst-24867	105	30	average	average	ADJ
ajst-24867	105	31	accuracy	accuracy	NOUN
ajst-24867	105	32	.	.	PUNCT
ajst-24867	106	1	among	among	ADP
ajst-24867	106	2	them	they	PRON
ajst-24867	106	3	,	,	PUNCT
ajst-24867	106	4	the	the	DET
ajst-24867	106	5	addition	addition	NOUN
ajst-24867	106	6	of	of	ADP
ajst-24867	106	7	a	a	DET
ajst-24867	106	8	small	small	ADJ
ajst-24867	106	9	target	target	NOUN
ajst-24867	106	10	layer	layer	NOUN
ajst-24867	106	11	led	lead	VERB
ajst-24867	106	12	to	to	ADP
ajst-24867	106	13	map@0.5	map@0.5	PROPN
ajst-24867	106	14	reached	reach	VERB
ajst-24867	106	15	91.5	91.5	NUM
ajst-24867	106	16	%	%	NOUN
ajst-24867	106	17	,	,	PUNCT
ajst-24867	106	18	an	an	DET
ajst-24867	106	19	increase	increase	NOUN
ajst-24867	106	20	of	of	ADP
ajst-24867	106	21	2.6	2.6	NUM
ajst-24867	106	22	percentage	percentage	NOUN
ajst-24867	106	23	points	point	NOUN
ajst-24867	106	24	,	,	PUNCT
ajst-24867	106	25	significantly	significantly	ADV
ajst-24867	106	26	improving	improve	VERB
ajst-24867	106	27	the	the	DET
ajst-24867	106	28	detection	detection	NOUN
ajst-24867	106	29	performance	performance	NOUN
ajst-24867	106	30	of	of	ADP
ajst-24867	106	31	small	small	ADJ
ajst-24867	106	32	targets	target	NOUN
ajst-24867	106	33	and	and	CCONJ
ajst-24867	106	34	effectively	effectively	ADV
ajst-24867	106	35	reducing	reduce	VERB
ajst-24867	106	36	missed	miss	VERB
ajst-24867	106	37	detections	detection	NOUN
ajst-24867	106	38	.	.	PUNCT
ajst-24867	107	1	introducing	introduce	VERB
ajst-24867	107	2	focaler	focaler	NOUN
ajst-24867	107	3	mpdiou	mpdiou	NOUN
ajst-24867	107	4	separately	separately	ADV
ajst-24867	107	5	,	,	PUNCT
ajst-24867	107	6	map@0.5	map@0.5	VERB
ajst-24867	107	7	by	by	ADP
ajst-24867	107	8	increasing	increase	VERB
ajst-24867	107	9	by	by	ADP
ajst-24867	107	10	0.5	0.5	NUM
ajst-24867	107	11	percentage	percentage	NOUN
ajst-24867	107	12	points	point	NOUN
ajst-24867	107	13	,	,	PUNCT
ajst-24867	107	14	p	p	NOUN
ajst-24867	107	15	and	and	CCONJ
ajst-24867	107	16	r	r	NOUN
ajst-24867	107	17	also	also	ADV
ajst-24867	107	18	showed	show	VERB
ajst-24867	107	19	varying	vary	VERB
ajst-24867	107	20	degrees	degree	NOUN
ajst-24867	107	21	of	of	ADP
ajst-24867	107	22	improvement	improvement	NOUN
ajst-24867	107	23	,	,	PUNCT
ajst-24867	107	24	while	while	SCONJ
ajst-24867	107	25	indicators	indicator	NOUN
ajst-24867	107	26	such	such	ADJ
ajst-24867	107	27	as	as	ADP
ajst-24867	107	28	computational	computational	ADJ
ajst-24867	107	29	complexity	complexity	NOUN
ajst-24867	107	30	remained	remain	VERB
ajst-24867	107	31	unchanged	unchanged	ADJ
ajst-24867	107	32	.	.	PUNCT
ajst-24867	108	1	this	this	PRON
ajst-24867	108	2	indicates	indicate	VERB
ajst-24867	108	3	that	that	SCONJ
ajst-24867	108	4	the	the	DET
ajst-24867	108	5	focaler	focaler	NOUN
ajst-24867	108	6	mpdiou	mpdiou	NOUN
ajst-24867	108	7	loss	loss	NOUN
ajst-24867	108	8	function	function	NOUN
ajst-24867	108	9	is	be	AUX
ajst-24867	108	10	lossless	lossless	ADJ
ajst-24867	108	11	in	in	ADP
ajst-24867	108	12	improving	improve	VERB
ajst-24867	108	13	the	the	DET
ajst-24867	108	14	detection	detection	NOUN
ajst-24867	108	15	performance	performance	NOUN
ajst-24867	108	16	of	of	ADP
ajst-24867	108	17	the	the	DET
ajst-24867	108	18	model	model	NOUN
ajst-24867	108	19	.	.	PUNCT
ajst-24867	109	1	only	only	ADV
ajst-24867	109	2	add	add	VERB
ajst-24867	109	3	v7downsampling	v7downsample	VERB
ajst-24867	109	4	,	,	PUNCT
ajst-24867	109	5	map@0.5	map@0.5	VERB
ajst-24867	109	6	an	an	DET
ajst-24867	109	7	increase	increase	NOUN
ajst-24867	109	8	of	of	ADP
ajst-24867	109	9	0.1	0.1	NUM
ajst-24867	109	10	percentage	percentage	NOUN
ajst-24867	109	11	points	point	NOUN
ajst-24867	109	12	,	,	PUNCT
ajst-24867	109	13	a	a	DET
ajst-24867	109	14	9	9	NUM
ajst-24867	109	15	%	%	NOUN
ajst-24867	109	16	reduction	reduction	NOUN
ajst-24867	109	17	in	in	ADP
ajst-24867	109	18	parameter	parameter	NOUN
ajst-24867	109	19	count	count	NOUN
ajst-24867	109	20	,	,	PUNCT
ajst-24867	109	21	and	and	CCONJ
ajst-24867	109	22	an	an	DET
ajst-24867	109	23	8	8	NUM
ajst-24867	109	24	%	%	NOUN
ajst-24867	109	25	reduction	reduction	NOUN
ajst-24867	109	26	in	in	ADP
ajst-24867	109	27	model	model	NOUN
ajst-24867	109	28	size	size	NOUN
ajst-24867	109	29	indicate	indicate	VERB
ajst-24867	109	30	that	that	SCONJ
ajst-24867	109	31	it	it	PRON
ajst-24867	109	32	can	can	AUX
ajst-24867	109	33	improve	improve	VERB
ajst-24867	109	34	detection	detection	NOUN
ajst-24867	109	35	accuracy	accuracy	NOUN
ajst-24867	109	36	while	while	SCONJ
ajst-24867	109	37	reducing	reduce	VERB
ajst-24867	109	38	model	model	NOUN
ajst-24867	109	39	complexity	complexity	NOUN
ajst-24867	109	40	.	.	PUNCT
ajst-24867	110	1	when	when	SCONJ
ajst-24867	110	2	the	the	DET
ajst-24867	110	3	three	three	NUM
ajst-24867	110	4	improved	improved	ADJ
ajst-24867	110	5	modules	module	NOUN
ajst-24867	110	6	were	be	AUX
ajst-24867	110	7	combined	combine	VERB
ajst-24867	110	8	in	in	ADP
ajst-24867	110	9	the	the	DET
ajst-24867	110	10	last	last	ADJ
ajst-24867	110	11	set	set	NOUN
ajst-24867	110	12	of	of	ADP
ajst-24867	110	13	experiments	experiment	NOUN
ajst-24867	110	14	,	,	PUNCT
ajst-24867	110	15	the	the	DET
ajst-24867	110	16	model	model	NOUN
ajst-24867	110	17	achieved	achieve	VERB
ajst-24867	110	18	optimal	optimal	ADJ
ajst-24867	110	19	performance	performance	NOUN
ajst-24867	110	20	,	,	PUNCT
ajst-24867	110	21	map@0.5	map@0.5	VERB
ajst-24867	110	22	the	the	DET
ajst-24867	110	23	highest	high	ADJ
ajst-24867	110	24	value	value	NOUN
ajst-24867	110	25	of	of	ADP
ajst-24867	110	26	92.3	92.3	NUM
ajst-24867	110	27	%	%	NOUN
ajst-24867	110	28	was	be	AUX
ajst-24867	110	29	achieved	achieve	VERB
ajst-24867	110	30	on	on	ADP
ajst-24867	110	31	yolov8n	yolov8n	NOUN
ajst-24867	110	32	,	,	PUNCT
ajst-24867	110	33	which	which	PRON
ajst-24867	110	34	increased	increase	VERB
ajst-24867	110	35	by	by	ADP
ajst-24867	110	36	3.4	3.4	NUM
ajst-24867	110	37	percentage	percentage	NOUN
ajst-24867	110	38	points	point	NOUN
ajst-24867	110	39	compared	compare	VERB
ajst-24867	110	40	to	to	ADP
ajst-24867	110	41	yolov8n	yolov8n	NOUN
ajst-24867	110	42	.	.	PUNCT
ajst-24867	111	1	at	at	ADP
ajst-24867	111	2	the	the	DET
ajst-24867	111	3	same	same	ADJ
ajst-24867	111	4	time	time	NOUN
ajst-24867	111	5	,	,	PUNCT
ajst-24867	111	6	the	the	DET
ajst-24867	111	7	number	number	NOUN
ajst-24867	111	8	of	of	ADP
ajst-24867	111	9	parameters	parameter	NOUN
ajst-24867	111	10	decreased	decrease	VERB
ajst-24867	111	11	by	by	ADP
ajst-24867	111	12	11.8	11.8	NUM
ajst-24867	111	13	%	%	NOUN
ajst-24867	111	14	and	and	CCONJ
ajst-24867	111	15	the	the	DET
ajst-24867	111	16	model	model	NOUN
ajst-24867	111	17	size	size	NOUN
ajst-24867	111	18	decreased	decrease	VERB
ajst-24867	111	19	by	by	ADP
ajst-24867	111	20	8	8	NUM
ajst-24867	111	21	%	%	NOUN
ajst-24867	111	22	.	.	PUNCT
ajst-24867	112	1	although	although	SCONJ
ajst-24867	112	2	it	it	PRON
ajst-24867	112	3	slightly	slightly	ADV
ajst-24867	112	4	increased	increase	VERB
ajst-24867	112	5	the	the	DET
ajst-24867	112	6	computational	computational	ADJ
ajst-24867	112	7	load	load	NOUN
ajst-24867	112	8	,	,	PUNCT
ajst-24867	112	9	the	the	DET
ajst-24867	112	10	significant	significant	ADJ
ajst-24867	112	11	performance	performance	NOUN
ajst-24867	112	12	improvement	improvement	NOUN
ajst-24867	112	13	it	it	PRON
ajst-24867	112	14	brought	bring	VERB
ajst-24867	112	15	was	be	AUX
ajst-24867	112	16	also	also	ADV
ajst-24867	112	17	worth	worth	ADJ
ajst-24867	112	18	it	it	PRON
ajst-24867	112	19	.	.	PUNCT
ajst-24867	113	1	in	in	ADP
ajst-24867	113	2	summary	summary	NOUN
ajst-24867	113	3	,	,	PUNCT
ajst-24867	113	4	each	each	DET
ajst-24867	113	5	improved	improve	VERB
ajst-24867	113	6	module	module	NOUN
ajst-24867	113	7	has	have	AUX
ajst-24867	113	8	been	be	AUX
ajst-24867	113	9	validated	validate	VERB
ajst-24867	113	10	through	through	ADP
ajst-24867	113	11	ablation	ablation	NOUN
ajst-24867	113	12	experiments	experiment	NOUN
ajst-24867	113	13	for	for	ADP
ajst-24867	113	14	its	its	PRON
ajst-24867	113	15	positive	positive	ADJ
ajst-24867	113	16	role	role	NOUN
ajst-24867	113	17	in	in	ADP
ajst-24867	113	18	improving	improve	VERB
ajst-24867	113	19	detection	detection	NOUN
ajst-24867	113	20	accuracy	accuracy	NOUN
ajst-24867	113	21	and	and	CCONJ
ajst-24867	113	22	optimizing	optimize	VERB
ajst-24867	113	23	model	model	NOUN
ajst-24867	113	24	complexity	complexity	NOUN
ajst-24867	113	25	.	.	PUNCT
ajst-24867	114	1	especially	especially	ADV
ajst-24867	114	2	after	after	ADP
ajst-24867	114	3	integrating	integrate	VERB
ajst-24867	114	4	all	all	DET
ajst-24867	114	5	the	the	DET
ajst-24867	114	6	improvement	improvement	NOUN
ajst-24867	114	7	points	point	NOUN
ajst-24867	114	8	,	,	PUNCT
ajst-24867	114	9	the	the	DET
ajst-24867	114	10	overall	overall	ADJ
ajst-24867	114	11	performance	performance	NOUN
ajst-24867	114	12	of	of	ADP
ajst-24867	114	13	the	the	DET
ajst-24867	114	14	model	model	NOUN
ajst-24867	114	15	has	have	AUX
ajst-24867	114	16	been	be	AUX
ajst-24867	114	17	significantly	significantly	ADV
ajst-24867	114	18	improved	improve	VERB
ajst-24867	114	19	,	,	PUNCT
ajst-24867	114	20	proving	prove	VERB
ajst-24867	114	21	the	the	DET
ajst-24867	114	22	effectiveness	effectiveness	NOUN
ajst-24867	114	23	and	and	CCONJ
ajst-24867	114	24	rationality	rationality	NOUN
ajst-24867	114	25	of	of	ADP
ajst-24867	114	26	these	these	DET
ajst-24867	114	27	improvement	improvement	NOUN
ajst-24867	114	28	methods	method	NOUN
ajst-24867	114	29	.	.	PUNCT
ajst-24867	115	1	5	5	X
ajst-24867	115	2	.	.	X
ajst-24867	115	3	comparative	comparative	ADJ
ajst-24867	115	4	experiments	experiment	NOUN
ajst-24867	115	5	of	of	ADP
ajst-24867	115	6	different	different	ADJ
ajst-24867	115	7	models	model	NOUN
ajst-24867	115	8	to	to	PART
ajst-24867	115	9	further	far	ADV
ajst-24867	115	10	highlight	highlight	VERB
ajst-24867	115	11	the	the	DET
ajst-24867	115	12	superiority	superiority	NOUN
ajst-24867	115	13	of	of	ADP
ajst-24867	115	14	the	the	DET
ajst-24867	115	15	algorithm	algorithm	NOUN
ajst-24867	115	16	proposed	propose	VERB
ajst-24867	115	17	in	in	ADP
ajst-24867	115	18	this	this	DET
ajst-24867	115	19	article	article	NOUN
ajst-24867	115	20	,	,	PUNCT
ajst-24867	115	21	a	a	DET
ajst-24867	115	22	comparative	comparative	ADJ
ajst-24867	115	23	experiment	experiment	NOUN
ajst-24867	115	24	was	be	AUX
ajst-24867	115	25	conducted	conduct	VERB
ajst-24867	115	26	with	with	ADP
ajst-24867	115	27	several	several	ADJ
ajst-24867	115	28	mainstream	mainstream	NOUN
ajst-24867	115	29	deep	deep	ADJ
ajst-24867	115	30	learning	learning	NOUN
ajst-24867	115	31	based	base	VERB
ajst-24867	115	32	object	object	NOUN
ajst-24867	115	33	detection	detection	NOUN
ajst-24867	115	34	algorithms	algorithm	NOUN
ajst-24867	115	35	.	.	PUNCT
ajst-24867	116	1	in	in	ADP
ajst-24867	116	2	this	this	DET
ajst-24867	116	3	comparative	comparative	ADJ
ajst-24867	116	4	experiment	experiment	NOUN
ajst-24867	116	5	,	,	PUNCT
ajst-24867	116	6	the	the	DET
ajst-24867	116	7	focus	focus	NOUN
ajst-24867	116	8	was	be	AUX
ajst-24867	116	9	on	on	ADP
ajst-24867	116	10	the	the	DET
ajst-24867	116	11	accuracy	accuracy	NOUN
ajst-24867	116	12	(	(	PUNCT
ajst-24867	116	13	p%	p%	PROPN
ajst-24867	116	14	)	)	PUNCT
ajst-24867	116	15	and	and	CCONJ
ajst-24867	116	16	recall	recall	NOUN
ajst-24867	116	17	(	(	PUNCT
ajst-24867	116	18	r%	r%	PROPN
ajst-24867	116	19	)	)	PUNCT
ajst-24867	116	20	of	of	ADP
ajst-24867	116	21	the	the	DET
ajst-24867	116	22	model	model	NOUN
ajst-24867	116	23	map@0.5	map@0.5	X
ajst-24867	117	1	%	%	INTJ
ajst-24867	117	2	these	these	DET
ajst-24867	117	3	three	three	NUM
ajst-24867	117	4	core	core	ADJ
ajst-24867	117	5	indicators	indicator	NOUN
ajst-24867	117	6	,	,	PUNCT
ajst-24867	117	7	as	as	ADV
ajst-24867	117	8	well	well	ADV
ajst-24867	117	9	as	as	ADP
ajst-24867	117	10	the	the	DET
ajst-24867	117	11	84	84	NUM
ajst-24867	117	12	three	three	NUM
ajst-24867	117	13	efficiency	efficiency	NOUN
ajst-24867	117	14	indicators	indicator	NOUN
ajst-24867	117	15	of	of	ADP
ajst-24867	117	16	parameter	parameter	NOUN
ajst-24867	117	17	quantity	quantity	NOUN
ajst-24867	117	18	,	,	PUNCT
ajst-24867	117	19	model	model	NOUN
ajst-24867	117	20	size	size	NOUN
ajst-24867	117	21	,	,	PUNCT
ajst-24867	117	22	and	and	CCONJ
ajst-24867	117	23	computational	computational	ADJ
ajst-24867	117	24	complexity	complexity	NOUN
ajst-24867	117	25	.	.	PUNCT
ajst-24867	118	1	the	the	DET
ajst-24867	118	2	experimental	experimental	ADJ
ajst-24867	118	3	results	result	NOUN
ajst-24867	118	4	are	be	AUX
ajst-24867	118	5	shown	show	VERB
ajst-24867	118	6	in	in	ADP
ajst-24867	118	7	table	table	NOUN
ajst-24867	118	8	3	3	NUM
ajst-24867	118	9	.	.	PUNCT
ajst-24867	118	10	table	table	NOUN
ajst-24867	118	11	2	2	NUM
ajst-24867	118	12	.	.	PUNCT
ajst-24867	118	13	ablation	ablation	NOUN
ajst-24867	118	14	experiment	experiment	NOUN
ajst-24867	118	15	model	model	NOUN
ajst-24867	118	16	p2	p2	PROPN
ajst-24867	118	17	f	f	PROPN
ajst-24867	118	18	v	v	ADP
ajst-24867	118	19	p/%	p/%	PROPN
ajst-24867	118	20	r/%	r/%	PROPN
ajst-24867	118	21	map@0.5/%	map@0.5/%	NOUN
ajst-24867	118	22	parameter	parameter	NOUN
ajst-24867	118	23	quantity	quantity	NOUN
ajst-24867	118	24	/106	/106	NOUN
ajst-24867	118	25	model	model	NOUN
ajst-24867	118	26	size	size	NOUN
ajst-24867	118	27	/	/	SYM
ajst-24867	118	28	mb	mb	ADP
ajst-24867	118	29	calculated	calculate	VERB
ajst-24867	118	30	amount	amount	NOUN
ajst-24867	118	31	(	(	PUNCT
ajst-24867	118	32	gflops	gflop	NOUN
ajst-24867	118	33	)	)	PUNCT
ajst-24867	118	34	yolov8n	yolov8n	NOUN
ajst-24867	118	35	90.3	90.3	NUM
ajst-24867	118	36	84.3	84.3	NUM
ajst-24867	118	37	88.9	88.9	NUM
ajst-24867	118	38	3.007013	3.007013	NUM
ajst-24867	118	39	6.3	6.3	NUM
ajst-24867	118	40	8.1	8.1	NUM
ajst-24867	118	41	a	a	DET
ajst-24867	118	42	√	√	NUM
ajst-24867	118	43	90.7	90.7	NUM
ajst-24867	118	44	87.5	87.5	NUM
ajst-24867	118	45	91.5	91.5	NUM
ajst-24867	118	46	2.921964	2.921964	NUM
ajst-24867	118	47	6.3	6.3	NUM
ajst-24867	119	1	12.2	12.2	NUM
ajst-24867	119	2	b	b	NOUN
ajst-24867	119	3	√	√	ADV
ajst-24867	119	4	90.8	90.8	NUM
ajst-24867	119	5	84.5	84.5	NUM
ajst-24867	119	6	89.4	89.4	NUM
ajst-24867	119	7	3.007013	3.007013	NUM
ajst-24867	119	8	6.3	6.3	NUM
ajst-24867	119	9	8.1	8.1	NUM
ajst-24867	119	10	c	c	NOUN
ajst-24867	119	11	√	√	PROPN
ajst-24867	119	12	91.5	91.5	NUM
ajst-24867	119	13	83.4	83.4	NUM
ajst-24867	119	14	89	89	NUM
ajst-24867	119	15	2.739045	2.739045	NUM
ajst-24867	119	16	5.8	5.8	NUM
ajst-24867	119	17	7.8	7.8	NUM
ajst-24867	119	18	d	d	NOUN
ajst-24867	119	19	√	√	NUM
ajst-24867	119	20	√	√	ADP
ajst-24867	119	21	90.7	90.7	NUM
ajst-24867	119	22	87.9	87.9	NUM
ajst-24867	119	23	92	92	NUM
ajst-24867	119	24	2.921964	2.921964	NUM
ajst-24867	119	25	6.3	6.3	NUM
ajst-24867	119	26	12.2	12.2	NUM
ajst-24867	119	27	e	e	NOUN
ajst-24867	119	28	√	√	ADP
ajst-24867	119	29	√	√	ADP
ajst-24867	119	30	90.7	90.7	NUM
ajst-24867	119	31	87.6	87.6	NUM
ajst-24867	119	32	91.7	91.7	NUM
ajst-24867	119	33	2.648124	2.648124	NUM
ajst-24867	119	34	5.8	5.8	NUM
ajst-24867	119	35	11.9	11.9	NUM
ajst-24867	119	36	ours	ours	PRON
ajst-24867	119	37	√	√	PROPN
ajst-24867	119	38	√	√	PROPN
ajst-24867	120	1	√	√	CCONJ
ajst-24867	120	2	90.4	90.4	NUM
ajst-24867	121	1	88.7	88.7	NUM
ajst-24867	121	2	92.3	92.3	NUM
ajst-24867	121	3	2.648124	2.648124	NUM
ajst-24867	121	4	5.8	5.8	NUM
ajst-24867	121	5	11.9	11.9	NUM
ajst-24867	121	6	table	table	NOUN
ajst-24867	121	7	3	3	NUM
ajst-24867	121	8	.	.	PUNCT
ajst-24867	121	9	comparison	comparison	NOUN
ajst-24867	121	10	experiments	experiment	NOUN
ajst-24867	121	11	of	of	ADP
ajst-24867	121	12	different	different	ADJ
ajst-24867	121	13	models	model	NOUN
ajst-24867	121	14	models	model	VERB
ajst-24867	121	15	p/%	p/%	PROPN
ajst-24867	121	16	r/%	r/%	PROPN
ajst-24867	122	1	map@0.5/	map@0.5/	NOUN
ajst-24867	122	2	%	%	NOUN
ajst-24867	123	1	parameter	parameter	NOUN
ajst-24867	124	1	/106	/106	PUNCT
ajst-24867	125	1	model	model	NOUN
ajst-24867	125	2	size	size	NOUN
ajst-24867	125	3	/	/	SYM
ajst-24867	125	4	mb	mb	NOUN
ajst-24867	125	5	flops	flop	NOUN
ajst-24867	125	6	/	/	SYM
ajst-24867	125	7	g	g	NOUN
ajst-24867	126	1	yolov3	yolov3	PROPN
ajst-24867	127	1	[	[	X
ajst-24867	127	2	15	15	NUM
ajst-24867	127	3	]	]	SYM
ajst-24867	127	4	88.7	88.7	NUM
ajst-24867	127	5	89.7	89.7	NUM
ajst-24867	127	6	90.9	90.9	NUM
ajst-24867	127	7	61.529748	61.529748	NUM
ajst-24867	127	8	123.5	123.5	NUM
ajst-24867	127	9	154.6	154.6	NUM
ajst-24867	127	10	yolov3	yolov3	PROPN
ajst-24867	127	11	-	-	PUNCT
ajst-24867	127	12	tiny	tiny	ADJ
ajst-24867	127	13	87.4	87.4	NUM
ajst-24867	127	14	83	83	NUM
ajst-24867	127	15	86.1	86.1	NUM
ajst-24867	127	16	8.680552	8.680552	NUM
ajst-24867	127	17	17.4	17.4	NUM
ajst-24867	127	18	12.9	12.9	NUM
ajst-24867	127	19	yolov5s	yolov5s	NOUN
ajst-24867	128	1	[	[	X
ajst-24867	128	2	16	16	NUM
ajst-24867	128	3	]	]	SYM
ajst-24867	128	4	91.6	91.6	NUM
ajst-24867	128	5	88.4	88.4	NUM
ajst-24867	128	6	91.6	91.6	NUM
ajst-24867	128	7	7.029004	7.029004	NUM
ajst-24867	128	8	14.5	14.5	NUM
ajst-24867	128	9	15.8	15.8	NUM
ajst-24867	128	10	yolov7	yolov7	NOUN
ajst-24867	128	11	-	-	PUNCT
ajst-24867	128	12	tiny	tiny	ADJ
ajst-24867	128	13	[	[	X
ajst-24867	128	14	8	8	NUM
ajst-24867	128	15	]	]	SYM
ajst-24867	128	16	87.8	87.8	NUM
ajst-24867	128	17	85.1	85.1	NUM
ajst-24867	128	18	89.4	89.4	NUM
ajst-24867	128	19	6.023832	6.023832	NUM
ajst-24867	128	20	12.3	12.3	NUM
ajst-24867	128	21	13.1	13.1	NUM
ajst-24867	128	22	rtdetr	rtdetr	NOUN
ajst-24867	128	23	-	-	PUNCT
ajst-24867	128	24	r18	r18	PROPN
ajst-24867	129	1	[	[	X
ajst-24867	129	2	17	17	NUM
ajst-24867	129	3	]	]	SYM
ajst-24867	129	4	91.4	91.4	NUM
ajst-24867	129	5	89.8	89.8	NUM
ajst-24867	129	6	92.5	92.5	NUM
ajst-24867	129	7	19.880748	19.880748	NUM
ajst-24867	129	8	40.5	40.5	NUM
ajst-24867	129	9	57	57	NUM
ajst-24867	129	10	literature	literature	NOUN
ajst-24867	129	11	[	[	X
ajst-24867	129	12	12	12	NUM
ajst-24867	129	13	]	]	SYM
ajst-24867	129	14	92.3	92.3	NUM
ajst-24867	129	15	90.9	90.9	NUM
ajst-24867	129	16	93.5	93.5	NUM
ajst-24867	129	17	22.900000	22.900000	NUM
ajst-24867	129	18	36.3	36.3	NUM
ajst-24867	129	19	yolov8n	yolov8n	NOUN
ajst-24867	129	20	90.3	90.3	NUM
ajst-24867	129	21	84.3	84.3	NUM
ajst-24867	129	22	88.9	88.9	NUM
ajst-24867	129	23	3.007013	3.007013	NUM
ajst-24867	129	24	6.3	6.3	NUM
ajst-24867	129	25	8.1	8.1	NUM
ajst-24867	129	26	ours	ours	PRON
ajst-24867	129	27	90.4	90.4	NUM
ajst-24867	129	28	88.7	88.7	NUM
ajst-24867	129	29	92.3	92.3	NUM
ajst-24867	129	30	2.648124	2.648124	NUM
ajst-24867	129	31	5.8	5.8	NUM
ajst-24867	129	32	11.9	11.9	NUM
ajst-24867	129	33	firstly	firstly	ADV
ajst-24867	129	34	,	,	PUNCT
ajst-24867	129	35	in	in	ADP
ajst-24867	129	36	terms	term	NOUN
ajst-24867	129	37	of	of	ADP
ajst-24867	129	38	precision	precision	NOUN
ajst-24867	129	39	(	(	PUNCT
ajst-24867	129	40	p%	p%	PROPN
ajst-24867	129	41	)	)	PUNCT
ajst-24867	129	42	and	and	CCONJ
ajst-24867	129	43	recall	recall	NOUN
ajst-24867	129	44	(	(	PUNCT
ajst-24867	129	45	r%	r%	PROPN
ajst-24867	129	46	)	)	PUNCT
ajst-24867	129	47	,	,	PUNCT
ajst-24867	129	48	although	although	SCONJ
ajst-24867	129	49	the	the	DET
ajst-24867	129	50	ours	ours	PRON
ajst-24867	129	51	algorithm	algorithm	NOUN
ajst-24867	129	52	did	do	AUX
ajst-24867	129	53	not	not	PART
ajst-24867	129	54	reach	reach	VERB
ajst-24867	129	55	the	the	DET
ajst-24867	129	56	highest	high	ADJ
ajst-24867	129	57	level	level	NOUN
ajst-24867	129	58	in	in	ADP
ajst-24867	129	59	these	these	DET
ajst-24867	129	60	two	two	NUM
ajst-24867	129	61	indicators	indicator	NOUN
ajst-24867	129	62	,	,	PUNCT
ajst-24867	129	63	it	it	PRON
ajst-24867	129	64	still	still	ADV
ajst-24867	129	65	performed	perform	VERB
ajst-24867	129	66	well	well	ADV
ajst-24867	129	67	,	,	PUNCT
ajst-24867	129	68	at	at	ADP
ajst-24867	129	69	90.4	90.4	NUM
ajst-24867	129	70	%	%	NOUN
ajst-24867	129	71	and	and	CCONJ
ajst-24867	129	72	88.7	88.7	NUM
ajst-24867	129	73	%	%	NOUN
ajst-24867	129	74	,	,	PUNCT
ajst-24867	129	75	respectively	respectively	ADV
ajst-24867	129	76	.	.	PUNCT
ajst-24867	130	1	this	this	PRON
ajst-24867	130	2	indicates	indicate	VERB
ajst-24867	130	3	that	that	SCONJ
ajst-24867	130	4	the	the	DET
ajst-24867	130	5	ours	ours	PRON
ajst-24867	130	6	algorithm	algorithm	NOUN
ajst-24867	130	7	has	have	VERB
ajst-24867	130	8	high	high	ADJ
ajst-24867	130	9	accuracy	accuracy	NOUN
ajst-24867	130	10	and	and	CCONJ
ajst-24867	130	11	recall	recall	NOUN
ajst-24867	130	12	in	in	ADP
ajst-24867	130	13	detecting	detect	VERB
ajst-24867	130	14	targets	target	NOUN
ajst-24867	130	15	,	,	PUNCT
ajst-24867	130	16	which	which	PRON
ajst-24867	130	17	can	can	AUX
ajst-24867	130	18	meet	meet	VERB
ajst-24867	130	19	the	the	DET
ajst-24867	130	20	needs	need	NOUN
ajst-24867	130	21	of	of	ADP
ajst-24867	130	22	most	most	ADJ
ajst-24867	130	23	applications	application	NOUN
ajst-24867	130	24	.	.	PUNCT
ajst-24867	131	1	next	next	ADV
ajst-24867	131	2	,	,	PUNCT
ajst-24867	131	3	we	we	PRON
ajst-24867	131	4	will	will	AUX
ajst-24867	131	5	focus	focus	VERB
ajst-24867	131	6	on	on	ADP
ajst-24867	131	7	the	the	DET
ajst-24867	131	8	average	average	ADJ
ajst-24867	131	9	precision	precision	NOUN
ajst-24867	131	10	mean(map@0.5%)this	mean(map@0.5%)this	PRON
ajst-24867	131	11	is	be	AUX
ajst-24867	131	12	an	an	DET
ajst-24867	131	13	important	important	ADJ
ajst-24867	131	14	indicator	indicator	NOUN
ajst-24867	131	15	for	for	ADP
ajst-24867	131	16	comprehensive	comprehensive	ADJ
ajst-24867	131	17	evaluation	evaluation	NOUN
ajst-24867	131	18	of	of	ADP
ajst-24867	131	19	algorithm	algorithm	NOUN
ajst-24867	131	20	performance	performance	NOUN
ajst-24867	131	21	.	.	PUNCT
ajst-24867	132	1	from	from	ADP
ajst-24867	132	2	the	the	DET
ajst-24867	132	3	table	table	NOUN
ajst-24867	132	4	,	,	PUNCT
ajst-24867	132	5	it	it	PRON
ajst-24867	132	6	can	can	AUX
ajst-24867	132	7	be	be	AUX
ajst-24867	132	8	seen	see	VERB
ajst-24867	132	9	that	that	SCONJ
ajst-24867	132	10	the	the	DET
ajst-24867	132	11	ours	ours	PRON
ajst-24867	132	12	algorithm	algorithm	NOUN
ajst-24867	132	13	map@0.5	map@0.5	X
ajst-24867	132	14	%	%	INTJ
ajst-24867	132	15	it	it	PRON
ajst-24867	132	16	is	be	AUX
ajst-24867	132	17	92.3	92.3	NUM
ajst-24867	132	18	%	%	NOUN
ajst-24867	132	19	,	,	PUNCT
ajst-24867	132	20	second	second	ADJ
ajst-24867	132	21	only	only	ADV
ajst-24867	132	22	to	to	ADP
ajst-24867	132	23	92.5	92.5	NUM
ajst-24867	132	24	%	%	NOUN
ajst-24867	132	25	of	of	ADP
ajst-24867	132	26	rtdetr	rtdetr	NOUN
ajst-24867	132	27	-	-	PUNCT
ajst-24867	132	28	r18	r18	PROPN
ajst-24867	132	29	and	and	CCONJ
ajst-24867	132	30	93.5	93.5	NUM
ajst-24867	132	31	%	%	NOUN
ajst-24867	132	32	of	of	ADP
ajst-24867	132	33	reference	reference	NOUN
ajst-24867	132	34	[	[	X
ajst-24867	132	35	11	11	NUM
ajst-24867	132	36	]	]	PUNCT
ajst-24867	132	37	,	,	PUNCT
ajst-24867	132	38	ranking	rank	VERB
ajst-24867	132	39	third	third	ADV
ajst-24867	132	40	.	.	PUNCT
ajst-24867	133	1	however	however	ADV
ajst-24867	133	2	,	,	PUNCT
ajst-24867	133	3	it	it	PRON
ajst-24867	133	4	is	be	AUX
ajst-24867	133	5	worth	worth	ADJ
ajst-24867	133	6	noting	note	VERB
ajst-24867	133	7	that	that	SCONJ
ajst-24867	133	8	the	the	DET
ajst-24867	133	9	ours	ours	PRON
ajst-24867	133	10	algorithm	algorithm	NOUN
ajst-24867	133	11	has	have	VERB
ajst-24867	133	12	significant	significant	ADJ
ajst-24867	133	13	advantages	advantage	NOUN
ajst-24867	133	14	in	in	ADP
ajst-24867	133	15	terms	term	NOUN
ajst-24867	133	16	of	of	ADP
ajst-24867	133	17	parameter	parameter	NOUN
ajst-24867	133	18	count	count	NOUN
ajst-24867	133	19	and	and	CCONJ
ajst-24867	133	20	model	model	NOUN
ajst-24867	133	21	size	size	NOUN
ajst-24867	133	22	.	.	PUNCT
ajst-24867	134	1	specifically	specifically	ADV
ajst-24867	134	2	,	,	PUNCT
ajst-24867	134	3	the	the	DET
ajst-24867	134	4	parameter	parameter	NOUN
ajst-24867	134	5	count	count	NOUN
ajst-24867	134	6	of	of	ADP
ajst-24867	134	7	our	our	PRON
ajst-24867	134	8	algorithm	algorithm	NOUN
ajst-24867	134	9	is	be	AUX
ajst-24867	134	10	only	only	ADV
ajst-24867	134	11	2648124	2648124	NUM
ajst-24867	134	12	,	,	PUNCT
ajst-24867	134	13	far	far	ADV
ajst-24867	134	14	lower	low	ADJ
ajst-24867	134	15	than	than	ADP
ajst-24867	134	16	most	most	ADJ
ajst-24867	134	17	other	other	ADJ
ajst-24867	134	18	models	model	NOUN
ajst-24867	134	19	such	such	ADJ
ajst-24867	134	20	as	as	ADP
ajst-24867	134	21	yolov3	yolov3	PROPN
ajst-24867	134	22	's	's	PART
ajst-24867	134	23	61529748	61529748	NUM
ajst-24867	134	24	and	and	CCONJ
ajst-24867	134	25	literature	literature	NOUN
ajst-24867	135	1	[	[	X
ajst-24867	135	2	11	11	NUM
ajst-24867	135	3	]	]	SYM
ajst-24867	135	4	's	's	PART
ajst-24867	135	5	22900000	22900000	NUM
ajst-24867	135	6	.	.	PUNCT
ajst-24867	136	1	meanwhile	meanwhile	ADV
ajst-24867	136	2	,	,	PUNCT
ajst-24867	136	3	the	the	DET
ajst-24867	136	4	model	model	NOUN
ajst-24867	136	5	size	size	NOUN
ajst-24867	136	6	of	of	ADP
ajst-24867	136	7	our	our	PRON
ajst-24867	136	8	algorithm	algorithm	NOUN
ajst-24867	136	9	is	be	AUX
ajst-24867	136	10	only	only	ADV
ajst-24867	136	11	5.8	5.8	NUM
ajst-24867	136	12	mb	mb	NOUN
ajst-24867	136	13	,	,	PUNCT
ajst-24867	136	14	which	which	PRON
ajst-24867	136	15	is	be	AUX
ajst-24867	136	16	smaller	small	ADJ
ajst-24867	136	17	than	than	ADP
ajst-24867	136	18	yolov8n	yolov8n	PROPN
ajst-24867	136	19	's	's	PART
ajst-24867	136	20	6.3	6.3	NUM
ajst-24867	136	21	mb	mb	NOUN
ajst-24867	136	22	.	.	PUNCT
ajst-24867	137	1	this	this	PRON
ajst-24867	137	2	means	mean	VERB
ajst-24867	137	3	that	that	SCONJ
ajst-24867	137	4	the	the	DET
ajst-24867	137	5	ours	ours	PRON
ajst-24867	137	6	algorithm	algorithm	NOUN
ajst-24867	137	7	is	be	AUX
ajst-24867	137	8	more	more	ADV
ajst-24867	137	9	efficient	efficient	ADJ
ajst-24867	137	10	in	in	ADP
ajst-24867	137	11	terms	term	NOUN
ajst-24867	137	12	of	of	ADP
ajst-24867	137	13	computing	compute	VERB
ajst-24867	137	14	resources	resource	NOUN
ajst-24867	137	15	and	and	CCONJ
ajst-24867	137	16	storage	storage	NOUN
ajst-24867	137	17	space	space	NOUN
ajst-24867	137	18	,	,	PUNCT
ajst-24867	137	19	and	and	CCONJ
ajst-24867	137	20	is	be	AUX
ajst-24867	137	21	suitable	suitable	ADJ
ajst-24867	137	22	for	for	ADP
ajst-24867	137	23	deployment	deployment	NOUN
ajst-24867	137	24	in	in	ADP
ajst-24867	137	25	resource	resource	NOUN
ajst-24867	137	26	constrained	constrain	VERB
ajst-24867	137	27	environments	environment	NOUN
ajst-24867	137	28	.	.	PUNCT
ajst-24867	138	1	finally	finally	ADV
ajst-24867	138	2	,	,	PUNCT
ajst-24867	138	3	in	in	ADP
ajst-24867	138	4	terms	term	NOUN
ajst-24867	138	5	of	of	ADP
ajst-24867	138	6	computational	computational	ADJ
ajst-24867	138	7	complexity	complexity	NOUN
ajst-24867	138	8	(	(	PUNCT
ajst-24867	138	9	gflops	gflop	NOUN
ajst-24867	138	10	)	)	PUNCT
ajst-24867	138	11	,	,	PUNCT
ajst-24867	138	12	the	the	DET
ajst-24867	138	13	ours	ours	PRON
ajst-24867	138	14	algorithm	algorithm	NOUN
ajst-24867	138	15	has	have	VERB
ajst-24867	138	16	a	a	DET
ajst-24867	138	17	computational	computational	ADJ
ajst-24867	138	18	complexity	complexity	NOUN
ajst-24867	138	19	of	of	ADP
ajst-24867	138	20	11.9	11.9	NUM
ajst-24867	138	21	gflops	gflop	NOUN
ajst-24867	138	22	,	,	PUNCT
ajst-24867	138	23	compared	compare	VERB
ajst-24867	138	24	with	with	ADP
ajst-24867	138	25	some	some	DET
ajst-24867	138	26	larger	large	ADJ
ajst-24867	138	27	models	model	NOUN
ajst-24867	138	28	such	such	ADJ
ajst-24867	138	29	as	as	ADP
ajst-24867	138	30	the	the	DET
ajst-24867	138	31	57gflops	57gflops	PROPN
ajst-24867	138	32	of	of	ADP
ajst-24867	138	33	rtdetr	rtdetr	NOUN
ajst-24867	138	34	-	-	PUNCT
ajst-24867	138	35	r18	r18	PROPN
ajst-24867	138	36	and	and	CCONJ
ajst-24867	138	37	the	the	DET
ajst-24867	138	38	154.6gflops	154.6gflops	NUM
ajst-24867	138	39	of	of	ADP
ajst-24867	138	40	yolov3	yolov3	PROPN
ajst-24867	138	41	,	,	PUNCT
ajst-24867	138	42	our	our	PRON
ajst-24867	138	43	algorithm	algorithm	NOUN
ajst-24867	138	44	also	also	ADV
ajst-24867	138	45	performs	perform	VERB
ajst-24867	138	46	well	well	ADV
ajst-24867	138	47	in	in	ADP
ajst-24867	138	48	computational	computational	ADJ
ajst-24867	138	49	efficiency	efficiency	NOUN
ajst-24867	138	50	,	,	PUNCT
ajst-24867	138	51	only	only	ADV
ajst-24867	138	52	slightly	slightly	ADV
ajst-24867	138	53	lower	low	ADJ
ajst-24867	138	54	than	than	ADP
ajst-24867	138	55	yolov8n	yolov8n	NOUN
ajst-24867	138	56	's	's	PART
ajst-24867	138	57	8.1	8.1	NUM
ajst-24867	138	58	gflops	gflop	NOUN
ajst-24867	138	59	.	.	PUNCT
ajst-24867	139	1	in	in	ADP
ajst-24867	139	2	summary	summary	NOUN
ajst-24867	139	3	,	,	PUNCT
ajst-24867	139	4	the	the	DET
ajst-24867	139	5	ours	ours	PRON
ajst-24867	139	6	algorithm	algorithm	NOUN
ajst-24867	139	7	maintains	maintain	VERB
ajst-24867	139	8	high	high	ADJ
ajst-24867	139	9	accuracy	accuracy	NOUN
ajst-24867	139	10	and	and	CCONJ
ajst-24867	139	11	recall	recall	NOUN
ajst-24867	139	12	while	while	SCONJ
ajst-24867	139	13	having	have	VERB
ajst-24867	139	14	a	a	DET
ajst-24867	139	15	small	small	ADJ
ajst-24867	139	16	number	number	NOUN
ajst-24867	139	17	of	of	ADP
ajst-24867	139	18	parameters	parameter	NOUN
ajst-24867	139	19	and	and	CCONJ
ajst-24867	139	20	model	model	NOUN
ajst-24867	139	21	size	size	NOUN
ajst-24867	139	22	,	,	PUNCT
ajst-24867	139	23	as	as	ADV
ajst-24867	139	24	well	well	ADV
ajst-24867	139	25	as	as	ADP
ajst-24867	139	26	low	low	ADJ
ajst-24867	139	27	computational	computational	ADJ
ajst-24867	139	28	complexity	complexity	NOUN
ajst-24867	139	29	.	.	PUNCT
ajst-24867	140	1	this	this	PRON
ajst-24867	140	2	makes	make	VERB
ajst-24867	140	3	the	the	DET
ajst-24867	140	4	ours	ours	PRON
ajst-24867	140	5	algorithm	algorithm	NOUN
ajst-24867	140	6	have	have	VERB
ajst-24867	140	7	a	a	DET
ajst-24867	140	8	high	high	ADJ
ajst-24867	140	9	performance	performance	NOUN
ajst-24867	140	10	advantage	advantage	NOUN
ajst-24867	140	11	in	in	ADP
ajst-24867	140	12	object	object	NOUN
ajst-24867	140	13	detection	detection	NOUN
ajst-24867	140	14	tasks	task	NOUN
ajst-24867	140	15	,	,	PUNCT
ajst-24867	140	16	especially	especially	ADV
ajst-24867	140	17	in	in	ADP
ajst-24867	140	18	resource	resource	NOUN
ajst-24867	140	19	constrained	constrain	VERB
ajst-24867	140	20	environments	environment	NOUN
ajst-24867	140	21	,	,	PUNCT
ajst-24867	140	22	where	where	SCONJ
ajst-24867	140	23	the	the	DET
ajst-24867	140	24	advantages	advantage	NOUN
ajst-24867	140	25	of	of	ADP
ajst-24867	140	26	the	the	DET
ajst-24867	140	27	ours	ours	PRON
ajst-24867	140	28	algorithm	algorithm	NOUN
ajst-24867	140	29	are	be	AUX
ajst-24867	140	30	more	more	ADV
ajst-24867	140	31	pronounced	pronounced	ADJ
ajst-24867	140	32	.	.	PUNCT
ajst-24867	141	1	therefore	therefore	ADV
ajst-24867	141	2	,	,	PUNCT
ajst-24867	141	3	it	it	PRON
ajst-24867	141	4	can	can	AUX
ajst-24867	141	5	be	be	AUX
ajst-24867	141	6	said	say	VERB
ajst-24867	141	7	that	that	SCONJ
ajst-24867	141	8	the	the	DET
ajst-24867	141	9	ours	ours	PRON
ajst-24867	141	10	algorithm	algorithm	NOUN
ajst-24867	141	11	is	be	AUX
ajst-24867	141	12	an	an	DET
ajst-24867	141	13	efficient	efficient	ADJ
ajst-24867	141	14	and	and	CCONJ
ajst-24867	141	15	lightweight	lightweight	ADJ
ajst-24867	141	16	object	object	NOUN
ajst-24867	141	17	detection	detection	NOUN
ajst-24867	141	18	algorithm	algorithm	NOUN
ajst-24867	141	19	.	.	PUNCT
ajst-24867	142	1	in	in	ADP
ajst-24867	142	2	order	order	NOUN
ajst-24867	142	3	to	to	PART
ajst-24867	142	4	compare	compare	VERB
ajst-24867	142	5	the	the	DET
ajst-24867	142	6	detection	detection	NOUN
ajst-24867	142	7	performance	performance	NOUN
ajst-24867	142	8	of	of	ADP
ajst-24867	142	9	the	the	DET
ajst-24867	142	10	improved	improved	ADJ
ajst-24867	142	11	model	model	NOUN
ajst-24867	142	12	and	and	CCONJ
ajst-24867	142	13	the	the	DET
ajst-24867	142	14	original	original	ADJ
ajst-24867	142	15	model	model	NOUN
ajst-24867	142	16	more	more	ADV
ajst-24867	142	17	intuitively	intuitively	ADV
ajst-24867	142	18	,	,	PUNCT
ajst-24867	142	19	figure	figure	VERB
ajst-24867	142	20	8	8	NUM
ajst-24867	142	21	shows	show	VERB
ajst-24867	142	22	some	some	PRON
ajst-24867	142	23	of	of	ADP
ajst-24867	142	24	the	the	DET
ajst-24867	142	25	detection	detection	NOUN
ajst-24867	142	26	results	result	VERB
ajst-24867	142	27	before	before	ADP
ajst-24867	142	28	and	and	CCONJ
ajst-24867	142	29	after	after	ADP
ajst-24867	142	30	the	the	DET
ajst-24867	142	31	model	model	NOUN
ajst-24867	142	32	improvement	improvement	NOUN
ajst-24867	142	33	.	.	PUNCT
ajst-24867	143	1	in	in	ADP
ajst-24867	143	2	the	the	DET
ajst-24867	143	3	original	original	ADJ
ajst-24867	143	4	model	model	NOUN
ajst-24867	143	5	,	,	PUNCT
ajst-24867	143	6	there	there	PRON
ajst-24867	143	7	were	be	VERB
ajst-24867	143	8	cases	case	NOUN
ajst-24867	143	9	of	of	ADP
ajst-24867	143	10	false	false	ADJ
ajst-24867	143	11	positives	positive	NOUN
ajst-24867	143	12	and	and	CCONJ
ajst-24867	143	13	false	false	ADJ
ajst-24867	143	14	negatives	negative	NOUN
ajst-24867	143	15	(	(	PUNCT
ajst-24867	143	16	marked	mark	VERB
ajst-24867	143	17	in	in	ADP
ajst-24867	143	18	red	red	ADJ
ajst-24867	143	19	)	)	PUNCT
ajst-24867	143	20	,	,	PUNCT
ajst-24867	143	21	and	and	CCONJ
ajst-24867	143	22	the	the	DET
ajst-24867	143	23	confidence	confidence	NOUN
ajst-24867	143	24	level	level	NOUN
ajst-24867	143	25	was	be	AUX
ajst-24867	143	26	lower	low	ADJ
ajst-24867	143	27	than	than	ADP
ajst-24867	143	28	that	that	PRON
ajst-24867	143	29	of	of	ADP
ajst-24867	143	30	the	the	DET
ajst-24867	143	31	improved	improved	ADJ
ajst-24867	143	32	model	model	NOUN
ajst-24867	143	33	.	.	PUNCT
ajst-24867	144	1	however	however	ADV
ajst-24867	144	2	,	,	PUNCT
ajst-24867	144	3	the	the	DET
ajst-24867	144	4	improved	improved	ADJ
ajst-24867	144	5	model	model	NOUN
ajst-24867	144	6	significantly	significantly	ADV
ajst-24867	144	7	improved	improve	VERB
ajst-24867	144	8	this	this	DET
ajst-24867	144	9	problem	problem	NOUN
ajst-24867	144	10	.	.	PUNCT
ajst-24867	145	1	overall	overall	ADV
ajst-24867	145	2	,	,	PUNCT
ajst-24867	145	3	the	the	DET
ajst-24867	145	4	improved	improved	ADJ
ajst-24867	145	5	model	model	NOUN
ajst-24867	145	6	showed	show	VERB
ajst-24867	145	7	higher	high	ADJ
ajst-24867	145	8	confidence	confidence	NOUN
ajst-24867	145	9	and	and	CCONJ
ajst-24867	145	10	lower	low	ADJ
ajst-24867	145	11	false	false	ADJ
ajst-24867	145	12	negatives	negative	NOUN
ajst-24867	145	13	in	in	ADP
ajst-24867	145	14	detecting	detect	VERB
ajst-24867	145	15	ships	ship	NOUN
ajst-24867	145	16	,	,	PUNCT
ajst-24867	145	17	which	which	PRON
ajst-24867	145	18	makes	make	VERB
ajst-24867	145	19	it	it	PRON
ajst-24867	145	20	more	more	ADV
ajst-24867	145	21	effective	effective	ADJ
ajst-24867	145	22	and	and	CCONJ
ajst-24867	145	23	reliable	reliable	ADJ
ajst-24867	145	24	in	in	ADP
ajst-24867	145	25	the	the	DET
ajst-24867	145	26	field	field	NOUN
ajst-24867	145	27	of	of	ADP
ajst-24867	145	28	ship	ship	NOUN
ajst-24867	145	29	detection	detection	NOUN
ajst-24867	145	30	.	.	PUNCT
ajst-24867	146	1	b	b	X
ajst-24867	147	1	e	e	NOUN
ajst-24867	147	2	f	f	NOUN
ajst-24867	147	3	o	o	NOUN
ajst-24867	147	4	r	r	NOUN
ajst-24867	147	5	e	e	NOUN
ajst-24867	148	1	i	i	PRON
ajst-24867	148	2	m	m	VERB
ajst-24867	148	3	p	p	NOUN
ajst-24867	148	4	r	r	NOUN
ajst-24867	148	5	o	o	X
ajst-24867	148	6	v	v	NOUN
ajst-24867	148	7	e	e	X
ajst-24867	148	8	m	m	NOUN
ajst-24867	148	9	e	e	NOUN
ajst-24867	148	10	n	n	NUM
ajst-24867	148	11	t	t	NOUN
ajst-24867	149	1	i	i	PRON
ajst-24867	149	2	m	m	VERB
ajst-24867	150	1	p	p	NOUN
ajst-24867	150	2	r	r	NOUN
ajst-24867	150	3	o	o	X
ajst-24867	150	4	v	v	NOUN
ajst-24867	150	5	e	e	X
ajst-24867	150	6	d	d	NOUN
ajst-24867	150	7	figure	figure	NOUN
ajst-24867	150	8	8	8	NUM
ajst-24867	150	9	.	.	PUNCT
ajst-24867	151	1	comparison	comparison	NOUN
ajst-24867	151	2	of	of	ADP
ajst-24867	151	3	detection	detection	NOUN
ajst-24867	151	4	effects	effect	NOUN
ajst-24867	151	5	before	before	ADV
ajst-24867	151	6	and	and	CCONJ
ajst-24867	151	7	after	after	ADP
ajst-24867	151	8	improvement	improvement	NOUN
ajst-24867	151	9	6	6	NUM
ajst-24867	151	10	.	.	PUNCT
ajst-24867	151	11	summarize	summarize	VERB
ajst-24867	151	12	this	this	DET
ajst-24867	151	13	article	article	NOUN
ajst-24867	151	14	proposes	propose	VERB
ajst-24867	151	15	an	an	DET
ajst-24867	151	16	infrared	infrared	ADJ
ajst-24867	151	17	ship	ship	NOUN
ajst-24867	151	18	detection	detection	NOUN
ajst-24867	151	19	algorithm	algorithm	NOUN
ajst-24867	151	20	based	base	VERB
ajst-24867	151	21	on	on	ADP
ajst-24867	151	22	improved	improved	ADJ
ajst-24867	151	23	yolov8n	yolov8n	NOUN
ajst-24867	151	24	.	.	PUNCT
ajst-24867	152	1	by	by	ADP
ajst-24867	152	2	adding	add	VERB
ajst-24867	152	3	a	a	DET
ajst-24867	152	4	small	small	ADJ
ajst-24867	152	5	target	target	NOUN
ajst-24867	152	6	detection	detection	NOUN
ajst-24867	152	7	layer	layer	NOUN
ajst-24867	152	8	,	,	PUNCT
ajst-24867	152	9	introducing	introduce	VERB
ajst-24867	152	10	the	the	DET
ajst-24867	152	11	focaler	focaler	NOUN
ajst-24867	152	12	mpdiou	mpdiou	NOUN
ajst-24867	152	13	loss	loss	NOUN
ajst-24867	152	14	function	function	NOUN
ajst-24867	152	15	,	,	PUNCT
ajst-24867	152	16	and	and	CCONJ
ajst-24867	152	17	improving	improve	VERB
ajst-24867	152	18	the	the	DET
ajst-24867	152	19	downsampling	downsample	VERB
ajst-24867	152	20	module	module	NOUN
ajst-24867	152	21	,	,	PUNCT
ajst-24867	152	22	the	the	DET
ajst-24867	152	23	model	model	NOUN
ajst-24867	152	24	has	have	AUX
ajst-24867	152	25	significantly	significantly	ADV
ajst-24867	152	26	improved	improve	VERB
ajst-24867	152	27	its	its	PRON
ajst-24867	152	28	detection	detection	NOUN
ajst-24867	152	29	accuracy	accuracy	NOUN
ajst-24867	152	30	when	when	SCONJ
ajst-24867	152	31	dealing	deal	VERB
ajst-24867	152	32	with	with	ADP
ajst-24867	152	33	small	small	ADJ
ajst-24867	152	34	or	or	CCONJ
ajst-24867	152	35	occluded	occluded	ADJ
ajst-24867	152	36	targets	target	NOUN
ajst-24867	152	37	.	.	PUNCT
ajst-24867	153	1	the	the	DET
ajst-24867	153	2	ablation	ablation	NOUN
ajst-24867	153	3	85	85	NUM
ajst-24867	153	4	experiment	experiment	NOUN
ajst-24867	153	5	further	far	ADV
ajst-24867	153	6	validated	validate	VERB
ajst-24867	153	7	the	the	DET
ajst-24867	153	8	effectiveness	effectiveness	NOUN
ajst-24867	153	9	of	of	ADP
ajst-24867	153	10	various	various	ADJ
ajst-24867	153	11	improvement	improvement	NOUN
ajst-24867	153	12	measures	measure	NOUN
ajst-24867	153	13	,	,	PUNCT
ajst-24867	153	14	demonstrating	demonstrate	VERB
ajst-24867	153	15	the	the	DET
ajst-24867	153	16	positive	positive	ADJ
ajst-24867	153	17	role	role	NOUN
ajst-24867	153	18	of	of	ADP
ajst-24867	153	19	these	these	DET
ajst-24867	153	20	methods	method	NOUN
ajst-24867	153	21	in	in	ADP
ajst-24867	153	22	improving	improve	VERB
ajst-24867	153	23	detection	detection	NOUN
ajst-24867	153	24	accuracy	accuracy	NOUN
ajst-24867	153	25	and	and	CCONJ
ajst-24867	153	26	optimizing	optimize	VERB
ajst-24867	153	27	model	model	NOUN
ajst-24867	153	28	complexity	complexity	NOUN
ajst-24867	153	29	.	.	PUNCT
ajst-24867	154	1	compared	compare	VERB
ajst-24867	154	2	with	with	ADP
ajst-24867	154	3	other	other	ADJ
ajst-24867	154	4	mainstream	mainstream	ADJ
ajst-24867	154	5	object	object	NOUN
ajst-24867	154	6	detection	detection	NOUN
ajst-24867	154	7	algorithms	algorithm	NOUN
ajst-24867	154	8	,	,	PUNCT
ajst-24867	154	9	the	the	DET
ajst-24867	154	10	improved	improve	VERB
ajst-24867	154	11	yolov8n	yolov8n	NOUN
ajst-24867	154	12	maintains	maintain	VERB
ajst-24867	154	13	high	high	ADJ
ajst-24867	154	14	accuracy	accuracy	NOUN
ajst-24867	154	15	and	and	CCONJ
ajst-24867	154	16	recall	recall	NOUN
ajst-24867	154	17	while	while	SCONJ
ajst-24867	154	18	having	have	VERB
ajst-24867	154	19	smaller	small	ADJ
ajst-24867	154	20	parameter	parameter	NOUN
ajst-24867	154	21	count	count	NOUN
ajst-24867	154	22	,	,	PUNCT
ajst-24867	154	23	smaller	small	ADJ
ajst-24867	154	24	model	model	NOUN
ajst-24867	154	25	size	size	NOUN
ajst-24867	154	26	,	,	PUNCT
ajst-24867	154	27	and	and	CCONJ
ajst-24867	154	28	lower	low	ADJ
ajst-24867	154	29	computational	computational	ADJ
ajst-24867	154	30	complexity	complexity	NOUN
ajst-24867	154	31	,	,	PUNCT
ajst-24867	154	32	making	make	VERB
ajst-24867	154	33	it	it	PRON
ajst-24867	154	34	more	more	ADV
ajst-24867	154	35	suitable	suitable	ADJ
ajst-24867	154	36	for	for	ADP
ajst-24867	154	37	deployment	deployment	NOUN
ajst-24867	154	38	in	in	ADP
ajst-24867	154	39	resource	resource	NOUN
ajst-24867	154	40	constrained	constrain	VERB
ajst-24867	154	41	environments	environment	NOUN
ajst-24867	154	42	.	.	PUNCT
ajst-24867	155	1	in	in	ADP
ajst-24867	155	2	summary	summary	NOUN
ajst-24867	155	3	,	,	PUNCT
ajst-24867	155	4	the	the	DET
ajst-24867	155	5	improved	improved	ADJ
ajst-24867	155	6	model	model	NOUN
ajst-24867	155	7	has	have	VERB
ajst-24867	155	8	better	well	ADJ
ajst-24867	155	9	performance	performance	NOUN
ajst-24867	155	10	and	and	CCONJ
ajst-24867	155	11	reliability	reliability	NOUN
ajst-24867	155	12	in	in	ADP
ajst-24867	155	13	the	the	DET
ajst-24867	155	14	field	field	NOUN
ajst-24867	155	15	of	of	ADP
ajst-24867	155	16	ship	ship	NOUN
ajst-24867	155	17	detection	detection	NOUN
ajst-24867	155	18	,	,	PUNCT
ajst-24867	155	19	and	and	CCONJ
ajst-24867	155	20	can	can	AUX
ajst-24867	155	21	provide	provide	VERB
ajst-24867	155	22	technical	technical	ADJ
ajst-24867	155	23	support	support	NOUN
ajst-24867	155	24	for	for	ADP
ajst-24867	155	25	practical	practical	ADJ
ajst-24867	155	26	applications	application	NOUN
ajst-24867	155	27	such	such	ADJ
ajst-24867	155	28	as	as	ADP
ajst-24867	155	29	ocean	ocean	NOUN
ajst-24867	155	30	monitoring	monitoring	NOUN
ajst-24867	155	31	and	and	CCONJ
ajst-24867	155	32	maritime	maritime	ADJ
ajst-24867	155	33	search	search	NOUN
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ajst-24867	155	35	rescue	rescue	NOUN
ajst-24867	155	36	.	.	PUNCT
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ajst-24867	156	2	main	main	ADJ
ajst-24867	156	3	followup	followup	NOUN
ajst-24867	156	4	work	work	NOUN
ajst-24867	156	5	will	will	AUX
ajst-24867	156	6	consider	consider	VERB
ajst-24867	156	7	further	far	ADV
ajst-24867	156	8	lightweighting	lightweighte	VERB
ajst-24867	156	9	the	the	DET
ajst-24867	156	10	model	model	NOUN
ajst-24867	156	11	while	while	SCONJ
ajst-24867	156	12	ensuring	ensure	VERB
ajst-24867	156	13	detection	detection	NOUN
ajst-24867	156	14	accuracy	accuracy	NOUN
ajst-24867	156	15	.	.	PUNCT
ajst-24867	157	1	references	reference	NOUN
ajst-24867	157	2	[	[	X
ajst-24867	157	3	1	1	NUM
ajst-24867	157	4	]	]	PUNCT
ajst-24867	157	5	gu	gu	NOUN
ajst-24867	157	6	jing	jing	PROPN
ajst-24867	157	7	research	research	NOUN
ajst-24867	157	8	on	on	ADP
ajst-24867	157	9	infrared	infrared	ADJ
ajst-24867	157	10	ship	ship	NOUN
ajst-24867	157	11	target	target	NOUN
ajst-24867	157	12	detection	detection	NOUN
ajst-24867	157	13	method	method	NOUN
ajst-24867	157	14	based	base	VERB
ajst-24867	157	15	on	on	ADP
ajst-24867	157	16	deep	deep	ADJ
ajst-24867	157	17	learning	learning	NOUN
ajst-24867	158	1	[	[	X
ajst-24867	158	2	d	d	X
ajst-24867	158	3	]	]	X
ajst-24867	158	4	.	.	PUNCT
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ajst-24867	159	2	university	university	PROPN
ajst-24867	159	3	of	of	ADP
ajst-24867	159	4	science	science	NOUN
ajst-24867	159	5	and	and	CCONJ
ajst-24867	159	6	technology	technology	NOUN
ajst-24867	159	7	,	,	PUNCT
ajst-24867	159	8	2023	2023	NUM
ajst-24867	159	9	.	.	PUNCT
ajst-24867	160	1	doi	doi	NOUN
ajst-24867	160	2	:	:	PUNCT
ajst-24867	160	3	10.27171	10.27171	NUM
ajst-24867	160	4	/	/	SYM
ajst-24867	160	5	d.cnki	d.cnki	NOUN
ajst-24867	160	6	.	.	PUNCT
ajst-24867	161	1	ghdcc	ghdcc	NOUN
ajst-24867	161	2	.	.	PUNCT
ajst-24867	162	1	2023	2023	NUM
ajst-24867	162	2	.	.	PUNCT
ajst-24867	163	1	000280	000280	NUM
ajst-24867	163	2	.	.	PUNCT
ajst-24867	164	1	[	[	X
ajst-24867	164	2	2	2	NUM
ajst-24867	164	3	]	]	X
ajst-24867	164	4	jia	jia	PROPN
ajst-24867	164	5	chunrong	chunrong	PROPN
ajst-24867	164	6	,	,	PUNCT
ajst-24867	164	7	yang	yang	PROPN
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ajst-24867	164	10	gao	gao	PROPN
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ajst-24867	164	19	detection	detection	NOUN
ajst-24867	164	20	technology	technology	NOUN
ajst-24867	164	21	for	for	ADP
ajst-24867	164	22	marine	marine	ADJ
ajst-24867	164	23	ship	ship	NOUN
ajst-24867	164	24	targets	target	NOUN
ajst-24867	164	25	[	[	X
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ajst-24867	165	6	11	11	NUM
ajst-24867	166	1	[	[	SYM
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ajst-24867	166	3	-	-	SYM
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ajst-24867	167	2	3	3	X
ajst-24867	167	3	]	]	X
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ajst-24867	168	13	880887	880887	NUM
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ajst-24867	169	17	with	with	ADP
ajst-24867	169	18	small	small	ADJ
ajst-24867	169	19	infrared	infrared	ADJ
ajst-24867	169	20	targets[j	targets[j	NOUN
ajst-24867	169	21	]	]	PUNCT
ajst-24867	169	22	.	.	PUNCT
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ajst-24867	170	3	,	,	PUNCT
ajst-24867	170	4	2022	2022	NUM
ajst-24867	170	5	,	,	PUNCT
ajst-24867	170	6	14(13	14(13	NUM
ajst-24867	170	7	):	):	PUNCT
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ajst-24867	171	1	[	[	X
ajst-24867	171	2	5	5	X
ajst-24867	171	3	]	]	PUNCT
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ajst-24867	171	6	,	,	PUNCT
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ajst-24867	171	9	.	.	PUNCT
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ajst-24867	172	3	infrared	infrared	ADJ
ajst-24867	172	4	image	image	NOUN
ajst-24867	172	5	edge	edge	NOUN
ajst-24867	172	6	detection	detection	NOUN
ajst-24867	172	7	algorithms	algorithm	NOUN
ajst-24867	172	8	[	[	X
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ajst-24867	172	11	.	.	PUNCT
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ajst-24867	173	2	technology	technology	NOUN
ajst-24867	173	3	,	,	PUNCT
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ajst-24867	173	5	,	,	PUNCT
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ajst-24867	173	8	03	03	NUM
ajst-24867	173	9	):	):	PUNCT
ajst-24867	173	10	199	199	NUM
ajst-24867	173	11	-	-	SYM
ajst-24867	173	12	207	207	NUM
ajst-24867	173	13	.	.	PUNCT
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ajst-24867	174	2	6	6	NUM
ajst-24867	174	3	]	]	X
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ajst-24867	174	8	s	s	PROPN
ajst-24867	174	9	,	,	PUNCT
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ajst-24867	174	12	,	,	PUNCT
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ajst-24867	174	14	al	al	PROPN
ajst-24867	174	15	.	.	PUNCT
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ajst-24867	175	2	only	only	ADV
ajst-24867	175	3	look	look	VERB
ajst-24867	175	4	once	once	ADV
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ajst-24867	175	9	-	-	PUNCT
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ajst-24867	175	18	computer	computer	NOUN
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ajst-24867	176	2	:	:	PUNCT
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ajst-24867	176	4	-	-	SYM
ajst-24867	176	5	788	788	NUM
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ajst-24867	177	8	c	c	PROPN
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ajst-24867	177	10	,	,	PUNCT
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ajst-24867	177	12	h	h	PROPN
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ajst-24867	177	14	m.	m.	PROPN
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ajst-24867	177	17	optimal	optimal	ADJ
ajst-24867	177	18	speed	speed	NOUN
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ajst-24867	177	21	of	of	ADP
ajst-24867	177	22	object	object	NOUN
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ajst-24867	177	25	.	.	PUNCT
ajst-24867	178	1	arxiv	arxiv	PROPN
ajst-24867	178	2	preprint	preprint	NOUN
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ajst-24867	178	4	,	,	PUNCT
ajst-24867	178	5	2020	2020	NUM
ajst-24867	178	6	.	.	PUNCT
ajst-24867	179	1	[	[	X
ajst-24867	179	2	8	8	NUM
ajst-24867	179	3	]	]	X
ajst-24867	179	4	wang	wang	PROPN
ajst-24867	179	5	c	c	PROPN
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ajst-24867	179	7	,	,	PUNCT
ajst-24867	179	8	bochkovskiy	bochkovskiy	VERB
ajst-24867	179	9	a	a	PRON
ajst-24867	179	10	,	,	PUNCT
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ajst-24867	179	13	y	y	PROPN
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ajst-24867	179	15	yolov7	yolov7	NOUN
ajst-24867	179	16	:	:	PUNCT
ajst-24867	179	17	trainable	trainable	ADJ
ajst-24867	179	18	bag	bag	NOUN
ajst-24867	179	19	-	-	PUNCT
ajst-24867	179	20	of	of	ADP
ajst-24867	179	21	-	-	PUNCT
ajst-24867	179	22	freebies	freebie	NOUN
ajst-24867	179	23	sets	set	VERB
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ajst-24867	179	25	state	state	NOUN
ajst-24867	179	26	-	-	PUNCT
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ajst-24867	179	28	-	-	PUNCT
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ajst-24867	179	30	-	-	PUNCT
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ajst-24867	179	32	for	for	ADP
ajst-24867	179	33	real	real	ADJ
ajst-24867	179	34	-	-	PUNCT
ajst-24867	179	35	time	time	NOUN
ajst-24867	179	36	object	object	NOUN
ajst-24867	179	37	detectors[c]//proceedings	detectors[c]//proceeding	NOUN
ajst-24867	179	38	of	of	ADP
ajst-24867	179	39	the	the	DET
ajst-24867	179	40	ieee	ieee	NOUN
ajst-24867	179	41	/	/	SYM
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ajst-24867	179	44	on	on	ADP
ajst-24867	179	45	computer	computer	NOUN
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ajst-24867	180	2	:	:	PUNCT
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ajst-24867	180	4	-	-	SYM
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ajst-24867	180	6	.	.	PUNCT
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ajst-24867	181	2	9	9	NUM
ajst-24867	181	3	]	]	SYM
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ajst-24867	181	5	w	w	PROPN
ajst-24867	181	6	,	,	PUNCT
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ajst-24867	181	9	,	,	PUNCT
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ajst-24867	181	17	-	-	PUNCT
ajst-24867	181	18	yolo	yolo	PROPN
ajst-24867	181	19	:	:	PUNCT
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ajst-24867	181	21	guidance	guidance	NOUN
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ajst-24867	181	24	infrared	infrared	ADJ
ajst-24867	181	25	ship	ship	NOUN
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ajst-24867	181	28	]	]	PUNCT
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ajst-24867	183	2	10	10	NUM
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ajst-24867	186	3	,	,	PUNCT
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ajst-24867	186	5	,	,	PUNCT
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ajst-24867	186	10	170	170	NUM
ajst-24867	186	11	-	-	SYM
ajst-24867	186	12	178	178	NUM
ajst-24867	186	13	.	.	PUNCT
ajst-24867	187	1	[	[	X
ajst-24867	187	2	11	11	NUM
ajst-24867	187	3	]	]	X
ajst-24867	187	4	miao	miao	NOUN
ajst-24867	187	5	r	r	PROPN
ajst-24867	187	6	,	,	PUNCT
ajst-24867	187	7	jiang	jiang	PROPN
ajst-24867	187	8	h	h	PROPN
ajst-24867	187	9	,	,	PUNCT
ajst-24867	187	10	tian	tian	PROPN
ajst-24867	187	11	f.	f.	PROPN
ajst-24867	187	12	robust	robust	ADJ
ajst-24867	187	13	ship	ship	NOUN
ajst-24867	187	14	detection	detection	NOUN
ajst-24867	187	15	in	in	ADP
ajst-24867	187	16	infrared	infrared	ADJ
ajst-24867	187	17	images	image	NOUN
ajst-24867	187	18	through	through	ADP
ajst-24867	187	19	multiscale	multiscale	ADJ
ajst-24867	187	20	feature	feature	NOUN
ajst-24867	187	21	extraction	extraction	NOUN
ajst-24867	187	22	and	and	CCONJ
ajst-24867	187	23	lightweight	lightweight	NOUN
ajst-24867	187	24	cnn[j	cnn[j	NOUN
ajst-24867	187	25	]	]	PUNCT
ajst-24867	187	26	.	.	PUNCT
ajst-24867	188	1	sensors	sensor	NOUN
ajst-24867	188	2	,	,	PUNCT
ajst-24867	188	3	2022	2022	NUM
ajst-24867	188	4	,	,	PUNCT
ajst-24867	188	5	22(3	22(3	NUM
ajst-24867	188	6	):	):	PUNCT
ajst-24867	188	7	1226	1226	NUM
ajst-24867	188	8	.	.	PUNCT
ajst-24867	189	1	[	[	X
ajst-24867	189	2	12	12	NUM
ajst-24867	189	3	]	]	X
ajst-24867	189	4	zhang	zhang	PROPN
ajst-24867	189	5	shen	shen	PROPN
ajst-24867	189	6	,	,	PUNCT
ajst-24867	189	7	hu	hu	PROPN
ajst-24867	189	8	lin	lin	PROPN
ajst-24867	189	9	,	,	PUNCT
ajst-24867	189	10	sun	sun	PROPN
ajst-24867	189	11	xiang'e	xiang'e	PROPN
ajst-24867	189	12	,	,	PUNCT
ajst-24867	189	13	et	et	PROPN
ajst-24867	189	14	al	al	PROPN
ajst-24867	189	15	.	.	PROPN
ajst-24867	189	16	infrared	infrared	PROPN
ajst-24867	189	17	ship	ship	NOUN
ajst-24867	189	18	detection	detection	NOUN
ajst-24867	189	19	based	base	VERB
ajst-24867	189	20	on	on	ADP
ajst-24867	189	21	attention	attention	NOUN
ajst-24867	189	22	mechanism	mechanism	NOUN
ajst-24867	189	23	and	and	CCONJ
ajst-24867	189	24	multi	multi	ADJ
ajst-24867	189	25	-	-	ADJ
ajst-24867	189	26	scale	scale	ADJ
ajst-24867	189	27	fusion	fusion	NOUN
ajst-24867	189	28	[	[	X
ajst-24867	189	29	j	j	X
ajst-24867	189	30	]	]	X
ajst-24867	189	31	.	.	PUNCT
ajst-24867	190	1	advances	advance	NOUN
ajst-24867	190	2	in	in	ADP
ajst-24867	190	3	laser	laser	NOUN
ajst-24867	190	4	and	and	CCONJ
ajst-24867	190	5	optoelectronics	optoelectronic	NOUN
ajst-24867	190	6	,	,	PUNCT
ajst-24867	190	7	2023	2023	NUM
ajst-24867	190	8	,	,	PUNCT
ajst-24867	190	9	60	60	NUM
ajst-24867	190	10	(	(	PUNCT
ajst-24867	190	11	22	22	NUM
ajst-24867	190	12	):	):	PUNCT
ajst-24867	190	13	256	256	NUM
ajst-24867	190	14	-	-	SYM
ajst-24867	190	15	262	262	NUM
ajst-24867	190	16	.	.	PUNCT
ajst-24867	191	1	[	[	X
ajst-24867	191	2	13	13	NUM
ajst-24867	191	3	]	]	X
ajst-24867	191	4	zhang	zhang	PROPN
ajst-24867	191	5	h	h	PROPN
ajst-24867	191	6	,	,	PUNCT
ajst-24867	191	7	zhang	zhang	PROPN
ajst-24867	191	8	s.	s.	PROPN
ajst-24867	191	9	focaler	focaler	PROPN
ajst-24867	191	10	-	-	PUNCT
ajst-24867	191	11	iou	iou	NOUN
ajst-24867	191	12	:	:	PUNCT
ajst-24867	191	13	more	more	ADV
ajst-24867	191	14	focused	focused	ADJ
ajst-24867	191	15	intersection	intersection	NOUN
ajst-24867	191	16	over	over	ADP
ajst-24867	191	17	union	union	PROPN
ajst-24867	191	18	loss[j	loss[j	PROPN
ajst-24867	191	19	]	]	PUNCT
ajst-24867	191	20	.	.	PUNCT
ajst-24867	192	1	arxiv	arxiv	PROPN
ajst-24867	192	2	preprint	preprint	PROPN
ajst-24867	192	3	arxiv:2401.10525	arxiv:2401.10525	PROPN
ajst-24867	192	4	,	,	PUNCT
ajst-24867	192	5	2024	2024	NUM
ajst-24867	192	6	.	.	PUNCT
ajst-24867	193	1	[	[	X
ajst-24867	193	2	14	14	NUM
ajst-24867	193	3	]	]	X
ajst-24867	193	4	siliang	siliang	PROPN
ajst-24867	193	5	m	m	PROPN
ajst-24867	193	6	,	,	PUNCT
ajst-24867	193	7	yong	yong	PROPN
ajst-24867	193	8	x.	x.	PROPN
ajst-24867	193	9	mpdiou	mpdiou	PROPN
ajst-24867	193	10	:	:	PUNCT
ajst-24867	193	11	a	a	DET
ajst-24867	193	12	loss	loss	NOUN
ajst-24867	193	13	for	for	ADP
ajst-24867	193	14	efficient	efficient	ADJ
ajst-24867	193	15	and	and	CCONJ
ajst-24867	193	16	accurate	accurate	ADJ
ajst-24867	193	17	bounding	bounding	NOUN
ajst-24867	193	18	box	box	NOUN
ajst-24867	193	19	regression[j	regression[j	PROPN
ajst-24867	193	20	]	]	PUNCT
ajst-24867	193	21	.	.	PUNCT
ajst-24867	194	1	arxiv	arxiv	PROPN
ajst-24867	194	2	preprint	preprint	PROPN
ajst-24867	194	3	arxiv:2307.07662	arxiv:2307.07662	NOUN
ajst-24867	194	4	,	,	PUNCT
ajst-24867	194	5	2023	2023	NUM
ajst-24867	194	6	.	.	PUNCT
ajst-24867	195	1	[	[	X
ajst-24867	195	2	15	15	NUM
ajst-24867	195	3	]	]	X
ajst-24867	195	4	redmon	redmon	PROPN
ajst-24867	195	5	j	j	PROPN
ajst-24867	195	6	,	,	PUNCT
ajst-24867	195	7	farhadi	farhadi	PROPN
ajst-24867	195	8	a.	a.	PROPN
ajst-24867	195	9	yolov3	yolov3	PROPN
ajst-24867	195	10	:	:	PUNCT
ajst-24867	196	1	an	an	DET
ajst-24867	196	2	incremental	incremental	ADJ
ajst-24867	196	3	improvement[j	improvement[j	NOUN
ajst-24867	196	4	]	]	PUNCT
ajst-24867	196	5	.	.	PUNCT
ajst-24867	197	1	arxiv	arxiv	PROPN
ajst-24867	197	2	preprint	preprint	VERB
ajst-24867	197	3	arxiv:1804.02767	arxiv:1804.02767	PROPN
ajst-24867	197	4	,	,	PUNCT
ajst-24867	197	5	2018	2018	NUM
ajst-24867	197	6	.	.	PUNCT
ajst-24867	198	1	[	[	X
ajst-24867	198	2	16	16	NUM
ajst-24867	198	3	]	]	X
ajst-24867	198	4	jocher	jocher	PROPN
ajst-24867	198	5	g	g	PROPN
ajst-24867	198	6	,	,	PUNCT
ajst-24867	198	7	chaurasia	chaurasia	PROPN
ajst-24867	198	8	a	a	X
ajst-24867	198	9	,	,	PUNCT
ajst-24867	198	10	stoken	stoken	VERB
ajst-24867	198	11	a	a	PRON
ajst-24867	198	12	,	,	PUNCT
ajst-24867	198	13	et	et	PROPN
ajst-24867	198	14	al	al	PROPN
ajst-24867	198	15	.	.	PUNCT
ajst-24867	198	16	ultralytics	ultralytics	PROPN
ajst-24867	198	17	/	/	SYM
ajst-24867	198	18	yolov5	yolov5	NOUN
ajst-24867	198	19	:	:	PUNCT
ajst-24867	198	20	v7	v7	VERB
ajst-24867	198	21	.	.	NOUN
ajst-24867	198	22	0	0	NUM
ajst-24867	198	23	-	-	PUNCT
ajst-24867	198	24	yolov5	yolov5	NOUN
ajst-24867	198	25	sota	sota	PROPN
ajst-24867	198	26	realtime	realtime	PROPN
ajst-24867	198	27	instance	instance	NOUN
ajst-24867	198	28	segmentation[j	segmentation[j	PROPN
ajst-24867	198	29	]	]	PUNCT
ajst-24867	198	30	.	.	PUNCT
ajst-24867	199	1	zenodo	zenodo	NOUN
ajst-24867	199	2	,	,	PUNCT
ajst-24867	199	3	2022	2022	NUM
ajst-24867	199	4	.	.	PUNCT
ajst-24867	200	1	[	[	X
ajst-24867	200	2	17	17	NUM
ajst-24867	200	3	]	]	X
ajst-24867	200	4	zhao	zhao	PROPN
ajst-24867	200	5	y	y	PROPN
ajst-24867	200	6	,	,	PUNCT
ajst-24867	200	7	lv	lv	PROPN
ajst-24867	200	8	w	w	PROPN
ajst-24867	200	9	,	,	PUNCT
ajst-24867	200	10	xu	xu	PROPN
ajst-24867	200	11	s	s	PROPN
ajst-24867	200	12	,	,	PUNCT
ajst-24867	200	13	et	et	PROPN
ajst-24867	200	14	al	al	PROPN
ajst-24867	200	15	.	.	PROPN
ajst-24867	200	16	detrs	detrs	PROPN
ajst-24867	200	17	beat	beat	VERB
ajst-24867	200	18	yolos	yolos	PROPN
ajst-24867	200	19	on	on	ADP
ajst-24867	200	20	real	real	ADJ
ajst-24867	200	21	-	-	PUNCT
ajst-24867	200	22	time	time	NOUN
ajst-24867	200	23	object	object	NOUN
ajst-24867	200	24	detection[c]//proceedings	detection[c]//proceeding	NOUN
ajst-24867	200	25	of	of	ADP
ajst-24867	200	26	the	the	DET
ajst-24867	200	27	ieee	ieee	NOUN
ajst-24867	200	28	/	/	SYM
ajst-24867	200	29	cvf	cvf	NOUN
ajst-24867	200	30	conference	conference	NOUN
ajst-24867	200	31	on	on	ADP
ajst-24867	200	32	computer	computer	NOUN
ajst-24867	200	33	vision	vision	NOUN
ajst-24867	200	34	and	and	CCONJ
ajst-24867	200	35	pattern	pattern	NOUN
ajst-24867	200	36	recognition	recognition	NOUN
ajst-24867	200	37	.	.	PUNCT
ajst-24867	201	1	2024	2024	NUM
ajst-24867	201	2	:	:	PUNCT
ajst-24867	201	3	16965	16965	NUM
ajst-24867	201	4	-	-	SYM
ajst-24867	201	5	1697	1697	NUM
ajst-24867	201	6	.	.	PUNCT