id	sid	tid	token	lemma	pos
brj-22962	1	1	peer	peer	NOUN
brj-22962	1	2	-	-	PUNCT
brj-22962	1	3	review	review	NOUN
brj-22962	1	4	article	article	NOUN
brj-22962	1	5	peer	peer	NOUN
brj-22962	1	6	-	-	PUNCT
brj-22962	1	7	reviewed	review	VERB
brj-22962	1	8	article	article	NOUN
brj-22962	1	9	bioresources.com	bioresources.com	X
brj-22962	1	10	wang	wang	PROPN
brj-22962	1	11	et	et	PROPN
brj-22962	1	12	al	al	PROPN
brj-22962	1	13	.	.	PROPN
brj-22962	1	14	(	(	PUNCT
brj-22962	1	15	2023	2023	NUM
brj-22962	1	16	)	)	PUNCT
brj-22962	1	17	.	.	PUNCT
brj-22962	2	1	“	"	PUNCT
brj-22962	2	2	timber	timber	NOUN
brj-22962	2	3	defect	defect	NOUN
brj-22962	2	4	i	i	PROPN
brj-22962	2	5	d	d	PROPN
brj-22962	2	6	algorithms	algorithm	NOUN
brj-22962	2	7	,	,	PUNCT
brj-22962	2	8	”	"	PUNCT
brj-22962	2	9	bioresources	bioresource	NOUN
brj-22962	2	10	18(4	18(4	NUM
brj-22962	2	11	)	)	PUNCT
brj-22962	2	12	,	,	PUNCT
brj-22962	2	13	8444	8444	NUM
brj-22962	2	14	-	-	SYM
brj-22962	2	15	8457	8457	NUM
brj-22962	2	16	.	.	PUNCT
brj-22962	3	1	8444	8444	NUM
brj-22962	4	1	tsw	tsw	PROPN
brj-22962	4	2	-	-	PUNCT
brj-22962	4	3	yolo	yolo	NOUN
brj-22962	4	4	-	-	PUNCT
brj-22962	4	5	v8n	v8n	ADJ
brj-22962	4	6	:	:	PUNCT
brj-22962	4	7	optimization	optimization	NOUN
brj-22962	4	8	of	of	ADP
brj-22962	4	9	detection	detection	NOUN
brj-22962	4	10	algorithms	algorithm	NOUN
brj-22962	4	11	for	for	ADP
brj-22962	4	12	surface	surface	NOUN
brj-22962	4	13	defects	defect	NOUN
brj-22962	4	14	on	on	ADP
brj-22962	4	15	sawn	sawn	NOUN
brj-22962	4	16	timber	timber	NOUN
brj-22962	4	17	mingtao	mingtao	PROPN
brj-22962	4	18	wang	wang	PROPN
brj-22962	4	19	,	,	PUNCT
brj-22962	4	20	a	a	DET
brj-22962	4	21	mingxi	mingxi	PROPN
brj-22962	4	22	li	li	PROPN
brj-22962	4	23	,	,	PUNCT
brj-22962	4	24	b	b	PROPN
brj-22962	4	25	wenyan	wenyan	ADJ
brj-22962	4	26	cui	cui	PROPN
brj-22962	4	27	,	,	PUNCT
brj-22962	4	28	a	a	DET
brj-22962	4	29	xiaoyang	xiaoyang	PROPN
brj-22962	4	30	xiang	xiang	PROPN
brj-22962	4	31	,	,	PUNCT
brj-22962	4	32	a	a	PRON
brj-22962	4	33	and	and	CCONJ
brj-22962	4	34	huaqiong	huaqiong	PROPN
brj-22962	4	35	duo	duo	PROPN
brj-22962	4	36	a	a	PRON
brj-22962	4	37	,	,	PUNCT
brj-22962	4	38	*	*	PUNCT
brj-22962	4	39	the	the	DET
brj-22962	4	40	goal	goal	NOUN
brj-22962	4	41	of	of	ADP
brj-22962	4	42	this	this	DET
brj-22962	4	43	work	work	NOUN
brj-22962	4	44	was	be	AUX
brj-22962	4	45	to	to	PART
brj-22962	4	46	better	well	ADV
brj-22962	4	47	meet	meet	VERB
brj-22962	4	48	the	the	DET
brj-22962	4	49	demand	demand	NOUN
brj-22962	4	50	for	for	ADP
brj-22962	4	51	rapid	rapid	ADJ
brj-22962	4	52	detection	detection	NOUN
brj-22962	4	53	of	of	ADP
brj-22962	4	54	surface	surface	NOUN
brj-22962	4	55	defects	defect	NOUN
brj-22962	4	56	in	in	ADP
brj-22962	4	57	sawn	sawn	NOUN
brj-22962	4	58	timber	timber	NOUN
brj-22962	4	59	in	in	ADP
brj-22962	4	60	forestry	forestry	NOUN
brj-22962	4	61	production	production	NOUN
brj-22962	4	62	.	.	PUNCT
brj-22962	5	1	this	this	DET
brj-22962	5	2	paper	paper	NOUN
brj-22962	5	3	introduces	introduce	VERB
brj-22962	5	4	a	a	DET
brj-22962	5	5	two	two	NUM
brj-22962	5	6	-	-	PUNCT
brj-22962	5	7	way	way	NOUN
brj-22962	5	8	feature	feature	NOUN
brj-22962	5	9	fusion	fusion	NOUN
brj-22962	5	10	network	network	NOUN
brj-22962	5	11	based	base	VERB
brj-22962	5	12	on	on	ADP
brj-22962	5	13	the	the	DET
brj-22962	5	14	yolo	yolo	ADJ
brj-22962	5	15	-	-	PUNCT
brj-22962	5	16	v8	v8	NOUN
brj-22962	5	17	algorithm	algorithm	NOUN
brj-22962	5	18	and	and	CCONJ
brj-22962	5	19	proposes	propose	VERB
brj-22962	5	20	a	a	DET
brj-22962	5	21	feature	feature	NOUN
brj-22962	5	22	fusion	fusion	NOUN
brj-22962	5	23	network	network	NOUN
brj-22962	5	24	model	model	NOUN
brj-22962	5	25	that	that	PRON
brj-22962	5	26	combines	combine	VERB
brj-22962	5	27	the	the	DET
brj-22962	5	28	attention	attention	NOUN
brj-22962	5	29	mechanism	mechanism	NOUN
brj-22962	5	30	and	and	CCONJ
brj-22962	5	31	loss	loss	NOUN
brj-22962	5	32	function	function	NOUN
brj-22962	5	33	optimization	optimization	NOUN
brj-22962	5	34	.	.	PUNCT
brj-22962	6	1	in	in	ADP
brj-22962	6	2	this	this	DET
brj-22962	6	3	way	way	NOUN
brj-22962	6	4	it	it	PRON
brj-22962	6	5	increases	increase	VERB
brj-22962	6	6	the	the	DET
brj-22962	6	7	tiny	tiny	ADJ
brj-22962	6	8	target	target	NOUN
brj-22962	6	9	detection	detection	NOUN
brj-22962	6	10	head	head	NOUN
brj-22962	6	11	in	in	ADP
brj-22962	6	12	order	order	NOUN
brj-22962	6	13	to	to	PART
brj-22962	6	14	more	more	ADV
brj-22962	6	15	effectively	effectively	ADV
brj-22962	6	16	detect	detect	VERB
brj-22962	6	17	small	small	ADJ
brj-22962	6	18	defective	defective	ADJ
brj-22962	6	19	targets	target	NOUN
brj-22962	6	20	in	in	ADP
brj-22962	6	21	the	the	DET
brj-22962	6	22	wood	wood	NOUN
brj-22962	6	23	,	,	PUNCT
brj-22962	6	24	thus	thus	ADV
brj-22962	6	25	realizing	realize	VERB
brj-22962	6	26	the	the	DET
brj-22962	6	27	model	model	NOUN
brj-22962	6	28	's	's	PART
brj-22962	6	29	highefficiency	highefficiency	NOUN
brj-22962	6	30	and	and	CCONJ
brj-22962	6	31	low	low	ADJ
brj-22962	6	32	-	-	PUNCT
brj-22962	6	33	consumption	consumption	NOUN
brj-22962	6	34	functional	functional	ADJ
brj-22962	6	35	design	design	NOUN
brj-22962	6	36	.	.	PUNCT
brj-22962	7	1	the	the	DET
brj-22962	7	2	results	result	NOUN
brj-22962	7	3	show	show	VERB
brj-22962	7	4	that	that	SCONJ
brj-22962	7	5	the	the	DET
brj-22962	7	6	improved	improved	ADJ
brj-22962	7	7	tsw	tsw	PROPN
brj-22962	7	8	-	-	PUNCT
brj-22962	7	9	yolo	yolo	ADJ
brj-22962	7	10	-	-	PUNCT
brj-22962	7	11	v8n	v8n	PROPN
brj-22962	7	12	model	model	NOUN
brj-22962	7	13	realized	realize	VERB
brj-22962	7	14	the	the	DET
brj-22962	7	15	identification	identification	NOUN
brj-22962	7	16	of	of	ADP
brj-22962	7	17	eight	eight	NUM
brj-22962	7	18	kinds	kind	NOUN
brj-22962	7	19	of	of	ADP
brj-22962	7	20	defects	defect	NOUN
brj-22962	7	21	in	in	ADP
brj-22962	7	22	sawn	sawn	ADJ
brj-22962	7	23	timber	timber	NOUN
brj-22962	7	24	with	with	ADP
brj-22962	7	25	a	a	DET
brj-22962	7	26	high	high	ADJ
brj-22962	7	27	efficiency	efficiency	NOUN
brj-22962	7	28	of	of	ADP
brj-22962	7	29	91.10	91.10	NUM
brj-22962	7	30	%	%	NOUN
brj-22962	7	31	map50	map50	NOUN
brj-22962	7	32	and	and	CCONJ
brj-22962	7	33	an	an	DET
brj-22962	7	34	average	average	ADJ
brj-22962	7	35	detection	detection	NOUN
brj-22962	7	36	6	6	NUM
brj-22962	7	37	ms	ms	NOUN
brj-22962	7	38	,	,	PUNCT
brj-22962	7	39	which	which	PRON
brj-22962	7	40	is	be	AUX
brj-22962	7	41	5.1	5.1	NUM
brj-22962	7	42	%	%	NOUN
brj-22962	7	43	higher	high	ADJ
brj-22962	7	44	than	than	ADP
brj-22962	7	45	the	the	DET
brj-22962	7	46	original	original	ADJ
brj-22962	7	47	model	model	NOUN
brj-22962	7	48	’s	’s	PART
brj-22962	7	49	map50	map50	PROPN
brj-22962	7	50	and	and	CCONJ
brj-22962	7	51	1	1	NUM
brj-22962	7	52	ms	ms	NOUN
brj-22962	7	53	shorter	short	ADJ
brj-22962	7	54	than	than	ADP
brj-22962	7	55	the	the	DET
brj-22962	7	56	original	original	ADJ
brj-22962	7	57	model	model	NOUN
brj-22962	7	58	’s	’s	PART
brj-22962	7	59	average	average	ADJ
brj-22962	7	60	detection	detection	NOUN
brj-22962	7	61	time	time	NOUN
brj-22962	7	62	.	.	PUNCT
brj-22962	8	1	the	the	DET
brj-22962	8	2	comparison	comparison	NOUN
brj-22962	8	3	of	of	ADP
brj-22962	8	4	the	the	DET
brj-22962	8	5	original	original	ADJ
brj-22962	8	6	model	model	NOUN
brj-22962	8	7	and	and	CCONJ
brj-22962	8	8	its	its	PRON
brj-22962	8	9	mainstream	mainstream	NOUN
brj-22962	8	10	algorithms	algorithm	NOUN
brj-22962	8	11	shows	show	VERB
brj-22962	8	12	that	that	SCONJ
brj-22962	8	13	the	the	DET
brj-22962	8	14	model	model	NOUN
brj-22962	8	15	of	of	ADP
brj-22962	8	16	this	this	DET
brj-22962	8	17	paper	paper	NOUN
brj-22962	8	18	had	have	VERB
brj-22962	8	19	better	well	ADJ
brj-22962	8	20	performance	performance	NOUN
brj-22962	8	21	and	and	CCONJ
brj-22962	8	22	better	well	ADJ
brj-22962	8	23	detection	detection	NOUN
brj-22962	8	24	capability	capability	NOUN
brj-22962	8	25	.	.	PUNCT
brj-22962	9	1	thus	thus	ADV
brj-22962	9	2	,	,	PUNCT
brj-22962	9	3	the	the	DET
brj-22962	9	4	improved	improved	ADJ
brj-22962	9	5	model	model	NOUN
brj-22962	9	6	achieved	achieve	VERB
brj-22962	9	7	better	well	ADJ
brj-22962	9	8	overall	overall	ADJ
brj-22962	9	9	performance	performance	NOUN
brj-22962	9	10	and	and	CCONJ
brj-22962	9	11	stronger	strong	ADJ
brj-22962	9	12	detection	detection	NOUN
brj-22962	9	13	ability	ability	NOUN
brj-22962	9	14	,	,	PUNCT
brj-22962	9	15	which	which	PRON
brj-22962	9	16	provides	provide	VERB
brj-22962	9	17	a	a	DET
brj-22962	9	18	new	new	ADJ
brj-22962	9	19	idea	idea	NOUN
brj-22962	9	20	for	for	ADP
brj-22962	9	21	the	the	DET
brj-22962	9	22	development	development	NOUN
brj-22962	9	23	of	of	ADP
brj-22962	9	24	detection	detection	NOUN
brj-22962	9	25	technology	technology	NOUN
brj-22962	9	26	in	in	ADP
brj-22962	9	27	the	the	DET
brj-22962	9	28	forestry	forestry	NOUN
brj-22962	9	29	industry	industry	NOUN
brj-22962	9	30	.	.	PUNCT
brj-22962	10	1	doi	doi	NOUN
brj-22962	10	2	:	:	PUNCT
brj-22962	10	3	10.15376	10.15376	NUM
brj-22962	10	4	/	/	SYM
brj-22962	10	5	biores.18.4.8444	biores.18.4.8444	ADJ
brj-22962	10	6	-	-	PUNCT
brj-22962	10	7	8457	8457	NUM
brj-22962	10	8	keywords	keyword	NOUN
brj-22962	10	9	:	:	PUNCT
brj-22962	10	10	deep	deep	ADJ
brj-22962	10	11	learning	learning	NOUN
brj-22962	10	12	;	;	PUNCT
brj-22962	10	13	target	target	NOUN
brj-22962	10	14	detection	detection	NOUN
brj-22962	10	15	;	;	PUNCT
brj-22962	10	16	surface	surface	NOUN
brj-22962	10	17	defects	defect	NOUN
brj-22962	10	18	of	of	ADP
brj-22962	10	19	sawn	sawn	NOUN
brj-22962	10	20	timber	timber	NOUN
brj-22962	10	21	;	;	PUNCT
brj-22962	10	22	yolo	yolo	PROPN
brj-22962	10	23	-	-	PUNCT
brj-22962	10	24	v8	v8	PROPN
brj-22962	10	25	;	;	PUNCT
brj-22962	10	26	attention	attention	NOUN
brj-22962	10	27	mechanism	mechanism	NOUN
brj-22962	10	28	;	;	PUNCT
brj-22962	10	29	loss	loss	NOUN
brj-22962	10	30	function	function	NOUN
brj-22962	10	31	;	;	PUNCT
brj-22962	10	32	feature	feature	NOUN
brj-22962	10	33	fusion	fusion	NOUN
brj-22962	10	34	contact	contact	NOUN
brj-22962	10	35	information	information	NOUN
brj-22962	10	36	:	:	PUNCT
brj-22962	10	37	a	a	X
brj-22962	10	38	:	:	PUNCT
brj-22962	10	39	college	college	NOUN
brj-22962	10	40	of	of	ADP
brj-22962	10	41	materials	material	NOUN
brj-22962	10	42	science	science	NOUN
brj-22962	10	43	and	and	CCONJ
brj-22962	10	44	art	art	NOUN
brj-22962	10	45	design	design	NOUN
brj-22962	10	46	,	,	PUNCT
brj-22962	10	47	inner	inner	PROPN
brj-22962	10	48	mongolia	mongolia	PROPN
brj-22962	10	49	agricultural	agricultural	PROPN
brj-22962	10	50	university	university	PROPN
brj-22962	10	51	,	,	PUNCT
brj-22962	10	52	hohhot	hohhot	ADJ
brj-22962	10	53	010018	010018	NUM
brj-22962	10	54	,	,	PUNCT
brj-22962	10	55	p.r	p.r	PROPN
brj-22962	10	56	.	.	PROPN
brj-22962	10	57	china	china	PROPN
brj-22962	10	58	;	;	PUNCT
brj-22962	10	59	b	b	X
brj-22962	10	60	:	:	PUNCT
brj-22962	10	61	zhengzhou	zhengzhou	PROPN
brj-22962	10	62	research	research	NOUN
brj-22962	10	63	base	base	NOUN
brj-22962	10	64	,	,	PUNCT
brj-22962	10	65	state	state	NOUN
brj-22962	10	66	key	key	ADJ
brj-22962	10	67	laboratory	laboratory	NOUN
brj-22962	10	68	of	of	ADP
brj-22962	10	69	cotton	cotton	NOUN
brj-22962	10	70	biology	biology	NOUN
brj-22962	10	71	,	,	PUNCT
brj-22962	10	72	school	school	NOUN
brj-22962	10	73	of	of	ADP
brj-22962	10	74	agricultural	agricultural	ADJ
brj-22962	10	75	sciences	science	NOUN
brj-22962	10	76	,	,	PUNCT
brj-22962	10	77	zhengzhou	zhengzhou	PROPN
brj-22962	10	78	university	university	PROPN
brj-22962	10	79	,	,	PUNCT
brj-22962	10	80	zhengzhou	zhengzhou	PROPN
brj-22962	10	81	450001	450001	NUM
brj-22962	10	82	,	,	PUNCT
brj-22962	10	83	henan	henan	PROPN
brj-22962	10	84	,	,	PUNCT
brj-22962	10	85	china	china	PROPN
brj-22962	10	86	;	;	PUNCT
brj-22962	10	87	*	*	PUNCT
brj-22962	10	88	corresponding	correspond	VERB
brj-22962	10	89	author	author	NOUN
brj-22962	10	90	:	:	PUNCT
brj-22962	10	91	duohuaqiong@163.com	duohuaqiong@163.com	X
brj-22962	10	92	introduction	introduction	NOUN
brj-22962	10	93	in	in	ADP
brj-22962	10	94	the	the	DET
brj-22962	10	95	era	era	NOUN
brj-22962	10	96	of	of	ADP
brj-22962	10	97	artificial	artificial	ADJ
brj-22962	10	98	intelligence	intelligence	NOUN
brj-22962	10	99	,	,	PUNCT
brj-22962	10	100	the	the	DET
brj-22962	10	101	wood	wood	NOUN
brj-22962	10	102	industry	industry	NOUN
brj-22962	10	103	is	be	AUX
brj-22962	10	104	undergoing	undergo	VERB
brj-22962	10	105	a	a	DET
brj-22962	10	106	profound	profound	ADJ
brj-22962	10	107	transformation	transformation	NOUN
brj-22962	10	108	as	as	SCONJ
brj-22962	10	109	it	it	PRON
brj-22962	10	110	embraces	embrace	VERB
brj-22962	10	111	a	a	DET
brj-22962	10	112	multitude	multitude	NOUN
brj-22962	10	113	of	of	ADP
brj-22962	10	114	cutting	cut	VERB
brj-22962	10	115	-	-	PUNCT
brj-22962	10	116	edge	edge	NOUN
brj-22962	10	117	technologies	technology	NOUN
brj-22962	10	118	,	,	PUNCT
brj-22962	10	119	striving	strive	VERB
brj-22962	10	120	to	to	PART
brj-22962	10	121	integrate	integrate	VERB
brj-22962	10	122	with	with	ADP
brj-22962	10	123	emerging	emerge	VERB
brj-22962	10	124	industries	industry	NOUN
brj-22962	10	125	and	and	CCONJ
brj-22962	10	126	achieve	achieve	VERB
brj-22962	10	127	a	a	DET
brj-22962	10	128	high	high	ADJ
brj-22962	10	129	level	level	NOUN
brj-22962	10	130	of	of	ADP
brj-22962	10	131	automation	automation	NOUN
brj-22962	10	132	and	and	CCONJ
brj-22962	10	133	intelligence	intelligence	NOUN
brj-22962	10	134	.	.	PUNCT
brj-22962	11	1	one	one	NUM
brj-22962	11	2	particularly	particularly	ADV
brj-22962	11	3	active	active	ADJ
brj-22962	11	4	area	area	NOUN
brj-22962	11	5	of	of	ADP
brj-22962	11	6	technological	technological	ADJ
brj-22962	11	7	exploration	exploration	NOUN
brj-22962	11	8	is	be	AUX
brj-22962	11	9	the	the	DET
brj-22962	11	10	application	application	NOUN
brj-22962	11	11	of	of	ADP
brj-22962	11	12	deep	deep	ADJ
brj-22962	11	13	learning	learning	NOUN
brj-22962	11	14	techniques	technique	NOUN
brj-22962	11	15	to	to	PART
brj-22962	11	16	detect	detect	VERB
brj-22962	11	17	surface	surface	NOUN
brj-22962	11	18	defects	defect	NOUN
brj-22962	11	19	in	in	ADP
brj-22962	11	20	wood	wood	NOUN
brj-22962	11	21	.	.	PUNCT
brj-22962	12	1	traditional	traditional	ADJ
brj-22962	12	2	manual	manual	ADJ
brj-22962	12	3	inspection	inspection	NOUN
brj-22962	12	4	methods	method	NOUN
brj-22962	12	5	for	for	ADP
brj-22962	12	6	wood	wood	NOUN
brj-22962	12	7	surface	surface	NOUN
brj-22962	12	8	defects	defect	NOUN
brj-22962	12	9	are	be	AUX
brj-22962	12	10	marred	mar	VERB
brj-22962	12	11	by	by	ADP
brj-22962	12	12	their	their	PRON
brj-22962	12	13	inherent	inherent	ADJ
brj-22962	12	14	inefficiencies	inefficiency	NOUN
brj-22962	12	15	.	.	PUNCT
brj-22962	13	1	they	they	PRON
brj-22962	13	2	are	be	AUX
brj-22962	13	3	time	time	NOUN
brj-22962	13	4	-	-	PUNCT
brj-22962	13	5	consuming	consume	VERB
brj-22962	13	6	,	,	PUNCT
brj-22962	13	7	demand	demand	VERB
brj-22962	13	8	a	a	DET
brj-22962	13	9	substantial	substantial	ADJ
brj-22962	13	10	labor	labor	NOUN
brj-22962	13	11	force	force	NOUN
brj-22962	13	12	,	,	PUNCT
brj-22962	13	13	and	and	CCONJ
brj-22962	13	14	are	be	AUX
brj-22962	13	15	generally	generally	ADV
brj-22962	13	16	inefficient	inefficient	ADJ
brj-22962	13	17	(	(	PUNCT
brj-22962	13	18	qayyum	qayyum	INTJ
brj-22962	13	19	et	et	PROPN
brj-22962	13	20	al	al	PROPN
brj-22962	13	21	.	.	PROPN
brj-22962	13	22	2016	2016	NUM
brj-22962	13	23	)	)	PUNCT
brj-22962	13	24	.	.	PUNCT
brj-22962	14	1	however	however	ADV
brj-22962	14	2	,	,	PUNCT
brj-22962	14	3	machine	machine	NOUN
brj-22962	14	4	-	-	PUNCT
brj-22962	14	5	based	base	VERB
brj-22962	14	6	wood	wood	NOUN
brj-22962	14	7	defect	defect	NOUN
brj-22962	14	8	detection	detection	NOUN
brj-22962	14	9	methods	method	NOUN
brj-22962	14	10	,	,	PUNCT
brj-22962	14	11	although	although	SCONJ
brj-22962	14	12	effective	effective	ADJ
brj-22962	14	13	,	,	PUNCT
brj-22962	14	14	bring	bring	VERB
brj-22962	14	15	their	their	PRON
brj-22962	14	16	own	own	ADJ
brj-22962	14	17	set	set	NOUN
brj-22962	14	18	of	of	ADP
brj-22962	14	19	challenges	challenge	NOUN
brj-22962	14	20	,	,	PUNCT
brj-22962	14	21	including	include	VERB
brj-22962	14	22	safety	safety	NOUN
brj-22962	14	23	hazards	hazard	NOUN
brj-22962	14	24	,	,	PUNCT
brj-22962	14	25	high	high	ADJ
brj-22962	14	26	costs	cost	NOUN
brj-22962	14	27	,	,	PUNCT
brj-22962	14	28	and	and	CCONJ
brj-22962	14	29	intricate	intricate	ADJ
brj-22962	14	30	operational	operational	ADJ
brj-22962	14	31	procedures	procedure	NOUN
brj-22962	14	32	.	.	PUNCT
brj-22962	15	1	in	in	ADP
brj-22962	15	2	stark	stark	ADJ
brj-22962	15	3	contrast	contrast	NOUN
brj-22962	15	4	,	,	PUNCT
brj-22962	15	5	the	the	DET
brj-22962	15	6	convergence	convergence	NOUN
brj-22962	15	7	of	of	ADP
brj-22962	15	8	computer	computer	NOUN
brj-22962	15	9	-	-	PUNCT
brj-22962	15	10	based	base	VERB
brj-22962	15	11	image	image	NOUN
brj-22962	15	12	processing	processing	NOUN
brj-22962	15	13	techniques	technique	NOUN
brj-22962	15	14	and	and	CCONJ
brj-22962	15	15	deep	deep	ADJ
brj-22962	15	16	learning	learning	NOUN
brj-22962	15	17	technology	technology	NOUN
brj-22962	15	18	,	,	PUNCT
brj-22962	15	19	operating	operate	VERB
brj-22962	15	20	at	at	ADP
brj-22962	15	21	the	the	DET
brj-22962	15	22	nanoscale	nanoscale	NOUN
brj-22962	15	23	level	level	NOUN
brj-22962	15	24	and	and	CCONJ
brj-22962	15	25	harnessed	harness	VERB
brj-22962	15	26	by	by	ADP
brj-22962	15	27	highperformance	highperformance	NOUN
brj-22962	15	28	processing	processing	NOUN
brj-22962	15	29	units	unit	NOUN
brj-22962	15	30	such	such	ADJ
brj-22962	15	31	as	as	ADP
brj-22962	15	32	gpus	gpu	NOUN
brj-22962	15	33	,	,	PUNCT
brj-22962	15	34	presents	present	VERB
brj-22962	15	35	a	a	DET
brj-22962	15	36	compelling	compelling	ADJ
brj-22962	15	37	solution	solution	NOUN
brj-22962	15	38	.	.	PUNCT
brj-22962	16	1	this	this	DET
brj-22962	16	2	approach	approach	NOUN
brj-22962	16	3	boasts	boast	VERB
brj-22962	16	4	many	many	ADJ
brj-22962	16	5	advantages	advantage	NOUN
brj-22962	16	6	,	,	PUNCT
brj-22962	16	7	including	include	VERB
brj-22962	16	8	rapid	rapid	ADJ
brj-22962	16	9	processing	processing	NOUN
brj-22962	16	10	speeds	speed	NOUN
brj-22962	16	11	,	,	PUNCT
brj-22962	16	12	cost	cost	NOUN
brj-22962	16	13	-	-	PUNCT
brj-22962	16	14	effectiveness	effectiveness	NOUN
brj-22962	16	15	,	,	PUNCT
brj-22962	16	16	and	and	CCONJ
brj-22962	16	17	ease	ease	NOUN
brj-22962	16	18	of	of	ADP
brj-22962	16	19	operation	operation	NOUN
brj-22962	16	20	.	.	PUNCT
brj-22962	17	1	these	these	DET
brj-22962	17	2	qualities	quality	NOUN
brj-22962	17	3	make	make	VERB
brj-22962	17	4	it	it	PRON
brj-22962	17	5	exceptionally	exceptionally	ADV
brj-22962	17	6	adept	adept	ADJ
brj-22962	17	7	at	at	ADP
brj-22962	17	8	identifying	identify	VERB
brj-22962	17	9	and	and	CCONJ
brj-22962	17	10	classifying	classify	VERB
brj-22962	17	11	faults	fault	NOUN
brj-22962	17	12	peer	peer	NOUN
brj-22962	17	13	-	-	PUNCT
brj-22962	17	14	reviewed	review	VERB
brj-22962	17	15	article	article	NOUN
brj-22962	17	16	bioresources.com	bioresources.com	X
brj-22962	17	17	wang	wang	PROPN
brj-22962	17	18	et	et	PROPN
brj-22962	17	19	al	al	PROPN
brj-22962	17	20	.	.	PROPN
brj-22962	18	1	(	(	PUNCT
brj-22962	18	2	2023	2023	NUM
brj-22962	18	3	)	)	PUNCT
brj-22962	18	4	.	.	PUNCT
brj-22962	19	1	“	"	PUNCT
brj-22962	19	2	timber	timber	NOUN
brj-22962	19	3	defect	defect	NOUN
brj-22962	19	4	i	i	PROPN
brj-22962	19	5	d	d	PROPN
brj-22962	19	6	algorithms	algorithm	NOUN
brj-22962	19	7	,	,	PUNCT
brj-22962	19	8	”	"	PUNCT
brj-22962	19	9	bioresources	bioresource	NOUN
brj-22962	19	10	18(4	18(4	NUM
brj-22962	19	11	)	)	PUNCT
brj-22962	19	12	,	,	PUNCT
brj-22962	19	13	8444	8444	NUM
brj-22962	19	14	-	-	SYM
brj-22962	19	15	8457	8457	NUM
brj-22962	19	16	.	.	PUNCT
brj-22962	19	17	8445	8445	NUM
brj-22962	19	18	in	in	ADP
brj-22962	19	19	wood	wood	NOUN
brj-22962	19	20	.	.	PUNCT
brj-22962	20	1	this	this	DET
brj-22962	20	2	fusion	fusion	NOUN
brj-22962	20	3	of	of	ADP
brj-22962	20	4	technologies	technology	NOUN
brj-22962	20	5	offers	offer	VERB
brj-22962	20	6	a	a	DET
brj-22962	20	7	promising	promising	ADJ
brj-22962	20	8	pathway	pathway	NOUN
brj-22962	20	9	to	to	ADP
brj-22962	20	10	revolutionizing	revolutionize	VERB
brj-22962	20	11	wood	wood	NOUN
brj-22962	20	12	defect	defect	NOUN
brj-22962	20	13	detection	detection	NOUN
brj-22962	20	14	with	with	ADP
brj-22962	20	15	efficiency	efficiency	NOUN
brj-22962	20	16	and	and	CCONJ
brj-22962	20	17	precision	precision	NOUN
brj-22962	20	18	(	(	PUNCT
brj-22962	20	19	yang	yang	PROPN
brj-22962	20	20	et	et	PROPN
brj-22962	20	21	al	al	PROPN
brj-22962	20	22	.	.	PROPN
brj-22962	20	23	2018	2018	NUM
brj-22962	20	24	)	)	PUNCT
brj-22962	20	25	.	.	PUNCT
brj-22962	21	1	intelligent	intelligent	ADJ
brj-22962	21	2	detection	detection	NOUN
brj-22962	21	3	of	of	ADP
brj-22962	21	4	wood	wood	NOUN
brj-22962	21	5	defects	defect	NOUN
brj-22962	21	6	can	can	AUX
brj-22962	21	7	be	be	AUX
brj-22962	21	8	categorized	categorize	VERB
brj-22962	21	9	into	into	ADP
brj-22962	21	10	two	two	NUM
brj-22962	21	11	types	type	NOUN
brj-22962	21	12	,	,	PUNCT
brj-22962	21	13	based	base	VERB
brj-22962	21	14	on	on	ADP
brj-22962	21	15	different	different	ADJ
brj-22962	21	16	prediction	prediction	NOUN
brj-22962	21	17	methods	method	NOUN
brj-22962	21	18	and	and	CCONJ
brj-22962	21	19	processing	processing	NOUN
brj-22962	21	20	procedures	procedure	NOUN
brj-22962	21	21	.	.	PUNCT
brj-22962	22	1	the	the	DET
brj-22962	22	2	first	first	ADJ
brj-22962	22	3	type	type	NOUN
brj-22962	22	4	is	be	AUX
brj-22962	22	5	single	single	ADJ
brj-22962	22	6	-	-	PUNCT
brj-22962	22	7	stage	stage	NOUN
brj-22962	22	8	wood	wood	NOUN
brj-22962	22	9	defect	defect	NOUN
brj-22962	22	10	detection	detection	NOUN
brj-22962	22	11	,	,	PUNCT
brj-22962	22	12	which	which	PRON
brj-22962	22	13	is	be	AUX
brj-22962	22	14	also	also	ADV
brj-22962	22	15	known	know	VERB
brj-22962	22	16	as	as	ADP
brj-22962	22	17	a	a	DET
brj-22962	22	18	target	target	NOUN
brj-22962	22	19	detection	detection	NOUN
brj-22962	22	20	algorithm	algorithm	NOUN
brj-22962	22	21	based	base	VERB
brj-22962	22	22	on	on	ADP
brj-22962	22	23	regression	regression	NOUN
brj-22962	22	24	analysis	analysis	NOUN
brj-22962	22	25	.	.	PUNCT
brj-22962	23	1	this	this	DET
brj-22962	23	2	algorithm	algorithm	NOUN
brj-22962	23	3	only	only	ADV
brj-22962	23	4	requires	require	VERB
brj-22962	23	5	one	one	NUM
brj-22962	23	6	feature	feature	NOUN
brj-22962	23	7	extraction	extraction	NOUN
brj-22962	23	8	to	to	PART
brj-22962	23	9	perform	perform	VERB
brj-22962	23	10	regression	regression	NOUN
brj-22962	23	11	analysis	analysis	NOUN
brj-22962	23	12	on	on	ADP
brj-22962	23	13	the	the	DET
brj-22962	23	14	target	target	NOUN
brj-22962	23	15	location	location	NOUN
brj-22962	23	16	and	and	CCONJ
brj-22962	23	17	category	category	NOUN
brj-22962	23	18	information	information	NOUN
brj-22962	23	19	.	.	PUNCT
brj-22962	24	1	the	the	DET
brj-22962	24	2	detection	detection	NOUN
brj-22962	24	3	results	result	NOUN
brj-22962	24	4	are	be	AUX
brj-22962	24	5	then	then	ADV
brj-22962	24	6	output	output	NOUN
brj-22962	24	7	using	use	VERB
brj-22962	24	8	a	a	DET
brj-22962	24	9	neural	neural	ADJ
brj-22962	24	10	network	network	NOUN
brj-22962	24	11	model	model	NOUN
brj-22962	24	12	(	(	PUNCT
brj-22962	24	13	zhu	zhu	X
brj-22962	24	14	et	et	PROPN
brj-22962	24	15	al	al	PROPN
brj-22962	24	16	.	.	PROPN
brj-22962	24	17	2023	2023	NUM
brj-22962	24	18	)	)	PUNCT
brj-22962	24	19	.	.	PUNCT
brj-22962	25	1	common	common	ADJ
brj-22962	25	2	single	single	ADJ
brj-22962	25	3	-	-	PUNCT
brj-22962	25	4	stage	stage	NOUN
brj-22962	25	5	algorithms	algorithm	NOUN
brj-22962	25	6	include	include	VERB
brj-22962	25	7	overfeat	overfeat	NOUN
brj-22962	25	8	,	,	PUNCT
brj-22962	25	9	the	the	DET
brj-22962	25	10	yolo	yolo	ADJ
brj-22962	25	11	series	series	PROPN
brj-22962	25	12	,	,	PUNCT
brj-22962	25	13	ssd	ssd	PROPN
brj-22962	25	14	,	,	PUNCT
brj-22962	25	15	and	and	CCONJ
brj-22962	25	16	retinanet	retinanet	NOUN
brj-22962	25	17	.	.	PUNCT
brj-22962	26	1	the	the	DET
brj-22962	26	2	second	second	ADJ
brj-22962	26	3	type	type	NOUN
brj-22962	26	4	is	be	AUX
brj-22962	26	5	two	two	NUM
brj-22962	26	6	-	-	PUNCT
brj-22962	26	7	stage	stage	NOUN
brj-22962	26	8	wood	wood	NOUN
brj-22962	26	9	defect	defect	NOUN
brj-22962	26	10	detection	detection	NOUN
brj-22962	26	11	,	,	PUNCT
brj-22962	26	12	also	also	ADV
brj-22962	26	13	known	know	VERB
brj-22962	26	14	as	as	ADP
brj-22962	26	15	the	the	DET
brj-22962	26	16	target	target	NOUN
brj-22962	26	17	detection	detection	NOUN
brj-22962	26	18	algorithm	algorithm	NOUN
brj-22962	26	19	,	,	PUNCT
brj-22962	26	20	based	base	VERB
brj-22962	26	21	on	on	ADP
brj-22962	26	22	region	region	NOUN
brj-22962	26	23	suggestions	suggestion	NOUN
brj-22962	26	24	.	.	PUNCT
brj-22962	27	1	this	this	DET
brj-22962	27	2	algorithm	algorithm	NOUN
brj-22962	27	3	converts	convert	VERB
brj-22962	27	4	the	the	DET
brj-22962	27	5	target	target	NOUN
brj-22962	27	6	detection	detection	NOUN
brj-22962	27	7	problem	problem	NOUN
brj-22962	27	8	into	into	ADP
brj-22962	27	9	processed	process	VERB
brj-22962	27	10	suggested	suggest	VERB
brj-22962	27	11	region	region	NOUN
brj-22962	27	12	image	image	NOUN
brj-22962	27	13	classification	classification	NOUN
brj-22962	27	14	through	through	ADP
brj-22962	27	15	explicit	explicit	ADJ
brj-22962	27	16	region	region	NOUN
brj-22962	27	17	suggestions	suggestion	NOUN
brj-22962	27	18	.	.	PUNCT
brj-22962	28	1	common	common	ADJ
brj-22962	28	2	two	two	NUM
brj-22962	28	3	-	-	PUNCT
brj-22962	28	4	stage	stage	NOUN
brj-22962	28	5	algorithms	algorithm	NOUN
brj-22962	28	6	include	include	VERB
brj-22962	28	7	r	r	NOUN
brj-22962	28	8	-	-	PUNCT
brj-22962	28	9	cnn	cnn	PROPN
brj-22962	28	10	,	,	PUNCT
brj-22962	28	11	spp	spp	NOUN
brj-22962	28	12	-	-	PUNCT
brj-22962	28	13	net	net	NOUN
brj-22962	28	14	,	,	PUNCT
brj-22962	28	15	fast	fast	ADJ
brj-22962	28	16	r	r	NOUN
brj-22962	28	17	-	-	PUNCT
brj-22962	28	18	cnn	cnn	PROPN
brj-22962	28	19	,	,	PUNCT
brj-22962	28	20	and	and	CCONJ
brj-22962	28	21	faster	fast	ADJ
brj-22962	28	22	r	r	NOUN
brj-22962	28	23	-	-	PUNCT
brj-22962	28	24	cnn	cnn	NOUN
brj-22962	28	25	.	.	PUNCT
brj-22962	29	1	these	these	DET
brj-22962	29	2	two	two	NUM
brj-22962	29	3	algorithms	algorithm	NOUN
brj-22962	29	4	have	have	VERB
brj-22962	29	5	their	their	PRON
brj-22962	29	6	respective	respective	ADJ
brj-22962	29	7	advantages	advantage	NOUN
brj-22962	29	8	and	and	CCONJ
brj-22962	29	9	disadvantages	disadvantage	NOUN
brj-22962	29	10	.	.	PUNCT
brj-22962	30	1	single	single	ADJ
brj-22962	30	2	-	-	PUNCT
brj-22962	30	3	stage	stage	NOUN
brj-22962	30	4	algorithms	algorithm	NOUN
brj-22962	30	5	perform	perform	VERB
brj-22962	30	6	classification	classification	NOUN
brj-22962	30	7	and	and	CCONJ
brj-22962	30	8	regression	regression	NOUN
brj-22962	30	9	directly	directly	ADV
brj-22962	30	10	without	without	ADP
brj-22962	30	11	generating	generate	VERB
brj-22962	30	12	candidate	candidate	NOUN
brj-22962	30	13	regions	region	NOUN
brj-22962	30	14	,	,	PUNCT
brj-22962	30	15	thus	thus	ADV
brj-22962	30	16	ensuring	ensure	VERB
brj-22962	30	17	high	high	ADJ
brj-22962	30	18	efficiency	efficiency	NOUN
brj-22962	30	19	and	and	CCONJ
brj-22962	30	20	suitability	suitability	NOUN
brj-22962	30	21	for	for	ADP
brj-22962	30	22	real	real	ADJ
brj-22962	30	23	-	-	PUNCT
brj-22962	30	24	time	time	NOUN
brj-22962	30	25	object	object	NOUN
brj-22962	30	26	detection	detection	NOUN
brj-22962	30	27	.	.	PUNCT
brj-22962	31	1	however	however	ADV
brj-22962	31	2	,	,	PUNCT
brj-22962	31	3	they	they	PRON
brj-22962	31	4	suffer	suffer	VERB
brj-22962	31	5	from	from	ADP
brj-22962	31	6	lower	low	ADJ
brj-22962	31	7	accuracy	accuracy	NOUN
brj-22962	31	8	in	in	ADP
brj-22962	31	9	detecting	detect	VERB
brj-22962	31	10	clustered	clustered	ADJ
brj-22962	31	11	objects	object	NOUN
brj-22962	31	12	and	and	CCONJ
brj-22962	31	13	small	small	ADJ
brj-22962	31	14	targets	target	NOUN
brj-22962	31	15	.	.	PUNCT
brj-22962	32	1	two	two	NUM
brj-22962	32	2	-	-	PUNCT
brj-22962	32	3	stage	stage	NOUN
brj-22962	32	4	algorithms	algorithm	NOUN
brj-22962	32	5	,	,	PUNCT
brj-22962	32	6	on	on	ADP
brj-22962	32	7	the	the	DET
brj-22962	32	8	other	other	ADJ
brj-22962	32	9	hand	hand	NOUN
brj-22962	32	10	,	,	PUNCT
brj-22962	32	11	first	first	ADV
brj-22962	32	12	generate	generate	VERB
brj-22962	32	13	candidate	candidate	NOUN
brj-22962	32	14	regions	region	NOUN
brj-22962	32	15	and	and	CCONJ
brj-22962	32	16	then	then	ADV
brj-22962	32	17	perform	perform	VERB
brj-22962	32	18	classification	classification	NOUN
brj-22962	32	19	and	and	CCONJ
brj-22962	32	20	regression	regression	NOUN
brj-22962	32	21	.	.	PUNCT
brj-22962	33	1	the	the	DET
brj-22962	33	2	benefit	benefit	NOUN
brj-22962	33	3	of	of	ADP
brj-22962	33	4	this	this	DET
brj-22962	33	5	approach	approach	NOUN
brj-22962	33	6	is	be	AUX
brj-22962	33	7	higher	high	ADJ
brj-22962	33	8	algorithm	algorithm	NOUN
brj-22962	33	9	accuracy	accuracy	NOUN
brj-22962	33	10	,	,	PUNCT
brj-22962	33	11	making	make	VERB
brj-22962	33	12	it	it	PRON
brj-22962	33	13	suitable	suitable	ADJ
brj-22962	33	14	for	for	ADP
brj-22962	33	15	precision	precision	NOUN
brj-22962	33	16	-	-	PUNCT
brj-22962	33	17	driven	drive	VERB
brj-22962	33	18	object	object	NOUN
brj-22962	33	19	detection	detection	NOUN
brj-22962	33	20	.	.	PUNCT
brj-22962	34	1	however	however	ADV
brj-22962	34	2	,	,	PUNCT
brj-22962	34	3	this	this	PRON
brj-22962	34	4	comes	come	VERB
brj-22962	34	5	at	at	ADP
brj-22962	34	6	the	the	DET
brj-22962	34	7	cost	cost	NOUN
brj-22962	34	8	of	of	ADP
brj-22962	34	9	reduced	reduce	VERB
brj-22962	34	10	real	real	ADJ
brj-22962	34	11	-	-	PUNCT
brj-22962	34	12	time	time	NOUN
brj-22962	34	13	detection	detection	NOUN
brj-22962	34	14	capabilities	capability	NOUN
brj-22962	34	15	and	and	CCONJ
brj-22962	34	16	less	less	ADV
brj-22962	34	17	effective	effective	ADJ
brj-22962	34	18	small	small	ADJ
brj-22962	34	19	object	object	NOUN
brj-22962	34	20	detection	detection	NOUN
brj-22962	34	21	.	.	PUNCT
brj-22962	35	1	yolo	yolo	PROPN
brj-22962	35	2	-	-	PUNCT
brj-22962	35	3	v1	v1	NOUN
brj-22962	35	4	(	(	PUNCT
brj-22962	35	5	the	the	DET
brj-22962	35	6	first	first	ADJ
brj-22962	35	7	version	version	NOUN
brj-22962	35	8	of	of	ADP
brj-22962	35	9	you	you	PRON
brj-22962	35	10	only	only	ADV
brj-22962	35	11	look	look	VERB
brj-22962	35	12	once	once	ADV
brj-22962	35	13	)	)	PUNCT
brj-22962	35	14	network	network	NOUN
brj-22962	35	15	,	,	PUNCT
brj-22962	35	16	the	the	DET
brj-22962	35	17	pioneer	pioneer	NOUN
brj-22962	35	18	of	of	ADP
brj-22962	35	19	yolo	yolo	ADJ
brj-22962	35	20	series	series	NOUN
brj-22962	35	21	,	,	PUNCT
brj-22962	35	22	was	be	AUX
brj-22962	35	23	produced	produce	VERB
brj-22962	35	24	in	in	ADP
brj-22962	35	25	2016	2016	NUM
brj-22962	35	26	.	.	PUNCT
brj-22962	36	1	it	it	PRON
brj-22962	36	2	has	have	AUX
brj-22962	36	3	received	receive	VERB
brj-22962	36	4	widespread	widespread	ADJ
brj-22962	36	5	attention	attention	NOUN
brj-22962	36	6	due	due	ADP
brj-22962	36	7	to	to	ADP
brj-22962	36	8	its	its	PRON
brj-22962	36	9	mechanism	mechanism	NOUN
brj-22962	36	10	of	of	ADP
brj-22962	36	11	direct	direct	ADJ
brj-22962	36	12	target	target	NOUN
brj-22962	36	13	localisation	localisation	NOUN
brj-22962	36	14	and	and	CCONJ
brj-22962	36	15	stereotyping	stereotyping	NOUN
brj-22962	36	16	of	of	ADP
brj-22962	36	17	the	the	DET
brj-22962	36	18	target	target	NOUN
brj-22962	36	19	to	to	PART
brj-22962	36	20	be	be	AUX
brj-22962	36	21	inspected	inspect	VERB
brj-22962	36	22	without	without	ADP
brj-22962	36	23	the	the	DET
brj-22962	36	24	need	need	NOUN
brj-22962	36	25	for	for	ADP
brj-22962	36	26	pre	pre	NOUN
brj-22962	36	27	-	-	NOUN
brj-22962	36	28	extraction	extraction	NOUN
brj-22962	36	29	of	of	ADP
brj-22962	36	30	candidate	candidate	NOUN
brj-22962	36	31	features	feature	NOUN
brj-22962	36	32	,	,	PUNCT
brj-22962	36	33	which	which	PRON
brj-22962	36	34	reduces	reduce	VERB
brj-22962	36	35	the	the	DET
brj-22962	36	36	resource	resource	NOUN
brj-22962	36	37	consumption	consumption	NOUN
brj-22962	36	38	and	and	CCONJ
brj-22962	36	39	also	also	ADV
brj-22962	36	40	improves	improve	VERB
brj-22962	36	41	the	the	DET
brj-22962	36	42	speed	speed	NOUN
brj-22962	36	43	of	of	ADP
brj-22962	36	44	the	the	DET
brj-22962	36	45	inspection	inspection	NOUN
brj-22962	36	46	.	.	PUNCT
brj-22962	37	1	wang	wang	PROPN
brj-22962	37	2	et	et	PROPN
brj-22962	37	3	al	al	PROPN
brj-22962	37	4	.	.	PROPN
brj-22962	37	5	(	(	PUNCT
brj-22962	37	6	2021a	2021a	NUM
brj-22962	37	7	)	)	PUNCT
brj-22962	37	8	proposed	propose	VERB
brj-22962	37	9	separable	separable	ADJ
brj-22962	37	10	convolutional	convolutional	ADJ
brj-22962	37	11	ideas	idea	NOUN
brj-22962	37	12	to	to	PART
brj-22962	37	13	improve	improve	VERB
brj-22962	37	14	the	the	DET
brj-22962	37	15	yolo	yolo	PROPN
brj-22962	37	16	-	-	PUNCT
brj-22962	37	17	v3	v3	PROPN
brj-22962	37	18	network	network	NOUN
brj-22962	37	19	,	,	PUNCT
brj-22962	37	20	but	but	CCONJ
brj-22962	37	21	only	only	ADV
brj-22962	37	22	in	in	ADP
brj-22962	37	23	the	the	DET
brj-22962	37	24	recognition	recognition	NOUN
brj-22962	37	25	of	of	ADP
brj-22962	37	26	the	the	DET
brj-22962	37	27	accuracy	accuracy	NOUN
brj-22962	37	28	and	and	CCONJ
brj-22962	37	29	speed	speed	NOUN
brj-22962	37	30	of	of	ADP
brj-22962	37	31	the	the	DET
brj-22962	37	32	improvement	improvement	NOUN
brj-22962	37	33	,	,	PUNCT
brj-22962	37	34	for	for	ADP
brj-22962	37	35	small	small	ADJ
brj-22962	37	36	defects	defect	NOUN
brj-22962	37	37	such	such	ADJ
brj-22962	37	38	as	as	ADP
brj-22962	37	39	cracks	crack	NOUN
brj-22962	37	40	and	and	CCONJ
brj-22962	37	41	small	small	ADJ
brj-22962	37	42	holes	hole	NOUN
brj-22962	37	43	in	in	ADP
brj-22962	37	44	the	the	DET
brj-22962	37	45	recognition	recognition	NOUN
brj-22962	37	46	of	of	ADP
brj-22962	37	47	low	low	ADJ
brj-22962	37	48	efficiency	efficiency	NOUN
brj-22962	37	49	.	.	PUNCT
brj-22962	38	1	kurdthongmee	kurdthongmee	PROPN
brj-22962	38	2	(	(	PUNCT
brj-22962	38	3	2023	2023	NUM
brj-22962	38	4	)	)	PUNCT
brj-22962	38	5	built	build	VERB
brj-22962	38	6	a	a	DET
brj-22962	38	7	framework	framework	NOUN
brj-22962	38	8	for	for	ADP
brj-22962	38	9	a	a	DET
brj-22962	38	10	wood	wood	NOUN
brj-22962	38	11	defect	defect	NOUN
brj-22962	38	12	detection	detection	NOUN
brj-22962	38	13	system	system	NOUN
brj-22962	38	14	based	base	VERB
brj-22962	38	15	on	on	ADP
brj-22962	38	16	yolo	yolo	PROPN
brj-22962	38	17	-	-	PUNCT
brj-22962	38	18	v3	v3	PROPN
brj-22962	38	19	,	,	PUNCT
brj-22962	38	20	which	which	PRON
brj-22962	38	21	focuses	focus	VERB
brj-22962	38	22	on	on	ADP
brj-22962	38	23	training	train	VERB
brj-22962	38	24	the	the	DET
brj-22962	38	25	dataset	dataset	NOUN
brj-22962	38	26	so	so	SCONJ
brj-22962	38	27	that	that	SCONJ
brj-22962	38	28	it	it	PRON
brj-22962	38	29	can	can	AUX
brj-22962	38	30	meet	meet	VERB
brj-22962	38	31	the	the	DET
brj-22962	38	32	requirements	requirement	NOUN
brj-22962	38	33	of	of	ADP
brj-22962	38	34	deep	deep	ADJ
brj-22962	38	35	learning	learning	NOUN
brj-22962	38	36	models	model	NOUN
brj-22962	38	37	in	in	ADP
brj-22962	38	38	terms	term	NOUN
brj-22962	38	39	of	of	ADP
brj-22962	38	40	size	size	NOUN
brj-22962	38	41	and	and	CCONJ
brj-22962	38	42	variability	variability	NOUN
brj-22962	38	43	.	.	PUNCT
brj-22962	39	1	however	however	ADV
brj-22962	39	2	,	,	PUNCT
brj-22962	39	3	the	the	DET
brj-22962	39	4	method	method	NOUN
brj-22962	39	5	has	have	VERB
brj-22962	39	6	limitations	limitation	NOUN
brj-22962	39	7	and	and	CCONJ
brj-22962	39	8	the	the	DET
brj-22962	39	9	final	final	ADJ
brj-22962	39	10	recognition	recognition	NOUN
brj-22962	39	11	results	result	NOUN
brj-22962	39	12	are	be	AUX
brj-22962	39	13	average	average	ADJ
brj-22962	39	14	.	.	PUNCT
brj-22962	40	1	cui	cui	NOUN
brj-22962	40	2	et	et	PROPN
brj-22962	40	3	al	al	PROPN
brj-22962	40	4	.	.	PROPN
brj-22962	41	1	(	(	PUNCT
brj-22962	41	2	2023	2023	NUM
brj-22962	41	3	)	)	PUNCT
brj-22962	41	4	proposed	propose	VERB
brj-22962	41	5	an	an	DET
brj-22962	41	6	improved	improved	ADJ
brj-22962	41	7	method	method	NOUN
brj-22962	41	8	based	base	VERB
brj-22962	41	9	on	on	ADP
brj-22962	41	10	the	the	DET
brj-22962	41	11	yolov3	yolov3	PROPN
brj-22962	41	12	network	network	NOUN
brj-22962	41	13	framework	framework	NOUN
brj-22962	41	14	with	with	ADP
brj-22962	41	15	spatial	spatial	ADJ
brj-22962	41	16	pyramid	pyramid	NOUN
brj-22962	41	17	pool	pool	NOUN
brj-22962	41	18	(	(	PUNCT
brj-22962	41	19	ssp	ssp	NOUN
brj-22962	41	20	)	)	PUNCT
brj-22962	41	21	network	network	NOUN
brj-22962	41	22	.	.	PUNCT
brj-22962	42	1	they	they	PRON
brj-22962	42	2	obtained	obtain	VERB
brj-22962	42	3	an	an	DET
brj-22962	42	4	accuracy	accuracy	NOUN
brj-22962	42	5	of	of	ADP
brj-22962	42	6	93.23	93.23	NUM
brj-22962	42	7	%	%	NOUN
brj-22962	42	8	for	for	ADP
brj-22962	42	9	identification	identification	NOUN
brj-22962	42	10	of	of	ADP
brj-22962	42	11	wood	wood	NOUN
brj-22962	42	12	defects	defect	NOUN
brj-22962	42	13	in	in	ADP
brj-22962	42	14	a	a	DET
brj-22962	42	15	test	test	NOUN
brj-22962	42	16	set	set	VERB
brj-22962	42	17	with	with	ADP
brj-22962	42	18	an	an	DET
brj-22962	42	19	industrial	industrial	ADJ
brj-22962	42	20	production	production	NOUN
brj-22962	42	21	detection	detection	NOUN
brj-22962	42	22	time	time	NOUN
brj-22962	42	23	of	of	ADP
brj-22962	42	24	less	less	ADJ
brj-22962	42	25	than	than	ADP
brj-22962	42	26	13	13	NUM
brj-22962	42	27	ms	ms	PROPN
brj-22962	42	28	.	.	PROPN
brj-22962	42	29	wang	wang	PROPN
brj-22962	42	30	et	et	PROPN
brj-22962	42	31	al	al	PROPN
brj-22962	42	32	.	.	PROPN
brj-22962	43	1	(	(	PUNCT
brj-22962	43	2	2021b	2021b	NUM
brj-22962	43	3	)	)	PUNCT
brj-22962	43	4	proposed	propose	VERB
brj-22962	43	5	an	an	DET
brj-22962	43	6	improved	improved	ADJ
brj-22962	43	7	version	version	NOUN
brj-22962	43	8	of	of	ADP
brj-22962	43	9	yolo	yolo	ADJ
brj-22962	43	10	-	-	PUNCT
brj-22962	43	11	v4	v4	NOUN
brj-22962	43	12	network	network	NOUN
brj-22962	43	13	and	and	CCONJ
brj-22962	43	14	successfully	successfully	ADV
brj-22962	43	15	achieved	achieve	VERB
brj-22962	43	16	the	the	DET
brj-22962	43	17	identification	identification	NOUN
brj-22962	43	18	and	and	CCONJ
brj-22962	43	19	classification	classification	NOUN
brj-22962	43	20	of	of	ADP
brj-22962	43	21	live	live	ADJ
brj-22962	43	22	knots	knot	NOUN
brj-22962	43	23	,	,	PUNCT
brj-22962	43	24	dead	dead	ADJ
brj-22962	43	25	knots	knot	NOUN
brj-22962	43	26	,	,	PUNCT
brj-22962	43	27	cracks	crack	NOUN
brj-22962	43	28	,	,	PUNCT
brj-22962	43	29	and	and	CCONJ
brj-22962	43	30	insect	insect	VERB
brj-22962	43	31	eyes	eye	NOUN
brj-22962	43	32	on	on	ADP
brj-22962	43	33	the	the	DET
brj-22962	43	34	surface	surface	NOUN
brj-22962	43	35	of	of	ADP
brj-22962	43	36	domestic	domestic	ADJ
brj-22962	43	37	spruce	spruce	NOUN
brj-22962	43	38	sawn	sawn	NOUN
brj-22962	43	39	timber	timber	NOUN
brj-22962	43	40	.	.	PUNCT
brj-22962	44	1	however	however	ADV
brj-22962	44	2	,	,	PUNCT
brj-22962	44	3	yolo	yolo	PROPN
brj-22962	44	4	-	-	PUNCT
brj-22962	44	5	v4	v4	NOUN
brj-22962	44	6	,	,	PUNCT
brj-22962	44	7	as	as	ADP
brj-22962	44	8	an	an	DET
brj-22962	44	9	enhanced	enhanced	ADJ
brj-22962	44	10	version	version	NOUN
brj-22962	44	11	of	of	ADP
brj-22962	44	12	yolo	yolo	PROPN
brj-22962	44	13	-	-	PUNCT
brj-22962	44	14	v3	v3	PROPN
brj-22962	44	15	,	,	PUNCT
brj-22962	44	16	has	have	AUX
brj-22962	44	17	not	not	PART
brj-22962	44	18	changed	change	VERB
brj-22962	44	19	its	its	PRON
brj-22962	44	20	core	core	NOUN
brj-22962	44	21	idea	idea	NOUN
brj-22962	44	22	,	,	PUNCT
brj-22962	44	23	and	and	CCONJ
brj-22962	44	24	still	still	ADV
brj-22962	44	25	has	have	VERB
brj-22962	44	26	the	the	DET
brj-22962	44	27	problem	problem	NOUN
brj-22962	44	28	of	of	ADP
brj-22962	44	29	misclassification	misclassification	NOUN
brj-22962	44	30	and	and	CCONJ
brj-22962	44	31	omission	omission	NOUN
brj-22962	44	32	of	of	ADP
brj-22962	44	33	small	small	ADJ
brj-22962	44	34	defects	defect	NOUN
brj-22962	44	35	such	such	ADJ
brj-22962	44	36	as	as	ADP
brj-22962	44	37	fine	fine	ADJ
brj-22962	44	38	cracks	crack	NOUN
brj-22962	44	39	and	and	CCONJ
brj-22962	44	40	small	small	ADJ
brj-22962	44	41	holes	hole	NOUN
brj-22962	44	42	.	.	PUNCT
brj-22962	45	1	based	base	VERB
brj-22962	45	2	on	on	ADP
brj-22962	45	3	the	the	DET
brj-22962	45	4	fact	fact	NOUN
brj-22962	45	5	that	that	SCONJ
brj-22962	45	6	the	the	DET
brj-22962	45	7	yolo	yolo	ADJ
brj-22962	45	8	series	series	NOUN
brj-22962	45	9	does	do	AUX
brj-22962	45	10	not	not	PART
brj-22962	45	11	make	make	VERB
brj-22962	45	12	outstanding	outstanding	ADJ
brj-22962	45	13	improvements	improvement	NOUN
brj-22962	45	14	for	for	ADP
brj-22962	45	15	small	small	ADJ
brj-22962	45	16	defects	defect	NOUN
brj-22962	45	17	on	on	ADP
brj-22962	45	18	the	the	DET
brj-22962	45	19	surface	surface	NOUN
brj-22962	45	20	of	of	ADP
brj-22962	45	21	wood	wood	NOUN
brj-22962	45	22	,	,	PUNCT
brj-22962	45	23	fang	fang	X
brj-22962	45	24	et	et	PROPN
brj-22962	45	25	al	al	PROPN
brj-22962	45	26	.	.	PROPN
brj-22962	46	1	(	(	PUNCT
brj-22962	46	2	2021	2021	NUM
brj-22962	46	3	)	)	PUNCT
brj-22962	46	4	focused	focus	VERB
brj-22962	46	5	on	on	ADP
brj-22962	46	6	the	the	DET
brj-22962	46	7	detection	detection	NOUN
brj-22962	46	8	and	and	CCONJ
brj-22962	46	9	identification	identification	NOUN
brj-22962	46	10	of	of	ADP
brj-22962	46	11	wood	wood	NOUN
brj-22962	46	12	knots	knot	NOUN
brj-22962	46	13	.	.	PUNCT
brj-22962	47	1	they	they	PRON
brj-22962	47	2	used	use	VERB
brj-22962	47	3	the	the	DET
brj-22962	47	4	yolo	yolo	PROPN
brj-22962	47	5	-	-	PUNCT
brj-22962	47	6	v5	v5	PROPN
brj-22962	47	7	detector	detector	NOUN
brj-22962	47	8	to	to	PART
brj-22962	47	9	adaptively	adaptively	ADV
brj-22962	47	10	learn	learn	VERB
brj-22962	47	11	and	and	CCONJ
brj-22962	47	12	extract	extract	VERB
brj-22962	47	13	knots	knot	NOUN
brj-22962	47	14	on	on	ADP
brj-22962	47	15	the	the	DET
brj-22962	47	16	surface	surface	NOUN
brj-22962	47	17	of	of	ADP
brj-22962	47	18	sawn	sawn	NOUN
brj-22962	47	19	timber	timber	NOUN
brj-22962	47	20	.	.	PUNCT
brj-22962	48	1	unfortunately	unfortunately	ADV
brj-22962	48	2	,	,	PUNCT
brj-22962	48	3	they	they	PRON
brj-22962	48	4	used	use	VERB
brj-22962	48	5	the	the	DET
brj-22962	48	6	yolo	yolo	ADJ
brj-22962	48	7	model	model	NOUN
brj-22962	48	8	for	for	ADP
brj-22962	48	9	detecting	detect	VERB
brj-22962	48	10	knot	knot	NOUN
brj-22962	48	11	defects	defect	NOUN
brj-22962	48	12	and	and	CCONJ
brj-22962	48	13	did	do	AUX
brj-22962	48	14	not	not	PART
brj-22962	48	15	conduct	conduct	VERB
brj-22962	48	16	experiments	experiment	NOUN
brj-22962	48	17	on	on	ADP
brj-22962	48	18	knot	knot	ADJ
brj-22962	48	19	classification	classification	NOUN
brj-22962	48	20	,	,	PUNCT
brj-22962	48	21	so	so	CCONJ
brj-22962	48	22	the	the	DET
brj-22962	48	23	usefulness	usefulness	NOUN
brj-22962	48	24	of	of	ADP
brj-22962	48	25	the	the	DET
brj-22962	48	26	yolo	yolo	PROPN
brj-22962	48	27	-	-	PUNCT
brj-22962	48	28	v5	v5	PROPN
brj-22962	48	29	network	network	NOUN
brj-22962	48	30	for	for	ADP
brj-22962	48	31	classifying	classify	VERB
brj-22962	48	32	wood	wood	NOUN
brj-22962	48	33	knots	knot	NOUN
brj-22962	48	34	has	have	VERB
brj-22962	48	35	yet	yet	ADV
brj-22962	48	36	to	to	PART
brj-22962	48	37	be	be	AUX
brj-22962	48	38	demonstrated	demonstrate	VERB
brj-22962	48	39	.	.	PUNCT
brj-22962	49	1	cao	cao	PROPN
brj-22962	49	2	et	et	PROPN
brj-22962	49	3	al	al	PROPN
brj-22962	49	4	.	.	PROPN
brj-22962	49	5	(	(	PUNCT
brj-22962	49	6	2023	2023	NUM
brj-22962	49	7	)	)	PUNCT
brj-22962	49	8	proposed	propose	VERB
brj-22962	49	9	a	a	DET
brj-22962	49	10	yolov5	yolov5	NOUN
brj-22962	49	11	-	-	PUNCT
brj-22962	49	12	lw	lw	PROPN
brj-22962	49	13	method	method	NOUN
brj-22962	49	14	for	for	ADP
brj-22962	49	15	detecting	detect	VERB
brj-22962	49	16	defects	defect	NOUN
brj-22962	49	17	in	in	ADP
brj-22962	49	18	lightweight	lightweight	ADJ
brj-22962	49	19	wood	wood	NOUN
brj-22962	49	20	boards	board	NOUN
brj-22962	49	21	.	.	PUNCT
brj-22962	50	1	their	their	PRON
brj-22962	50	2	system	system	NOUN
brj-22962	50	3	combines	combine	VERB
brj-22962	50	4	the	the	DET
brj-22962	50	5	attention	attention	NOUN
brj-22962	50	6	mechanism	mechanism	NOUN
brj-22962	50	7	and	and	CCONJ
brj-22962	50	8	feature	feature	NOUN
brj-22962	50	9	fusion	fusion	NOUN
brj-22962	50	10	network	network	NOUN
brj-22962	50	11	peer	peer	NOUN
brj-22962	50	12	-	-	PUNCT
brj-22962	50	13	reviewed	review	VERB
brj-22962	50	14	article	article	NOUN
brj-22962	50	15	bioresources.com	bioresources.com	X
brj-22962	50	16	wang	wang	PROPN
brj-22962	50	17	et	et	PROPN
brj-22962	50	18	al	al	PROPN
brj-22962	50	19	.	.	PROPN
brj-22962	51	1	(	(	PUNCT
brj-22962	51	2	2023	2023	NUM
brj-22962	51	3	)	)	PUNCT
brj-22962	51	4	.	.	PUNCT
brj-22962	52	1	“	"	PUNCT
brj-22962	52	2	timber	timber	NOUN
brj-22962	52	3	defect	defect	NOUN
brj-22962	52	4	i	i	PROPN
brj-22962	52	5	d	d	PROPN
brj-22962	52	6	algorithms	algorithm	NOUN
brj-22962	52	7	,	,	PUNCT
brj-22962	52	8	”	"	PUNCT
brj-22962	52	9	bioresources	bioresource	NOUN
brj-22962	52	10	18(4	18(4	NUM
brj-22962	52	11	)	)	PUNCT
brj-22962	52	12	,	,	PUNCT
brj-22962	52	13	8444	8444	NUM
brj-22962	52	14	-	-	SYM
brj-22962	52	15	8457	8457	NUM
brj-22962	52	16	.	.	PUNCT
brj-22962	52	17	8446	8446	NUM
brj-22962	52	18	to	to	PART
brj-22962	52	19	solve	solve	VERB
brj-22962	52	20	the	the	DET
brj-22962	52	21	problems	problem	NOUN
brj-22962	52	22	of	of	ADP
brj-22962	52	23	slow	slow	ADJ
brj-22962	52	24	detection	detection	NOUN
brj-22962	52	25	speed	speed	NOUN
brj-22962	52	26	and	and	CCONJ
brj-22962	52	27	difficulty	difficulty	NOUN
brj-22962	52	28	in	in	ADP
brj-22962	52	29	deploying	deploy	VERB
brj-22962	52	30	embedded	embed	VERB
brj-22962	52	31	devices	device	NOUN
brj-22962	52	32	for	for	ADP
brj-22962	52	33	defect	defect	NOUN
brj-22962	52	34	detection	detection	NOUN
brj-22962	52	35	in	in	ADP
brj-22962	52	36	wood	wood	NOUN
brj-22962	52	37	boards	board	NOUN
brj-22962	52	38	.	.	PUNCT
brj-22962	53	1	the	the	DET
brj-22962	53	2	approach	approach	NOUN
brj-22962	53	3	reduces	reduce	VERB
brj-22962	53	4	the	the	DET
brj-22962	53	5	number	number	NOUN
brj-22962	53	6	of	of	ADP
brj-22962	53	7	parameters	parameter	NOUN
brj-22962	53	8	and	and	CCONJ
brj-22962	53	9	computation	computation	NOUN
brj-22962	53	10	of	of	ADP
brj-22962	53	11	the	the	DET
brj-22962	53	12	whole	whole	ADJ
brj-22962	53	13	model	model	NOUN
brj-22962	53	14	and	and	CCONJ
brj-22962	53	15	improves	improve	VERB
brj-22962	53	16	the	the	DET
brj-22962	53	17	detection	detection	NOUN
brj-22962	53	18	speed	speed	NOUN
brj-22962	53	19	while	while	SCONJ
brj-22962	53	20	improving	improve	VERB
brj-22962	53	21	the	the	DET
brj-22962	53	22	recognition	recognition	NOUN
brj-22962	53	23	accuracy	accuracy	NOUN
brj-22962	53	24	.	.	PUNCT
brj-22962	54	1	at	at	ADP
brj-22962	54	2	present	present	ADJ
brj-22962	54	3	,	,	PUNCT
brj-22962	54	4	the	the	DET
brj-22962	54	5	existing	exist	VERB
brj-22962	54	6	research	research	NOUN
brj-22962	54	7	on	on	ADP
brj-22962	54	8	wood	wood	NOUN
brj-22962	54	9	defect	defect	NOUN
brj-22962	54	10	detection	detection	NOUN
brj-22962	54	11	mainly	mainly	ADV
brj-22962	54	12	has	have	AUX
brj-22962	54	13	focused	focus	VERB
brj-22962	54	14	on	on	ADP
brj-22962	54	15	detecting	detect	VERB
brj-22962	54	16	a	a	DET
brj-22962	54	17	single	single	ADJ
brj-22962	54	18	type	type	NOUN
brj-22962	54	19	or	or	CCONJ
brj-22962	54	20	a	a	DET
brj-22962	54	21	few	few	ADJ
brj-22962	54	22	common	common	ADJ
brj-22962	54	23	defects	defect	NOUN
brj-22962	54	24	,	,	PUNCT
brj-22962	54	25	which	which	PRON
brj-22962	54	26	can	can	AUX
brj-22962	54	27	not	not	PART
brj-22962	54	28	meet	meet	VERB
brj-22962	54	29	the	the	DET
brj-22962	54	30	needs	need	NOUN
brj-22962	54	31	of	of	ADP
brj-22962	54	32	more	more	ADJ
brj-22962	54	33	delicate	delicate	ADJ
brj-22962	54	34	wood	wood	NOUN
brj-22962	54	35	processing	processing	NOUN
brj-22962	54	36	.	.	PUNCT
brj-22962	55	1	han	han	PROPN
brj-22962	55	2	et	et	PROPN
brj-22962	55	3	al	al	PROPN
brj-22962	55	4	.	.	PROPN
brj-22962	56	1	(	(	PUNCT
brj-22962	56	2	2023	2023	NUM
brj-22962	56	3	)	)	PUNCT
brj-22962	56	4	optimised	optimise	VERB
brj-22962	56	5	the	the	DET
brj-22962	56	6	backbone	backbone	NOUN
brj-22962	56	7	network	network	NOUN
brj-22962	56	8	while	while	SCONJ
brj-22962	56	9	introducing	introduce	VERB
brj-22962	56	10	bifpn	bifpn	NOUN
brj-22962	56	11	in	in	ADP
brj-22962	56	12	the	the	DET
brj-22962	56	13	neck	neck	NOUN
brj-22962	56	14	to	to	PART
brj-22962	56	15	achieve	achieve	VERB
brj-22962	56	16	a	a	DET
brj-22962	56	17	multi	multi	ADJ
brj-22962	56	18	-	-	ADJ
brj-22962	56	19	scale	scale	ADJ
brj-22962	56	20	weighted	weight	VERB
brj-22962	56	21	bidirectional	bidirectional	ADJ
brj-22962	56	22	feature	feature	NOUN
brj-22962	56	23	fusion	fusion	NOUN
brj-22962	56	24	stc	stc	NOUN
brj-22962	56	25	-	-	PUNCT
brj-22962	56	26	yolov5	yolov5	NOUN
brj-22962	56	27	,	,	PUNCT
brj-22962	56	28	which	which	PRON
brj-22962	56	29	achieved	achieve	VERB
brj-22962	56	30	a	a	DET
brj-22962	56	31	better	well	ADJ
brj-22962	56	32	detection	detection	NOUN
brj-22962	56	33	effect	effect	NOUN
brj-22962	56	34	for	for	ADP
brj-22962	56	35	the	the	DET
brj-22962	56	36	seven	seven	NUM
brj-22962	56	37	types	type	NOUN
brj-22962	56	38	of	of	ADP
brj-22962	56	39	defects	defect	NOUN
brj-22962	56	40	and	and	CCONJ
brj-22962	56	41	has	have	VERB
brj-22962	56	42	great	great	ADJ
brj-22962	56	43	potential	potential	NOUN
brj-22962	56	44	for	for	ADP
brj-22962	56	45	application	application	NOUN
brj-22962	56	46	in	in	ADP
brj-22962	56	47	the	the	DET
brj-22962	56	48	field	field	NOUN
brj-22962	56	49	of	of	ADP
brj-22962	56	50	forestry	forestry	NOUN
brj-22962	56	51	industry	industry	NOUN
brj-22962	56	52	.	.	PUNCT
brj-22962	57	1	the	the	DET
brj-22962	57	2	yolo	yolo	ADJ
brj-22962	57	3	series	series	NOUN
brj-22962	57	4	of	of	ADP
brj-22962	57	5	algorithms	algorithms	PROPN
brj-22962	57	6	is	be	AUX
brj-22962	57	7	well	well	ADV
brj-22962	57	8	-	-	PUNCT
brj-22962	57	9	regarded	regard	VERB
brj-22962	57	10	for	for	ADP
brj-22962	57	11	their	their	PRON
brj-22962	57	12	efficient	efficient	ADJ
brj-22962	57	13	detection	detection	NOUN
brj-22962	57	14	capabilities	capability	NOUN
brj-22962	57	15	,	,	PUNCT
brj-22962	57	16	modular	modular	ADJ
brj-22962	57	17	design	design	NOUN
brj-22962	57	18	,	,	PUNCT
brj-22962	57	19	and	and	CCONJ
brj-22962	57	20	simplicity	simplicity	NOUN
brj-22962	57	21	,	,	PUNCT
brj-22962	57	22	making	make	VERB
brj-22962	57	23	them	they	PRON
brj-22962	57	24	an	an	DET
brj-22962	57	25	attractive	attractive	ADJ
brj-22962	57	26	choice	choice	NOUN
brj-22962	57	27	for	for	ADP
brj-22962	57	28	singlestage	singlestage	NOUN
brj-22962	57	29	target	target	NOUN
brj-22962	57	30	detection	detection	NOUN
brj-22962	57	31	tasks	task	NOUN
brj-22962	57	32	.	.	PUNCT
brj-22962	58	1	over	over	ADP
brj-22962	58	2	time	time	NOUN
brj-22962	58	3	,	,	PUNCT
brj-22962	58	4	various	various	ADJ
brj-22962	58	5	optimized	optimize	VERB
brj-22962	58	6	and	and	CCONJ
brj-22962	58	7	enhanced	enhanced	ADJ
brj-22962	58	8	models	model	NOUN
brj-22962	58	9	within	within	ADP
brj-22962	58	10	the	the	DET
brj-22962	58	11	yolo	yolo	ADJ
brj-22962	58	12	series	series	NOUN
brj-22962	58	13	have	have	AUX
brj-22962	58	14	emerged	emerge	VERB
brj-22962	58	15	,	,	PUNCT
brj-22962	58	16	gaining	gain	VERB
brj-22962	58	17	application	application	NOUN
brj-22962	58	18	in	in	ADP
brj-22962	58	19	diverse	diverse	ADJ
brj-22962	58	20	fields	field	NOUN
brj-22962	58	21	,	,	PUNCT
brj-22962	58	22	including	include	VERB
brj-22962	58	23	wood	wood	NOUN
brj-22962	58	24	defect	defect	NOUN
brj-22962	58	25	detection	detection	NOUN
brj-22962	58	26	.	.	PUNCT
brj-22962	59	1	these	these	DET
brj-22962	59	2	algorithms	algorithm	NOUN
brj-22962	59	3	,	,	PUNCT
brj-22962	59	4	both	both	PRON
brj-22962	59	5	in	in	ADP
brj-22962	59	6	their	their	PRON
brj-22962	59	7	basic	basic	ADJ
brj-22962	59	8	form	form	NOUN
brj-22962	59	9	and	and	CCONJ
brj-22962	59	10	as	as	ADP
brj-22962	59	11	improved	improved	ADJ
brj-22962	59	12	models	model	NOUN
brj-22962	59	13	,	,	PUNCT
brj-22962	59	14	have	have	AUX
brj-22962	59	15	significantly	significantly	ADV
brj-22962	59	16	propelled	propel	VERB
brj-22962	59	17	the	the	DET
brj-22962	59	18	advancement	advancement	NOUN
brj-22962	59	19	of	of	ADP
brj-22962	59	20	defect	defect	ADJ
brj-22962	59	21	detection	detection	NOUN
brj-22962	59	22	technology	technology	NOUN
brj-22962	59	23	within	within	ADP
brj-22962	59	24	the	the	DET
brj-22962	59	25	timber	timber	NOUN
brj-22962	59	26	industry	industry	NOUN
brj-22962	59	27	.	.	PUNCT
brj-22962	60	1	they	they	PRON
brj-22962	60	2	represent	represent	VERB
brj-22962	60	3	a	a	DET
brj-22962	60	4	valuable	valuable	ADJ
brj-22962	60	5	technological	technological	ADJ
brj-22962	60	6	asset	asset	NOUN
brj-22962	60	7	for	for	ADP
brj-22962	60	8	improving	improve	VERB
brj-22962	60	9	production	production	NOUN
brj-22962	60	10	and	and	CCONJ
brj-22962	60	11	enhancing	enhance	VERB
brj-22962	60	12	the	the	DET
brj-22962	60	13	quality	quality	NOUN
brj-22962	60	14	of	of	ADP
brj-22962	60	15	life	life	NOUN
brj-22962	60	16	.	.	PUNCT
brj-22962	61	1	addressing	address	VERB
brj-22962	61	2	the	the	DET
brj-22962	61	3	specific	specific	ADJ
brj-22962	61	4	requirements	requirement	NOUN
brj-22962	61	5	of	of	ADP
brj-22962	61	6	the	the	DET
brj-22962	61	7	wood	wood	NOUN
brj-22962	61	8	industry	industry	NOUN
brj-22962	61	9	,	,	PUNCT
brj-22962	61	10	particularly	particularly	ADV
brj-22962	61	11	the	the	DET
brj-22962	61	12	challenge	challenge	NOUN
brj-22962	61	13	of	of	ADP
brj-22962	61	14	detecting	detect	VERB
brj-22962	61	15	small	small	ADJ
brj-22962	61	16	defects	defect	NOUN
brj-22962	61	17	,	,	PUNCT
brj-22962	61	18	this	this	DET
brj-22962	61	19	paper	paper	NOUN
brj-22962	61	20	introduces	introduce	VERB
brj-22962	61	21	an	an	DET
brj-22962	61	22	improved	improved	ADJ
brj-22962	61	23	yolo	yolo	ADJ
brj-22962	61	24	-	-	PUNCT
brj-22962	61	25	v8	v8	NOUN
brj-22962	61	26	algorithm	algorithm	NOUN
brj-22962	61	27	,	,	PUNCT
brj-22962	61	28	denoted	denote	VERB
brj-22962	61	29	as	as	ADP
brj-22962	61	30	tsw	tsw	PROPN
brj-22962	61	31	-	-	PUNCT
brj-22962	61	32	yolo	yolo	NOUN
brj-22962	61	33	-	-	PUNCT
brj-22962	61	34	v8n	v8n	NOUN
brj-22962	61	35	.	.	PUNCT
brj-22962	62	1	the	the	DET
brj-22962	62	2	primary	primary	ADJ
brj-22962	62	3	objective	objective	NOUN
brj-22962	62	4	of	of	ADP
brj-22962	62	5	this	this	DET
brj-22962	62	6	enhanced	enhance	VERB
brj-22962	62	7	algorithm	algorithm	NOUN
brj-22962	62	8	is	be	AUX
brj-22962	62	9	to	to	PART
brj-22962	62	10	excel	excel	VERB
brj-22962	62	11	in	in	ADP
brj-22962	62	12	the	the	DET
brj-22962	62	13	detection	detection	NOUN
brj-22962	62	14	of	of	ADP
brj-22962	62	15	small	small	ADJ
brj-22962	62	16	defects	defect	NOUN
brj-22962	62	17	while	while	SCONJ
brj-22962	62	18	keeping	keep	VERB
brj-22962	62	19	computational	computational	ADJ
brj-22962	62	20	resource	resource	NOUN
brj-22962	62	21	requirements	requirement	NOUN
brj-22962	62	22	manageable	manageable	ADJ
brj-22962	62	23	.	.	PUNCT
brj-22962	63	1	it	it	PRON
brj-22962	63	2	strives	strive	VERB
brj-22962	63	3	to	to	PART
brj-22962	63	4	enhance	enhance	VERB
brj-22962	63	5	the	the	DET
brj-22962	63	6	accuracy	accuracy	NOUN
brj-22962	63	7	and	and	CCONJ
brj-22962	63	8	speed	speed	NOUN
brj-22962	63	9	of	of	ADP
brj-22962	63	10	detecting	detect	VERB
brj-22962	63	11	surface	surface	NOUN
brj-22962	63	12	defects	defect	NOUN
brj-22962	63	13	in	in	ADP
brj-22962	63	14	sawn	sawn	NOUN
brj-22962	63	15	timber	timber	NOUN
brj-22962	63	16	,	,	PUNCT
brj-22962	63	17	meeting	meet	VERB
brj-22962	63	18	the	the	DET
brj-22962	63	19	demand	demand	NOUN
brj-22962	63	20	for	for	ADP
brj-22962	63	21	high	high	ADJ
brj-22962	63	22	-	-	PUNCT
brj-22962	63	23	precision	precision	NOUN
brj-22962	63	24	real	real	ADJ
brj-22962	63	25	-	-	PUNCT
brj-22962	63	26	time	time	NOUN
brj-22962	63	27	detection	detection	NOUN
brj-22962	63	28	.	.	PUNCT
brj-22962	64	1	the	the	DET
brj-22962	64	2	proposed	propose	VERB
brj-22962	64	3	algorithm	algorithm	NOUN
brj-22962	64	4	’s	’s	PART
brj-22962	64	5	performance	performance	NOUN
brj-22962	64	6	is	be	AUX
brj-22962	64	7	rigorously	rigorously	ADV
brj-22962	64	8	validated	validate	VERB
brj-22962	64	9	using	use	VERB
brj-22962	64	10	a	a	DET
brj-22962	64	11	custommade	custommade	NOUN
brj-22962	64	12	dataset	dataset	NOUN
brj-22962	64	13	,	,	PUNCT
brj-22962	64	14	ensuring	ensure	VERB
brj-22962	64	15	that	that	SCONJ
brj-22962	64	16	it	it	PRON
brj-22962	64	17	meets	meet	VERB
brj-22962	64	18	the	the	DET
brj-22962	64	19	stringent	stringent	ADJ
brj-22962	64	20	requirements	requirement	NOUN
brj-22962	64	21	for	for	ADP
brj-22962	64	22	defect	defect	NOUN
brj-22962	64	23	detection	detection	NOUN
brj-22962	64	24	tasks	task	NOUN
brj-22962	64	25	within	within	ADP
brj-22962	64	26	the	the	DET
brj-22962	64	27	wood	wood	NOUN
brj-22962	64	28	industry	industry	NOUN
brj-22962	64	29	.	.	PUNCT
brj-22962	65	1	this	this	DET
brj-22962	65	2	research	research	NOUN
brj-22962	65	3	contributes	contribute	VERB
brj-22962	65	4	to	to	ADP
brj-22962	65	5	advancing	advance	VERB
brj-22962	65	6	the	the	DET
brj-22962	65	7	state	state	NOUN
brj-22962	65	8	-	-	PUNCT
brj-22962	65	9	of	of	ADP
brj-22962	65	10	-	-	PUNCT
brj-22962	65	11	the	the	DET
brj-22962	65	12	-	-	PUNCT
brj-22962	65	13	art	art	NOUN
brj-22962	65	14	in	in	ADP
brj-22962	65	15	wood	wood	NOUN
brj-22962	65	16	defect	defect	NOUN
brj-22962	65	17	detection	detection	NOUN
brj-22962	65	18	and	and	CCONJ
brj-22962	65	19	reflects	reflect	VERB
brj-22962	65	20	the	the	DET
brj-22962	65	21	ongoing	ongoing	ADJ
brj-22962	65	22	evolution	evolution	NOUN
brj-22962	65	23	of	of	ADP
brj-22962	65	24	yolo	yolo	NOUN
brj-22962	65	25	-	-	PUNCT
brj-22962	65	26	based	base	VERB
brj-22962	65	27	algorithms	algorithm	NOUN
brj-22962	65	28	for	for	ADP
brj-22962	65	29	diverse	diverse	ADJ
brj-22962	65	30	applications	application	NOUN
brj-22962	65	31	.	.	PUNCT
brj-22962	66	1	the	the	DET
brj-22962	66	2	main	main	ADJ
brj-22962	66	3	contributions	contribution	NOUN
brj-22962	66	4	of	of	ADP
brj-22962	66	5	this	this	DET
brj-22962	66	6	study	study	NOUN
brj-22962	66	7	are	be	AUX
brj-22962	66	8	:	:	PUNCT
brj-22962	66	9	1	1	X
brj-22962	66	10	.	.	X
brj-22962	66	11	adding	add	VERB
brj-22962	66	12	tiny	tiny	ADJ
brj-22962	66	13	target	target	NOUN
brj-22962	66	14	detection	detection	NOUN
brj-22962	66	15	heads	head	NOUN
brj-22962	66	16	to	to	PART
brj-22962	66	17	improve	improve	VERB
brj-22962	66	18	the	the	DET
brj-22962	66	19	ability	ability	NOUN
brj-22962	66	20	of	of	ADP
brj-22962	66	21	the	the	DET
brj-22962	66	22	yolo	yolo	ADJ
brj-22962	66	23	-	-	PUNCT
brj-22962	66	24	v8	v8	PROPN
brj-22962	66	25	model	model	NOUN
brj-22962	66	26	for	for	ADP
brj-22962	66	27	small	small	ADJ
brj-22962	66	28	defect	defect	NOUN
brj-22962	66	29	detection	detection	NOUN
brj-22962	66	30	.	.	PUNCT
brj-22962	67	1	2	2	X
brj-22962	67	2	.	.	X
brj-22962	67	3	fusing	fuse	VERB
brj-22962	67	4	yolo	yolo	PROPN
brj-22962	67	5	-	-	PUNCT
brj-22962	67	6	v8	v8	PROPN
brj-22962	67	7	model	model	NOUN
brj-22962	67	8	using	use	VERB
brj-22962	67	9	the	the	DET
brj-22962	67	10	triplet	triplet	NOUN
brj-22962	67	11	attention	attention	NOUN
brj-22962	67	12	mechanism	mechanism	NOUN
brj-22962	67	13	to	to	PART
brj-22962	67	14	further	far	ADV
brj-22962	67	15	improve	improve	VERB
brj-22962	67	16	the	the	DET
brj-22962	67	17	model	model	NOUN
brj-22962	67	18	’s	’s	PART
brj-22962	67	19	ability	ability	NOUN
brj-22962	67	20	to	to	PART
brj-22962	67	21	detect	detect	VERB
brj-22962	67	22	small	small	ADJ
brj-22962	67	23	defects	defect	NOUN
brj-22962	67	24	.	.	PUNCT
brj-22962	68	1	3	3	X
brj-22962	68	2	.	.	X
brj-22962	68	3	adopting	adopt	VERB
brj-22962	68	4	bifpn	bifpn	PROPN
brj-22962	68	5	bidirectional	bidirectional	ADJ
brj-22962	68	6	cross	cross	ADJ
brj-22962	68	7	-	-	ADJ
brj-22962	68	8	scale	scale	ADJ
brj-22962	68	9	connectivity	connectivity	NOUN
brj-22962	68	10	with	with	ADP
brj-22962	68	11	weighted	weight	VERB
brj-22962	68	12	feature	feature	NOUN
brj-22962	68	13	fusion	fusion	NOUN
brj-22962	68	14	to	to	PART
brj-22962	68	15	improve	improve	VERB
brj-22962	68	16	the	the	DET
brj-22962	68	17	accuracy	accuracy	NOUN
brj-22962	68	18	and	and	CCONJ
brj-22962	68	19	efficiency	efficiency	NOUN
brj-22962	68	20	trade	trade	NOUN
brj-22962	68	21	-	-	PUNCT
brj-22962	68	22	off	off	NOUN
brj-22962	68	23	of	of	ADP
brj-22962	68	24	the	the	DET
brj-22962	68	25	model	model	NOUN
brj-22962	68	26	.	.	PUNCT
brj-22962	69	1	4	4	X
brj-22962	69	2	.	.	X
brj-22962	69	3	introducing	introduce	VERB
brj-22962	69	4	the	the	DET
brj-22962	69	5	wise	wise	ADJ
brj-22962	69	6	-	-	PUNCT
brj-22962	69	7	iou	iou	NOUN
brj-22962	69	8	loss	loss	NOUN
brj-22962	69	9	function	function	NOUN
brj-22962	69	10	to	to	PART
brj-22962	69	11	enhance	enhance	VERB
brj-22962	69	12	the	the	DET
brj-22962	69	13	ability	ability	NOUN
brj-22962	69	14	of	of	ADP
brj-22962	69	15	yolo	yolo	ADJ
brj-22962	69	16	-	-	PUNCT
brj-22962	69	17	v8	v8	PROPN
brj-22962	69	18	model	model	NOUN
brj-22962	69	19	to	to	PART
brj-22962	69	20	capture	capture	VERB
brj-22962	69	21	information	information	NOUN
brj-22962	69	22	and	and	CCONJ
brj-22962	69	23	improve	improve	VERB
brj-22962	69	24	the	the	DET
brj-22962	69	25	defect	defect	ADJ
brj-22962	69	26	information	information	NOUN
brj-22962	69	27	learning	learn	VERB
brj-22962	69	28	ability	ability	NOUN
brj-22962	69	29	.	.	PUNCT
brj-22962	70	1	experimental	experimental	ADJ
brj-22962	70	2	wood	wood	NOUN
brj-22962	70	3	defects	defect	NOUN
brj-22962	70	4	dataset	dataset	VERB
brj-22962	70	5	the	the	DET
brj-22962	70	6	dataset	dataset	NOUN
brj-22962	70	7	used	use	VERB
brj-22962	70	8	for	for	ADP
brj-22962	70	9	the	the	DET
brj-22962	70	10	experiment	experiment	NOUN
brj-22962	70	11	was	be	AUX
brj-22962	70	12	from	from	ADP
brj-22962	70	13	a	a	DET
brj-22962	70	14	large	large	ADJ
brj-22962	70	15	dataset	dataset	NOUN
brj-22962	70	16	of	of	ADP
brj-22962	70	17	wood	wood	NOUN
brj-22962	70	18	surface	surface	NOUN
brj-22962	70	19	defect	defect	NOUN
brj-22962	70	20	images	image	NOUN
brj-22962	70	21	provided	provide	VERB
brj-22962	70	22	by	by	ADP
brj-22962	70	23	(	(	PUNCT
brj-22962	70	24	kodytek	kodytek	X
brj-22962	70	25	et	et	PROPN
brj-22962	70	26	al	al	PROPN
brj-22962	70	27	.	.	PROPN
brj-22962	70	28	2022	2022	NUM
brj-22962	70	29	)	)	PUNCT
brj-22962	70	30	.	.	PUNCT
brj-22962	71	1	to	to	PART
brj-22962	71	2	ensure	ensure	VERB
brj-22962	71	3	the	the	DET
brj-22962	71	4	reliability	reliability	NOUN
brj-22962	71	5	and	and	CCONJ
brj-22962	71	6	utility	utility	NOUN
brj-22962	71	7	of	of	ADP
brj-22962	71	8	the	the	DET
brj-22962	71	9	experimental	experimental	ADJ
brj-22962	71	10	data	datum	NOUN
brj-22962	71	11	,	,	PUNCT
brj-22962	71	12	a	a	DET
brj-22962	71	13	screening	screening	NOUN
brj-22962	71	14	process	process	NOUN
brj-22962	71	15	was	be	AUX
brj-22962	71	16	conducted	conduct	VERB
brj-22962	71	17	based	base	VERB
brj-22962	71	18	on	on	ADP
brj-22962	71	19	the	the	DET
brj-22962	71	20	original	original	ADJ
brj-22962	71	21	dataset	dataset	NOUN
brj-22962	71	22	.	.	PUNCT
brj-22962	72	1	this	this	DET
brj-22962	72	2	screening	screening	NOUN
brj-22962	72	3	resulted	result	VERB
brj-22962	72	4	in	in	ADP
brj-22962	72	5	the	the	DET
brj-22962	72	6	selection	selection	NOUN
brj-22962	72	7	of	of	ADP
brj-22962	72	8	3,612	3,612	NUM
brj-22962	72	9	defective	defective	ADJ
brj-22962	72	10	wood	wood	NOUN
brj-22962	72	11	defect	defect	NOUN
brj-22962	72	12	images	image	NOUN
brj-22962	72	13	(	(	PUNCT
brj-22962	72	14	as	as	SCONJ
brj-22962	72	15	shown	show	VERB
brj-22962	72	16	in	in	ADP
brj-22962	72	17	fig	fig	NOUN
brj-22962	72	18	.	.	PUNCT
brj-22962	73	1	1	1	NUM
brj-22962	73	2	)	)	PUNCT
brj-22962	73	3	.	.	PUNCT
brj-22962	74	1	to	to	PART
brj-22962	74	2	augment	augment	VERB
brj-22962	74	3	the	the	DET
brj-22962	74	4	dataset	dataset	NOUN
brj-22962	74	5	and	and	CCONJ
brj-22962	74	6	enhance	enhance	VERB
brj-22962	74	7	its	its	PRON
brj-22962	74	8	diversity	diversity	NOUN
brj-22962	74	9	,	,	PUNCT
brj-22962	74	10	various	various	ADJ
brj-22962	74	11	image	image	NOUN
brj-22962	74	12	processing	processing	NOUN
brj-22962	74	13	techniques	technique	NOUN
brj-22962	74	14	were	be	AUX
brj-22962	74	15	applied	apply	VERB
brj-22962	74	16	.	.	PUNCT
brj-22962	75	1	specifically	specifically	ADV
brj-22962	75	2	,	,	PUNCT
brj-22962	75	3	six	six	NUM
brj-22962	75	4	methods	method	NOUN
brj-22962	75	5	were	be	AUX
brj-22962	75	6	employed	employ	VERB
brj-22962	75	7	,	,	PUNCT
brj-22962	75	8	including	include	VERB
brj-22962	75	9	random	random	ADJ
brj-22962	75	10	combinations	combination	NOUN
brj-22962	75	11	peer	peer	NOUN
brj-22962	75	12	-	-	PUNCT
brj-22962	75	13	reviewed	review	VERB
brj-22962	75	14	article	article	NOUN
brj-22962	75	15	bioresources.com	bioresources.com	X
brj-22962	75	16	wang	wang	PROPN
brj-22962	75	17	et	et	PROPN
brj-22962	75	18	al	al	PROPN
brj-22962	75	19	.	.	PROPN
brj-22962	76	1	(	(	PUNCT
brj-22962	76	2	2023	2023	NUM
brj-22962	76	3	)	)	PUNCT
brj-22962	76	4	.	.	PUNCT
brj-22962	77	1	“	"	PUNCT
brj-22962	77	2	timber	timber	NOUN
brj-22962	77	3	defect	defect	NOUN
brj-22962	77	4	i	i	PROPN
brj-22962	77	5	d	d	PROPN
brj-22962	77	6	algorithms	algorithm	NOUN
brj-22962	77	7	,	,	PUNCT
brj-22962	77	8	”	"	PUNCT
brj-22962	77	9	bioresources	bioresource	NOUN
brj-22962	77	10	18(4	18(4	NUM
brj-22962	77	11	)	)	PUNCT
brj-22962	77	12	,	,	PUNCT
brj-22962	77	13	8444	8444	NUM
brj-22962	77	14	-	-	SYM
brj-22962	77	15	8457	8457	NUM
brj-22962	77	16	.	.	PUNCT
brj-22962	77	17	8447	8447	NUM
brj-22962	77	18	of	of	ADP
brj-22962	77	19	pixel	pixel	PROPN
brj-22962	77	20	point	point	NOUN
brj-22962	77	21	removal	removal	NOUN
brj-22962	77	22	,	,	PUNCT
brj-22962	77	23	sharpening	sharpening	NOUN
brj-22962	77	24	,	,	PUNCT
brj-22962	77	25	affine	affine	NOUN
brj-22962	77	26	transformation	transformation	NOUN
brj-22962	77	27	,	,	PUNCT
brj-22962	77	28	brightness	brightness	NOUN
brj-22962	77	29	adjustment	adjustment	NOUN
brj-22962	77	30	,	,	PUNCT
brj-22962	77	31	random	random	ADJ
brj-22962	77	32	hue	hue	NOUN
brj-22962	77	33	modification	modification	NOUN
brj-22962	77	34	,	,	PUNCT
brj-22962	77	35	and	and	CCONJ
brj-22962	77	36	horizontal	horizontal	ADJ
brj-22962	77	37	flipping	flipping	NOUN
brj-22962	77	38	.	.	PUNCT
brj-22962	78	1	these	these	DET
brj-22962	78	2	methods	method	NOUN
brj-22962	78	3	were	be	AUX
brj-22962	78	4	randomly	randomly	ADV
brj-22962	78	5	applied	apply	VERB
brj-22962	78	6	to	to	ADP
brj-22962	78	7	the	the	DET
brj-22962	78	8	original	original	ADJ
brj-22962	78	9	defective	defective	ADJ
brj-22962	78	10	images	image	NOUN
brj-22962	78	11	,	,	PUNCT
brj-22962	78	12	generating	generate	VERB
brj-22962	78	13	a	a	DET
brj-22962	78	14	total	total	NOUN
brj-22962	78	15	of	of	ADP
brj-22962	78	16	18,060	18,060	NUM
brj-22962	78	17	augmented	augment	VERB
brj-22962	78	18	defective	defective	ADJ
brj-22962	78	19	datasets	dataset	NOUN
brj-22962	78	20	.	.	PUNCT
brj-22962	79	1	when	when	SCONJ
brj-22962	79	2	combined	combine	VERB
brj-22962	79	3	with	with	ADP
brj-22962	79	4	the	the	DET
brj-22962	79	5	original	original	ADJ
brj-22962	79	6	images	image	NOUN
brj-22962	79	7	,	,	PUNCT
brj-22962	79	8	this	this	PRON
brj-22962	79	9	resulted	result	VERB
brj-22962	79	10	in	in	ADP
brj-22962	79	11	a	a	DET
brj-22962	79	12	dataset	dataset	NOUN
brj-22962	79	13	comprising	comprise	VERB
brj-22962	79	14	21,672	21,672	NUM
brj-22962	79	15	images	image	NOUN
brj-22962	79	16	in	in	ADP
brj-22962	79	17	total	total	NOUN
brj-22962	79	18	.	.	PUNCT
brj-22962	80	1	fig	fig	NOUN
brj-22962	80	2	.	.	PUNCT
brj-22962	81	1	1	1	NUM
brj-22962	81	2	.	.	X
brj-22962	81	3	eight	eight	NUM
brj-22962	81	4	kinds	kind	NOUN
brj-22962	81	5	of	of	ADP
brj-22962	81	6	defects	defect	NOUN
brj-22962	81	7	on	on	ADP
brj-22962	81	8	the	the	DET
brj-22962	81	9	surface	surface	NOUN
brj-22962	81	10	of	of	ADP
brj-22962	81	11	sawn	sawn	NOUN
brj-22962	81	12	timber	timber	NOUN
brj-22962	81	13	to	to	PART
brj-22962	81	14	facilitate	facilitate	VERB
brj-22962	81	15	the	the	DET
brj-22962	81	16	machine	machine	NOUN
brj-22962	81	17	learning	learn	VERB
brj-22962	81	18	experiments	experiment	NOUN
brj-22962	81	19	,	,	PUNCT
brj-22962	81	20	the	the	DET
brj-22962	81	21	dataset	dataset	NOUN
brj-22962	81	22	was	be	AUX
brj-22962	81	23	divided	divide	VERB
brj-22962	81	24	into	into	ADP
brj-22962	81	25	three	three	NUM
brj-22962	81	26	subsets	subset	NOUN
brj-22962	81	27	:	:	PUNCT
brj-22962	81	28	a	a	DET
brj-22962	81	29	training	training	NOUN
brj-22962	81	30	set	set	NOUN
brj-22962	81	31	,	,	PUNCT
brj-22962	81	32	a	a	DET
brj-22962	81	33	validation	validation	NOUN
brj-22962	81	34	set	set	NOUN
brj-22962	81	35	,	,	PUNCT
brj-22962	81	36	and	and	CCONJ
brj-22962	81	37	a	a	DET
brj-22962	81	38	test	test	NOUN
brj-22962	81	39	set	set	NOUN
brj-22962	81	40	,	,	PUNCT
brj-22962	81	41	distributed	distribute	VERB
brj-22962	81	42	in	in	ADP
brj-22962	81	43	an	an	DET
brj-22962	81	44	8:1:1	8:1:1	NUM
brj-22962	81	45	ratio	ratio	NOUN
brj-22962	81	46	.	.	PUNCT
brj-22962	82	1	this	this	DET
brj-22962	82	2	division	division	NOUN
brj-22962	82	3	ensures	ensure	VERB
brj-22962	82	4	that	that	SCONJ
brj-22962	82	5	the	the	DET
brj-22962	82	6	dataset	dataset	NOUN
brj-22962	82	7	is	be	AUX
brj-22962	82	8	appropriately	appropriately	ADV
brj-22962	82	9	utilized	utilize	VERB
brj-22962	82	10	for	for	ADP
brj-22962	82	11	model	model	NOUN
brj-22962	82	12	training	training	NOUN
brj-22962	82	13	,	,	PUNCT
brj-22962	82	14	validation	validation	NOUN
brj-22962	82	15	,	,	PUNCT
brj-22962	82	16	and	and	CCONJ
brj-22962	82	17	evaluation	evaluation	NOUN
brj-22962	82	18	,	,	PUNCT
brj-22962	82	19	respectively	respectively	ADV
brj-22962	82	20	.	.	PUNCT
brj-22962	83	1	the	the	DET
brj-22962	83	2	enhanced	enhance	VERB
brj-22962	83	3	dataset	dataset	NOUN
brj-22962	83	4	utilized	utilize	VERB
brj-22962	83	5	in	in	ADP
brj-22962	83	6	this	this	DET
brj-22962	83	7	study	study	NOUN
brj-22962	83	8	encompasses	encompass	VERB
brj-22962	83	9	eight	eight	NUM
brj-22962	83	10	distinct	distinct	ADJ
brj-22962	83	11	types	type	NOUN
brj-22962	83	12	of	of	ADP
brj-22962	83	13	defects	defect	NOUN
brj-22962	83	14	,	,	PUNCT
brj-22962	83	15	including	include	VERB
brj-22962	83	16	live	live	ADJ
brj-22962	83	17	knots	knot	NOUN
brj-22962	83	18	,	,	PUNCT
brj-22962	83	19	dead	dead	ADJ
brj-22962	83	20	knots	knot	NOUN
brj-22962	83	21	,	,	PUNCT
brj-22962	83	22	and	and	CCONJ
brj-22962	83	23	cracks	crack	NOUN
brj-22962	83	24	,	,	PUNCT
brj-22962	83	25	among	among	ADP
brj-22962	83	26	others	other	NOUN
brj-22962	83	27	.	.	PUNCT
brj-22962	84	1	figure	figure	NOUN
brj-22962	84	2	2	2	NUM
brj-22962	84	3	provides	provide	VERB
brj-22962	84	4	relevant	relevant	ADJ
brj-22962	84	5	insights	insight	NOUN
brj-22962	84	6	into	into	ADP
brj-22962	84	7	the	the	DET
brj-22962	84	8	characteristics	characteristic	NOUN
brj-22962	84	9	of	of	ADP
brj-22962	84	10	these	these	DET
brj-22962	84	11	defects	defect	NOUN
brj-22962	84	12	within	within	ADP
brj-22962	84	13	the	the	DET
brj-22962	84	14	dataset	dataset	NOUN
brj-22962	84	15	:	:	PUNCT
brj-22962	84	16	1	1	X
brj-22962	84	17	.	.	X
brj-22962	84	18	figure	figure	VERB
brj-22962	84	19	2	2	NUM
brj-22962	84	20	-	-	PUNCT
brj-22962	84	21	a	a	DET
brj-22962	84	22	presents	present	VERB
brj-22962	84	23	an	an	DET
brj-22962	84	24	overview	overview	NOUN
brj-22962	84	25	of	of	ADP
brj-22962	84	26	the	the	DET
brj-22962	84	27	distribution	distribution	NOUN
brj-22962	84	28	of	of	ADP
brj-22962	84	29	various	various	ADJ
brj-22962	84	30	defects	defect	NOUN
brj-22962	84	31	in	in	ADP
brj-22962	84	32	the	the	DET
brj-22962	84	33	dataset	dataset	NOUN
brj-22962	84	34	.	.	PUNCT
brj-22962	85	1	it	it	PRON
brj-22962	85	2	is	be	AUX
brj-22962	85	3	notable	notable	ADJ
brj-22962	85	4	that	that	SCONJ
brj-22962	85	5	live	live	VERB
brj-22962	85	6	and	and	CCONJ
brj-22962	85	7	dead	dead	ADJ
brj-22962	85	8	knots	knot	NOUN
brj-22962	85	9	predominate	predominate	ADJ
brj-22962	85	10	in	in	ADP
brj-22962	85	11	the	the	DET
brj-22962	85	12	dataset	dataset	NOUN
brj-22962	85	13	,	,	PUNCT
brj-22962	85	14	mirroring	mirror	VERB
brj-22962	85	15	realworld	realworld	NOUN
brj-22962	85	16	scenarios	scenario	NOUN
brj-22962	85	17	.	.	PUNCT
brj-22962	86	1	2	2	X
brj-22962	86	2	.	.	X
brj-22962	86	3	figure	figure	NOUN
brj-22962	86	4	2	2	NUM
brj-22962	86	5	-	-	PUNCT
brj-22962	86	6	b	b	NOUN
brj-22962	86	7	illustrates	illustrate	VERB
brj-22962	86	8	the	the	DET
brj-22962	86	9	size	size	NOUN
brj-22962	86	10	distribution	distribution	NOUN
brj-22962	86	11	of	of	ADP
brj-22962	86	12	the	the	DET
brj-22962	86	13	bounding	bounding	NOUN
brj-22962	86	14	boxes	box	NOUN
brj-22962	86	15	for	for	ADP
brj-22962	86	16	different	different	ADJ
brj-22962	86	17	defects	defect	NOUN
brj-22962	86	18	in	in	ADP
brj-22962	86	19	the	the	DET
brj-22962	86	20	dataset	dataset	NOUN
brj-22962	86	21	.	.	PUNCT
brj-22962	87	1	3	3	X
brj-22962	87	2	.	.	X
brj-22962	87	3	figure	figure	NOUN
brj-22962	87	4	2	2	NUM
brj-22962	87	5	-	-	PUNCT
brj-22962	87	6	c	c	NOUN
brj-22962	87	7	offers	offer	VERB
brj-22962	87	8	an	an	DET
brj-22962	87	9	insight	insight	NOUN
brj-22962	87	10	into	into	ADP
brj-22962	87	11	the	the	DET
brj-22962	87	12	distribution	distribution	NOUN
brj-22962	87	13	of	of	ADP
brj-22962	87	14	coordinates	coordinate	NOUN
brj-22962	87	15	for	for	ADP
brj-22962	87	16	the	the	DET
brj-22962	87	17	center	center	ADJ
brj-22962	87	18	points	point	NOUN
brj-22962	87	19	of	of	ADP
brj-22962	87	20	the	the	DET
brj-22962	87	21	bounding	bounding	NOUN
brj-22962	87	22	boxes	box	NOUN
brj-22962	87	23	for	for	ADP
brj-22962	87	24	various	various	ADJ
brj-22962	87	25	defects	defect	NOUN
brj-22962	87	26	.	.	PUNCT
brj-22962	88	1	it	it	PRON
brj-22962	88	2	appears	appear	VERB
brj-22962	88	3	that	that	SCONJ
brj-22962	88	4	the	the	DET
brj-22962	88	5	center	center	NOUN
brj-22962	88	6	points	point	NOUN
brj-22962	88	7	are	be	AUX
brj-22962	88	8	concentrated	concentrate	VERB
brj-22962	88	9	towards	towards	ADP
brj-22962	88	10	the	the	DET
brj-22962	88	11	middle	middle	NOUN
brj-22962	88	12	of	of	ADP
brj-22962	88	13	the	the	DET
brj-22962	88	14	bounding	bounding	NOUN
brj-22962	88	15	boxes	box	NOUN
brj-22962	88	16	.	.	PUNCT
brj-22962	89	1	4	4	X
brj-22962	89	2	.	.	X
brj-22962	89	3	figure	figure	NOUN
brj-22962	89	4	2	2	NUM
brj-22962	89	5	-	-	PUNCT
brj-22962	89	6	d	d	NOUN
brj-22962	89	7	displays	display	VERB
brj-22962	89	8	a	a	DET
brj-22962	89	9	scatter	scatter	NOUN
brj-22962	89	10	plot	plot	NOUN
brj-22962	89	11	showing	show	VERB
brj-22962	89	12	the	the	DET
brj-22962	89	13	relationship	relationship	NOUN
brj-22962	89	14	between	between	ADP
brj-22962	89	15	the	the	DET
brj-22962	89	16	width	width	NOUN
brj-22962	89	17	and	and	CCONJ
brj-22962	89	18	height	height	NOUN
brj-22962	89	19	of	of	ADP
brj-22962	89	20	the	the	DET
brj-22962	89	21	defective	defective	ADJ
brj-22962	89	22	bounding	bounding	NOUN
brj-22962	89	23	boxes	box	NOUN
brj-22962	89	24	.	.	PUNCT
brj-22962	90	1	the	the	DET
brj-22962	90	2	concentration	concentration	NOUN
brj-22962	90	3	of	of	ADP
brj-22962	90	4	dark	dark	ADJ
brj-22962	90	5	-	-	PUNCT
brj-22962	90	6	colored	color	VERB
brj-22962	90	7	blocks	block	NOUN
brj-22962	90	8	in	in	ADP
brj-22962	90	9	the	the	DET
brj-22962	90	10	lower	lower	ADV
brj-22962	90	11	-	-	PUNCT
brj-22962	90	12	left	leave	VERB
brj-22962	90	13	corner	corner	NOUN
brj-22962	90	14	indicates	indicate	VERB
brj-22962	90	15	that	that	SCONJ
brj-22962	90	16	small	small	ADJ
brj-22962	90	17	defects	defect	NOUN
brj-22962	90	18	constitute	constitute	VERB
brj-22962	90	19	the	the	DET
brj-22962	90	20	majority	majority	NOUN
brj-22962	90	21	of	of	ADP
brj-22962	90	22	instances	instance	NOUN
brj-22962	90	23	in	in	ADP
brj-22962	90	24	this	this	DET
brj-22962	90	25	dataset	dataset	NOUN
brj-22962	90	26	.	.	PUNCT
brj-22962	91	1	peer	peer	NOUN
brj-22962	91	2	-	-	PUNCT
brj-22962	91	3	reviewed	review	VERB
brj-22962	91	4	article	article	NOUN
brj-22962	91	5	bioresources.com	bioresources.com	X
brj-22962	91	6	wang	wang	PROPN
brj-22962	91	7	et	et	PROPN
brj-22962	91	8	al	al	PROPN
brj-22962	91	9	.	.	PROPN
brj-22962	91	10	(	(	PUNCT
brj-22962	91	11	2023	2023	NUM
brj-22962	91	12	)	)	PUNCT
brj-22962	91	13	.	.	PUNCT
brj-22962	92	1	“	"	PUNCT
brj-22962	92	2	timber	timber	NOUN
brj-22962	92	3	defect	defect	NOUN
brj-22962	92	4	i	i	PROPN
brj-22962	92	5	d	d	PROPN
brj-22962	92	6	algorithms	algorithm	NOUN
brj-22962	92	7	,	,	PUNCT
brj-22962	92	8	”	"	PUNCT
brj-22962	92	9	bioresources	bioresource	NOUN
brj-22962	92	10	18(4	18(4	NUM
brj-22962	92	11	)	)	PUNCT
brj-22962	92	12	,	,	PUNCT
brj-22962	92	13	8444	8444	NUM
brj-22962	92	14	-	-	SYM
brj-22962	92	15	8457	8457	NUM
brj-22962	92	16	.	.	PUNCT
brj-22962	93	1	8448	8448	NUM
brj-22962	93	2	(	(	PUNCT
brj-22962	93	3	a	a	NOUN
brj-22962	93	4	)	)	PUNCT
brj-22962	93	5	(	(	PUNCT
brj-22962	93	6	b	b	X
brj-22962	93	7	)	)	PUNCT
brj-22962	93	8	(	(	PUNCT
brj-22962	93	9	c	c	X
brj-22962	93	10	)	)	PUNCT
brj-22962	93	11	(	(	PUNCT
brj-22962	93	12	d	d	X
brj-22962	93	13	)	)	PUNCT
brj-22962	93	14	fig	fig	NOUN
brj-22962	93	15	.	.	PUNCT
brj-22962	94	1	2	2	X
brj-22962	94	2	.	.	X
brj-22962	94	3	dataset	dataset	NOUN
brj-22962	94	4	infographic	infographic	ADJ
brj-22962	94	5	these	these	DET
brj-22962	94	6	visualizations	visualization	NOUN
brj-22962	94	7	provide	provide	VERB
brj-22962	94	8	valuable	valuable	ADJ
brj-22962	94	9	information	information	NOUN
brj-22962	94	10	about	about	ADP
brj-22962	94	11	the	the	DET
brj-22962	94	12	composition	composition	NOUN
brj-22962	94	13	and	and	CCONJ
brj-22962	94	14	characteristics	characteristic	NOUN
brj-22962	94	15	of	of	ADP
brj-22962	94	16	the	the	DET
brj-22962	94	17	dataset	dataset	NOUN
brj-22962	94	18	,	,	PUNCT
brj-22962	94	19	highlighting	highlight	VERB
brj-22962	94	20	the	the	DET
brj-22962	94	21	prevalence	prevalence	NOUN
brj-22962	94	22	of	of	ADP
brj-22962	94	23	certain	certain	ADJ
brj-22962	94	24	defect	defect	NOUN
brj-22962	94	25	types	type	NOUN
brj-22962	94	26	and	and	CCONJ
brj-22962	94	27	their	their	PRON
brj-22962	94	28	size	size	NOUN
brj-22962	94	29	distribution	distribution	NOUN
brj-22962	94	30	.	.	PUNCT
brj-22962	95	1	tsw	tsw	PROPN
brj-22962	95	2	-	-	PUNCT
brj-22962	95	3	yolo	yolo	NOUN
brj-22962	95	4	-	-	PUNCT
brj-22962	95	5	v8n	v8n	PROPN
brj-22962	95	6	the	the	DET
brj-22962	95	7	yolo	yolo	PROPN
brj-22962	95	8	-	-	PUNCT
brj-22962	95	9	v8	v8	PROPN
brj-22962	95	10	model	model	NOUN
brj-22962	95	11	represents	represent	VERB
brj-22962	95	12	a	a	DET
brj-22962	95	13	significant	significant	ADJ
brj-22962	95	14	advancement	advancement	NOUN
brj-22962	95	15	in	in	ADP
brj-22962	95	16	object	object	NOUN
brj-22962	95	17	detection	detection	NOUN
brj-22962	95	18	and	and	CCONJ
brj-22962	95	19	instance	instance	NOUN
brj-22962	95	20	segmentation	segmentation	NOUN
brj-22962	95	21	,	,	PUNCT
brj-22962	95	22	building	build	VERB
brj-22962	95	23	upon	upon	SCONJ
brj-22962	95	24	the	the	DET
brj-22962	95	25	foundations	foundation	NOUN
brj-22962	95	26	of	of	ADP
brj-22962	95	27	the	the	DET
brj-22962	95	28	previously	previously	ADV
brj-22962	95	29	introduced	introduce	VERB
brj-22962	95	30	yolov5	yolov5	NOUN
brj-22962	95	31	by	by	ADP
brj-22962	95	32	ultralytics	ultralytic	NOUN
brj-22962	95	33	at	at	ADP
brj-22962	95	34	the	the	DET
brj-22962	95	35	beginning	beginning	NOUN
brj-22962	95	36	of	of	ADP
brj-22962	95	37	2023	2023	NUM
brj-22962	95	38	.	.	PUNCT
brj-22962	96	1	yolo	yolo	PROPN
brj-22962	96	2	-	-	PUNCT
brj-22962	96	3	v8	v8	PROPN
brj-22962	96	4	not	not	PART
brj-22962	96	5	only	only	ADV
brj-22962	96	6	achieves	achieve	VERB
brj-22962	96	7	enhanced	enhance	VERB
brj-22962	96	8	speed	speed	NOUN
brj-22962	96	9	and	and	CCONJ
brj-22962	96	10	accuracy	accuracy	NOUN
brj-22962	96	11	compared	compare	VERB
brj-22962	96	12	to	to	ADP
brj-22962	96	13	its	its	PRON
brj-22962	96	14	predecessors	predecessor	NOUN
brj-22962	96	15	but	but	CCONJ
brj-22962	96	16	also	also	ADV
brj-22962	96	17	extends	extend	VERB
brj-22962	96	18	its	its	PRON
brj-22962	96	19	capabilities	capability	NOUN
brj-22962	96	20	to	to	PART
brj-22962	96	21	support	support	VERB
brj-22962	96	22	a	a	DET
brj-22962	96	23	range	range	NOUN
brj-22962	96	24	of	of	ADP
brj-22962	96	25	tasks	task	NOUN
brj-22962	96	26	,	,	PUNCT
brj-22962	96	27	including	include	VERB
brj-22962	96	28	image	image	NOUN
brj-22962	96	29	classification	classification	NOUN
brj-22962	96	30	,	,	PUNCT
brj-22962	96	31	object	object	NOUN
brj-22962	96	32	detection	detection	NOUN
brj-22962	96	33	,	,	PUNCT
brj-22962	96	34	and	and	CCONJ
brj-22962	96	35	instance	instance	NOUN
brj-22962	96	36	segmentation	segmentation	NOUN
brj-22962	96	37	.	.	PUNCT
brj-22962	97	1	this	this	PRON
brj-22962	97	2	makes	make	VERB
brj-22962	97	3	it	it	PRON
brj-22962	97	4	a	a	DET
brj-22962	97	5	versatile	versatile	ADJ
brj-22962	97	6	and	and	CCONJ
brj-22962	97	7	high	high	ADJ
brj-22962	97	8	-	-	PUNCT
brj-22962	97	9	performance	performance	NOUN
brj-22962	97	10	algorithmic	algorithmic	ADJ
brj-22962	97	11	model	model	NOUN
brj-22962	97	12	suitable	suitable	ADJ
brj-22962	97	13	for	for	ADP
brj-22962	97	14	multitasking	multitaske	VERB
brj-22962	97	15	scenarios	scenario	NOUN
brj-22962	97	16	.	.	PUNCT
brj-22962	98	1	for	for	ADP
brj-22962	98	2	this	this	DET
brj-22962	98	3	paper	paper	NOUN
brj-22962	98	4	’s	’s	PART
brj-22962	98	5	objectives	objective	NOUN
brj-22962	98	6	,	,	PUNCT
brj-22962	98	7	yolo	yolo	NOUN
brj-22962	98	8	-	-	PUNCT
brj-22962	98	9	v8n	v8n	PROPN
brj-22962	98	10	was	be	AUX
brj-22962	98	11	chosen	choose	VERB
brj-22962	98	12	as	as	ADP
brj-22962	98	13	the	the	DET
brj-22962	98	14	base	base	NOUN
brj-22962	98	15	model	model	NOUN
brj-22962	98	16	for	for	ADP
brj-22962	98	17	enhancement	enhancement	NOUN
brj-22962	98	18	,	,	PUNCT
brj-22962	98	19	considering	consider	VERB
brj-22962	98	20	practical	practical	ADJ
brj-22962	98	21	real	real	ADJ
brj-22962	98	22	-	-	PUNCT
brj-22962	98	23	world	world	NOUN
brj-22962	98	24	considerations	consideration	NOUN
brj-22962	98	25	.	.	PUNCT
brj-22962	99	1	yolo	yolo	PROPN
brj-22962	99	2	-	-	PUNCT
brj-22962	99	3	v8n	v8n	PROPN
brj-22962	99	4	was	be	AUX
brj-22962	99	5	selected	select	VERB
brj-22962	99	6	because	because	SCONJ
brj-22962	99	7	it	it	PRON
brj-22962	99	8	offers	offer	VERB
brj-22962	99	9	a	a	DET
brj-22962	99	10	relatively	relatively	ADV
brj-22962	99	11	small	small	ADJ
brj-22962	99	12	pre	pre	ADJ
brj-22962	99	13	-	-	ADJ
brj-22962	99	14	training	training	ADJ
brj-22962	99	15	model	model	NOUN
brj-22962	99	16	size	size	NOUN
brj-22962	99	17	of	of	ADP
brj-22962	99	18	only	only	ADV
brj-22962	99	19	6	6	NUM
brj-22962	99	20	mb	mb	NOUN
brj-22962	99	21	,	,	PUNCT
brj-22962	99	22	making	make	VERB
brj-22962	99	23	it	it	PRON
brj-22962	99	24	suitable	suitable	ADJ
brj-22962	99	25	for	for	ADP
brj-22962	99	26	deployment	deployment	NOUN
brj-22962	99	27	on	on	ADP
brj-22962	99	28	mobile	mobile	ADJ
brj-22962	99	29	devices	device	NOUN
brj-22962	99	30	,	,	PUNCT
brj-22962	99	31	while	while	SCONJ
brj-22962	99	32	also	also	ADV
brj-22962	99	33	maintaining	maintain	VERB
brj-22962	99	34	a	a	DET
brj-22962	99	35	fast	fast	ADJ
brj-22962	99	36	detection	detection	NOUN
brj-22962	99	37	speed	speed	NOUN
brj-22962	99	38	.	.	PUNCT
brj-22962	100	1	however	however	ADV
brj-22962	100	2	,	,	PUNCT
brj-22962	100	3	yolo	yolo	ADJ
brj-22962	100	4	-	-	PUNCT
brj-22962	100	5	v8n	v8n	PROPN
brj-22962	100	6	’s	’s	PART
brj-22962	100	7	detection	detection	NOUN
brj-22962	100	8	performance	performance	NOUN
brj-22962	100	9	,	,	PUNCT
brj-22962	100	10	although	although	SCONJ
brj-22962	100	11	fast	fast	ADV
brj-22962	100	12	,	,	PUNCT
brj-22962	100	13	does	do	AUX
brj-22962	100	14	not	not	PART
brj-22962	100	15	meet	meet	VERB
brj-22962	100	16	the	the	DET
brj-22962	100	17	rigorous	rigorous	ADJ
brj-22962	100	18	requirements	requirement	NOUN
brj-22962	100	19	of	of	ADP
brj-22962	100	20	factory	factory	NOUN
brj-22962	100	21	applications	application	NOUN
brj-22962	100	22	when	when	SCONJ
brj-22962	100	23	it	it	PRON
brj-22962	100	24	comes	come	VERB
brj-22962	100	25	to	to	ADP
brj-22962	100	26	detecting	detect	VERB
brj-22962	100	27	surface	surface	NOUN
brj-22962	100	28	defects	defect	NOUN
brj-22962	100	29	on	on	ADP
brj-22962	100	30	sawn	sawn	ADJ
brj-22962	100	31	timber	timber	NOUN
brj-22962	100	32	.	.	PUNCT
brj-22962	101	1	to	to	PART
brj-22962	101	2	address	address	VERB
brj-22962	101	3	this	this	PRON
brj-22962	101	4	,	,	PUNCT
brj-22962	101	5	this	this	DET
brj-22962	101	6	paper	paper	NOUN
brj-22962	101	7	introduces	introduce	VERB
brj-22962	101	8	four	four	NUM
brj-22962	101	9	key	key	ADJ
brj-22962	101	10	improvements	improvement	NOUN
brj-22962	101	11	to	to	ADP
brj-22962	101	12	yolov8	yolov8	PROPN
brj-22962	101	13	,	,	PUNCT
brj-22962	101	14	resulting	result	VERB
brj-22962	101	15	in	in	ADP
brj-22962	101	16	the	the	DET
brj-22962	101	17	development	development	NOUN
brj-22962	101	18	of	of	ADP
brj-22962	101	19	an	an	DET
brj-22962	101	20	advanced	advanced	ADJ
brj-22962	101	21	intelligent	intelligent	ADJ
brj-22962	101	22	detection	detection	NOUN
brj-22962	101	23	model	model	NOUN
brj-22962	101	24	called	call	VERB
brj-22962	101	25	tswyolo	tswyolo	NOUN
brj-22962	101	26	-	-	PUNCT
brj-22962	101	27	v8n	v8n	NOUN
brj-22962	101	28	.	.	PUNCT
brj-22962	102	1	these	these	DET
brj-22962	102	2	enhancements	enhancement	NOUN
brj-22962	102	3	encompass	encompass	VERB
brj-22962	102	4	the	the	DET
brj-22962	102	5	addition	addition	NOUN
brj-22962	102	6	of	of	ADP
brj-22962	102	7	a	a	DET
brj-22962	102	8	tiny	tiny	ADJ
brj-22962	102	9	target	target	NOUN
brj-22962	102	10	detection	detection	NOUN
brj-22962	102	11	head	head	NOUN
brj-22962	102	12	,	,	PUNCT
brj-22962	102	13	the	the	DET
brj-22962	102	14	incorporation	incorporation	NOUN
brj-22962	102	15	of	of	ADP
brj-22962	102	16	an	an	DET
brj-22962	102	17	attention	attention	NOUN
brj-22962	102	18	mechanism	mechanism	NOUN
brj-22962	102	19	,	,	PUNCT
brj-22962	102	20	the	the	DET
brj-22962	102	21	integration	integration	NOUN
brj-22962	102	22	of	of	ADP
brj-22962	102	23	a	a	DET
brj-22962	102	24	feature	feature	NOUN
brj-22962	102	25	fusion	fusion	NOUN
brj-22962	102	26	mechanism	mechanism	NOUN
brj-22962	102	27	,	,	PUNCT
brj-22962	102	28	and	and	CCONJ
brj-22962	102	29	the	the	DET
brj-22962	102	30	optimization	optimization	NOUN
brj-22962	102	31	of	of	ADP
brj-22962	102	32	the	the	DET
brj-22962	102	33	loss	loss	NOUN
brj-22962	102	34	function	function	NOUN
brj-22962	102	35	.	.	PUNCT
brj-22962	103	1	the	the	DET
brj-22962	103	2	schematic	schematic	ADJ
brj-22962	103	3	structure	structure	NOUN
brj-22962	103	4	of	of	ADP
brj-22962	103	5	the	the	DET
brj-22962	103	6	improved	improve	VERB
brj-22962	103	7	tswyolo	tswyolo	NOUN
brj-22962	103	8	-	-	PUNCT
brj-22962	103	9	v8n	v8n	NUM
brj-22962	103	10	model	model	NOUN
brj-22962	103	11	is	be	AUX
brj-22962	103	12	visually	visually	ADV
brj-22962	103	13	depicted	depict	VERB
brj-22962	103	14	in	in	ADP
brj-22962	103	15	fig	fig	NOUN
brj-22962	103	16	.	.	PUNCT
brj-22962	104	1	3	3	NUM
brj-22962	104	2	,	,	PUNCT
brj-22962	104	3	showcasing	showcase	VERB
brj-22962	104	4	the	the	DET
brj-22962	104	5	novel	novel	ADJ
brj-22962	104	6	architecture	architecture	NOUN
brj-22962	104	7	designed	design	VERB
brj-22962	104	8	to	to	PART
brj-22962	104	9	achieve	achieve	VERB
brj-22962	104	10	superior	superior	ADJ
brj-22962	104	11	performance	performance	NOUN
brj-22962	104	12	in	in	ADP
brj-22962	104	13	the	the	DET
brj-22962	104	14	detection	detection	NOUN
brj-22962	104	15	of	of	ADP
brj-22962	104	16	surface	surface	NOUN
brj-22962	104	17	defects	defect	NOUN
brj-22962	104	18	in	in	ADP
brj-22962	104	19	sawn	sawn	ADJ
brj-22962	104	20	timber	timber	NOUN
brj-22962	104	21	.	.	PUNCT
brj-22962	105	1	peer	peer	NOUN
brj-22962	105	2	-	-	PUNCT
brj-22962	105	3	reviewed	review	VERB
brj-22962	105	4	article	article	NOUN
brj-22962	105	5	bioresources.com	bioresources.com	X
brj-22962	105	6	wang	wang	PROPN
brj-22962	105	7	et	et	PROPN
brj-22962	105	8	al	al	PROPN
brj-22962	105	9	.	.	PROPN
brj-22962	105	10	(	(	PUNCT
brj-22962	105	11	2023	2023	NUM
brj-22962	105	12	)	)	PUNCT
brj-22962	105	13	.	.	PUNCT
brj-22962	106	1	“	"	PUNCT
brj-22962	106	2	timber	timber	NOUN
brj-22962	106	3	defect	defect	NOUN
brj-22962	106	4	i	i	PROPN
brj-22962	106	5	d	d	PROPN
brj-22962	106	6	algorithms	algorithm	NOUN
brj-22962	106	7	,	,	PUNCT
brj-22962	106	8	”	"	PUNCT
brj-22962	106	9	bioresources	bioresource	NOUN
brj-22962	106	10	18(4	18(4	NUM
brj-22962	106	11	)	)	PUNCT
brj-22962	106	12	,	,	PUNCT
brj-22962	106	13	8444	8444	NUM
brj-22962	106	14	-	-	SYM
brj-22962	106	15	8457	8457	NUM
brj-22962	106	16	.	.	PUNCT
brj-22962	107	1	8449	8449	NUM
brj-22962	107	2	fig	fig	NOUN
brj-22962	107	3	.	.	PUNCT
brj-22962	108	1	3	3	X
brj-22962	108	2	.	.	X
brj-22962	108	3	tsw	tsw	PROPN
brj-22962	108	4	-	-	PUNCT
brj-22962	108	5	yolo	yolo	ADJ
brj-22962	108	6	-	-	PUNCT
brj-22962	108	7	v8n	v8n	PROPN
brj-22962	108	8	structure	structure	NOUN
brj-22962	108	9	diagram	diagram	NOUN
brj-22962	108	10	small	small	ADJ
brj-22962	108	11	target	target	NOUN
brj-22962	108	12	detection	detection	NOUN
brj-22962	108	13	head	head	NOUN
brj-22962	108	14	to	to	PART
brj-22962	108	15	enhance	enhance	VERB
brj-22962	108	16	the	the	DET
brj-22962	108	17	yolov8	yolov8	PROPN
brj-22962	108	18	model	model	PROPN
brj-22962	108	19	’s	’s	PART
brj-22962	108	20	capability	capability	NOUN
brj-22962	108	21	for	for	ADP
brj-22962	108	22	detecting	detect	VERB
brj-22962	108	23	small	small	ADJ
brj-22962	108	24	targets	target	NOUN
brj-22962	108	25	,	,	PUNCT
brj-22962	108	26	a	a	DET
brj-22962	108	27	novel	novel	ADJ
brj-22962	108	28	small	small	ADJ
brj-22962	108	29	-	-	PUNCT
brj-22962	108	30	target	target	NOUN
brj-22962	108	31	detection	detection	NOUN
brj-22962	108	32	head	head	NOUN
brj-22962	108	33	was	be	AUX
brj-22962	108	34	introduced	introduce	VERB
brj-22962	108	35	in	in	ADP
brj-22962	108	36	response	response	NOUN
brj-22962	108	37	to	to	ADP
brj-22962	108	38	the	the	DET
brj-22962	108	39	specific	specific	ADJ
brj-22962	108	40	requirements	requirement	NOUN
brj-22962	108	41	of	of	ADP
brj-22962	108	42	this	this	DET
brj-22962	108	43	paper	paper	NOUN
brj-22962	108	44	’s	’s	PART
brj-22962	108	45	dataset	dataset	NOUN
brj-22962	108	46	.	.	PUNCT
brj-22962	109	1	this	this	DET
brj-22962	109	2	new	new	ADJ
brj-22962	109	3	detection	detection	NOUN
brj-22962	109	4	head	head	NOUN
brj-22962	109	5	is	be	AUX
brj-22962	109	6	seamlessly	seamlessly	ADV
brj-22962	109	7	integrated	integrate	VERB
brj-22962	109	8	with	with	ADP
brj-22962	109	9	bi	bi	ADJ
brj-22962	109	10	-	-	ADJ
brj-22962	109	11	fpn	fpn	ADJ
brj-22962	109	12	features	feature	NOUN
brj-22962	109	13	,	,	PUNCT
brj-22962	109	14	effectively	effectively	ADV
brj-22962	109	15	bolstering	bolster	VERB
brj-22962	109	16	the	the	DET
brj-22962	109	17	model	model	NOUN
brj-22962	109	18	's	's	PART
brj-22962	109	19	performance	performance	NOUN
brj-22962	109	20	when	when	SCONJ
brj-22962	109	21	it	it	PRON
brj-22962	109	22	comes	come	VERB
brj-22962	109	23	to	to	ADP
brj-22962	109	24	detecting	detect	VERB
brj-22962	109	25	small	small	ADJ
brj-22962	109	26	targets	target	NOUN
brj-22962	109	27	.	.	PUNCT
brj-22962	110	1	this	this	DET
brj-22962	110	2	strategic	strategic	ADJ
brj-22962	110	3	addition	addition	NOUN
brj-22962	110	4	and	and	CCONJ
brj-22962	110	5	fusion	fusion	NOUN
brj-22962	110	6	of	of	ADP
brj-22962	110	7	features	feature	NOUN
brj-22962	110	8	cater	cater	NOUN
brj-22962	110	9	to	to	ADP
brj-22962	110	10	the	the	DET
brj-22962	110	11	unique	unique	ADJ
brj-22962	110	12	characteristics	characteristic	NOUN
brj-22962	110	13	of	of	ADP
brj-22962	110	14	the	the	DET
brj-22962	110	15	dataset	dataset	NOUN
brj-22962	110	16	,	,	PUNCT
brj-22962	110	17	ensuring	ensure	VERB
brj-22962	110	18	that	that	SCONJ
brj-22962	110	19	the	the	DET
brj-22962	110	20	model	model	NOUN
brj-22962	110	21	excels	excel	VERB
brj-22962	110	22	in	in	ADP
brj-22962	110	23	identifying	identify	VERB
brj-22962	110	24	and	and	CCONJ
brj-22962	110	25	accurately	accurately	ADV
brj-22962	110	26	detecting	detect	VERB
brj-22962	110	27	small	small	ADJ
brj-22962	110	28	targets	target	NOUN
brj-22962	110	29	,	,	PUNCT
brj-22962	110	30	further	far	ADV
brj-22962	110	31	enhancing	enhance	VERB
brj-22962	110	32	its	its	PRON
brj-22962	110	33	overall	overall	ADJ
brj-22962	110	34	detection	detection	NOUN
brj-22962	110	35	performance	performance	NOUN
brj-22962	110	36	.	.	PUNCT
brj-22962	111	1	triplet	triplet	NOUN
brj-22962	111	2	attention	attention	NOUN
brj-22962	111	3	mechanism	mechanism	NOUN
brj-22962	111	4	wood	wood	NOUN
brj-22962	111	5	,	,	PUNCT
brj-22962	111	6	as	as	ADP
brj-22962	111	7	a	a	DET
brj-22962	111	8	natural	natural	ADJ
brj-22962	111	9	plant	plant	NOUN
brj-22962	111	10	material	material	NOUN
brj-22962	111	11	,	,	PUNCT
brj-22962	111	12	exhibits	exhibit	VERB
brj-22962	111	13	a	a	DET
brj-22962	111	14	significant	significant	ADJ
brj-22962	111	15	challenge	challenge	NOUN
brj-22962	111	16	in	in	ADP
brj-22962	111	17	defect	defect	NOUN
brj-22962	111	18	detection	detection	NOUN
brj-22962	111	19	due	due	ADP
brj-22962	111	20	to	to	ADP
brj-22962	111	21	the	the	DET
brj-22962	111	22	seamless	seamless	ADJ
brj-22962	111	23	integration	integration	NOUN
brj-22962	111	24	of	of	ADP
brj-22962	111	25	defects	defect	NOUN
brj-22962	111	26	with	with	ADP
brj-22962	111	27	the	the	DET
brj-22962	111	28	wood	wood	NOUN
brj-22962	111	29	itself	itself	PRON
brj-22962	111	30	.	.	PUNCT
brj-22962	112	1	sawn	sawn	NOUN
brj-22962	112	2	timber	timber	NOUN
brj-22962	112	3	defects	defect	NOUN
brj-22962	112	4	often	often	ADV
brj-22962	112	5	blend	blend	VERB
brj-22962	112	6	into	into	ADP
brj-22962	112	7	the	the	DET
brj-22962	112	8	background	background	NOUN
brj-22962	112	9	,	,	PUNCT
brj-22962	112	10	making	make	VERB
brj-22962	112	11	them	they	PRON
brj-22962	112	12	challenging	challenge	VERB
brj-22962	112	13	to	to	PART
brj-22962	112	14	detect	detect	VERB
brj-22962	112	15	.	.	PUNCT
brj-22962	113	1	to	to	PART
brj-22962	113	2	address	address	VERB
brj-22962	113	3	this	this	DET
brj-22962	113	4	issue	issue	NOUN
brj-22962	113	5	,	,	PUNCT
brj-22962	113	6	the	the	DET
brj-22962	113	7	triplet	triplet	NOUN
brj-22962	113	8	attention	attention	NOUN
brj-22962	113	9	mechanism	mechanism	NOUN
brj-22962	113	10	is	be	AUX
brj-22962	113	11	introduced	introduce	VERB
brj-22962	113	12	to	to	PART
brj-22962	113	13	enhance	enhance	VERB
brj-22962	113	14	the	the	DET
brj-22962	113	15	yolo	yolo	ADJ
brj-22962	113	16	-	-	PUNCT
brj-22962	113	17	v8	v8	PROPN
brj-22962	113	18	model	model	NOUN
brj-22962	113	19	’s	’s	PART
brj-22962	113	20	ability	ability	NOUN
brj-22962	113	21	to	to	PART
brj-22962	113	22	capture	capture	VERB
brj-22962	113	23	information	information	NOUN
brj-22962	113	24	interactions	interaction	NOUN
brj-22962	113	25	across	across	ADP
brj-22962	113	26	different	different	ADJ
brj-22962	113	27	dimensions	dimension	NOUN
brj-22962	113	28	.	.	PUNCT
brj-22962	114	1	this	this	DET
brj-22962	114	2	augmentation	augmentation	NOUN
brj-22962	114	3	aims	aim	VERB
brj-22962	114	4	to	to	PART
brj-22962	114	5	improve	improve	VERB
brj-22962	114	6	the	the	DET
brj-22962	114	7	model	model	NOUN
brj-22962	114	8	's	's	PART
brj-22962	114	9	capacity	capacity	NOUN
brj-22962	114	10	to	to	PART
brj-22962	114	11	detect	detect	VERB
brj-22962	114	12	defects	defect	NOUN
brj-22962	114	13	when	when	SCONJ
brj-22962	114	14	they	they	PRON
brj-22962	114	15	are	be	AUX
brj-22962	114	16	intertwined	intertwine	VERB
brj-22962	114	17	with	with	ADP
brj-22962	114	18	the	the	DET
brj-22962	114	19	texture	texture	ADJ
brj-22962	114	20	background	background	NOUN
brj-22962	114	21	of	of	ADP
brj-22962	114	22	sawn	sawn	NOUN
brj-22962	114	23	timber	timber	NOUN
brj-22962	114	24	.	.	PUNCT
brj-22962	115	1	furthermore	furthermore	ADV
brj-22962	115	2	,	,	PUNCT
brj-22962	115	3	the	the	DET
brj-22962	115	4	triplet	triplet	NOUN
brj-22962	115	5	attention	attention	NOUN
brj-22962	115	6	mechanism	mechanism	NOUN
brj-22962	115	7	is	be	AUX
brj-22962	115	8	engineered	engineer	VERB
brj-22962	115	9	to	to	PART
brj-22962	115	10	be	be	AUX
brj-22962	115	11	computationally	computationally	ADV
brj-22962	115	12	efficient	efficient	ADJ
brj-22962	115	13	while	while	SCONJ
brj-22962	115	14	delivering	deliver	VERB
brj-22962	115	15	substantial	substantial	ADJ
brj-22962	115	16	performance	performance	NOUN
brj-22962	115	17	improvements	improvement	NOUN
brj-22962	115	18	.	.	PUNCT
brj-22962	116	1	this	this	DET
brj-22962	116	2	efficiency	efficiency	NOUN
brj-22962	116	3	aligns	align	VERB
brj-22962	116	4	with	with	ADP
brj-22962	116	5	the	the	DET
brj-22962	116	6	practical	practical	ADJ
brj-22962	116	7	requirements	requirement	NOUN
brj-22962	116	8	of	of	ADP
brj-22962	116	9	the	the	DET
brj-22962	116	10	enhanced	enhance	VERB
brj-22962	116	11	yolo	yolo	PROPN
brj-22962	116	12	-	-	PUNCT
brj-22962	116	13	v8	v8	PROPN
brj-22962	116	14	model	model	NOUN
brj-22962	116	15	,	,	PUNCT
brj-22962	116	16	particularly	particularly	ADV
brj-22962	116	17	for	for	ADP
brj-22962	116	18	the	the	DET
brj-22962	116	19	deployment	deployment	NOUN
brj-22962	116	20	of	of	ADP
brj-22962	116	21	mobile	mobile	ADJ
brj-22962	116	22	inspection	inspection	NOUN
brj-22962	116	23	devices	device	NOUN
brj-22962	116	24	.	.	PUNCT
brj-22962	117	1	in	in	ADP
brj-22962	117	2	this	this	DET
brj-22962	117	3	paper	paper	NOUN
brj-22962	117	4	,	,	PUNCT
brj-22962	117	5	the	the	DET
brj-22962	117	6	triplet	triplet	NOUN
brj-22962	117	7	attention	attention	NOUN
brj-22962	117	8	mechanism	mechanism	NOUN
brj-22962	117	9	is	be	AUX
brj-22962	117	10	integrated	integrate	VERB
brj-22962	117	11	after	after	ADP
brj-22962	117	12	the	the	DET
brj-22962	117	13	last	last	ADJ
brj-22962	117	14	c2f	c2f	NOUN
brj-22962	117	15	module	module	NOUN
brj-22962	117	16	of	of	ADP
brj-22962	117	17	the	the	DET
brj-22962	117	18	yolo	yolo	PROPN
brj-22962	117	19	-	-	PUNCT
brj-22962	117	20	v8	v8	PROPN
brj-22962	117	21	backbone	backbone	NOUN
brj-22962	117	22	network	network	NOUN
brj-22962	117	23	.	.	PUNCT
brj-22962	118	1	this	this	DET
brj-22962	118	2	strategic	strategic	ADJ
brj-22962	118	3	placement	placement	NOUN
brj-22962	118	4	addresses	address	VERB
brj-22962	118	5	the	the	DET
brj-22962	118	6	challenge	challenge	NOUN
brj-22962	118	7	of	of	ADP
brj-22962	118	8	defects	defect	NOUN
brj-22962	118	9	blending	blend	VERB
brj-22962	118	10	into	into	ADP
brj-22962	118	11	the	the	DET
brj-22962	118	12	background	background	NOUN
brj-22962	118	13	,	,	PUNCT
brj-22962	118	14	redirecting	redirect	VERB
brj-22962	118	15	the	the	DET
brj-22962	118	16	network	network	NOUN
brj-22962	118	17	's	's	PART
brj-22962	118	18	attention	attention	NOUN
brj-22962	118	19	towards	towards	ADP
brj-22962	118	20	surface	surface	NOUN
brj-22962	118	21	defects	defect	NOUN
brj-22962	118	22	on	on	ADP
brj-22962	118	23	sawn	sawn	NOUN
brj-22962	118	24	timber	timber	NOUN
brj-22962	118	25	and	and	CCONJ
brj-22962	118	26	effectively	effectively	ADV
brj-22962	118	27	separating	separate	VERB
brj-22962	118	28	them	they	PRON
brj-22962	118	29	from	from	ADP
brj-22962	118	30	the	the	DET
brj-22962	118	31	background	background	NOUN
brj-22962	118	32	during	during	ADP
brj-22962	118	33	the	the	DET
brj-22962	118	34	inspection	inspection	NOUN
brj-22962	118	35	task	task	NOUN
brj-22962	118	36	.	.	PUNCT
brj-22962	119	1	the	the	DET
brj-22962	119	2	schematic	schematic	ADJ
brj-22962	119	3	diagram	diagram	NOUN
brj-22962	119	4	illustrating	illustrate	VERB
brj-22962	119	5	this	this	DET
brj-22962	119	6	integration	integration	NOUN
brj-22962	119	7	is	be	AUX
brj-22962	119	8	presented	present	VERB
brj-22962	119	9	in	in	ADP
brj-22962	119	10	fig	fig	NOUN
brj-22962	119	11	.	.	PUNCT
brj-22962	120	1	4	4	NUM
brj-22962	120	2	.	.	X
brj-22962	120	3	peer	peer	NOUN
brj-22962	120	4	-	-	PUNCT
brj-22962	120	5	reviewed	review	VERB
brj-22962	120	6	article	article	NOUN
brj-22962	120	7	bioresources.com	bioresources.com	X
brj-22962	120	8	wang	wang	PROPN
brj-22962	120	9	et	et	PROPN
brj-22962	120	10	al	al	PROPN
brj-22962	120	11	.	.	PROPN
brj-22962	120	12	(	(	PUNCT
brj-22962	120	13	2023	2023	NUM
brj-22962	120	14	)	)	PUNCT
brj-22962	120	15	.	.	PUNCT
brj-22962	121	1	“	"	PUNCT
brj-22962	121	2	timber	timber	NOUN
brj-22962	121	3	defect	defect	NOUN
brj-22962	121	4	i	i	PROPN
brj-22962	121	5	d	d	PROPN
brj-22962	121	6	algorithms	algorithm	NOUN
brj-22962	121	7	,	,	PUNCT
brj-22962	121	8	”	"	PUNCT
brj-22962	121	9	bioresources	bioresource	NOUN
brj-22962	121	10	18(4	18(4	NUM
brj-22962	121	11	)	)	PUNCT
brj-22962	121	12	,	,	PUNCT
brj-22962	121	13	8444	8444	NUM
brj-22962	121	14	-	-	SYM
brj-22962	121	15	8457	8457	NUM
brj-22962	121	16	.	.	PUNCT
brj-22962	122	1	8450	8450	NUM
brj-22962	122	2	fig	fig	NOUN
brj-22962	122	3	.	.	PUNCT
brj-22962	123	1	4	4	X
brj-22962	123	2	.	.	X
brj-22962	123	3	triplet	triplet	NOUN
brj-22962	123	4	attention	attention	NOUN
brj-22962	123	5	structure	structure	NOUN
brj-22962	123	6	diagram	diagram	VERB
brj-22962	123	7	the	the	DET
brj-22962	123	8	triplet	triplet	NOUN
brj-22962	123	9	attention	attention	NOUN
brj-22962	123	10	mechanism	mechanism	NOUN
brj-22962	123	11	(	(	PUNCT
brj-22962	123	12	misra	misra	NOUN
brj-22962	123	13	et	et	PROPN
brj-22962	123	14	al	al	PROPN
brj-22962	123	15	.	.	PROPN
brj-22962	123	16	2020	2020	NUM
brj-22962	123	17	)	)	PUNCT
brj-22962	123	18	is	be	AUX
brj-22962	123	19	structured	structure	VERB
brj-22962	123	20	with	with	ADP
brj-22962	123	21	three	three	NUM
brj-22962	123	22	parallel	parallel	ADJ
brj-22962	123	23	branches	branch	NOUN
brj-22962	123	24	.	.	PUNCT
brj-22962	124	1	two	two	NUM
brj-22962	124	2	of	of	ADP
brj-22962	124	3	these	these	DET
brj-22962	124	4	branches	branch	NOUN
brj-22962	124	5	are	be	AUX
brj-22962	124	6	responsible	responsible	ADJ
brj-22962	124	7	for	for	ADP
brj-22962	124	8	capturing	capture	VERB
brj-22962	124	9	interactions	interaction	NOUN
brj-22962	124	10	across	across	ADP
brj-22962	124	11	different	different	ADJ
brj-22962	124	12	dimensions	dimension	NOUN
brj-22962	124	13	:	:	PUNCT
brj-22962	124	14	one	one	NUM
brj-22962	124	15	focuses	focus	VERB
brj-22962	124	16	on	on	ADP
brj-22962	124	17	interactions	interaction	NOUN
brj-22962	124	18	between	between	ADP
brj-22962	124	19	the	the	DET
brj-22962	124	20	channel	channel	NOUN
brj-22962	124	21	dimension	dimension	NOUN
brj-22962	124	22	(	(	PUNCT
brj-22962	124	23	c	c	NOUN
brj-22962	124	24	)	)	PUNCT
brj-22962	124	25	and	and	CCONJ
brj-22962	124	26	the	the	DET
brj-22962	124	27	spatial	spatial	ADJ
brj-22962	124	28	dimensions	dimension	NOUN
brj-22962	124	29	(	(	PUNCT
brj-22962	124	30	h	h	NOUN
brj-22962	124	31	or	or	CCONJ
brj-22962	124	32	w	w	NOUN
brj-22962	124	33	)	)	PUNCT
brj-22962	124	34	,	,	PUNCT
brj-22962	124	35	and	and	CCONJ
brj-22962	124	36	the	the	DET
brj-22962	124	37	last	last	ADJ
brj-22962	124	38	one	one	NOUN
brj-22962	124	39	is	be	AUX
brj-22962	124	40	used	use	VERB
brj-22962	124	41	in	in	ADP
brj-22962	124	42	the	the	DET
brj-22962	124	43	same	same	ADJ
brj-22962	124	44	way	way	NOUN
brj-22962	124	45	as	as	ADP
brj-22962	124	46	in	in	ADP
brj-22962	124	47	woo	woo	NOUN
brj-22962	124	48	et	et	PROPN
brj-22962	124	49	al	al	PROPN
brj-22962	124	50	.	.	PROPN
brj-22962	125	1	(	(	PUNCT
brj-22962	125	2	2018	2018	NUM
brj-22962	125	3	)	)	PUNCT
brj-22962	125	4	to	to	PART
brj-22962	125	5	build	build	VERB
brj-22962	125	6	spatial	spatial	ADJ
brj-22962	125	7	attention	attention	NOUN
brj-22962	125	8	.	.	PUNCT
brj-22962	126	1	the	the	DET
brj-22962	126	2	outputs	output	NOUN
brj-22962	126	3	of	of	ADP
brj-22962	126	4	all	all	DET
brj-22962	126	5	three	three	NUM
brj-22962	126	6	branches	branch	NOUN
brj-22962	126	7	were	be	AUX
brj-22962	126	8	combined	combine	VERB
brj-22962	126	9	by	by	ADP
brj-22962	126	10	averaging	average	VERB
brj-22962	126	11	their	their	PRON
brj-22962	126	12	respective	respective	ADJ
brj-22962	126	13	weights	weight	NOUN
brj-22962	126	14	and	and	CCONJ
brj-22962	126	15	then	then	ADV
brj-22962	126	16	aggregated	aggregate	VERB
brj-22962	126	17	.	.	PUNCT
brj-22962	127	1	this	this	DET
brj-22962	127	2	innovative	innovative	ADJ
brj-22962	127	3	design	design	NOUN
brj-22962	127	4	with	with	ADP
brj-22962	127	5	cross	cross	ADJ
brj-22962	127	6	-	-	ADJ
brj-22962	127	7	latitudinal	latitudinal	ADJ
brj-22962	127	8	interaction	interaction	NOUN
brj-22962	127	9	addresses	address	VERB
brj-22962	127	10	the	the	DET
brj-22962	127	11	conventional	conventional	ADJ
brj-22962	127	12	computational	computational	ADJ
brj-22962	127	13	model	model	NOUN
brj-22962	127	14	’s	’s	PART
brj-22962	127	15	challenge	challenge	NOUN
brj-22962	127	16	of	of	ADP
brj-22962	127	17	separating	separate	VERB
brj-22962	127	18	channel	channel	NOUN
brj-22962	127	19	attention	attention	NOUN
brj-22962	127	20	and	and	CCONJ
brj-22962	127	21	spatial	spatial	ADJ
brj-22962	127	22	attention	attention	NOUN
brj-22962	127	23	.	.	PUNCT
brj-22962	128	1	instead	instead	ADV
brj-22962	128	2	,	,	PUNCT
brj-22962	128	3	it	it	PRON
brj-22962	128	4	captures	capture	VERB
brj-22962	128	5	the	the	DET
brj-22962	128	6	spatial	spatial	ADJ
brj-22962	128	7	dimension	dimension	NOUN
brj-22962	128	8	’s	’s	PART
brj-22962	128	9	interaction	interaction	NOUN
brj-22962	128	10	with	with	ADP
brj-22962	128	11	the	the	DET
brj-22962	128	12	channel	channel	NOUN
brj-22962	128	13	dimension	dimension	NOUN
brj-22962	128	14	within	within	ADP
brj-22962	128	15	the	the	DET
brj-22962	128	16	same	same	ADJ
brj-22962	128	17	framework	framework	NOUN
brj-22962	128	18	.	.	PUNCT
brj-22962	129	1	in	in	ADP
brj-22962	129	2	essence	essence	NOUN
brj-22962	129	3	,	,	PUNCT
brj-22962	129	4	it	it	PRON
brj-22962	129	5	simultaneously	simultaneously	ADV
brj-22962	129	6	captures	capture	VERB
brj-22962	129	7	information	information	NOUN
brj-22962	129	8	interactions	interaction	NOUN
brj-22962	129	9	in	in	ADP
brj-22962	129	10	three	three	NUM
brj-22962	129	11	dimensions	dimension	NOUN
brj-22962	129	12	:	:	PUNCT
brj-22962	129	13	(	(	PUNCT
brj-22962	129	14	c	c	X
brj-22962	129	15	,	,	PUNCT
brj-22962	129	16	h	h	NOUN
brj-22962	129	17	)	)	PUNCT
brj-22962	129	18	,	,	PUNCT
brj-22962	129	19	(	(	PUNCT
brj-22962	129	20	c	c	X
brj-22962	129	21	,	,	PUNCT
brj-22962	129	22	w	w	NOUN
brj-22962	129	23	)	)	PUNCT
brj-22962	129	24	,	,	PUNCT
brj-22962	129	25	and	and	CCONJ
brj-22962	129	26	(	(	PUNCT
brj-22962	129	27	h	h	NOUN
brj-22962	129	28	,	,	PUNCT
brj-22962	129	29	w	w	PROPN
brj-22962	129	30	)	)	PUNCT
brj-22962	129	31	,	,	PUNCT
brj-22962	129	32	which	which	PRON
brj-22962	129	33	represent	represent	VERB
brj-22962	129	34	the	the	DET
brj-22962	129	35	interactions	interaction	NOUN
brj-22962	129	36	between	between	ADP
brj-22962	129	37	channel	channel	NOUN
brj-22962	129	38	,	,	PUNCT
brj-22962	129	39	height	height	NOUN
brj-22962	129	40	,	,	PUNCT
brj-22962	129	41	and	and	CCONJ
brj-22962	129	42	width	width	ADJ
brj-22962	129	43	dimensions	dimension	NOUN
brj-22962	129	44	of	of	ADP
brj-22962	129	45	the	the	DET
brj-22962	129	46	input	input	NOUN
brj-22962	129	47	data	datum	NOUN
brj-22962	129	48	,	,	PUNCT
brj-22962	129	49	respectively	respectively	ADV
brj-22962	129	50	.	.	PUNCT
brj-22962	130	1	bifpn	bifpn	PROPN
brj-22962	130	2	feature	feature	NOUN
brj-22962	130	3	fusion	fusion	NOUN
brj-22962	130	4	the	the	DET
brj-22962	130	5	yolo	yolo	ADJ
brj-22962	130	6	-	-	PUNCT
brj-22962	130	7	v8	v8	PROPN
brj-22962	130	8	model	model	NOUN
brj-22962	130	9	utilizes	utilize	VERB
brj-22962	130	10	the	the	DET
brj-22962	130	11	feature	feature	NOUN
brj-22962	130	12	pyramid	pyramid	NOUN
brj-22962	130	13	network	network	NOUN
brj-22962	130	14	(	(	PUNCT
brj-22962	130	15	fpn	fpn	PROPN
brj-22962	130	16	)	)	PUNCT
brj-22962	130	17	to	to	PART
brj-22962	130	18	integrate	integrate	VERB
brj-22962	130	19	multi	multi	ADJ
brj-22962	130	20	-	-	ADJ
brj-22962	130	21	scale	scale	ADJ
brj-22962	130	22	features	feature	NOUN
brj-22962	130	23	from	from	ADP
brj-22962	130	24	an	an	DET
brj-22962	130	25	image	image	NOUN
brj-22962	130	26	through	through	ADP
brj-22962	130	27	the	the	DET
brj-22962	130	28	conventional	conventional	ADJ
brj-22962	130	29	top	top	ADJ
brj-22962	130	30	-	-	PUNCT
brj-22962	130	31	down	down	ADP
brj-22962	130	32	pathway	pathway	NOUN
brj-22962	130	33	.	.	PUNCT
brj-22962	131	1	this	this	DET
brj-22962	131	2	approach	approach	NOUN
brj-22962	131	3	results	result	VERB
brj-22962	131	4	in	in	ADP
brj-22962	131	5	the	the	DET
brj-22962	131	6	generation	generation	NOUN
brj-22962	131	7	of	of	ADP
brj-22962	131	8	different	different	ADJ
brj-22962	131	9	feature	feature	NOUN
brj-22962	131	10	maps	map	NOUN
brj-22962	131	11	by	by	ADP
brj-22962	131	12	downsizing	downsize	VERB
brj-22962	131	13	the	the	DET
brj-22962	131	14	image	image	NOUN
brj-22962	131	15	,	,	PUNCT
brj-22962	131	16	allowing	allow	VERB
brj-22962	131	17	predictions	prediction	NOUN
brj-22962	131	18	to	to	PART
brj-22962	131	19	be	be	AUX
brj-22962	131	20	made	make	VERB
brj-22962	131	21	on	on	ADP
brj-22962	131	22	each	each	PRON
brj-22962	131	23	of	of	ADP
brj-22962	131	24	these	these	DET
brj-22962	131	25	feature	feature	NOUN
brj-22962	131	26	maps	map	NOUN
brj-22962	131	27	.	.	PUNCT
brj-22962	132	1	while	while	SCONJ
brj-22962	132	2	this	this	DET
brj-22962	132	3	strategy	strategy	NOUN
brj-22962	132	4	aids	aid	VERB
brj-22962	132	5	the	the	DET
brj-22962	132	6	model	model	NOUN
brj-22962	132	7	in	in	ADP
brj-22962	132	8	identifying	identify	VERB
brj-22962	132	9	targets	target	NOUN
brj-22962	132	10	of	of	ADP
brj-22962	132	11	various	various	ADJ
brj-22962	132	12	sizes	size	NOUN
brj-22962	132	13	,	,	PUNCT
brj-22962	132	14	it	it	PRON
brj-22962	132	15	comes	come	VERB
brj-22962	132	16	with	with	ADP
brj-22962	132	17	several	several	ADJ
brj-22962	132	18	drawbacks	drawback	NOUN
brj-22962	132	19	,	,	PUNCT
brj-22962	132	20	including	include	VERB
brj-22962	132	21	a	a	DET
brj-22962	132	22	high	high	ADJ
brj-22962	132	23	demand	demand	NOUN
brj-22962	132	24	for	for	ADP
brj-22962	132	25	computational	computational	ADJ
brj-22962	132	26	resources	resource	NOUN
brj-22962	132	27	,	,	PUNCT
brj-22962	132	28	sluggish	sluggish	ADJ
brj-22962	132	29	inference	inference	NOUN
brj-22962	132	30	times	time	NOUN
brj-22962	132	31	,	,	PUNCT
brj-22962	132	32	and	and	CCONJ
brj-22962	132	33	a	a	DET
brj-22962	132	34	lack	lack	NOUN
brj-22962	132	35	of	of	ADP
brj-22962	132	36	suitability	suitability	NOUN
brj-22962	132	37	for	for	ADP
brj-22962	132	38	real	real	ADJ
brj-22962	132	39	-	-	PUNCT
brj-22962	132	40	time	time	NOUN
brj-22962	132	41	detection	detection	NOUN
brj-22962	132	42	tasks	task	NOUN
brj-22962	132	43	.	.	PUNCT
brj-22962	133	1	these	these	DET
brj-22962	133	2	limitations	limitation	NOUN
brj-22962	133	3	do	do	AUX
brj-22962	133	4	not	not	PART
brj-22962	133	5	align	align	VERB
brj-22962	133	6	with	with	ADP
brj-22962	133	7	the	the	DET
brj-22962	133	8	objectives	objective	NOUN
brj-22962	133	9	of	of	ADP
brj-22962	133	10	this	this	DET
brj-22962	133	11	paper	paper	NOUN
brj-22962	133	12	.	.	PUNCT
brj-22962	134	1	to	to	PART
brj-22962	134	2	address	address	VERB
brj-22962	134	3	these	these	DET
brj-22962	134	4	challenges	challenge	NOUN
brj-22962	134	5	,	,	PUNCT
brj-22962	134	6	the	the	DET
brj-22962	134	7	paper	paper	NOUN
brj-22962	134	8	introduces	introduce	VERB
brj-22962	134	9	the	the	DET
brj-22962	134	10	bifpn	bifpn	PROPN
brj-22962	134	11	(	(	PUNCT
brj-22962	134	12	bidirectional	bidirectional	ADJ
brj-22962	134	13	feature	feature	NOUN
brj-22962	134	14	pyramid	pyramid	NOUN
brj-22962	134	15	network	network	NOUN
brj-22962	134	16	,	,	PUNCT
brj-22962	134	17	tan	tan	PROPN
brj-22962	134	18	et	et	PROPN
brj-22962	134	19	al	al	PROPN
brj-22962	134	20	.	.	PROPN
brj-22962	134	21	2020	2020	NUM
brj-22962	134	22	)	)	PUNCT
brj-22962	134	23	.	.	PUNCT
brj-22962	135	1	the	the	DET
brj-22962	135	2	bifpn	bifpn	PROPN
brj-22962	135	3	mechanism	mechanism	NOUN
brj-22962	135	4	incorporates	incorporate	VERB
brj-22962	135	5	bidirectional	bidirectional	ADJ
brj-22962	135	6	cross	cross	ADJ
brj-22962	135	7	-	-	ADJ
brj-22962	135	8	scale	scale	ADJ
brj-22962	135	9	connectivity	connectivity	NOUN
brj-22962	135	10	and	and	CCONJ
brj-22962	135	11	a	a	DET
brj-22962	135	12	weighted	weight	VERB
brj-22962	135	13	feature	feature	NOUN
brj-22962	135	14	fusion	fusion	NOUN
brj-22962	135	15	approach	approach	NOUN
brj-22962	135	16	.	.	PUNCT
brj-22962	136	1	this	this	DET
brj-22962	136	2	enhancement	enhancement	NOUN
brj-22962	136	3	not	not	PART
brj-22962	136	4	only	only	ADV
brj-22962	136	5	bolsters	bolster	VERB
brj-22962	136	6	the	the	DET
brj-22962	136	7	model	model	NOUN
brj-22962	136	8	’s	’s	PART
brj-22962	136	9	feature	feature	NOUN
brj-22962	136	10	extraction	extraction	NOUN
brj-22962	136	11	capabilities	capability	NOUN
brj-22962	136	12	but	but	CCONJ
brj-22962	136	13	also	also	ADV
brj-22962	136	14	mitigates	mitigate	VERB
brj-22962	136	15	the	the	DET
brj-22962	136	16	computational	computational	ADJ
brj-22962	136	17	resource	resource	NOUN
brj-22962	136	18	overhead	overhead	ADV
brj-22962	136	19	.	.	PUNCT
brj-22962	137	1	additionally	additionally	ADV
brj-22962	137	2	,	,	PUNCT
brj-22962	137	3	it	it	PRON
brj-22962	137	4	accelerates	accelerate	VERB
brj-22962	137	5	detection	detection	NOUN
brj-22962	137	6	speed	speed	NOUN
brj-22962	137	7	and	and	CCONJ
brj-22962	137	8	optimizes	optimize	VERB
brj-22962	137	9	the	the	DET
brj-22962	137	10	model	model	NOUN
brj-22962	137	11	’s	’s	PART
brj-22962	137	12	real	real	ADJ
brj-22962	137	13	-	-	PUNCT
brj-22962	137	14	time	time	NOUN
brj-22962	137	15	detection	detection	NOUN
brj-22962	137	16	capabilities	capability	NOUN
brj-22962	137	17	by	by	ADP
brj-22962	137	18	adjusting	adjust	VERB
brj-22962	137	19	the	the	DET
brj-22962	137	20	weights	weight	NOUN
brj-22962	137	21	and	and	CCONJ
brj-22962	137	22	finetuning	finetune	VERB
brj-22962	137	23	the	the	DET
brj-22962	137	24	contribution	contribution	NOUN
brj-22962	137	25	of	of	ADP
brj-22962	137	26	each	each	DET
brj-22962	137	27	scale	scale	NOUN
brj-22962	137	28	to	to	ADP
brj-22962	137	29	the	the	DET
brj-22962	137	30	feature	feature	NOUN
brj-22962	137	31	fusion	fusion	NOUN
brj-22962	137	32	network	network	NOUN
brj-22962	137	33	.	.	PUNCT
brj-22962	138	1	this	this	DET
brj-22962	138	2	innovation	innovation	NOUN
brj-22962	138	3	represents	represent	VERB
brj-22962	138	4	a	a	DET
brj-22962	138	5	more	more	ADV
brj-22962	138	6	efficient	efficient	ADJ
brj-22962	138	7	and	and	CCONJ
brj-22962	138	8	effective	effective	ADJ
brj-22962	138	9	approach	approach	NOUN
brj-22962	138	10	to	to	ADP
brj-22962	138	11	multi	multi	ADJ
brj-22962	138	12	-	-	ADJ
brj-22962	138	13	scale	scale	ADJ
brj-22962	138	14	feature	feature	NOUN
brj-22962	138	15	integration	integration	NOUN
brj-22962	138	16	for	for	ADP
brj-22962	138	17	improved	improved	ADJ
brj-22962	138	18	model	model	NOUN
brj-22962	138	19	performance	performance	NOUN
brj-22962	138	20	.	.	PUNCT
brj-22962	139	1	figure	figure	NOUN
brj-22962	139	2	5	5	NUM
brj-22962	139	3	vividly	vividly	ADV
brj-22962	139	4	illustrates	illustrate	VERB
brj-22962	139	5	the	the	DET
brj-22962	139	6	bipfn	bipfn	PROPN
brj-22962	139	7	(	(	PUNCT
brj-22962	139	8	bilateral	bilateral	ADJ
brj-22962	139	9	pyramid	pyramid	NOUN
brj-22962	139	10	feature	feature	NOUN
brj-22962	139	11	network	network	NOUN
brj-22962	139	12	)	)	PUNCT
brj-22962	139	13	feature	feature	NOUN
brj-22962	139	14	fusion	fusion	NOUN
brj-22962	139	15	mechanism	mechanism	NOUN
brj-22962	139	16	,	,	PUNCT
brj-22962	139	17	which	which	PRON
brj-22962	139	18	represents	represent	VERB
brj-22962	139	19	a	a	DET
brj-22962	139	20	significant	significant	ADJ
brj-22962	139	21	departure	departure	NOUN
brj-22962	139	22	from	from	ADP
brj-22962	139	23	the	the	DET
brj-22962	139	24	traditional	traditional	ADJ
brj-22962	139	25	unidirectional	unidirectional	ADJ
brj-22962	139	26	information	information	NOUN
brj-22962	139	27	flow	flow	NOUN
brj-22962	139	28	in	in	ADP
brj-22962	139	29	fpn	fpn	PROPN
brj-22962	139	30	(	(	PUNCT
brj-22962	139	31	feature	feature	NOUN
brj-22962	139	32	pyramid	pyramid	NOUN
brj-22962	139	33	network	network	NOUN
brj-22962	139	34	)	)	PUNCT
brj-22962	139	35	as	as	SCONJ
brj-22962	139	36	shown	show	VERB
brj-22962	139	37	in	in	ADP
brj-22962	139	38	(	(	PUNCT
brj-22962	139	39	a	a	NOUN
brj-22962	139	40	)	)	PUNCT
brj-22962	139	41	.	.	PUNCT
brj-22962	140	1	this	this	DET
brj-22962	140	2	innovative	innovative	ADJ
brj-22962	140	3	approach	approach	NOUN
brj-22962	140	4	is	be	AUX
brj-22962	140	5	designed	design	VERB
brj-22962	140	6	to	to	PART
brj-22962	140	7	enhance	enhance	VERB
brj-22962	140	8	the	the	DET
brj-22962	140	9	model	model	NOUN
brj-22962	140	10	’s	’s	PART
brj-22962	140	11	efficiency	efficiency	NOUN
brj-22962	140	12	by	by	ADP
brj-22962	140	13	introducing	introduce	VERB
brj-22962	140	14	an	an	DET
brj-22962	140	15	additional	additional	ADJ
brj-22962	140	16	connection	connection	NOUN
brj-22962	140	17	when	when	SCONJ
brj-22962	140	18	the	the	DET
brj-22962	140	19	original	original	ADJ
brj-22962	140	20	input	input	NOUN
brj-22962	140	21	and	and	CCONJ
brj-22962	140	22	output	output	NOUN
brj-22962	140	23	nodes	node	NOUN
brj-22962	140	24	are	be	AUX
brj-22962	140	25	at	at	ADP
brj-22962	140	26	the	the	DET
brj-22962	140	27	same	same	ADJ
brj-22962	140	28	level	level	NOUN
brj-22962	140	29	.	.	PUNCT
brj-22962	141	1	this	this	DET
brj-22962	141	2	addition	addition	NOUN
brj-22962	141	3	enables	enable	VERB
brj-22962	141	4	the	the	DET
brj-22962	141	5	fusion	fusion	NOUN
brj-22962	141	6	of	of	ADP
brj-22962	141	7	more	more	ADJ
brj-22962	141	8	features	feature	NOUN
brj-22962	141	9	with	with	ADP
brj-22962	141	10	only	only	ADV
brj-22962	141	11	a	a	DET
brj-22962	141	12	minimal	minimal	ADJ
brj-22962	141	13	increase	increase	NOUN
brj-22962	141	14	in	in	ADP
brj-22962	141	15	computational	computational	ADJ
brj-22962	141	16	cost	cost	NOUN
brj-22962	141	17	.	.	PUNCT
brj-22962	142	1	peer	peer	NOUN
brj-22962	142	2	-	-	PUNCT
brj-22962	142	3	reviewed	review	VERB
brj-22962	142	4	article	article	NOUN
brj-22962	142	5	bioresources.com	bioresources.com	X
brj-22962	142	6	wang	wang	PROPN
brj-22962	142	7	et	et	PROPN
brj-22962	142	8	al	al	PROPN
brj-22962	142	9	.	.	PROPN
brj-22962	142	10	(	(	PUNCT
brj-22962	142	11	2023	2023	NUM
brj-22962	142	12	)	)	PUNCT
brj-22962	142	13	.	.	PUNCT
brj-22962	143	1	“	"	PUNCT
brj-22962	143	2	timber	timber	NOUN
brj-22962	143	3	defect	defect	NOUN
brj-22962	143	4	i	i	PROPN
brj-22962	143	5	d	d	PROPN
brj-22962	143	6	algorithms	algorithm	NOUN
brj-22962	143	7	,	,	PUNCT
brj-22962	143	8	”	"	PUNCT
brj-22962	143	9	bioresources	bioresource	NOUN
brj-22962	143	10	18(4	18(4	NUM
brj-22962	143	11	)	)	PUNCT
brj-22962	143	12	,	,	PUNCT
brj-22962	143	13	8444	8444	NUM
brj-22962	143	14	-	-	SYM
brj-22962	143	15	8457	8457	NUM
brj-22962	143	16	.	.	PUNCT
brj-22962	143	17	8451	8451	NUM
brj-22962	143	18	fig	fig	NOUN
brj-22962	143	19	.	.	PUNCT
brj-22962	144	1	5	5	NUM
brj-22962	144	2	.	.	X
brj-22962	144	3	bifpn	bifpn	PROPN
brj-22962	144	4	and	and	CCONJ
brj-22962	144	5	pfn	pfn	PROPN
brj-22962	144	6	structure	structure	NOUN
brj-22962	144	7	comparison	comparison	NOUN
brj-22962	144	8	diagram	diagram	NOUN
brj-22962	144	9	moreover	moreover	ADV
brj-22962	144	10	,	,	PUNCT
brj-22962	144	11	the	the	DET
brj-22962	144	12	bipfn	bipfn	NOUN
brj-22962	144	13	framework	framework	NOUN
brj-22962	144	14	incorporates	incorporate	VERB
brj-22962	144	15	both	both	PRON
brj-22962	144	16	top	top	ADJ
brj-22962	144	17	-	-	PUNCT
brj-22962	144	18	down	down	NOUN
brj-22962	144	19	and	and	CCONJ
brj-22962	144	20	bottom	bottom	NOUN
brj-22962	144	21	-	-	PUNCT
brj-22962	144	22	up	up	ADP
brj-22962	144	23	pathways	pathway	NOUN
brj-22962	144	24	,	,	PUNCT
brj-22962	144	25	which	which	PRON
brj-22962	144	26	are	be	AUX
brj-22962	144	27	considered	consider	VERB
brj-22962	144	28	as	as	ADP
brj-22962	144	29	feature	feature	NOUN
brj-22962	144	30	network	network	NOUN
brj-22962	144	31	layers	layer	NOUN
brj-22962	144	32	that	that	PRON
brj-22962	144	33	are	be	AUX
brj-22962	144	34	recurrently	recurrently	ADV
brj-22962	144	35	activated	activate	VERB
brj-22962	144	36	.	.	PUNCT
brj-22962	145	1	this	this	DET
brj-22962	145	2	design	design	NOUN
brj-22962	145	3	choice	choice	NOUN
brj-22962	145	4	facilitates	facilitate	VERB
brj-22962	145	5	extensive	extensive	ADJ
brj-22962	145	6	feature	feature	NOUN
brj-22962	145	7	fusion	fusion	NOUN
brj-22962	145	8	,	,	PUNCT
brj-22962	145	9	significantly	significantly	ADV
brj-22962	145	10	amplifying	amplify	VERB
brj-22962	145	11	the	the	DET
brj-22962	145	12	amount	amount	NOUN
brj-22962	145	13	of	of	ADP
brj-22962	145	14	feature	feature	NOUN
brj-22962	145	15	extraction	extraction	NOUN
brj-22962	145	16	information	information	NOUN
brj-22962	145	17	available	available	ADJ
brj-22962	145	18	to	to	ADP
brj-22962	145	19	the	the	DET
brj-22962	145	20	model	model	NOUN
brj-22962	145	21	.	.	PUNCT
brj-22962	146	1	consequently	consequently	ADV
brj-22962	146	2	,	,	PUNCT
brj-22962	146	3	this	this	DET
brj-22962	146	4	approach	approach	NOUN
brj-22962	146	5	augments	augment	VERB
brj-22962	146	6	the	the	DET
brj-22962	146	7	model	model	NOUN
brj-22962	146	8	's	's	PART
brj-22962	146	9	feature	feature	NOUN
brj-22962	146	10	extraction	extraction	NOUN
brj-22962	146	11	capacity	capacity	NOUN
brj-22962	146	12	and	and	CCONJ
brj-22962	146	13	overall	overall	ADJ
brj-22962	146	14	efficiency	efficiency	NOUN
brj-22962	146	15	,	,	PUNCT
brj-22962	146	16	effectively	effectively	ADV
brj-22962	146	17	meeting	meet	VERB
brj-22962	146	18	the	the	DET
brj-22962	146	19	real	real	ADJ
brj-22962	146	20	-	-	PUNCT
brj-22962	146	21	time	time	NOUN
brj-22962	146	22	detection	detection	NOUN
brj-22962	146	23	requirements	requirement	NOUN
brj-22962	146	24	.	.	PUNCT
brj-22962	147	1	wise	wise	ADJ
brj-22962	147	2	-	-	PUNCT
brj-22962	147	3	iou	iou	NOUN
brj-22962	147	4	loss	loss	NOUN
brj-22962	147	5	function	function	NOUN
brj-22962	147	6	in	in	ADP
brj-22962	147	7	this	this	DET
brj-22962	147	8	study	study	NOUN
brj-22962	147	9	,	,	PUNCT
brj-22962	147	10	surface	surface	NOUN
brj-22962	147	11	defects	defect	NOUN
brj-22962	147	12	in	in	ADP
brj-22962	147	13	sawn	sawn	ADJ
brj-22962	147	14	timber	timber	NOUN
brj-22962	147	15	,	,	PUNCT
brj-22962	147	16	particularly	particularly	ADV
brj-22962	147	17	live	live	ADJ
brj-22962	147	18	and	and	CCONJ
brj-22962	147	19	dead	dead	ADJ
brj-22962	147	20	knots	knot	NOUN
brj-22962	147	21	,	,	PUNCT
brj-22962	147	22	constitute	constitute	VERB
brj-22962	147	23	a	a	DET
brj-22962	147	24	significant	significant	ADJ
brj-22962	147	25	proportion	proportion	NOUN
brj-22962	147	26	of	of	ADP
brj-22962	147	27	the	the	DET
brj-22962	147	28	dataset	dataset	NOUN
brj-22962	147	29	.	.	PUNCT
brj-22962	148	1	these	these	DET
brj-22962	148	2	defects	defect	NOUN
brj-22962	148	3	often	often	ADV
brj-22962	148	4	present	present	VERB
brj-22962	148	5	a	a	DET
brj-22962	148	6	challenge	challenge	NOUN
brj-22962	148	7	due	due	ADP
brj-22962	148	8	to	to	ADP
brj-22962	148	9	their	their	PRON
brj-22962	148	10	relatively	relatively	ADV
brj-22962	148	11	small	small	ADJ
brj-22962	148	12	sizes	size	NOUN
brj-22962	148	13	.	.	PUNCT
brj-22962	149	1	while	while	SCONJ
brj-22962	149	2	yolov8	yolov8	PROPN
brj-22962	149	3	employs	employ	VERB
brj-22962	149	4	distance	distance	NOUN
brj-22962	149	5	-	-	PUNCT
brj-22962	149	6	iou	iou	NOUN
brj-22962	149	7	(	(	PUNCT
brj-22962	149	8	dfl	dfl	PROPN
brj-22962	149	9	)	)	PUNCT
brj-22962	149	10	and	and	CCONJ
brj-22962	149	11	complete	complete	ADJ
brj-22962	149	12	-	-	PUNCT
brj-22962	149	13	iou	iou	NOUN
brj-22962	149	14	(	(	PUNCT
brj-22962	149	15	ciou	ciou	NOUN
brj-22962	149	16	)	)	PUNCT
brj-22962	149	17	for	for	ADP
brj-22962	149	18	computing	compute	VERB
brj-22962	149	19	bounding	bounding	NOUN
brj-22962	149	20	box	box	PROPN
brj-22962	149	21	regression	regression	NOUN
brj-22962	149	22	loss	loss	NOUN
brj-22962	149	23	,	,	PUNCT
brj-22962	149	24	ciou	ciou	NOUN
brj-22962	149	25	exhibits	exhibit	VERB
brj-22962	149	26	limitations	limitation	NOUN
brj-22962	149	27	.	.	PUNCT
brj-22962	150	1	it	it	PRON
brj-22962	150	2	not	not	PART
brj-22962	150	3	only	only	ADV
brj-22962	150	4	neglects	neglect	VERB
brj-22962	150	5	the	the	DET
brj-22962	150	6	balance	balance	NOUN
brj-22962	150	7	issue	issue	NOUN
brj-22962	150	8	between	between	ADP
brj-22962	150	9	difficult	difficult	ADJ
brj-22962	150	10	and	and	CCONJ
brj-22962	150	11	easy	easy	ADJ
brj-22962	150	12	samples	sample	NOUN
brj-22962	150	13	but	but	CCONJ
brj-22962	150	14	also	also	ADV
brj-22962	150	15	struggles	struggle	VERB
brj-22962	150	16	with	with	ADP
brj-22962	150	17	accurately	accurately	ADV
brj-22962	150	18	representing	represent	VERB
brj-22962	150	19	aspect	aspect	NOUN
brj-22962	150	20	ratios	ratio	NOUN
brj-22962	150	21	,	,	PUNCT
brj-22962	150	22	resulting	result	VERB
brj-22962	150	23	in	in	ADP
brj-22962	150	24	imprecise	imprecise	ADJ
brj-22962	150	25	detection	detection	NOUN
brj-22962	150	26	outcomes	outcome	NOUN
brj-22962	150	27	.	.	PUNCT
brj-22962	151	1	to	to	PART
brj-22962	151	2	address	address	VERB
brj-22962	151	3	these	these	DET
brj-22962	151	4	shortcomings	shortcoming	NOUN
brj-22962	151	5	,	,	PUNCT
brj-22962	151	6	this	this	DET
brj-22962	151	7	paper	paper	NOUN
brj-22962	151	8	introduces	introduce	VERB
brj-22962	151	9	wise	wise	ADJ
brj-22962	151	10	-	-	PUNCT
brj-22962	151	11	iou	iou	NOUN
brj-22962	151	12	(	(	PUNCT
brj-22962	151	13	tong	tong	PROPN
brj-22962	151	14	et	et	PROPN
brj-22962	151	15	al	al	PROPN
brj-22962	151	16	.	.	PROPN
brj-22962	151	17	2023	2023	NUM
brj-22962	151	18	)	)	PUNCT
brj-22962	151	19	,	,	PUNCT
brj-22962	151	20	a	a	DET
brj-22962	151	21	pixel	pixel	ADJ
brj-22962	151	22	-	-	PUNCT
brj-22962	151	23	level	level	NOUN
brj-22962	151	24	semantic	semantic	ADJ
brj-22962	151	25	segmentation	segmentation	NOUN
brj-22962	151	26	loss	loss	NOUN
brj-22962	151	27	function	function	NOUN
brj-22962	151	28	for	for	ADP
brj-22962	151	29	deep	deep	ADJ
brj-22962	151	30	learning	learning	NOUN
brj-22962	151	31	models	model	NOUN
brj-22962	151	32	.	.	PUNCT
brj-22962	152	1	wise	wise	ADJ
brj-22962	152	2	-	-	PUNCT
brj-22962	152	3	iou	iou	NOUN
brj-22962	152	4	is	be	AUX
brj-22962	152	5	calculated	calculate	VERB
brj-22962	152	6	by	by	ADP
brj-22962	152	7	assessing	assess	VERB
brj-22962	152	8	the	the	DET
brj-22962	152	9	similarity	similarity	NOUN
brj-22962	152	10	between	between	ADP
brj-22962	152	11	two	two	NUM
brj-22962	152	12	binary	binary	ADJ
brj-22962	152	13	images	image	NOUN
brj-22962	152	14	,	,	PUNCT
brj-22962	152	15	essentially	essentially	ADV
brj-22962	152	16	quantifying	quantify	VERB
brj-22962	152	17	the	the	DET
brj-22962	152	18	weighted	weighted	ADJ
brj-22962	152	19	average	average	NOUN
brj-22962	152	20	of	of	ADP
brj-22962	152	21	intersection	intersection	NOUN
brj-22962	152	22	over	over	ADP
brj-22962	152	23	union	union	NOUN
brj-22962	152	24	(	(	PUNCT
brj-22962	152	25	iou	iou	PROPN
brj-22962	152	26	)	)	PUNCT
brj-22962	152	27	between	between	ADP
brj-22962	152	28	the	the	DET
brj-22962	152	29	predicted	predict	VERB
brj-22962	152	30	segmentation	segmentation	NOUN
brj-22962	152	31	mask	mask	NOUN
brj-22962	152	32	and	and	CCONJ
brj-22962	152	33	the	the	DET
brj-22962	152	34	true	true	ADJ
brj-22962	152	35	segmentation	segmentation	NOUN
brj-22962	152	36	mask	mask	NOUN
brj-22962	152	37	.	.	PUNCT
brj-22962	153	1	the	the	DET
brj-22962	153	2	work	work	NOUN
brj-22962	153	3	by	by	ADP
brj-22962	153	4	tong	tong	PROPN
brj-22962	153	5	et	et	PROPN
brj-22962	153	6	al	al	PROPN
brj-22962	153	7	.	.	PROPN
brj-22962	153	8	presents	present	VERB
brj-22962	153	9	three	three	NUM
brj-22962	153	10	versions	version	NOUN
brj-22962	153	11	of	of	ADP
brj-22962	153	12	wise	wise	ADJ
brj-22962	153	13	-	-	PUNCT
brj-22962	153	14	iou	iou	NOUN
brj-22962	153	15	,	,	PUNCT
brj-22962	153	16	with	with	ADP
brj-22962	153	17	version	version	NOUN
brj-22962	153	18	3	3	NUM
brj-22962	153	19	(	(	PUNCT
brj-22962	153	20	v3	v3	PROPN
brj-22962	153	21	)	)	PUNCT
brj-22962	153	22	incorporating	incorporate	VERB
brj-22962	153	23	attention	attention	NOUN
brj-22962	153	24	-	-	PUNCT
brj-22962	153	25	based	base	VERB
brj-22962	153	26	prediction	prediction	NOUN
brj-22962	153	27	frame	frame	NOUN
brj-22962	153	28	loss	loss	NOUN
brj-22962	153	29	and	and	CCONJ
brj-22962	153	30	the	the	DET
brj-22962	153	31	inclusion	inclusion	NOUN
brj-22962	153	32	of	of	ADP
brj-22962	153	33	focusing	focus	VERB
brj-22962	153	34	coefficients	coefficient	NOUN
brj-22962	153	35	.	.	PUNCT
brj-22962	154	1	these	these	DET
brj-22962	154	2	enhancements	enhancement	NOUN
brj-22962	154	3	empower	empower	VERB
brj-22962	154	4	the	the	DET
brj-22962	154	5	model	model	NOUN
brj-22962	154	6	to	to	PART
brj-22962	154	7	better	well	ADV
brj-22962	154	8	localize	localize	VERB
brj-22962	154	9	defects	defect	NOUN
brj-22962	154	10	while	while	SCONJ
brj-22962	154	11	leveraging	leverage	VERB
brj-22962	154	12	the	the	DET
brj-22962	154	13	strengths	strength	NOUN
brj-22962	154	14	of	of	ADP
brj-22962	154	15	eiou	eiou	NOUN
brj-22962	154	16	(	(	PUNCT
brj-22962	154	17	enhanced	enhance	VERB
brj-22962	154	18	iou	iou	NOUN
brj-22962	154	19	)	)	PUNCT
brj-22962	154	20	and	and	CCONJ
brj-22962	154	21	siou	siou	NOUN
brj-22962	154	22	(	(	PUNCT
brj-22962	154	23	scaled	scale	VERB
brj-22962	154	24	iou	iou	NOUN
brj-22962	154	25	)	)	PUNCT
brj-22962	154	26	,	,	PUNCT
brj-22962	154	27	with	with	ADP
brj-22962	154	28	a	a	DET
brj-22962	154	29	particular	particular	ADJ
brj-22962	154	30	emphasis	emphasis	NOUN
brj-22962	154	31	on	on	ADP
brj-22962	154	32	dynamically	dynamically	ADV
brj-22962	154	33	optimizing	optimize	VERB
brj-22962	154	34	loss	loss	NOUN
brj-22962	154	35	weights	weight	NOUN
brj-22962	154	36	for	for	ADP
brj-22962	154	37	small	small	ADJ
brj-22962	154	38	defects	defect	NOUN
brj-22962	154	39	.	.	PUNCT
brj-22962	155	1	this	this	DET
brj-22962	155	2	holistic	holistic	ADJ
brj-22962	155	3	approach	approach	NOUN
brj-22962	155	4	contributes	contribute	VERB
brj-22962	155	5	to	to	ADP
brj-22962	155	6	a	a	DET
brj-22962	155	7	significant	significant	ADJ
brj-22962	155	8	improvement	improvement	NOUN
brj-22962	155	9	in	in	ADP
brj-22962	155	10	the	the	DET
brj-22962	155	11	detection	detection	NOUN
brj-22962	155	12	performance	performance	NOUN
brj-22962	155	13	of	of	ADP
brj-22962	155	14	yolo	yolo	PROPN
brj-22962	155	15	-	-	PUNCT
brj-22962	155	16	v8	v8	PROPN
brj-22962	155	17	.	.	PUNCT
brj-22962	156	1	the	the	DET
brj-22962	156	2	specific	specific	ADJ
brj-22962	156	3	formula	formula	NOUN
brj-22962	156	4	for	for	ADP
brj-22962	156	5	wise	wise	ADJ
brj-22962	156	6	-	-	PUNCT
brj-22962	156	7	iou	iou	NOUN
brj-22962	156	8	v3	v3	PROPN
brj-22962	156	9	is	be	AUX
brj-22962	156	10	depicted	depict	VERB
brj-22962	156	11	in	in	ADP
brj-22962	156	12	eq	eq	NOUN
brj-22962	156	13	.	.	PROPN
brj-22962	156	14	1	1	NUM
brj-22962	156	15	.	.	SYM
brj-22962	156	16	3	3	NUM
brj-22962	156	17	3	3	NUM
brj-22962	156	18	=	=	SYM
brj-22962	156	19	r	r	NOUN
brj-22962	156	20	,	,	PUNCT
brj-22962	156	21	=	=	PUNCT
brj-22962	156	22	wiouv	wiouv	PROPN
brj-22962	156	23	wiouv	wiouv	PROPN
brj-22962	156	24	r	r	PROPN
brj-22962	156	25			PROPN
brj-22962	156	26			PROPN
brj-22962	156	27			PROPN
brj-22962	156	28			PROPN
brj-22962	156	29	−	−	PROPN
brj-22962	156	30	l	l	PROPN
brj-22962	156	31	l	l	NOUN
brj-22962	156	32	(	(	PUNCT
brj-22962	156	33	1	1	NUM
brj-22962	156	34	)	)	PUNCT
brj-22962	156	35	(	(	PUNCT
brj-22962	156	36	a	a	X
brj-22962	156	37	)	)	PUNCT
brj-22962	156	38	pfn	pfn	PROPN
brj-22962	156	39	(	(	PUNCT
brj-22962	156	40	b	b	NOUN
brj-22962	156	41	)	)	PUNCT
brj-22962	156	42	bifpn	bifpn	PROPN
brj-22962	156	43	peer	peer	NOUN
brj-22962	156	44	-	-	PUNCT
brj-22962	156	45	reviewed	review	VERB
brj-22962	156	46	article	article	NOUN
brj-22962	156	47	bioresources.com	bioresources.com	X
brj-22962	156	48	wang	wang	PROPN
brj-22962	156	49	et	et	PROPN
brj-22962	156	50	al	al	PROPN
brj-22962	156	51	.	.	PROPN
brj-22962	156	52	(	(	PUNCT
brj-22962	156	53	2023	2023	NUM
brj-22962	156	54	)	)	PUNCT
brj-22962	156	55	.	.	PUNCT
brj-22962	157	1	“	"	PUNCT
brj-22962	157	2	timber	timber	NOUN
brj-22962	157	3	defect	defect	NOUN
brj-22962	157	4	i	i	PROPN
brj-22962	157	5	d	d	PROPN
brj-22962	157	6	algorithms	algorithm	NOUN
brj-22962	157	7	,	,	PUNCT
brj-22962	157	8	”	"	PUNCT
brj-22962	157	9	bioresources	bioresource	NOUN
brj-22962	157	10	18(4	18(4	NUM
brj-22962	157	11	)	)	PUNCT
brj-22962	157	12	,	,	PUNCT
brj-22962	157	13	8444	8444	NUM
brj-22962	157	14	-	-	SYM
brj-22962	157	15	8457	8457	NUM
brj-22962	157	16	.	.	PUNCT
brj-22962	157	17	8452	8452	NUM
brj-22962	157	18	in	in	ADP
brj-22962	157	19	eq.1	eq.1	NOUN
brj-22962	157	20	,	,	PUNCT
brj-22962	157	21	𝛽	𝛽	PROPN
brj-22962	157	22	denotes	denote	NOUN
brj-22962	157	23	outlier	outlier	NOUN
brj-22962	157	24	,	,	PUNCT
brj-22962	157	25	r	r	NOUN
brj-22962	157	26	denotes	denote	NOUN
brj-22962	157	27	gradient	gradient	ADJ
brj-22962	157	28	gain	gain	NOUN
brj-22962	157	29	,	,	PUNCT
brj-22962	157	30	α	α	PROPN
brj-22962	157	31	and	and	CCONJ
brj-22962	157	32	δ	δ	PROPN
brj-22962	157	33	are	be	AUX
brj-22962	157	34	hyperparameters.when	hyperparameters.when	PROPN
brj-22962	157	35			NOUN
brj-22962	157	36	=	=	PROPN
brj-22962	157	37			NUM
brj-22962	157	38	,	,	PUNCT
brj-22962	157	39	so	so	SCONJ
brj-22962	157	40	that	that	SCONJ
brj-22962	157	41	r	r	NOUN
brj-22962	157	42	=	=	SYM
brj-22962	157	43	1	1	NUM
brj-22962	157	44	,	,	PUNCT
brj-22962	157	45	the	the	DET
brj-22962	157	46	anchor	anchor	NOUN
brj-22962	157	47	frame	frame	NOUN
brj-22962	157	48	has	have	VERB
brj-22962	157	49	the	the	DET
brj-22962	157	50	highest	high	ADJ
brj-22962	157	51	gradient	gradient	ADJ
brj-22962	157	52	gain	gain	NOUN
brj-22962	157	53	when	when	SCONJ
brj-22962	157	54	the	the	DET
brj-22962	157	55	outlier	outlier	NOUN
brj-22962	157	56	of	of	ADP
brj-22962	157	57	the	the	DET
brj-22962	157	58	anchor	anchor	NOUN
brj-22962	157	59	frame	frame	NOUN
brj-22962	157	60	satisfies	satisfie	NOUN
brj-22962	158	1	=	=	PUNCT
brj-22962	158	2	c	c	X
brj-22962	158	3	(	(	PUNCT
brj-22962	158	4	c	c	NOUN
brj-22962	158	5	is	be	AUX
brj-22962	158	6	a	a	DET
brj-22962	158	7	constant	constant	ADJ
brj-22962	158	8	)	)	PUNCT
brj-22962	158	9	.	.	PUNCT
brj-22962	159	1	therefore	therefore	ADV
brj-22962	159	2	it	it	PRON
brj-22962	159	3	has	have	VERB
brj-22962	159	4	a	a	DET
brj-22962	159	5	dynamic	dynamic	ADJ
brj-22962	159	6	anchor	anchor	NOUN
brj-22962	159	7	frame	frame	NOUN
brj-22962	159	8	quality	quality	NOUN
brj-22962	159	9	division	division	NOUN
brj-22962	159	10	criterion	criterion	NOUN
brj-22962	159	11	,	,	PUNCT
brj-22962	159	12	which	which	PRON
brj-22962	159	13	enables	enable	VERB
brj-22962	159	14	wiouv3	wiouv3	NOUN
brj-22962	159	15	to	to	PART
brj-22962	159	16	give	give	VERB
brj-22962	159	17	the	the	DET
brj-22962	159	18	most	most	ADV
brj-22962	159	19	appropriate	appropriate	ADJ
brj-22962	159	20	gradient	gradient	NOUN
brj-22962	159	21	gain	gain	NOUN
brj-22962	159	22	allocation	allocation	NOUN
brj-22962	159	23	strategy	strategy	NOUN
brj-22962	159	24	at	at	ADP
brj-22962	159	25	different	different	ADJ
brj-22962	159	26	moments	moment	NOUN
brj-22962	159	27	.	.	PUNCT
brj-22962	160	1	experimental	experimental	ADJ
brj-22962	160	2	environment	environment	NOUN
brj-22962	160	3	experimental	experimental	ADJ
brj-22962	160	4	environment	environment	NOUN
brj-22962	160	5	the	the	DET
brj-22962	160	6	experimental	experimental	ADJ
brj-22962	160	7	environment	environment	NOUN
brj-22962	160	8	configuration	configuration	NOUN
brj-22962	160	9	is	be	AUX
brj-22962	160	10	outlined	outline	VERB
brj-22962	160	11	in	in	ADP
brj-22962	160	12	table	table	NOUN
brj-22962	160	13	1	1	NUM
brj-22962	160	14	.	.	PUNCT
brj-22962	161	1	specifically	specifically	ADV
brj-22962	161	2	,	,	PUNCT
brj-22962	161	3	the	the	DET
brj-22962	161	4	training	training	NOUN
brj-22962	161	5	parameters	parameter	NOUN
brj-22962	161	6	used	use	VERB
brj-22962	161	7	in	in	ADP
brj-22962	161	8	this	this	DET
brj-22962	161	9	experiment	experiment	NOUN
brj-22962	161	10	are	be	AUX
brj-22962	161	11	as	as	SCONJ
brj-22962	161	12	follows	follow	VERB
brj-22962	161	13	:	:	PUNCT
brj-22962	161	14	1	1	X
brj-22962	161	15	.	.	X
brj-22962	161	16	input	input	NOUN
brj-22962	161	17	image	image	NOUN
brj-22962	161	18	size	size	NOUN
brj-22962	161	19	:	:	PUNCT
brj-22962	161	20	640	640	NUM
brj-22962	161	21	pixels	pixel	NOUN
brj-22962	161	22	2	2	NUM
brj-22962	161	23	.	.	PUNCT
brj-22962	161	24	iteration	iteration	NOUN
brj-22962	161	25	period	period	NOUN
brj-22962	161	26	:	:	PUNCT
brj-22962	161	27	400	400	NUM
brj-22962	161	28	iterations	iteration	NOUN
brj-22962	161	29	3	3	NUM
brj-22962	161	30	.	.	NOUN
brj-22962	161	31	batch	batch	NOUN
brj-22962	161	32	size	size	NOUN
brj-22962	161	33	:	:	PUNCT
brj-22962	161	34	16	16	NUM
brj-22962	161	35	4	4	NUM
brj-22962	161	36	.	.	PUNCT
brj-22962	161	37	initial	initial	ADJ
brj-22962	161	38	learning	learning	NOUN
brj-22962	161	39	rate	rate	NOUN
brj-22962	161	40	:	:	PUNCT
brj-22962	161	41	0.001	0.001	NUM
brj-22962	161	42	5	5	NUM
brj-22962	161	43	.	.	PUNCT
brj-22962	161	44	weight	weight	NOUN
brj-22962	161	45	decay	decay	NOUN
brj-22962	161	46	coefficient	coefficient	NOUN
brj-22962	161	47	:	:	PUNCT
brj-22962	162	1	0.0005	0.0005	NUM
brj-22962	162	2	6	6	NUM
brj-22962	162	3	.	.	PUNCT
brj-22962	162	4	intersection	intersection	NOUN
brj-22962	162	5	over	over	ADP
brj-22962	162	6	union	union	NOUN
brj-22962	162	7	(	(	PUNCT
brj-22962	162	8	iou	iou	NOUN
brj-22962	162	9	)	)	PUNCT
brj-22962	162	10	threshold	threshold	NOUN
brj-22962	162	11	for	for	ADP
brj-22962	162	12	testing	testing	NOUN
brj-22962	162	13	:	:	PUNCT
brj-22962	162	14	0.7	0.7	NUM
brj-22962	162	15	table	table	NOUN
brj-22962	162	16	1	1	NUM
brj-22962	162	17	.	.	PUNCT
brj-22962	162	18	experimental	experimental	ADJ
brj-22962	162	19	environment	environment	PROPN
brj-22962	162	20	configuration	configuration	NOUN
brj-22962	162	21	configuration	configuration	NOUN
brj-22962	162	22	version	version	NOUN
brj-22962	162	23	parameter	parameter	NOUN
brj-22962	162	24	system	system	NOUN
brj-22962	162	25	environment	environment	NOUN
brj-22962	162	26	windows	window	VERB
brj-22962	162	27	10	10	NUM
brj-22962	162	28	professional	professional	ADJ
brj-22962	162	29	21h2	21h2	NUM
brj-22962	162	30	central	central	ADJ
brj-22962	162	31	processor	processor	NOUN
brj-22962	162	32	13th	13th	NOUN
brj-22962	162	33	gen	gen	PROPN
brj-22962	162	34	inter(r	inter(r	NOUN
brj-22962	162	35	)	)	PUNCT
brj-22962	162	36	core(tm	core(tm	NOUN
brj-22962	162	37	)	)	PUNCT
brj-22962	162	38	i5	i5	ADJ
brj-22962	162	39	-	-	PUNCT
brj-22962	162	40	13600kf	13600kf	NOUN
brj-22962	162	41	3.50ghz	3.50ghz	NUM
brj-22962	162	42	graphics	graphic	NOUN
brj-22962	162	43	processor	processor	NOUN
brj-22962	162	44	nvidia	nvidia	PROPN
brj-22962	162	45	geforce	geforce	PROPN
brj-22962	162	46	rtx	rtx	PROPN
brj-22962	162	47	4060ti	4060ti	PROPN
brj-22962	162	48	8	8	NUM
brj-22962	162	49	gb	gb	PROPN
brj-22962	162	50	graphics	graphic	NOUN
brj-22962	162	51	processor	processor	NOUN
brj-22962	162	52	accelerator	accelerator	PROPN
brj-22962	162	53	library	library	PROPN
brj-22962	162	54	cuda	cuda	PROPN
brj-22962	162	55	11.8.0	11.8.0	PROPN
brj-22962	162	56	,	,	PUNCT
brj-22962	162	57	cudnn8.0	cudnn8.0	X
brj-22962	162	58	random	random	ADJ
brj-22962	162	59	access	access	NOUN
brj-22962	162	60	storage	storage	NOUN
brj-22962	162	61	32.0	32.0	NUM
brj-22962	162	62	gb	gb	ADP
brj-22962	162	63	deep	deep	ADJ
brj-22962	162	64	learning	learn	VERB
brj-22962	162	65	environment	environment	NOUN
brj-22962	162	66	pytorch	pytorch	NOUN
brj-22962	162	67	2.0.1	2.0.1	NUM
brj-22962	162	68	deep	deep	ADJ
brj-22962	162	69	learning	learning	NOUN
brj-22962	162	70	frameworks	framework	NOUN
brj-22962	162	71	python	python	NOUN
brj-22962	162	72	3.9.16	3.9.16	NUM
brj-22962	162	73	performance	performance	NOUN
brj-22962	162	74	indicators	indicator	NOUN
brj-22962	162	75	in	in	ADP
brj-22962	162	76	order	order	NOUN
brj-22962	162	77	to	to	PART
brj-22962	162	78	assess	assess	VERB
brj-22962	162	79	the	the	DET
brj-22962	162	80	detection	detection	NOUN
brj-22962	162	81	effect	effect	NOUN
brj-22962	162	82	of	of	ADP
brj-22962	162	83	the	the	DET
brj-22962	162	84	improved	improved	ADJ
brj-22962	162	85	model	model	NOUN
brj-22962	162	86	,	,	PUNCT
brj-22962	162	87	the	the	DET
brj-22962	162	88	common	common	ADJ
brj-22962	162	89	evaluation	evaluation	NOUN
brj-22962	162	90	indexes	index	NOUN
brj-22962	162	91	for	for	ADP
brj-22962	162	92	wood	wood	NOUN
brj-22962	162	93	defect	defect	NOUN
brj-22962	162	94	detection	detection	NOUN
brj-22962	162	95	were	be	AUX
brj-22962	162	96	selected	select	VERB
brj-22962	162	97	:	:	PUNCT
brj-22962	162	98	precision	precision	NOUN
brj-22962	162	99	,	,	PUNCT
brj-22962	162	100	recall	recall	NOUN
brj-22962	162	101	,	,	PUNCT
brj-22962	162	102	f1	f1	NOUN
brj-22962	162	103	score	score	NOUN
brj-22962	162	104	,	,	PUNCT
brj-22962	162	105	map	map	NOUN
brj-22962	162	106	and	and	CCONJ
brj-22962	162	107	confusion	confusion	NOUN
brj-22962	162	108	matrix	matrix	NOUN
brj-22962	162	109	.	.	PUNCT
brj-22962	163	1	results	result	NOUN
brj-22962	163	2	and	and	CCONJ
brj-22962	163	3	discussion	discussion	NOUN
brj-22962	163	4	comparison	comparison	NOUN
brj-22962	163	5	with	with	ADP
brj-22962	163	6	yolo	yolo	PROPN
brj-22962	163	7	-	-	PUNCT
brj-22962	163	8	v8	v8	PROPN
brj-22962	163	9	and	and	CCONJ
brj-22962	163	10	its	its	PRON
brj-22962	163	11	mainstream	mainstream	NOUN
brj-22962	163	12	models	model	NOUN
brj-22962	163	13	to	to	PART
brj-22962	163	14	substantiate	substantiate	VERB
brj-22962	163	15	the	the	DET
brj-22962	163	16	effectiveness	effectiveness	NOUN
brj-22962	163	17	of	of	ADP
brj-22962	163	18	the	the	DET
brj-22962	163	19	enhanced	enhanced	ADJ
brj-22962	163	20	model	model	NOUN
brj-22962	163	21	,	,	PUNCT
brj-22962	163	22	tsw	tsw	PROPN
brj-22962	163	23	-	-	PUNCT
brj-22962	163	24	yolo	yolo	NOUN
brj-22962	163	25	-	-	PUNCT
brj-22962	163	26	v8n	v8n	ADJ
brj-22962	163	27	,	,	PUNCT
brj-22962	163	28	in	in	ADP
brj-22962	163	29	terms	term	NOUN
brj-22962	163	30	of	of	ADP
brj-22962	163	31	detection	detection	NOUN
brj-22962	163	32	performance	performance	NOUN
brj-22962	163	33	,	,	PUNCT
brj-22962	163	34	a	a	DET
brj-22962	163	35	comparative	comparative	ADJ
brj-22962	163	36	experiment	experiment	NOUN
brj-22962	163	37	was	be	AUX
brj-22962	163	38	conducted	conduct	VERB
brj-22962	163	39	against	against	ADP
brj-22962	163	40	the	the	DET
brj-22962	163	41	original	original	ADJ
brj-22962	163	42	yolo	yolo	ADJ
brj-22962	163	43	-	-	PUNCT
brj-22962	163	44	v8	v8	PROPN
brj-22962	163	45	model	model	NOUN
brj-22962	163	46	.	.	PUNCT
brj-22962	164	1	as	as	SCONJ
brj-22962	164	2	presented	present	VERB
brj-22962	164	3	in	in	ADP
brj-22962	164	4	table	table	NOUN
brj-22962	164	5	2	2	NUM
brj-22962	164	6	,	,	PUNCT
brj-22962	164	7	the	the	DET
brj-22962	164	8	results	result	NOUN
brj-22962	164	9	underscore	underscore	VERB
brj-22962	164	10	the	the	DET
brj-22962	164	11	substantial	substantial	ADJ
brj-22962	164	12	improvements	improvement	NOUN
brj-22962	164	13	achieved	achieve	VERB
brj-22962	164	14	by	by	ADP
brj-22962	164	15	the	the	DET
brj-22962	164	16	enhanced	enhanced	ADJ
brj-22962	164	17	model	model	NOUN
brj-22962	164	18	.	.	PUNCT
brj-22962	165	1	specifically	specifically	ADV
brj-22962	165	2	,	,	PUNCT
brj-22962	165	3	the	the	DET
brj-22962	165	4	mean	mean	ADJ
brj-22962	165	5	average	average	ADJ
brj-22962	165	6	precision	precision	NOUN
brj-22962	165	7	(	(	PUNCT
brj-22962	165	8	map	map	NOUN
brj-22962	165	9	)	)	PUNCT
brj-22962	165	10	was	be	AUX
brj-22962	165	11	elevated	elevate	VERB
brj-22962	165	12	by	by	ADP
brj-22962	165	13	5.1	5.1	NUM
brj-22962	165	14	%	%	NOUN
brj-22962	165	15	.	.	PUNCT
brj-22962	166	1	across	across	ADP
brj-22962	166	2	various	various	ADJ
brj-22962	166	3	defect	defect	NOUN
brj-22962	166	4	categories	category	NOUN
brj-22962	166	5	,	,	PUNCT
brj-22962	166	6	there	there	PRON
brj-22962	166	7	were	be	VERB
brj-22962	166	8	notable	notable	ADJ
brj-22962	166	9	enhancements	enhancement	NOUN
brj-22962	166	10	,	,	PUNCT
brj-22962	166	11	with	with	ADP
brj-22962	166	12	the	the	DET
brj-22962	166	13	exception	exception	NOUN
brj-22962	166	14	of	of	ADP
brj-22962	166	15	“	"	PUNCT
brj-22962	166	16	missing	miss	VERB
brj-22962	166	17	nodes	node	NOUN
brj-22962	166	18	.	.	PUNCT
brj-22962	166	19	”	"	PUNCT
brj-22962	167	1	particularly	particularly	ADV
brj-22962	167	2	noteworthy	noteworthy	ADJ
brj-22962	167	3	is	be	AUX
brj-22962	167	4	the	the	DET
brj-22962	167	5	improved	improve	VERB
brj-22962	167	6	capability	capability	NOUN
brj-22962	167	7	to	to	PART
brj-22962	167	8	detect	detect	VERB
brj-22962	167	9	small	small	ADJ
brj-22962	167	10	defects	defect	NOUN
brj-22962	167	11	,	,	PUNCT
brj-22962	167	12	such	such	ADJ
brj-22962	167	13	as	as	ADP
brj-22962	167	14	live	live	ADJ
brj-22962	167	15	knots	knot	NOUN
brj-22962	167	16	,	,	PUNCT
brj-22962	167	17	dead	dead	ADJ
brj-22962	167	18	knots	knot	NOUN
brj-22962	167	19	,	,	PUNCT
brj-22962	167	20	and	and	CCONJ
brj-22962	167	21	cracks	crack	NOUN
brj-22962	167	22	,	,	PUNCT
brj-22962	167	23	which	which	PRON
brj-22962	167	24	exhibit	exhibit	VERB
brj-22962	167	25	significant	significant	ADJ
brj-22962	167	26	performance	performance	NOUN
brj-22962	167	27	gains	gain	NOUN
brj-22962	167	28	.	.	PUNCT
brj-22962	168	1	furthermore	furthermore	ADV
brj-22962	168	2	,	,	PUNCT
brj-22962	168	3	the	the	DET
brj-22962	168	4	improvement	improvement	NOUN
brj-22962	168	5	in	in	ADP
brj-22962	168	6	quartzity	quartzity	NOUN
brj-22962	168	7	detection	detection	NOUN
brj-22962	168	8	exceeded	exceed	VERB
brj-22962	168	9	20	20	NUM
brj-22962	168	10	%	%	NOUN
brj-22962	168	11	.	.	PUNCT
brj-22962	169	1	these	these	DET
brj-22962	169	2	findings	finding	NOUN
brj-22962	169	3	demonstrate	demonstrate	VERB
brj-22962	169	4	that	that	SCONJ
brj-22962	169	5	the	the	DET
brj-22962	169	6	enhanced	enhanced	ADJ
brj-22962	169	7	model	model	NOUN
brj-22962	169	8	effectively	effectively	ADV
brj-22962	169	9	enhanced	enhance	VERB
brj-22962	169	10	the	the	DET
brj-22962	169	11	detection	detection	NOUN
brj-22962	169	12	accuracy	accuracy	NOUN
brj-22962	169	13	of	of	ADP
brj-22962	169	14	small	small	ADJ
brj-22962	169	15	defects	defect	NOUN
brj-22962	169	16	and	and	CCONJ
brj-22962	169	17	overall	overall	ADJ
brj-22962	169	18	elevated	elevate	VERB
brj-22962	169	19	the	the	DET
brj-22962	169	20	model	model	NOUN
brj-22962	169	21	’s	’s	PART
brj-22962	169	22	detection	detection	NOUN
brj-22962	169	23	performance	performance	NOUN
brj-22962	169	24	.	.	PUNCT
brj-22962	170	1	peer	peer	NOUN
brj-22962	170	2	-	-	PUNCT
brj-22962	170	3	reviewed	review	VERB
brj-22962	170	4	article	article	NOUN
brj-22962	170	5	bioresources.com	bioresources.com	X
brj-22962	170	6	wang	wang	PROPN
brj-22962	170	7	et	et	PROPN
brj-22962	170	8	al	al	PROPN
brj-22962	170	9	.	.	PROPN
brj-22962	170	10	(	(	PUNCT
brj-22962	170	11	2023	2023	NUM
brj-22962	170	12	)	)	PUNCT
brj-22962	170	13	.	.	PUNCT
brj-22962	171	1	“	"	PUNCT
brj-22962	171	2	timber	timber	NOUN
brj-22962	171	3	defect	defect	NOUN
brj-22962	171	4	i	i	PROPN
brj-22962	171	5	d	d	PROPN
brj-22962	171	6	algorithms	algorithm	NOUN
brj-22962	171	7	,	,	PUNCT
brj-22962	171	8	”	"	PUNCT
brj-22962	171	9	bioresources	bioresource	NOUN
brj-22962	171	10	18(4	18(4	NUM
brj-22962	171	11	)	)	PUNCT
brj-22962	171	12	,	,	PUNCT
brj-22962	171	13	8444	8444	NUM
brj-22962	171	14	-	-	SYM
brj-22962	171	15	8457	8457	NUM
brj-22962	171	16	.	.	PUNCT
brj-22962	171	17	8453	8453	NUM
brj-22962	171	18	to	to	PART
brj-22962	171	19	further	far	ADV
brj-22962	171	20	underscore	underscore	VERB
brj-22962	171	21	the	the	DET
brj-22962	171	22	superiority	superiority	NOUN
brj-22962	171	23	of	of	ADP
brj-22962	171	24	the	the	DET
brj-22962	171	25	current	current	ADJ
brj-22962	171	26	tsw	tsw	PROPN
brj-22962	171	27	-	-	PUNCT
brj-22962	171	28	yolo	yolo	ADJ
brj-22962	171	29	-	-	PUNCT
brj-22962	171	30	v8n	v8n	PROPN
brj-22962	171	31	model	model	NOUN
brj-22962	171	32	,	,	PUNCT
brj-22962	171	33	we	we	PRON
brj-22962	171	34	also	also	ADV
brj-22962	171	35	comprehensive	comprehensive	ADJ
brj-22962	171	36	comparisons	comparison	NOUN
brj-22962	171	37	and	and	CCONJ
brj-22962	171	38	testing	testing	NOUN
brj-22962	171	39	were	be	AUX
brj-22962	171	40	conducted	conduct	VERB
brj-22962	171	41	with	with	ADP
brj-22962	171	42	other	other	ADJ
brj-22962	171	43	prominent	prominent	ADJ
brj-22962	171	44	models	model	NOUN
brj-22962	171	45	,	,	PUNCT
brj-22962	171	46	as	as	SCONJ
brj-22962	171	47	detailed	detailed	ADJ
brj-22962	171	48	in	in	ADP
brj-22962	171	49	table	table	NOUN
brj-22962	171	50	2	2	NUM
brj-22962	171	51	.	.	PUNCT
brj-22962	172	1	the	the	DET
brj-22962	172	2	outcomes	outcome	NOUN
brj-22962	172	3	of	of	ADP
brj-22962	172	4	these	these	DET
brj-22962	172	5	comparative	comparative	ADJ
brj-22962	172	6	tests	test	NOUN
brj-22962	172	7	,	,	PUNCT
brj-22962	172	8	as	as	SCONJ
brj-22962	172	9	presented	present	VERB
brj-22962	172	10	in	in	ADP
brj-22962	172	11	the	the	DET
brj-22962	172	12	table	table	NOUN
brj-22962	172	13	,	,	PUNCT
brj-22962	172	14	unequivocally	unequivocally	ADV
brj-22962	172	15	showcase	showcase	VERB
brj-22962	172	16	the	the	DET
brj-22962	172	17	exceptional	exceptional	ADJ
brj-22962	172	18	detection	detection	NOUN
brj-22962	172	19	performance	performance	NOUN
brj-22962	172	20	of	of	ADP
brj-22962	172	21	the	the	DET
brj-22962	172	22	enhanced	enhanced	ADJ
brj-22962	172	23	model	model	NOUN
brj-22962	172	24	proposed	propose	VERB
brj-22962	172	25	within	within	ADP
brj-22962	172	26	this	this	DET
brj-22962	172	27	paper	paper	NOUN
brj-22962	172	28	.	.	PUNCT
brj-22962	173	1	notably	notably	ADV
brj-22962	173	2	,	,	PUNCT
brj-22962	173	3	while	while	SCONJ
brj-22962	173	4	mitigating	mitigate	VERB
brj-22962	173	5	issues	issue	NOUN
brj-22962	173	6	associated	associate	VERB
brj-22962	173	7	with	with	ADP
brj-22962	173	8	substantial	substantial	ADJ
brj-22962	173	9	target	target	NOUN
brj-22962	173	10	positioning	positioning	NOUN
brj-22962	173	11	errors	error	NOUN
brj-22962	173	12	and	and	CCONJ
brj-22962	173	13	the	the	DET
brj-22962	173	14	challenging	challenging	ADJ
brj-22962	173	15	task	task	NOUN
brj-22962	173	16	of	of	ADP
brj-22962	173	17	detecting	detect	VERB
brj-22962	173	18	small	small	ADJ
brj-22962	173	19	targets	target	NOUN
brj-22962	173	20	inherent	inherent	ADJ
brj-22962	173	21	to	to	ADP
brj-22962	173	22	the	the	DET
brj-22962	173	23	yolo	yolo	ADJ
brj-22962	173	24	series	series	NOUN
brj-22962	173	25	,	,	PUNCT
brj-22962	173	26	this	this	DET
brj-22962	173	27	improved	improved	ADJ
brj-22962	173	28	model	model	NOUN
brj-22962	173	29	simultaneously	simultaneously	ADV
brj-22962	173	30	enhanced	enhance	VERB
brj-22962	173	31	both	both	DET
brj-22962	173	32	recognition	recognition	NOUN
brj-22962	173	33	and	and	CCONJ
brj-22962	173	34	detection	detection	NOUN
brj-22962	173	35	capabilities	capability	NOUN
brj-22962	173	36	pertaining	pertain	VERB
brj-22962	173	37	to	to	ADP
brj-22962	173	38	small	small	ADJ
brj-22962	173	39	defects	defect	NOUN
brj-22962	173	40	.	.	PUNCT
brj-22962	174	1	table	table	NOUN
brj-22962	174	2	2	2	NUM
brj-22962	174	3	.	.	PUNCT
brj-22962	174	4	comparison	comparison	NOUN
brj-22962	174	5	of	of	ADP
brj-22962	174	6	defect	defect	ADJ
brj-22962	174	7	identification	identification	NOUN
brj-22962	174	8	diagrams	diagram	NOUN
brj-22962	174	9	between	between	ADP
brj-22962	174	10	yolo	yolo	PROPN
brj-22962	174	11	-	-	PUNCT
brj-22962	174	12	v8n	v8n	PROPN
brj-22962	174	13	and	and	CCONJ
brj-22962	174	14	mainstream	mainstream	NOUN
brj-22962	174	15	models	model	NOUN
brj-22962	174	16	and	and	CCONJ
brj-22962	174	17	tsw	tsw	PROPN
brj-22962	174	18	-	-	PUNCT
brj-22962	174	19	yolo	yolo	ADJ
brj-22962	174	20	-	-	PUNCT
brj-22962	174	21	v8n	v8n	PROPN
brj-22962	174	22	defect	defect	NOUN
brj-22962	174	23	model	model	NOUN
brj-22962	174	24	live	live	ADJ
brj-22962	174	25	knot	knot	ADJ
brj-22962	174	26	dead	dead	ADJ
brj-22962	174	27	knot	knot	NOUN
brj-22962	174	28	knot	knot	NOUN
brj-22962	174	29	with	with	ADP
brj-22962	174	30	crack	crack	NOUN
brj-22962	174	31	knot	knot	NOUN
brj-22962	174	32	missing	miss	VERB
brj-22962	174	33	crack	crack	NOUN
brj-22962	174	34	resin	resin	NOUN
brj-22962	174	35	marrow	marrow	NOUN
brj-22962	174	36	quartzity	quartzity	NOUN
brj-22962	174	37	map	map	VERB
brj-22962	174	38	yolov8n	yolov8n	NOUN
brj-22962	174	39	94.7	94.7	NUM
brj-22962	174	40	%	%	NOUN
brj-22962	174	41	94.6	94.6	NUM
brj-22962	174	42	%	%	NOUN
brj-22962	174	43	79.2	79.2	NUM
brj-22962	174	44	%	%	NOUN
brj-22962	174	45	89.6	89.6	NUM
brj-22962	174	46	%	%	NOUN
brj-22962	174	47	92.7	92.7	NUM
brj-22962	174	48	%	%	NOUN
brj-22962	174	49	94.9	94.9	NUM
brj-22962	174	50	%	%	NOUN
brj-22962	174	51	98.0	98.0	NUM
brj-22962	174	52	%	%	NOUN
brj-22962	174	53	44.4	44.4	NUM
brj-22962	174	54	%	%	NOUN
brj-22962	174	55	86.0	86.0	NUM
brj-22962	174	56	%	%	NOUN
brj-22962	174	57	faster	fast	ADJ
brj-22962	174	58	r	r	NOUN
brj-22962	174	59	-	-	PUNCT
brj-22962	174	60	cnn	cnn	PROPN
brj-22962	174	61	(	(	PUNCT
brj-22962	174	62	shih	shih	PROPN
brj-22962	174	63	et	et	PROPN
brj-22962	174	64	al	al	PROPN
brj-22962	174	65	.	.	PROPN
brj-22962	174	66	2019	2019	NUM
brj-22962	174	67	)	)	PUNCT
brj-22962	175	1	77.70	77.70	NUM
brj-22962	175	2	%	%	NOUN
brj-22962	175	3	86.30	86.30	NUM
brj-22962	175	4	%	%	NOUN
brj-22962	175	5	88.30	88.30	NUM
brj-22962	175	6	%	%	NOUN
brj-22962	175	7	88.40	88.40	NUM
brj-22962	175	8	%	%	NOUN
brj-22962	175	9	84.40	84.40	NUM
brj-22962	175	10	%	%	NOUN
brj-22962	175	11	81.80	81.80	NUM
brj-22962	175	12	%	%	NOUN
brj-22962	175	13	85.30	85.30	NUM
brj-22962	175	14	%	%	NOUN
brj-22962	175	15	83.50	83.50	NUM
brj-22962	175	16	%	%	NOUN
brj-22962	175	17	84.80	84.80	NUM
brj-22962	175	18	%	%	NOUN
brj-22962	175	19	ssd	ssd	NOUN
brj-22962	175	20	(	(	PUNCT
brj-22962	175	21	liu	liu	PROPN
brj-22962	175	22	et	et	PROPN
brj-22962	175	23	al	al	PROPN
brj-22962	175	24	.	.	PROPN
brj-22962	175	25	2016	2016	NUM
brj-22962	175	26	)	)	PUNCT
brj-22962	175	27	61.00	61.00	NUM
brj-22962	175	28	%	%	NOUN
brj-22962	175	29	71.67	71.67	NUM
brj-22962	175	30	%	%	NOUN
brj-22962	175	31	40.27	40.27	NUM
brj-22962	175	32	%	%	NOUN
brj-22962	175	33	66.33	66.33	NUM
brj-22962	175	34	%	%	NOUN
brj-22962	175	35	53.92	53.92	NUM
brj-22962	175	36	%	%	NOUN
brj-22962	175	37	54.66	54.66	NUM
brj-22962	175	38	%	%	NOUN
brj-22962	175	39	59.94	59.94	NUM
brj-22962	175	40	%	%	NOUN
brj-22962	175	41	75.74	75.74	NUM
brj-22962	175	42	%	%	NOUN
brj-22962	175	43	60.44	60.44	NUM
brj-22962	175	44	%	%	NOUN
brj-22962	175	45	yolov5	yolov5	NOUN
brj-22962	175	46	88.10	88.10	NUM
brj-22962	175	47	%	%	NOUN
brj-22962	175	48	90.90	90.90	NUM
brj-22962	175	49	%	%	NOUN
brj-22962	175	50	71.70	71.70	NUM
brj-22962	175	51	%	%	NOUN
brj-22962	175	52	75.10	75.10	NUM
brj-22962	175	53	%	%	NOUN
brj-22962	175	54	77.80	77.80	NUM
brj-22962	175	55	%	%	NOUN
brj-22962	175	56	90.80	90.80	NUM
brj-22962	175	57	%	%	NOUN
brj-22962	175	58	97.40	97.40	NUM
brj-22962	175	59	50.30	50.30	NUM
brj-22962	175	60	%	%	NOUN
brj-22962	175	61	80.30	80.30	NUM
brj-22962	175	62	%	%	NOUN
brj-22962	175	63	tswyolov8n	tswyolov8n	NOUN
brj-22962	175	64	96.6	96.6	NUM
brj-22962	175	65	%	%	NOUN
brj-22962	175	66	97.7	97.7	NUM
brj-22962	175	67	%	%	NOUN
brj-22962	175	68	88.30	88.30	NUM
brj-22962	175	69	%	%	NOUN
brj-22962	175	70	82.4	82.4	NUM
brj-22962	175	71	%	%	NOUN
brj-22962	175	72	99.0	99.0	NUM
brj-22962	175	73	%	%	NOUN
brj-22962	175	74	97.9	97.9	NUM
brj-22962	175	75	%	%	NOUN
brj-22962	175	76	98.8	98.8	NUM
brj-22962	175	77	%	%	NOUN
brj-22962	175	78	68.5	68.5	NUM
brj-22962	175	79	%	%	NOUN
brj-22962	175	80	91.1	91.1	NUM
brj-22962	175	81	%	%	NOUN
brj-22962	175	82	figure	figure	NOUN
brj-22962	175	83	6	6	NUM
brj-22962	175	84	illustrates	illustrate	VERB
brj-22962	175	85	the	the	DET
brj-22962	175	86	change	change	NOUN
brj-22962	175	87	curves	curve	NOUN
brj-22962	175	88	of	of	ADP
brj-22962	175	89	key	key	ADJ
brj-22962	175	90	evaluation	evaluation	NOUN
brj-22962	175	91	metrics	metric	NOUN
brj-22962	175	92	throughout	throughout	ADP
brj-22962	175	93	the	the	DET
brj-22962	175	94	training	training	NOUN
brj-22962	175	95	process	process	NOUN
brj-22962	175	96	,	,	PUNCT
brj-22962	175	97	depicting	depict	VERB
brj-22962	175	98	a	a	DET
brj-22962	175	99	comparison	comparison	NOUN
brj-22962	175	100	between	between	ADP
brj-22962	175	101	the	the	DET
brj-22962	175	102	improved	improved	ADJ
brj-22962	175	103	model	model	NOUN
brj-22962	175	104	and	and	CCONJ
brj-22962	175	105	the	the	DET
brj-22962	175	106	original	original	ADJ
brj-22962	175	107	model	model	NOUN
brj-22962	175	108	.	.	PUNCT
brj-22962	176	1	the	the	DET
brj-22962	176	2	metrics	metric	NOUN
brj-22962	176	3	are	be	AUX
brj-22962	176	4	presented	present	VERB
brj-22962	176	5	as	as	SCONJ
brj-22962	176	6	follows	follow	VERB
brj-22962	176	7	:	:	PUNCT
brj-22962	176	8	(	(	PUNCT
brj-22962	176	9	a	a	X
brj-22962	176	10	)	)	PUNCT
brj-22962	176	11	comparison	comparison	NOUN
brj-22962	176	12	of	of	ADP
brj-22962	176	13	classification	classification	NOUN
brj-22962	176	14	loss	loss	NOUN
brj-22962	176	15	(	(	PUNCT
brj-22962	176	16	cls_loss	cls_loss	NOUN
brj-22962	176	17	)	)	PUNCT
brj-22962	176	18	between	between	ADP
brj-22962	176	19	the	the	DET
brj-22962	176	20	model	model	NOUN
brj-22962	176	21	's	's	PART
brj-22962	176	22	training	training	NOUN
brj-22962	176	23	classification	classification	NOUN
brj-22962	176	24	results	result	NOUN
brj-22962	176	25	and	and	CCONJ
brj-22962	176	26	actual	actual	ADJ
brj-22962	176	27	ground	ground	NOUN
brj-22962	176	28	truth	truth	NOUN
brj-22962	176	29	annotations	annotation	NOUN
brj-22962	176	30	.	.	PUNCT
brj-22962	177	1	(	(	PUNCT
brj-22962	177	2	b	b	X
brj-22962	177	3	)	)	PUNCT
brj-22962	177	4	comparison	comparison	NOUN
brj-22962	177	5	of	of	ADP
brj-22962	177	6	precision	precision	NOUN
brj-22962	177	7	in	in	ADP
brj-22962	177	8	model	model	NOUN
brj-22962	177	9	recognition	recognition	NOUN
brj-22962	177	10	.	.	PUNCT
brj-22962	178	1	(	(	PUNCT
brj-22962	178	2	c	c	X
brj-22962	178	3	)	)	PUNCT
brj-22962	178	4	comparison	comparison	NOUN
brj-22962	178	5	of	of	ADP
brj-22962	178	6	the	the	DET
brj-22962	178	7	mean	mean	ADJ
brj-22962	178	8	average	average	ADJ
brj-22962	178	9	precision	precision	NOUN
brj-22962	178	10	(	(	PUNCT
brj-22962	178	11	map	map	NOUN
brj-22962	178	12	)	)	PUNCT
brj-22962	178	13	for	for	ADP
brj-22962	178	14	each	each	DET
brj-22962	178	15	individual	individual	ADJ
brj-22962	178	16	category	category	NOUN
brj-22962	178	17	.	.	PUNCT
brj-22962	179	1	(	(	PUNCT
brj-22962	179	2	d	d	X
brj-22962	179	3	)	)	PUNCT
brj-22962	179	4	comparison	comparison	NOUN
brj-22962	179	5	of	of	ADP
brj-22962	179	6	the	the	DET
brj-22962	179	7	recall	recall	NOUN
brj-22962	179	8	rate	rate	NOUN
brj-22962	179	9	(	(	PUNCT
brj-22962	179	10	recall	recall	NOUN
brj-22962	179	11	)	)	PUNCT
brj-22962	179	12	.	.	PUNCT
brj-22962	180	1	peer	peer	NOUN
brj-22962	180	2	-	-	PUNCT
brj-22962	180	3	reviewed	review	VERB
brj-22962	180	4	article	article	NOUN
brj-22962	180	5	bioresources.com	bioresources.com	X
brj-22962	180	6	wang	wang	PROPN
brj-22962	180	7	et	et	PROPN
brj-22962	180	8	al	al	PROPN
brj-22962	180	9	.	.	PROPN
brj-22962	180	10	(	(	PUNCT
brj-22962	180	11	2023	2023	NUM
brj-22962	180	12	)	)	PUNCT
brj-22962	180	13	.	.	PUNCT
brj-22962	181	1	“	"	PUNCT
brj-22962	181	2	timber	timber	NOUN
brj-22962	181	3	defect	defect	NOUN
brj-22962	181	4	i	i	PROPN
brj-22962	181	5	d	d	PROPN
brj-22962	181	6	algorithms	algorithm	NOUN
brj-22962	181	7	,	,	PUNCT
brj-22962	181	8	”	"	PUNCT
brj-22962	181	9	bioresources	bioresource	NOUN
brj-22962	181	10	18(4	18(4	NUM
brj-22962	181	11	)	)	PUNCT
brj-22962	181	12	,	,	PUNCT
brj-22962	181	13	8444	8444	NUM
brj-22962	181	14	-	-	SYM
brj-22962	181	15	8457	8457	NUM
brj-22962	181	16	.	.	PUNCT
brj-22962	181	17	8454	8454	NUM
brj-22962	181	18	(	(	PUNCT
brj-22962	181	19	a	a	NOUN
brj-22962	181	20	)	)	PUNCT
brj-22962	181	21	(	(	PUNCT
brj-22962	181	22	b	b	X
brj-22962	181	23	)	)	PUNCT
brj-22962	181	24	(	(	PUNCT
brj-22962	181	25	c	c	X
brj-22962	181	26	)	)	PUNCT
brj-22962	181	27	(	(	PUNCT
brj-22962	181	28	d	d	X
brj-22962	181	29	)	)	PUNCT
brj-22962	181	30	fig	fig	NOUN
brj-22962	181	31	.	.	PUNCT
brj-22962	182	1	6	6	NUM
brj-22962	182	2	.	.	X
brj-22962	182	3	comparison	comparison	NOUN
brj-22962	182	4	between	between	ADP
brj-22962	182	5	yolo	yolo	PROPN
brj-22962	182	6	-	-	PUNCT
brj-22962	182	7	v8n	v8n	PROPN
brj-22962	182	8	and	and	CCONJ
brj-22962	182	9	tsw	tsw	PROPN
brj-22962	182	10	-	-	PUNCT
brj-22962	182	11	yolo	yolo	NOUN
brj-22962	182	12	-	-	PUNCT
brj-22962	182	13	v8n	v8n	PROPN
brj-22962	182	14	from	from	ADP
brj-22962	182	15	the	the	DET
brj-22962	182	16	figure	figure	NOUN
brj-22962	182	17	,	,	PUNCT
brj-22962	182	18	it	it	PRON
brj-22962	182	19	is	be	AUX
brj-22962	182	20	evident	evident	ADJ
brj-22962	182	21	that	that	SCONJ
brj-22962	182	22	the	the	DET
brj-22962	182	23	improved	improved	ADJ
brj-22962	182	24	tsw	tsw	PROPN
brj-22962	182	25	-	-	PUNCT
brj-22962	182	26	yolo	yolo	ADJ
brj-22962	182	27	-	-	PUNCT
brj-22962	182	28	v8n	v8n	PROPN
brj-22962	182	29	model	model	NOUN
brj-22962	182	30	surpassed	surpass	VERB
brj-22962	182	31	the	the	DET
brj-22962	182	32	original	original	ADJ
brj-22962	182	33	yolo	yolo	ADJ
brj-22962	182	34	-	-	PUNCT
brj-22962	182	35	v8n	v8n	PROPN
brj-22962	182	36	model	model	NOUN
brj-22962	182	37	across	across	ADP
brj-22962	182	38	all	all	DET
brj-22962	182	39	metrics	metric	NOUN
brj-22962	182	40	.	.	PUNCT
brj-22962	183	1	moreover	moreover	ADV
brj-22962	183	2	,	,	PUNCT
brj-22962	183	3	the	the	DET
brj-22962	183	4	trend	trend	NOUN
brj-22962	183	5	of	of	ADP
brj-22962	183	6	the	the	DET
brj-22962	183	7	curves	curve	NOUN
brj-22962	183	8	reveals	reveal	VERB
brj-22962	183	9	that	that	SCONJ
brj-22962	183	10	the	the	DET
brj-22962	183	11	enhanced	enhanced	ADJ
brj-22962	183	12	model	model	NOUN
brj-22962	183	13	maintained	maintain	VERB
brj-22962	183	14	greater	great	ADJ
brj-22962	183	15	stability	stability	NOUN
brj-22962	183	16	and	and	CCONJ
brj-22962	183	17	exhibited	exhibit	VERB
brj-22962	183	18	superior	superior	ADJ
brj-22962	183	19	detection	detection	NOUN
brj-22962	183	20	performance	performance	NOUN
brj-22962	183	21	throughout	throughout	ADP
brj-22962	183	22	the	the	DET
brj-22962	183	23	training	training	NOUN
brj-22962	183	24	process	process	NOUN
brj-22962	183	25	.	.	PUNCT
brj-22962	184	1	visual	visual	ADJ
brj-22962	184	2	results	result	VERB
brj-22962	184	3	analysis	analysis	NOUN
brj-22962	184	4	in	in	ADP
brj-22962	184	5	light	light	NOUN
brj-22962	184	6	of	of	ADP
brj-22962	184	7	the	the	DET
brj-22962	184	8	challenge	challenge	NOUN
brj-22962	184	9	posed	pose	VERB
brj-22962	184	10	by	by	ADP
brj-22962	184	11	the	the	DET
brj-22962	184	12	limited	limited	ADJ
brj-22962	184	13	interpretability	interpretability	NOUN
brj-22962	184	14	of	of	ADP
brj-22962	184	15	deep	deep	ADJ
brj-22962	184	16	learning	learning	NOUN
brj-22962	184	17	models	model	NOUN
brj-22962	184	18	,	,	PUNCT
brj-22962	184	19	an	an	DET
brj-22962	184	20	analysis	analysis	NOUN
brj-22962	184	21	was	be	AUX
brj-22962	184	22	conducted	conduct	VERB
brj-22962	184	23	of	of	ADP
brj-22962	184	24	the	the	DET
brj-22962	184	25	model	model	NOUN
brj-22962	184	26	's	's	PART
brj-22962	184	27	detection	detection	NOUN
brj-22962	184	28	performance	performance	NOUN
brj-22962	184	29	improvement	improvement	NOUN
brj-22962	184	30	through	through	ADP
brj-22962	184	31	two	two	NUM
brj-22962	184	32	distinct	distinct	ADJ
brj-22962	184	33	lenses	lense	NOUN
brj-22962	184	34	:	:	PUNCT
brj-22962	184	35	the	the	DET
brj-22962	184	36	examination	examination	NOUN
brj-22962	184	37	of	of	ADP
brj-22962	184	38	the	the	DET
brj-22962	184	39	confusion	confusion	NOUN
brj-22962	184	40	matrix	matrix	NOUN
brj-22962	184	41	and	and	CCONJ
brj-22962	184	42	a	a	DET
brj-22962	184	43	thorough	thorough	ADJ
brj-22962	184	44	evaluation	evaluation	NOUN
brj-22962	184	45	of	of	ADP
brj-22962	184	46	the	the	DET
brj-22962	184	47	model	model	NOUN
brj-22962	184	48	's	's	PART
brj-22962	184	49	inference	inference	NOUN
brj-22962	184	50	results	result	NOUN
brj-22962	184	51	.	.	PUNCT
brj-22962	185	1	confusion	confusion	NOUN
brj-22962	185	2	matrix	matrix	NOUN
brj-22962	185	3	result	result	VERB
brj-22962	185	4	analysis	analysis	NOUN
brj-22962	185	5	as	as	ADP
brj-22962	185	6	evident	evident	ADJ
brj-22962	185	7	from	from	ADP
brj-22962	185	8	fig	fig	NOUN
brj-22962	185	9	.	.	PUNCT
brj-22962	186	1	7	7	NUM
brj-22962	186	2	-	-	SYM
brj-22962	186	3	a	a	PRON
brj-22962	186	4	,	,	PUNCT
brj-22962	186	5	the	the	DET
brj-22962	186	6	diagonal	diagonal	ADJ
brj-22962	186	7	region	region	NOUN
brj-22962	186	8	of	of	ADP
brj-22962	186	9	the	the	DET
brj-22962	186	10	confusion	confusion	NOUN
brj-22962	186	11	matrix	matrix	NOUN
brj-22962	186	12	in	in	ADP
brj-22962	186	13	the	the	DET
brj-22962	186	14	enhanced	enhanced	ADJ
brj-22962	186	15	tsw	tsw	PROPN
brj-22962	186	16	-	-	PUNCT
brj-22962	186	17	yolo	yolo	ADJ
brj-22962	186	18	-	-	PUNCT
brj-22962	186	19	v8n	v8n	PROPN
brj-22962	186	20	model	model	NOUN
brj-22962	186	21	exhibited	exhibit	VERB
brj-22962	186	22	a	a	DET
brj-22962	186	23	notably	notably	ADV
brj-22962	186	24	darker	dark	ADJ
brj-22962	186	25	hue	hue	NOUN
brj-22962	186	26	compared	compare	VERB
brj-22962	186	27	to	to	ADP
brj-22962	186	28	the	the	DET
brj-22962	186	29	diagonal	diagonal	ADJ
brj-22962	186	30	region	region	NOUN
brj-22962	186	31	of	of	ADP
brj-22962	186	32	the	the	DET
brj-22962	186	33	confusion	confusion	NOUN
brj-22962	186	34	matrix	matrix	NOUN
brj-22962	186	35	in	in	ADP
brj-22962	186	36	yolo	yolo	PROPN
brj-22962	186	37	-	-	PUNCT
brj-22962	186	38	v8n	v8n	ADJ
brj-22962	186	39	,	,	PUNCT
brj-22962	186	40	as	as	SCONJ
brj-22962	186	41	depicted	depict	VERB
brj-22962	186	42	in	in	ADP
brj-22962	186	43	fig	fig	NOUN
brj-22962	186	44	.	.	PUNCT
brj-22962	187	1	7	7	NUM
brj-22962	187	2	-	-	PUNCT
brj-22962	187	3	b.	b.	NOUN
brj-22962	187	4	this	this	DET
brj-22962	187	5	discrepancy	discrepancy	NOUN
brj-22962	187	6	serves	serve	VERB
brj-22962	187	7	as	as	ADP
brj-22962	187	8	a	a	DET
brj-22962	187	9	visual	visual	ADJ
brj-22962	187	10	indicator	indicator	NOUN
brj-22962	187	11	of	of	ADP
brj-22962	187	12	the	the	DET
brj-22962	187	13	improved	improved	ADJ
brj-22962	187	14	model	model	NOUN
brj-22962	187	15	’s	’s	PART
brj-22962	187	16	heightened	heighten	VERB
brj-22962	187	17	capability	capability	NOUN
brj-22962	187	18	in	in	ADP
brj-22962	187	19	detecting	detect	VERB
brj-22962	187	20	various	various	ADJ
brj-22962	187	21	defect	defect	ADJ
brj-22962	187	22	categories	category	NOUN
brj-22962	187	23	to	to	ADP
brj-22962	187	24	a	a	DET
brj-22962	187	25	significant	significant	ADJ
brj-22962	187	26	extent	extent	NOUN
brj-22962	187	27	.	.	PUNCT
brj-22962	188	1	peer	peer	NOUN
brj-22962	188	2	-	-	PUNCT
brj-22962	188	3	reviewed	review	VERB
brj-22962	188	4	article	article	NOUN
brj-22962	188	5	bioresources.com	bioresources.com	X
brj-22962	188	6	wang	wang	PROPN
brj-22962	188	7	et	et	PROPN
brj-22962	188	8	al	al	PROPN
brj-22962	188	9	.	.	PROPN
brj-22962	188	10	(	(	PUNCT
brj-22962	188	11	2023	2023	NUM
brj-22962	188	12	)	)	PUNCT
brj-22962	188	13	.	.	PUNCT
brj-22962	189	1	“	"	PUNCT
brj-22962	189	2	timber	timber	NOUN
brj-22962	189	3	defect	defect	NOUN
brj-22962	189	4	i	i	PROPN
brj-22962	189	5	d	d	PROPN
brj-22962	189	6	algorithms	algorithm	NOUN
brj-22962	189	7	,	,	PUNCT
brj-22962	189	8	”	"	PUNCT
brj-22962	189	9	bioresources	bioresource	NOUN
brj-22962	189	10	18(4	18(4	NUM
brj-22962	189	11	)	)	PUNCT
brj-22962	189	12	,	,	PUNCT
brj-22962	189	13	8444	8444	NUM
brj-22962	189	14	-	-	SYM
brj-22962	189	15	8457	8457	NUM
brj-22962	189	16	.	.	PUNCT
brj-22962	189	17	8455	8455	NUM
brj-22962	189	18	(	(	PUNCT
brj-22962	189	19	a	a	NOUN
brj-22962	189	20	)	)	PUNCT
brj-22962	189	21	(	(	PUNCT
brj-22962	189	22	b	b	X
brj-22962	189	23	)	)	PUNCT
brj-22962	189	24	fig	fig	NOUN
brj-22962	189	25	.	.	PUNCT
brj-22962	190	1	7	7	X
brj-22962	190	2	.	.	X
brj-22962	190	3	(	(	PUNCT
brj-22962	190	4	a	a	X
brj-22962	190	5	)	)	PUNCT
brj-22962	190	6	tsw	tsw	PROPN
brj-22962	190	7	-	-	PUNCT
brj-22962	190	8	yolo	yolo	ADJ
brj-22962	190	9	-	-	PUNCT
brj-22962	190	10	v8n	v8n	PROPN
brj-22962	190	11	confusion	confusion	NOUN
brj-22962	190	12	matrix	matrix	NOUN
brj-22962	190	13	diagram	diagram	NOUN
brj-22962	190	14	;	;	PUNCT
brj-22962	190	15	(	(	PUNCT
brj-22962	190	16	b	b	X
brj-22962	190	17	)	)	PUNCT
brj-22962	190	18	yolo	yolo	ADJ
brj-22962	190	19	-	-	PUNCT
brj-22962	190	20	v8n	v8n	PROPN
brj-22962	190	21	confusion	confusion	NOUN
brj-22962	190	22	matrix	matrix	NOUN
brj-22962	190	23	diagram	diagram	NOUN
brj-22962	190	24	analysis	analysis	NOUN
brj-22962	190	25	of	of	ADP
brj-22962	190	26	picture	picture	NOUN
brj-22962	190	27	reasoning	reasoning	NOUN
brj-22962	190	28	results	result	VERB
brj-22962	190	29	eight	eight	NUM
brj-22962	190	30	sawn	sawn	NOUN
brj-22962	190	31	timber	timber	NOUN
brj-22962	190	32	images	image	NOUN
brj-22962	190	33	were	be	AUX
brj-22962	190	34	randomly	randomly	ADV
brj-22962	190	35	selected	select	VERB
brj-22962	190	36	to	to	PART
brj-22962	190	37	construct	construct	VERB
brj-22962	190	38	a	a	DET
brj-22962	190	39	graphical	graphical	ADJ
brj-22962	190	40	representation	representation	NOUN
brj-22962	190	41	,	,	PUNCT
brj-22962	190	42	and	and	CCONJ
brj-22962	190	43	subsequently	subsequently	ADV
brj-22962	190	44	,	,	PUNCT
brj-22962	190	45	defect	defect	ADJ
brj-22962	190	46	detection	detection	NOUN
brj-22962	190	47	was	be	AUX
brj-22962	190	48	carried	carry	VERB
brj-22962	190	49	out	out	ADP
brj-22962	190	50	using	use	VERB
brj-22962	190	51	both	both	CCONJ
brj-22962	190	52	the	the	DET
brj-22962	190	53	yolov8n	yolov8n	NOUN
brj-22962	190	54	and	and	CCONJ
brj-22962	190	55	the	the	DET
brj-22962	190	56	enhanced	enhanced	ADJ
brj-22962	190	57	tsw	tsw	PROPN
brj-22962	190	58	-	-	PUNCT
brj-22962	190	59	yolo	yolo	ADJ
brj-22962	190	60	-	-	PUNCT
brj-22962	190	61	v8n	v8n	NUM
brj-22962	190	62	models	model	NOUN
brj-22962	190	63	.	.	PUNCT
brj-22962	191	1	as	as	SCONJ
brj-22962	191	2	depicted	depict	VERB
brj-22962	191	3	in	in	ADP
brj-22962	191	4	fig	fig	NOUN
brj-22962	191	5	.	.	PUNCT
brj-22962	192	1	8	8	NUM
brj-22962	192	2	-	-	SYM
brj-22962	192	3	a	a	NOUN
brj-22962	192	4	,	,	PUNCT
brj-22962	192	5	one	one	NUM
brj-22962	192	6	live	live	ADJ
brj-22962	192	7	knot	knot	NOUN
brj-22962	192	8	and	and	CCONJ
brj-22962	192	9	one	one	NUM
brj-22962	192	10	dead	dead	ADJ
brj-22962	192	11	knot	knot	NOUN
brj-22962	192	12	remained	remain	VERB
brj-22962	192	13	undetected	undetected	ADJ
brj-22962	192	14	,	,	PUNCT
brj-22962	192	15	with	with	ADP
brj-22962	192	16	a	a	DET
brj-22962	192	17	total	total	ADJ
brj-22962	192	18	processing	processing	NOUN
brj-22962	192	19	time	time	NOUN
brj-22962	192	20	of	of	ADP
brj-22962	192	21	7	7	NUM
brj-22962	192	22	milliseconds	millisecond	NOUN
brj-22962	192	23	.	.	PUNCT
brj-22962	193	1	conversely	conversely	ADV
brj-22962	193	2	,	,	PUNCT
brj-22962	193	3	the	the	DET
brj-22962	193	4	predictions	prediction	NOUN
brj-22962	193	5	generated	generate	VERB
brj-22962	193	6	by	by	ADP
brj-22962	193	7	the	the	DET
brj-22962	193	8	improved	improved	ADJ
brj-22962	193	9	tsw	tsw	PROPN
brj-22962	193	10	-	-	PUNCT
brj-22962	193	11	yolo	yolo	ADJ
brj-22962	193	12	-	-	PUNCT
brj-22962	193	13	v8n	v8n	PROPN
brj-22962	193	14	model	model	NOUN
brj-22962	193	15	,	,	PUNCT
brj-22962	193	16	illustrated	illustrate	VERB
brj-22962	193	17	in	in	ADP
brj-22962	193	18	figure	figure	NOUN
brj-22962	193	19	8	8	NUM
brj-22962	193	20	-	-	PUNCT
brj-22962	193	21	b	b	NOUN
brj-22962	193	22	,	,	PUNCT
brj-22962	193	23	not	not	PART
brj-22962	193	24	only	only	ADV
brj-22962	193	25	successfully	successfully	ADV
brj-22962	193	26	identified	identify	VERB
brj-22962	193	27	the	the	DET
brj-22962	193	28	previously	previously	ADV
brj-22962	193	29	overlooked	overlook	VERB
brj-22962	193	30	defects	defect	NOUN
brj-22962	193	31	in	in	ADP
brj-22962	193	32	fig	fig	NOUN
brj-22962	193	33	.	.	PUNCT
brj-22962	194	1	8a	8a	NUM
brj-22962	194	2	but	but	CCONJ
brj-22962	194	3	also	also	ADV
brj-22962	194	4	accomplished	accomplish	VERB
brj-22962	194	5	this	this	DET
brj-22962	194	6	task	task	NOUN
brj-22962	194	7	within	within	ADP
brj-22962	194	8	a	a	DET
brj-22962	194	9	reduced	reduced	ADJ
brj-22962	194	10	total	total	ADJ
brj-22962	194	11	processing	processing	NOUN
brj-22962	194	12	time	time	NOUN
brj-22962	194	13	of	of	ADP
brj-22962	194	14	6	6	NUM
brj-22962	194	15	milliseconds	millisecond	NOUN
brj-22962	194	16	.	.	PUNCT
brj-22962	195	1	fig	fig	NOUN
brj-22962	195	2	.	.	PUNCT
brj-22962	196	1	8	8	NUM
brj-22962	196	2	.	.	PUNCT
brj-22962	196	3	(	(	PUNCT
brj-22962	196	4	a	a	X
brj-22962	196	5	)	)	PUNCT
brj-22962	196	6	yolo	yolo	ADJ
brj-22962	196	7	-	-	PUNCT
brj-22962	196	8	v8n	v8n	PROPN
brj-22962	196	9	picture	picture	NOUN
brj-22962	196	10	inference	inference	NOUN
brj-22962	196	11	results	result	NOUN
brj-22962	196	12	;	;	PUNCT
brj-22962	196	13	(	(	PUNCT
brj-22962	196	14	b	b	X
brj-22962	196	15	)	)	PUNCT
brj-22962	196	16	tsw	tsw	PROPN
brj-22962	196	17	-	-	PUNCT
brj-22962	196	18	yolo	yolo	ADJ
brj-22962	196	19	-	-	PUNCT
brj-22962	196	20	v8n	v8n	ADJ
brj-22962	196	21	image	image	NOUN
brj-22962	196	22	inference	inference	NOUN
brj-22962	196	23	results	result	NOUN
brj-22962	196	24	while	while	SCONJ
brj-22962	196	25	this	this	DET
brj-22962	196	26	paper	paper	NOUN
brj-22962	196	27	’s	’s	PART
brj-22962	196	28	improved	improved	ADJ
brj-22962	196	29	method	method	NOUN
brj-22962	196	30	primarily	primarily	ADV
brj-22962	196	31	targets	target	VERB
brj-22962	196	32	the	the	DET
brj-22962	196	33	detection	detection	NOUN
brj-22962	196	34	of	of	ADP
brj-22962	196	35	small	small	ADJ
brj-22962	196	36	targets	target	NOUN
brj-22962	196	37	,	,	PUNCT
brj-22962	196	38	it	it	PRON
brj-22962	196	39	acknowledges	acknowledge	VERB
brj-22962	196	40	that	that	SCONJ
brj-22962	196	41	the	the	DET
brj-22962	196	42	enhancement	enhancement	NOUN
brj-22962	196	43	in	in	ADP
brj-22962	196	44	quartzity	quartzity	NOUN
brj-22962	196	45	is	be	AUX
brj-22962	196	46	relatively	relatively	ADV
brj-22962	196	47	modest	modest	ADJ
brj-22962	196	48	,	,	PUNCT
brj-22962	196	49	and	and	CCONJ
brj-22962	196	50	the	the	DET
brj-22962	196	51	recognition	recognition	NOUN
brj-22962	196	52	accuracy	accuracy	NOUN
brj-22962	196	53	remains	remain	VERB
brj-22962	196	54	suboptimal	suboptimal	ADJ
brj-22962	196	55	.	.	PUNCT
brj-22962	197	1	consequently	consequently	ADV
brj-22962	197	2	,	,	PUNCT
brj-22962	197	3	future	future	ADJ
brj-22962	197	4	research	research	NOUN
brj-22962	197	5	endeavors	endeavor	NOUN
brj-22962	197	6	should	should	AUX
brj-22962	197	7	concentrate	concentrate	VERB
brj-22962	197	8	on	on	ADP
brj-22962	197	9	further	far	ADV
brj-22962	197	10	optimizing	optimize	VERB
brj-22962	197	11	the	the	DET
brj-22962	197	12	model	model	NOUN
brj-22962	197	13	’s	’s	PART
brj-22962	197	14	detection	detection	NOUN
brj-22962	197	15	accuracy	accuracy	NOUN
brj-22962	197	16	,	,	PUNCT
brj-22962	197	17	particularly	particularly	ADV
brj-22962	197	18	in	in	ADP
brj-22962	197	19	the	the	DET
brj-22962	197	20	context	context	NOUN
brj-22962	197	21	of	of	ADP
brj-22962	197	22	small	small	ADJ
brj-22962	197	23	target	target	NOUN
brj-22962	197	24	defects	defect	NOUN
brj-22962	197	25	.	.	PUNCT
brj-22962	198	1	(	(	PUNCT
brj-22962	198	2	a	a	X
brj-22962	198	3	)	)	PUNCT
brj-22962	198	4	(	(	PUNCT
brj-22962	198	5	b	b	NOUN
brj-22962	198	6	)	)	PUNCT
brj-22962	198	7	peer	peer	NOUN
brj-22962	198	8	-	-	PUNCT
brj-22962	198	9	reviewed	review	VERB
brj-22962	198	10	article	article	NOUN
brj-22962	198	11	bioresources.com	bioresources.com	X
brj-22962	198	12	wang	wang	PROPN
brj-22962	198	13	et	et	PROPN
brj-22962	198	14	al	al	PROPN
brj-22962	198	15	.	.	PROPN
brj-22962	198	16	(	(	PUNCT
brj-22962	198	17	2023	2023	NUM
brj-22962	198	18	)	)	PUNCT
brj-22962	198	19	.	.	PUNCT
brj-22962	199	1	“	"	PUNCT
brj-22962	199	2	timber	timber	NOUN
brj-22962	199	3	defect	defect	NOUN
brj-22962	199	4	i	i	PROPN
brj-22962	199	5	d	d	PROPN
brj-22962	199	6	algorithms	algorithm	NOUN
brj-22962	199	7	,	,	PUNCT
brj-22962	199	8	”	"	PUNCT
brj-22962	199	9	bioresources	bioresource	NOUN
brj-22962	199	10	18(4	18(4	NUM
brj-22962	199	11	)	)	PUNCT
brj-22962	199	12	,	,	PUNCT
brj-22962	199	13	8444	8444	NUM
brj-22962	199	14	-	-	SYM
brj-22962	199	15	8457	8457	NUM
brj-22962	199	16	.	.	PUNCT
brj-22962	200	1	8456	8456	NUM
brj-22962	200	2	conclusions	conclusion	NOUN
brj-22962	200	3	1	1	NUM
brj-22962	200	4	.	.	PUNCT
brj-22962	201	1	in	in	ADP
brj-22962	201	2	response	response	NOUN
brj-22962	201	3	to	to	ADP
brj-22962	201	4	the	the	DET
brj-22962	201	5	prevalence	prevalence	NOUN
brj-22962	201	6	of	of	ADP
brj-22962	201	7	small	small	ADJ
brj-22962	201	8	defects	defect	NOUN
brj-22962	201	9	such	such	ADJ
brj-22962	201	10	as	as	ADP
brj-22962	201	11	live	live	ADJ
brj-22962	201	12	knots	knot	NOUN
brj-22962	201	13	,	,	PUNCT
brj-22962	201	14	dead	dead	ADJ
brj-22962	201	15	knots	knot	NOUN
brj-22962	201	16	,	,	PUNCT
brj-22962	201	17	and	and	CCONJ
brj-22962	201	18	cracks	crack	NOUN
brj-22962	201	19	on	on	ADP
brj-22962	201	20	the	the	DET
brj-22962	201	21	surface	surface	NOUN
brj-22962	201	22	of	of	ADP
brj-22962	201	23	sawn	sawn	NOUN
brj-22962	201	24	timber	timber	NOUN
brj-22962	201	25	,	,	PUNCT
brj-22962	201	26	coupled	couple	VERB
brj-22962	201	27	with	with	ADP
brj-22962	201	28	the	the	DET
brj-22962	201	29	substantial	substantial	ADJ
brj-22962	201	30	fusion	fusion	NOUN
brj-22962	201	31	between	between	ADP
brj-22962	201	32	sawn	sawn	NOUN
brj-22962	201	33	timber	timber	NOUN
brj-22962	201	34	texture	texture	NOUN
brj-22962	201	35	features	feature	NOUN
brj-22962	201	36	and	and	CCONJ
brj-22962	201	37	defects	defect	NOUN
brj-22962	201	38	,	,	PUNCT
brj-22962	201	39	this	this	DET
brj-22962	201	40	paper	paper	NOUN
brj-22962	201	41	introduces	introduce	VERB
brj-22962	201	42	a	a	DET
brj-22962	201	43	lightweight	lightweight	ADJ
brj-22962	201	44	sawn	sawn	NOUN
brj-22962	201	45	timber	timber	NOUN
brj-22962	201	46	surface	surface	NOUN
brj-22962	201	47	defects	defect	NOUN
brj-22962	201	48	detection	detection	NOUN
brj-22962	201	49	model	model	NOUN
brj-22962	201	50	known	know	VERB
brj-22962	201	51	as	as	ADP
brj-22962	201	52	tsw	tsw	PROPN
brj-22962	201	53	-	-	PUNCT
brj-22962	201	54	yolo	yolo	NOUN
brj-22962	201	55	-	-	PUNCT
brj-22962	201	56	v8n	v8n	NOUN
brj-22962	201	57	,	,	PUNCT
brj-22962	201	58	which	which	PRON
brj-22962	201	59	was	be	AUX
brj-22962	201	60	built	build	VERB
brj-22962	201	61	upon	upon	SCONJ
brj-22962	201	62	the	the	DET
brj-22962	201	63	yolov8n	yolov8n	NOUN
brj-22962	201	64	framework	framework	NOUN
brj-22962	201	65	.	.	PUNCT
brj-22962	202	1	2	2	X
brj-22962	202	2	.	.	X
brj-22962	202	3	the	the	DET
brj-22962	202	4	primary	primary	ADJ
brj-22962	202	5	focus	focus	NOUN
brj-22962	202	6	of	of	ADP
brj-22962	202	7	the	the	DET
brj-22962	202	8	tsw	tsw	PROPN
brj-22962	202	9	-	-	PUNCT
brj-22962	202	10	yolo	yolo	ADJ
brj-22962	202	11	-	-	PUNCT
brj-22962	202	12	v8n	v8n	PROPN
brj-22962	202	13	model	model	NOUN
brj-22962	202	14	lies	lie	VERB
brj-22962	202	15	in	in	ADP
brj-22962	202	16	addressing	address	VERB
brj-22962	202	17	the	the	DET
brj-22962	202	18	challenges	challenge	NOUN
brj-22962	202	19	posed	pose	VERB
brj-22962	202	20	by	by	ADP
brj-22962	202	21	the	the	DET
brj-22962	202	22	detection	detection	NOUN
brj-22962	202	23	of	of	ADP
brj-22962	202	24	small	small	ADJ
brj-22962	202	25	,	,	PUNCT
brj-22962	202	26	hard	hard	ADJ
brj-22962	202	27	-	-	PUNCT
brj-22962	202	28	to	to	PART
brj-22962	202	29	-	-	PUNCT
brj-22962	202	30	identify	identify	VERB
brj-22962	202	31	defects	defect	NOUN
brj-22962	202	32	and	and	CCONJ
brj-22962	202	33	the	the	DET
brj-22962	202	34	substantial	substantial	ADJ
brj-22962	202	35	blending	blending	NOUN
brj-22962	202	36	of	of	ADP
brj-22962	202	37	defects	defect	NOUN
brj-22962	202	38	with	with	ADP
brj-22962	202	39	the	the	DET
brj-22962	202	40	background	background	NOUN
brj-22962	202	41	.	.	PUNCT
brj-22962	203	1	to	to	PART
brj-22962	203	2	achieve	achieve	VERB
brj-22962	203	3	this	this	PRON
brj-22962	203	4	,	,	PUNCT
brj-22962	203	5	the	the	DET
brj-22962	203	6	model	model	NOUN
brj-22962	203	7	employs	employ	VERB
brj-22962	203	8	an	an	DET
brj-22962	203	9	improvement	improvement	NOUN
brj-22962	203	10	strategy	strategy	NOUN
brj-22962	203	11	that	that	PRON
brj-22962	203	12	enhances	enhance	VERB
brj-22962	203	13	its	its	PRON
brj-22962	203	14	performance	performance	NOUN
brj-22962	203	15	while	while	SCONJ
brj-22962	203	16	minimizing	minimize	VERB
brj-22962	203	17	its	its	PRON
brj-22962	203	18	computational	computational	ADJ
brj-22962	203	19	footprint	footprint	NOUN
brj-22962	203	20	.	.	PUNCT
brj-22962	204	1	notably	notably	ADV
brj-22962	204	2	,	,	PUNCT
brj-22962	204	3	the	the	DET
brj-22962	204	4	improved	improved	ADJ
brj-22962	204	5	model	model	NOUN
brj-22962	204	6	enhances	enhance	VERB
brj-22962	204	7	detection	detection	NOUN
brj-22962	204	8	efficiency	efficiency	NOUN
brj-22962	204	9	and	and	CCONJ
brj-22962	204	10	accuracy	accuracy	NOUN
brj-22962	204	11	,	,	PUNCT
brj-22962	204	12	achieving	achieve	VERB
brj-22962	204	13	a	a	DET
brj-22962	204	14	5.1	5.1	NUM
brj-22962	204	15	%	%	NOUN
brj-22962	204	16	increase	increase	NOUN
brj-22962	204	17	in	in	ADP
brj-22962	204	18	average	average	ADJ
brj-22962	204	19	detection	detection	NOUN
brj-22962	204	20	accuracy	accuracy	NOUN
brj-22962	204	21	compared	compare	VERB
brj-22962	204	22	to	to	ADP
brj-22962	204	23	the	the	DET
brj-22962	204	24	original	original	ADJ
brj-22962	204	25	model	model	NOUN
brj-22962	204	26	.	.	PUNCT
brj-22962	205	1	it	it	PRON
brj-22962	205	2	accomplishes	accomplish	VERB
brj-22962	205	3	defect	defect	NOUN
brj-22962	205	4	detection	detection	NOUN
brj-22962	205	5	with	with	ADP
brj-22962	205	6	an	an	DET
brj-22962	205	7	impressive	impressive	ADJ
brj-22962	205	8	elapsed	elapse	VERB
brj-22962	205	9	time	time	NOUN
brj-22962	205	10	of	of	ADP
brj-22962	205	11	6	6	NUM
brj-22962	205	12	ms	ms	NOUN
brj-22962	205	13	,	,	PUNCT
brj-22962	205	14	significantly	significantly	ADV
brj-22962	205	15	elevating	elevate	VERB
brj-22962	205	16	its	its	PRON
brj-22962	205	17	defect	defect	NOUN
brj-22962	205	18	detection	detection	NOUN
brj-22962	205	19	capabilities	capability	NOUN
brj-22962	205	20	.	.	PUNCT
brj-22962	206	1	furthermore	furthermore	ADV
brj-22962	206	2	,	,	PUNCT
brj-22962	206	3	the	the	DET
brj-22962	206	4	improved	improved	ADJ
brj-22962	206	5	model	model	NOUN
brj-22962	206	6	surpasses	surpass	VERB
brj-22962	206	7	mainstream	mainstream	ADJ
brj-22962	206	8	algorithms	algorithm	NOUN
brj-22962	206	9	in	in	ADP
brj-22962	206	10	terms	term	NOUN
brj-22962	206	11	of	of	ADP
brj-22962	206	12	detection	detection	NOUN
brj-22962	206	13	accuracy	accuracy	NOUN
brj-22962	206	14	.	.	PUNCT
brj-22962	207	1	acknowledgments	acknowledgment	NOUN
brj-22962	207	2	the	the	DET
brj-22962	207	3	authors	author	NOUN
brj-22962	207	4	are	be	AUX
brj-22962	207	5	grateful	grateful	ADJ
brj-22962	207	6	for	for	ADP
brj-22962	207	7	the	the	DET
brj-22962	207	8	support	support	NOUN
brj-22962	207	9	of	of	ADP
brj-22962	207	10	the	the	DET
brj-22962	207	11	key	key	ADJ
brj-22962	207	12	r&d	r&d	NOUN
brj-22962	207	13	and	and	CCONJ
brj-22962	207	14	achievement	achievement	NOUN
brj-22962	207	15	transformation	transformation	NOUN
brj-22962	207	16	plan	plan	NOUN
brj-22962	207	17	of	of	ADP
brj-22962	207	18	inner	inner	PROPN
brj-22962	207	19	mongolia	mongolia	PROPN
brj-22962	207	20	autonomous	autonomous	PROPN
brj-22962	207	21	region	region	PROPN
brj-22962	207	22	,	,	PUNCT
brj-22962	207	23	project	project	NOUN
brj-22962	207	24	no	no	NOUN
brj-22962	207	25	.	.	PUNCT
brj-22962	208	1	2022yfdz0031	2022yfdz0031	NUM
brj-22962	208	2	.	.	PUNCT
brj-22962	209	1	references	reference	NOUN
brj-22962	209	2	cited	cite	VERB
brj-22962	209	3	cao	cao	PROPN
brj-22962	209	4	,	,	PUNCT
brj-22962	209	5	y.	y.	PROPN
brj-22962	209	6	,	,	PUNCT
brj-22962	209	7	liu	liu	PROPN
brj-22962	209	8	,	,	PUNCT
brj-22962	209	9	f.	f.	PROPN
brj-22962	209	10	,	,	PUNCT
brj-22962	209	11	jiang	jiang	PROPN
brj-22962	209	12	,	,	PUNCT
brj-22962	209	13	l.	l.	PROPN
brj-22962	209	14	,	,	PUNCT
brj-22962	209	15	bao	bao	PROPN
brj-22962	209	16	,	,	PUNCT
brj-22962	209	17	c.	c.	PROPN
brj-22962	209	18	,	,	PUNCT
brj-22962	209	19	miao	miao	NOUN
brj-22962	209	20	,	,	PUNCT
brj-22962	209	21	y.	y.	PROPN
brj-22962	209	22	,	,	PUNCT
brj-22962	209	23	chen	chen	PROPN
brj-22962	209	24	,	,	PUNCT
brj-22962	209	25	y.	y.	PROPN
brj-22962	209	26	(	(	PUNCT
brj-22962	209	27	2023	2023	NUM
brj-22962	209	28	)	)	PUNCT
brj-22962	209	29	.	.	PUNCT
brj-22962	210	1	“	"	PUNCT
brj-22962	210	2	lightweight	lightweight	ADJ
brj-22962	210	3	wood	wood	NOUN
brj-22962	210	4	panel	panel	NOUN
brj-22962	210	5	defect	defect	NOUN
brj-22962	210	6	detection	detection	NOUN
brj-22962	210	7	method	method	NOUN
brj-22962	210	8	incorporating	incorporate	VERB
brj-22962	210	9	attention	attention	NOUN
brj-22962	210	10	mechanism	mechanism	NOUN
brj-22962	210	11	and	and	CCONJ
brj-22962	210	12	feature	feature	NOUN
brj-22962	210	13	fusion	fusion	NOUN
brj-22962	210	14	network	network	NOUN
brj-22962	210	15	,	,	PUNCT
brj-22962	210	16	”	"	PUNCT
brj-22962	210	17	arxiv	arxiv	PROPN
brj-22962	210	18	preprint	preprint	PROPN
brj-22962	210	19	arxiv:2306.12113	arxiv:2306.12113	PROPN
brj-22962	210	20	.	.	PUNCT
brj-22962	211	1	doi	doi	NOUN
brj-22962	211	2	:	:	PUNCT
brj-22962	211	3	10.48550	10.48550	NUM
brj-22962	211	4	/	/	SYM
brj-22962	211	5	arxiv.2306.12113	arxiv.2306.12113	NUM
brj-22962	211	6	cui	cui	NOUN
brj-22962	211	7	,	,	PUNCT
brj-22962	211	8	y.	y.	PROPN
brj-22962	211	9	,	,	PUNCT
brj-22962	211	10	lu	lu	PROPN
brj-22962	211	11	,	,	PUNCT
brj-22962	211	12	s.	s.	PROPN
brj-22962	211	13	,	,	PUNCT
brj-22962	211	14	and	and	CCONJ
brj-22962	211	15	liu	liu	PROPN
brj-22962	211	16	,	,	PUNCT
brj-22962	211	17	s.	s.	PROPN
brj-22962	211	18	(	(	PUNCT
brj-22962	211	19	2023	2023	NUM
brj-22962	211	20	)	)	PUNCT
brj-22962	211	21	.	.	PUNCT
brj-22962	212	1	“	"	PUNCT
brj-22962	212	2	real	real	ADJ
brj-22962	212	3	-	-	PUNCT
brj-22962	212	4	time	time	NOUN
brj-22962	212	5	detection	detection	NOUN
brj-22962	212	6	of	of	ADP
brj-22962	212	7	wood	wood	NOUN
brj-22962	212	8	defects	defect	NOUN
brj-22962	212	9	based	base	VERB
brj-22962	212	10	on	on	ADP
brj-22962	212	11	sppimproved	sppimprove	VERB
brj-22962	212	12	yolo	yolo	ADJ
brj-22962	212	13	algorithm	algorithm	NOUN
brj-22962	212	14	,	,	PUNCT
brj-22962	212	15	”	"	PUNCT
brj-22962	212	16	multimedia	multimedia	NOUN
brj-22962	212	17	tools	tool	NOUN
brj-22962	212	18	and	and	CCONJ
brj-22962	212	19	applications	application	NOUN
brj-22962	212	20	,	,	PUNCT
brj-22962	212	21	1	1	NUM
brj-22962	212	22	-	-	SYM
brj-22962	212	23	14	14	NUM
brj-22962	212	24	.	.	PUNCT
brj-22962	213	1	doi	doi	NOUN
brj-22962	213	2	:	:	PUNCT
brj-22962	213	3	10.1007	10.1007	NUM
brj-22962	213	4	/	/	SYM
brj-22962	213	5	s11042	s11042	PROPN
brj-22962	213	6	-	-	PUNCT
brj-22962	213	7	023	023	NUM
brj-22962	213	8	-	-	PUNCT
brj-22962	213	9	14588	14588	NUM
brj-22962	213	10	-	-	SYM
brj-22962	213	11	7	7	NUM
brj-22962	213	12	fang	fang	X
brj-22962	213	13	,	,	PUNCT
brj-22962	213	14	y.	y.	PROPN
brj-22962	213	15	,	,	PUNCT
brj-22962	213	16	guo	guo	PROPN
brj-22962	213	17	,	,	PUNCT
brj-22962	213	18	x.	x.	PROPN
brj-22962	213	19	,	,	PUNCT
brj-22962	213	20	chen	chen	PROPN
brj-22962	213	21	,	,	PUNCT
brj-22962	213	22	k.	k.	PROPN
brj-22962	213	23	,	,	PUNCT
brj-22962	213	24	zhou	zhou	PROPN
brj-22962	213	25	,	,	PUNCT
brj-22962	213	26	z.	z.	PROPN
brj-22962	213	27	,	,	PUNCT
brj-22962	213	28	ye	ye	PROPN
brj-22962	213	29	,	,	PUNCT
brj-22962	213	30	q.	q.	NOUN
brj-22962	213	31	(	(	PUNCT
brj-22962	213	32	2021	2021	NUM
brj-22962	213	33	)	)	PUNCT
brj-22962	213	34	.	.	PUNCT
brj-22962	214	1	“	"	PUNCT
brj-22962	214	2	accurate	accurate	ADJ
brj-22962	214	3	and	and	CCONJ
brj-22962	214	4	automated	automate	VERB
brj-22962	214	5	detection	detection	NOUN
brj-22962	214	6	of	of	ADP
brj-22962	214	7	surface	surface	NOUN
brj-22962	214	8	knots	knot	NOUN
brj-22962	214	9	on	on	ADP
brj-22962	214	10	sawn	sawn	NOUN
brj-22962	214	11	timbers	timber	NOUN
brj-22962	214	12	using	use	VERB
brj-22962	214	13	yolo	yolo	PROPN
brj-22962	214	14	-	-	PUNCT
brj-22962	214	15	v5	v5	PROPN
brj-22962	214	16	model	model	NOUN
brj-22962	214	17	,	,	PUNCT
brj-22962	214	18	”	"	PUNCT
brj-22962	214	19	bioresources	bioresource	NOUN
brj-22962	214	20	16(3	16(3	NUM
brj-22962	214	21	)	)	PUNCT
brj-22962	214	22	,	,	PUNCT
brj-22962	214	23	5390	5390	NUM
brj-22962	214	24	-	-	SYM
brj-22962	214	25	5406	5406	NUM
brj-22962	214	26	.	.	PUNCT
brj-22962	215	1	doi:10.15376	doi:10.15376	NOUN
brj-22962	215	2	/	/	SYM
brj-22962	215	3	biores.16.3.5390	biores.16.3.5390	NOUN
brj-22962	215	4	-	-	PUNCT
brj-22962	215	5	5406	5406	NUM
brj-22962	215	6	han	han	PROPN
brj-22962	215	7	,	,	PUNCT
brj-22962	215	8	s.	s.	PROPN
brj-22962	215	9	,	,	PUNCT
brj-22962	215	10	jiang	jiang	PROPN
brj-22962	215	11	,	,	PUNCT
brj-22962	215	12	x.	x.	NOUN
brj-22962	215	13	,	,	PUNCT
brj-22962	215	14	and	and	CCONJ
brj-22962	215	15	wu	wu	PROPN
brj-22962	215	16	,	,	PUNCT
brj-22962	215	17	z.	z.	PROPN
brj-22962	215	18	(	(	PUNCT
brj-22962	215	19	2023	2023	NUM
brj-22962	215	20	)	)	PUNCT
brj-22962	215	21	.	.	PUNCT
brj-22962	216	1	“	"	PUNCT
brj-22962	216	2	an	an	DET
brj-22962	216	3	improved	improved	ADJ
brj-22962	216	4	yolov5	yolov5	NOUN
brj-22962	216	5	algorithm	algorithm	NOUN
brj-22962	216	6	for	for	ADP
brj-22962	216	7	wood	wood	NOUN
brj-22962	216	8	defect	defect	NOUN
brj-22962	216	9	detection	detection	NOUN
brj-22962	216	10	based	base	VERB
brj-22962	216	11	on	on	ADP
brj-22962	216	12	attention	attention	NOUN
brj-22962	216	13	,	,	PUNCT
brj-22962	216	14	”	"	PUNCT
brj-22962	216	15	ieee	ieee	NOUN
brj-22962	216	16	access	access	NOUN
brj-22962	216	17	.	.	PUNCT
brj-22962	217	1	doi	doi	NOUN
brj-22962	217	2	:	:	PUNCT
brj-22962	217	3	10.1109	10.1109	NUM
brj-22962	217	4	/	/	SYM
brj-22962	217	5	access.2023.3293864	access.2023.3293864	PROPN
brj-22962	217	6	kodytek	kodytek	NOUN
brj-22962	217	7	,	,	PUNCT
brj-22962	217	8	p.	p.	NOUN
brj-22962	217	9	,	,	PUNCT
brj-22962	217	10	bodzas	bodzas	NOUN
brj-22962	217	11	,	,	PUNCT
brj-22962	217	12	a.	a.	NOUN
brj-22962	217	13	,	,	PUNCT
brj-22962	217	14	and	and	CCONJ
brj-22962	217	15	bilik	bilik	NOUN
brj-22962	217	16	,	,	PUNCT
brj-22962	217	17	p.	p.	NOUN
brj-22962	217	18	(	(	PUNCT
brj-22962	217	19	2022	2022	NUM
brj-22962	217	20	)	)	PUNCT
brj-22962	217	21	.	.	PUNCT
brj-22962	218	1	“	"	PUNCT
brj-22962	218	2	a	a	DET
brj-22962	218	3	large	large	ADJ
brj-22962	218	4	-	-	PUNCT
brj-22962	218	5	scale	scale	NOUN
brj-22962	218	6	image	image	NOUN
brj-22962	218	7	dataset	dataset	NOUN
brj-22962	218	8	of	of	ADP
brj-22962	218	9	wood	wood	NOUN
brj-22962	218	10	surface	surface	NOUN
brj-22962	218	11	defects	defect	NOUN
brj-22962	218	12	for	for	ADP
brj-22962	218	13	automated	automate	VERB
brj-22962	218	14	vision	vision	NOUN
brj-22962	218	15	-	-	PUNCT
brj-22962	218	16	based	base	VERB
brj-22962	218	17	quality	quality	NOUN
brj-22962	218	18	control	control	NOUN
brj-22962	218	19	processes	process	NOUN
brj-22962	218	20	,	,	PUNCT
brj-22962	218	21	”	"	PUNCT
brj-22962	218	22	f1000research	f1000research	VERB
brj-22962	218	23	10	10	NUM
brj-22962	218	24	,	,	PUNCT
brj-22962	218	25	581	581	NUM
brj-22962	218	26	.	.	PUNCT
brj-22962	219	1	doi	doi	NOUN
brj-22962	219	2	:	:	PUNCT
brj-22962	219	3	10.12688	10.12688	NUM
brj-22962	219	4	/	/	SYM
brj-22962	219	5	f1000research.52903.2	f1000research.52903.2	PROPN
brj-22962	219	6	kurdthongmee	kurdthongmee	PROPN
brj-22962	219	7	,	,	PUNCT
brj-22962	219	8	w.	w.	PROPN
brj-22962	219	9	(	(	PUNCT
brj-22962	219	10	2023	2023	NUM
brj-22962	219	11	)	)	PUNCT
brj-22962	219	12	.	.	PUNCT
brj-22962	220	1	“	"	PUNCT
brj-22962	220	2	improving	improve	VERB
brj-22962	220	3	wood	wood	NOUN
brj-22962	220	4	defect	defect	NOUN
brj-22962	220	5	detection	detection	NOUN
brj-22962	220	6	accuracy	accuracy	NOUN
brj-22962	220	7	with	with	ADP
brj-22962	220	8	yolo	yolo	PROPN
brj-22962	220	9	v3	v3	PROPN
brj-22962	220	10	by	by	ADP
brj-22962	220	11	incorporating	incorporate	VERB
brj-22962	220	12	out	out	ADV
brj-22962	220	13	-	-	PUNCT
brj-22962	220	14	of	of	ADP
brj-22962	220	15	-	-	PUNCT
brj-22962	220	16	defect	defect	NOUN
brj-22962	220	17	area	area	NOUN
brj-22962	220	18	annotations	annotation	NOUN
brj-22962	220	19	,	,	PUNCT
brj-22962	220	20	”	"	PUNCT
brj-22962	220	21	preprint	preprint	NOUN
brj-22962	220	22	available	available	ADJ
brj-22962	220	23	at	at	ADP
brj-22962	220	24	ssrn	ssrn	PROPN
brj-22962	220	25	4395580	4395580	NUM
brj-22962	220	26	.	.	PUNCT
brj-22962	221	1	doi	doi	NOUN
brj-22962	221	2	:	:	PUNCT
brj-22962	221	3	10.2139	10.2139	NUM
brj-22962	221	4	/	/	SYM
brj-22962	221	5	ssrn.4395580	ssrn.4395580	PROPN
brj-22962	221	6	liu	liu	PROPN
brj-22962	221	7	,	,	PUNCT
brj-22962	221	8	w.	w.	PROPN
brj-22962	221	9	,	,	PUNCT
brj-22962	221	10	anguelov	anguelov	PROPN
brj-22962	221	11	,	,	PUNCT
brj-22962	221	12	d.	d.	PROPN
brj-22962	221	13	,	,	PUNCT
brj-22962	221	14	erhan	erhan	PROPN
brj-22962	221	15	,	,	PUNCT
brj-22962	221	16	d.	d.	PROPN
brj-22962	221	17	,	,	PUNCT
brj-22962	221	18	szegedy	szegedy	PROPN
brj-22962	221	19	,	,	PUNCT
brj-22962	221	20	c.	c.	NOUN
brj-22962	221	21	,	,	PUNCT
brj-22962	221	22	reed	reed	PROPN
brj-22962	221	23	,	,	PUNCT
brj-22962	221	24	s.	s.	PROPN
brj-22962	221	25	,	,	PUNCT
brj-22962	221	26	fu	fu	PROPN
brj-22962	221	27	,	,	PUNCT
brj-22962	221	28	c.	c.	PROPN
brj-22962	221	29	y.	y.	PROPN
brj-22962	221	30	,	,	PUNCT
brj-22962	221	31	and	and	CCONJ
brj-22962	221	32	berg	berg	PROPN
brj-22962	221	33	,	,	PUNCT
brj-22962	221	34	a.	a.	PROPN
brj-22962	221	35	c.	c.	PROPN
brj-22962	221	36	(	(	PUNCT
brj-22962	221	37	2016	2016	NUM
brj-22962	221	38	)	)	PUNCT
brj-22962	221	39	.	.	PUNCT
brj-22962	222	1	“	"	PUNCT
brj-22962	222	2	ssd	ssd	NOUN
brj-22962	222	3	:	:	PUNCT
brj-22962	222	4	single	single	ADJ
brj-22962	222	5	shot	shot	PROPN
brj-22962	222	6	multibox	multibox	NOUN
brj-22962	222	7	detector	detector	NOUN
brj-22962	222	8	,	,	PUNCT
brj-22962	222	9	”	"	PUNCT
brj-22962	222	10	in	in	ADP
brj-22962	222	11	:	:	PUNCT
brj-22962	222	12	computer	computer	NOUN
brj-22962	222	13	vision	vision	NOUN
brj-22962	222	14	–	–	PUNCT
brj-22962	222	15	eccv	eccv	NOUN
brj-22962	222	16	2016	2016	NUM
brj-22962	222	17	:	:	PUNCT
brj-22962	222	18	14th	14th	ADJ
brj-22962	222	19	european	european	ADJ
brj-22962	222	20	conference	conference	PROPN
brj-22962	222	21	,	,	PUNCT
brj-22962	222	22	amsterdam	amsterdam	PROPN
brj-22962	222	23	,	,	PUNCT
brj-22962	222	24	the	the	DET
brj-22962	222	25	netherlands	netherlands	PROPN
brj-22962	222	26	,	,	PUNCT
brj-22962	222	27	october	october	PROPN
brj-22962	222	28	11–14	11–14	NUM
brj-22962	222	29	,	,	PUNCT
brj-22962	222	30	2016	2016	NUM
brj-22962	222	31	,	,	PUNCT
brj-22962	222	32	proceedings	proceeding	NOUN
brj-22962	222	33	,	,	PUNCT
brj-22962	222	34	part	part	NOUN
brj-22962	222	35	i	i	PRON
brj-22962	222	36	14	14	NUM
brj-22962	222	37	(	(	PUNCT
brj-22962	222	38	pp	pp	ADJ
brj-22962	222	39	.	.	PUNCT
brj-22962	223	1	21	21	NUM
brj-22962	223	2	-	-	SYM
brj-22962	223	3	37	37	NUM
brj-22962	223	4	)	)	PUNCT
brj-22962	223	5	.	.	PUNCT
brj-22962	224	1	springer	springer	NOUN
brj-22962	224	2	international	international	ADJ
brj-22962	224	3	publishing	publishing	NOUN
brj-22962	224	4	.	.	PUNCT
brj-22962	225	1	doi	doi	NOUN
brj-22962	225	2	:	:	PUNCT
brj-22962	225	3	10.1007/978	10.1007/978	NUM
brj-22962	225	4	-	-	SYM
brj-22962	225	5	3	3	NUM
brj-22962	225	6	-	-	NUM
brj-22962	225	7	319	319	NUM
brj-22962	225	8	-	-	PUNCT
brj-22962	225	9	46448	46448	NUM
brj-22962	225	10	-	-	SYM
brj-22962	225	11	0_2	0_2	NUM
brj-22962	225	12	peer	peer	NOUN
brj-22962	225	13	-	-	PUNCT
brj-22962	225	14	reviewed	review	VERB
brj-22962	225	15	article	article	NOUN
brj-22962	225	16	bioresources.com	bioresources.com	X
brj-22962	225	17	wang	wang	PROPN
brj-22962	225	18	et	et	PROPN
brj-22962	225	19	al	al	PROPN
brj-22962	225	20	.	.	PROPN
brj-22962	225	21	(	(	PUNCT
brj-22962	225	22	2023	2023	NUM
brj-22962	225	23	)	)	PUNCT
brj-22962	225	24	.	.	PUNCT
brj-22962	226	1	“	"	PUNCT
brj-22962	226	2	timber	timber	NOUN
brj-22962	226	3	defect	defect	NOUN
brj-22962	226	4	i	i	PROPN
brj-22962	226	5	d	d	PROPN
brj-22962	226	6	algorithms	algorithm	NOUN
brj-22962	226	7	,	,	PUNCT
brj-22962	226	8	”	"	PUNCT
brj-22962	226	9	bioresources	bioresource	NOUN
brj-22962	226	10	18(4	18(4	NUM
brj-22962	226	11	)	)	PUNCT
brj-22962	226	12	,	,	PUNCT
brj-22962	226	13	8444	8444	NUM
brj-22962	226	14	-	-	SYM
brj-22962	226	15	8457	8457	NUM
brj-22962	226	16	.	.	PUNCT
brj-22962	226	17	8457	8457	NUM
brj-22962	226	18	misra	misra	PROPN
brj-22962	226	19	,	,	PUNCT
brj-22962	226	20	d.	d.	PROPN
brj-22962	226	21	,	,	PUNCT
brj-22962	226	22	nalamada	nalamada	PROPN
brj-22962	226	23	,	,	PUNCT
brj-22962	226	24	t.	t.	PROPN
brj-22962	226	25	,	,	PUNCT
brj-22962	226	26	arasanipalai	arasanipalai	PROPN
brj-22962	226	27	,	,	PUNCT
brj-22962	226	28	a.	a.	NOUN
brj-22962	226	29	u.	u.	PROPN
brj-22962	226	30	,	,	PUNCT
brj-22962	226	31	and	and	CCONJ
brj-22962	226	32	hou	hou	NOUN
brj-22962	226	33	,	,	PUNCT
brj-22962	226	34	q.	q.	PROPN
brj-22962	226	35	(	(	PUNCT
brj-22962	226	36	2020	2020	NUM
brj-22962	226	37	)	)	PUNCT
brj-22962	226	38	.	.	PUNCT
brj-22962	227	1	“	"	PUNCT
brj-22962	227	2	rotate	rotate	VERB
brj-22962	227	3	to	to	PART
brj-22962	227	4	attend	attend	VERB
brj-22962	227	5	:	:	PUNCT
brj-22962	227	6	convolutional	convolutional	ADJ
brj-22962	227	7	triplet	triplet	NOUN
brj-22962	227	8	attention	attention	NOUN
brj-22962	227	9	module	module	NOUN
brj-22962	227	10	,	,	PUNCT
brj-22962	227	11	”	"	PUNCT
brj-22962	227	12	in	in	ADP
brj-22962	227	13	:	:	PUNCT
brj-22962	227	14	proceedings	proceeding	NOUN
brj-22962	227	15	of	of	ADP
brj-22962	227	16	the	the	DET
brj-22962	227	17	ieee	ieee	NOUN
brj-22962	227	18	/	/	SYM
brj-22962	227	19	cvf	cvf	NOUN
brj-22962	227	20	winter	winter	NOUN
brj-22962	227	21	conference	conference	NOUN
brj-22962	227	22	on	on	ADP
brj-22962	227	23	applications	application	NOUN
brj-22962	227	24	of	of	ADP
brj-22962	227	25	computer	computer	NOUN
brj-22962	227	26	vision	vision	NOUN
brj-22962	227	27	,	,	PUNCT
brj-22962	227	28	pp	pp	ADP
brj-22962	227	29	.	.	PUNCT
brj-22962	228	1	3139	3139	NUM
brj-22962	228	2	-	-	SYM
brj-22962	228	3	3148	3148	NUM
brj-22962	228	4	.	.	PUNCT
brj-22962	229	1	shih	shih	PROPN
brj-22962	229	2	,	,	PUNCT
brj-22962	229	3	k.	k.	PROPN
brj-22962	229	4	h.	h.	PROPN
brj-22962	229	5	,	,	PUNCT
brj-22962	229	6	chiu	chiu	PROPN
brj-22962	229	7	,	,	PUNCT
brj-22962	229	8	c.	c.	PROPN
brj-22962	229	9	t.	t.	PROPN
brj-22962	229	10	,	,	PUNCT
brj-22962	229	11	lin	lin	PROPN
brj-22962	229	12	,	,	PUNCT
brj-22962	229	13	j.	j.	PROPN
brj-22962	229	14	a.	a.	PROPN
brj-22962	229	15	,	,	PUNCT
brj-22962	229	16	and	and	CCONJ
brj-22962	229	17	bu	bu	ADP
brj-22962	229	18	,	,	PUNCT
brj-22962	229	19	y.	y.	PROPN
brj-22962	229	20	y.	y.	PROPN
brj-22962	229	21	(	(	PUNCT
brj-22962	229	22	2019	2019	NUM
brj-22962	229	23	)	)	PUNCT
brj-22962	229	24	.	.	PUNCT
brj-22962	230	1	“	"	PUNCT
brj-22962	230	2	real	real	ADJ
brj-22962	230	3	-	-	PUNCT
brj-22962	230	4	time	time	NOUN
brj-22962	230	5	object	object	NOUN
brj-22962	230	6	detection	detection	NOUN
brj-22962	230	7	with	with	ADP
brj-22962	230	8	reduced	reduced	ADJ
brj-22962	230	9	region	region	NOUN
brj-22962	230	10	proposal	proposal	NOUN
brj-22962	230	11	network	network	NOUN
brj-22962	230	12	via	via	ADP
brj-22962	230	13	multi	multi	ADJ
brj-22962	230	14	-	-	ADJ
brj-22962	230	15	feature	feature	ADJ
brj-22962	230	16	concatenation	concatenation	NOUN
brj-22962	230	17	,	,	PUNCT
brj-22962	230	18	”	"	PUNCT
brj-22962	230	19	ieee	ieee	NOUN
brj-22962	230	20	transactions	transaction	NOUN
brj-22962	230	21	on	on	ADP
brj-22962	230	22	neural	neural	ADJ
brj-22962	230	23	networks	network	NOUN
brj-22962	230	24	and	and	CCONJ
brj-22962	230	25	learning	learn	VERB
brj-22962	230	26	systems	system	NOUN
brj-22962	230	27	31(6	31(6	NUM
brj-22962	230	28	)	)	PUNCT
brj-22962	230	29	,	,	PUNCT
brj-22962	230	30	2164	2164	NUM
brj-22962	230	31	-	-	SYM
brj-22962	230	32	2173	2173	NUM
brj-22962	230	33	.	.	PUNCT
brj-22962	231	1	tan	tan	PROPN
brj-22962	231	2	,	,	PUNCT
brj-22962	231	3	m.	m.	NOUN
brj-22962	231	4	,	,	PUNCT
brj-22962	231	5	pang	pang	NOUN
brj-22962	231	6	,	,	PUNCT
brj-22962	231	7	r.	r.	PROPN
brj-22962	231	8	,	,	PUNCT
brj-22962	231	9	and	and	CCONJ
brj-22962	231	10	le	le	X
brj-22962	231	11	,	,	PUNCT
brj-22962	231	12	q.	q.	PROPN
brj-22962	231	13	v.	v.	PROPN
brj-22962	231	14	(	(	PUNCT
brj-22962	231	15	2020	2020	NUM
brj-22962	231	16	)	)	PUNCT
brj-22962	231	17	.	.	PUNCT
brj-22962	232	1	“	"	PUNCT
brj-22962	232	2	efficientdet	efficientdet	NOUN
brj-22962	232	3	:	:	PUNCT
brj-22962	232	4	scalable	scalable	ADJ
brj-22962	232	5	and	and	CCONJ
brj-22962	232	6	efficient	efficient	ADJ
brj-22962	232	7	object	object	NOUN
brj-22962	232	8	detection	detection	NOUN
brj-22962	232	9	,	,	PUNCT
brj-22962	232	10	”	"	PUNCT
brj-22962	232	11	in	in	ADP
brj-22962	232	12	proceedings	proceeding	NOUN
brj-22962	232	13	of	of	ADP
brj-22962	232	14	the	the	DET
brj-22962	232	15	ieee	ieee	NOUN
brj-22962	232	16	/	/	SYM
brj-22962	232	17	cvf	cvf	NOUN
brj-22962	232	18	conference	conference	NOUN
brj-22962	232	19	on	on	ADP
brj-22962	232	20	computer	computer	NOUN
brj-22962	232	21	vision	vision	NOUN
brj-22962	232	22	and	and	CCONJ
brj-22962	232	23	pattern	pattern	NOUN
brj-22962	232	24	recognition	recognition	NOUN
brj-22962	232	25	,	,	PUNCT
brj-22962	232	26	pp	pp	ADJ
brj-22962	232	27	.	.	PUNCT
brj-22962	233	1	10781	10781	NUM
brj-22962	233	2	-	-	SYM
brj-22962	233	3	10790	10790	NUM
brj-22962	233	4	.	.	PUNCT
brj-22962	234	1	tong	tong	PROPN
brj-22962	234	2	,	,	PUNCT
brj-22962	234	3	z.	z.	PROPN
brj-22962	234	4	,	,	PUNCT
brj-22962	234	5	chen	chen	PROPN
brj-22962	234	6	,	,	PUNCT
brj-22962	234	7	y.	y.	PROPN
brj-22962	234	8	,	,	PUNCT
brj-22962	234	9	xu	xu	PROPN
brj-22962	234	10	,	,	PUNCT
brj-22962	234	11	z.	z.	PROPN
brj-22962	234	12	,	,	PUNCT
brj-22962	234	13	and	and	CCONJ
brj-22962	234	14	yu	yu	PROPN
brj-22962	234	15	,	,	PUNCT
brj-22962	234	16	r.	r.	PROPN
brj-22962	234	17	(	(	PUNCT
brj-22962	234	18	2023	2023	NUM
brj-22962	234	19	)	)	PUNCT
brj-22962	234	20	.	.	PUNCT
brj-22962	235	1	“	"	PUNCT
brj-22962	235	2	wise	wise	ADJ
brj-22962	235	3	-	-	PUNCT
brj-22962	235	4	iou	iou	NOUN
brj-22962	235	5	:	:	PUNCT
brj-22962	235	6	bounding	bound	VERB
brj-22962	235	7	box	box	NOUN
brj-22962	235	8	regression	regression	NOUN
brj-22962	235	9	loss	loss	NOUN
brj-22962	235	10	with	with	ADP
brj-22962	235	11	dynamic	dynamic	ADJ
brj-22962	235	12	focusing	focus	VERB
brj-22962	235	13	mechanism	mechanism	NOUN
brj-22962	235	14	,	,	PUNCT
brj-22962	235	15	”	"	PUNCT
brj-22962	235	16	arxiv	arxiv	PROPN
brj-22962	235	17	preprint	preprint	PROPN
brj-22962	235	18	arxiv:2301.10051	arxiv:2301.10051	PROPN
brj-22962	235	19	.	.	PUNCT
brj-22962	236	1	doi	doi	NOUN
brj-22962	236	2	:	:	PUNCT
brj-22962	236	3	10.48550	10.48550	NUM
brj-22962	236	4	/	/	SYM
brj-22962	236	5	arxiv.2301.10051	arxiv.2301.10051	PROPN
brj-22962	236	6	wang	wang	PROPN
brj-22962	236	7	,	,	PUNCT
brj-22962	236	8	b.	b.	PROPN
brj-22962	236	9	,	,	PUNCT
brj-22962	236	10	yang	yang	PROPN
brj-22962	236	11	,	,	PUNCT
brj-22962	236	12	c.	c.	PROPN
brj-22962	236	13	,	,	PUNCT
brj-22962	236	14	ding	ding	NOUN
brj-22962	236	15	,	,	PUNCT
brj-22962	236	16	y.	y.	NOUN
brj-22962	236	17	,	,	PUNCT
brj-22962	236	18	and	and	CCONJ
brj-22962	236	19	qin	qin	INTJ
brj-22962	236	20	,	,	PUNCT
brj-22962	236	21	g.	g.	PROPN
brj-22962	236	22	(	(	PUNCT
brj-22962	236	23	2021a	2021a	NUM
brj-22962	236	24	)	)	PUNCT
brj-22962	236	25	.	.	PUNCT
brj-22962	237	1	“	"	PUNCT
brj-22962	237	2	detection	detection	NOUN
brj-22962	237	3	of	of	ADP
brj-22962	237	4	wood	wood	NOUN
brj-22962	237	5	surface	surface	NOUN
brj-22962	237	6	defects	defect	NOUN
brj-22962	237	7	based	base	VERB
brj-22962	237	8	on	on	ADP
brj-22962	237	9	improved	improved	ADJ
brj-22962	237	10	yolov3	yolov3	PROPN
brj-22962	237	11	algorithm	algorithm	PROPN
brj-22962	237	12	,	,	PUNCT
brj-22962	237	13	”	"	PUNCT
brj-22962	237	14	bioresources	bioresource	NOUN
brj-22962	237	15	16(4	16(4	NUM
brj-22962	237	16	)	)	PUNCT
brj-22962	237	17	,	,	PUNCT
brj-22962	237	18	6766	6766	NUM
brj-22962	237	19	-	-	SYM
brj-22962	237	20	6780	6780	NUM
brj-22962	237	21	.	.	PUNCT
brj-22962	238	1	doi	doi	NOUN
brj-22962	238	2	:	:	PUNCT
brj-22962	238	3	10.15376	10.15376	NUM
brj-22962	238	4	/	/	SYM
brj-22962	238	5	biores.16.4.6766	biores.16.4.6766	PROPN
brj-22962	238	6	-	-	PUNCT
brj-22962	238	7	6780	6780	NUM
brj-22962	238	8	wang	wang	PROPN
brj-22962	238	9	,	,	PUNCT
brj-22962	238	10	y.	y.	PROPN
brj-22962	238	11	,	,	PUNCT
brj-22962	238	12	zhang	zhang	PROPN
brj-22962	238	13	w.	w.	PROPN
brj-22962	238	14	,	,	PUNCT
brj-22962	238	15	gao	gao	PROPN
brj-22962	238	16	r.	r.	PROPN
brj-22962	238	17	,	,	PUNCT
brj-22962	238	18	and	and	CCONJ
brj-22962	238	19	jin	jin	PROPN
brj-22962	238	20	z.	z.	PROPN
brj-22962	238	21	(	(	PUNCT
brj-22962	238	22	2021b	2021b	NUM
brj-22962	238	23	)	)	PUNCT
brj-22962	238	24	.	.	PUNCT
brj-22962	239	1	“	"	PUNCT
brj-22962	239	2	identification	identification	NOUN
brj-22962	239	3	of	of	ADP
brj-22962	239	4	surface	surface	NOUN
brj-22962	239	5	defects	defect	NOUN
brj-22962	239	6	in	in	ADP
brj-22962	239	7	structural	structural	ADJ
brj-22962	239	8	sawn	sawn	NOUN
brj-22962	239	9	timber	timber	NOUN
brj-22962	239	10	based	base	VERB
brj-22962	239	11	on	on	ADP
brj-22962	239	12	yolov4	yolov4	PROPN
brj-22962	239	13	,	,	PUNCT
brj-22962	239	14	”	"	PUNCT
brj-22962	239	15	journal	journal	NOUN
brj-22962	239	16	of	of	ADP
brj-22962	239	17	forest	forest	NOUN
brj-22962	239	18	engineering	engineering	NOUN
brj-22962	239	19	6(4	6(4	PROPN
brj-22962	239	20	)	)	PUNCT
brj-22962	239	21	,	,	PUNCT
brj-22962	239	22	120126	120126	NUM
brj-22962	239	23	.	.	PUNCT
brj-22962	240	1	doi:10.13360	doi:10.13360	NOUN
brj-22962	240	2	/	/	SYM
brj-22962	240	3	j.issn.2096	j.issn.2096	NOUN
brj-22962	240	4	-	-	PUNCT
brj-22962	240	5	1359.202010009	1359.202010009	NUM
brj-22962	240	6	woo	woo	NOUN
brj-22962	240	7	,	,	PUNCT
brj-22962	240	8	s.	s.	PROPN
brj-22962	240	9	,	,	PUNCT
brj-22962	240	10	park	park	PROPN
brj-22962	240	11	,	,	PUNCT
brj-22962	240	12	j.	j.	PROPN
brj-22962	240	13	,	,	PUNCT
brj-22962	240	14	lee	lee	PROPN
brj-22962	240	15	,	,	PUNCT
brj-22962	240	16	j.	j.	PROPN
brj-22962	240	17	y.	y.	PROPN
brj-22962	240	18	,	,	PUNCT
brj-22962	240	19	and	and	CCONJ
brj-22962	240	20	kweon	kweon	PROPN
brj-22962	240	21	,	,	PUNCT
brj-22962	240	22	i.	i.	PROPN
brj-22962	240	23	s.	s.	PROPN
brj-22962	240	24	(	(	PUNCT
brj-22962	240	25	2018	2018	NUM
brj-22962	240	26	)	)	PUNCT
brj-22962	240	27	.	.	PUNCT
brj-22962	241	1	“	"	PUNCT
brj-22962	241	2	cbam	cbam	NOUN
brj-22962	241	3	:	:	PUNCT
brj-22962	241	4	convolutional	convolutional	ADJ
brj-22962	241	5	block	block	NOUN
brj-22962	241	6	attention	attention	NOUN
brj-22962	241	7	module	module	NOUN
brj-22962	241	8	,	,	PUNCT
brj-22962	241	9	”	"	PUNCT
brj-22962	241	10	in	in	ADP
brj-22962	241	11	:	:	PUNCT
brj-22962	241	12	proceedings	proceeding	NOUN
brj-22962	241	13	of	of	ADP
brj-22962	241	14	the	the	DET
brj-22962	241	15	european	european	PROPN
brj-22962	241	16	conference	conference	PROPN
brj-22962	241	17	on	on	ADP
brj-22962	241	18	computer	computer	NOUN
brj-22962	241	19	vision	vision	NOUN
brj-22962	241	20	(	(	PUNCT
brj-22962	241	21	eccv	eccv	ADV
brj-22962	241	22	)	)	PUNCT
brj-22962	241	23	,	,	PUNCT
brj-22962	241	24	pp	pp	ADP
brj-22962	241	25	.	.	PUNCT
brj-22962	242	1	3	3	NUM
brj-22962	242	2	-	-	SYM
brj-22962	242	3	19	19	NUM
brj-22962	242	4	.	.	PUNCT
brj-22962	242	5	yang	yang	PROPN
brj-22962	242	6	,	,	PUNCT
brj-22962	242	7	f.	f.	PROPN
brj-22962	242	8	,	,	PUNCT
brj-22962	242	9	wang	wang	PROPN
brj-22962	242	10	,	,	PUNCT
brj-22962	242	11	y.	y.	PROPN
brj-22962	242	12	,	,	PUNCT
brj-22962	242	13	wang	wang	PROPN
brj-22962	242	14	,	,	PUNCT
brj-22962	242	15	s.	s.	PROPN
brj-22962	242	16	,	,	PUNCT
brj-22962	242	17	and	and	CCONJ
brj-22962	242	18	cheng	cheng	PROPN
brj-22962	242	19	,	,	PUNCT
brj-22962	242	20	y.	y.	PROPN
brj-22962	242	21	(	(	PUNCT
brj-22962	242	22	2018	2018	NUM
brj-22962	242	23	)	)	PUNCT
brj-22962	242	24	.	.	PUNCT
brj-22962	243	1	“	"	PUNCT
brj-22962	243	2	wood	wood	NOUN
brj-22962	243	3	veneer	veneer	NOUN
brj-22962	243	4	defect	defect	NOUN
brj-22962	243	5	detection	detection	NOUN
brj-22962	243	6	system	system	NOUN
brj-22962	243	7	based	base	VERB
brj-22962	243	8	on	on	ADP
brj-22962	243	9	machine	machine	NOUN
brj-22962	243	10	vision	vision	NOUN
brj-22962	243	11	,	,	PUNCT
brj-22962	243	12	”	"	PUNCT
brj-22962	243	13	in	in	ADP
brj-22962	243	14	:	:	PUNCT
brj-22962	243	15	2018	2018	NUM
brj-22962	243	16	international	international	ADJ
brj-22962	243	17	symposium	symposium	NOUN
brj-22962	243	18	on	on	ADP
brj-22962	243	19	communication	communication	NOUN
brj-22962	243	20	engineering	engineering	NOUN
brj-22962	243	21	&	&	CCONJ
brj-22962	243	22	computer	computer	PROPN
brj-22962	243	23	science	science	NOUN
brj-22962	243	24	(	(	PUNCT
brj-22962	243	25	cecs	cec	NOUN
brj-22962	243	26	2018	2018	NUM
brj-22962	243	27	)	)	PUNCT
brj-22962	243	28	,	,	PUNCT
brj-22962	243	29	atlantis	atlantis	PROPN
brj-22962	243	30	press	press	PROPN
brj-22962	243	31	,	,	PUNCT
brj-22962	243	32	pp	pp	ADJ
brj-22962	243	33	.	.	PUNCT
brj-22962	244	1	413	413	NUM
brj-22962	244	2	-	-	SYM
brj-22962	244	3	418	418	NUM
brj-22962	244	4	.	.	PUNCT
brj-22962	245	1	zhu	zhu	PROPN
brj-22962	245	2	,	,	PUNCT
brj-22962	245	3	h.	h.	PROPN
brj-22962	245	4	,	,	PUNCT
brj-22962	245	5	zhou	zhou	PROPN
brj-22962	245	6	s.	s.	PROPN
brj-22962	245	7	,	,	PUNCT
brj-22962	245	8	liu	liu	PROPN
brj-22962	245	9	x.	x.	PROPN
brj-22962	245	10	,	,	PUNCT
brj-22962	245	11	zeng	zeng	PROPN
brj-22962	245	12	y.	y.	PROPN
brj-22962	245	13	,	,	PUNCT
brj-22962	245	14	and	and	CCONJ
brj-22962	245	15	li	li	PROPN
brj-22962	245	16	,	,	PUNCT
brj-22962	245	17	s.	s.	PROPN
brj-22962	245	18	(	(	PUNCT
brj-22962	245	19	2023	2023	NUM
brj-22962	245	20	)	)	PUNCT
brj-22962	245	21	.	.	PUNCT
brj-22962	246	1	“	"	PUNCT
brj-22962	246	2	a	a	DET
brj-22962	246	3	review	review	NOUN
brj-22962	246	4	of	of	ADP
brj-22962	246	5	single	single	ADJ
brj-22962	246	6	-	-	PUNCT
brj-22962	246	7	stage	stage	NOUN
brj-22962	246	8	object	object	NOUN
brj-22962	246	9	detection	detection	NOUN
brj-22962	246	10	algorithms	algorithm	NOUN
brj-22962	246	11	based	base	VERB
brj-22962	246	12	on	on	ADP
brj-22962	246	13	deep	deep	ADJ
brj-22962	246	14	learning	learning	NOUN
brj-22962	246	15	,	,	PUNCT
brj-22962	246	16	”	"	PUNCT
brj-22962	246	17	industrial	industrial	ADJ
brj-22962	246	18	control	control	NOUN
brj-22962	246	19	computer	computer	NOUN
brj-22962	246	20	36(04	36(04	PROPN
brj-22962	246	21	)	)	PUNCT
brj-22962	246	22	,	,	PUNCT
brj-22962	246	23	101	101	NUM
brj-22962	246	24	-	-	SYM
brj-22962	246	25	103	103	NUM
brj-22962	246	26	.	.	PUNCT
brj-22962	247	1	article	article	NOUN
brj-22962	247	2	submitted	submit	VERB
brj-22962	247	3	:	:	PUNCT
brj-22962	247	4	september	september	PROPN
brj-22962	247	5	11	11	NUM
brj-22962	247	6	,	,	PUNCT
brj-22962	247	7	2023	2023	NUM
brj-22962	247	8	;	;	PUNCT
brj-22962	247	9	peer	peer	NOUN
brj-22962	247	10	review	review	NOUN
brj-22962	247	11	completed	complete	VERB
brj-22962	247	12	:	:	PUNCT
brj-22962	247	13	october	october	PROPN
brj-22962	247	14	7	7	NUM
brj-22962	247	15	,	,	PUNCT
brj-22962	247	16	2023	2023	NUM
brj-22962	247	17	;	;	PUNCT
brj-22962	247	18	revised	revise	VERB
brj-22962	247	19	version	version	NOUN
brj-22962	247	20	received	receive	VERB
brj-22962	247	21	and	and	CCONJ
brj-22962	247	22	accepted	accept	VERB
brj-22962	247	23	:	:	PUNCT
brj-22962	247	24	october	october	PROPN
brj-22962	247	25	8	8	NUM
brj-22962	247	26	,	,	PUNCT
brj-22962	247	27	2023	2023	NUM
brj-22962	247	28	;	;	PUNCT
brj-22962	247	29	published	publish	VERB
brj-22962	247	30	:	:	PUNCT
brj-22962	247	31	october	october	PROPN
brj-22962	247	32	26	26	NUM
brj-22962	247	33	,	,	PUNCT
brj-22962	247	34	2023	2023	NUM
brj-22962	247	35	.	.	PUNCT
brj-22962	248	1	doi	doi	NOUN
brj-22962	248	2	:	:	PUNCT
brj-22962	248	3	10.15376	10.15376	NUM
brj-22962	248	4	/	/	SYM
brj-22962	248	5	biores.18.4.8444	biores.18.4.8444	PROPN
brj-22962	248	6	-	-	PUNCT
brj-22962	248	7	8457	8457	NUM