id	sid	tid	token	lemma	pos
brj-23254	1	1	peer	peer	NOUN
brj-23254	1	2	-	-	PUNCT
brj-23254	1	3	review	review	NOUN
brj-23254	1	4	article	article	NOUN
brj-23254	1	5	peer	peer	NOUN
brj-23254	1	6	-	-	PUNCT
brj-23254	1	7	reviewed	review	VERB
brj-23254	1	8	article	article	NOUN
brj-23254	1	9	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	1	10	ma	ma	PROPN
brj-23254	1	11	et	et	PROPN
brj-23254	1	12	al	al	PROPN
brj-23254	1	13	.	.	PROPN
brj-23254	2	1	(	(	PUNCT
brj-23254	2	2	2024	2024	NUM
brj-23254	2	3	)	)	PUNCT
brj-23254	2	4	.	.	PUNCT
brj-23254	3	1	“	"	PUNCT
brj-23254	3	2	wood	wood	NOUN
brj-23254	3	3	i	i	X
brj-23254	3	4	d	d	PROPN
brj-23254	3	5	via	via	ADP
brj-23254	3	6	deep	deep	ADJ
brj-23254	3	7	learning	learning	NOUN
brj-23254	3	8	,	,	PUNCT
brj-23254	3	9	”	"	PUNCT
brj-23254	3	10	bioresources	bioresource	NOUN
brj-23254	3	11	19(3	19(3	NUM
brj-23254	3	12	)	)	PUNCT
brj-23254	3	13	,	,	PUNCT
brj-23254	3	14	4838	4838	NUM
brj-23254	3	15	-	-	SYM
brj-23254	3	16	4851	4851	NUM
brj-23254	3	17	.	.	PUNCT
brj-23254	4	1	4838	4838	NUM
brj-23254	4	2	validation	validation	NOUN
brj-23254	4	3	study	study	NOUN
brj-23254	4	4	on	on	ADP
brj-23254	4	5	the	the	DET
brj-23254	4	6	practical	practical	ADJ
brj-23254	4	7	accuracy	accuracy	NOUN
brj-23254	4	8	of	of	ADP
brj-23254	4	9	wood	wood	NOUN
brj-23254	4	10	species	species	NOUN
brj-23254	4	11	identification	identification	NOUN
brj-23254	4	12	via	via	ADP
brj-23254	4	13	deep	deep	ADJ
brj-23254	4	14	learning	learning	NOUN
brj-23254	4	15	from	from	ADP
brj-23254	4	16	visible	visible	ADJ
brj-23254	4	17	microscopic	microscopic	ADJ
brj-23254	4	18	images	image	NOUN
brj-23254	4	19	te	te	ADP
brj-23254	4	20	ma	ma	PROPN
brj-23254	4	21	,	,	PUNCT
brj-23254	4	22	a	a	DET
brj-23254	4	23	fumiya	fumiya	PROPN
brj-23254	4	24	kimura	kimura	NOUN
brj-23254	4	25	,	,	PUNCT
brj-23254	4	26	a	a	DET
brj-23254	4	27	satoru	satoru	PROPN
brj-23254	4	28	tsuchikawa	tsuchikawa	PROPN
brj-23254	4	29	,	,	PUNCT
brj-23254	4	30	a	a	DET
brj-23254	4	31	miho	miho	PROPN
brj-23254	4	32	kojima	kojima	PROPN
brj-23254	4	33	,	,	PUNCT
brj-23254	4	34	b	b	PROPN
brj-23254	4	35	and	and	CCONJ
brj-23254	4	36	tetsuya	tetsuya	PROPN
brj-23254	4	37	inagaki	inagaki	VERB
brj-23254	4	38	a	a	DET
brj-23254	4	39	,	,	PUNCT
brj-23254	4	40	*	*	PUNCT
brj-23254	4	41	this	this	DET
brj-23254	4	42	study	study	NOUN
brj-23254	4	43	aimed	aim	VERB
brj-23254	4	44	to	to	PART
brj-23254	4	45	validate	validate	VERB
brj-23254	4	46	the	the	DET
brj-23254	4	47	accuracy	accuracy	NOUN
brj-23254	4	48	of	of	ADP
brj-23254	4	49	identifying	identify	VERB
brj-23254	4	50	japanese	japanese	ADJ
brj-23254	4	51	hardwood	hardwood	NOUN
brj-23254	4	52	species	specie	NOUN
brj-23254	4	53	from	from	ADP
brj-23254	4	54	microscopic	microscopic	ADJ
brj-23254	4	55	cross	cross	ADJ
brj-23254	4	56	-	-	ADJ
brj-23254	4	57	sectional	sectional	ADJ
brj-23254	4	58	images	image	NOUN
brj-23254	4	59	using	use	VERB
brj-23254	4	60	convolutional	convolutional	ADJ
brj-23254	4	61	neural	neural	ADJ
brj-23254	4	62	networks	network	NOUN
brj-23254	4	63	(	(	PUNCT
brj-23254	4	64	cnn	cnn	PROPN
brj-23254	4	65	)	)	PUNCT
brj-23254	4	66	.	.	PUNCT
brj-23254	5	1	the	the	DET
brj-23254	5	2	overarching	overarching	ADJ
brj-23254	5	3	goal	goal	NOUN
brj-23254	5	4	is	be	AUX
brj-23254	5	5	to	to	PART
brj-23254	5	6	create	create	VERB
brj-23254	5	7	a	a	DET
brj-23254	5	8	versatile	versatile	ADJ
brj-23254	5	9	model	model	NOUN
brj-23254	5	10	that	that	PRON
brj-23254	5	11	can	can	AUX
brj-23254	5	12	handle	handle	VERB
brj-23254	5	13	microscopic	microscopic	ADJ
brj-23254	5	14	cross	cross	ADJ
brj-23254	5	15	-	-	ADJ
brj-23254	5	16	sectional	sectional	ADJ
brj-23254	5	17	images	image	NOUN
brj-23254	5	18	of	of	ADP
brj-23254	5	19	wood	wood	NOUN
brj-23254	5	20	.	.	PUNCT
brj-23254	6	1	to	to	PART
brj-23254	6	2	gauge	gauge	VERB
brj-23254	6	3	the	the	DET
brj-23254	6	4	practical	practical	ADJ
brj-23254	6	5	accuracy	accuracy	NOUN
brj-23254	6	6	,	,	PUNCT
brj-23254	6	7	a	a	DET
brj-23254	6	8	comprehensive	comprehensive	ADJ
brj-23254	6	9	database	database	NOUN
brj-23254	6	10	of	of	ADP
brj-23254	6	11	microscopic	microscopic	ADJ
brj-23254	6	12	images	image	NOUN
brj-23254	6	13	of	of	ADP
brj-23254	6	14	japanese	japanese	ADJ
brj-23254	6	15	hardwood	hardwood	NOUN
brj-23254	6	16	species	specie	NOUN
brj-23254	6	17	was	be	AUX
brj-23254	6	18	provided	provide	VERB
brj-23254	6	19	by	by	ADP
brj-23254	6	20	the	the	DET
brj-23254	6	21	forest	forest	NOUN
brj-23254	6	22	research	research	NOUN
brj-23254	6	23	and	and	CCONJ
brj-23254	6	24	management	management	NOUN
brj-23254	6	25	organization	organization	NOUN
brj-23254	6	26	.	.	PUNCT
brj-23254	7	1	these	these	DET
brj-23254	7	2	images	image	NOUN
brj-23254	7	3	,	,	PUNCT
brj-23254	7	4	captured	capture	VERB
brj-23254	7	5	from	from	ADP
brj-23254	7	6	various	various	ADJ
brj-23254	7	7	positions	position	NOUN
brj-23254	7	8	on	on	ADP
brj-23254	7	9	wood	wood	NOUN
brj-23254	7	10	blocks	block	NOUN
brj-23254	7	11	,	,	PUNCT
brj-23254	7	12	different	different	ADJ
brj-23254	7	13	trees	tree	NOUN
brj-23254	7	14	,	,	PUNCT
brj-23254	7	15	and	and	CCONJ
brj-23254	7	16	diverse	diverse	ADJ
brj-23254	7	17	production	production	NOUN
brj-23254	7	18	areas	area	NOUN
brj-23254	7	19	,	,	PUNCT
brj-23254	7	20	resulted	result	VERB
brj-23254	7	21	in	in	ADP
brj-23254	7	22	substantial	substantial	ADJ
brj-23254	7	23	intra	intra	ADJ
brj-23254	7	24	-	-	ADJ
brj-23254	7	25	species	species	ADJ
brj-23254	7	26	image	image	NOUN
brj-23254	7	27	variation	variation	NOUN
brj-23254	7	28	.	.	PUNCT
brj-23254	8	1	to	to	PART
brj-23254	8	2	assess	assess	VERB
brj-23254	8	3	the	the	DET
brj-23254	8	4	effect	effect	NOUN
brj-23254	8	5	of	of	ADP
brj-23254	8	6	data	datum	NOUN
brj-23254	8	7	distribution	distribution	NOUN
brj-23254	8	8	on	on	ADP
brj-23254	8	9	accuracy	accuracy	NOUN
brj-23254	8	10	,	,	PUNCT
brj-23254	8	11	two	two	NUM
brj-23254	8	12	datasets	dataset	NOUN
brj-23254	8	13	,	,	PUNCT
brj-23254	8	14	d1	d1	PROPN
brj-23254	8	15	and	and	CCONJ
brj-23254	8	16	d2	d2	PROPN
brj-23254	8	17	,	,	PUNCT
brj-23254	8	18	representing	represent	VERB
brj-23254	8	19	a	a	DET
brj-23254	8	20	segregated	segregated	ADJ
brj-23254	8	21	and	and	CCONJ
brj-23254	8	22	a	a	DET
brj-23254	8	23	non	non	ADJ
brj-23254	8	24	-	-	ADJ
brj-23254	8	25	segregated	segregated	ADJ
brj-23254	8	26	dataset	dataset	NOUN
brj-23254	8	27	,	,	PUNCT
brj-23254	8	28	respectively	respectively	ADV
brj-23254	8	29	—	—	PUNCT
brj-23254	8	30	from	from	ADP
brj-23254	8	31	1,000	1,000	NUM
brj-23254	8	32	images	image	NOUN
brj-23254	8	33	(	(	PUNCT
brj-23254	8	34	20	20	NUM
brj-23254	8	35	images	image	NOUN
brj-23254	8	36	from	from	ADP
brj-23254	8	37	each	each	PRON
brj-23254	8	38	of	of	ADP
brj-23254	8	39	the	the	DET
brj-23254	8	40	50	50	NUM
brj-23254	8	41	species	specie	NOUN
brj-23254	8	42	)	)	PUNCT
brj-23254	8	43	were	be	AUX
brj-23254	8	44	compiled	compile	VERB
brj-23254	8	45	.	.	PUNCT
brj-23254	9	1	for	for	ADP
brj-23254	9	2	d1	d1	PROPN
brj-23254	9	3	,	,	PUNCT
brj-23254	9	4	distinct	distinct	ADJ
brj-23254	9	5	images	image	NOUN
brj-23254	9	6	were	be	AUX
brj-23254	9	7	allocated	allocate	VERB
brj-23254	9	8	to	to	ADP
brj-23254	9	9	the	the	DET
brj-23254	9	10	training	training	NOUN
brj-23254	9	11	,	,	PUNCT
brj-23254	9	12	validation	validation	NOUN
brj-23254	9	13	,	,	PUNCT
brj-23254	9	14	and	and	CCONJ
brj-23254	9	15	testing	testing	NOUN
brj-23254	9	16	sets	set	NOUN
brj-23254	9	17	.	.	PUNCT
brj-23254	10	1	however	however	ADV
brj-23254	10	2	,	,	PUNCT
brj-23254	10	3	in	in	ADP
brj-23254	10	4	d2	d2	PROPN
brj-23254	10	5	,	,	PUNCT
brj-23254	10	6	the	the	DET
brj-23254	10	7	same	same	ADJ
brj-23254	10	8	images	image	NOUN
brj-23254	10	9	were	be	AUX
brj-23254	10	10	used	use	VERB
brj-23254	10	11	for	for	ADP
brj-23254	10	12	both	both	DET
brj-23254	10	13	training	training	NOUN
brj-23254	10	14	and	and	CCONJ
brj-23254	10	15	testing	testing	NOUN
brj-23254	10	16	.	.	PUNCT
brj-23254	11	1	furthermore	furthermore	ADV
brj-23254	11	2	,	,	PUNCT
brj-23254	11	3	the	the	DET
brj-23254	11	4	influence	influence	NOUN
brj-23254	11	5	of	of	ADP
brj-23254	11	6	the	the	DET
brj-23254	11	7	evaluation	evaluation	NOUN
brj-23254	11	8	methodology	methodology	NOUN
brj-23254	11	9	on	on	ADP
brj-23254	11	10	the	the	DET
brj-23254	11	11	identification	identification	NOUN
brj-23254	11	12	accuracy	accuracy	NOUN
brj-23254	11	13	was	be	AUX
brj-23254	11	14	investigated	investigate	VERB
brj-23254	11	15	by	by	ADP
brj-23254	11	16	comparing	compare	VERB
brj-23254	11	17	two	two	NUM
brj-23254	11	18	approaches	approach	NOUN
brj-23254	11	19	:	:	PUNCT
brj-23254	11	20	patch	patch	ADJ
brj-23254	11	21	evaluation	evaluation	NOUN
brj-23254	11	22	and	and	CCONJ
brj-23254	11	23	e2	e2	NOUN
brj-23254	11	24	image	image	NOUN
brj-23254	11	25	evaluation	evaluation	NOUN
brj-23254	11	26	.	.	PUNCT
brj-23254	12	1	the	the	DET
brj-23254	12	2	accuracy	accuracy	NOUN
brj-23254	12	3	of	of	ADP
brj-23254	12	4	the	the	DET
brj-23254	12	5	model	model	NOUN
brj-23254	12	6	for	for	ADP
brj-23254	12	7	uniformly	uniformly	ADV
brj-23254	12	8	sized	sized	ADJ
brj-23254	12	9	images	image	NOUN
brj-23254	12	10	was	be	AUX
brj-23254	12	11	approximately	approximately	ADV
brj-23254	12	12	90	90	NUM
brj-23254	12	13	%	%	NOUN
brj-23254	12	14	,	,	PUNCT
brj-23254	12	15	whereas	whereas	SCONJ
brj-23254	12	16	that	that	PRON
brj-23254	12	17	for	for	ADP
brj-23254	12	18	variably	variably	ADV
brj-23254	12	19	sized	sized	ADJ
brj-23254	12	20	images	image	NOUN
brj-23254	12	21	it	it	PRON
brj-23254	12	22	was	be	AUX
brj-23254	12	23	approximately	approximately	ADV
brj-23254	12	24	70	70	NUM
brj-23254	12	25	%	%	NOUN
brj-23254	12	26	.	.	PUNCT
brj-23254	13	1	doi	doi	NOUN
brj-23254	13	2	:	:	PUNCT
brj-23254	13	3	10.15376	10.15376	NUM
brj-23254	13	4	/	/	SYM
brj-23254	13	5	biores.19.3.4838	biores.19.3.4838	NOUN
brj-23254	13	6	-	-	PUNCT
brj-23254	13	7	4851	4851	NUM
brj-23254	13	8	keywords	keyword	NOUN
brj-23254	13	9	:	:	PUNCT
brj-23254	13	10	wood	wood	NOUN
brj-23254	13	11	species	specie	NOUN
brj-23254	13	12	identification	identification	NOUN
brj-23254	13	13	;	;	PUNCT
brj-23254	13	14	microscopic	microscopic	ADJ
brj-23254	13	15	cross	cross	ADJ
brj-23254	13	16	-	-	ADJ
brj-23254	13	17	sectional	sectional	ADJ
brj-23254	13	18	images	image	NOUN
brj-23254	13	19	;	;	PUNCT
brj-23254	13	20	convolutional	convolutional	ADJ
brj-23254	13	21	neural	neural	ADJ
brj-23254	13	22	networks	network	NOUN
brj-23254	13	23	(	(	PUNCT
brj-23254	13	24	cnn	cnn	PROPN
brj-23254	13	25	)	)	PUNCT
brj-23254	13	26	;	;	PUNCT
brj-23254	13	27	practical	practical	ADJ
brj-23254	13	28	accuracy	accuracy	NOUN
brj-23254	13	29	;	;	PUNCT
brj-23254	13	30	interactive	interactive	ADJ
brj-23254	13	31	platform	platform	NOUN
brj-23254	13	32	;	;	PUNCT
brj-23254	13	33	web	web	NOUN
brj-23254	13	34	-	-	PUNCT
brj-23254	13	35	based	base	VERB
brj-23254	13	36	identification	identification	NOUN
brj-23254	13	37	contact	contact	NOUN
brj-23254	13	38	information	information	NOUN
brj-23254	13	39	:	:	PUNCT
brj-23254	13	40	a	a	DET
brj-23254	13	41	:	:	PUNCT
brj-23254	13	42	graduate	graduate	NOUN
brj-23254	13	43	school	school	NOUN
brj-23254	13	44	of	of	ADP
brj-23254	13	45	bioagricultural	bioagricultural	ADJ
brj-23254	13	46	sciences	sciences	PROPN
brj-23254	13	47	,	,	PUNCT
brj-23254	13	48	nagoya	nagoya	PROPN
brj-23254	13	49	university	university	PROPN
brj-23254	13	50	,	,	PUNCT
brj-23254	13	51	furo	furo	PROPN
brj-23254	13	52	-	-	PUNCT
brj-23254	13	53	cho	cho	PROPN
brj-23254	13	54	,	,	PUNCT
brj-23254	13	55	chikusa	chikusa	PROPN
brj-23254	13	56	-	-	PUNCT
brj-23254	13	57	ku	ku	PROPN
brj-23254	13	58	,	,	PUNCT
brj-23254	13	59	nagoya	nagoya	PROPN
brj-23254	13	60	464	464	NUM
brj-23254	13	61	-	-	PUNCT
brj-23254	13	62	8601	8601	NUM
brj-23254	13	63	,	,	PUNCT
brj-23254	13	64	japan	japan	PROPN
brj-23254	13	65	;	;	PUNCT
brj-23254	13	66	b	b	X
brj-23254	13	67	:	:	PUNCT
brj-23254	13	68	forestry	forestry	NOUN
brj-23254	13	69	and	and	CCONJ
brj-23254	13	70	forest	forest	NOUN
brj-23254	13	71	products	product	NOUN
brj-23254	13	72	research	research	PROPN
brj-23254	13	73	institute	institute	PROPN
brj-23254	13	74	,	,	PUNCT
brj-23254	13	75	matsunosato	matsunosato	PROPN
brj-23254	13	76	,	,	PUNCT
brj-23254	13	77	tsukuba	tsukuba	PROPN
brj-23254	13	78	305	305	NUM
brj-23254	13	79	-	-	SYM
brj-23254	13	80	8687	8687	NUM
brj-23254	13	81	,	,	PUNCT
brj-23254	13	82	japan	japan	PROPN
brj-23254	13	83	;	;	PUNCT
brj-23254	13	84	*	*	PUNCT
brj-23254	13	85	corresponding	correspond	VERB
brj-23254	13	86	author	author	NOUN
brj-23254	13	87	:	:	PUNCT
brj-23254	13	88	inatetsu@agr.nagoya-u.ac.jp	inatetsu@agr.nagoya-u.ac.jp	NOUN
brj-23254	13	89	introduction	introduction	NOUN
brj-23254	13	90	the	the	DET
brj-23254	13	91	accurate	accurate	ADJ
brj-23254	13	92	identification	identification	NOUN
brj-23254	13	93	of	of	ADP
brj-23254	13	94	wood	wood	NOUN
brj-23254	13	95	species	specie	NOUN
brj-23254	13	96	is	be	AUX
brj-23254	13	97	important	important	ADJ
brj-23254	13	98	for	for	ADP
brj-23254	13	99	efficient	efficient	ADJ
brj-23254	13	100	resource	resource	NOUN
brj-23254	13	101	utilization	utilization	NOUN
brj-23254	13	102	and	and	CCONJ
brj-23254	13	103	archaeological	archaeological	ADJ
brj-23254	13	104	research	research	NOUN
brj-23254	13	105	.	.	PUNCT
brj-23254	14	1	however	however	ADV
brj-23254	14	2	,	,	PUNCT
brj-23254	14	3	discerning	discern	VERB
brj-23254	14	4	species	specie	NOUN
brj-23254	14	5	using	use	VERB
brj-23254	14	6	microscopic	microscopic	ADJ
brj-23254	14	7	cross	cross	ADJ
brj-23254	14	8	-	-	ADJ
brj-23254	14	9	sectional	sectional	ADJ
brj-23254	14	10	images	image	NOUN
brj-23254	14	11	requires	require	VERB
brj-23254	14	12	prior	prior	ADJ
brj-23254	14	13	knowledge	knowledge	NOUN
brj-23254	14	14	or	or	CCONJ
brj-23254	14	15	experience	experience	NOUN
brj-23254	14	16	related	relate	VERB
brj-23254	14	17	to	to	ADP
brj-23254	14	18	the	the	DET
brj-23254	14	19	sizes	size	NOUN
brj-23254	14	20	and	and	CCONJ
brj-23254	14	21	positions	position	NOUN
brj-23254	14	22	of	of	ADP
brj-23254	14	23	vessel	vessel	NOUN
brj-23254	14	24	or	or	CCONJ
brj-23254	14	25	tracheid	tracheid	NOUN
brj-23254	14	26	in	in	ADP
brj-23254	14	27	wood	wood	NOUN
brj-23254	14	28	cells	cell	NOUN
brj-23254	14	29	.	.	PUNCT
brj-23254	15	1	in	in	ADP
brj-23254	15	2	the	the	DET
brj-23254	15	3	context	context	NOUN
brj-23254	15	4	of	of	ADP
brj-23254	15	5	addressing	address	VERB
brj-23254	15	6	illegal	illegal	ADJ
brj-23254	15	7	logging	logging	NOUN
brj-23254	15	8	practices	practice	NOUN
brj-23254	15	9	and	and	CCONJ
brj-23254	15	10	conducting	conduct	VERB
brj-23254	15	11	comprehensive	comprehensive	ADJ
brj-23254	15	12	wood	wood	NOUN
brj-23254	15	13	property	property	NOUN
brj-23254	15	14	analyses	analysis	NOUN
brj-23254	15	15	,	,	PUNCT
brj-23254	15	16	there	there	PRON
brj-23254	15	17	is	be	VERB
brj-23254	15	18	a	a	DET
brj-23254	15	19	pressing	press	VERB
brj-23254	15	20	contemporary	contemporary	ADJ
brj-23254	15	21	requirement	requirement	NOUN
brj-23254	15	22	for	for	ADP
brj-23254	15	23	the	the	DET
brj-23254	15	24	advancement	advancement	NOUN
brj-23254	15	25	and	and	CCONJ
brj-23254	15	26	implementation	implementation	NOUN
brj-23254	15	27	of	of	ADP
brj-23254	15	28	a	a	DET
brj-23254	15	29	machine	machine	NOUN
brj-23254	15	30	learningbased	learningbase	VERB
brj-23254	15	31	systems	system	NOUN
brj-23254	15	32	dedicated	dedicate	VERB
brj-23254	15	33	to	to	ADP
brj-23254	15	34	wood	wood	NOUN
brj-23254	15	35	species	specie	NOUN
brj-23254	15	36	identification	identification	NOUN
brj-23254	15	37	.	.	PUNCT
brj-23254	16	1	deep	deep	ADJ
brj-23254	16	2	learning	learning	NOUN
brj-23254	16	3	has	have	AUX
brj-23254	16	4	emerged	emerge	VERB
brj-23254	16	5	as	as	ADP
brj-23254	16	6	a	a	DET
brj-23254	16	7	dominant	dominant	ADJ
brj-23254	16	8	research	research	NOUN
brj-23254	16	9	trend	trend	NOUN
brj-23254	16	10	worldwide	worldwide	ADV
brj-23254	16	11	and	and	CCONJ
brj-23254	16	12	is	be	AUX
brj-23254	16	13	applicable	applicable	ADJ
brj-23254	16	14	to	to	ADP
brj-23254	16	15	classification	classification	NOUN
brj-23254	16	16	,	,	PUNCT
brj-23254	16	17	segmentation	segmentation	NOUN
brj-23254	16	18	,	,	PUNCT
brj-23254	16	19	and	and	CCONJ
brj-23254	16	20	detection	detection	NOUN
brj-23254	16	21	with	with	ADP
brj-23254	16	22	high	high	ADJ
brj-23254	16	23	accuracy	accuracy	NOUN
brj-23254	16	24	.	.	PUNCT
brj-23254	17	1	it	it	PRON
brj-23254	17	2	is	be	AUX
brj-23254	17	3	characterized	characterize	VERB
brj-23254	17	4	by	by	ADP
brj-23254	17	5	a	a	DET
brj-23254	17	6	structure	structure	NOUN
brj-23254	17	7	that	that	PRON
brj-23254	17	8	mimics	mimic	VERB
brj-23254	17	9	the	the	DET
brj-23254	17	10	neurons	neuron	NOUN
brj-23254	17	11	and	and	CCONJ
brj-23254	17	12	synapses	synapsis	NOUN
brj-23254	17	13	in	in	ADP
brj-23254	17	14	the	the	DET
brj-23254	17	15	human	human	ADJ
brj-23254	17	16	brain	brain	NOUN
brj-23254	17	17	.	.	PUNCT
brj-23254	18	1	each	each	DET
brj-23254	18	2	neuron	neuron	NOUN
brj-23254	18	3	receives	receive	VERB
brj-23254	18	4	information	information	NOUN
brj-23254	18	5	as	as	ADP
brj-23254	18	6	an	an	DET
brj-23254	18	7	input	input	NOUN
brj-23254	18	8	and	and	CCONJ
brj-23254	18	9	transmits	transmit	VERB
brj-23254	18	10	the	the	DET
brj-23254	18	11	calculated	calculated	ADJ
brj-23254	18	12	data	datum	NOUN
brj-23254	18	13	via	via	ADP
brj-23254	18	14	a	a	DET
brj-23254	18	15	synapse	synapse	NOUN
brj-23254	18	16	(	(	PUNCT
brj-23254	18	17	lecun	lecun	PROPN
brj-23254	18	18	et	et	PROPN
brj-23254	18	19	al	al	PROPN
brj-23254	18	20	.	.	PROPN
brj-23254	18	21	1998	1998	NUM
brj-23254	18	22	)	)	PUNCT
brj-23254	18	23	.	.	PUNCT
brj-23254	19	1	four	four	NUM
brj-23254	19	2	dominant	dominant	ADJ
brj-23254	19	3	machine	machine	NOUN
brj-23254	19	4	learning	learn	VERB
brj-23254	19	5	methods	method	NOUN
brj-23254	19	6	are	be	AUX
brj-23254	19	7	employed	employ	VERB
brj-23254	19	8	in	in	ADP
brj-23254	19	9	the	the	DET
brj-23254	19	10	deep	deep	ADJ
brj-23254	19	11	learning	learning	NOUN
brj-23254	19	12	domain	domain	NOUN
brj-23254	19	13	:	:	PUNCT
brj-23254	19	14	convolutional	convolutional	ADJ
brj-23254	19	15	neural	neural	ADJ
brj-23254	19	16	networks	network	NOUN
brj-23254	19	17	(	(	PUNCT
brj-23254	19	18	cnns	cnns	PROPN
brj-23254	19	19	)	)	PUNCT
brj-23254	19	20	for	for	ADP
brj-23254	19	21	image	image	NOUN
brj-23254	19	22	recognition	recognition	NOUN
brj-23254	19	23	(	(	PUNCT
brj-23254	19	24	drakopoulos	drakopoulo	NOUN
brj-23254	19	25	et	et	PROPN
brj-23254	19	26	al	al	PROPN
brj-23254	19	27	.	.	PROPN
brj-23254	19	28	2021	2021	NUM
brj-23254	19	29	)	)	PUNCT
brj-23254	19	30	,	,	PUNCT
brj-23254	19	31	recurrent	recurrent	ADJ
brj-23254	19	32	neural	neural	ADJ
brj-23254	19	33	peer	peer	NOUN
brj-23254	19	34	-	-	PUNCT
brj-23254	19	35	reviewed	review	VERB
brj-23254	19	36	article	article	NOUN
brj-23254	19	37	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	19	38	ma	ma	PROPN
brj-23254	19	39	et	et	PROPN
brj-23254	19	40	al	al	PROPN
brj-23254	19	41	.	.	PROPN
brj-23254	20	1	(	(	PUNCT
brj-23254	20	2	2024	2024	NUM
brj-23254	20	3	)	)	PUNCT
brj-23254	20	4	.	.	PUNCT
brj-23254	21	1	“	"	PUNCT
brj-23254	21	2	wood	wood	NOUN
brj-23254	21	3	i	i	X
brj-23254	21	4	d	d	PROPN
brj-23254	21	5	via	via	ADP
brj-23254	21	6	deep	deep	ADJ
brj-23254	21	7	learning	learning	NOUN
brj-23254	21	8	,	,	PUNCT
brj-23254	21	9	”	"	PUNCT
brj-23254	21	10	bioresources	bioresource	NOUN
brj-23254	21	11	19(3	19(3	NUM
brj-23254	21	12	)	)	PUNCT
brj-23254	21	13	,	,	PUNCT
brj-23254	21	14	4838	4838	NUM
brj-23254	21	15	-	-	SYM
brj-23254	21	16	4851	4851	NUM
brj-23254	21	17	.	.	PUNCT
brj-23254	22	1	4839	4839	NUM
brj-23254	22	2	networks	network	NOUN
brj-23254	22	3	used	use	VERB
brj-23254	22	4	for	for	ADP
brj-23254	22	5	time	time	NOUN
brj-23254	22	6	-	-	PUNCT
brj-23254	22	7	series	series	NOUN
brj-23254	22	8	data	datum	NOUN
brj-23254	22	9	analysis	analysis	NOUN
brj-23254	22	10	(	(	PUNCT
brj-23254	22	11	sherstinsky	sherstinsky	NOUN
brj-23254	22	12	2020	2020	NUM
brj-23254	22	13	)	)	PUNCT
brj-23254	22	14	,	,	PUNCT
brj-23254	22	15	autoencoders	autoencoder	NOUN
brj-23254	22	16	used	use	VERB
brj-23254	22	17	for	for	ADP
brj-23254	22	18	dimensionality	dimensionality	NOUN
brj-23254	22	19	reduction	reduction	NOUN
brj-23254	22	20	,	,	PUNCT
brj-23254	22	21	and	and	CCONJ
brj-23254	22	22	generative	generative	ADJ
brj-23254	22	23	adversarial	adversarial	ADJ
brj-23254	22	24	networks	network	NOUN
brj-23254	22	25	used	use	VERB
brj-23254	22	26	for	for	ADP
brj-23254	22	27	image	image	NOUN
brj-23254	22	28	generation	generation	NOUN
brj-23254	22	29	(	(	PUNCT
brj-23254	22	30	goodfellow	goodfellow	PROPN
brj-23254	22	31	et	et	PROPN
brj-23254	22	32	al	al	PROPN
brj-23254	22	33	.	.	PROPN
brj-23254	22	34	2014	2014	NUM
brj-23254	22	35	)	)	PUNCT
brj-23254	22	36	.	.	PUNCT
brj-23254	23	1	among	among	ADP
brj-23254	23	2	the	the	DET
brj-23254	23	3	methodologies	methodology	NOUN
brj-23254	23	4	utilized	utilize	VERB
brj-23254	23	5	,	,	PUNCT
brj-23254	23	6	cnns	cnn	NOUN
brj-23254	23	7	have	have	AUX
brj-23254	23	8	been	be	AUX
brj-23254	23	9	used	use	VERB
brj-23254	23	10	for	for	ADP
brj-23254	23	11	the	the	DET
brj-23254	23	12	recognition	recognition	NOUN
brj-23254	23	13	of	of	ADP
brj-23254	23	14	wood	wood	NOUN
brj-23254	23	15	defects	defect	NOUN
brj-23254	23	16	and	and	CCONJ
brj-23254	23	17	the	the	DET
brj-23254	23	18	identification	identification	NOUN
brj-23254	23	19	of	of	ADP
brj-23254	23	20	wood	wood	NOUN
brj-23254	23	21	species	specie	NOUN
brj-23254	23	22	.	.	PUNCT
brj-23254	24	1	oktaria	oktaria	PROPN
brj-23254	24	2	et	et	PROPN
brj-23254	24	3	al	al	PROPN
brj-23254	24	4	.	.	PROPN
brj-23254	25	1	(	(	PUNCT
brj-23254	25	2	2019	2019	NUM
brj-23254	25	3	)	)	PUNCT
brj-23254	25	4	reported	report	VERB
brj-23254	25	5	an	an	DET
brj-23254	25	6	accuracy	accuracy	NOUN
brj-23254	25	7	of	of	ADP
brj-23254	25	8	97	97	NUM
brj-23254	25	9	%	%	NOUN
brj-23254	25	10	in	in	ADP
brj-23254	25	11	the	the	DET
brj-23254	25	12	identification	identification	NOUN
brj-23254	25	13	of	of	ADP
brj-23254	25	14	30	30	NUM
brj-23254	25	15	wood	wood	NOUN
brj-23254	25	16	species	specie	NOUN
brj-23254	25	17	from	from	ADP
brj-23254	25	18	macroscopic	macroscopic	ADJ
brj-23254	25	19	images	image	NOUN
brj-23254	25	20	using	use	VERB
brj-23254	25	21	a	a	DET
brj-23254	25	22	cnn	cnn	NOUN
brj-23254	25	23	via	via	ADP
brj-23254	25	24	resnet	resnet	NOUN
brj-23254	25	25	transfer	transfer	NOUN
brj-23254	25	26	learning	learning	NOUN
brj-23254	25	27	.	.	PUNCT
brj-23254	26	1	likewise	likewise	ADV
brj-23254	26	2	,	,	PUNCT
brj-23254	26	3	an	an	DET
brj-23254	26	4	accuracy	accuracy	NOUN
brj-23254	26	5	of	of	ADP
brj-23254	26	6	97.31	97.31	NUM
brj-23254	26	7	±	±	NUM
brj-23254	26	8	1.85	1.85	NUM
brj-23254	26	9	%	%	NOUN
brj-23254	26	10	was	be	AUX
brj-23254	26	11	obtained	obtain	VERB
brj-23254	26	12	via	via	ADP
brj-23254	26	13	resnet	resnet	ADJ
brj-23254	26	14	transfer	transfer	NOUN
brj-23254	26	15	learning	learn	VERB
brj-23254	26	16	when	when	SCONJ
brj-23254	26	17	classifying	classify	VERB
brj-23254	26	18	11	11	NUM
brj-23254	26	19	wood	wood	NOUN
brj-23254	26	20	species	specie	NOUN
brj-23254	26	21	of	of	ADP
brj-23254	26	22	macroscopic	macroscopic	ADJ
brj-23254	26	23	images	image	NOUN
brj-23254	26	24	by	by	ADP
brj-23254	26	25	geus	geus	NOUN
brj-23254	26	26	et	et	PROPN
brj-23254	26	27	al	al	PROPN
brj-23254	26	28	.	.	PROPN
brj-23254	27	1	(	(	PUNCT
brj-23254	27	2	2021	2021	NUM
brj-23254	27	3	)	)	PUNCT
brj-23254	27	4	.	.	PUNCT
brj-23254	28	1	they	they	PRON
brj-23254	28	2	subsequently	subsequently	ADV
brj-23254	28	3	identified	identify	VERB
brj-23254	28	4	281	281	NUM
brj-23254	28	5	wood	wood	NOUN
brj-23254	28	6	species	specie	NOUN
brj-23254	28	7	using	use	VERB
brj-23254	28	8	densenet	densenet	NOUN
brj-23254	28	9	with	with	ADP
brj-23254	28	10	an	an	DET
brj-23254	28	11	accuracy	accuracy	NOUN
brj-23254	28	12	of	of	ADP
brj-23254	28	13	98.75	98.75	NUM
brj-23254	28	14	%	%	NOUN
brj-23254	28	15	(	(	PUNCT
brj-23254	28	16	geus	geus	NOUN
brj-23254	28	17	et	et	PROPN
brj-23254	28	18	al	al	PROPN
brj-23254	28	19	.	.	PROPN
brj-23254	28	20	2020	2020	NUM
brj-23254	28	21	)	)	PUNCT
brj-23254	28	22	.	.	PUNCT
brj-23254	29	1	transfer	transfer	NOUN
brj-23254	29	2	learning	learning	NOUN
brj-23254	29	3	is	be	AUX
brj-23254	29	4	an	an	DET
brj-23254	29	5	effective	effective	ADJ
brj-23254	29	6	approach	approach	NOUN
brj-23254	29	7	for	for	ADP
brj-23254	29	8	handling	handle	VERB
brj-23254	29	9	limited	limited	ADJ
brj-23254	29	10	datasets	dataset	NOUN
brj-23254	29	11	(	(	PUNCT
brj-23254	29	12	sun	sun	PROPN
brj-23254	29	13	et	et	PROPN
brj-23254	29	14	al	al	PROPN
brj-23254	29	15	.	.	PROPN
brj-23254	29	16	2021	2021	NUM
brj-23254	29	17	)	)	PUNCT
brj-23254	29	18	.	.	PUNCT
brj-23254	30	1	in	in	ADP
brj-23254	30	2	their	their	PRON
brj-23254	30	3	study	study	NOUN
brj-23254	30	4	,	,	PUNCT
brj-23254	30	5	25	25	NUM
brj-23254	30	6	species	specie	NOUN
brj-23254	30	7	(	(	PUNCT
brj-23254	30	8	120	120	NUM
brj-23254	30	9	for	for	ADP
brj-23254	30	10	each	each	DET
brj-23254	30	11	species	specie	NOUN
brj-23254	30	12	)	)	PUNCT
brj-23254	30	13	were	be	AUX
brj-23254	30	14	successfully	successfully	ADV
brj-23254	30	15	identified	identify	VERB
brj-23254	30	16	with	with	ADP
brj-23254	30	17	99.6	99.6	NUM
brj-23254	30	18	%	%	NOUN
brj-23254	30	19	accuracy	accuracy	NOUN
brj-23254	30	20	.	.	PUNCT
brj-23254	31	1	he	he	PRON
brj-23254	31	2	et	et	PROPN
brj-23254	31	3	al	al	PROPN
brj-23254	31	4	.	.	PROPN
brj-23254	31	5	(	(	PUNCT
brj-23254	31	6	2021	2021	NUM
brj-23254	31	7	)	)	PUNCT
brj-23254	31	8	trained	train	VERB
brj-23254	31	9	and	and	CCONJ
brj-23254	31	10	evaluated	evaluate	VERB
brj-23254	31	11	nine	nine	NUM
brj-23254	31	12	cnn	cnn	PROPN
brj-23254	31	13	architectures	architecture	NOUN
brj-23254	31	14	using	use	VERB
brj-23254	31	15	two	two	NUM
brj-23254	31	16	macroscopic	macroscopic	ADJ
brj-23254	31	17	wood	wood	NOUN
brj-23254	31	18	image	image	NOUN
brj-23254	31	19	datasets	dataset	NOUN
brj-23254	31	20	.	.	PUNCT
brj-23254	32	1	their	their	PRON
brj-23254	32	2	proposed	propose	VERB
brj-23254	32	3	network	network	NOUN
brj-23254	32	4	achieved	achieve	VERB
brj-23254	32	5	a	a	DET
brj-23254	32	6	100	100	NUM
brj-23254	32	7	%	%	NOUN
brj-23254	32	8	test	test	NOUN
brj-23254	32	9	rate	rate	NOUN
brj-23254	32	10	on	on	ADP
brj-23254	32	11	a	a	DET
brj-23254	32	12	dataset	dataset	NOUN
brj-23254	32	13	comprising	comprise	VERB
brj-23254	32	14	eight	eight	NUM
brj-23254	32	15	wood	wood	NOUN
brj-23254	32	16	species	specie	NOUN
brj-23254	32	17	and	and	CCONJ
brj-23254	32	18	918	918	NUM
brj-23254	32	19	images	image	NOUN
brj-23254	32	20	after	after	ADP
brj-23254	32	21	two	two	NUM
brj-23254	32	22	rounds	round	NOUN
brj-23254	32	23	of	of	ADP
brj-23254	32	24	training	training	NOUN
brj-23254	32	25	.	.	PUNCT
brj-23254	33	1	in	in	ADP
brj-23254	33	2	another	another	DET
brj-23254	33	3	dataset	dataset	NOUN
brj-23254	33	4	with	with	ADP
brj-23254	33	5	41	41	NUM
brj-23254	33	6	species	specie	NOUN
brj-23254	33	7	and	and	CCONJ
brj-23254	33	8	11,984	11,984	NUM
brj-23254	33	9	images	image	NOUN
brj-23254	33	10	,	,	PUNCT
brj-23254	33	11	it	it	PRON
brj-23254	33	12	attained	attain	VERB
brj-23254	33	13	a	a	DET
brj-23254	33	14	98.81	98.81	NUM
brj-23254	33	15	%	%	NOUN
brj-23254	33	16	test	test	NOUN
brj-23254	33	17	recognition	recognition	NOUN
brj-23254	33	18	rate	rate	NOUN
brj-23254	33	19	after	after	ADP
brj-23254	33	20	three	three	NUM
brj-23254	33	21	training	training	NOUN
brj-23254	33	22	cycles	cycle	NOUN
brj-23254	33	23	.	.	PUNCT
brj-23254	34	1	moulin	moulin	PROPN
brj-23254	34	2	et	et	PROPN
brj-23254	34	3	al	al	PROPN
brj-23254	34	4	.	.	PROPN
brj-23254	34	5	(	(	PUNCT
brj-23254	34	6	2022	2022	NUM
brj-23254	34	7	)	)	PUNCT
brj-23254	34	8	developed	develop	VERB
brj-23254	34	9	a	a	DET
brj-23254	34	10	custom	custom	NOUN
brj-23254	34	11	deep	deep	ADJ
brj-23254	34	12	cnn	cnn	PROPN
brj-23254	34	13	model	model	NOUN
brj-23254	34	14	to	to	PART
brj-23254	34	15	differentiate	differentiate	VERB
brj-23254	34	16	between	between	ADP
brj-23254	34	17	images	image	NOUN
brj-23254	34	18	of	of	ADP
brj-23254	34	19	brazilian	brazilian	ADJ
brj-23254	34	20	native	native	ADJ
brj-23254	34	21	and	and	CCONJ
brj-23254	34	22	introduced	introduce	VERB
brj-23254	34	23	wood	wood	NOUN
brj-23254	34	24	species	specie	NOUN
brj-23254	34	25	.	.	PUNCT
brj-23254	35	1	the	the	DET
brj-23254	35	2	custom	custom	NOUN
brj-23254	35	3	model	model	NOUN
brj-23254	35	4	achieved	achieve	VERB
brj-23254	35	5	excellent	excellent	ADJ
brj-23254	35	6	accuracy	accuracy	NOUN
brj-23254	35	7	(	(	PUNCT
brj-23254	35	8	>	>	NOUN
brj-23254	35	9	0.90	0.90	NUM
brj-23254	35	10	)	)	PUNCT
brj-23254	35	11	and	and	CCONJ
brj-23254	35	12	,	,	PUNCT
brj-23254	35	13	in	in	ADP
brj-23254	35	14	some	some	DET
brj-23254	35	15	cases	case	NOUN
brj-23254	35	16	,	,	PUNCT
brj-23254	35	17	even	even	ADV
brj-23254	35	18	surpassed	surpass	VERB
brj-23254	35	19	human	human	ADJ
brj-23254	35	20	identification	identification	NOUN
brj-23254	35	21	with	with	ADP
brj-23254	35	22	an	an	DET
brj-23254	35	23	f1	f1	NOUN
brj-23254	35	24	-	-	PUNCT
brj-23254	35	25	score	score	NOUN
brj-23254	35	26	of	of	ADP
brj-23254	35	27	0.99	0.99	NUM
brj-23254	35	28	.	.	PUNCT
brj-23254	36	1	lens	lens	NOUN
brj-23254	36	2	et	et	PROPN
brj-23254	36	3	al	al	PROPN
brj-23254	36	4	.	.	PROPN
brj-23254	36	5	(	(	PUNCT
brj-23254	36	6	2020	2020	NUM
brj-23254	36	7	)	)	PUNCT
brj-23254	36	8	asserted	assert	VERB
brj-23254	36	9	that	that	SCONJ
brj-23254	36	10	computers	computer	NOUN
brj-23254	36	11	can	can	AUX
brj-23254	36	12	differentiate	differentiate	VERB
brj-23254	36	13	between	between	ADP
brj-23254	36	14	wood	wood	NOUN
brj-23254	36	15	species	specie	NOUN
brj-23254	36	16	by	by	ADP
brj-23254	36	17	focusing	focus	VERB
brj-23254	36	18	on	on	ADP
brj-23254	36	19	the	the	DET
brj-23254	36	20	corners	corner	NOUN
brj-23254	36	21	and	and	CCONJ
brj-23254	36	22	edges	edge	NOUN
brj-23254	36	23	of	of	ADP
brj-23254	36	24	tissues	tissue	NOUN
brj-23254	36	25	,	,	PUNCT
brj-23254	36	26	such	such	ADJ
brj-23254	36	27	as	as	ADP
brj-23254	36	28	vessel	vessel	NOUN
brj-23254	36	29	elements	element	NOUN
brj-23254	36	30	.	.	PUNCT
brj-23254	37	1	kwon	kwon	VERB
brj-23254	37	2	et	et	PROPN
brj-23254	37	3	al	al	PROPN
brj-23254	37	4	.	.	PROPN
brj-23254	38	1	(	(	PUNCT
brj-23254	38	2	2017	2017	NUM
brj-23254	38	3	)	)	PUNCT
brj-23254	38	4	and	and	CCONJ
brj-23254	38	5	lopes	lope	NOUN
brj-23254	38	6	et	et	PROPN
brj-23254	38	7	al	al	PROPN
brj-23254	38	8	.	.	PROPN
brj-23254	39	1	(	(	PUNCT
brj-23254	39	2	2020	2020	NUM
brj-23254	39	3	)	)	PUNCT
brj-23254	39	4	demonstrated	demonstrate	VERB
brj-23254	39	5	through	through	ADP
brj-23254	39	6	their	their	PRON
brj-23254	39	7	respective	respective	ADJ
brj-23254	39	8	studies	study	NOUN
brj-23254	39	9	that	that	PRON
brj-23254	39	10	cnns	cnn	NOUN
brj-23254	39	11	,	,	PUNCT
brj-23254	39	12	utilizing	utilize	VERB
brj-23254	39	13	transfer	transfer	NOUN
brj-23254	39	14	learning	learning	NOUN
brj-23254	39	15	techniques	technique	NOUN
brj-23254	39	16	,	,	PUNCT
brj-23254	39	17	exhibit	exhibit	VERB
brj-23254	39	18	remarkable	remarkable	ADJ
brj-23254	39	19	accuracy	accuracy	NOUN
brj-23254	39	20	in	in	ADP
brj-23254	39	21	the	the	DET
brj-23254	39	22	identification	identification	NOUN
brj-23254	39	23	of	of	ADP
brj-23254	39	24	wood	wood	NOUN
brj-23254	39	25	species	specie	NOUN
brj-23254	39	26	across	across	ADP
brj-23254	39	27	datasets	dataset	NOUN
brj-23254	39	28	encompassing	encompass	VERB
brj-23254	39	29	both	both	CCONJ
brj-23254	39	30	hardwood	hardwood	NOUN
brj-23254	39	31	and	and	CCONJ
brj-23254	39	32	softwood	softwood	NOUN
brj-23254	39	33	specimens	specimen	NOUN
brj-23254	39	34	.	.	PUNCT
brj-23254	40	1	notably	notably	ADV
brj-23254	40	2	,	,	PUNCT
brj-23254	40	3	one	one	NUM
brj-23254	40	4	study	study	NOUN
brj-23254	40	5	achieved	achieve	VERB
brj-23254	40	6	a	a	DET
brj-23254	40	7	classification	classification	NOUN
brj-23254	40	8	accuracy	accuracy	NOUN
brj-23254	40	9	of	of	ADP
brj-23254	40	10	97.32	97.32	NUM
brj-23254	40	11	%	%	NOUN
brj-23254	40	12	when	when	SCONJ
brj-23254	40	13	employing	employ	VERB
brj-23254	40	14	a	a	DET
brj-23254	40	15	cnn	cnn	NOUN
brj-23254	40	16	to	to	PART
brj-23254	40	17	classify	classify	VERB
brj-23254	40	18	the	the	DET
brj-23254	40	19	microscopic	microscopic	ADJ
brj-23254	40	20	images	image	NOUN
brj-23254	40	21	of	of	ADP
brj-23254	40	22	brazilian	brazilian	ADJ
brj-23254	40	23	wood	wood	NOUN
brj-23254	40	24	specimens	specimen	NOUN
brj-23254	40	25	,	,	PUNCT
brj-23254	40	26	encompassing	encompass	VERB
brj-23254	40	27	112	112	NUM
brj-23254	40	28	species	specie	NOUN
brj-23254	40	29	(	(	PUNCT
brj-23254	40	30	hafemann	hafemann	PROPN
brj-23254	40	31	et	et	PROPN
brj-23254	40	32	al	al	PROPN
brj-23254	40	33	.	.	PROPN
brj-23254	40	34	2014	2014	NUM
brj-23254	40	35	)	)	PUNCT
brj-23254	40	36	.	.	PUNCT
brj-23254	41	1	kırbaş	kırbaş	PROPN
brj-23254	41	2	and	and	CCONJ
brj-23254	41	3	çifci	çifci	ADJ
brj-23254	41	4	(	(	PUNCT
brj-23254	41	5	2022	2022	NUM
brj-23254	41	6	)	)	PUNCT
brj-23254	41	7	delved	delve	VERB
brj-23254	41	8	into	into	ADP
brj-23254	41	9	classifying	classify	VERB
brj-23254	41	10	wood	wood	NOUN
brj-23254	41	11	species	specie	NOUN
brj-23254	41	12	using	use	VERB
brj-23254	41	13	the	the	DET
brj-23254	41	14	wood	wood	NOUN
brj-23254	41	15	-	-	PUNCT
brj-23254	41	16	auth	auth	NOUN
brj-23254	41	17	dataset	dataset	NOUN
brj-23254	41	18	and	and	CCONJ
brj-23254	41	19	assessing	assess	VERB
brj-23254	41	20	the	the	DET
brj-23254	41	21	effectiveness	effectiveness	NOUN
brj-23254	41	22	of	of	ADP
brj-23254	41	23	different	different	ADJ
brj-23254	41	24	deep	deep	ADJ
brj-23254	41	25	learning	learning	NOUN
brj-23254	41	26	architectures	architecture	NOUN
brj-23254	41	27	including	include	VERB
brj-23254	41	28	resnet-50	resnet-50	PROPN
brj-23254	41	29	,	,	PUNCT
brj-23254	41	30	inception	inception	NOUN
brj-23254	41	31	v3	v3	PROPN
brj-23254	41	32	,	,	PUNCT
brj-23254	41	33	xception	xception	NOUN
brj-23254	41	34	,	,	PUNCT
brj-23254	41	35	and	and	CCONJ
brj-23254	41	36	vgg19	vgg19	VERB
brj-23254	41	37	with	with	ADP
brj-23254	41	38	transfer	transfer	NOUN
brj-23254	41	39	learning	learning	NOUN
brj-23254	41	40	.	.	PUNCT
brj-23254	42	1	the	the	DET
brj-23254	42	2	dataset	dataset	NOUN
brj-23254	42	3	comprised	comprise	VERB
brj-23254	42	4	macroscopic	macroscopic	ADJ
brj-23254	42	5	images	image	NOUN
brj-23254	42	6	of	of	ADP
brj-23254	42	7	12	12	NUM
brj-23254	42	8	wood	wood	NOUN
brj-23254	42	9	species	specie	NOUN
brj-23254	42	10	across	across	ADP
brj-23254	42	11	the	the	DET
brj-23254	42	12	cross	cross	NOUN
brj-23254	42	13	,	,	PUNCT
brj-23254	42	14	radial	radial	ADJ
brj-23254	42	15	,	,	PUNCT
brj-23254	42	16	and	and	CCONJ
brj-23254	42	17	tangential	tangential	ADJ
brj-23254	42	18	sections	section	NOUN
brj-23254	42	19	.	.	PUNCT
brj-23254	43	1	the	the	DET
brj-23254	43	2	results	result	NOUN
brj-23254	43	3	indicated	indicate	VERB
brj-23254	43	4	the	the	DET
brj-23254	43	5	superior	superior	ADJ
brj-23254	43	6	performance	performance	NOUN
brj-23254	43	7	of	of	ADP
brj-23254	43	8	xception	xception	NOUN
brj-23254	43	9	,	,	PUNCT
brj-23254	43	10	achieving	achieve	VERB
brj-23254	43	11	a	a	DET
brj-23254	43	12	classification	classification	NOUN
brj-23254	43	13	accuracy	accuracy	NOUN
brj-23254	43	14	of	of	ADP
brj-23254	43	15	95.88	95.88	NUM
brj-23254	43	16	%	%	NOUN
brj-23254	43	17	,	,	PUNCT
brj-23254	43	18	surpassing	surpass	VERB
brj-23254	43	19	that	that	PRON
brj-23254	43	20	of	of	ADP
brj-23254	43	21	the	the	DET
brj-23254	43	22	other	other	ADJ
brj-23254	43	23	models	model	NOUN
brj-23254	43	24	.	.	PUNCT
brj-23254	44	1	hwang	hwang	PROPN
brj-23254	44	2	and	and	CCONJ
brj-23254	44	3	sugiyama	sugiyama	NOUN
brj-23254	44	4	(	(	PUNCT
brj-23254	44	5	2021	2021	NUM
brj-23254	44	6	)	)	PUNCT
brj-23254	44	7	presented	present	VERB
brj-23254	44	8	a	a	DET
brj-23254	44	9	thorough	thorough	ADJ
brj-23254	44	10	assessment	assessment	NOUN
brj-23254	44	11	of	of	ADP
brj-23254	44	12	this	this	DET
brj-23254	44	13	subject	subject	NOUN
brj-23254	44	14	and	and	CCONJ
brj-23254	44	15	provided	provide	VERB
brj-23254	44	16	an	an	DET
brj-23254	44	17	essential	essential	ADJ
brj-23254	44	18	foundation	foundation	NOUN
brj-23254	44	19	for	for	ADP
brj-23254	44	20	the	the	DET
brj-23254	44	21	development	development	NOUN
brj-23254	44	22	of	of	ADP
brj-23254	44	23	a	a	DET
brj-23254	44	24	framework	framework	NOUN
brj-23254	44	25	for	for	ADP
brj-23254	44	26	automatic	automatic	ADJ
brj-23254	44	27	wood	wood	NOUN
brj-23254	44	28	identification	identification	NOUN
brj-23254	44	29	.	.	PUNCT
brj-23254	45	1	this	this	DET
brj-23254	45	2	study	study	NOUN
brj-23254	45	3	also	also	ADV
brj-23254	45	4	highlighted	highlight	VERB
brj-23254	45	5	the	the	DET
brj-23254	45	6	potential	potential	NOUN
brj-23254	45	7	for	for	ADP
brj-23254	45	8	expanding	expand	VERB
brj-23254	45	9	the	the	DET
brj-23254	45	10	use	use	NOUN
brj-23254	45	11	of	of	ADP
brj-23254	45	12	computer	computer	NOUN
brj-23254	45	13	vision	vision	NOUN
brj-23254	45	14	in	in	ADP
brj-23254	45	15	wood	wood	NOUN
brj-23254	45	16	science	science	NOUN
brj-23254	45	17	,	,	PUNCT
brj-23254	45	18	offering	offer	VERB
brj-23254	45	19	an	an	DET
brj-23254	45	20	insightful	insightful	ADJ
brj-23254	45	21	discourse	discourse	NOUN
brj-23254	45	22	on	on	ADP
brj-23254	45	23	the	the	DET
brj-23254	45	24	future	future	ADJ
brj-23254	45	25	trajectory	trajectory	NOUN
brj-23254	45	26	of	of	ADP
brj-23254	45	27	the	the	DET
brj-23254	45	28	field	field	NOUN
brj-23254	45	29	.	.	PUNCT
brj-23254	46	1	similarly	similarly	ADV
brj-23254	46	2	,	,	PUNCT
brj-23254	46	3	noteworthy	noteworthy	ADJ
brj-23254	46	4	contributions	contribution	NOUN
brj-23254	46	5	have	have	AUX
brj-23254	46	6	been	be	AUX
brj-23254	46	7	made	make	VERB
brj-23254	46	8	to	to	ADP
brj-23254	46	9	the	the	DET
brj-23254	46	10	utilization	utilization	NOUN
brj-23254	46	11	of	of	ADP
brj-23254	46	12	computer	computer	NOUN
brj-23254	46	13	vision	vision	NOUN
brj-23254	46	14	techniques	technique	NOUN
brj-23254	46	15	for	for	ADP
brj-23254	46	16	the	the	DET
brj-23254	46	17	identification	identification	NOUN
brj-23254	46	18	of	of	ADP
brj-23254	46	19	ring	ring	NOUN
brj-23254	46	20	-	-	PUNCT
brj-23254	46	21	porous	porous	ADJ
brj-23254	46	22	hardwood	hardwood	NOUN
brj-23254	46	23	species	specie	NOUN
brj-23254	46	24	(	(	PUNCT
brj-23254	46	25	ravindran	ravindran	NOUN
brj-23254	46	26	et	et	PROPN
brj-23254	46	27	al	al	PROPN
brj-23254	46	28	.	.	PROPN
brj-23254	46	29	2022	2022	NUM
brj-23254	46	30	)	)	PUNCT
brj-23254	46	31	.	.	PUNCT
brj-23254	47	1	that	that	DET
brj-23254	47	2	research	research	NOUN
brj-23254	47	3	highlights	highlight	VERB
brj-23254	47	4	the	the	DET
brj-23254	47	5	significance	significance	NOUN
brj-23254	47	6	of	of	ADP
brj-23254	47	7	technological	technological	ADJ
brj-23254	47	8	advancements	advancement	NOUN
brj-23254	47	9	in	in	ADP
brj-23254	47	10	promoting	promote	VERB
brj-23254	47	11	sustainability	sustainability	NOUN
brj-23254	47	12	within	within	ADP
brj-23254	47	13	north	north	ADJ
brj-23254	47	14	american	american	ADJ
brj-23254	47	15	wood	wood	NOUN
brj-23254	47	16	product	product	NOUN
brj-23254	47	17	value	value	NOUN
brj-23254	47	18	chains	chain	NOUN
brj-23254	47	19	,	,	PUNCT
brj-23254	47	20	while	while	SCONJ
brj-23254	47	21	presenting	present	VERB
brj-23254	47	22	a	a	DET
brj-23254	47	23	novel	novel	ADJ
brj-23254	47	24	approach	approach	NOUN
brj-23254	47	25	for	for	ADP
brj-23254	47	26	the	the	DET
brj-23254	47	27	precise	precise	ADJ
brj-23254	47	28	identification	identification	NOUN
brj-23254	47	29	of	of	ADP
brj-23254	47	30	specific	specific	ADJ
brj-23254	47	31	types	type	NOUN
brj-23254	47	32	of	of	ADP
brj-23254	47	33	wood	wood	NOUN
brj-23254	47	34	.	.	PUNCT
brj-23254	48	1	fundamentally	fundamentally	ADV
brj-23254	48	2	,	,	PUNCT
brj-23254	48	3	these	these	DET
brj-23254	48	4	two	two	NUM
brj-23254	48	5	studies	study	NOUN
brj-23254	48	6	made	make	VERB
brj-23254	48	7	significant	significant	ADJ
brj-23254	48	8	and	and	CCONJ
brj-23254	48	9	essential	essential	ADJ
brj-23254	48	10	contributions	contribution	NOUN
brj-23254	48	11	to	to	ADP
brj-23254	48	12	the	the	DET
brj-23254	48	13	advancement	advancement	NOUN
brj-23254	48	14	of	of	ADP
brj-23254	48	15	knowledge	knowledge	NOUN
brj-23254	48	16	regarding	regard	VERB
brj-23254	48	17	wood	wood	NOUN
brj-23254	48	18	species	specie	NOUN
brj-23254	48	19	identification	identification	NOUN
brj-23254	48	20	,	,	PUNCT
brj-23254	48	21	with	with	ADP
brj-23254	48	22	particular	particular	ADJ
brj-23254	48	23	focus	focus	NOUN
brj-23254	48	24	on	on	ADP
brj-23254	48	25	the	the	DET
brj-23254	48	26	application	application	NOUN
brj-23254	48	27	of	of	ADP
brj-23254	48	28	computer	computer	NOUN
brj-23254	48	29	vision	vision	NOUN
brj-23254	48	30	methodologies	methodology	NOUN
brj-23254	48	31	.	.	PUNCT
brj-23254	49	1	these	these	DET
brj-23254	49	2	invaluable	invaluable	ADJ
brj-23254	49	3	insights	insight	NOUN
brj-23254	49	4	and	and	CCONJ
brj-23254	49	5	directions	direction	NOUN
brj-23254	49	6	guide	guide	VERB
brj-23254	49	7	the	the	DET
brj-23254	49	8	methodological	methodological	ADJ
brj-23254	49	9	and	and	CCONJ
brj-23254	49	10	theoretical	theoretical	ADJ
brj-23254	49	11	basis	basis	NOUN
brj-23254	49	12	of	of	ADP
brj-23254	49	13	this	this	DET
brj-23254	49	14	current	current	ADJ
brj-23254	49	15	research	research	NOUN
brj-23254	49	16	.	.	PUNCT
brj-23254	50	1	while	while	SCONJ
brj-23254	50	2	numerous	numerous	ADJ
brj-23254	50	3	previous	previous	ADJ
brj-23254	50	4	studies	study	NOUN
brj-23254	50	5	have	have	AUX
brj-23254	50	6	reported	report	VERB
brj-23254	50	7	high	high	ADJ
brj-23254	50	8	accuracy	accuracy	NOUN
brj-23254	50	9	in	in	ADP
brj-23254	50	10	wood	wood	NOUN
brj-23254	50	11	species	specie	NOUN
brj-23254	50	12	identification	identification	NOUN
brj-23254	50	13	,	,	PUNCT
brj-23254	50	14	many	many	ADJ
brj-23254	50	15	have	have	AUX
brj-23254	50	16	not	not	PART
brj-23254	50	17	thoroughly	thoroughly	ADV
brj-23254	50	18	addressed	address	VERB
brj-23254	50	19	the	the	DET
brj-23254	50	20	specific	specific	ADJ
brj-23254	50	21	factors	factor	NOUN
brj-23254	50	22	that	that	PRON
brj-23254	50	23	influence	influence	NOUN
brj-23254	50	24	accuracy	accuracy	NOUN
brj-23254	50	25	and	and	CCONJ
brj-23254	50	26	robustness	robustness	NOUN
brj-23254	50	27	,	,	PUNCT
brj-23254	50	28	such	such	ADJ
brj-23254	50	29	as	as	ADP
brj-23254	50	30	image	image	NOUN
brj-23254	50	31	dimensionality	dimensionality	NOUN
brj-23254	50	32	and	and	CCONJ
brj-23254	50	33	the	the	DET
brj-23254	50	34	distribution	distribution	NOUN
brj-23254	50	35	of	of	ADP
brj-23254	50	36	data	datum	NOUN
brj-23254	50	37	between	between	ADP
brj-23254	50	38	peer	peer	NOUN
brj-23254	50	39	-	-	PUNCT
brj-23254	50	40	reviewed	review	VERB
brj-23254	50	41	article	article	NOUN
brj-23254	50	42	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	50	43	ma	ma	PROPN
brj-23254	50	44	et	et	PROPN
brj-23254	50	45	al	al	PROPN
brj-23254	50	46	.	.	PROPN
brj-23254	51	1	(	(	PUNCT
brj-23254	51	2	2024	2024	NUM
brj-23254	51	3	)	)	PUNCT
brj-23254	51	4	.	.	PUNCT
brj-23254	52	1	“	"	PUNCT
brj-23254	52	2	wood	wood	NOUN
brj-23254	52	3	i	i	X
brj-23254	52	4	d	d	PROPN
brj-23254	52	5	via	via	ADP
brj-23254	52	6	deep	deep	ADJ
brj-23254	52	7	learning	learning	NOUN
brj-23254	52	8	,	,	PUNCT
brj-23254	52	9	”	"	PUNCT
brj-23254	52	10	bioresources	bioresource	NOUN
brj-23254	52	11	19(3	19(3	NUM
brj-23254	52	12	)	)	PUNCT
brj-23254	52	13	,	,	PUNCT
brj-23254	52	14	4838	4838	NUM
brj-23254	52	15	-	-	SYM
brj-23254	52	16	4851	4851	NUM
brj-23254	52	17	.	.	PUNCT
brj-23254	53	1	4840	4840	NUM
brj-23254	53	2	the	the	DET
brj-23254	53	3	training	training	NOUN
brj-23254	53	4	and	and	CCONJ
brj-23254	53	5	testing	testing	NOUN
brj-23254	53	6	sets	set	NOUN
brj-23254	53	7	.	.	PUNCT
brj-23254	54	1	to	to	PART
brj-23254	54	2	develop	develop	VERB
brj-23254	54	3	a	a	DET
brj-23254	54	4	model	model	NOUN
brj-23254	54	5	for	for	ADP
brj-23254	54	6	the	the	DET
brj-23254	54	7	identification	identification	NOUN
brj-23254	54	8	of	of	ADP
brj-23254	54	9	wood	wood	NOUN
brj-23254	54	10	species	specie	NOUN
brj-23254	54	11	based	base	VERB
brj-23254	54	12	on	on	ADP
brj-23254	54	13	microscopic	microscopic	ADJ
brj-23254	54	14	cross	cross	ADJ
brj-23254	54	15	-	-	ADJ
brj-23254	54	16	sectional	sectional	ADJ
brj-23254	54	17	images	image	NOUN
brj-23254	54	18	,	,	PUNCT
brj-23254	54	19	it	it	PRON
brj-23254	54	20	is	be	AUX
brj-23254	54	21	essential	essential	ADJ
brj-23254	54	22	to	to	PART
brj-23254	54	23	discern	discern	VERB
brj-23254	54	24	pertinent	pertinent	ADJ
brj-23254	54	25	features	feature	NOUN
brj-23254	54	26	,	,	PUNCT
brj-23254	54	27	such	such	ADJ
brj-23254	54	28	as	as	ADP
brj-23254	54	29	the	the	DET
brj-23254	54	30	position	position	NOUN
brj-23254	54	31	and	and	CCONJ
brj-23254	54	32	size	size	NOUN
brj-23254	54	33	of	of	ADP
brj-23254	54	34	vessels	vessel	NOUN
brj-23254	54	35	and	and	CCONJ
brj-23254	54	36	tracheids	tracheid	NOUN
brj-23254	54	37	in	in	ADP
brj-23254	54	38	wood	wood	NOUN
brj-23254	54	39	cells	cell	NOUN
brj-23254	54	40	.	.	PUNCT
brj-23254	55	1	however	however	ADV
brj-23254	55	2	,	,	PUNCT
brj-23254	55	3	these	these	DET
brj-23254	55	4	approaches	approach	NOUN
brj-23254	55	5	ideally	ideally	ADV
brj-23254	55	6	require	require	VERB
brj-23254	55	7	consistent	consistent	ADJ
brj-23254	55	8	factors	factor	NOUN
brj-23254	55	9	,	,	PUNCT
brj-23254	55	10	including	include	VERB
brj-23254	55	11	image	image	NOUN
brj-23254	55	12	resolution	resolution	NOUN
brj-23254	55	13	and	and	CCONJ
brj-23254	55	14	calibration	calibration	NOUN
brj-23254	55	15	,	,	PUNCT
brj-23254	55	16	when	when	SCONJ
brj-23254	55	17	using	use	VERB
brj-23254	55	18	microscopes	microscope	NOUN
brj-23254	55	19	with	with	ADP
brj-23254	55	20	different	different	ADJ
brj-23254	55	21	magnification	magnification	NOUN
brj-23254	55	22	ratios	ratio	NOUN
brj-23254	55	23	.	.	PUNCT
brj-23254	56	1	the	the	DET
brj-23254	56	2	objective	objective	NOUN
brj-23254	56	3	of	of	ADP
brj-23254	56	4	this	this	DET
brj-23254	56	5	study	study	NOUN
brj-23254	56	6	was	be	AUX
brj-23254	56	7	to	to	PART
brj-23254	56	8	assess	assess	VERB
brj-23254	56	9	the	the	DET
brj-23254	56	10	discriminatory	discriminatory	ADJ
brj-23254	56	11	capabilities	capability	NOUN
brj-23254	56	12	of	of	ADP
brj-23254	56	13	a	a	DET
brj-23254	56	14	cnn	cnn	NOUN
brj-23254	56	15	for	for	ADP
brj-23254	56	16	classifying	classify	VERB
brj-23254	56	17	different	different	ADJ
brj-23254	56	18	wood	wood	NOUN
brj-23254	56	19	species	specie	NOUN
brj-23254	56	20	,	,	PUNCT
brj-23254	56	21	irrespective	irrespective	ADV
brj-23254	56	22	of	of	ADP
brj-23254	56	23	specific	specific	ADJ
brj-23254	56	24	image	image	NOUN
brj-23254	56	25	characteristics	characteristic	NOUN
brj-23254	56	26	.	.	PUNCT
brj-23254	57	1	to	to	PART
brj-23254	57	2	achieve	achieve	VERB
brj-23254	57	3	this	this	DET
brj-23254	57	4	objective	objective	NOUN
brj-23254	57	5	,	,	PUNCT
brj-23254	57	6	this	this	DET
brj-23254	57	7	study	study	NOUN
brj-23254	57	8	utilized	utilize	VERB
brj-23254	57	9	images	image	NOUN
brj-23254	57	10	with	with	ADP
brj-23254	57	11	various	various	ADJ
brj-23254	57	12	pixel	pixel	PROPN
brj-23254	57	13	sizes	size	NOUN
brj-23254	57	14	,	,	PUNCT
brj-23254	57	15	enabling	enable	VERB
brj-23254	57	16	a	a	DET
brj-23254	57	17	comparison	comparison	NOUN
brj-23254	57	18	of	of	ADP
brj-23254	57	19	model	model	NOUN
brj-23254	57	20	accuracy	accuracy	NOUN
brj-23254	57	21	against	against	ADP
brj-23254	57	22	scenarios	scenario	NOUN
brj-23254	57	23	in	in	ADP
brj-23254	57	24	which	which	PRON
brj-23254	57	25	only	only	ADV
brj-23254	57	26	images	image	NOUN
brj-23254	57	27	of	of	ADP
brj-23254	57	28	identical	identical	ADJ
brj-23254	57	29	pixel	pixel	NOUN
brj-23254	57	30	sizes	size	NOUN
brj-23254	57	31	were	be	AUX
brj-23254	57	32	analyzed	analyze	VERB
brj-23254	57	33	.	.	PUNCT
brj-23254	58	1	in	in	ADP
brj-23254	58	2	addition	addition	NOUN
brj-23254	58	3	,	,	PUNCT
brj-23254	58	4	the	the	DET
brj-23254	58	5	impact	impact	NOUN
brj-23254	58	6	of	of	ADP
brj-23254	58	7	dataset	dataset	NOUN
brj-23254	58	8	partitioning	partitioning	NOUN
brj-23254	58	9	(	(	PUNCT
brj-23254	58	10	i.e.	i.e.	X
brj-23254	58	11	,	,	PUNCT
brj-23254	58	12	training	training	NOUN
brj-23254	58	13	and	and	CCONJ
brj-23254	58	14	test	test	NOUN
brj-23254	58	15	sets	set	NOUN
brj-23254	58	16	)	)	PUNCT
brj-23254	58	17	on	on	ADP
brj-23254	58	18	model	model	NOUN
brj-23254	58	19	accuracy	accuracy	NOUN
brj-23254	58	20	was	be	AUX
brj-23254	58	21	examined	examine	VERB
brj-23254	58	22	.	.	PUNCT
brj-23254	59	1	furthermore	furthermore	ADV
brj-23254	59	2	,	,	PUNCT
brj-23254	59	3	this	this	DET
brj-23254	59	4	study	study	NOUN
brj-23254	59	5	presented	present	VERB
brj-23254	59	6	a	a	DET
brj-23254	59	7	novel	novel	ADJ
brj-23254	59	8	model	model	NOUN
brj-23254	59	9	capable	capable	ADJ
brj-23254	59	10	of	of	ADP
brj-23254	59	11	generating	generate	VERB
brj-23254	59	12	reasonably	reasonably	ADV
brj-23254	59	13	accurate	accurate	ADJ
brj-23254	59	14	estimations	estimation	NOUN
brj-23254	59	15	,	,	PUNCT
brj-23254	59	16	regardless	regardless	ADV
brj-23254	59	17	of	of	ADP
brj-23254	59	18	the	the	DET
brj-23254	59	19	type	type	NOUN
brj-23254	59	20	of	of	ADP
brj-23254	59	21	microscopic	microscopic	ADJ
brj-23254	59	22	photograph	photograph	NOUN
brj-23254	59	23	employed	employ	VERB
brj-23254	59	24	.	.	PUNCT
brj-23254	60	1	to	to	PART
brj-23254	60	2	facilitate	facilitate	VERB
brj-23254	60	3	practical	practical	ADJ
brj-23254	60	4	implementation	implementation	NOUN
brj-23254	60	5	and	and	CCONJ
brj-23254	60	6	promote	promote	VERB
brj-23254	60	7	collaborative	collaborative	ADJ
brj-23254	60	8	efforts	effort	NOUN
brj-23254	60	9	,	,	PUNCT
brj-23254	60	10	the	the	DET
brj-23254	60	11	secondary	secondary	ADJ
brj-23254	60	12	goal	goal	NOUN
brj-23254	60	13	was	be	AUX
brj-23254	60	14	to	to	PART
brj-23254	60	15	establish	establish	VERB
brj-23254	60	16	a	a	DET
brj-23254	60	17	publicly	publicly	ADV
brj-23254	60	18	accessible	accessible	ADJ
brj-23254	60	19	website	website	NOUN
brj-23254	60	20	that	that	PRON
brj-23254	60	21	facilitated	facilitate	VERB
brj-23254	60	22	hardwood	hardwood	NOUN
brj-23254	60	23	identification	identification	NOUN
brj-23254	60	24	using	use	VERB
brj-23254	60	25	customized	customize	VERB
brj-23254	60	26	image	image	NOUN
brj-23254	60	27	data	datum	NOUN
brj-23254	60	28	.	.	PUNCT
brj-23254	61	1	experimental	experimental	ADJ
brj-23254	61	2	image	image	NOUN
brj-23254	61	3	processing	process	VERB
brj-23254	61	4	microscopic	microscopic	ADJ
brj-23254	61	5	cross	cross	ADJ
brj-23254	61	6	-	-	ADJ
brj-23254	61	7	sectional	sectional	ADJ
brj-23254	61	8	images	image	NOUN
brj-23254	61	9	of	of	ADP
brj-23254	61	10	50	50	NUM
brj-23254	61	11	japanese	japanese	ADJ
brj-23254	61	12	hardwood	hardwood	NOUN
brj-23254	61	13	species	specie	NOUN
brj-23254	61	14	(	(	PUNCT
brj-23254	61	15	totaling	total	VERB
brj-23254	61	16	1,000	1,000	NUM
brj-23254	61	17	images	image	NOUN
brj-23254	61	18	,	,	PUNCT
brj-23254	61	19	with	with	ADP
brj-23254	61	20	20	20	NUM
brj-23254	61	21	images	image	NOUN
brj-23254	61	22	per	per	ADP
brj-23254	61	23	species	specie	NOUN
brj-23254	61	24	)	)	PUNCT
brj-23254	61	25	were	be	AUX
brj-23254	61	26	sourced	source	VERB
brj-23254	61	27	from	from	ADP
brj-23254	61	28	the	the	DET
brj-23254	61	29	japanese	japanese	ADJ
brj-23254	61	30	wood	wood	NOUN
brj-23254	61	31	identification	identification	NOUN
brj-23254	61	32	database	database	NOUN
brj-23254	61	33	of	of	ADP
brj-23254	61	34	the	the	DET
brj-23254	61	35	forest	forest	NOUN
brj-23254	61	36	research	research	NOUN
brj-23254	61	37	and	and	CCONJ
brj-23254	61	38	management	management	NOUN
brj-23254	61	39	organization	organization	NOUN
brj-23254	61	40	.	.	PUNCT
brj-23254	62	1	all	all	DET
brj-23254	62	2	images	image	NOUN
brj-23254	62	3	were	be	AUX
brj-23254	62	4	captured	capture	VERB
brj-23254	62	5	using	use	VERB
brj-23254	62	6	a	a	DET
brj-23254	62	7	d100	d100	PROPN
brj-23254	62	8	camera	camera	NOUN
brj-23254	62	9	(	(	PUNCT
brj-23254	62	10	nikon	nikon	PROPN
brj-23254	62	11	,	,	PUNCT
brj-23254	62	12	tokyo	tokyo	PROPN
brj-23254	62	13	,	,	PUNCT
brj-23254	62	14	japan	japan	PROPN
brj-23254	62	15	)	)	PUNCT
brj-23254	62	16	or	or	CCONJ
brj-23254	62	17	a	a	DET
brj-23254	62	18	dp72	dp72	PROPN
brj-23254	62	19	camera	camera	NOUN
brj-23254	62	20	(	(	PUNCT
brj-23254	62	21	olympus	olympus	PROPN
brj-23254	62	22	)	)	PUNCT
brj-23254	62	23	.	.	PUNCT
brj-23254	63	1	the	the	DET
brj-23254	63	2	50	50	NUM
brj-23254	63	3	species	specie	NOUN
brj-23254	63	4	included	include	VERB
brj-23254	63	5	in	in	ADP
brj-23254	63	6	the	the	DET
brj-23254	63	7	dataset	dataset	NOUN
brj-23254	63	8	,	,	PUNCT
brj-23254	63	9	spanning	span	VERB
brj-23254	63	10	39	39	NUM
brj-23254	63	11	genera	genera	NOUN
brj-23254	63	12	and	and	CCONJ
brj-23254	63	13	29	29	NUM
brj-23254	63	14	families	family	NOUN
brj-23254	63	15	,	,	PUNCT
brj-23254	63	16	are	be	AUX
brj-23254	63	17	summarized	summarize	VERB
brj-23254	63	18	in	in	ADP
brj-23254	63	19	table	table	NOUN
brj-23254	63	20	1	1	NUM
brj-23254	63	21	.	.	PUNCT
brj-23254	64	1	this	this	PRON
brj-23254	64	2	means	mean	VERB
brj-23254	64	3	that	that	SCONJ
brj-23254	64	4	the	the	DET
brj-23254	64	5	dispersion	dispersion	NOUN
brj-23254	64	6	of	of	ADP
brj-23254	64	7	anatomical	anatomical	ADJ
brj-23254	64	8	features	feature	NOUN
brj-23254	64	9	was	be	AUX
brj-23254	64	10	quite	quite	ADV
brj-23254	64	11	high	high	ADJ
brj-23254	64	12	.	.	PUNCT
brj-23254	65	1	when	when	SCONJ
brj-23254	65	2	the	the	DET
brj-23254	65	3	database	database	NOUN
brj-23254	65	4	contained	contain	VERB
brj-23254	65	5	more	more	ADJ
brj-23254	65	6	than	than	ADP
brj-23254	65	7	20	20	NUM
brj-23254	65	8	images	image	NOUN
brj-23254	65	9	of	of	ADP
brj-23254	65	10	any	any	DET
brj-23254	65	11	species	specie	NOUN
brj-23254	65	12	,	,	PUNCT
brj-23254	65	13	surplus	surplus	NOUN
brj-23254	65	14	images	image	NOUN
brj-23254	65	15	were	be	AUX
brj-23254	65	16	harnessed	harness	VERB
brj-23254	65	17	to	to	PART
brj-23254	65	18	evaluate	evaluate	VERB
brj-23254	65	19	the	the	DET
brj-23254	65	20	robustness	robustness	NOUN
brj-23254	65	21	of	of	ADP
brj-23254	65	22	the	the	DET
brj-23254	65	23	model	model	NOUN
brj-23254	65	24	.	.	PUNCT
brj-23254	66	1	the	the	DET
brj-23254	66	2	images	image	NOUN
brj-23254	66	3	varied	varied	ADJ
brj-23254	66	4	in	in	ADP
brj-23254	66	5	terms	term	NOUN
brj-23254	66	6	of	of	ADP
brj-23254	66	7	resolution	resolution	NOUN
brj-23254	66	8	(	(	PUNCT
brj-23254	66	9	spanning	span	VERB
brj-23254	66	10	3,840	3,840	NUM
brj-23254	66	11	×	×	NOUN
brj-23254	66	12	3,072	3,072	NUM
brj-23254	66	13	;	;	PUNCT
brj-23254	66	14	3,200	3,200	NUM
brj-23254	66	15	×	×	NOUN
brj-23254	66	16	2,560	2,560	NUM
brj-23254	66	17	;	;	PUNCT
brj-23254	66	18	3,008	3,008	NUM
brj-23254	66	19	×	×	NOUN
brj-23254	66	20	2,000	2,000	NUM
brj-23254	66	21	;	;	PUNCT
brj-23254	66	22	and	and	CCONJ
brj-23254	66	23	1,360	1,360	NUM
brj-23254	66	24	×	×	NOUN
brj-23254	66	25	1,024	1,024	NUM
brj-23254	66	26	)	)	PUNCT
brj-23254	66	27	.	.	PUNCT
brj-23254	67	1	although	although	SCONJ
brj-23254	67	2	certain	certain	ADJ
brj-23254	67	3	properties	property	NOUN
brj-23254	67	4	such	such	ADJ
brj-23254	67	5	as	as	ADP
brj-23254	67	6	resolution	resolution	NOUN
brj-23254	67	7	are	be	AUX
brj-23254	67	8	not	not	PART
brj-23254	67	9	preserved	preserve	VERB
brj-23254	67	10	as	as	ADP
brj-23254	67	11	digital	digital	ADJ
brj-23254	67	12	values	value	NOUN
brj-23254	67	13	,	,	PUNCT
brj-23254	67	14	one	one	NUM
brj-23254	67	15	certainty	certainty	NOUN
brj-23254	67	16	is	be	AUX
brj-23254	67	17	that	that	SCONJ
brj-23254	67	18	if	if	SCONJ
brj-23254	67	19	the	the	DET
brj-23254	67	20	twtw	twtw	ADJ
brj-23254	67	21	no	no	NOUN
brj-23254	67	22	.	.	PUNCT
brj-23254	68	1	differs	differ	NOUN
brj-23254	68	2	,	,	PUNCT
brj-23254	68	3	and	and	CCONJ
brj-23254	68	4	it	it	PRON
brj-23254	68	5	indicates	indicate	VERB
brj-23254	68	6	a	a	DET
brj-23254	68	7	difference	difference	NOUN
brj-23254	68	8	in	in	ADP
brj-23254	68	9	individual	individual	ADJ
brj-23254	68	10	specimens	specimen	NOUN
brj-23254	68	11	.	.	PUNCT
brj-23254	69	1	the	the	DET
brj-23254	69	2	camera	camera	NOUN
brj-23254	69	3	used	use	VERB
brj-23254	69	4	varied	varied	ADJ
brj-23254	69	5	across	across	ADP
brj-23254	69	6	the	the	DET
brj-23254	69	7	images	image	NOUN
brj-23254	69	8	.	.	PUNCT
brj-23254	70	1	this	this	DET
brj-23254	70	2	variation	variation	NOUN
brj-23254	70	3	served	serve	VERB
brj-23254	70	4	as	as	ADP
brj-23254	70	5	an	an	DET
brj-23254	70	6	appropriate	appropriate	ADJ
brj-23254	70	7	test	test	NOUN
brj-23254	70	8	for	for	ADP
brj-23254	70	9	the	the	DET
brj-23254	70	10	adaptability	adaptability	NOUN
brj-23254	70	11	of	of	ADP
brj-23254	70	12	the	the	DET
brj-23254	70	13	model	model	NOUN
brj-23254	70	14	to	to	ADP
brj-23254	70	15	images	image	NOUN
brj-23254	70	16	of	of	ADP
brj-23254	70	17	different	different	ADJ
brj-23254	70	18	sizes	size	NOUN
brj-23254	70	19	.	.	PUNCT
brj-23254	71	1	in	in	ADP
brj-23254	71	2	the	the	DET
brj-23254	71	3	process	process	NOUN
brj-23254	71	4	of	of	ADP
brj-23254	71	5	data	datum	NOUN
brj-23254	71	6	extraction	extraction	NOUN
brj-23254	71	7	from	from	ADP
brj-23254	71	8	the	the	DET
brj-23254	71	9	images	image	NOUN
brj-23254	71	10	,	,	PUNCT
brj-23254	71	11	the	the	DET
brj-23254	71	12	distance	distance	NOUN
brj-23254	71	13	per	per	ADP
brj-23254	71	14	pixel	pixel	NOUN
brj-23254	71	15	and	and	CCONJ
brj-23254	71	16	field	field	NOUN
brj-23254	71	17	of	of	ADP
brj-23254	71	18	view	view	NOUN
brj-23254	71	19	(	(	PUNCT
brj-23254	71	20	fov	fov	NOUN
brj-23254	71	21	)	)	PUNCT
brj-23254	71	22	on	on	ADP
brj-23254	71	23	the	the	DET
brj-23254	71	24	xand	xand	PROPN
brj-23254	71	25	y	y	PROPN
brj-23254	71	26	-	-	PUNCT
brj-23254	71	27	axes	axis	NOUN
brj-23254	71	28	varied	varied	ADJ
brj-23254	71	29	according	accord	VERB
brj-23254	71	30	to	to	ADP
brj-23254	71	31	the	the	DET
brj-23254	71	32	image	image	NOUN
brj-23254	71	33	resolution	resolution	NOUN
brj-23254	71	34	.	.	PUNCT
brj-23254	72	1	the	the	DET
brj-23254	72	2	following	follow	VERB
brj-23254	72	3	parameters	parameter	NOUN
brj-23254	72	4	were	be	AUX
brj-23254	72	5	observed	observe	VERB
brj-23254	72	6	for	for	ADP
brj-23254	72	7	each	each	DET
brj-23254	72	8	resolution	resolution	NOUN
brj-23254	72	9	category	category	NOUN
brj-23254	72	10	:	:	PUNCT
brj-23254	72	11	for	for	ADP
brj-23254	72	12	images	image	NOUN
brj-23254	72	13	with	with	ADP
brj-23254	72	14	a	a	DET
brj-23254	72	15	resolution	resolution	NOUN
brj-23254	72	16	of	of	ADP
brj-23254	72	17	3,840	3,840	NUM
brj-23254	72	18	×	×	NOUN
brj-23254	72	19	3,072	3,072	NUM
brj-23254	72	20	pixels	pixel	NOUN
brj-23254	72	21	,	,	PUNCT
brj-23254	72	22	the	the	DET
brj-23254	72	23	distance	distance	NOUN
brj-23254	72	24	per	per	ADP
brj-23254	72	25	pixel	pixel	NOUN
brj-23254	72	26	was	be	AUX
brj-23254	72	27	0.9	0.9	NUM
brj-23254	72	28	μm	μm	NOUN
brj-23254	72	29	,	,	PUNCT
brj-23254	72	30	and	and	CCONJ
brj-23254	72	31	the	the	DET
brj-23254	72	32	fov	fov	NOUN
brj-23254	72	33	was	be	AUX
brj-23254	72	34	3.5	3.5	NUM
brj-23254	72	35	mm	mm	NOUN
brj-23254	72	36	and	and	CCONJ
brj-23254	72	37	2.8	2.8	NUM
brj-23254	72	38	mm	mm	NOUN
brj-23254	72	39	on	on	ADP
brj-23254	72	40	the	the	DET
brj-23254	72	41	xand	xand	PROPN
brj-23254	72	42	y	y	PROPN
brj-23254	72	43	-	-	PUNCT
brj-23254	72	44	axes	axis	NOUN
brj-23254	72	45	,	,	PUNCT
brj-23254	72	46	respectively	respectively	ADV
brj-23254	72	47	.	.	PUNCT
brj-23254	73	1	for	for	ADP
brj-23254	73	2	images	image	NOUN
brj-23254	73	3	with	with	ADP
brj-23254	73	4	a	a	DET
brj-23254	73	5	resolution	resolution	NOUN
brj-23254	73	6	of	of	ADP
brj-23254	73	7	3,200	3,200	NUM
brj-23254	73	8	×	×	NOUN
brj-23254	73	9	2,560	2,560	NUM
brj-23254	73	10	pixels	pixel	NOUN
brj-23254	73	11	,	,	PUNCT
brj-23254	73	12	the	the	DET
brj-23254	73	13	distance	distance	NOUN
brj-23254	73	14	per	per	ADP
brj-23254	73	15	pixel	pixel	NOUN
brj-23254	73	16	was	be	AUX
brj-23254	73	17	0.9	0.9	NUM
brj-23254	73	18	μm	μm	NOUN
brj-23254	73	19	,	,	PUNCT
brj-23254	73	20	and	and	CCONJ
brj-23254	73	21	the	the	DET
brj-23254	73	22	fov	fov	NOUN
brj-23254	73	23	was	be	AUX
brj-23254	73	24	2.9	2.9	NUM
brj-23254	73	25	mm	mm	NOUN
brj-23254	73	26	and	and	CCONJ
brj-23254	73	27	2.3	2.3	NUM
brj-23254	73	28	mm	mm	NOUN
brj-23254	73	29	on	on	ADP
brj-23254	73	30	the	the	DET
brj-23254	73	31	xand	xand	PROPN
brj-23254	73	32	y	y	PROPN
brj-23254	73	33	-	-	PUNCT
brj-23254	73	34	axes	axis	NOUN
brj-23254	73	35	,	,	PUNCT
brj-23254	73	36	respectively	respectively	ADV
brj-23254	73	37	.	.	PUNCT
brj-23254	74	1	for	for	ADP
brj-23254	74	2	images	image	NOUN
brj-23254	74	3	with	with	ADP
brj-23254	74	4	a	a	DET
brj-23254	74	5	resolution	resolution	NOUN
brj-23254	74	6	of	of	ADP
brj-23254	74	7	3,008	3,008	NUM
brj-23254	74	8	×	×	NOUN
brj-23254	74	9	2,000	2,000	NUM
brj-23254	74	10	pixels	pixel	NOUN
brj-23254	74	11	,	,	PUNCT
brj-23254	74	12	the	the	DET
brj-23254	74	13	distance	distance	NOUN
brj-23254	74	14	per	per	ADP
brj-23254	74	15	pixel	pixel	NOUN
brj-23254	74	16	was	be	AUX
brj-23254	74	17	1.3	1.3	NUM
brj-23254	74	18	μm	μm	NOUN
brj-23254	74	19	,	,	PUNCT
brj-23254	74	20	and	and	CCONJ
brj-23254	74	21	the	the	DET
brj-23254	74	22	fov	fov	NOUN
brj-23254	74	23	was	be	AUX
brj-23254	74	24	3.9	3.9	NUM
brj-23254	74	25	mm	mm	NOUN
brj-23254	74	26	and	and	CCONJ
brj-23254	74	27	2.6	2.6	NUM
brj-23254	74	28	mm	mm	NOUN
brj-23254	74	29	on	on	ADP
brj-23254	74	30	the	the	DET
brj-23254	74	31	xand	xand	PROPN
brj-23254	74	32	y	y	PROPN
brj-23254	74	33	-	-	PUNCT
brj-23254	74	34	axes	axis	NOUN
brj-23254	74	35	,	,	PUNCT
brj-23254	74	36	respectively	respectively	ADV
brj-23254	74	37	.	.	PUNCT
brj-23254	75	1	for	for	ADP
brj-23254	75	2	images	image	NOUN
brj-23254	75	3	with	with	ADP
brj-23254	75	4	a	a	DET
brj-23254	75	5	resolution	resolution	NOUN
brj-23254	75	6	of	of	ADP
brj-23254	75	7	1,360	1,360	NUM
brj-23254	75	8	×	×	NOUN
brj-23254	75	9	1,024	1,024	NUM
brj-23254	75	10	pixels	pixel	NOUN
brj-23254	75	11	,	,	PUNCT
brj-23254	75	12	the	the	DET
brj-23254	75	13	distance	distance	NOUN
brj-23254	75	14	per	per	ADP
brj-23254	75	15	pixel	pixel	NOUN
brj-23254	75	16	was	be	AUX
brj-23254	75	17	3.2	3.2	NUM
brj-23254	75	18	μm	μm	NOUN
brj-23254	75	19	,	,	PUNCT
brj-23254	75	20	and	and	CCONJ
brj-23254	75	21	the	the	DET
brj-23254	75	22	fov	fov	NOUN
brj-23254	75	23	was	be	AUX
brj-23254	75	24	4.4	4.4	NUM
brj-23254	75	25	mm	mm	NOUN
brj-23254	75	26	and	and	CCONJ
brj-23254	75	27	3.3	3.3	NUM
brj-23254	75	28	mm	mm	NOUN
brj-23254	75	29	on	on	ADP
brj-23254	75	30	the	the	DET
brj-23254	75	31	x	x	X
brj-23254	75	32	and	and	CCONJ
brj-23254	75	33	y	y	PROPN
brj-23254	75	34	axes	axis	NOUN
brj-23254	75	35	,	,	PUNCT
brj-23254	75	36	respectively	respectively	ADV
brj-23254	75	37	.	.	PUNCT
brj-23254	76	1	peer	peer	NOUN
brj-23254	76	2	-	-	PUNCT
brj-23254	76	3	reviewed	review	VERB
brj-23254	76	4	article	article	NOUN
brj-23254	76	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	76	6	ma	ma	PROPN
brj-23254	76	7	et	et	PROPN
brj-23254	76	8	al	al	PROPN
brj-23254	76	9	.	.	PROPN
brj-23254	77	1	(	(	PUNCT
brj-23254	77	2	2024	2024	NUM
brj-23254	77	3	)	)	PUNCT
brj-23254	77	4	.	.	PUNCT
brj-23254	78	1	“	"	PUNCT
brj-23254	78	2	wood	wood	NOUN
brj-23254	78	3	i	i	X
brj-23254	78	4	d	d	PROPN
brj-23254	78	5	via	via	ADP
brj-23254	78	6	deep	deep	ADJ
brj-23254	78	7	learning	learning	NOUN
brj-23254	78	8	,	,	PUNCT
brj-23254	78	9	”	"	PUNCT
brj-23254	78	10	bioresources	bioresource	NOUN
brj-23254	78	11	19(3	19(3	NUM
brj-23254	78	12	)	)	PUNCT
brj-23254	78	13	,	,	PUNCT
brj-23254	78	14	4838	4838	NUM
brj-23254	78	15	-	-	SYM
brj-23254	78	16	4851	4851	NUM
brj-23254	78	17	.	.	PUNCT
brj-23254	79	1	4841	4841	NUM
brj-23254	79	2	table	table	NOUN
brj-23254	79	3	1	1	NUM
brj-23254	79	4	.	.	PUNCT
brj-23254	80	1	the	the	DET
brj-23254	80	2	50	50	NUM
brj-23254	80	3	species	specie	NOUN
brj-23254	80	4	included	include	VERB
brj-23254	80	5	in	in	ADP
brj-23254	80	6	the	the	DET
brj-23254	80	7	dataset	dataset	NOUN
brj-23254	80	8	sn*1	sn*1	NOUN
brj-23254	80	9	sorted	sort	VERB
brj-23254	80	10	into	into	ADP
brj-23254	80	11	29	29	NUM
brj-23254	80	12	families	family	NOUN
brj-23254	80	13	scientific	scientific	ADJ
brj-23254	80	14	name	name	NOUN
brj-23254	80	15	of	of	ADP
brj-23254	80	16	wood	wood	NOUN
brj-23254	80	17	species	specie	NOUN
brj-23254	80	18	nsi*2	nsi*2	PROPN
brj-23254	80	19	sorted	sort	VERB
brj-23254	80	20	into	into	ADP
brj-23254	80	21	29	29	NUM
brj-23254	80	22	families	family	NOUN
brj-23254	80	23	sn*1	sn*1	ADV
brj-23254	80	24	scientific	scientific	ADJ
brj-23254	80	25	name	name	NOUN
brj-23254	80	26	of	of	ADP
brj-23254	80	27	wood	wood	NOUN
brj-23254	80	28	species	specie	NOUN
brj-23254	80	29	nsi*2	nsi*2	PROPN
brj-23254	80	30	1	1	NUM
brj-23254	80	31	sapindaceae	sapindaceae	PROPN
brj-23254	80	32	acer	acer	NOUN
brj-23254	80	33	sieboldianum	sieboldianum	ADJ
brj-23254	80	34	2	2	NUM
brj-23254	80	35	fagaceae	fagaceae	PROPN
brj-23254	80	36	26	26	NUM
brj-23254	80	37	quercus	quercus	ADJ
brj-23254	80	38	stenophylla	stenophylla	NOUN
brj-23254	80	39	3	3	NUM
brj-23254	80	40	2	2	NUM
brj-23254	80	41	actinidiaceae	actinidiaceae	ADJ
brj-23254	80	42	actinidia	actinidia	NOUN
brj-23254	80	43	arguta	arguta	PROPN
brj-23254	80	44	5	5	NUM
brj-23254	80	45	27	27	NUM
brj-23254	80	46	quercus	quercus	ADJ
brj-23254	80	47	serrata	serrata	NOUN
brj-23254	80	48	8	8	NUM
brj-23254	80	49	3	3	NUM
brj-23254	80	50	anacardiaceae	anacardiaceae	NOUN
brj-23254	80	51	rhus	rhus	NOUN
brj-23254	80	52	chinensis	chinensis	VERB
brj-23254	80	53	7	7	NUM
brj-23254	80	54	28	28	NUM
brj-23254	80	55	quercus	quercus	ADJ
brj-23254	80	56	crispula	crispula	NOUN
brj-23254	80	57	12	12	NUM
brj-23254	80	58	4	4	NUM
brj-23254	80	59	rhus	rhus	NOUN
brj-23254	80	60	trichocarpa	trichocarpa	NOUN
brj-23254	80	61	3	3	NUM
brj-23254	80	62	salicaceae	salicaceae	ADP
brj-23254	80	63	29	29	NUM
brj-23254	80	64	idesia	idesia	NOUN
brj-23254	80	65	polycarpa	polycarpa	PROPN
brj-23254	80	66	6	6	NUM
brj-23254	80	67	5	5	NUM
brj-23254	80	68	aquifoliaceae	aquifoliaceae	PROPN
brj-23254	80	69	ilex	ilex	PROPN
brj-23254	80	70	macropoda	macropoda	PROPN
brj-23254	80	71	0	0	NUM
brj-23254	81	1	lauraceae	lauraceae	ADP
brj-23254	81	2	30	30	NUM
brj-23254	81	3	cinnamomum	cinnamomum	ADJ
brj-23254	81	4	japonicum	japonicum	NOUN
brj-23254	81	5	8	8	NUM
brj-23254	81	6	6	6	NUM
brj-23254	81	7	araliaceae	araliaceae	NOUN
brj-23254	81	8	aralia	aralia	PROPN
brj-23254	81	9	elata	elata	NOUN
brj-23254	81	10	1	1	NUM
brj-23254	81	11	31	31	NUM
brj-23254	81	12	lindera	lindera	NOUN
brj-23254	81	13	erythrocarpa	erythrocarpa	NOUN
brj-23254	81	14	3	3	NUM
brj-23254	81	15	7	7	NUM
brj-23254	81	16	betulaceae	betulaceae	ADJ
brj-23254	81	17	betula	betula	ADJ
brj-23254	81	18	grossa	grossa	PROPN
brj-23254	81	19	4	4	NUM
brj-23254	81	20	32	32	NUM
brj-23254	81	21	lindera	lindera	NOUN
brj-23254	81	22	umbellata	umbellata	ADJ
brj-23254	81	23	2	2	NUM
brj-23254	81	24	8	8	NUM
brj-23254	81	25	carpinus	carpinus	NOUN
brj-23254	81	26	laxiflora	laxiflora	PROPN
brj-23254	81	27	7	7	NUM
brj-23254	81	28	moraceae	moraceae	PROPN
brj-23254	81	29	33	33	NUM
brj-23254	81	30	ficus	ficus	NOUN
brj-23254	81	31	erecta	erecta	ADJ
brj-23254	81	32	4	4	NUM
brj-23254	81	33	9	9	NUM
brj-23254	81	34	carpinus	carpinu	VERB
brj-23254	81	35	japonica	japonica	NOUN
brj-23254	81	36	4	4	NUM
brj-23254	81	37	34	34	NUM
brj-23254	81	38	morus	morus	NOUN
brj-23254	81	39	australis	australi	VERB
brj-23254	81	40	12	12	NUM
brj-23254	81	41	10	10	NUM
brj-23254	81	42	adoxaceae	adoxaceae	PROPN
brj-23254	81	43	viburnum	viburnum	ADJ
brj-23254	81	44	furcatum	furcatum	NOUN
brj-23254	81	45	0	0	NUM
brj-23254	81	46	oleaceae	oleaceae	ADJ
brj-23254	81	47	35	35	NUM
brj-23254	81	48	ligustrum	ligustrum	ADJ
brj-23254	81	49	japonicum	japonicum	NOUN
brj-23254	81	50	3	3	NUM
brj-23254	81	51	11	11	NUM
brj-23254	81	52	viburnum	viburnum	NOUN
brj-23254	81	53	dilatatum	dilatatum	NOUN
brj-23254	81	54	5	5	NUM
brj-23254	81	55	rosaceae	rosaceae	PROPN
brj-23254	81	56	36	36	NUM
brj-23254	81	57	pourthiaea	pourthiaea	ADJ
brj-23254	81	58	villosa	villosa	NOUN
brj-23254	81	59	3	3	NUM
brj-23254	81	60	12	12	NUM
brj-23254	81	61	celastraceae	celastraceae	ADP
brj-23254	81	62	euonymus	euonymus	PROPN
brj-23254	81	63	oxyphyllus	oxyphyllus	NOUN
brj-23254	81	64	7	7	NUM
brj-23254	81	65	37	37	NUM
brj-23254	81	66	prunus	prunus	NOUN
brj-23254	81	67	grayana	grayana	VERB
brj-23254	81	68	11	11	NUM
brj-23254	81	69	13	13	NUM
brj-23254	81	70	clethraceae	clethraceae	PROPN
brj-23254	81	71	clethra	clethra	NOUN
brj-23254	81	72	barbinervis	barbinervi	VERB
brj-23254	81	73	10	10	NUM
brj-23254	81	74	38	38	NUM
brj-23254	81	75	prunus	prunus	NOUN
brj-23254	81	76	jamasakura	jamasakura	NOUN
brj-23254	81	77	19	19	NUM
brj-23254	81	78	14	14	NUM
brj-23254	81	79	garryaceae	garryaceae	ADJ
brj-23254	81	80	aucuba	aucuba	PROPN
brj-23254	81	81	japonica	japonica	PROPN
brj-23254	81	82	0	0	NUM
brj-23254	82	1	rutaceae	rutaceae	PROPN
brj-23254	82	2	39	39	NUM
brj-23254	82	3	zanthoxylum	zanthoxylum	ADJ
brj-23254	82	4	piperitum	piperitum	NOUN
brj-23254	82	5	0	0	NUM
brj-23254	82	6	15	15	NUM
brj-23254	82	7	cornaceae	cornaceae	PROPN
brj-23254	82	8	cornus	cornus	PROPN
brj-23254	82	9	kousa	kousa	NOUN
brj-23254	83	1	6	6	NUM
brj-23254	83	2	hydrangeaceae	hydrangeaceae	PART
brj-23254	83	3	40	40	NUM
brj-23254	83	4	deutzia	deutzia	NOUN
brj-23254	83	5	crenata	crenata	NOUN
brj-23254	83	6	13	13	NUM
brj-23254	83	7	16	16	NUM
brj-23254	83	8	cornus	cornus	NOUN
brj-23254	83	9	macrophylla	macrophylla	NOUN
brj-23254	83	10	6	6	NUM
brj-23254	83	11	41	41	NUM
brj-23254	83	12	hydrangea	hydrangea	NOUN
brj-23254	83	13	paniculata	paniculata	VERB
brj-23254	83	14	8	8	NUM
brj-23254	83	15	17	17	NUM
brj-23254	83	16	cornus	cornus	PROPN
brj-23254	83	17	controversa	controversa	NOUN
brj-23254	83	18	15	15	NUM
brj-23254	83	19	42	42	NUM
brj-23254	83	20	schizophragma	schizophragma	NOUN
brj-23254	83	21	hydrangeoides	hydrangeoide	NOUN
brj-23254	83	22	4	4	NUM
brj-23254	83	23	18	18	NUM
brj-23254	83	24	daphniphyllaceae	daphniphyllaceae	NOUN
brj-23254	83	25	daphniphyllum	daphniphyllum	NOUN
brj-23254	83	26	teijsmannii	teijsmannii	PROPN
brj-23254	83	27	1	1	NUM
brj-23254	83	28	stachyuraceae	stachyuraceae	PROPN
brj-23254	83	29	43	43	NUM
brj-23254	83	30	stachyurus	stachyurus	NOUN
brj-23254	83	31	praecox	praecox	PROPN
brj-23254	83	32	19	19	NUM
brj-23254	83	33	19	19	NUM
brj-23254	83	34	ericaceae	ericaceae	PROPN
brj-23254	83	35	lyonia	lyonia	NOUN
brj-23254	83	36	ovalifolia	ovalifolia	PROPN
brj-23254	83	37	10	10	NUM
brj-23254	83	38	styracaceae	styracaceae	PROPN
brj-23254	83	39	45	45	NUM
brj-23254	83	40	styrax	styrax	NOUN
brj-23254	83	41	japonicus	japonicus	NOUN
brj-23254	83	42	13	13	NUM
brj-23254	83	43	20	20	NUM
brj-23254	83	44	pieris	pieris	NOUN
brj-23254	83	45	japonica	japonica	NOUN
brj-23254	83	46	7	7	NUM
brj-23254	83	47	staphyleaceae	staphyleaceae	NOUN
brj-23254	83	48	44	44	NUM
brj-23254	83	49	euscaphis	euscaphis	PRON
brj-23254	83	50	japonica	japonica	NOUN
brj-23254	83	51	10	10	NUM
brj-23254	83	52	21	21	NUM
brj-23254	83	53	rhododendron	rhododendron	NOUN
brj-23254	83	54	kaempferi	kaempferi	NOUN
brj-23254	83	55	9	9	NUM
brj-23254	83	56	theaceae	theaceae	NOUN
brj-23254	83	57	46	46	NUM
brj-23254	83	58	camellia	camellia	PROPN
brj-23254	83	59	japonica	japonica	NOUN
brj-23254	83	60	11	11	NUM
brj-23254	83	61	22	22	NUM
brj-23254	83	62	euphorbiaceae	euphorbiaceae	PROPN
brj-23254	83	63	mallotus	mallotus	NOUN
brj-23254	83	64	japonicus	japonicus	NOUN
brj-23254	83	65	10	10	NUM
brj-23254	83	66	pentaphylacaceae	pentaphylacaceae	NOUN
brj-23254	83	67	47	47	NUM
brj-23254	83	68	eurya	eurya	ADJ
brj-23254	83	69	japonica	japonica	NOUN
brj-23254	83	70	17	17	NUM
brj-23254	83	71	23	23	NUM
brj-23254	83	72	eupteleaceae	eupteleaceae	ADJ
brj-23254	83	73	euptelea	euptelea	PROPN
brj-23254	83	74	polyandra	polyandra	PROPN
brj-23254	83	75	5	5	NUM
brj-23254	83	76	lamiaceae	lamiaceae	PROPN
brj-23254	83	77	48	48	NUM
brj-23254	83	78	callicarpa	callicarpa	ADJ
brj-23254	83	79	japonica	japonica	NOUN
brj-23254	83	80	11	11	NUM
brj-23254	83	81	24	24	NUM
brj-23254	83	82	fagaceae	fagaceae	PROPN
brj-23254	83	83	castanea	castanea	PROPN
brj-23254	83	84	crenata	crenata	PROPN
brj-23254	83	85	8	8	NUM
brj-23254	83	86	49	49	NUM
brj-23254	83	87	callicarpa	callicarpa	VERB
brj-23254	83	88	mollis	molli	NOUN
brj-23254	83	89	3	3	NUM
brj-23254	83	90	25	25	NUM
brj-23254	83	91	quercus	quercus	ADJ
brj-23254	83	92	acuta	acuta	NOUN
brj-23254	83	93	4	4	NUM
brj-23254	83	94	50	50	NUM
brj-23254	83	95	clerodendrum	clerodendrum	NOUN
brj-23254	83	96	trichotomum	trichotomum	NOUN
brj-23254	83	97	0	0	NUM
brj-23254	84	1	*	*	SYM
brj-23254	84	2	1	1	NUM
brj-23254	84	3	species	species	NOUN
brj-23254	84	4	number	number	NOUN
brj-23254	84	5	,	,	PUNCT
brj-23254	84	6	*	*	NOUN
brj-23254	84	7	2	2	NUM
brj-23254	84	8	number	number	NOUN
brj-23254	84	9	of	of	ADP
brj-23254	84	10	surplus	surplus	NOUN
brj-23254	84	11	images	image	NOUN
brj-23254	84	12	because	because	SCONJ
brj-23254	84	13	these	these	DET
brj-23254	84	14	images	image	NOUN
brj-23254	84	15	were	be	AUX
brj-23254	84	16	captured	capture	VERB
brj-23254	84	17	under	under	ADP
brj-23254	84	18	a	a	DET
brj-23254	84	19	variety	variety	NOUN
brj-23254	84	20	of	of	ADP
brj-23254	84	21	microscope	microscope	NOUN
brj-23254	84	22	settings	setting	NOUN
brj-23254	84	23	,	,	PUNCT
brj-23254	84	24	they	they	PRON
brj-23254	84	25	presented	present	VERB
brj-23254	84	26	different	different	ADJ
brj-23254	84	27	resolutions	resolution	NOUN
brj-23254	84	28	and	and	CCONJ
brj-23254	84	29	dimensionalities	dimensionality	NOUN
brj-23254	84	30	.	.	PUNCT
brj-23254	85	1	although	although	SCONJ
brj-23254	85	2	challenging	challenge	VERB
brj-23254	85	3	,	,	PUNCT
brj-23254	85	4	these	these	DET
brj-23254	85	5	variable	variable	ADJ
brj-23254	85	6	conditions	condition	NOUN
brj-23254	85	7	helped	help	VERB
brj-23254	85	8	test	test	VERB
brj-23254	85	9	the	the	DET
brj-23254	85	10	robustness	robustness	NOUN
brj-23254	85	11	of	of	ADP
brj-23254	85	12	this	this	DET
brj-23254	85	13	model	model	NOUN
brj-23254	85	14	in	in	ADP
brj-23254	85	15	handling	handle	VERB
brj-23254	85	16	diverse	diverse	ADJ
brj-23254	85	17	and	and	CCONJ
brj-23254	85	18	realistically	realistically	ADV
brj-23254	85	19	inconsistent	inconsistent	ADJ
brj-23254	85	20	data	datum	NOUN
brj-23254	85	21	.	.	PUNCT
brj-23254	86	1	because	because	SCONJ
brj-23254	86	2	each	each	DET
brj-23254	86	3	image	image	NOUN
brj-23254	86	4	featured	feature	VERB
brj-23254	86	5	a	a	DET
brj-23254	86	6	scale	scale	NOUN
brj-23254	86	7	bar	bar	NOUN
brj-23254	86	8	in	in	ADP
brj-23254	86	9	the	the	DET
brj-23254	86	10	bottom	bottom	ADJ
brj-23254	86	11	-	-	PUNCT
brj-23254	86	12	right	right	NOUN
brj-23254	86	13	corner	corner	NOUN
brj-23254	86	14	,	,	PUNCT
brj-23254	86	15	the	the	DET
brj-23254	86	16	corresponding	corresponding	ADJ
brj-23254	86	17	pixels	pixel	NOUN
brj-23254	86	18	were	be	AUX
brj-23254	86	19	cropped	crop	VERB
brj-23254	86	20	out	out	ADP
brj-23254	86	21	.	.	PUNCT
brj-23254	87	1	the	the	DET
brj-23254	87	2	images	image	NOUN
brj-23254	87	3	were	be	AUX
brj-23254	87	4	then	then	ADV
brj-23254	87	5	processed	process	VERB
brj-23254	87	6	,	,	PUNCT
brj-23254	87	7	as	as	SCONJ
brj-23254	87	8	shown	show	VERB
brj-23254	87	9	in	in	ADP
brj-23254	87	10	fig	fig	NOUN
brj-23254	87	11	.	.	PUNCT
brj-23254	88	1	1	1	NUM
brj-23254	88	2	,	,	PUNCT
brj-23254	88	3	and	and	CCONJ
brj-23254	88	4	the	the	DET
brj-23254	88	5	previously	previously	ADV
brj-23254	88	6	mentioned	mention	VERB
brj-23254	88	7	image	image	NOUN
brj-23254	88	8	dimensions	dimension	NOUN
brj-23254	88	9	were	be	AUX
brj-23254	88	10	reduced	reduce	VERB
brj-23254	88	11	to	to	ADP
brj-23254	88	12	3,840	3,840	NUM
brj-23254	88	13	×	×	NOUN
brj-23254	88	14	2,591	2,591	NUM
brj-23254	88	15	,	,	PUNCT
brj-23254	88	16	3,200	3,200	NUM
brj-23254	88	17	×	×	NOUN
brj-23254	88	18	2,153	2,153	NUM
brj-23254	88	19	,	,	PUNCT
brj-23254	88	20	3,008	3,008	NUM
brj-23254	88	21	×	×	NOUN
brj-23254	88	22	2,000	2,000	NUM
brj-23254	88	23	,	,	PUNCT
brj-23254	88	24	and	and	CCONJ
brj-23254	88	25	1,360	1,360	NUM
brj-23254	88	26	×	×	NOUN
brj-23254	88	27	972	972	NUM
brj-23254	88	28	,	,	PUNCT
brj-23254	88	29	respectively	respectively	ADV
brj-23254	88	30	.	.	PUNCT
brj-23254	89	1	subsequently	subsequently	ADV
brj-23254	89	2	,	,	PUNCT
brj-23254	89	3	square	square	ADJ
brj-23254	89	4	areas	area	NOUN
brj-23254	89	5	corresponding	correspond	VERB
brj-23254	89	6	to	to	ADP
brj-23254	89	7	2,501	2,501	NUM
brj-23254	89	8	×	×	NOUN
brj-23254	89	9	2,501	2,501	NUM
brj-23254	89	10	,	,	PUNCT
brj-23254	89	11	2,153	2,153	NUM
brj-23254	89	12	×	×	NOUN
brj-23254	89	13	2,153	2,153	NUM
brj-23254	89	14	,	,	PUNCT
brj-23254	89	15	2,000	2,000	NUM
brj-23254	89	16	×	×	NOUN
brj-23254	89	17	2,000	2,000	NUM
brj-23254	89	18	,	,	PUNCT
brj-23254	89	19	and	and	CCONJ
brj-23254	89	20	972	972	NUM
brj-23254	89	21	×	×	NOUN
brj-23254	89	22	972	972	NUM
brj-23254	89	23	pixels	pixel	NOUN
brj-23254	89	24	were	be	AUX
brj-23254	89	25	randomly	randomly	ADV
brj-23254	89	26	extracted	extract	VERB
brj-23254	89	27	from	from	ADP
brj-23254	89	28	each	each	DET
brj-23254	89	29	image	image	NOUN
brj-23254	89	30	category	category	NOUN
brj-23254	89	31	and	and	CCONJ
brj-23254	89	32	resized	resize	VERB
brj-23254	89	33	to	to	ADP
brj-23254	89	34	640	640	NUM
brj-23254	89	35	×	×	NOUN
brj-23254	89	36	640	640	NUM
brj-23254	89	37	pixels	pixel	NOUN
brj-23254	89	38	.	.	PUNCT
brj-23254	90	1	it	it	PRON
brj-23254	90	2	is	be	AUX
brj-23254	90	3	important	important	ADJ
brj-23254	90	4	to	to	PART
brj-23254	90	5	note	note	VERB
brj-23254	90	6	that	that	SCONJ
brj-23254	90	7	the	the	DET
brj-23254	90	8	exact	exact	ADJ
brj-23254	90	9	scale	scale	NOUN
brj-23254	90	10	lengths	length	NOUN
brj-23254	90	11	between	between	ADP
brj-23254	90	12	pixels	pixel	NOUN
brj-23254	90	13	vary	vary	VERB
brj-23254	90	14	across	across	ADP
brj-23254	90	15	images	image	NOUN
brj-23254	90	16	.	.	PUNCT
brj-23254	91	1	next	next	ADJ
brj-23254	91	2	,	,	PUNCT
brj-23254	91	3	64	64	NUM
brj-23254	91	4	×	×	NOUN
brj-23254	91	5	64	64	NUM
brj-23254	91	6	nonoverlapping	nonoverlapping	ADJ
brj-23254	91	7	grid	grid	NOUN
brj-23254	91	8	patches	patch	NOUN
brj-23254	91	9	were	be	AUX
brj-23254	91	10	extracted	extract	VERB
brj-23254	91	11	from	from	ADP
brj-23254	91	12	these	these	DET
brj-23254	91	13	images	image	NOUN
brj-23254	91	14	,	,	PUNCT
brj-23254	91	15	accumulating	accumulate	VERB
brj-23254	91	16	a	a	DET
brj-23254	91	17	total	total	NOUN
brj-23254	91	18	of	of	ADP
brj-23254	91	19	100	100	NUM
brj-23254	91	20	patches	patch	NOUN
brj-23254	91	21	per	per	ADP
brj-23254	91	22	image	image	NOUN
brj-23254	91	23	.	.	PUNCT
brj-23254	92	1	these	these	DET
brj-23254	92	2	patches	patch	NOUN
brj-23254	92	3	were	be	AUX
brj-23254	92	4	divided	divide	VERB
brj-23254	92	5	into	into	ADP
brj-23254	92	6	training	training	NOUN
brj-23254	92	7	,	,	PUNCT
brj-23254	92	8	validation	validation	NOUN
brj-23254	92	9	,	,	PUNCT
brj-23254	92	10	and	and	CCONJ
brj-23254	92	11	testing	testing	NOUN
brj-23254	92	12	datasets	dataset	NOUN
brj-23254	92	13	.	.	PUNCT
brj-23254	93	1	the	the	DET
brj-23254	93	2	rgb	rgb	PROPN
brj-23254	93	3	color	color	NOUN
brj-23254	93	4	of	of	ADP
brj-23254	93	5	each	each	DET
brj-23254	93	6	patch	patch	NOUN
brj-23254	93	7	was	be	AUX
brj-23254	93	8	converted	convert	VERB
brj-23254	93	9	to	to	ADP
brj-23254	93	10	grayscale	grayscale	NOUN
brj-23254	93	11	to	to	PART
brj-23254	93	12	minimize	minimize	VERB
brj-23254	93	13	the	the	DET
brj-23254	93	14	impact	impact	NOUN
brj-23254	93	15	of	of	ADP
brj-23254	93	16	differences	difference	NOUN
brj-23254	93	17	in	in	ADP
brj-23254	93	18	microscope	microscope	NOUN
brj-23254	93	19	devices	device	NOUN
brj-23254	93	20	.	.	PUNCT
brj-23254	94	1	peer	peer	NOUN
brj-23254	94	2	-	-	PUNCT
brj-23254	94	3	reviewed	review	VERB
brj-23254	94	4	article	article	NOUN
brj-23254	94	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	94	6	ma	ma	PROPN
brj-23254	94	7	et	et	PROPN
brj-23254	94	8	al	al	PROPN
brj-23254	94	9	.	.	PROPN
brj-23254	95	1	(	(	PUNCT
brj-23254	95	2	2024	2024	NUM
brj-23254	95	3	)	)	PUNCT
brj-23254	95	4	.	.	PUNCT
brj-23254	96	1	“	"	PUNCT
brj-23254	96	2	wood	wood	NOUN
brj-23254	96	3	i	i	X
brj-23254	96	4	d	d	PROPN
brj-23254	96	5	via	via	ADP
brj-23254	96	6	deep	deep	ADJ
brj-23254	96	7	learning	learning	NOUN
brj-23254	96	8	,	,	PUNCT
brj-23254	96	9	”	"	PUNCT
brj-23254	96	10	bioresources	bioresource	NOUN
brj-23254	96	11	19(3	19(3	NUM
brj-23254	96	12	)	)	PUNCT
brj-23254	96	13	,	,	PUNCT
brj-23254	96	14	4838	4838	NUM
brj-23254	96	15	-	-	SYM
brj-23254	96	16	4851	4851	NUM
brj-23254	96	17	.	.	PUNCT
brj-23254	97	1	4842	4842	NUM
brj-23254	97	2	fig	fig	NOUN
brj-23254	97	3	.	.	PUNCT
brj-23254	98	1	1	1	X
brj-23254	98	2	.	.	X
brj-23254	98	3	diagram	diagram	NOUN
brj-23254	98	4	of	of	ADP
brj-23254	98	5	the	the	DET
brj-23254	98	6	image	image	NOUN
brj-23254	98	7	preprocessing	preprocesse	VERB
brj-23254	98	8	to	to	PART
brj-23254	98	9	ascertain	ascertain	VERB
brj-23254	98	10	the	the	DET
brj-23254	98	11	effect	effect	NOUN
brj-23254	98	12	of	of	ADP
brj-23254	98	13	image	image	NOUN
brj-23254	98	14	size	size	NOUN
brj-23254	98	15	on	on	ADP
brj-23254	98	16	wood	wood	NOUN
brj-23254	98	17	identification	identification	NOUN
brj-23254	98	18	accuracy	accuracy	NOUN
brj-23254	98	19	,	,	PUNCT
brj-23254	98	20	an	an	DET
brj-23254	98	21	additional	additional	ADJ
brj-23254	98	22	dataset	dataset	NOUN
brj-23254	98	23	was	be	AUX
brj-23254	98	24	composed	compose	VERB
brj-23254	98	25	of	of	ADP
brj-23254	98	26	images	image	NOUN
brj-23254	98	27	from	from	ADP
brj-23254	98	28	10	10	NUM
brj-23254	98	29	species	specie	NOUN
brj-23254	98	30	(	(	PUNCT
brj-23254	98	31	denoted	denote	VERB
brj-23254	98	32	in	in	ADP
brj-23254	98	33	orange	orange	NOUN
brj-23254	98	34	in	in	ADP
brj-23254	98	35	table	table	NOUN
brj-23254	98	36	1	1	NUM
brj-23254	98	37	)	)	PUNCT
brj-23254	98	38	in	in	ADP
brj-23254	98	39	their	their	PRON
brj-23254	98	40	original	original	ADJ
brj-23254	98	41	dimensions	dimension	NOUN
brj-23254	98	42	(	(	PUNCT
brj-23254	98	43	3,840	3,840	NUM
brj-23254	98	44	×	×	NOUN
brj-23254	98	45	3,720	3,720	NUM
brj-23254	98	46	pixels	pixel	NOUN
brj-23254	98	47	)	)	PUNCT
brj-23254	98	48	,	,	PUNCT
brj-23254	98	49	processed	process	VERB
brj-23254	98	50	in	in	ADP
brj-23254	98	51	line	line	NOUN
brj-23254	98	52	with	with	ADP
brj-23254	98	53	the	the	DET
brj-23254	98	54	main	main	ADJ
brj-23254	98	55	dataset	dataset	NOUN
brj-23254	98	56	.	.	PUNCT
brj-23254	99	1	the	the	DET
brj-23254	99	2	present	present	ADJ
brj-23254	99	3	study	study	NOUN
brj-23254	99	4	utilized	utilize	VERB
brj-23254	99	5	this	this	DET
brj-23254	99	6	diverse	diverse	ADJ
brj-23254	99	7	dataset	dataset	NOUN
brj-23254	99	8	to	to	PART
brj-23254	99	9	assess	assess	VERB
brj-23254	99	10	the	the	DET
brj-23254	99	11	practical	practical	ADJ
brj-23254	99	12	identification	identification	NOUN
brj-23254	99	13	performance	performance	NOUN
brj-23254	99	14	of	of	ADP
brj-23254	99	15	various	various	ADJ
brj-23254	99	16	cnn	cnn	PROPN
brj-23254	99	17	models	model	NOUN
brj-23254	99	18	.	.	PUNCT
brj-23254	100	1	a	a	DET
brj-23254	100	2	fundamental	fundamental	ADJ
brj-23254	100	3	principle	principle	NOUN
brj-23254	100	4	of	of	ADP
brj-23254	100	5	machine	machine	NOUN
brj-23254	100	6	learning	learning	NOUN
brj-23254	100	7	is	be	AUX
brj-23254	100	8	the	the	DET
brj-23254	100	9	exclusion	exclusion	NOUN
brj-23254	100	10	of	of	ADP
brj-23254	100	11	identical	identical	ADJ
brj-23254	100	12	images	image	NOUN
brj-23254	100	13	from	from	ADP
brj-23254	100	14	the	the	DET
brj-23254	100	15	training	training	NOUN
brj-23254	100	16	,	,	PUNCT
brj-23254	100	17	validation	validation	NOUN
brj-23254	100	18	,	,	PUNCT
brj-23254	100	19	and	and	CCONJ
brj-23254	100	20	testing	testing	NOUN
brj-23254	100	21	sets	set	NOUN
brj-23254	100	22	.	.	PUNCT
brj-23254	101	1	to	to	PART
brj-23254	101	2	elucidate	elucidate	VERB
brj-23254	101	3	the	the	DET
brj-23254	101	4	impact	impact	NOUN
brj-23254	101	5	of	of	ADP
brj-23254	101	6	the	the	DET
brj-23254	101	7	data	datum	NOUN
brj-23254	101	8	distribution	distribution	NOUN
brj-23254	101	9	,	,	PUNCT
brj-23254	101	10	data	datum	NOUN
brj-23254	101	11	allocation	allocation	NOUN
brj-23254	101	12	was	be	AUX
brj-23254	101	13	evaluated	evaluate	VERB
brj-23254	101	14	using	use	VERB
brj-23254	101	15	two	two	NUM
brj-23254	101	16	prepared	prepared	ADJ
brj-23254	101	17	datasets	dataset	NOUN
brj-23254	101	18	,	,	PUNCT
brj-23254	101	19	as	as	SCONJ
brj-23254	101	20	shown	show	VERB
brj-23254	101	21	in	in	ADP
brj-23254	101	22	fig	fig	NOUN
brj-23254	101	23	.	.	PUNCT
brj-23254	102	1	2	2	NUM
brj-23254	102	2	.	.	X
brj-23254	102	3	two	two	NUM
brj-23254	102	4	datasets	dataset	NOUN
brj-23254	102	5	,	,	PUNCT
brj-23254	102	6	d1	d1	PROPN
brj-23254	102	7	and	and	CCONJ
brj-23254	102	8	d2	d2	PROPN
brj-23254	102	9	—	—	PUNCT
brj-23254	102	10	from	from	ADP
brj-23254	102	11	1,000	1,000	NUM
brj-23254	102	12	images	image	NOUN
brj-23254	102	13	(	(	PUNCT
brj-23254	102	14	20	20	NUM
brj-23254	102	15	images	image	NOUN
brj-23254	102	16	per	per	ADP
brj-23254	102	17	each	each	PRON
brj-23254	102	18	of	of	ADP
brj-23254	102	19	the	the	DET
brj-23254	102	20	50	50	NUM
brj-23254	102	21	species	specie	NOUN
brj-23254	102	22	)	)	PUNCT
brj-23254	102	23	were	be	AUX
brj-23254	102	24	assembled	assemble	VERB
brj-23254	102	25	.	.	PUNCT
brj-23254	103	1	for	for	ADP
brj-23254	103	2	d1	d1	PROPN
brj-23254	103	3	,	,	PUNCT
brj-23254	103	4	entirely	entirely	ADV
brj-23254	103	5	distinct	distinct	ADJ
brj-23254	103	6	images	image	NOUN
brj-23254	103	7	were	be	AUX
brj-23254	103	8	used	use	VERB
brj-23254	103	9	for	for	ADP
brj-23254	103	10	training	training	NOUN
brj-23254	103	11	,	,	PUNCT
brj-23254	103	12	validation	validation	NOUN
brj-23254	103	13	,	,	PUNCT
brj-23254	103	14	and	and	CCONJ
brj-23254	103	15	testing	testing	NOUN
brj-23254	103	16	.	.	PUNCT
brj-23254	104	1	conversely	conversely	ADV
brj-23254	104	2	,	,	PUNCT
brj-23254	104	3	d2	d2	PROPN
brj-23254	104	4	used	use	VERB
brj-23254	104	5	the	the	DET
brj-23254	104	6	same	same	ADJ
brj-23254	104	7	images	image	NOUN
brj-23254	104	8	for	for	ADP
brj-23254	104	9	both	both	DET
brj-23254	104	10	training	training	NOUN
brj-23254	104	11	and	and	CCONJ
brj-23254	104	12	testing	testing	NOUN
brj-23254	104	13	.	.	PUNCT
brj-23254	105	1	in	in	ADP
brj-23254	105	2	addition	addition	NOUN
brj-23254	105	3	,	,	PUNCT
brj-23254	105	4	two	two	NUM
brj-23254	105	5	evaluation	evaluation	NOUN
brj-23254	105	6	methodologies	methodology	NOUN
brj-23254	105	7	were	be	AUX
brj-23254	105	8	compared	compare	VERB
brj-23254	105	9	:	:	PUNCT
brj-23254	105	10	patch	patch	ADJ
brj-23254	105	11	evaluation	evaluation	NOUN
brj-23254	105	12	(	(	PUNCT
brj-23254	105	13	e1	e1	NOUN
brj-23254	105	14	)	)	PUNCT
brj-23254	105	15	and	and	CCONJ
brj-23254	105	16	image	image	NOUN
brj-23254	105	17	evaluation	evaluation	NOUN
brj-23254	105	18	(	(	PUNCT
brj-23254	105	19	e2	e2	PROPN
brj-23254	105	20	)	)	PUNCT
brj-23254	105	21	.	.	PUNCT
brj-23254	106	1	for	for	ADP
brj-23254	106	2	the	the	DET
brj-23254	106	3	former	former	ADJ
brj-23254	106	4	,	,	PUNCT
brj-23254	106	5	species	specie	NOUN
brj-23254	106	6	predictions	prediction	NOUN
brj-23254	106	7	were	be	AUX
brj-23254	106	8	made	make	VERB
brj-23254	106	9	for	for	ADP
brj-23254	106	10	each	each	DET
brj-23254	106	11	patch	patch	NOUN
brj-23254	106	12	,	,	PUNCT
brj-23254	106	13	and	and	CCONJ
brj-23254	106	14	accuracy	accuracy	NOUN
brj-23254	106	15	was	be	AUX
brj-23254	106	16	calculated	calculate	VERB
brj-23254	106	17	accordingly	accordingly	ADV
brj-23254	106	18	.	.	PUNCT
brj-23254	107	1	in	in	ADP
brj-23254	107	2	the	the	DET
brj-23254	107	3	latter	latter	ADJ
brj-23254	107	4	scenario	scenario	NOUN
brj-23254	107	5	,	,	PUNCT
brj-23254	107	6	following	follow	VERB
brj-23254	107	7	the	the	DET
brj-23254	107	8	species	species	NOUN
brj-23254	107	9	prediction	prediction	NOUN
brj-23254	107	10	for	for	ADP
brj-23254	107	11	each	each	DET
brj-23254	107	12	patch	patch	NOUN
brj-23254	107	13	,	,	PUNCT
brj-23254	107	14	the	the	DET
brj-23254	107	15	cumulative	cumulative	ADJ
brj-23254	107	16	accuracy	accuracy	NOUN
brj-23254	107	17	was	be	AUX
brj-23254	107	18	computed	compute	VERB
brj-23254	107	19	by	by	ADP
brj-23254	107	20	considering	consider	VERB
brj-23254	107	21	the	the	DET
brj-23254	107	22	summation	summation	NOUN
brj-23254	107	23	of	of	ADP
brj-23254	107	24	all	all	DET
brj-23254	107	25	patches	patch	NOUN
brj-23254	107	26	within	within	ADP
brj-23254	107	27	the	the	DET
brj-23254	107	28	image	image	NOUN
brj-23254	107	29	.	.	PUNCT
brj-23254	108	1	peer	peer	NOUN
brj-23254	108	2	-	-	PUNCT
brj-23254	108	3	reviewed	review	VERB
brj-23254	108	4	article	article	NOUN
brj-23254	108	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	108	6	ma	ma	PROPN
brj-23254	108	7	et	et	PROPN
brj-23254	108	8	al	al	PROPN
brj-23254	108	9	.	.	PROPN
brj-23254	109	1	(	(	PUNCT
brj-23254	109	2	2024	2024	NUM
brj-23254	109	3	)	)	PUNCT
brj-23254	109	4	.	.	PUNCT
brj-23254	110	1	“	"	PUNCT
brj-23254	110	2	wood	wood	NOUN
brj-23254	110	3	i	i	X
brj-23254	110	4	d	d	PROPN
brj-23254	110	5	via	via	ADP
brj-23254	110	6	deep	deep	ADJ
brj-23254	110	7	learning	learning	NOUN
brj-23254	110	8	,	,	PUNCT
brj-23254	110	9	”	"	PUNCT
brj-23254	110	10	bioresources	bioresource	NOUN
brj-23254	110	11	19(3	19(3	NUM
brj-23254	110	12	)	)	PUNCT
brj-23254	110	13	,	,	PUNCT
brj-23254	110	14	4838	4838	NUM
brj-23254	110	15	-	-	SYM
brj-23254	110	16	4851	4851	NUM
brj-23254	110	17	.	.	PUNCT
brj-23254	111	1	4843	4843	NUM
brj-23254	111	2	fig	fig	NOUN
brj-23254	111	3	.	.	PUNCT
brj-23254	112	1	2	2	X
brj-23254	112	2	.	.	X
brj-23254	112	3	data	datum	NOUN
brj-23254	112	4	allocation	allocation	NOUN
brj-23254	112	5	of	of	ADP
brj-23254	112	6	d1	d1	PROPN
brj-23254	112	7	and	and	CCONJ
brj-23254	112	8	d2	d2	PROPN
brj-23254	112	9	peer	peer	NOUN
brj-23254	112	10	-	-	PUNCT
brj-23254	112	11	reviewed	review	VERB
brj-23254	112	12	article	article	NOUN
brj-23254	112	13	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	112	14	ma	ma	PROPN
brj-23254	112	15	et	et	PROPN
brj-23254	112	16	al	al	PROPN
brj-23254	112	17	.	.	PROPN
brj-23254	113	1	(	(	PUNCT
brj-23254	113	2	2024	2024	NUM
brj-23254	113	3	)	)	PUNCT
brj-23254	113	4	.	.	PUNCT
brj-23254	114	1	“	"	PUNCT
brj-23254	114	2	wood	wood	NOUN
brj-23254	114	3	i	i	X
brj-23254	114	4	d	d	PROPN
brj-23254	114	5	via	via	ADP
brj-23254	114	6	deep	deep	ADJ
brj-23254	114	7	learning	learning	NOUN
brj-23254	114	8	,	,	PUNCT
brj-23254	114	9	”	"	PUNCT
brj-23254	114	10	bioresources	bioresource	NOUN
brj-23254	114	11	19(3	19(3	NUM
brj-23254	114	12	)	)	PUNCT
brj-23254	114	13	,	,	PUNCT
brj-23254	114	14	4838	4838	NUM
brj-23254	114	15	-	-	SYM
brj-23254	114	16	4851	4851	NUM
brj-23254	114	17	.	.	PUNCT
brj-23254	115	1	4844	4844	NUM
brj-23254	115	2	the	the	DET
brj-23254	115	3	potential	potential	NOUN
brj-23254	115	4	for	for	ADP
brj-23254	115	5	fine	fine	ADV
brj-23254	115	6	-	-	PUNCT
brj-23254	115	7	tuning	tuning	NOUN
brj-23254	115	8	was	be	AUX
brj-23254	115	9	also	also	ADV
brj-23254	115	10	considered	consider	VERB
brj-23254	115	11	in	in	ADP
brj-23254	115	12	the	the	DET
brj-23254	115	13	exploration	exploration	NOUN
brj-23254	115	14	of	of	ADP
brj-23254	115	15	accuracy	accuracy	NOUN
brj-23254	115	16	enhancement	enhancement	NOUN
brj-23254	115	17	.	.	PUNCT
brj-23254	116	1	for	for	ADP
brj-23254	116	2	d1	d1	NOUN
brj-23254	116	3	,	,	PUNCT
brj-23254	116	4	20	20	NUM
brj-23254	116	5	images	image	NOUN
brj-23254	116	6	from	from	ADP
brj-23254	116	7	each	each	DET
brj-23254	116	8	species	specie	NOUN
brj-23254	116	9	were	be	AUX
brj-23254	116	10	apportioned	apportion	VERB
brj-23254	116	11	from	from	ADP
brj-23254	116	12	the	the	DET
brj-23254	116	13	training	training	NOUN
brj-23254	116	14	(	(	PUNCT
brj-23254	116	15	12	12	NUM
brj-23254	116	16	images	image	NOUN
brj-23254	116	17	=	=	SYM
brj-23254	116	18	1,200	1,200	NUM
brj-23254	116	19	patches	patch	NOUN
brj-23254	116	20	)	)	PUNCT
brj-23254	116	21	,	,	PUNCT
brj-23254	116	22	validation	validation	NOUN
brj-23254	116	23	(	(	PUNCT
brj-23254	116	24	three	three	NUM
brj-23254	116	25	images	image	NOUN
brj-23254	116	26	=	=	SYM
brj-23254	116	27	300	300	NUM
brj-23254	116	28	patches	patch	NOUN
brj-23254	116	29	)	)	PUNCT
brj-23254	116	30	,	,	PUNCT
brj-23254	116	31	and	and	CCONJ
brj-23254	116	32	testing	testing	NOUN
brj-23254	116	33	(	(	PUNCT
brj-23254	116	34	five	five	NUM
brj-23254	116	35	images	image	NOUN
brj-23254	116	36	=	=	SYM
brj-23254	116	37	500	500	NUM
brj-23254	116	38	patches	patch	NOUN
brj-23254	116	39	)	)	PUNCT
brj-23254	116	40	datasets	dataset	NOUN
brj-23254	116	41	without	without	ADP
brj-23254	116	42	overlap	overlap	NOUN
brj-23254	116	43	.	.	PUNCT
brj-23254	117	1	the	the	DET
brj-23254	117	2	impact	impact	NOUN
brj-23254	117	3	of	of	ADP
brj-23254	117	4	variations	variation	NOUN
brj-23254	117	5	in	in	ADP
brj-23254	117	6	location	location	NOUN
brj-23254	117	7	and	and	CCONJ
brj-23254	117	8	camera	camera	NOUN
brj-23254	117	9	settings	setting	NOUN
brj-23254	117	10	across	across	ADP
brj-23254	117	11	images	image	NOUN
brj-23254	117	12	on	on	ADP
brj-23254	117	13	identification	identification	NOUN
brj-23254	117	14	accuracy	accuracy	NOUN
brj-23254	117	15	was	be	AUX
brj-23254	117	16	assessed	assess	VERB
brj-23254	117	17	.	.	PUNCT
brj-23254	118	1	for	for	ADP
brj-23254	118	2	d2	d2	PROPN
brj-23254	118	3	,	,	PUNCT
brj-23254	118	4	20	20	NUM
brj-23254	118	5	images	image	NOUN
brj-23254	118	6	from	from	ADP
brj-23254	118	7	each	each	DET
brj-23254	118	8	species	specie	NOUN
brj-23254	118	9	were	be	AUX
brj-23254	118	10	allocated	allocate	VERB
brj-23254	118	11	to	to	ADP
brj-23254	118	12	the	the	DET
brj-23254	118	13	training	training	NOUN
brj-23254	118	14	(	(	PUNCT
brj-23254	118	15	16	16	NUM
brj-23254	118	16	images	image	NOUN
brj-23254	118	17	=	=	SYM
brj-23254	118	18	1,600	1,600	NUM
brj-23254	118	19	patches	patch	NOUN
brj-23254	118	20	)	)	PUNCT
brj-23254	118	21	and	and	CCONJ
brj-23254	118	22	validation	validation	NOUN
brj-23254	118	23	(	(	PUNCT
brj-23254	118	24	four	four	NUM
brj-23254	118	25	images	image	NOUN
brj-23254	118	26	=	=	SYM
brj-23254	118	27	400	400	NUM
brj-23254	118	28	patches	patch	NOUN
brj-23254	118	29	)	)	PUNCT
brj-23254	118	30	datasets	dataset	NOUN
brj-23254	118	31	.	.	PUNCT
brj-23254	119	1	after	after	ADP
brj-23254	119	2	the	the	DET
brj-23254	119	3	development	development	NOUN
brj-23254	119	4	of	of	ADP
brj-23254	119	5	the	the	DET
brj-23254	119	6	cnn	cnn	PROPN
brj-23254	119	7	models	model	NOUN
brj-23254	119	8	,	,	PUNCT
brj-23254	119	9	these	these	DET
brj-23254	119	10	20	20	NUM
brj-23254	119	11	images	image	NOUN
brj-23254	119	12	were	be	AUX
brj-23254	119	13	reused	reuse	VERB
brj-23254	119	14	for	for	ADP
brj-23254	119	15	testing	testing	NOUN
brj-23254	119	16	.	.	PUNCT
brj-23254	120	1	the	the	DET
brj-23254	120	2	findings	finding	NOUN
brj-23254	120	3	from	from	ADP
brj-23254	120	4	this	this	DET
brj-23254	120	5	study	study	NOUN
brj-23254	120	6	suggest	suggest	VERB
brj-23254	120	7	superior	superior	ADJ
brj-23254	120	8	accuracy	accuracy	NOUN
brj-23254	120	9	in	in	ADP
brj-23254	120	10	wood	wood	NOUN
brj-23254	120	11	identification	identification	NOUN
brj-23254	120	12	from	from	ADP
brj-23254	120	13	d2	d2	PROPN
brj-23254	120	14	compared	compare	VERB
brj-23254	120	15	to	to	ADP
brj-23254	120	16	d1	d1	PROPN
brj-23254	120	17	.	.	PUNCT
brj-23254	121	1	however	however	ADV
brj-23254	121	2	,	,	PUNCT
brj-23254	121	3	model	model	NOUN
brj-23254	121	4	robustness	robustness	NOUN
brj-23254	121	5	should	should	AUX
brj-23254	121	6	be	be	AUX
brj-23254	121	7	higher	high	ADJ
brj-23254	121	8	in	in	ADP
brj-23254	121	9	d1	d1	PROPN
brj-23254	121	10	than	than	ADP
brj-23254	121	11	in	in	ADP
brj-23254	121	12	d2	d2	PROPN
brj-23254	121	13	.	.	PUNCT
brj-23254	122	1	to	to	PART
brj-23254	122	2	evaluate	evaluate	VERB
brj-23254	122	3	model	model	NOUN
brj-23254	122	4	robustness	robustness	NOUN
brj-23254	122	5	,	,	PUNCT
brj-23254	122	6	surplus	surplus	ADJ
brj-23254	122	7	data	datum	NOUN
brj-23254	122	8	corresponding	correspond	VERB
brj-23254	122	9	to	to	ADP
brj-23254	122	10	species	specie	NOUN
brj-23254	122	11	with	with	ADP
brj-23254	122	12	more	more	ADJ
brj-23254	122	13	than	than	ADP
brj-23254	122	14	20	20	NUM
brj-23254	122	15	images	image	NOUN
brj-23254	122	16	in	in	ADP
brj-23254	122	17	the	the	DET
brj-23254	122	18	original	original	ADJ
brj-23254	122	19	database	database	NOUN
brj-23254	122	20	were	be	AUX
brj-23254	122	21	prepared	prepare	VERB
brj-23254	122	22	.	.	PUNCT
brj-23254	123	1	the	the	DET
brj-23254	123	2	quantity	quantity	NOUN
brj-23254	123	3	of	of	ADP
brj-23254	123	4	surplus	surplus	ADJ
brj-23254	123	5	data	datum	NOUN
brj-23254	123	6	for	for	ADP
brj-23254	123	7	each	each	DET
brj-23254	123	8	species	specie	NOUN
brj-23254	123	9	is	be	AUX
brj-23254	123	10	shown	show	VERB
brj-23254	123	11	in	in	ADP
brj-23254	123	12	table	table	NOUN
brj-23254	123	13	1	1	NUM
brj-23254	123	14	.	.	PUNCT
brj-23254	123	15	to	to	PART
brj-23254	123	16	evaluate	evaluate	VERB
brj-23254	123	17	the	the	DET
brj-23254	123	18	accuracy	accuracy	NOUN
brj-23254	123	19	of	of	ADP
brj-23254	123	20	the	the	DET
brj-23254	123	21	model	model	NOUN
brj-23254	123	22	,	,	PUNCT
brj-23254	123	23	it	it	PRON
brj-23254	123	24	is	be	AUX
brj-23254	123	25	crucial	crucial	ADJ
brj-23254	123	26	to	to	PART
brj-23254	123	27	use	use	VERB
brj-23254	123	28	a	a	DET
brj-23254	123	29	test	test	NOUN
brj-23254	123	30	set	set	VERB
brj-23254	123	31	in	in	ADP
brj-23254	123	32	which	which	PRON
brj-23254	123	33	the	the	DET
brj-23254	123	34	number	number	NOUN
brj-23254	123	35	of	of	ADP
brj-23254	123	36	samples	sample	NOUN
brj-23254	123	37	across	across	ADP
brj-23254	123	38	each	each	DET
brj-23254	123	39	category	category	NOUN
brj-23254	123	40	is	be	AUX
brj-23254	123	41	equal	equal	ADJ
brj-23254	123	42	.	.	PUNCT
brj-23254	124	1	however	however	ADV
brj-23254	124	2	,	,	PUNCT
brj-23254	124	3	achieving	achieve	VERB
brj-23254	124	4	such	such	DET
brj-23254	124	5	a	a	DET
brj-23254	124	6	balanced	balanced	ADJ
brj-23254	124	7	representation	representation	NOUN
brj-23254	124	8	is	be	AUX
brj-23254	124	9	challenging	challenge	VERB
brj-23254	124	10	in	in	ADP
brj-23254	124	11	the	the	DET
brj-23254	124	12	context	context	NOUN
brj-23254	124	13	of	of	ADP
brj-23254	124	14	real	real	ADJ
brj-23254	124	15	-	-	PUNCT
brj-23254	124	16	world	world	NOUN
brj-23254	124	17	scientific	scientific	ADJ
brj-23254	124	18	data	datum	NOUN
brj-23254	124	19	.	.	PUNCT
brj-23254	125	1	considering	consider	VERB
brj-23254	125	2	these	these	DET
brj-23254	125	3	practical	practical	ADJ
brj-23254	125	4	limitations	limitation	NOUN
brj-23254	125	5	,	,	PUNCT
brj-23254	125	6	this	this	DET
brj-23254	125	7	study	study	NOUN
brj-23254	125	8	was	be	AUX
brj-23254	125	9	not	not	PART
brj-23254	125	10	restricted	restrict	VERB
brj-23254	125	11	to	to	ADP
brj-23254	125	12	a	a	DET
brj-23254	125	13	perfectly	perfectly	ADV
brj-23254	125	14	balanced	balanced	ADJ
brj-23254	125	15	test	test	NOUN
brj-23254	125	16	set	set	NOUN
brj-23254	125	17	.	.	PUNCT
brj-23254	126	1	instead	instead	ADV
brj-23254	126	2	,	,	PUNCT
brj-23254	126	3	all	all	DET
brj-23254	126	4	remaining	remain	VERB
brj-23254	126	5	samples	sample	NOUN
brj-23254	126	6	were	be	AUX
brj-23254	126	7	used	use	VERB
brj-23254	126	8	as	as	ADP
brj-23254	126	9	surplus	surplus	ADJ
brj-23254	126	10	data	datum	NOUN
brj-23254	126	11	to	to	PART
brj-23254	126	12	evaluate	evaluate	VERB
brj-23254	126	13	the	the	DET
brj-23254	126	14	robustness	robustness	NOUN
brj-23254	126	15	of	of	ADP
brj-23254	126	16	the	the	DET
brj-23254	126	17	model	model	NOUN
brj-23254	126	18	.	.	PUNCT
brj-23254	127	1	this	this	DET
brj-23254	127	2	approach	approach	NOUN
brj-23254	127	3	enabled	enable	VERB
brj-23254	127	4	assessment	assessment	NOUN
brj-23254	127	5	of	of	ADP
brj-23254	127	6	how	how	SCONJ
brj-23254	127	7	well	well	ADV
brj-23254	127	8	the	the	DET
brj-23254	127	9	model	model	NOUN
brj-23254	127	10	performed	perform	VERB
brj-23254	127	11	on	on	ADP
brj-23254	127	12	a	a	DET
brj-23254	127	13	broader	broad	ADJ
brj-23254	127	14	scale	scale	NOUN
brj-23254	127	15	and	and	CCONJ
brj-23254	127	16	reflected	reflect	VERB
brj-23254	127	17	its	its	PRON
brj-23254	127	18	true	true	ADJ
brj-23254	127	19	capacity	capacity	NOUN
brj-23254	127	20	for	for	ADP
brj-23254	127	21	generalization	generalization	NOUN
brj-23254	127	22	and	and	CCONJ
brj-23254	127	23	adaptability	adaptability	NOUN
brj-23254	127	24	.	.	PUNCT
brj-23254	128	1	it	it	PRON
brj-23254	128	2	is	be	AUX
brj-23254	128	3	crucial	crucial	ADJ
brj-23254	128	4	to	to	PART
brj-23254	128	5	emphasize	emphasize	VERB
brj-23254	128	6	that	that	SCONJ
brj-23254	128	7	different	different	ADJ
brj-23254	128	8	twtw	twtw	ADJ
brj-23254	128	9	no	no	NOUN
brj-23254	128	10	.	.	PUNCT
brj-23254	129	1	signifies	signify	VERB
brj-23254	129	2	distinct	distinct	ADJ
brj-23254	129	3	individuals	individual	NOUN
brj-23254	129	4	from	from	ADP
brj-23254	129	5	which	which	PRON
brj-23254	129	6	samples	sample	NOUN
brj-23254	129	7	were	be	AUX
brj-23254	129	8	extracted	extract	VERB
brj-23254	129	9	.	.	PUNCT
brj-23254	130	1	a	a	DET
brj-23254	130	2	comprehensive	comprehensive	ADJ
brj-23254	130	3	summary	summary	NOUN
brj-23254	130	4	of	of	ADP
brj-23254	130	5	twtw	twtw	ADJ
brj-23254	130	6	no	no	NOUN
brj-23254	130	7	.	.	PUNCT
brj-23254	131	1	for	for	ADP
brj-23254	131	2	the	the	DET
brj-23254	131	3	database	database	NOUN
brj-23254	131	4	used	use	VERB
brj-23254	131	5	in	in	ADP
brj-23254	131	6	this	this	DET
brj-23254	131	7	study	study	NOUN
brj-23254	131	8	is	be	AUX
brj-23254	131	9	available	available	ADJ
brj-23254	131	10	at	at	ADP
brj-23254	131	11	https://inatetsu2nd-woodspecrecog-01home-f1zh5g.streamlit.app/.	https://inatetsu2nd-woodspecrecog-01home-f1zh5g.streamlit.app/.	PROPN
brj-23254	131	12	network	network	NOUN
brj-23254	131	13	architecture	architecture	NOUN
brj-23254	131	14	in	in	ADP
brj-23254	131	15	this	this	DET
brj-23254	131	16	study	study	NOUN
brj-23254	131	17	,	,	PUNCT
brj-23254	131	18	a	a	DET
brj-23254	131	19	cnn	cnn	PROPN
brj-23254	131	20	structure	structure	NOUN
brj-23254	131	21	was	be	AUX
brj-23254	131	22	employed	employ	VERB
brj-23254	131	23	(	(	PUNCT
brj-23254	131	24	hafemann	hafemann	NOUN
brj-23254	131	25	et	et	PROPN
brj-23254	131	26	al	al	PROPN
brj-23254	131	27	.	.	PROPN
brj-23254	131	28	2014	2014	NUM
brj-23254	131	29	)	)	PUNCT
brj-23254	131	30	.	.	PUNCT
brj-23254	132	1	the	the	DET
brj-23254	132	2	rationale	rationale	NOUN
brj-23254	132	3	for	for	ADP
brj-23254	132	4	this	this	DET
brj-23254	132	5	choice	choice	NOUN
brj-23254	132	6	stems	stem	VERB
brj-23254	132	7	from	from	ADP
brj-23254	132	8	its	its	PRON
brj-23254	132	9	remarkable	remarkable	ADJ
brj-23254	132	10	accuracy	accuracy	NOUN
brj-23254	132	11	in	in	ADP
brj-23254	132	12	the	the	DET
brj-23254	132	13	specific	specific	ADJ
brj-23254	132	14	task	task	NOUN
brj-23254	132	15	of	of	ADP
brj-23254	132	16	wood	wood	NOUN
brj-23254	132	17	species	specie	NOUN
brj-23254	132	18	identification	identification	NOUN
brj-23254	132	19	.	.	PUNCT
brj-23254	133	1	such	such	DET
brj-23254	133	2	a	a	DET
brj-23254	133	3	high	high	ADJ
brj-23254	133	4	level	level	NOUN
brj-23254	133	5	of	of	ADP
brj-23254	133	6	precision	precision	NOUN
brj-23254	133	7	in	in	ADP
brj-23254	133	8	this	this	DET
brj-23254	133	9	context	context	NOUN
brj-23254	133	10	is	be	AUX
brj-23254	133	11	astonishing	astonishing	ADJ
brj-23254	133	12	,	,	PUNCT
brj-23254	133	13	making	make	VERB
brj-23254	133	14	their	their	PRON
brj-23254	133	15	approach	approach	NOUN
brj-23254	133	16	particularly	particularly	ADV
brj-23254	133	17	compelling	compelling	ADJ
brj-23254	133	18	.	.	PUNCT
brj-23254	134	1	this	this	DET
brj-23254	134	2	structure	structure	NOUN
brj-23254	134	3	incorporates	incorporate	VERB
brj-23254	134	4	a	a	DET
brj-23254	134	5	64	64	NUM
brj-23254	134	6	×	×	NOUN
brj-23254	134	7	64	64	NUM
brj-23254	134	8	input	input	NOUN
brj-23254	134	9	layer	layer	NOUN
brj-23254	134	10	,	,	PUNCT
brj-23254	134	11	two	two	NUM
brj-23254	134	12	convolutional	convolutional	ADJ
brj-23254	134	13	layer	layer	NOUN
brj-23254	134	14	sets	set	NOUN
brj-23254	134	15	with	with	ADP
brj-23254	134	16	5	5	NUM
brj-23254	134	17	×	×	NOUN
brj-23254	134	18	5	5	NUM
brj-23254	134	19	sliding	slide	VERB
brj-23254	134	20	kernels	kernel	NOUN
brj-23254	134	21	and	and	CCONJ
brj-23254	134	22	a	a	DET
brj-23254	134	23	stride	stride	NOUN
brj-23254	134	24	of	of	ADP
brj-23254	134	25	one	one	NUM
brj-23254	134	26	pixel	pixel	NOUN
brj-23254	134	27	,	,	PUNCT
brj-23254	134	28	a	a	DET
brj-23254	134	29	pooling	pooling	NOUN
brj-23254	134	30	layer	layer	NOUN
brj-23254	134	31	with	with	ADP
brj-23254	134	32	3	3	NUM
brj-23254	134	33	×	×	NOUN
brj-23254	134	34	3	3	NUM
brj-23254	134	35	kernels	kernel	NOUN
brj-23254	134	36	and	and	CCONJ
brj-23254	134	37	a	a	DET
brj-23254	134	38	stride	stride	NOUN
brj-23254	134	39	of	of	ADP
brj-23254	134	40	two	two	NUM
brj-23254	134	41	pixels	pixel	NOUN
brj-23254	134	42	,	,	PUNCT
brj-23254	134	43	two	two	NUM
brj-23254	134	44	locally	locally	ADV
brj-23254	134	45	connected	connected	ADJ
brj-23254	134	46	layers	layer	NOUN
brj-23254	134	47	featuring	feature	VERB
brj-23254	134	48	3	3	NUM
brj-23254	134	49	×	×	NOUN
brj-23254	134	50	3	3	NUM
brj-23254	134	51	sliding	slide	VERB
brj-23254	134	52	kernels	kernel	NOUN
brj-23254	134	53	and	and	CCONJ
brj-23254	134	54	a	a	DET
brj-23254	134	55	stride	stride	NOUN
brj-23254	134	56	of	of	ADP
brj-23254	134	57	one	one	NUM
brj-23254	134	58	pixel	pixel	NOUN
brj-23254	134	59	,	,	PUNCT
brj-23254	134	60	and	and	CCONJ
brj-23254	134	61	a	a	DET
brj-23254	134	62	flattened	flatten	VERB
brj-23254	134	63	layer	layer	NOUN
brj-23254	134	64	that	that	PRON
brj-23254	134	65	shares	share	VERB
brj-23254	134	66	weights	weight	NOUN
brj-23254	134	67	across	across	ADP
brj-23254	134	68	all	all	DET
brj-23254	134	69	the	the	DET
brj-23254	134	70	nodes	node	NOUN
brj-23254	134	71	.	.	PUNCT
brj-23254	135	1	the	the	DET
brj-23254	135	2	output	output	NOUN
brj-23254	135	3	layer	layer	NOUN
brj-23254	135	4	encompasses	encompass	VERB
brj-23254	135	5	50	50	NUM
brj-23254	135	6	classes	class	NOUN
brj-23254	135	7	,	,	PUNCT
brj-23254	135	8	each	each	PRON
brj-23254	135	9	representing	represent	VERB
brj-23254	135	10	a	a	DET
brj-23254	135	11	different	different	ADJ
brj-23254	135	12	wood	wood	NOUN
brj-23254	135	13	species	specie	NOUN
brj-23254	135	14	.	.	PUNCT
brj-23254	136	1	the	the	DET
brj-23254	136	2	adam	adam	PROPN
brj-23254	136	3	algorithm	algorithm	PROPN
brj-23254	136	4	was	be	AUX
brj-23254	136	5	used	use	VERB
brj-23254	136	6	to	to	PART
brj-23254	136	7	automatically	automatically	ADV
brj-23254	136	8	optimize	optimize	VERB
brj-23254	136	9	the	the	DET
brj-23254	136	10	learning	learning	NOUN
brj-23254	136	11	rate	rate	NOUN
brj-23254	136	12	.	.	PUNCT
brj-23254	137	1	all	all	DET
brj-23254	137	2	convolutional	convolutional	ADJ
brj-23254	137	3	layers	layer	NOUN
brj-23254	137	4	employed	employ	VERB
brj-23254	137	5	a	a	DET
brj-23254	137	6	rectified	rectified	ADJ
brj-23254	137	7	linear	linear	NOUN
brj-23254	137	8	unit	unit	NOUN
brj-23254	137	9	(	(	PUNCT
brj-23254	137	10	relu	relu	NOUN
brj-23254	137	11	)	)	PUNCT
brj-23254	137	12	activation	activation	NOUN
brj-23254	137	13	function	function	NOUN
brj-23254	137	14	with	with	ADP
brj-23254	137	15	a	a	DET
brj-23254	137	16	batch	batch	NOUN
brj-23254	137	17	size	size	NOUN
brj-23254	137	18	of	of	ADP
brj-23254	137	19	512	512	NUM
brj-23254	137	20	.	.	PUNCT
brj-23254	138	1	after	after	ADP
brj-23254	138	2	relu	relu	NOUN
brj-23254	138	3	activation	activation	NOUN
brj-23254	138	4	,	,	PUNCT
brj-23254	138	5	any	any	DET
brj-23254	138	6	input	input	NOUN
brj-23254	138	7	values	value	NOUN
brj-23254	138	8	that	that	PRON
brj-23254	138	9	were	be	AUX
brj-23254	138	10	not	not	PART
brj-23254	138	11	positive	positive	ADJ
brj-23254	138	12	were	be	AUX
brj-23254	138	13	translated	translate	VERB
brj-23254	138	14	to	to	ADP
brj-23254	138	15	an	an	DET
brj-23254	138	16	output	output	NOUN
brj-23254	138	17	of	of	ADP
brj-23254	138	18	zero	zero	NUM
brj-23254	138	19	.	.	PUNCT
brj-23254	139	1	the	the	DET
brj-23254	139	2	final	final	ADJ
brj-23254	139	3	dense	dense	ADJ
brj-23254	139	4	layer	layer	NOUN
brj-23254	139	5	uses	use	VERB
brj-23254	139	6	softmax	softmax	ADJ
brj-23254	139	7	activation	activation	NOUN
brj-23254	139	8	,	,	PUNCT
brj-23254	139	9	thereby	thereby	ADV
brj-23254	139	10	producing	produce	VERB
brj-23254	139	11	output	output	NOUN
brj-23254	139	12	values	value	NOUN
brj-23254	139	13	within	within	ADP
brj-23254	139	14	the	the	DET
brj-23254	139	15	zero	zero	NUM
brj-23254	139	16	to	to	ADP
brj-23254	139	17	1.0	1.0	NUM
brj-23254	139	18	range	range	NOUN
brj-23254	139	19	.	.	PUNCT
brj-23254	140	1	all	all	DET
brj-23254	140	2	the	the	DET
brj-23254	140	3	models	model	NOUN
brj-23254	140	4	were	be	AUX
brj-23254	140	5	trained	train	VERB
brj-23254	140	6	over	over	ADP
brj-23254	140	7	22	22	NUM
brj-23254	140	8	epochs	epoch	NOUN
brj-23254	140	9	until	until	SCONJ
brj-23254	140	10	the	the	DET
brj-23254	140	11	validation	validation	NOUN
brj-23254	140	12	loss	loss	NOUN
brj-23254	140	13	stabilized	stabilize	VERB
brj-23254	140	14	.	.	PUNCT
brj-23254	141	1	the	the	DET
brj-23254	141	2	authors	author	NOUN
brj-23254	141	3	scrutinized	scrutinize	VERB
brj-23254	141	4	the	the	DET
brj-23254	141	5	loss	loss	NOUN
brj-23254	141	6	progression	progression	NOUN
brj-23254	141	7	when	when	SCONJ
brj-23254	141	8	assessing	assess	VERB
brj-23254	141	9	the	the	DET
brj-23254	141	10	model	model	NOUN
brj-23254	141	11	results	result	NOUN
brj-23254	141	12	.	.	PUNCT
brj-23254	142	1	each	each	DET
brj-23254	142	2	dataset	dataset	NOUN
brj-23254	142	3	was	be	AUX
brj-23254	142	4	trained	train	VERB
brj-23254	142	5	for	for	ADP
brj-23254	142	6	approximately	approximately	ADV
brj-23254	142	7	5	5	NUM
brj-23254	142	8	min	min	NOUN
brj-23254	142	9	using	use	VERB
brj-23254	142	10	a	a	DET
brj-23254	142	11	geforce	geforce	NOUN
brj-23254	142	12	gtx	gtx	PROPN
brj-23254	142	13	1080	1080	NUM
brj-23254	142	14	gpu	gpu	X
brj-23254	142	15	(	(	PUNCT
brj-23254	142	16	nvidia	nvidia	PROPN
brj-23254	142	17	,	,	PUNCT
brj-23254	142	18	usa	usa	PROPN
brj-23254	142	19	)	)	PUNCT
brj-23254	142	20	.	.	PUNCT
brj-23254	143	1	to	to	PART
brj-23254	143	2	evaluate	evaluate	VERB
brj-23254	143	3	the	the	DET
brj-23254	143	4	model	model	NOUN
brj-23254	143	5	accuracy	accuracy	NOUN
brj-23254	143	6	,	,	PUNCT
brj-23254	143	7	fine	fine	ADV
brj-23254	143	8	-	-	PUNCT
brj-23254	143	9	tuning	tuning	NOUN
brj-23254	143	10	was	be	AUX
brj-23254	143	11	applied	apply	VERB
brj-23254	143	12	by	by	ADP
brj-23254	143	13	building	build	VERB
brj-23254	143	14	on	on	ADP
brj-23254	143	15	vgg16	vgg16	NOUN
brj-23254	143	16	with	with	ADP
brj-23254	143	17	weights	weight	NOUN
brj-23254	143	18	derived	derive	VERB
brj-23254	143	19	from	from	ADP
brj-23254	143	20	imagenet	imagenet	NOUN
brj-23254	143	21	(	(	PUNCT
brj-23254	143	22	resnet50	resnet50	NOUN
brj-23254	143	23	)	)	PUNCT
brj-23254	143	24	.	.	PUNCT
brj-23254	144	1	this	this	DET
brj-23254	144	2	fine	fine	ADJ
brj-23254	144	3	-	-	PUNCT
brj-23254	144	4	tuning	tuning	NOUN
brj-23254	144	5	merges	merge	NOUN
brj-23254	144	6	15	15	NUM
brj-23254	144	7	layers	layer	NOUN
brj-23254	144	8	of	of	ADP
brj-23254	144	9	a	a	DET
brj-23254	144	10	preexisting	preexisting	ADJ
brj-23254	144	11	fixed	fix	VERB
brj-23254	144	12	model	model	NOUN
brj-23254	144	13	with	with	ADP
brj-23254	144	14	new	new	ADJ
brj-23254	144	15	additions	addition	NOUN
brj-23254	144	16	,	,	PUNCT
brj-23254	144	17	facilitating	facilitate	VERB
brj-23254	144	18	the	the	DET
brj-23254	144	19	learning	learning	NOUN
brj-23254	144	20	of	of	ADP
brj-23254	144	21	new	new	ADJ
brj-23254	144	22	weights	weight	NOUN
brj-23254	144	23	and	and	CCONJ
brj-23254	144	24	enhancing	enhance	VERB
brj-23254	144	25	the	the	DET
brj-23254	144	26	generalization	generalization	NOUN
brj-23254	144	27	capacity	capacity	NOUN
brj-23254	144	28	of	of	ADP
brj-23254	144	29	the	the	DET
brj-23254	144	30	model	model	NOUN
brj-23254	144	31	.	.	PUNCT
brj-23254	145	1	because	because	SCONJ
brj-23254	145	2	fine	fine	NOUN
brj-23254	145	3	-	-	PUNCT
brj-23254	145	4	tuning	tuning	NOUN
brj-23254	145	5	relies	relie	NOUN
brj-23254	145	6	on	on	ADP
brj-23254	145	7	three	three	NUM
brj-23254	145	8	-	-	PUNCT
brj-23254	145	9	dimensional	dimensional	ADJ
brj-23254	145	10	input	input	NOUN
brj-23254	145	11	models	model	NOUN
brj-23254	145	12	,	,	PUNCT
brj-23254	145	13	grayscale	grayscale	NOUN
brj-23254	145	14	conversion	conversion	NOUN
brj-23254	145	15	was	be	AUX
brj-23254	145	16	not	not	PART
brj-23254	145	17	applied	apply	VERB
brj-23254	145	18	to	to	ADP
brj-23254	145	19	the	the	DET
brj-23254	145	20	images	image	NOUN
brj-23254	145	21	.	.	PUNCT
brj-23254	146	1	peer	peer	NOUN
brj-23254	146	2	-	-	PUNCT
brj-23254	146	3	reviewed	review	VERB
brj-23254	146	4	article	article	NOUN
brj-23254	146	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	146	6	ma	ma	PROPN
brj-23254	146	7	et	et	PROPN
brj-23254	146	8	al	al	PROPN
brj-23254	146	9	.	.	PROPN
brj-23254	147	1	(	(	PUNCT
brj-23254	147	2	2024	2024	NUM
brj-23254	147	3	)	)	PUNCT
brj-23254	147	4	.	.	PUNCT
brj-23254	148	1	“	"	PUNCT
brj-23254	148	2	wood	wood	NOUN
brj-23254	148	3	i	i	X
brj-23254	148	4	d	d	PROPN
brj-23254	148	5	via	via	ADP
brj-23254	148	6	deep	deep	ADJ
brj-23254	148	7	learning	learning	NOUN
brj-23254	148	8	,	,	PUNCT
brj-23254	148	9	”	"	PUNCT
brj-23254	148	10	bioresources	bioresource	NOUN
brj-23254	148	11	19(3	19(3	NUM
brj-23254	148	12	)	)	PUNCT
brj-23254	148	13	,	,	PUNCT
brj-23254	148	14	4838	4838	NUM
brj-23254	148	15	-	-	SYM
brj-23254	148	16	4851	4851	NUM
brj-23254	148	17	.	.	PUNCT
brj-23254	149	1	4845	4845	NUM
brj-23254	149	2	accuracy	accuracy	NOUN
brj-23254	149	3	evaluation	evaluation	NOUN
brj-23254	149	4	as	as	SCONJ
brj-23254	149	5	delineated	delineated	ADJ
brj-23254	149	6	in	in	ADP
brj-23254	149	7	section	section	NOUN
brj-23254	149	8	“	"	PUNCT
brj-23254	149	9	image	image	NOUN
brj-23254	149	10	processing	processing	NOUN
brj-23254	149	11	”	"	PUNCT
brj-23254	149	12	,	,	PUNCT
brj-23254	149	13	each	each	DET
brj-23254	149	14	species	specie	NOUN
brj-23254	149	15	was	be	AUX
brj-23254	149	16	assigned	assign	VERB
brj-23254	149	17	500	500	NUM
brj-23254	149	18	testing	testing	NOUN
brj-23254	149	19	patches	patch	NOUN
brj-23254	149	20	for	for	ADP
brj-23254	149	21	d1	d1	NOUN
brj-23254	149	22	and	and	CCONJ
brj-23254	149	23	2,000	2,000	NUM
brj-23254	149	24	testing	testing	NOUN
brj-23254	149	25	patches	patch	NOUN
brj-23254	149	26	for	for	ADP
brj-23254	149	27	d2	d2	PROPN
brj-23254	149	28	.	.	PUNCT
brj-23254	150	1	two	two	NUM
brj-23254	150	2	evaluation	evaluation	NOUN
brj-23254	150	3	methods	method	NOUN
brj-23254	150	4	were	be	AUX
brj-23254	150	5	used	use	VERB
brj-23254	150	6	in	in	ADP
brj-23254	150	7	this	this	DET
brj-23254	150	8	study	study	NOUN
brj-23254	150	9	.	.	PUNCT
brj-23254	151	1	for	for	ADP
brj-23254	151	2	evaluation	evaluation	NOUN
brj-23254	151	3	method	method	NOUN
brj-23254	151	4	1	1	NUM
brj-23254	151	5	(	(	PUNCT
brj-23254	151	6	e1	e1	PROPN
brj-23254	151	7	)	)	PUNCT
brj-23254	151	8	,	,	PUNCT
brj-23254	151	9	the	the	DET
brj-23254	151	10	species	specie	NOUN
brj-23254	151	11	from	from	ADP
brj-23254	151	12	all	all	DET
brj-23254	151	13	patches	patch	NOUN
brj-23254	151	14	were	be	AUX
brj-23254	151	15	predicted	predict	VERB
brj-23254	151	16	and	and	CCONJ
brj-23254	151	17	used	use	VERB
brj-23254	151	18	to	to	PART
brj-23254	151	19	calculate	calculate	VERB
brj-23254	151	20	accuracy	accuracy	NOUN
brj-23254	151	21	,	,	PUNCT
brj-23254	151	22	meaning	mean	VERB
brj-23254	151	23	that	that	SCONJ
brj-23254	151	24	the	the	DET
brj-23254	151	25	predicted	predict	VERB
brj-23254	151	26	outcomes	outcome	NOUN
brj-23254	151	27	from	from	ADP
brj-23254	151	28	all	all	DET
brj-23254	151	29	patches	patch	NOUN
brj-23254	151	30	were	be	AUX
brj-23254	151	31	considered	consider	VERB
brj-23254	151	32	when	when	SCONJ
brj-23254	151	33	determining	determine	VERB
brj-23254	151	34	accuracy	accuracy	NOUN
brj-23254	151	35	.	.	PUNCT
brj-23254	152	1	thus	thus	ADV
brj-23254	152	2	,	,	PUNCT
brj-23254	152	3	100	100	NUM
brj-23254	152	4	predictions	prediction	NOUN
brj-23254	152	5	corresponding	correspond	VERB
brj-23254	152	6	to	to	ADP
brj-23254	152	7	each	each	DET
brj-23254	152	8	patch	patch	NOUN
brj-23254	152	9	were	be	AUX
brj-23254	152	10	derived	derive	VERB
brj-23254	152	11	from	from	ADP
brj-23254	152	12	each	each	DET
brj-23254	152	13	image	image	NOUN
brj-23254	152	14	.	.	PUNCT
brj-23254	153	1	the	the	DET
brj-23254	153	2	accuracy	accuracy	NOUN
brj-23254	153	3	of	of	ADP
brj-23254	153	4	all	all	DET
brj-23254	153	5	predictions	prediction	NOUN
brj-23254	153	6	was	be	AUX
brj-23254	153	7	calculated	calculate	VERB
brj-23254	153	8	,	,	PUNCT
brj-23254	153	9	thereby	thereby	ADV
brj-23254	153	10	providing	provide	VERB
brj-23254	153	11	a	a	DET
brj-23254	153	12	comprehensive	comprehensive	ADJ
brj-23254	153	13	view	view	NOUN
brj-23254	153	14	of	of	ADP
brj-23254	153	15	the	the	DET
brj-23254	153	16	model	model	NOUN
brj-23254	153	17	's	's	PART
brj-23254	153	18	performance	performance	NOUN
brj-23254	153	19	across	across	ADP
brj-23254	153	20	the	the	DET
brj-23254	153	21	entirety	entirety	NOUN
brj-23254	153	22	of	of	ADP
brj-23254	153	23	each	each	DET
brj-23254	153	24	image	image	NOUN
brj-23254	153	25	.	.	PUNCT
brj-23254	154	1	in	in	ADP
brj-23254	154	2	evaluation	evaluation	NOUN
brj-23254	154	3	method	method	NOUN
brj-23254	154	4	2	2	NUM
brj-23254	154	5	(	(	PUNCT
brj-23254	154	6	e2	e2	PROPN
brj-23254	154	7	)	)	PUNCT
brj-23254	154	8	,	,	PUNCT
brj-23254	154	9	a	a	DET
brj-23254	154	10	sum	sum	NOUN
brj-23254	154	11	rule	rule	NOUN
brj-23254	154	12	was	be	AUX
brj-23254	154	13	implemented	implement	VERB
brj-23254	154	14	,	,	PUNCT
brj-23254	154	15	as	as	SCONJ
brj-23254	154	16	shown	show	VERB
brj-23254	154	17	in	in	ADP
brj-23254	154	18	table	table	NOUN
brj-23254	154	19	2	2	NUM
brj-23254	154	20	,	,	PUNCT
brj-23254	154	21	wherein	wherein	SCONJ
brj-23254	154	22	the	the	DET
brj-23254	154	23	sum	sum	NOUN
brj-23254	154	24	of	of	ADP
brj-23254	154	25	all	all	DET
brj-23254	154	26	probabilities	probability	NOUN
brj-23254	154	27	associated	associate	VERB
brj-23254	154	28	with	with	ADP
brj-23254	154	29	patches	patch	NOUN
brj-23254	154	30	for	for	ADP
brj-23254	154	31	each	each	DET
brj-23254	154	32	image	image	NOUN
brj-23254	154	33	was	be	AUX
brj-23254	154	34	maximized	maximize	VERB
brj-23254	154	35	.	.	PUNCT
brj-23254	155	1	consequently	consequently	ADV
brj-23254	155	2	,	,	PUNCT
brj-23254	155	3	the	the	DET
brj-23254	155	4	probabilities	probability	NOUN
brj-23254	155	5	generated	generate	VERB
brj-23254	155	6	by	by	ADP
brj-23254	155	7	the	the	DET
brj-23254	155	8	cnn	cnn	PROPN
brj-23254	155	9	,	,	PUNCT
brj-23254	155	10	which	which	PRON
brj-23254	155	11	corresponded	correspond	VERB
brj-23254	155	12	to	to	ADP
brj-23254	155	13	all	all	DET
brj-23254	155	14	the	the	DET
brj-23254	155	15	species	specie	NOUN
brj-23254	155	16	,	,	PUNCT
brj-23254	155	17	were	be	AUX
brj-23254	155	18	summed	sum	VERB
brj-23254	155	19	over	over	ADP
brj-23254	155	20	the	the	DET
brj-23254	155	21	patches	patch	NOUN
brj-23254	155	22	to	to	PART
brj-23254	155	23	categorize	categorize	VERB
brj-23254	155	24	the	the	DET
brj-23254	155	25	wood	wood	NOUN
brj-23254	155	26	species	specie	NOUN
brj-23254	155	27	.	.	PUNCT
brj-23254	156	1	in	in	ADP
brj-23254	156	2	other	other	ADJ
brj-23254	156	3	words	word	NOUN
brj-23254	156	4	,	,	PUNCT
brj-23254	156	5	a	a	DET
brj-23254	156	6	single	single	ADJ
brj-23254	156	7	prediction	prediction	NOUN
brj-23254	156	8	value	value	NOUN
brj-23254	156	9	was	be	AUX
brj-23254	156	10	generated	generate	VERB
brj-23254	156	11	for	for	ADP
brj-23254	156	12	each	each	DET
brj-23254	156	13	image	image	NOUN
brj-23254	156	14	.	.	PUNCT
brj-23254	157	1	this	this	DET
brj-23254	157	2	single	single	ADJ
brj-23254	157	3	prediction	prediction	NOUN
brj-23254	157	4	represents	represent	VERB
brj-23254	157	5	the	the	DET
brj-23254	157	6	model	model	NOUN
brj-23254	157	7	's	's	PART
brj-23254	157	8	assessment	assessment	NOUN
brj-23254	157	9	of	of	ADP
brj-23254	157	10	the	the	DET
brj-23254	157	11	entire	entire	ADJ
brj-23254	157	12	given	give	VERB
brj-23254	157	13	image	image	NOUN
brj-23254	157	14	.	.	PUNCT
brj-23254	158	1	to	to	PART
brj-23254	158	2	assess	assess	VERB
brj-23254	158	3	the	the	DET
brj-23254	158	4	impact	impact	NOUN
brj-23254	158	5	of	of	ADP
brj-23254	158	6	the	the	DET
brj-23254	158	7	pixel	pixel	ADJ
brj-23254	158	8	size	size	NOUN
brj-23254	158	9	on	on	ADP
brj-23254	158	10	the	the	DET
brj-23254	158	11	accuracy	accuracy	NOUN
brj-23254	158	12	of	of	ADP
brj-23254	158	13	the	the	DET
brj-23254	158	14	cnn	cnn	PROPN
brj-23254	158	15	model	model	NOUN
brj-23254	158	16	,	,	PUNCT
brj-23254	158	17	the	the	DET
brj-23254	158	18	extracted	extract	VERB
brj-23254	158	19	files	file	NOUN
brj-23254	158	20	were	be	AUX
brj-23254	158	21	tested	test	VERB
brj-23254	158	22	at	at	ADP
brj-23254	158	23	pixel	pixel	ADJ
brj-23254	158	24	sizes	size	NOUN
brj-23254	158	25	of	of	ADP
brj-23254	158	26	16	16	NUM
brj-23254	158	27	,	,	PUNCT
brj-23254	158	28	32	32	NUM
brj-23254	158	29	,	,	PUNCT
brj-23254	158	30	64	64	NUM
brj-23254	158	31	,	,	PUNCT
brj-23254	158	32	128	128	NUM
brj-23254	158	33	,	,	PUNCT
brj-23254	158	34	and	and	CCONJ
brj-23254	158	35	256	256	NUM
brj-23254	158	36	.	.	PUNCT
brj-23254	159	1	the	the	DET
brj-23254	159	2	results	result	NOUN
brj-23254	159	3	revealed	reveal	VERB
brj-23254	159	4	no	no	DET
brj-23254	159	5	dramatic	dramatic	ADJ
brj-23254	159	6	improvements	improvement	NOUN
brj-23254	159	7	in	in	ADP
brj-23254	159	8	the	the	DET
brj-23254	159	9	accuracy	accuracy	NOUN
brj-23254	159	10	for	for	ADP
brj-23254	159	11	pixel	pixel	NOUN
brj-23254	159	12	sizes	size	NOUN
brj-23254	159	13	greater	great	ADJ
brj-23254	159	14	than	than	ADP
brj-23254	159	15	64	64	NUM
brj-23254	159	16	.	.	PUNCT
brj-23254	160	1	consequently	consequently	ADV
brj-23254	160	2	,	,	PUNCT
brj-23254	160	3	64	64	NUM
brj-23254	160	4	pixels	pixel	NOUN
brj-23254	160	5	were	be	AUX
brj-23254	160	6	selected	select	VERB
brj-23254	160	7	for	for	ADP
brj-23254	160	8	the	the	DET
brj-23254	160	9	study	study	NOUN
brj-23254	160	10	.	.	PUNCT
brj-23254	161	1	table	table	NOUN
brj-23254	161	2	2	2	NUM
brj-23254	161	3	.	.	X
brj-23254	161	4	sum	sum	NOUN
brj-23254	161	5	rule	rule	NOUN
brj-23254	161	6	for	for	ADP
brj-23254	161	7	accuracy	accuracy	NOUN
brj-23254	161	8	calculation	calculation	NOUN
brj-23254	161	9	class1	class1	NOUN
brj-23254	161	10	class1	class1	NOUN
brj-23254	161	11	class1	class1	NOUN
brj-23254	161	12	…	…	PUNCT
brj-23254	161	13	class50	class50	ADJ
brj-23254	161	14	patch1	patch1	NOUN
brj-23254	161	15	0.5	0.5	NUM
brj-23254	161	16	*	*	SYM
brj-23254	161	17	0.03	0.03	NUM
brj-23254	161	18	0.01	0.01	NUM
brj-23254	161	19	…	…	PUNCT
brj-23254	161	20	0.001	0.001	NUM
brj-23254	161	21	patch2	patch2	NOUN
brj-23254	161	22	0.7	0.7	NUM
brj-23254	161	23	*	*	SYM
brj-23254	161	24	0.01	0.01	NUM
brj-23254	161	25	0	0	NUM
brj-23254	161	26	…	…	SYM
brj-23254	161	27	0.001	0.001	NUM
brj-23254	161	28	…	…	PUNCT
brj-23254	161	29	…	…	PUNCT
brj-23254	161	30	…	…	PUNCT
brj-23254	161	31	…	…	PUNCT
brj-23254	161	32	…	…	PUNCT
brj-23254	161	33	…	…	PUNCT
brj-23254	161	34	patch99	patch99	X
brj-23254	161	35	0.1	0.1	NUM
brj-23254	161	36	0.5	0.5	NUM
brj-23254	161	37	*	*	SYM
brj-23254	161	38	0.1	0.1	NUM
brj-23254	161	39	…	…	PUNCT
brj-23254	161	40	0.01	0.01	NUM
brj-23254	161	41	patch100	patch100	PROPN
brj-23254	161	42	0.8	0.8	NUM
brj-23254	161	43	*	*	NOUN
brj-23254	161	44	0.1	0.1	NUM
brj-23254	161	45	0.1	0.1	NUM
brj-23254	161	46	…	…	PUNCT
brj-23254	161	47	0.2	0.2	NUM
brj-23254	161	48	sum	sum	NOUN
brj-23254	161	49	of	of	ADP
brj-23254	161	50	predict	predict	ADJ
brj-23254	161	51	value	value	NOUN
brj-23254	161	52	↓	↓	PROPN
brj-23254	161	53	↓	↓	PROPN
brj-23254	161	54	↓	↓	PROPN
brj-23254	161	55	↓	↓	PROPN
brj-23254	161	56	↓	↓	PROPN
brj-23254	161	57	image1	image1	PROPN
brj-23254	162	1	57	57	NUM
brj-23254	162	2	*	*	SYM
brj-23254	162	3	3	3	NUM
brj-23254	162	4	2	2	NUM
brj-23254	162	5	…	…	SYM
brj-23254	162	6	0.9	0.9	NUM
brj-23254	162	7	*	*	NUM
brj-23254	162	8	predicted	predict	VERB
brj-23254	162	9	class	class	NOUN
brj-23254	162	10	by	by	ADP
brj-23254	162	11	patch	patch	NOUN
brj-23254	162	12	or	or	CCONJ
brj-23254	162	13	image	image	NOUN
brj-23254	162	14	results	result	NOUN
brj-23254	162	15	and	and	CCONJ
brj-23254	162	16	discussion	discussion	NOUN
brj-23254	162	17	effect	effect	NOUN
brj-23254	162	18	of	of	ADP
brj-23254	162	19	evaluation	evaluation	NOUN
brj-23254	162	20	method	method	NOUN
brj-23254	162	21	on	on	ADP
brj-23254	162	22	accuracy	accuracy	NOUN
brj-23254	162	23	table	table	NOUN
brj-23254	162	24	3	3	NUM
brj-23254	162	25	presents	present	VERB
brj-23254	162	26	the	the	DET
brj-23254	162	27	accuracy	accuracy	NOUN
brj-23254	162	28	of	of	ADP
brj-23254	162	29	the	the	DET
brj-23254	162	30	predictions	prediction	NOUN
brj-23254	162	31	derived	derive	VERB
brj-23254	162	32	from	from	ADP
brj-23254	162	33	both	both	CCONJ
brj-23254	162	34	d1	d1	PROPN
brj-23254	162	35	and	and	CCONJ
brj-23254	162	36	d2	d2	PROPN
brj-23254	162	37	datasets	dataset	NOUN
brj-23254	162	38	.	.	PUNCT
brj-23254	163	1	notably	notably	ADV
brj-23254	163	2	,	,	PUNCT
brj-23254	163	3	e2	e2	PROPN
brj-23254	163	4	consistently	consistently	ADV
brj-23254	163	5	outperformed	outperform	VERB
brj-23254	163	6	e1	e1	NOUN
brj-23254	163	7	.	.	PUNCT
brj-23254	164	1	consequently	consequently	ADV
brj-23254	164	2	,	,	PUNCT
brj-23254	164	3	the	the	DET
brj-23254	164	4	prediction	prediction	NOUN
brj-23254	164	5	accuracy	accuracy	NOUN
brj-23254	164	6	was	be	AUX
brj-23254	164	7	enhanced	enhance	VERB
brj-23254	164	8	by	by	ADP
brj-23254	164	9	aggregating	aggregate	VERB
brj-23254	164	10	the	the	DET
brj-23254	164	11	outcomes	outcome	NOUN
brj-23254	164	12	of	of	ADP
brj-23254	164	13	100	100	NUM
brj-23254	164	14	patches	patch	NOUN
brj-23254	164	15	extracted	extract	VERB
brj-23254	164	16	from	from	ADP
brj-23254	164	17	each	each	DET
brj-23254	164	18	image	image	NOUN
brj-23254	164	19	.	.	PUNCT
brj-23254	165	1	the	the	DET
brj-23254	165	2	e2	e2	PROPN
brj-23254	165	3	evaluation	evaluation	NOUN
brj-23254	165	4	used	use	VERB
brj-23254	165	5	in	in	ADP
brj-23254	165	6	this	this	DET
brj-23254	165	7	study	study	NOUN
brj-23254	165	8	closely	closely	ADV
brj-23254	165	9	mirrors	mirror	VERB
brj-23254	165	10	the	the	DET
brj-23254	165	11	method	method	NOUN
brj-23254	165	12	utilized	utilize	VERB
brj-23254	165	13	by	by	ADP
brj-23254	165	14	hafemann	hafemann	PROPN
brj-23254	165	15	et	et	PROPN
brj-23254	165	16	al	al	PROPN
brj-23254	165	17	.	.	PROPN
brj-23254	166	1	(	(	PUNCT
brj-23254	166	2	2014	2014	NUM
brj-23254	166	3	)	)	PUNCT
brj-23254	166	4	,	,	PUNCT
brj-23254	166	5	who	who	PRON
brj-23254	166	6	stated	state	VERB
brj-23254	166	7	that	that	SCONJ
brj-23254	166	8	"	"	PUNCT
brj-23254	166	9	for	for	ADP
brj-23254	166	10	the	the	DET
brj-23254	166	11	recognition	recognition	NOUN
brj-23254	166	12	,	,	PUNCT
brj-23254	166	13	patch	patch	NOUN
brj-23254	166	14	results	result	NOUN
brj-23254	166	15	are	be	AUX
brj-23254	166	16	combined	combine	VERB
brj-23254	166	17	for	for	ADP
brj-23254	166	18	the	the	DET
brj-23254	166	19	entire	entire	ADJ
brj-23254	166	20	image	image	NOUN
brj-23254	166	21	.	.	PUNCT
brj-23254	167	1	the	the	DET
brj-23254	167	2	straightforward	straightforward	ADJ
brj-23254	167	3	solution	solution	NOUN
brj-23254	167	4	is	be	AUX
brj-23254	167	5	to	to	PART
brj-23254	167	6	solely	solely	ADV
brj-23254	167	7	use	use	VERB
brj-23254	167	8	the	the	DET
brj-23254	167	9	central	central	ADJ
brj-23254	167	10	patch	patch	NOUN
brj-23254	167	11	of	of	ADP
brj-23254	167	12	the	the	DET
brj-23254	167	13	image	image	NOUN
brj-23254	167	14	for	for	ADP
brj-23254	167	15	testing	testing	NOUN
brj-23254	167	16	,	,	PUNCT
brj-23254	167	17	but	but	CCONJ
brj-23254	167	18	this	this	PRON
brj-23254	167	19	yields	yield	VERB
brj-23254	167	20	suboptimal	suboptimal	ADJ
brj-23254	167	21	results	result	NOUN
brj-23254	167	22	,	,	PUNCT
brj-23254	167	23	as	as	SCONJ
brj-23254	167	24	patches	patch	NOUN
brj-23254	167	25	are	be	AUX
brj-23254	167	26	smaller	small	ADJ
brj-23254	167	27	than	than	ADP
brj-23254	167	28	the	the	DET
brj-23254	167	29	images	image	NOUN
brj-23254	167	30	.	.	PUNCT
brj-23254	168	1	in	in	ADP
brj-23254	168	2	this	this	DET
brj-23254	168	3	work	work	NOUN
brj-23254	168	4	,	,	PUNCT
brj-23254	168	5	we	we	PRON
brj-23254	168	6	consider	consider	VERB
brj-23254	168	7	the	the	DET
brj-23254	168	8	sum	sum	NOUN
brj-23254	168	9	rule	rule	NOUN
brj-23254	168	10	:	:	PUNCT
brj-23254	168	11	the	the	DET
brj-23254	168	12	prediction	prediction	NOUN
brj-23254	168	13	for	for	ADP
brj-23254	168	14	a	a	DET
brj-23254	168	15	given	give	VERB
brj-23254	168	16	test	test	NOUN
brj-23254	168	17	image	image	NOUN
brj-23254	168	18	is	be	AUX
brj-23254	168	19	the	the	DET
brj-23254	168	20	class	class	NOUN
brj-23254	168	21	that	that	PRON
brj-23254	168	22	maximizes	maximize	VERB
brj-23254	168	23	the	the	DET
brj-23254	168	24	sum	sum	NOUN
brj-23254	168	25	of	of	ADP
brj-23254	168	26	the	the	DET
brj-23254	168	27	probabilities	probability	NOUN
brj-23254	168	28	on	on	ADP
brj-23254	168	29	all	all	DET
brj-23254	168	30	patches	patch	NOUN
brj-23254	168	31	of	of	ADP
brj-23254	168	32	the	the	DET
brj-23254	168	33	image	image	NOUN
brj-23254	168	34	.	.	PUNCT
brj-23254	168	35	"	"	PUNCT
brj-23254	169	1	nevertheless	nevertheless	ADV
brj-23254	169	2	,	,	PUNCT
brj-23254	169	3	the	the	DET
brj-23254	169	4	prediction	prediction	NOUN
brj-23254	169	5	accuracy	accuracy	NOUN
brj-23254	169	6	achieved	achieve	VERB
brj-23254	169	7	in	in	ADP
brj-23254	169	8	this	this	DET
brj-23254	169	9	study	study	NOUN
brj-23254	169	10	was	be	AUX
brj-23254	169	11	relatively	relatively	ADV
brj-23254	169	12	low	low	ADJ
brj-23254	169	13	(	(	PUNCT
brj-23254	169	14	44	44	NUM
brj-23254	169	15	%	%	NOUN
brj-23254	169	16	for	for	ADP
brj-23254	169	17	50	50	NUM
brj-23254	169	18	species	specie	NOUN
brj-23254	169	19	with	with	ADP
brj-23254	169	20	20	20	NUM
brj-23254	169	21	images	image	NOUN
brj-23254	169	22	per	per	ADP
brj-23254	169	23	class	class	NOUN
brj-23254	169	24	)	)	PUNCT
brj-23254	169	25	compared	compare	VERB
brj-23254	169	26	to	to	ADP
brj-23254	169	27	that	that	PRON
brj-23254	169	28	(	(	PUNCT
brj-23254	169	29	97	97	NUM
brj-23254	169	30	%	%	NOUN
brj-23254	169	31	for	for	ADP
brj-23254	169	32	112	112	NUM
brj-23254	169	33	species	specie	NOUN
brj-23254	169	34	with	with	ADP
brj-23254	169	35	20	20	NUM
brj-23254	169	36	images	image	NOUN
brj-23254	169	37	per	per	ADP
brj-23254	169	38	class	class	NOUN
brj-23254	169	39	)	)	PUNCT
brj-23254	169	40	reported	report	VERB
brj-23254	169	41	by	by	ADP
brj-23254	169	42	hafemann	hafemann	PROPN
brj-23254	169	43	et	et	PROPN
brj-23254	169	44	al	al	PROPN
brj-23254	169	45	.	.	PROPN
brj-23254	170	1	(	(	PUNCT
brj-23254	170	2	2014	2014	NUM
brj-23254	170	3	)	)	PUNCT
brj-23254	170	4	.	.	PUNCT
brj-23254	171	1	this	this	DET
brj-23254	171	2	discrepancy	discrepancy	NOUN
brj-23254	171	3	can	can	AUX
brj-23254	171	4	be	be	AUX
brj-23254	171	5	attributed	attribute	VERB
brj-23254	171	6	to	to	ADP
brj-23254	171	7	the	the	DET
brj-23254	171	8	authors	author	NOUN
brj-23254	171	9	’	’	PART
brj-23254	171	10	distinct	distinct	ADJ
brj-23254	171	11	patch	patch	NOUN
brj-23254	171	12	extraction	extraction	NOUN
brj-23254	171	13	method	method	NOUN
brj-23254	171	14	,	,	PUNCT
brj-23254	171	15	which	which	PRON
brj-23254	171	16	extracts	extract	VERB
brj-23254	171	17	100	100	NUM
brj-23254	171	18	patches	patch	NOUN
brj-23254	171	19	from	from	ADP
brj-23254	171	20	each	each	DET
brj-23254	171	21	image	image	NOUN
brj-23254	171	22	,	,	PUNCT
brj-23254	171	23	whereas	whereas	SCONJ
brj-23254	171	24	hafemann	hafemann	NOUN
brj-23254	171	25	et	et	PROPN
brj-23254	171	26	al	al	PROPN
brj-23254	171	27	.	.	PROPN
brj-23254	172	1	(	(	PUNCT
brj-23254	172	2	2014	2014	NUM
brj-23254	172	3	)	)	PUNCT
brj-23254	172	4	extracted	extract	VERB
brj-23254	172	5	a	a	DET
brj-23254	172	6	single	single	ADJ
brj-23254	172	7	patch	patch	NOUN
brj-23254	172	8	per	per	ADP
brj-23254	172	9	training	train	VERB
brj-23254	172	10	epoch	epoch	NOUN
brj-23254	172	11	from	from	ADP
brj-23254	172	12	each	each	DET
brj-23254	172	13	image	image	NOUN
brj-23254	172	14	.	.	PUNCT
brj-23254	173	1	however	however	ADV
brj-23254	173	2	,	,	PUNCT
brj-23254	173	3	it	it	PRON
brj-23254	173	4	is	be	AUX
brj-23254	173	5	not	not	PART
brj-23254	173	6	anticipated	anticipate	VERB
brj-23254	173	7	that	that	SCONJ
brj-23254	173	8	a	a	DET
brj-23254	173	9	significant	significant	ADJ
brj-23254	173	10	improvement	improvement	NOUN
brj-23254	173	11	in	in	ADP
brj-23254	173	12	the	the	DET
brj-23254	173	13	accuracy	accuracy	NOUN
brj-23254	173	14	will	will	AUX
brj-23254	173	15	be	be	AUX
brj-23254	173	16	gained	gain	VERB
brj-23254	173	17	if	if	SCONJ
brj-23254	173	18	an	an	DET
brj-23254	173	19	exact	exact	ADJ
brj-23254	173	20	approach	approach	NOUN
brj-23254	173	21	is	be	AUX
brj-23254	173	22	adopted	adopt	VERB
brj-23254	173	23	.	.	PUNCT
brj-23254	174	1	additionally	additionally	ADV
brj-23254	174	2	,	,	PUNCT
brj-23254	174	3	considerable	considerable	ADJ
brj-23254	174	4	fluctuation	fluctuation	NOUN
brj-23254	174	5	in	in	ADP
brj-23254	174	6	accuracy	accuracy	NOUN
brj-23254	174	7	was	be	AUX
brj-23254	174	8	observed	observe	VERB
brj-23254	174	9	,	,	PUNCT
brj-23254	174	10	peer	peer	NOUN
brj-23254	174	11	-	-	PUNCT
brj-23254	174	12	reviewed	review	VERB
brj-23254	174	13	article	article	NOUN
brj-23254	174	14	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	174	15	ma	ma	PROPN
brj-23254	174	16	et	et	PROPN
brj-23254	174	17	al	al	PROPN
brj-23254	174	18	.	.	PROPN
brj-23254	175	1	(	(	PUNCT
brj-23254	175	2	2024	2024	NUM
brj-23254	175	3	)	)	PUNCT
brj-23254	175	4	.	.	PUNCT
brj-23254	176	1	“	"	PUNCT
brj-23254	176	2	wood	wood	NOUN
brj-23254	176	3	i	i	X
brj-23254	176	4	d	d	PROPN
brj-23254	176	5	via	via	ADP
brj-23254	176	6	deep	deep	ADJ
brj-23254	176	7	learning	learning	NOUN
brj-23254	176	8	,	,	PUNCT
brj-23254	176	9	”	"	PUNCT
brj-23254	176	10	bioresources	bioresource	NOUN
brj-23254	176	11	19(3	19(3	NUM
brj-23254	176	12	)	)	PUNCT
brj-23254	176	13	,	,	PUNCT
brj-23254	176	14	4838	4838	NUM
brj-23254	176	15	-	-	SYM
brj-23254	176	16	4851	4851	NUM
brj-23254	176	17	.	.	PUNCT
brj-23254	177	1	4846	4846	NUM
brj-23254	177	2	depending	depend	VERB
brj-23254	177	3	on	on	ADP
brj-23254	177	4	how	how	SCONJ
brj-23254	177	5	the	the	DET
brj-23254	177	6	data	datum	NOUN
brj-23254	177	7	were	be	AUX
brj-23254	177	8	split	split	VERB
brj-23254	177	9	between	between	ADP
brj-23254	177	10	the	the	DET
brj-23254	177	11	training	training	NOUN
brj-23254	177	12	and	and	CCONJ
brj-23254	177	13	test	test	NOUN
brj-23254	177	14	sets	set	NOUN
brj-23254	177	15	.	.	PUNCT
brj-23254	178	1	this	this	PRON
brj-23254	178	2	is	be	AUX
brj-23254	178	3	a	a	DET
brj-23254	178	4	common	common	ADJ
brj-23254	178	5	phenomenon	phenomenon	NOUN
brj-23254	178	6	in	in	ADP
brj-23254	178	7	the	the	DET
brj-23254	178	8	field	field	NOUN
brj-23254	178	9	of	of	ADP
brj-23254	178	10	data	datum	NOUN
brj-23254	178	11	science	science	NOUN
brj-23254	178	12	,	,	PUNCT
brj-23254	178	13	and	and	CCONJ
brj-23254	178	14	it	it	PRON
brj-23254	178	15	underlines	underline	VERB
brj-23254	178	16	the	the	DET
brj-23254	178	17	importance	importance	NOUN
brj-23254	178	18	of	of	ADP
brj-23254	178	19	partitioning	partition	VERB
brj-23254	178	20	data	datum	NOUN
brj-23254	178	21	for	for	ADP
brj-23254	178	22	model	model	NOUN
brj-23254	178	23	training	training	NOUN
brj-23254	178	24	and	and	CCONJ
brj-23254	178	25	evaluation	evaluation	NOUN
brj-23254	178	26	.	.	PUNCT
brj-23254	179	1	notably	notably	ADV
brj-23254	179	2	,	,	PUNCT
brj-23254	179	3	this	this	DET
brj-23254	179	4	model	model	NOUN
brj-23254	179	5	must	must	AUX
brj-23254	179	6	be	be	AUX
brj-23254	179	7	evaluated	evaluate	VERB
brj-23254	179	8	using	use	VERB
brj-23254	179	9	a	a	DET
brj-23254	179	10	dataset	dataset	NOUN
brj-23254	179	11	divided	divide	VERB
brj-23254	179	12	in	in	ADP
brj-23254	179	13	a	a	DET
brj-23254	179	14	manner	manner	NOUN
brj-23254	179	15	similar	similar	ADJ
brj-23254	179	16	to	to	ADP
brj-23254	179	17	that	that	PRON
brj-23254	179	18	of	of	ADP
brj-23254	179	19	the	the	DET
brj-23254	179	20	d1	d1	NOUN
brj-23254	179	21	-	-	PUNCT
brj-23254	179	22	divided	divide	VERB
brj-23254	179	23	dataset	dataset	NOUN
brj-23254	179	24	.	.	PUNCT
brj-23254	180	1	this	this	DET
brj-23254	180	2	partitioning	partition	VERB
brj-23254	180	3	strategy	strategy	NOUN
brj-23254	180	4	ensures	ensure	VERB
brj-23254	180	5	a	a	DET
brj-23254	180	6	more	more	ADV
brj-23254	180	7	reliable	reliable	ADJ
brj-23254	180	8	assessment	assessment	NOUN
brj-23254	180	9	of	of	ADP
brj-23254	180	10	the	the	DET
brj-23254	180	11	model	model	NOUN
brj-23254	180	12	's	's	PART
brj-23254	180	13	real	real	ADJ
brj-23254	180	14	-	-	PUNCT
brj-23254	180	15	world	world	NOUN
brj-23254	180	16	applicability	applicability	NOUN
brj-23254	180	17	and	and	CCONJ
brj-23254	180	18	robustness	robustness	NOUN
brj-23254	180	19	.	.	PUNCT
brj-23254	181	1	table	table	NOUN
brj-23254	181	2	3	3	NUM
brj-23254	181	3	.	.	PUNCT
brj-23254	182	1	the	the	DET
brj-23254	182	2	accuracy	accuracy	NOUN
brj-23254	182	3	of	of	ADP
brj-23254	182	4	predictions	prediction	NOUN
brj-23254	182	5	derived	derive	VERB
brj-23254	182	6	from	from	ADP
brj-23254	182	7	both	both	CCONJ
brj-23254	182	8	d1	d1	PROPN
brj-23254	182	9	and	and	CCONJ
brj-23254	182	10	d2	d2	PROPN
brj-23254	182	11	datasets	dataset	NOUN
brj-23254	182	12	number	number	NOUN
brj-23254	182	13	of	of	ADP
brj-23254	182	14	classes	class	NOUN
brj-23254	182	15	model	model	VERB
brj-23254	182	16	dataset	dataset	NOUN
brj-23254	182	17	evaluation	evaluation	NOUN
brj-23254	182	18	accuracy	accuracy	NOUN
brj-23254	182	19	(	(	PUNCT
brj-23254	182	20	%	%	INTJ
brj-23254	182	21	)	)	PUNCT
brj-23254	182	22	test	test	NOUN
brj-23254	182	23	set	set	VERB
brj-23254	182	24	surplus	surplus	NOUN
brj-23254	182	25	set	set	VERB
brj-23254	182	26	50	50	NUM
brj-23254	182	27	(	(	PUNCT
brj-23254	182	28	species	specie	NOUN
brj-23254	182	29	)	)	PUNCT
brj-23254	182	30	hafemann	hafemann	NOUN
brj-23254	182	31	et	et	PROPN
brj-23254	182	32	al	al	PROPN
brj-23254	182	33	.	.	PROPN
brj-23254	183	1	(	(	PUNCT
brj-23254	183	2	2014	2014	NUM
brj-23254	183	3	)	)	PUNCT
brj-23254	183	4	d1	d1	NOUN
brj-23254	183	5	-	-	PUNCT
brj-23254	183	6	divided	divide	VERB
brj-23254	183	7	e1	e1	NOUN
brj-23254	183	8	-	-	PUNCT
brj-23254	183	9	patch	patch	NOUN
brj-23254	183	10	28	28	NUM
brj-23254	183	11	30	30	NUM
brj-23254	183	12	e2	e2	NOUN
brj-23254	183	13	-	-	PUNCT
brj-23254	183	14	image	image	NOUN
brj-23254	183	15	44	44	NUM
brj-23254	183	16	45	45	NUM
brj-23254	183	17	d2	d2	PROPN
brj-23254	183	18	-	-	PUNCT
brj-23254	183	19	non	non	ADJ
brj-23254	183	20	-	-	ADJ
brj-23254	183	21	divided	divide	VERB
brj-23254	183	22	e1	e1	NOUN
brj-23254	183	23	-	-	PUNCT
brj-23254	183	24	patch	patch	NOUN
brj-23254	183	25	44	44	NUM
brj-23254	183	26	33	33	NUM
brj-23254	183	27	e2	e2	NOUN
brj-23254	183	28	-	-	PUNCT
brj-23254	183	29	image	image	NOUN
brj-23254	183	30	70	70	NUM
brj-23254	183	31	52	52	NUM
brj-23254	183	32	effect	effect	NOUN
brj-23254	183	33	of	of	ADP
brj-23254	183	34	data	datum	NOUN
brj-23254	183	35	allocation	allocation	NOUN
brj-23254	183	36	scheme	scheme	NOUN
brj-23254	183	37	on	on	ADP
brj-23254	183	38	accuracy	accuracy	NOUN
brj-23254	183	39	a	a	DET
brj-23254	183	40	comparison	comparison	NOUN
brj-23254	183	41	of	of	ADP
brj-23254	183	42	the	the	DET
brj-23254	183	43	accuracy	accuracy	NOUN
brj-23254	183	44	between	between	ADP
brj-23254	183	45	datasets	dataset	NOUN
brj-23254	183	46	d1	d1	PROPN
brj-23254	183	47	and	and	CCONJ
brj-23254	183	48	d2	d2	PROPN
brj-23254	183	49	revealed	reveal	VERB
brj-23254	183	50	two	two	NUM
brj-23254	183	51	noteworthy	noteworthy	ADJ
brj-23254	183	52	insights	insight	NOUN
brj-23254	183	53	(	(	PUNCT
brj-23254	183	54	fig	fig	NOUN
brj-23254	183	55	.	.	PUNCT
brj-23254	184	1	3	3	NUM
brj-23254	184	2	)	)	PUNCT
brj-23254	184	3	,	,	PUNCT
brj-23254	184	4	in	in	ADP
brj-23254	184	5	which	which	PRON
brj-23254	184	6	d2	d2	PROPN
brj-23254	184	7	consistently	consistently	ADV
brj-23254	184	8	outperformed	outperform	VERB
brj-23254	184	9	d1	d1	PROPN
brj-23254	184	10	across	across	ADP
brj-23254	184	11	both	both	DET
brj-23254	184	12	evaluation	evaluation	NOUN
brj-23254	184	13	methods	method	NOUN
brj-23254	184	14	;	;	PUNCT
brj-23254	184	15	however	however	ADV
brj-23254	184	16	,	,	PUNCT
brj-23254	184	17	the	the	DET
brj-23254	184	18	accuracy	accuracy	NOUN
brj-23254	184	19	associated	associate	VERB
brj-23254	184	20	with	with	ADP
brj-23254	184	21	d2	d2	PROPN
brj-23254	184	22	experienced	experience	VERB
brj-23254	184	23	a	a	DET
brj-23254	184	24	substantial	substantial	ADJ
brj-23254	184	25	decrease	decrease	NOUN
brj-23254	184	26	when	when	SCONJ
brj-23254	184	27	tested	test	VERB
brj-23254	184	28	on	on	ADP
brj-23254	184	29	surplus	surplus	ADJ
brj-23254	184	30	data	datum	NOUN
brj-23254	184	31	,	,	PUNCT
brj-23254	184	32	whereas	whereas	SCONJ
brj-23254	184	33	d1	d1	PROPN
brj-23254	184	34	's	's	PART
brj-23254	184	35	accuracy	accuracy	NOUN
brj-23254	184	36	remained	remain	VERB
brj-23254	184	37	nearly	nearly	ADV
brj-23254	184	38	unchanged	unchanged	ADJ
brj-23254	184	39	.	.	PUNCT
brj-23254	185	1	this	this	PRON
brj-23254	185	2	underlines	underline	VERB
brj-23254	185	3	the	the	DET
brj-23254	185	4	fundamental	fundamental	ADJ
brj-23254	185	5	rule	rule	NOUN
brj-23254	185	6	of	of	ADP
brj-23254	185	7	machine	machine	NOUN
brj-23254	185	8	learning	learning	NOUN
brj-23254	185	9	:	:	PUNCT
brj-23254	185	10	the	the	DET
brj-23254	185	11	robustness	robustness	NOUN
brj-23254	185	12	of	of	ADP
brj-23254	185	13	a	a	DET
brj-23254	185	14	model	model	NOUN
brj-23254	185	15	can	can	AUX
brj-23254	185	16	not	not	PART
brj-23254	185	17	be	be	AUX
brj-23254	185	18	ensured	ensure	VERB
brj-23254	185	19	if	if	SCONJ
brj-23254	185	20	the	the	DET
brj-23254	185	21	same	same	ADJ
brj-23254	185	22	data	datum	NOUN
brj-23254	185	23	are	be	AUX
brj-23254	185	24	used	use	VERB
brj-23254	185	25	for	for	ADP
brj-23254	185	26	training	training	NOUN
brj-23254	185	27	and	and	CCONJ
brj-23254	185	28	testing	testing	NOUN
brj-23254	185	29	.	.	PUNCT
brj-23254	186	1	therefore	therefore	ADV
brj-23254	186	2	,	,	PUNCT
brj-23254	186	3	the	the	DET
brj-23254	186	4	authors	author	NOUN
brj-23254	186	5	used	use	VERB
brj-23254	186	6	d1	d1	PROPN
brj-23254	186	7	in	in	ADP
brj-23254	186	8	all	all	DET
brj-23254	186	9	subsequent	subsequent	ADJ
brj-23254	186	10	evaluations	evaluation	NOUN
brj-23254	186	11	and	and	CCONJ
brj-23254	186	12	analyses	analysis	NOUN
brj-23254	186	13	.	.	PUNCT
brj-23254	187	1	when	when	SCONJ
brj-23254	187	2	the	the	DET
brj-23254	187	3	accuracy	accuracy	NOUN
brj-23254	187	4	for	for	ADP
brj-23254	187	5	each	each	DET
brj-23254	187	6	species	specie	NOUN
brj-23254	187	7	was	be	AUX
brj-23254	187	8	observed	observe	VERB
brj-23254	187	9	,	,	PUNCT
brj-23254	187	10	the	the	DET
brj-23254	187	11	species	specie	NOUN
brj-23254	187	12	with	with	ADP
brj-23254	187	13	the	the	DET
brj-23254	187	14	highest	high	ADJ
brj-23254	187	15	classification	classification	NOUN
brj-23254	187	16	accuracy	accuracy	NOUN
brj-23254	187	17	include	include	VERB
brj-23254	187	18	pourthiaea	pourthiaea	ADJ
brj-23254	187	19	villosa	villosa	NOUN
brj-23254	187	20	(	(	PUNCT
brj-23254	187	21	73	73	NUM
brj-23254	187	22	%	%	NOUN
brj-23254	187	23	)	)	PUNCT
brj-23254	187	24	for	for	ADP
brj-23254	187	25	d1	d1	PROPN
brj-23254	187	26	under	under	ADP
brj-23254	187	27	method	method	NOUN
brj-23254	187	28	e1	e1	PROPN
brj-23254	187	29	,	,	PUNCT
brj-23254	187	30	castanea	castanea	PROPN
brj-23254	187	31	crenata	crenata	PROPN
brj-23254	187	32	and	and	CCONJ
brj-23254	187	33	quercus	quercus	ADJ
brj-23254	187	34	stenophylla	stenophylla	NOUN
brj-23254	187	35	(	(	PUNCT
brj-23254	187	36	100	100	NUM
brj-23254	187	37	%	%	NOUN
brj-23254	187	38	)	)	PUNCT
brj-23254	187	39	for	for	ADP
brj-23254	187	40	d1	d1	PROPN
brj-23254	187	41	under	under	ADP
brj-23254	187	42	method	method	NOUN
brj-23254	187	43	e2	e2	PROPN
brj-23254	187	44	,	,	PUNCT
brj-23254	187	45	daphniphyllum	daphniphyllum	NOUN
brj-23254	187	46	teijsmannii	teijsmannii	NOUN
brj-23254	187	47	(	(	PUNCT
brj-23254	187	48	83	83	NUM
brj-23254	187	49	%	%	NOUN
brj-23254	187	50	)	)	PUNCT
brj-23254	187	51	for	for	ADP
brj-23254	187	52	d2	d2	PROPN
brj-23254	187	53	under	under	ADP
brj-23254	187	54	e1	e1	PROPN
brj-23254	187	55	,	,	PUNCT
brj-23254	187	56	and	and	CCONJ
brj-23254	187	57	daphniphyllum	daphniphyllum	NOUN
brj-23254	187	58	teijsmannii	teijsmannii	NOUN
brj-23254	187	59	(	(	PUNCT
brj-23254	187	60	100	100	NUM
brj-23254	187	61	%	%	NOUN
brj-23254	187	62	)	)	PUNCT
brj-23254	187	63	for	for	ADP
brj-23254	187	64	d2	d2	PROPN
brj-23254	187	65	under	under	ADP
brj-23254	187	66	e2	e2	PROPN
brj-23254	187	67	.	.	PUNCT
brj-23254	188	1	fig	fig	NOUN
brj-23254	188	2	.	.	PUNCT
brj-23254	189	1	3	3	X
brj-23254	189	2	.	.	X
brj-23254	189	3	comparison	comparison	NOUN
brj-23254	189	4	of	of	ADP
brj-23254	189	5	the	the	DET
brj-23254	189	6	accuracy	accuracy	NOUN
brj-23254	189	7	between	between	ADP
brj-23254	189	8	datasets	dataset	NOUN
brj-23254	189	9	d1	d1	PROPN
brj-23254	189	10	and	and	CCONJ
brj-23254	189	11	d2	d2	PROPN
brj-23254	189	12	peer	peer	NOUN
brj-23254	189	13	-	-	PUNCT
brj-23254	189	14	reviewed	review	VERB
brj-23254	189	15	article	article	NOUN
brj-23254	189	16	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	189	17	ma	ma	PROPN
brj-23254	189	18	et	et	PROPN
brj-23254	189	19	al	al	PROPN
brj-23254	189	20	.	.	PROPN
brj-23254	190	1	(	(	PUNCT
brj-23254	190	2	2024	2024	NUM
brj-23254	190	3	)	)	PUNCT
brj-23254	190	4	.	.	PUNCT
brj-23254	191	1	“	"	PUNCT
brj-23254	191	2	wood	wood	NOUN
brj-23254	191	3	i	i	X
brj-23254	191	4	d	d	PROPN
brj-23254	191	5	via	via	ADP
brj-23254	191	6	deep	deep	ADJ
brj-23254	191	7	learning	learning	NOUN
brj-23254	191	8	,	,	PUNCT
brj-23254	191	9	”	"	PUNCT
brj-23254	191	10	bioresources	bioresource	NOUN
brj-23254	191	11	19(3	19(3	NUM
brj-23254	191	12	)	)	PUNCT
brj-23254	191	13	,	,	PUNCT
brj-23254	191	14	4838	4838	NUM
brj-23254	191	15	-	-	SYM
brj-23254	191	16	4851	4851	NUM
brj-23254	191	17	.	.	PUNCT
brj-23254	192	1	4847	4847	NUM
brj-23254	192	2	accuracy	accuracy	NOUN
brj-23254	192	3	comparison	comparison	NOUN
brj-23254	192	4	among	among	ADP
brj-23254	192	5	cnn	cnn	PROPN
brj-23254	192	6	structures	structure	NOUN
brj-23254	192	7	in	in	ADP
brj-23254	192	8	line	line	NOUN
brj-23254	192	9	with	with	ADP
brj-23254	192	10	the	the	DET
brj-23254	192	11	suggestion	suggestion	NOUN
brj-23254	192	12	of	of	ADP
brj-23254	192	13	hafemann	hafemann	NOUN
brj-23254	192	14	et	et	PROPN
brj-23254	192	15	al	al	PROPN
brj-23254	192	16	.	.	PROPN
brj-23254	193	1	(	(	PUNCT
brj-23254	193	2	2014	2014	NUM
brj-23254	193	3	)	)	PUNCT
brj-23254	193	4	,	,	PUNCT
brj-23254	193	5	the	the	DET
brj-23254	193	6	model	model	NOUN
brj-23254	193	7	was	be	AUX
brj-23254	193	8	fine	fine	ADV
brj-23254	193	9	-	-	PUNCT
brj-23254	193	10	tuned	tune	VERB
brj-23254	193	11	based	base	VERB
brj-23254	193	12	on	on	ADP
brj-23254	193	13	vgg16	vgg16	PROPN
brj-23254	193	14	to	to	PART
brj-23254	193	15	compare	compare	VERB
brj-23254	193	16	the	the	DET
brj-23254	193	17	accuracy	accuracy	NOUN
brj-23254	193	18	achieved	achieve	VERB
brj-23254	193	19	with	with	ADP
brj-23254	193	20	and	and	CCONJ
brj-23254	193	21	without	without	ADP
brj-23254	193	22	fine	fine	ADV
brj-23254	193	23	-	-	PUNCT
brj-23254	193	24	tuning	tuning	NOUN
brj-23254	193	25	.	.	PUNCT
brj-23254	194	1	the	the	DET
brj-23254	194	2	results	result	NOUN
brj-23254	194	3	are	be	AUX
brj-23254	194	4	summarized	summarize	VERB
brj-23254	194	5	in	in	ADP
brj-23254	194	6	table	table	NOUN
brj-23254	194	7	4	4	NUM
brj-23254	194	8	.	.	PUNCT
brj-23254	195	1	in	in	ADP
brj-23254	195	2	all	all	DET
brj-23254	195	3	the	the	DET
brj-23254	195	4	instances	instance	NOUN
brj-23254	195	5	,	,	PUNCT
brj-23254	195	6	the	the	DET
brj-23254	195	7	highest	high	ADJ
brj-23254	195	8	accuracy	accuracy	NOUN
brj-23254	195	9	was	be	AUX
brj-23254	195	10	obtained	obtain	VERB
brj-23254	195	11	using	use	VERB
brj-23254	195	12	the	the	DET
brj-23254	195	13	fine	fine	ADV
brj-23254	195	14	-	-	PUNCT
brj-23254	195	15	tuned	tune	VERB
brj-23254	195	16	model	model	NOUN
brj-23254	195	17	.	.	PUNCT
brj-23254	196	1	using	use	VERB
brj-23254	196	2	the	the	DET
brj-23254	196	3	second	second	ADJ
brj-23254	196	4	evaluation	evaluation	NOUN
brj-23254	196	5	method	method	NOUN
brj-23254	196	6	(	(	PUNCT
brj-23254	196	7	e2	e2	PROPN
brj-23254	196	8	)	)	PUNCT
brj-23254	196	9	,	,	PUNCT
brj-23254	196	10	the	the	DET
brj-23254	196	11	fine	fine	ADV
brj-23254	196	12	-	-	PUNCT
brj-23254	196	13	tuned	tune	VERB
brj-23254	196	14	model	model	NOUN
brj-23254	196	15	achieved	achieve	VERB
brj-23254	196	16	a	a	DET
brj-23254	196	17	testing	testing	NOUN
brj-23254	196	18	accuracy	accuracy	NOUN
brj-23254	196	19	of	of	ADP
brj-23254	196	20	72	72	NUM
brj-23254	196	21	%	%	NOUN
brj-23254	196	22	and	and	CCONJ
brj-23254	196	23	surplus	surplus	ADJ
brj-23254	196	24	accuracy	accuracy	NOUN
brj-23254	196	25	of	of	ADP
brj-23254	196	26	71	71	NUM
brj-23254	196	27	%	%	NOUN
brj-23254	196	28	.	.	PUNCT
brj-23254	197	1	in	in	ADP
brj-23254	197	2	machine	machine	NOUN
brj-23254	197	3	learning	learn	VERB
brj-23254	197	4	analysis	analysis	NOUN
brj-23254	197	5	,	,	PUNCT
brj-23254	197	6	especially	especially	ADV
brj-23254	197	7	when	when	SCONJ
brj-23254	197	8	the	the	DET
brj-23254	197	9	internal	internal	ADJ
brj-23254	197	10	mechanisms	mechanism	NOUN
brj-23254	197	11	are	be	AUX
brj-23254	197	12	largely	largely	ADV
brj-23254	197	13	unknown	unknown	ADJ
brj-23254	197	14	—	—	PUNCT
brj-23254	197	15	often	often	ADV
brj-23254	197	16	referred	refer	VERB
brj-23254	197	17	to	to	ADP
brj-23254	197	18	as	as	ADP
brj-23254	197	19	a	a	DET
brj-23254	197	20	"	"	PUNCT
brj-23254	197	21	black	black	ADJ
brj-23254	197	22	box"—the	box"—the	DET
brj-23254	197	23	number	number	NOUN
brj-23254	197	24	of	of	ADP
brj-23254	197	25	samples	sample	NOUN
brj-23254	197	26	or	or	CCONJ
brj-23254	197	27	corpus	corpus	NOUN
brj-23254	197	28	size	size	NOUN
brj-23254	197	29	plays	play	VERB
brj-23254	197	30	a	a	DET
brj-23254	197	31	pivotal	pivotal	ADJ
brj-23254	197	32	role	role	NOUN
brj-23254	197	33	.	.	PUNCT
brj-23254	198	1	this	this	DET
brj-23254	198	2	principle	principle	NOUN
brj-23254	198	3	holds	hold	VERB
brj-23254	198	4	true	true	ADJ
brj-23254	198	5	across	across	ADP
brj-23254	198	6	fields	field	NOUN
brj-23254	198	7	,	,	PUNCT
brj-23254	198	8	but	but	CCONJ
brj-23254	198	9	in	in	ADP
brj-23254	198	10	the	the	DET
brj-23254	198	11	realm	realm	NOUN
brj-23254	198	12	of	of	ADP
brj-23254	198	13	scientific	scientific	ADJ
brj-23254	198	14	data	datum	NOUN
brj-23254	198	15	,	,	PUNCT
brj-23254	198	16	acquiring	acquire	VERB
brj-23254	198	17	a	a	DET
brj-23254	198	18	large	large	ADJ
brj-23254	198	19	-	-	PUNCT
brj-23254	198	20	scale	scale	NOUN
brj-23254	198	21	,	,	PUNCT
brj-23254	198	22	or	or	CCONJ
brj-23254	198	23	"	"	PUNCT
brj-23254	198	24	big	big	ADJ
brj-23254	198	25	data	datum	NOUN
brj-23254	198	26	"	"	PUNCT
brj-23254	198	27	set	set	VERB
brj-23254	198	28	is	be	AUX
brj-23254	198	29	a	a	DET
brj-23254	198	30	hard	hard	ADJ
brj-23254	198	31	task	task	NOUN
brj-23254	198	32	.	.	PUNCT
brj-23254	199	1	considering	consider	VERB
brj-23254	199	2	these	these	DET
brj-23254	199	3	challenges	challenge	NOUN
brj-23254	199	4	,	,	PUNCT
brj-23254	199	5	an	an	DET
brj-23254	199	6	achievable	achievable	ADJ
brj-23254	199	7	sample	sample	NOUN
brj-23254	199	8	size	size	NOUN
brj-23254	199	9	of	of	ADP
brj-23254	199	10	one	one	NUM
brj-23254	199	11	thousand	thousand	NUM
brj-23254	199	12	specimens	specimen	NOUN
brj-23254	199	13	was	be	AUX
brj-23254	199	14	used	use	VERB
brj-23254	199	15	for	for	ADP
brj-23254	199	16	model	model	NOUN
brj-23254	199	17	construction	construction	NOUN
brj-23254	199	18	.	.	PUNCT
brj-23254	200	1	this	this	PRON
brj-23254	200	2	may	may	AUX
brj-23254	200	3	seem	seem	VERB
brj-23254	200	4	modest	modest	ADJ
brj-23254	200	5	compared	compare	VERB
brj-23254	200	6	to	to	ADP
brj-23254	200	7	models	model	NOUN
brj-23254	200	8	trained	train	VERB
brj-23254	200	9	on	on	ADP
brj-23254	200	10	larger	large	ADJ
brj-23254	200	11	databases	database	NOUN
brj-23254	200	12	,	,	PUNCT
brj-23254	200	13	but	but	CCONJ
brj-23254	200	14	is	be	AUX
brj-23254	200	15	sufficient	sufficient	ADJ
brj-23254	200	16	for	for	ADP
brj-23254	200	17	the	the	DET
brj-23254	200	18	level	level	NOUN
brj-23254	200	19	of	of	ADP
brj-23254	200	20	complexity	complexity	NOUN
brj-23254	200	21	inherent	inherent	ADJ
brj-23254	200	22	in	in	ADP
brj-23254	200	23	wood	wood	NOUN
brj-23254	200	24	science	science	NOUN
brj-23254	200	25	and	and	CCONJ
brj-23254	200	26	for	for	ADP
brj-23254	200	27	making	make	VERB
brj-23254	200	28	reliable	reliable	ADJ
brj-23254	200	29	predictions	prediction	NOUN
brj-23254	200	30	.	.	PUNCT
brj-23254	201	1	transparency	transparency	NOUN
brj-23254	201	2	is	be	AUX
brj-23254	201	3	of	of	ADP
brj-23254	201	4	paramount	paramount	ADJ
brj-23254	201	5	importance	importance	NOUN
brj-23254	201	6	in	in	ADP
brj-23254	201	7	this	this	DET
brj-23254	201	8	approach	approach	NOUN
brj-23254	201	9	.	.	PUNCT
brj-23254	202	1	accuracy	accuracy	NOUN
brj-23254	202	2	for	for	ADP
brj-23254	202	3	genes	gene	NOUN
brj-23254	202	4	and	and	CCONJ
brj-23254	202	5	family	family	NOUN
brj-23254	202	6	prediction	prediction	NOUN
brj-23254	202	7	an	an	DET
brj-23254	202	8	additional	additional	ADJ
brj-23254	202	9	cnn	cnn	NOUN
brj-23254	202	10	model	model	NOUN
brj-23254	202	11	was	be	AUX
brj-23254	202	12	developed	develop	VERB
brj-23254	202	13	to	to	PART
brj-23254	202	14	predict	predict	VERB
brj-23254	202	15	the	the	DET
brj-23254	202	16	genera	genera	NOUN
brj-23254	202	17	and	and	CCONJ
brj-23254	202	18	families	family	NOUN
brj-23254	202	19	of	of	ADP
brj-23254	202	20	the	the	DET
brj-23254	202	21	wood	wood	NOUN
brj-23254	202	22	samples	sample	NOUN
brj-23254	202	23	.	.	PUNCT
brj-23254	203	1	as	as	SCONJ
brj-23254	203	2	shown	show	VERB
brj-23254	203	3	in	in	ADP
brj-23254	203	4	table	table	NOUN
brj-23254	203	5	1	1	NUM
brj-23254	203	6	,	,	PUNCT
brj-23254	203	7	the	the	DET
brj-23254	203	8	50	50	NUM
brj-23254	203	9	wood	wood	NOUN
brj-23254	203	10	species	specie	NOUN
brj-23254	203	11	investigated	investigate	VERB
brj-23254	203	12	in	in	ADP
brj-23254	203	13	this	this	DET
brj-23254	203	14	study	study	NOUN
brj-23254	203	15	spanned	span	VERB
brj-23254	203	16	39	39	NUM
brj-23254	203	17	genera	genera	NOUN
brj-23254	203	18	and	and	CCONJ
brj-23254	203	19	29	29	NUM
brj-23254	203	20	families	family	NOUN
brj-23254	203	21	,	,	PUNCT
brj-23254	203	22	and	and	CCONJ
brj-23254	203	23	the	the	DET
brj-23254	203	24	corresponding	corresponding	ADJ
brj-23254	203	25	accurate	accurate	ADJ
brj-23254	203	26	results	result	NOUN
brj-23254	203	27	are	be	AUX
brj-23254	203	28	outlined	outline	VERB
brj-23254	203	29	in	in	ADP
brj-23254	203	30	table	table	NOUN
brj-23254	203	31	4	4	NUM
brj-23254	203	32	.	.	PUNCT
brj-23254	204	1	interestingly	interestingly	ADV
brj-23254	204	2	,	,	PUNCT
brj-23254	204	3	the	the	DET
brj-23254	204	4	accuracy	accuracy	NOUN
brj-23254	204	5	of	of	ADP
brj-23254	204	6	the	the	DET
brj-23254	204	7	fine	fine	ADV
brj-23254	204	8	-	-	PUNCT
brj-23254	204	9	tuned	tune	VERB
brj-23254	204	10	model	model	NOUN
brj-23254	204	11	using	use	VERB
brj-23254	204	12	the	the	DET
brj-23254	204	13	e2	e2	PROPN
brj-23254	204	14	evaluation	evaluation	NOUN
brj-23254	204	15	method	method	NOUN
brj-23254	204	16	did	do	AUX
brj-23254	204	17	not	not	PART
brj-23254	204	18	improve	improve	VERB
brj-23254	204	19	significantly	significantly	ADV
brj-23254	204	20	.	.	PUNCT
brj-23254	205	1	when	when	SCONJ
brj-23254	205	2	the	the	DET
brj-23254	205	3	species	specie	NOUN
brj-23254	205	4	were	be	AUX
brj-23254	205	5	grouped	group	VERB
brj-23254	205	6	by	by	ADP
brj-23254	205	7	genus	genus	NOUN
brj-23254	205	8	and	and	CCONJ
brj-23254	205	9	family	family	NOUN
brj-23254	205	10	,	,	PUNCT
brj-23254	205	11	the	the	DET
brj-23254	205	12	rate	rate	NOUN
brj-23254	205	13	of	of	ADP
brj-23254	205	14	correct	correct	ADJ
brj-23254	205	15	identification	identification	NOUN
brj-23254	205	16	increased	increase	VERB
brj-23254	205	17	in	in	ADP
brj-23254	205	18	some	some	DET
brj-23254	205	19	instances	instance	NOUN
brj-23254	205	20	,	,	PUNCT
brj-23254	205	21	decreased	decrease	VERB
brj-23254	205	22	in	in	ADP
brj-23254	205	23	others	other	NOUN
brj-23254	205	24	,	,	PUNCT
brj-23254	205	25	and	and	CCONJ
brj-23254	205	26	showed	show	VERB
brj-23254	205	27	no	no	DET
brj-23254	205	28	change	change	NOUN
brj-23254	205	29	on	on	ADP
brj-23254	205	30	average	average	ADJ
brj-23254	205	31	.	.	PUNCT
brj-23254	206	1	notably	notably	ADV
brj-23254	206	2	,	,	PUNCT
brj-23254	206	3	the	the	DET
brj-23254	206	4	rate	rate	NOUN
brj-23254	206	5	of	of	ADP
brj-23254	206	6	correct	correct	ADJ
brj-23254	206	7	identification	identification	NOUN
brj-23254	206	8	increased	increase	VERB
brj-23254	206	9	significantly	significantly	ADV
brj-23254	206	10	for	for	ADP
brj-23254	206	11	the	the	DET
brj-23254	206	12	ring	ring	NOUN
brj-23254	206	13	-	-	PUNCT
brj-23254	206	14	porous	porous	ADJ
brj-23254	206	15	species	specie	NOUN
brj-23254	206	16	.	.	PUNCT
brj-23254	207	1	this	this	PRON
brj-23254	207	2	likely	likely	ADV
brj-23254	207	3	arises	arise	VERB
brj-23254	207	4	from	from	ADP
brj-23254	207	5	the	the	DET
brj-23254	207	6	fact	fact	NOUN
brj-23254	207	7	that	that	SCONJ
brj-23254	207	8	ring	ring	NOUN
brj-23254	207	9	-	-	PUNCT
brj-23254	207	10	porous	porous	ADJ
brj-23254	207	11	species	specie	NOUN
brj-23254	207	12	within	within	ADP
brj-23254	207	13	a	a	DET
brj-23254	207	14	given	give	VERB
brj-23254	207	15	genus	genus	NOUN
brj-23254	207	16	or	or	CCONJ
brj-23254	207	17	family	family	NOUN
brj-23254	207	18	share	share	VERB
brj-23254	207	19	similar	similar	ADJ
brj-23254	207	20	characteristics	characteristic	NOUN
brj-23254	207	21	,	,	PUNCT
brj-23254	207	22	thus	thus	ADV
brj-23254	207	23	exhibiting	exhibit	VERB
brj-23254	207	24	clear	clear	ADJ
brj-23254	207	25	distinctions	distinction	NOUN
brj-23254	207	26	between	between	ADP
brj-23254	207	27	different	different	ADJ
brj-23254	207	28	classes	class	NOUN
brj-23254	207	29	.	.	PUNCT
brj-23254	208	1	effect	effect	NOUN
brj-23254	208	2	of	of	ADP
brj-23254	208	3	original	original	ADJ
brj-23254	208	4	image	image	NOUN
brj-23254	208	5	dimensionality	dimensionality	NOUN
brj-23254	208	6	on	on	ADP
brj-23254	208	7	accuracy	accuracy	NOUN
brj-23254	208	8	to	to	PART
brj-23254	208	9	assess	assess	VERB
brj-23254	208	10	the	the	DET
brj-23254	208	11	impact	impact	NOUN
brj-23254	208	12	of	of	ADP
brj-23254	208	13	the	the	DET
brj-23254	208	14	original	original	ADJ
brj-23254	208	15	image	image	NOUN
brj-23254	208	16	size	size	NOUN
brj-23254	208	17	on	on	ADP
brj-23254	208	18	the	the	DET
brj-23254	208	19	accuracy	accuracy	NOUN
brj-23254	208	20	of	of	ADP
brj-23254	208	21	wood	wood	NOUN
brj-23254	208	22	species	specie	NOUN
brj-23254	208	23	identification	identification	NOUN
brj-23254	208	24	,	,	PUNCT
brj-23254	208	25	the	the	DET
brj-23254	208	26	authors	author	NOUN
brj-23254	208	27	assembled	assemble	VERB
brj-23254	208	28	a	a	DET
brj-23254	208	29	dataset	dataset	NOUN
brj-23254	208	30	of	of	ADP
brj-23254	208	31	images	image	NOUN
brj-23254	208	32	from	from	ADP
brj-23254	208	33	10	10	NUM
brj-23254	208	34	species	specie	NOUN
brj-23254	208	35	,	,	PUNCT
brj-23254	208	36	each	each	PRON
brj-23254	208	37	of	of	ADP
brj-23254	208	38	which	which	PRON
brj-23254	208	39	had	have	VERB
brj-23254	208	40	the	the	DET
brj-23254	208	41	same	same	ADJ
brj-23254	208	42	size	size	NOUN
brj-23254	208	43	(	(	PUNCT
brj-23254	208	44	3,840	3,840	NUM
brj-23254	208	45	×	×	NOUN
brj-23254	208	46	3,720	3,720	NUM
brj-23254	208	47	pixels	pixel	NOUN
brj-23254	208	48	)	)	PUNCT
brj-23254	208	49	.	.	PUNCT
brj-23254	209	1	the	the	DET
brj-23254	209	2	dataset	dataset	NOUN
brj-23254	209	3	was	be	AUX
brj-23254	209	4	processed	process	VERB
brj-23254	209	5	according	accord	VERB
brj-23254	209	6	to	to	ADP
brj-23254	209	7	the	the	DET
brj-23254	209	8	methodology	methodology	NOUN
brj-23254	209	9	depicted	depict	VERB
brj-23254	209	10	in	in	ADP
brj-23254	209	11	figs	fig	NOUN
brj-23254	209	12	.	.	PUNCT
brj-23254	210	1	1	1	NUM
brj-23254	210	2	to	to	PART
brj-23254	210	3	3	3	NUM
brj-23254	210	4	.	.	PUNCT
brj-23254	211	1	an	an	DET
brj-23254	211	2	additional	additional	ADJ
brj-23254	211	3	dataset	dataset	NOUN
brj-23254	211	4	corresponding	corresponding	NOUN
brj-23254	211	5	to	to	ADP
brj-23254	211	6	the	the	DET
brj-23254	211	7	same	same	ADJ
brj-23254	211	8	species	specie	NOUN
brj-23254	211	9	was	be	AUX
brj-23254	211	10	curated	curate	VERB
brj-23254	211	11	,	,	PUNCT
brj-23254	211	12	albeit	albeit	SCONJ
brj-23254	211	13	with	with	ADP
brj-23254	211	14	diverse	diverse	ADJ
brj-23254	211	15	image	image	NOUN
brj-23254	211	16	sizes	size	NOUN
brj-23254	211	17	.	.	PUNCT
brj-23254	212	1	it	it	PRON
brj-23254	212	2	should	should	AUX
brj-23254	212	3	be	be	AUX
brj-23254	212	4	noted	note	VERB
brj-23254	212	5	that	that	SCONJ
brj-23254	212	6	standardizing	standardize	VERB
brj-23254	212	7	the	the	DET
brj-23254	212	8	microscopic	microscopic	ADJ
brj-23254	212	9	magnification	magnification	NOUN
brj-23254	212	10	across	across	ADP
brj-23254	212	11	all	all	DET
brj-23254	212	12	images	image	NOUN
brj-23254	212	13	is	be	AUX
brj-23254	212	14	challenging	challenge	VERB
brj-23254	212	15	because	because	SCONJ
brj-23254	212	16	many	many	ADJ
brj-23254	212	17	images	image	NOUN
brj-23254	212	18	are	be	AUX
brj-23254	212	19	collected	collect	VERB
brj-23254	212	20	at	at	ADP
brj-23254	212	21	undisclosed	undisclosed	ADJ
brj-23254	212	22	magnifications	magnification	NOUN
brj-23254	212	23	.	.	PUNCT
brj-23254	213	1	as	as	SCONJ
brj-23254	213	2	anticipated	anticipate	VERB
brj-23254	213	3	,	,	PUNCT
brj-23254	213	4	the	the	DET
brj-23254	213	5	fine	fine	ADV
brj-23254	213	6	-	-	PUNCT
brj-23254	213	7	tuned	tune	VERB
brj-23254	213	8	model	model	NOUN
brj-23254	213	9	under	under	ADP
brj-23254	213	10	the	the	DET
brj-23254	213	11	e2	e2	PROPN
brj-23254	213	12	evaluation	evaluation	NOUN
brj-23254	213	13	strategy	strategy	NOUN
brj-23254	213	14	yielded	yield	VERB
brj-23254	213	15	a	a	DET
brj-23254	213	16	higher	high	ADJ
brj-23254	213	17	accuracy	accuracy	NOUN
brj-23254	213	18	(	(	PUNCT
brj-23254	213	19	94	94	NUM
brj-23254	213	20	%	%	NOUN
brj-23254	213	21	for	for	ADP
brj-23254	213	22	the	the	DET
brj-23254	213	23	test	test	NOUN
brj-23254	213	24	set	set	VERB
brj-23254	213	25	and	and	CCONJ
brj-23254	213	26	83	83	NUM
brj-23254	213	27	%	%	NOUN
brj-23254	213	28	for	for	ADP
brj-23254	213	29	the	the	DET
brj-23254	213	30	surplus	surplus	NOUN
brj-23254	213	31	set	set	NOUN
brj-23254	213	32	)	)	PUNCT
brj-23254	213	33	when	when	SCONJ
brj-23254	213	34	working	work	VERB
brj-23254	213	35	with	with	ADP
brj-23254	213	36	standardized	standardized	ADJ
brj-23254	213	37	image	image	NOUN
brj-23254	213	38	settings	setting	NOUN
brj-23254	213	39	compared	compare	VERB
brj-23254	213	40	with	with	ADP
brj-23254	213	41	those	those	PRON
brj-23254	213	42	with	with	ADP
brj-23254	213	43	varied	varied	ADJ
brj-23254	213	44	dimensions	dimension	NOUN
brj-23254	213	45	(	(	PUNCT
brj-23254	213	46	86	86	NUM
brj-23254	213	47	%	%	NOUN
brj-23254	213	48	for	for	ADP
brj-23254	213	49	the	the	DET
brj-23254	213	50	test	test	NOUN
brj-23254	213	51	set	set	VERB
brj-23254	213	52	and	and	CCONJ
brj-23254	213	53	75	75	NUM
brj-23254	213	54	%	%	NOUN
brj-23254	213	55	for	for	ADP
brj-23254	213	56	the	the	DET
brj-23254	213	57	surplus	surplus	NOUN
brj-23254	213	58	set	set	NOUN
brj-23254	213	59	)	)	PUNCT
brj-23254	213	60	.	.	PUNCT
brj-23254	214	1	the	the	DET
brj-23254	214	2	attained	attain	VERB
brj-23254	214	3	accuracy	accuracy	NOUN
brj-23254	214	4	of	of	ADP
brj-23254	214	5	94	94	NUM
brj-23254	214	6	%	%	NOUN
brj-23254	214	7	in	in	ADP
brj-23254	214	8	this	this	DET
brj-23254	214	9	study	study	NOUN
brj-23254	214	10	mirrors	mirror	NOUN
brj-23254	214	11	the	the	DET
brj-23254	214	12	findings	finding	NOUN
brj-23254	214	13	reported	report	VERB
brj-23254	214	14	by	by	ADP
brj-23254	214	15	hafemann	hafemann	PROPN
brj-23254	214	16	et	et	PROPN
brj-23254	214	17	al	al	PROPN
brj-23254	214	18	.	.	PROPN
brj-23254	215	1	(	(	PUNCT
brj-23254	215	2	2014	2014	NUM
brj-23254	215	3	)	)	PUNCT
brj-23254	215	4	,	,	PUNCT
brj-23254	215	5	where	where	SCONJ
brj-23254	215	6	97	97	NUM
brj-23254	215	7	%	%	NOUN
brj-23254	215	8	accuracy	accuracy	NOUN
brj-23254	215	9	was	be	AUX
brj-23254	215	10	used	use	VERB
brj-23254	215	11	for	for	ADP
brj-23254	215	12	classification	classification	NOUN
brj-23254	215	13	across	across	ADP
brj-23254	215	14	112	112	NUM
brj-23254	215	15	species	specie	NOUN
brj-23254	215	16	,	,	PUNCT
brj-23254	215	17	each	each	PRON
brj-23254	215	18	represented	represent	VERB
brj-23254	215	19	by	by	ADP
brj-23254	215	20	20	20	NUM
brj-23254	215	21	images	image	NOUN
brj-23254	215	22	.	.	PUNCT
brj-23254	216	1	consequently	consequently	ADV
brj-23254	216	2	,	,	PUNCT
brj-23254	216	3	these	these	DET
brj-23254	216	4	accuracy	accuracy	NOUN
brj-23254	216	5	results	result	NOUN
brj-23254	216	6	demonstrated	demonstrate	VERB
brj-23254	216	7	a	a	DET
brj-23254	216	8	reasonably	reasonably	ADV
brj-23254	216	9	high	high	ADJ
brj-23254	216	10	level	level	NOUN
brj-23254	216	11	of	of	ADP
brj-23254	216	12	performance	performance	NOUN
brj-23254	216	13	,	,	PUNCT
brj-23254	216	14	even	even	ADV
brj-23254	216	15	when	when	SCONJ
brj-23254	216	16	there	there	PRON
brj-23254	216	17	was	be	VERB
brj-23254	216	18	considerable	considerable	ADJ
brj-23254	216	19	size	size	NOUN
brj-23254	216	20	variability	variability	NOUN
brj-23254	216	21	among	among	ADP
brj-23254	216	22	the	the	DET
brj-23254	216	23	original	original	ADJ
brj-23254	216	24	images	image	NOUN
brj-23254	216	25	.	.	PUNCT
brj-23254	217	1	estimation	estimation	NOUN
brj-23254	217	2	of	of	ADP
brj-23254	217	3	practical	practical	ADJ
brj-23254	217	4	accuracy	accuracy	NOUN
brj-23254	217	5	to	to	PART
brj-23254	217	6	gauge	gauge	VERB
brj-23254	217	7	the	the	DET
brj-23254	217	8	practical	practical	ADJ
brj-23254	217	9	accuracy	accuracy	NOUN
brj-23254	217	10	of	of	ADP
brj-23254	217	11	wood	wood	NOUN
brj-23254	217	12	species	specie	NOUN
brj-23254	217	13	identification	identification	NOUN
brj-23254	217	14	from	from	ADP
brj-23254	217	15	microscopic	microscopic	ADJ
brj-23254	217	16	images	image	NOUN
brj-23254	217	17	via	via	ADP
brj-23254	217	18	a	a	DET
brj-23254	217	19	cnn	cnn	PROPN
brj-23254	217	20	,	,	PUNCT
brj-23254	217	21	the	the	DET
brj-23254	217	22	impact	impact	NOUN
brj-23254	217	23	of	of	ADP
brj-23254	217	24	various	various	ADJ
brj-23254	217	25	factors	factor	NOUN
brj-23254	217	26	,	,	PUNCT
brj-23254	217	27	including	include	VERB
brj-23254	217	28	the	the	DET
brj-23254	217	29	evaluation	evaluation	NOUN
brj-23254	217	30	method	method	NOUN
brj-23254	217	31	,	,	PUNCT
brj-23254	217	32	data	datum	NOUN
brj-23254	217	33	allocation	allocation	NOUN
brj-23254	217	34	,	,	PUNCT
brj-23254	217	35	parameter	parameter	NOUN
brj-23254	217	36	tuning	tuning	NOUN
brj-23254	217	37	,	,	PUNCT
brj-23254	217	38	classification	classification	NOUN
brj-23254	217	39	target	target	NOUN
brj-23254	217	40	,	,	PUNCT
brj-23254	217	41	and	and	CCONJ
brj-23254	217	42	image	image	NOUN
brj-23254	217	43	dimensions	dimension	NOUN
brj-23254	217	44	,	,	PUNCT
brj-23254	217	45	was	be	AUX
brj-23254	217	46	assessed	assess	VERB
brj-23254	217	47	.	.	PUNCT
brj-23254	218	1	surplus	surplus	NOUN
brj-23254	218	2	data	datum	NOUN
brj-23254	218	3	were	be	AUX
brj-23254	218	4	compiled	compile	VERB
brj-23254	218	5	to	to	PART
brj-23254	218	6	examine	examine	VERB
brj-23254	218	7	the	the	DET
brj-23254	218	8	robustness	robustness	NOUN
brj-23254	218	9	of	of	ADP
brj-23254	218	10	the	the	DET
brj-23254	218	11	model	model	NOUN
brj-23254	218	12	.	.	PUNCT
brj-23254	219	1	peer	peer	NOUN
brj-23254	219	2	-	-	PUNCT
brj-23254	219	3	reviewed	review	VERB
brj-23254	219	4	article	article	NOUN
brj-23254	219	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	219	6	ma	ma	PROPN
brj-23254	219	7	et	et	PROPN
brj-23254	219	8	al	al	PROPN
brj-23254	219	9	.	.	PROPN
brj-23254	220	1	(	(	PUNCT
brj-23254	220	2	2024	2024	NUM
brj-23254	220	3	)	)	PUNCT
brj-23254	220	4	.	.	PUNCT
brj-23254	221	1	“	"	PUNCT
brj-23254	221	2	wood	wood	NOUN
brj-23254	221	3	i	i	X
brj-23254	221	4	d	d	PROPN
brj-23254	221	5	via	via	ADP
brj-23254	221	6	deep	deep	ADJ
brj-23254	221	7	learning	learning	NOUN
brj-23254	221	8	,	,	PUNCT
brj-23254	221	9	”	"	PUNCT
brj-23254	221	10	bioresources	bioresource	NOUN
brj-23254	221	11	19(3	19(3	NUM
brj-23254	221	12	)	)	PUNCT
brj-23254	221	13	,	,	PUNCT
brj-23254	221	14	4838	4838	NUM
brj-23254	221	15	-	-	SYM
brj-23254	221	16	4851	4851	NUM
brj-23254	221	17	.	.	PUNCT
brj-23254	222	1	4848	4848	NUM
brj-23254	222	2	table	table	NOUN
brj-23254	222	3	4	4	NUM
brj-23254	222	4	.	.	PUNCT
brj-23254	222	5	accuracy	accuracy	NOUN
brj-23254	222	6	comparison	comparison	NOUN
brj-23254	222	7	among	among	ADP
brj-23254	222	8	cnn	cnn	PROPN
brj-23254	222	9	structures	structure	NOUN
brj-23254	222	10	*	*	SYM
brj-23254	222	11	1	1	NUM
brj-23254	222	12	original	original	ADJ
brj-23254	222	13	images	image	NOUN
brj-23254	222	14	of	of	ADP
brj-23254	222	15	3,840	3,840	NUM
brj-23254	222	16	×	×	NOUN
brj-23254	222	17	3,072	3,072	NUM
brj-23254	222	18	pixels	pixel	NOUN
brj-23254	222	19	,	,	PUNCT
brj-23254	222	20	3,200	3,200	NUM
brj-23254	222	21	×	×	NOUN
brj-23254	222	22	2,560	2,560	NUM
brj-23254	222	23	pixels	pixel	NOUN
brj-23254	222	24	,	,	PUNCT
brj-23254	222	25	3,008	3,008	NUM
brj-23254	222	26	×	×	NOUN
brj-23254	222	27	2,000	2,000	NUM
brj-23254	222	28	pixels	pixel	NOUN
brj-23254	222	29	,	,	PUNCT
brj-23254	222	30	1,360	1,360	NUM
brj-23254	222	31	×	×	NOUN
brj-23254	222	32	1,024	1,024	NUM
brj-23254	222	33	pixels	pixel	NOUN
brj-23254	222	34	were	be	AUX
brj-23254	222	35	used	use	VERB
brj-23254	222	36	.	.	PUNCT
brj-23254	223	1	*	*	PUNCT
brj-23254	223	2	2	2	NUM
brj-23254	223	3	only	only	ADV
brj-23254	223	4	original	original	ADJ
brj-23254	223	5	images	image	NOUN
brj-23254	223	6	of	of	ADP
brj-23254	223	7	3,840	3,840	NUM
brj-23254	223	8	×	×	NOUN
brj-23254	223	9	3,072	3,072	NUM
brj-23254	223	10	pixels	pixel	NOUN
brj-23254	223	11	were	be	AUX
brj-23254	223	12	used	use	VERB
brj-23254	223	13	.	.	PUNCT
brj-23254	224	1	dataset	dataset	VERB
brj-23254	224	2	the	the	DET
brj-23254	224	3	number	number	NOUN
brj-23254	224	4	of	of	ADP
brj-23254	224	5	classes	class	NOUN
brj-23254	224	6	pixel	pixel	VERB
brj-23254	224	7	of	of	ADP
brj-23254	224	8	original	original	ADJ
brj-23254	224	9	image	image	NOUN
brj-23254	224	10	evaluation	evaluation	NOUN
brj-23254	224	11	model	model	NOUN
brj-23254	224	12	accuracy	accuracy	NOUN
brj-23254	224	13	(	(	PUNCT
brj-23254	224	14	%	%	INTJ
brj-23254	224	15	)	)	PUNCT
brj-23254	224	16	test	test	NOUN
brj-23254	224	17	set	set	VERB
brj-23254	224	18	surplus	surplus	NOUN
brj-23254	224	19	set	set	VERB
brj-23254	224	20	d1	d1	NOUN
brj-23254	224	21	-	-	PUNCT
brj-23254	224	22	divided	divide	VERB
brj-23254	224	23	50	50	NUM
brj-23254	224	24	(	(	PUNCT
brj-23254	224	25	species	specie	NOUN
brj-23254	224	26	)	)	PUNCT
brj-23254	224	27	4	4	NUM
brj-23254	224	28	kinds*1	kinds*1	NOUN
brj-23254	224	29	e1	e1	NOUN
brj-23254	224	30	-	-	PUNCT
brj-23254	224	31	patch	patch	NOUN
brj-23254	224	32	vgg16	vgg16	NOUN
brj-23254	224	33	(	(	PUNCT
brj-23254	224	34	fine	fine	ADV
brj-23254	224	35	-	-	PUNCT
brj-23254	224	36	tuning	tuning	NOUN
brj-23254	224	37	)	)	PUNCT
brj-23254	224	38	51	51	NUM
brj-23254	224	39	51	51	NUM
brj-23254	224	40	hafemann	hafemann	NOUN
brj-23254	224	41	et	et	PROPN
brj-23254	224	42	al	al	PROPN
brj-23254	224	43	.	.	PROPN
brj-23254	225	1	(	(	PUNCT
brj-23254	225	2	2014	2014	NUM
brj-23254	225	3	)	)	PUNCT
brj-23254	225	4	28	28	NUM
brj-23254	225	5	30	30	NUM
brj-23254	225	6	e2	e2	NOUN
brj-23254	225	7	-	-	PUNCT
brj-23254	225	8	image	image	NOUN
brj-23254	225	9	vgg16	vgg16	NOUN
brj-23254	225	10	(	(	PUNCT
brj-23254	225	11	fine	fine	ADV
brj-23254	225	12	-	-	PUNCT
brj-23254	225	13	tuning	tuning	NOUN
brj-23254	225	14	)	)	PUNCT
brj-23254	225	15	72	72	NUM
brj-23254	225	16	71	71	NUM
brj-23254	225	17	hafemann	hafemann	NOUN
brj-23254	225	18	et	et	PROPN
brj-23254	225	19	al	al	PROPN
brj-23254	225	20	.	.	PROPN
brj-23254	226	1	(	(	PUNCT
brj-23254	226	2	2014	2014	NUM
brj-23254	226	3	)	)	PUNCT
brj-23254	227	1	44	44	NUM
brj-23254	227	2	45	45	NUM
brj-23254	227	3	39	39	NUM
brj-23254	227	4	(	(	PUNCT
brj-23254	227	5	genus	genus	NOUN
brj-23254	227	6	)	)	PUNCT
brj-23254	227	7	4	4	NUM
brj-23254	227	8	kinds*1	kinds*1	NOUN
brj-23254	227	9	e1	e1	NOUN
brj-23254	227	10	-	-	PUNCT
brj-23254	227	11	patch	patch	NOUN
brj-23254	227	12	vgg16	vgg16	NOUN
brj-23254	227	13	(	(	PUNCT
brj-23254	227	14	fine	fine	ADV
brj-23254	227	15	-	-	PUNCT
brj-23254	227	16	tuning	tuning	NOUN
brj-23254	227	17	)	)	PUNCT
brj-23254	227	18	56	56	NUM
brj-23254	227	19	45	45	NUM
brj-23254	227	20	hafemann	hafemann	NOUN
brj-23254	227	21	et	et	PROPN
brj-23254	227	22	al	al	PROPN
brj-23254	227	23	.	.	PROPN
brj-23254	228	1	(	(	PUNCT
brj-23254	228	2	2014	2014	NUM
brj-23254	228	3	)	)	PUNCT
brj-23254	228	4	35	35	NUM
brj-23254	228	5	28	28	NUM
brj-23254	228	6	e2	e2	NOUN
brj-23254	228	7	-	-	PUNCT
brj-23254	228	8	image	image	NOUN
brj-23254	228	9	vgg16	vgg16	NOUN
brj-23254	228	10	(	(	PUNCT
brj-23254	228	11	fine	fine	ADV
brj-23254	228	12	-	-	PUNCT
brj-23254	228	13	tuning	tuning	NOUN
brj-23254	228	14	)	)	PUNCT
brj-23254	228	15	76	76	NUM
brj-23254	228	16	64	64	NUM
brj-23254	228	17	hafemann	hafemann	NOUN
brj-23254	228	18	et	et	NOUN
brj-23254	228	19	al.(2014	al.(2014	PROPN
brj-23254	228	20	)	)	PUNCT
brj-23254	228	21	54	54	NUM
brj-23254	228	22	44	44	NUM
brj-23254	228	23	29	29	NUM
brj-23254	228	24	(	(	PUNCT
brj-23254	228	25	family	family	NOUN
brj-23254	228	26	)	)	PUNCT
brj-23254	228	27	4	4	NUM
brj-23254	228	28	kinds*1	kinds*1	NOUN
brj-23254	228	29	e1	e1	NOUN
brj-23254	228	30	-	-	PUNCT
brj-23254	228	31	patch	patch	NOUN
brj-23254	228	32	vgg16	vgg16	NOUN
brj-23254	228	33	(	(	PUNCT
brj-23254	228	34	fine	fine	ADV
brj-23254	228	35	-	-	PUNCT
brj-23254	228	36	tuning	tuning	NOUN
brj-23254	228	37	)	)	PUNCT
brj-23254	228	38	55	55	NUM
brj-23254	228	39	45	45	NUM
brj-23254	228	40	hafemann	hafemann	NOUN
brj-23254	228	41	et	et	PROPN
brj-23254	228	42	al	al	PROPN
brj-23254	228	43	.	.	PROPN
brj-23254	229	1	(	(	PUNCT
brj-23254	229	2	2014	2014	NUM
brj-23254	229	3	)	)	PUNCT
brj-23254	229	4	29	29	NUM
brj-23254	229	5	21	21	NUM
brj-23254	229	6	e2	e2	NOUN
brj-23254	229	7	-	-	PUNCT
brj-23254	229	8	image	image	NOUN
brj-23254	229	9	vgg16	vgg16	NOUN
brj-23254	229	10	(	(	PUNCT
brj-23254	229	11	fine	fine	ADV
brj-23254	229	12	-	-	PUNCT
brj-23254	229	13	tuning	tuning	NOUN
brj-23254	229	14	)	)	PUNCT
brj-23254	229	15	78	78	NUM
brj-23254	229	16	64	64	NUM
brj-23254	229	17	hafemann	hafemann	NOUN
brj-23254	229	18	et	et	PROPN
brj-23254	229	19	al	al	PROPN
brj-23254	229	20	.	.	PROPN
brj-23254	230	1	(	(	PUNCT
brj-23254	230	2	2014	2014	NUM
brj-23254	230	3	)	)	PUNCT
brj-23254	230	4	43	43	NUM
brj-23254	231	1	31	31	NUM
brj-23254	231	2	10	10	NUM
brj-23254	231	3	(	(	PUNCT
brj-23254	231	4	species	specie	NOUN
brj-23254	231	5	)	)	PUNCT
brj-23254	231	6	4	4	NUM
brj-23254	231	7	kinds*1	kinds*1	NOUN
brj-23254	231	8	e1	e1	NOUN
brj-23254	231	9	-	-	PUNCT
brj-23254	231	10	patch	patch	NOUN
brj-23254	231	11	vgg16	vgg16	NOUN
brj-23254	231	12	(	(	PUNCT
brj-23254	231	13	fine	fine	ADV
brj-23254	231	14	-	-	PUNCT
brj-23254	231	15	tuning	tuning	NOUN
brj-23254	231	16	)	)	PUNCT
brj-23254	231	17	70	70	NUM
brj-23254	231	18	64	64	NUM
brj-23254	231	19	hafemann	hafemann	NOUN
brj-23254	231	20	et	et	PROPN
brj-23254	231	21	al	al	PROPN
brj-23254	231	22	.	.	PROPN
brj-23254	232	1	(	(	PUNCT
brj-23254	232	2	2014	2014	NUM
brj-23254	232	3	)	)	PUNCT
brj-23254	232	4	47	47	NUM
brj-23254	232	5	43	43	NUM
brj-23254	232	6	e2	e2	NOUN
brj-23254	232	7	-	-	PUNCT
brj-23254	232	8	image	image	NOUN
brj-23254	232	9	vgg16	vgg16	NOUN
brj-23254	232	10	(	(	PUNCT
brj-23254	232	11	fine	fine	ADV
brj-23254	232	12	-	-	PUNCT
brj-23254	232	13	tuning	tuning	NOUN
brj-23254	232	14	)	)	PUNCT
brj-23254	232	15	86	86	NUM
brj-23254	232	16	75	75	NUM
brj-23254	232	17	hafemann	hafemann	NOUN
brj-23254	232	18	et	et	PROPN
brj-23254	232	19	al	al	PROPN
brj-23254	232	20	.	.	PROPN
brj-23254	233	1	(	(	PUNCT
brj-23254	233	2	2014	2014	NUM
brj-23254	233	3	)	)	PUNCT
brj-23254	233	4	70	70	NUM
brj-23254	233	5	56	56	NUM
brj-23254	233	6	1	1	NUM
brj-23254	233	7	kind*2	kind*2	NOUN
brj-23254	233	8	e1	e1	NOUN
brj-23254	233	9	-	-	PUNCT
brj-23254	233	10	patch	patch	NOUN
brj-23254	233	11	vgg16	vgg16	NOUN
brj-23254	233	12	(	(	PUNCT
brj-23254	233	13	fine	fine	ADV
brj-23254	233	14	-	-	PUNCT
brj-23254	233	15	tuning	tuning	NOUN
brj-23254	233	16	)	)	PUNCT
brj-23254	233	17	79	79	NUM
brj-23254	233	18	71	71	NUM
brj-23254	233	19	hafemann	hafemann	NOUN
brj-23254	233	20	et	et	PROPN
brj-23254	233	21	al	al	PROPN
brj-23254	233	22	.	.	PROPN
brj-23254	234	1	(	(	PUNCT
brj-23254	234	2	2014	2014	NUM
brj-23254	234	3	)	)	PUNCT
brj-23254	234	4	55	55	NUM
brj-23254	234	5	47	47	NUM
brj-23254	234	6	e2	e2	NOUN
brj-23254	234	7	-	-	PUNCT
brj-23254	234	8	image	image	NOUN
brj-23254	234	9	vgg16	vgg16	NOUN
brj-23254	234	10	(	(	PUNCT
brj-23254	234	11	fine	fine	ADV
brj-23254	234	12	-	-	PUNCT
brj-23254	234	13	tuning	tuning	NOUN
brj-23254	234	14	)	)	PUNCT
brj-23254	234	15	94	94	NUM
brj-23254	234	16	83	83	NUM
brj-23254	234	17	hafemann	hafemann	NOUN
brj-23254	234	18	et	et	PROPN
brj-23254	234	19	al	al	PROPN
brj-23254	234	20	.	.	PROPN
brj-23254	235	1	(	(	PUNCT
brj-23254	235	2	2014	2014	NUM
brj-23254	235	3	)	)	PUNCT
brj-23254	235	4	74	74	NUM
brj-23254	235	5	63	63	NUM
brj-23254	235	6	peer	peer	NOUN
brj-23254	235	7	-	-	PUNCT
brj-23254	235	8	reviewed	review	VERB
brj-23254	235	9	article	article	NOUN
brj-23254	235	10	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	235	11	ma	ma	PROPN
brj-23254	235	12	et	et	PROPN
brj-23254	235	13	al	al	PROPN
brj-23254	235	14	.	.	PROPN
brj-23254	236	1	(	(	PUNCT
brj-23254	236	2	2024	2024	NUM
brj-23254	236	3	)	)	PUNCT
brj-23254	236	4	.	.	PUNCT
brj-23254	237	1	“	"	PUNCT
brj-23254	237	2	wood	wood	NOUN
brj-23254	237	3	i	i	X
brj-23254	237	4	d	d	PROPN
brj-23254	237	5	via	via	ADP
brj-23254	237	6	deep	deep	ADJ
brj-23254	237	7	learning	learning	NOUN
brj-23254	237	8	,	,	PUNCT
brj-23254	237	9	”	"	PUNCT
brj-23254	237	10	bioresources	bioresource	NOUN
brj-23254	237	11	19(3	19(3	NUM
brj-23254	237	12	)	)	PUNCT
brj-23254	237	13	,	,	PUNCT
brj-23254	237	14	4838	4838	NUM
brj-23254	237	15	-	-	SYM
brj-23254	237	16	4851	4851	NUM
brj-23254	237	17	.	.	PUNCT
brj-23254	238	1	4849	4849	NUM
brj-23254	238	2	despite	despite	SCONJ
brj-23254	238	3	d2	d2	PROPN
brj-23254	238	4	having	have	VERB
brj-23254	238	5	a	a	DET
brj-23254	238	6	higher	high	ADJ
brj-23254	238	7	testing	testing	NOUN
brj-23254	238	8	accuracy	accuracy	NOUN
brj-23254	238	9	than	than	ADP
brj-23254	238	10	d1	d1	NOUN
brj-23254	238	11	,	,	PUNCT
brj-23254	238	12	further	further	ADJ
brj-23254	238	13	tests	test	NOUN
brj-23254	238	14	on	on	ADP
brj-23254	238	15	surplus	surplus	ADJ
brj-23254	238	16	data	datum	NOUN
brj-23254	238	17	revealed	reveal	VERB
brj-23254	238	18	a	a	DET
brj-23254	238	19	lack	lack	NOUN
brj-23254	238	20	of	of	ADP
brj-23254	238	21	robustness	robustness	NOUN
brj-23254	238	22	.	.	PUNCT
brj-23254	239	1	fine	fine	ADJ
brj-23254	239	2	-	-	PUNCT
brj-23254	239	3	tuning	tuning	NOUN
brj-23254	239	4	based	base	VERB
brj-23254	239	5	on	on	ADP
brj-23254	239	6	vgg16	vgg16	PROPN
brj-23254	239	7	consistently	consistently	ADV
brj-23254	239	8	led	lead	VERB
brj-23254	239	9	to	to	ADP
brj-23254	239	10	higher	high	ADJ
brj-23254	239	11	accuracy	accuracy	NOUN
brj-23254	239	12	than	than	ADP
brj-23254	239	13	the	the	DET
brj-23254	239	14	original	original	ADJ
brj-23254	239	15	parameter	parameter	NOUN
brj-23254	239	16	setup	setup	NOUN
brj-23254	239	17	.	.	PUNCT
brj-23254	240	1	no	no	DET
brj-23254	240	2	significant	significant	ADJ
brj-23254	240	3	improvement	improvement	NOUN
brj-23254	240	4	in	in	ADP
brj-23254	240	5	accuracy	accuracy	NOUN
brj-23254	240	6	was	be	AUX
brj-23254	240	7	observed	observe	VERB
brj-23254	240	8	when	when	SCONJ
brj-23254	240	9	predicting	predict	VERB
brj-23254	240	10	genera	genera	NOUN
brj-23254	240	11	or	or	CCONJ
brj-23254	240	12	families	family	NOUN
brj-23254	240	13	,	,	PUNCT
brj-23254	240	14	as	as	SCONJ
brj-23254	240	15	opposed	oppose	VERB
brj-23254	240	16	to	to	ADP
brj-23254	240	17	species	specie	NOUN
brj-23254	240	18	.	.	PUNCT
brj-23254	241	1	consistent	consistent	ADJ
brj-23254	241	2	with	with	ADP
brj-23254	241	3	the	the	DET
brj-23254	241	4	findings	finding	NOUN
brj-23254	241	5	of	of	ADP
brj-23254	241	6	hafemann	hafemann	PROPN
brj-23254	241	7	et	et	PROPN
brj-23254	241	8	al	al	PROPN
brj-23254	241	9	.	.	PROPN
brj-23254	242	1	(	(	PUNCT
brj-23254	242	2	2014	2014	NUM
brj-23254	242	3	)	)	PUNCT
brj-23254	242	4	,	,	PUNCT
brj-23254	242	5	increased	increase	VERB
brj-23254	242	6	accuracy	accuracy	NOUN
brj-23254	242	7	was	be	AUX
brj-23254	242	8	observed	observe	VERB
brj-23254	242	9	when	when	SCONJ
brj-23254	242	10	using	use	VERB
brj-23254	242	11	a	a	DET
brj-23254	242	12	single	single	ADJ
brj-23254	242	13	image	image	NOUN
brj-23254	242	14	size	size	NOUN
brj-23254	242	15	.	.	PUNCT
brj-23254	243	1	however	however	ADV
brj-23254	243	2	,	,	PUNCT
brj-23254	243	3	the	the	DET
brj-23254	243	4	current	current	ADJ
brj-23254	243	5	study	study	NOUN
brj-23254	243	6	found	find	VERB
brj-23254	243	7	prediction	prediction	NOUN
brj-23254	243	8	accuracies	accuracy	NOUN
brj-23254	243	9	reaching	reach	VERB
brj-23254	243	10	86	86	NUM
brj-23254	243	11	%	%	NOUN
brj-23254	243	12	(	(	PUNCT
brj-23254	243	13	for	for	ADP
brj-23254	243	14	the	the	DET
brj-23254	243	15	testing	testing	NOUN
brj-23254	243	16	set	set	NOUN
brj-23254	243	17	)	)	PUNCT
brj-23254	243	18	and	and	CCONJ
brj-23254	243	19	75	75	NUM
brj-23254	243	20	%	%	NOUN
brj-23254	243	21	(	(	PUNCT
brj-23254	243	22	for	for	ADP
brj-23254	243	23	the	the	DET
brj-23254	243	24	surplus	surplus	NOUN
brj-23254	243	25	set	set	NOUN
brj-23254	243	26	)	)	PUNCT
brj-23254	243	27	,	,	PUNCT
brj-23254	243	28	despite	despite	SCONJ
brj-23254	243	29	variations	variation	NOUN
brj-23254	243	30	in	in	ADP
brj-23254	243	31	the	the	DET
brj-23254	243	32	dimensions	dimension	NOUN
brj-23254	243	33	of	of	ADP
brj-23254	243	34	the	the	DET
brj-23254	243	35	original	original	ADJ
brj-23254	243	36	images	image	NOUN
brj-23254	243	37	.	.	PUNCT
brj-23254	244	1	to	to	PART
brj-23254	244	2	validate	validate	VERB
brj-23254	244	3	if	if	SCONJ
brj-23254	244	4	the	the	DET
brj-23254	244	5	constructed	construct	VERB
brj-23254	244	6	cnn	cnn	PROPN
brj-23254	244	7	model	model	NOUN
brj-23254	244	8	is	be	AUX
brj-23254	244	9	universally	universally	ADV
brj-23254	244	10	applicable	applicable	ADJ
brj-23254	244	11	,	,	PUNCT
brj-23254	244	12	further	further	ADJ
brj-23254	244	13	samples	sample	NOUN
brj-23254	244	14	are	be	AUX
brj-23254	244	15	required	require	VERB
brj-23254	244	16	.	.	PUNCT
brj-23254	245	1	consequently	consequently	ADV
brj-23254	245	2	,	,	PUNCT
brj-23254	245	3	the	the	DET
brj-23254	245	4	authors	author	NOUN
brj-23254	245	5	launched	launch	VERB
brj-23254	245	6	a	a	DET
brj-23254	245	7	website	website	NOUN
brj-23254	245	8	that	that	PRON
brj-23254	245	9	enables	enable	VERB
brj-23254	245	10	anyone	anyone	PRON
brj-23254	245	11	to	to	PART
brj-23254	245	12	identify	identify	VERB
brj-23254	245	13	wood	wood	NOUN
brj-23254	245	14	species	specie	NOUN
brj-23254	245	15	using	use	VERB
brj-23254	245	16	their	their	PRON
brj-23254	245	17	own	own	ADJ
brj-23254	245	18	photos	photo	NOUN
brj-23254	245	19	.	.	PUNCT
brj-23254	246	1	the	the	DET
brj-23254	246	2	website	website	NOUN
brj-23254	246	3	employs	employ	VERB
brj-23254	246	4	two	two	NUM
brj-23254	246	5	configurations	configuration	NOUN
brj-23254	246	6	of	of	ADP
brj-23254	246	7	the	the	DET
brj-23254	246	8	fine	fine	ADV
brj-23254	246	9	-	-	PUNCT
brj-23254	246	10	tuned	tune	VERB
brj-23254	246	11	vgg16	vgg16	NOUN
brj-23254	246	12	model	model	NOUN
brj-23254	246	13	using	use	VERB
brj-23254	246	14	d1	d1	PROPN
brj-23254	246	15	and	and	CCONJ
brj-23254	246	16	e2	e2	PROPN
brj-23254	246	17	:	:	PUNCT
brj-23254	246	18	one	one	NUM
brj-23254	246	19	designed	design	VERB
brj-23254	246	20	for	for	ADP
brj-23254	246	21	predicting	predict	VERB
brj-23254	246	22	50	50	NUM
brj-23254	246	23	species	specie	NOUN
brj-23254	246	24	,	,	PUNCT
brj-23254	246	25	and	and	CCONJ
brj-23254	246	26	the	the	DET
brj-23254	246	27	other	other	ADJ
brj-23254	246	28	for	for	ADP
brj-23254	246	29	predicting	predict	VERB
brj-23254	246	30	10	10	NUM
brj-23254	246	31	species	specie	NOUN
brj-23254	246	32	from	from	ADP
brj-23254	246	33	images	image	NOUN
brj-23254	246	34	of	of	ADP
brj-23254	246	35	equal	equal	ADJ
brj-23254	246	36	dimensions	dimension	NOUN
brj-23254	246	37	.	.	PUNCT
brj-23254	247	1	their	their	PRON
brj-23254	247	2	accuracies	accuracy	NOUN
brj-23254	247	3	for	for	ADP
brj-23254	247	4	the	the	DET
brj-23254	247	5	test	test	NOUN
brj-23254	247	6	dataset	dataset	NOUN
brj-23254	247	7	were	be	AUX
brj-23254	247	8	72	72	NUM
brj-23254	247	9	%	%	NOUN
brj-23254	247	10	and	and	CCONJ
brj-23254	247	11	94	94	NUM
brj-23254	247	12	%	%	NOUN
brj-23254	247	13	,	,	PUNCT
brj-23254	247	14	respectively	respectively	ADV
brj-23254	247	15	.	.	PUNCT
brj-23254	248	1	the	the	DET
brj-23254	248	2	second	second	ADJ
brj-23254	248	3	goal	goal	NOUN
brj-23254	248	4	is	be	AUX
brj-23254	248	5	to	to	PART
brj-23254	248	6	facilitate	facilitate	VERB
brj-23254	248	7	opportunities	opportunity	NOUN
brj-23254	248	8	for	for	SCONJ
brj-23254	248	9	many	many	ADJ
brj-23254	248	10	people	people	NOUN
brj-23254	248	11	to	to	PART
brj-23254	248	12	attempt	attempt	VERB
brj-23254	248	13	tree	tree	NOUN
brj-23254	248	14	species	specie	NOUN
brj-23254	248	15	identification	identification	NOUN
brj-23254	248	16	through	through	ADP
brj-23254	248	17	this	this	DET
brj-23254	248	18	website	website	NOUN
brj-23254	248	19	,	,	PUNCT
brj-23254	248	20	and	and	CCONJ
brj-23254	248	21	the	the	DET
brj-23254	248	22	incorporation	incorporation	NOUN
brj-23254	248	23	of	of	ADP
brj-23254	248	24	accumulated	accumulate	VERB
brj-23254	248	25	data	datum	NOUN
brj-23254	248	26	into	into	ADP
brj-23254	248	27	the	the	DET
brj-23254	248	28	model	model	NOUN
brj-23254	248	29	will	will	AUX
brj-23254	248	30	lead	lead	VERB
brj-23254	248	31	to	to	ADP
brj-23254	248	32	further	further	ADJ
brj-23254	248	33	performance	performance	NOUN
brj-23254	248	34	enhancements	enhancement	NOUN
brj-23254	248	35	.	.	PUNCT
brj-23254	249	1	by	by	ADP
brj-23254	249	2	opening	open	VERB
brj-23254	249	3	the	the	DET
brj-23254	249	4	authors	author	NOUN
brj-23254	249	5	’	’	PART
brj-23254	249	6	process	process	NOUN
brj-23254	249	7	and	and	CCONJ
brj-23254	249	8	providing	provide	VERB
brj-23254	249	9	these	these	DET
brj-23254	249	10	resources	resource	NOUN
brj-23254	249	11	,	,	PUNCT
brj-23254	249	12	it	it	PRON
brj-23254	249	13	not	not	PART
brj-23254	249	14	only	only	ADV
brj-23254	249	15	adds	add	VERB
brj-23254	249	16	to	to	ADP
brj-23254	249	17	the	the	DET
brj-23254	249	18	global	global	ADJ
brj-23254	249	19	repository	repository	NOUN
brj-23254	249	20	of	of	ADP
brj-23254	249	21	scientific	scientific	ADJ
brj-23254	249	22	knowledge	knowledge	NOUN
brj-23254	249	23	,	,	PUNCT
brj-23254	249	24	but	but	CCONJ
brj-23254	249	25	also	also	ADV
brj-23254	249	26	facilitates	facilitate	VERB
brj-23254	249	27	advancements	advancement	NOUN
brj-23254	249	28	in	in	ADP
brj-23254	249	29	wood	wood	NOUN
brj-23254	249	30	science	science	NOUN
brj-23254	249	31	at	at	ADP
brj-23254	249	32	the	the	DET
brj-23254	249	33	grassroots	grassroots	ADJ
brj-23254	249	34	level	level	NOUN
brj-23254	249	35	.	.	PUNCT
brj-23254	250	1	conclusions	conclusion	NOUN
brj-23254	250	2	this	this	DET
brj-23254	250	3	study	study	NOUN
brj-23254	250	4	aimed	aim	VERB
brj-23254	250	5	to	to	PART
brj-23254	250	6	estimate	estimate	VERB
brj-23254	250	7	the	the	DET
brj-23254	250	8	practical	practical	ADJ
brj-23254	250	9	accuracy	accuracy	NOUN
brj-23254	250	10	of	of	ADP
brj-23254	250	11	identifying	identify	VERB
brj-23254	250	12	japanese	japanese	ADJ
brj-23254	250	13	wood	wood	NOUN
brj-23254	250	14	species	specie	NOUN
brj-23254	250	15	from	from	ADP
brj-23254	250	16	microscopic	microscopic	ADJ
brj-23254	250	17	images	image	NOUN
brj-23254	250	18	using	use	VERB
brj-23254	250	19	a	a	DET
brj-23254	250	20	cnn	cnn	NOUN
brj-23254	250	21	.	.	PUNCT
brj-23254	251	1	1	1	X
brj-23254	251	2	.	.	X
brj-23254	251	3	assessments	assessment	NOUN
brj-23254	251	4	were	be	AUX
brj-23254	251	5	made	make	VERB
brj-23254	251	6	based	base	VERB
brj-23254	251	7	on	on	ADP
brj-23254	251	8	various	various	ADJ
brj-23254	251	9	factors	factor	NOUN
brj-23254	251	10	,	,	PUNCT
brj-23254	251	11	including	include	VERB
brj-23254	251	12	the	the	DET
brj-23254	251	13	evaluation	evaluation	NOUN
brj-23254	251	14	methodology	methodology	NOUN
brj-23254	251	15	,	,	PUNCT
brj-23254	251	16	data	data	NOUN
brj-23254	251	17	allocation	allocation	NOUN
brj-23254	251	18	strategy	strategy	NOUN
brj-23254	251	19	,	,	PUNCT
brj-23254	251	20	cnn	cnn	PROPN
brj-23254	251	21	structure	structure	NOUN
brj-23254	251	22	,	,	PUNCT
brj-23254	251	23	classification	classification	NOUN
brj-23254	251	24	objective	objective	NOUN
brj-23254	251	25	,	,	PUNCT
brj-23254	251	26	and	and	CCONJ
brj-23254	251	27	original	original	ADJ
brj-23254	251	28	image	image	NOUN
brj-23254	251	29	size	size	NOUN
brj-23254	251	30	.	.	PUNCT
brj-23254	252	1	the	the	DET
brj-23254	252	2	overall	overall	ADJ
brj-23254	252	3	practical	practical	ADJ
brj-23254	252	4	accuracy	accuracy	NOUN
brj-23254	252	5	for	for	ADP
brj-23254	252	6	the	the	DET
brj-23254	252	7	identification	identification	NOUN
brj-23254	252	8	of	of	ADP
brj-23254	252	9	the	the	DET
brj-23254	252	10	50	50	NUM
brj-23254	252	11	japanese	japanese	ADJ
brj-23254	252	12	wood	wood	NOUN
brj-23254	252	13	species	specie	NOUN
brj-23254	252	14	stands	stand	VERB
brj-23254	252	15	at	at	ADP
brj-23254	252	16	approximately	approximately	ADV
brj-23254	252	17	70	70	NUM
brj-23254	252	18	%	%	NOUN
brj-23254	252	19	.	.	PUNCT
brj-23254	253	1	moreover	moreover	ADV
brj-23254	253	2	,	,	PUNCT
brj-23254	253	3	it	it	PRON
brj-23254	253	4	was	be	AUX
brj-23254	253	5	demonstrated	demonstrate	VERB
brj-23254	253	6	that	that	SCONJ
brj-23254	253	7	the	the	DET
brj-23254	253	8	constructed	construct	VERB
brj-23254	253	9	model	model	NOUN
brj-23254	253	10	could	could	AUX
brj-23254	253	11	be	be	AUX
brj-23254	253	12	used	use	VERB
brj-23254	253	13	to	to	PART
brj-23254	253	14	classify	classify	VERB
brj-23254	253	15	images	image	NOUN
brj-23254	253	16	procured	procure	VERB
brj-23254	253	17	at	at	ADP
brj-23254	253	18	varying	vary	VERB
brj-23254	253	19	magnification	magnification	NOUN
brj-23254	253	20	levels	level	NOUN
brj-23254	253	21	.	.	PUNCT
brj-23254	254	1	2	2	X
brj-23254	254	2	.	.	PUNCT
brj-23254	254	3	to	to	PART
brj-23254	254	4	promote	promote	VERB
brj-23254	254	5	the	the	DET
brj-23254	254	6	broader	broad	ADJ
brj-23254	254	7	use	use	NOUN
brj-23254	254	8	of	of	ADP
brj-23254	254	9	tree	tree	NOUN
brj-23254	254	10	species	specie	NOUN
brj-23254	254	11	identification	identification	NOUN
brj-23254	254	12	,	,	PUNCT
brj-23254	254	13	the	the	DET
brj-23254	254	14	authors	author	NOUN
brj-23254	254	15	created	create	VERB
brj-23254	254	16	a	a	DET
brj-23254	254	17	model	model	NOUN
brj-23254	254	18	using	use	VERB
brj-23254	254	19	vgg16	vgg16	NOUN
brj-23254	254	20	on	on	ADP
brj-23254	254	21	their	their	PRON
brj-23254	254	22	website	website	NOUN
brj-23254	254	23	.	.	PUNCT
brj-23254	255	1	users	user	NOUN
brj-23254	255	2	can	can	AUX
brj-23254	255	3	view	view	VERB
brj-23254	255	4	the	the	DET
brj-23254	255	5	outputs	output	NOUN
brj-23254	255	6	from	from	ADP
brj-23254	255	7	two	two	NUM
brj-23254	255	8	distinct	distinct	ADJ
brj-23254	255	9	models	model	NOUN
brj-23254	255	10	:	:	PUNCT
brj-23254	255	11	one	one	NUM
brj-23254	255	12	developed	develop	VERB
brj-23254	255	13	with	with	ADP
brj-23254	255	14	50	50	NUM
brj-23254	255	15	species	specie	NOUN
brj-23254	255	16	,	,	PUNCT
brj-23254	255	17	and	and	CCONJ
brj-23254	255	18	the	the	DET
brj-23254	255	19	other	other	ADJ
brj-23254	255	20	with	with	ADP
brj-23254	255	21	10	10	NUM
brj-23254	255	22	species	specie	NOUN
brj-23254	255	23	of	of	ADP
brj-23254	255	24	uniform	uniform	ADJ
brj-23254	255	25	dimensions	dimension	NOUN
brj-23254	255	26	.	.	PUNCT
brj-23254	256	1	the	the	DET
brj-23254	256	2	accuracy	accuracy	NOUN
brj-23254	256	3	of	of	ADP
brj-23254	256	4	the	the	DET
brj-23254	256	5	test	test	NOUN
brj-23254	256	6	datasets	dataset	NOUN
brj-23254	256	7	for	for	ADP
brj-23254	256	8	these	these	DET
brj-23254	256	9	models	model	NOUN
brj-23254	256	10	are	be	AUX
brj-23254	256	11	72	72	NUM
brj-23254	256	12	%	%	NOUN
brj-23254	256	13	and	and	CCONJ
brj-23254	256	14	94	94	NUM
brj-23254	256	15	%	%	NOUN
brj-23254	256	16	,	,	PUNCT
brj-23254	256	17	respectively	respectively	ADV
brj-23254	256	18	.	.	PUNCT
brj-23254	257	1	it	it	PRON
brj-23254	257	2	is	be	AUX
brj-23254	257	3	believed	believe	VERB
brj-23254	257	4	that	that	SCONJ
brj-23254	257	5	for	for	SCONJ
brj-23254	257	6	tree	tree	NOUN
brj-23254	257	7	species	specie	NOUN
brj-23254	257	8	identification	identification	NOUN
brj-23254	257	9	to	to	PART
brj-23254	257	10	become	become	VERB
brj-23254	257	11	universally	universally	ADV
brj-23254	257	12	applicable	applicable	ADJ
brj-23254	257	13	,	,	PUNCT
brj-23254	257	14	it	it	PRON
brj-23254	257	15	is	be	AUX
brj-23254	257	16	imperative	imperative	ADJ
brj-23254	257	17	that	that	SCONJ
brj-23254	257	18	the	the	DET
brj-23254	257	19	model	model	NOUN
brj-23254	257	20	be	be	AUX
brj-23254	257	21	adapted	adapt	VERB
brj-23254	257	22	to	to	ADP
brj-23254	257	23	any	any	DET
brj-23254	257	24	type	type	NOUN
brj-23254	257	25	of	of	ADP
brj-23254	257	26	microscope	microscope	NOUN
brj-23254	257	27	used	use	VERB
brj-23254	257	28	.	.	PUNCT
brj-23254	258	1	therefore	therefore	ADV
brj-23254	258	2	,	,	PUNCT
brj-23254	258	3	this	this	DET
brj-23254	258	4	study	study	NOUN
brj-23254	258	5	is	be	AUX
brj-23254	258	6	considered	consider	VERB
brj-23254	258	7	a	a	DET
brj-23254	258	8	continuing	continue	VERB
brj-23254	258	9	process	process	NOUN
brj-23254	258	10	,	,	PUNCT
brj-23254	258	11	and	and	CCONJ
brj-23254	258	12	the	the	DET
brj-23254	258	13	authors	author	NOUN
brj-23254	258	14	aim	aim	VERB
brj-23254	258	15	to	to	PART
brj-23254	258	16	further	far	ADV
brj-23254	258	17	validate	validate	VERB
brj-23254	258	18	its	its	PRON
brj-23254	258	19	practical	practical	ADJ
brj-23254	258	20	accuracy	accuracy	NOUN
brj-23254	258	21	through	through	ADP
brj-23254	258	22	the	the	DET
brj-23254	258	23	collection	collection	NOUN
brj-23254	258	24	and	and	CCONJ
brj-23254	258	25	analysis	analysis	NOUN
brj-23254	258	26	of	of	ADP
brj-23254	258	27	predicted	predict	VERB
brj-23254	258	28	results	result	NOUN
brj-23254	258	29	from	from	ADP
brj-23254	258	30	the	the	DET
brj-23254	258	31	website	website	NOUN
brj-23254	258	32	.	.	PUNCT
brj-23254	259	1	it	it	PRON
brj-23254	259	2	is	be	AUX
brj-23254	259	3	anticipated	anticipate	VERB
brj-23254	259	4	that	that	SCONJ
brj-23254	259	5	the	the	DET
brj-23254	259	6	data	datum	NOUN
brj-23254	259	7	accumulated	accumulate	VERB
brj-23254	259	8	from	from	ADP
brj-23254	259	9	this	this	DET
brj-23254	259	10	interactive	interactive	ADJ
brj-23254	259	11	platform	platform	NOUN
brj-23254	259	12	will	will	AUX
brj-23254	259	13	contribute	contribute	VERB
brj-23254	259	14	significantly	significantly	ADV
brj-23254	259	15	to	to	ADP
brj-23254	259	16	the	the	DET
brj-23254	259	17	ongoing	ongoing	ADJ
brj-23254	259	18	refinement	refinement	NOUN
brj-23254	259	19	and	and	CCONJ
brj-23254	259	20	improvement	improvement	NOUN
brj-23254	259	21	of	of	ADP
brj-23254	259	22	the	the	DET
brj-23254	259	23	authors	author	NOUN
brj-23254	259	24	’	’	PART
brj-23254	259	25	identification	identification	NOUN
brj-23254	259	26	model	model	NOUN
brj-23254	259	27	.	.	PUNCT
brj-23254	260	1	peer	peer	NOUN
brj-23254	260	2	-	-	PUNCT
brj-23254	260	3	reviewed	review	VERB
brj-23254	260	4	article	article	NOUN
brj-23254	260	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	260	6	ma	ma	PROPN
brj-23254	260	7	et	et	PROPN
brj-23254	260	8	al	al	PROPN
brj-23254	260	9	.	.	PROPN
brj-23254	261	1	(	(	PUNCT
brj-23254	261	2	2024	2024	NUM
brj-23254	261	3	)	)	PUNCT
brj-23254	261	4	.	.	PUNCT
brj-23254	262	1	“	"	PUNCT
brj-23254	262	2	wood	wood	NOUN
brj-23254	262	3	i	i	X
brj-23254	262	4	d	d	PROPN
brj-23254	262	5	via	via	ADP
brj-23254	262	6	deep	deep	ADJ
brj-23254	262	7	learning	learning	NOUN
brj-23254	262	8	,	,	PUNCT
brj-23254	262	9	”	"	PUNCT
brj-23254	262	10	bioresources	bioresource	NOUN
brj-23254	262	11	19(3	19(3	NUM
brj-23254	262	12	)	)	PUNCT
brj-23254	262	13	,	,	PUNCT
brj-23254	262	14	4838	4838	NUM
brj-23254	262	15	-	-	SYM
brj-23254	262	16	4851	4851	NUM
brj-23254	262	17	.	.	PUNCT
brj-23254	263	1	4850	4850	NUM
brj-23254	263	2	declarations	declaration	VERB
brj-23254	263	3	availability	availability	NOUN
brj-23254	263	4	of	of	ADP
brj-23254	263	5	data	datum	NOUN
brj-23254	263	6	and	and	CCONJ
brj-23254	263	7	materials	material	NOUN
brj-23254	263	8	the	the	DET
brj-23254	263	9	datasets	dataset	NOUN
brj-23254	263	10	generated	generate	VERB
brj-23254	263	11	and/or	and/or	CCONJ
brj-23254	263	12	analysed	analyse	VERB
brj-23254	263	13	during	during	ADP
brj-23254	263	14	the	the	DET
brj-23254	263	15	current	current	ADJ
brj-23254	263	16	study	study	NOUN
brj-23254	263	17	are	be	AUX
brj-23254	263	18	available	available	ADJ
brj-23254	263	19	in	in	ADP
brj-23254	263	20	the	the	DET
brj-23254	263	21	database	database	NOUN
brj-23254	263	22	repository	repository	NOUN
brj-23254	263	23	,	,	PUNCT
brj-23254	263	24	[	[	X
brj-23254	263	25	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	X
brj-23254	263	26	]	]	X
brj-23254	263	27	.	.	PUNCT
brj-23254	264	1	anyone	anyone	PRON
brj-23254	264	2	can	can	AUX
brj-23254	264	3	use	use	VERB
brj-23254	264	4	the	the	DET
brj-23254	264	5	cnn	cnn	PROPN
brj-23254	264	6	models	model	NOUN
brj-23254	264	7	and	and	CCONJ
brj-23254	264	8	information	information	NOUN
brj-23254	264	9	of	of	ADP
brj-23254	264	10	the	the	DET
brj-23254	264	11	twtw	twtw	ADJ
brj-23254	264	12	no	no	NOUN
brj-23254	264	13	.	.	PUNCT
brj-23254	265	1	used	use	VERB
brj-23254	265	2	for	for	ADP
brj-23254	265	3	training	training	NOUN
brj-23254	265	4	,	,	PUNCT
brj-23254	265	5	validation	validation	NOUN
brj-23254	265	6	and	and	CCONJ
brj-23254	265	7	test	test	NOUN
brj-23254	265	8	data	datum	NOUN
brj-23254	265	9	set	set	VERB
brj-23254	265	10	are	be	AUX
brj-23254	265	11	also	also	ADV
brj-23254	265	12	available	available	ADJ
brj-23254	265	13	from	from	ADP
brj-23254	265	14	the	the	DET
brj-23254	265	15	url	url	NOUN
brj-23254	265	16	:	:	PUNCT
brj-23254	265	17	https://inatetsu2nd-woodspecrecog-01home-f1zh5g.streamlit.app/.	https://inatetsu2nd-woodspecrecog-01home-f1zh5g.streamlit.app/.	X
brj-23254	266	1	acknowledgments	acknowledgment	NOUN
brj-23254	266	2	the	the	DET
brj-23254	266	3	authors	author	NOUN
brj-23254	266	4	would	would	AUX
brj-23254	266	5	like	like	VERB
brj-23254	266	6	to	to	PART
brj-23254	266	7	gratefully	gratefully	ADV
brj-23254	266	8	acknowledge	acknowledge	VERB
brj-23254	266	9	the	the	DET
brj-23254	266	10	use	use	NOUN
brj-23254	266	11	of	of	ADP
brj-23254	266	12	image	image	NOUN
brj-23254	266	13	data	datum	NOUN
brj-23254	266	14	from	from	ADP
brj-23254	266	15	forest	forest	NOUN
brj-23254	266	16	research	research	NOUN
brj-23254	266	17	and	and	CCONJ
brj-23254	266	18	management	management	NOUN
brj-23254	266	19	organization	organization	NOUN
brj-23254	266	20	japanese	japanese	ADJ
brj-23254	266	21	wood	wood	NOUN
brj-23254	266	22	identification	identification	NOUN
brj-23254	266	23	database	database	NOUN
brj-23254	266	24	,	,	PUNCT
brj-23254	266	25	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	PROPN
brj-23254	266	26	)	)	PUNCT
brj-23254	266	27	.	.	PUNCT
brj-23254	267	1	the	the	DET
brj-23254	267	2	authors	author	NOUN
brj-23254	267	3	would	would	AUX
brj-23254	267	4	like	like	VERB
brj-23254	267	5	to	to	PART
brj-23254	267	6	acknowledge	acknowledge	VERB
brj-23254	267	7	financial	financial	ADJ
brj-23254	267	8	support	support	NOUN
brj-23254	267	9	from	from	ADP
brj-23254	267	10	jsps	jsps	PROPN
brj-23254	267	11	(	(	PUNCT
brj-23254	267	12	kakenhi	kakenhi	PROPN
brj-23254	267	13	,	,	PUNCT
brj-23254	267	14	no	no	INTJ
brj-23254	267	15	.	.	NOUN
brj-23254	267	16	26850111	26850111	NUM
brj-23254	267	17	)	)	PUNCT
brj-23254	267	18	.	.	PUNCT
brj-23254	268	1	references	reference	NOUN
brj-23254	268	2	cited	cite	VERB
brj-23254	268	3	drakopoulos	drakopoulos	PROPN
brj-23254	268	4	,	,	PUNCT
brj-23254	268	5	f.	f.	PROPN
brj-23254	268	6	,	,	PUNCT
brj-23254	268	7	baby	baby	PROPN
brj-23254	268	8	,	,	PUNCT
brj-23254	268	9	d.	d.	PROPN
brj-23254	268	10	,	,	PUNCT
brj-23254	268	11	and	and	CCONJ
brj-23254	268	12	verhulst	verhulst	PROPN
brj-23254	268	13	,	,	PUNCT
brj-23254	268	14	s.	s.	PROPN
brj-23254	268	15	(	(	PUNCT
brj-23254	268	16	2021	2021	NUM
brj-23254	268	17	)	)	PUNCT
brj-23254	268	18	.	.	PUNCT
brj-23254	269	1	“	"	PUNCT
brj-23254	269	2	a	a	DET
brj-23254	269	3	convolutional	convolutional	ADJ
brj-23254	269	4	neural	neural	ADJ
brj-23254	269	5	-	-	PUNCT
brj-23254	269	6	network	network	NOUN
brj-23254	269	7	framework	framework	NOUN
brj-23254	269	8	for	for	ADP
brj-23254	269	9	modelling	model	VERB
brj-23254	269	10	auditory	auditory	ADJ
brj-23254	269	11	sensory	sensory	ADJ
brj-23254	269	12	cells	cell	NOUN
brj-23254	269	13	and	and	CCONJ
brj-23254	269	14	synapses	synapsis	NOUN
brj-23254	269	15	,	,	PUNCT
brj-23254	269	16	”	"	PUNCT
brj-23254	269	17	communications	communication	NOUN
brj-23254	269	18	biology	biology	NOUN
brj-23254	269	19	4	4	NUM
brj-23254	269	20	,	,	PUNCT
brj-23254	269	21	article	article	NOUN
brj-23254	269	22	827	827	NUM
brj-23254	269	23	.	.	PUNCT
brj-23254	270	1	doi	doi	NOUN
brj-23254	270	2	:	:	PUNCT
brj-23254	270	3	10.1038	10.1038	NUM
brj-23254	270	4	/	/	SYM
brj-23254	270	5	s42003	s42003	NOUN
brj-23254	270	6	-	-	PUNCT
brj-23254	270	7	021	021	NUM
brj-23254	270	8	-	-	PUNCT
brj-23254	270	9	02341	02341	NUM
brj-23254	270	10	-	-	SYM
brj-23254	270	11	5	5	NUM
brj-23254	270	12	geus	geus	NOUN
brj-23254	270	13	,	,	PUNCT
brj-23254	270	14	a.	a.	PROPN
brj-23254	270	15	r.	r.	PROPN
brj-23254	270	16	,	,	PUNCT
brj-23254	270	17	silva	silva	PROPN
brj-23254	270	18	,	,	PUNCT
brj-23254	270	19	s.	s.	PROPN
brj-23254	270	20	f.	f.	PROPN
brj-23254	270	21	,	,	PUNCT
brj-23254	270	22	gontijo	gontijo	NOUN
brj-23254	270	23	,	,	PUNCT
brj-23254	270	24	a.	a.	PROPN
brj-23254	270	25	b.	b.	PROPN
brj-23254	270	26	,	,	PUNCT
brj-23254	270	27	silva	silva	PROPN
brj-23254	270	28	,	,	PUNCT
brj-23254	270	29	f.	f.	PROPN
brj-23254	270	30	o.	o.	PROPN
brj-23254	270	31	,	,	PUNCT
brj-23254	270	32	batista	batista	PROPN
brj-23254	270	33	,	,	PUNCT
brj-23254	270	34	m.	m.	NOUN
brj-23254	270	35	a.	a.	PROPN
brj-23254	270	36	,	,	PUNCT
brj-23254	270	37	and	and	CCONJ
brj-23254	270	38	souza	souza	PROPN
brj-23254	270	39	,	,	PUNCT
brj-23254	270	40	j.	j.	PROPN
brj-23254	270	41	r.	r.	PROPN
brj-23254	270	42	(	(	PUNCT
brj-23254	270	43	2020	2020	NUM
brj-23254	270	44	)	)	PUNCT
brj-23254	270	45	.	.	PUNCT
brj-23254	271	1	“	"	PUNCT
brj-23254	271	2	an	an	DET
brj-23254	271	3	analysis	analysis	NOUN
brj-23254	271	4	of	of	ADP
brj-23254	271	5	timber	timber	NOUN
brj-23254	271	6	sections	section	NOUN
brj-23254	271	7	and	and	CCONJ
brj-23254	271	8	deep	deep	ADJ
brj-23254	271	9	learning	learning	NOUN
brj-23254	271	10	for	for	ADP
brj-23254	271	11	wood	wood	NOUN
brj-23254	271	12	species	specie	NOUN
brj-23254	271	13	classification	classification	NOUN
brj-23254	271	14	,	,	PUNCT
brj-23254	271	15	”	"	PUNCT
brj-23254	271	16	multimedia	multimedia	NOUN
brj-23254	271	17	tools	tool	NOUN
brj-23254	271	18	and	and	CCONJ
brj-23254	271	19	applications	application	NOUN
brj-23254	271	20	79	79	NUM
brj-23254	271	21	,	,	PUNCT
brj-23254	271	22	34513	34513	NUM
brj-23254	271	23	-	-	SYM
brj-23254	271	24	34529	34529	NUM
brj-23254	271	25	.	.	PUNCT
brj-23254	272	1	doi	doi	NOUN
brj-23254	272	2	:	:	PUNCT
brj-23254	272	3	10.1007	10.1007	NUM
brj-23254	272	4	/	/	SYM
brj-23254	272	5	s11042	s11042	PROPN
brj-23254	272	6	-	-	PUNCT
brj-23254	272	7	020	020	NUM
brj-23254	272	8	-	-	PUNCT
brj-23254	272	9	09212	09212	NUM
brj-23254	272	10	-	-	PUNCT
brj-23254	272	11	x	x	NOUN
brj-23254	272	12	geus	geus	NOUN
brj-23254	272	13	,	,	PUNCT
brj-23254	272	14	a.	a.	PROPN
brj-23254	272	15	r.	r.	PROPN
brj-23254	272	16	,	,	PUNCT
brj-23254	272	17	backes	backes	PROPN
brj-23254	272	18	,	,	PUNCT
brj-23254	272	19	a.	a.	PROPN
brj-23254	272	20	r.	r.	PROPN
brj-23254	272	21	,	,	PUNCT
brj-23254	272	22	gontijo	gontijo	NOUN
brj-23254	272	23	,	,	PUNCT
brj-23254	272	24	a.	a.	PROPN
brj-23254	272	25	b.	b.	PROPN
brj-23254	272	26	,	,	PUNCT
brj-23254	272	27	albuquerque	albuquerque	PROPN
brj-23254	272	28	,	,	PUNCT
brj-23254	272	29	g.	g.	PROPN
brj-23254	272	30	h.	h.	PROPN
brj-23254	272	31	q.	q.	PROPN
brj-23254	272	32	,	,	PUNCT
brj-23254	272	33	and	and	CCONJ
brj-23254	272	34	souza	souza	PROPN
brj-23254	272	35	,	,	PUNCT
brj-23254	272	36	j.	j.	PROPN
brj-23254	272	37	r.	r.	PROPN
brj-23254	272	38	(	(	PUNCT
brj-23254	272	39	2021	2021	NUM
brj-23254	272	40	)	)	PUNCT
brj-23254	272	41	.	.	PUNCT
brj-23254	273	1	“	"	PUNCT
brj-23254	273	2	amazon	amazon	NOUN
brj-23254	273	3	wood	wood	NOUN
brj-23254	273	4	species	specie	NOUN
brj-23254	273	5	classification	classification	NOUN
brj-23254	273	6	:	:	PUNCT
brj-23254	273	7	a	a	DET
brj-23254	273	8	comparison	comparison	NOUN
brj-23254	273	9	between	between	ADP
brj-23254	273	10	deep	deep	ADJ
brj-23254	273	11	learning	learning	NOUN
brj-23254	273	12	and	and	CCONJ
brj-23254	273	13	pre	pre	VERB
brj-23254	273	14	-	-	ADJ
brj-23254	273	15	designed	design	VERB
brj-23254	273	16	features	feature	NOUN
brj-23254	273	17	,	,	PUNCT
brj-23254	273	18	”	"	PUNCT
brj-23254	273	19	wood	wood	NOUN
brj-23254	273	20	science	science	NOUN
brj-23254	273	21	and	and	CCONJ
brj-23254	273	22	technology	technology	NOUN
brj-23254	273	23	55	55	NUM
brj-23254	273	24	,	,	PUNCT
brj-23254	273	25	857	857	NUM
brj-23254	273	26	-	-	SYM
brj-23254	273	27	872	872	NUM
brj-23254	273	28	.	.	PUNCT
brj-23254	274	1	doi	doi	NOUN
brj-23254	274	2	:	:	PUNCT
brj-23254	274	3	10.1007	10.1007	NUM
brj-23254	274	4	/	/	SYM
brj-23254	274	5	s00226	s00226	PROPN
brj-23254	274	6	-	-	PUNCT
brj-23254	274	7	021	021	NUM
brj-23254	274	8	-	-	PUNCT
brj-23254	274	9	01282	01282	NUM
brj-23254	274	10	-	-	PUNCT
brj-23254	274	11	w	w	NOUN
brj-23254	274	12	goodfellow	goodfellow	PROPN
brj-23254	274	13	,	,	PUNCT
brj-23254	274	14	i.	i.	PROPN
brj-23254	274	15	j.	j.	PROPN
brj-23254	274	16	,	,	PUNCT
brj-23254	274	17	pouget	pouget	NOUN
brj-23254	274	18	-	-	PUNCT
brj-23254	274	19	abadie	abadie	ADJ
brj-23254	274	20	,	,	PUNCT
brj-23254	274	21	j.	j.	PROPN
brj-23254	274	22	,	,	PUNCT
brj-23254	274	23	mirza	mirza	PROPN
brj-23254	274	24	,	,	PUNCT
brj-23254	274	25	m.	m.	NOUN
brj-23254	274	26	,	,	PUNCT
brj-23254	274	27	xu	xu	PROPN
brj-23254	274	28	,	,	PUNCT
brj-23254	274	29	b.	b.	PROPN
brj-23254	274	30	,	,	PUNCT
brj-23254	274	31	warde	warde	PROPN
brj-23254	274	32	-	-	PUNCT
brj-23254	274	33	farley	farley	PROPN
brj-23254	274	34	,	,	PUNCT
brj-23254	274	35	d.	d.	PROPN
brj-23254	274	36	,	,	PUNCT
brj-23254	274	37	ozair	ozair	PROPN
brj-23254	274	38	,	,	PUNCT
brj-23254	274	39	s.	s.	PROPN
brj-23254	274	40	,	,	PUNCT
brj-23254	274	41	courville	courville	NOUN
brj-23254	274	42	,	,	PUNCT
brj-23254	274	43	a.	a.	NOUN
brj-23254	274	44	,	,	PUNCT
brj-23254	274	45	and	and	CCONJ
brj-23254	274	46	bengio	bengio	PROPN
brj-23254	274	47	,	,	PUNCT
brj-23254	274	48	y.	y.	PROPN
brj-23254	274	49	(	(	PUNCT
brj-23254	274	50	2014	2014	NUM
brj-23254	274	51	)	)	PUNCT
brj-23254	274	52	.	.	PUNCT
brj-23254	275	1	“	"	PUNCT
brj-23254	275	2	generative	generative	ADJ
brj-23254	275	3	adversarial	adversarial	ADJ
brj-23254	275	4	nets	net	NOUN
brj-23254	275	5	,	,	PUNCT
brj-23254	275	6	”	"	PUNCT
brj-23254	275	7	advances	advance	NOUN
brj-23254	275	8	in	in	ADP
brj-23254	275	9	neural	neural	ADJ
brj-23254	275	10	information	information	NOUN
brj-23254	275	11	processing	processing	NOUN
brj-23254	275	12	systems	system	NOUN
brj-23254	275	13	27	27	NUM
brj-23254	275	14	,	,	PUNCT
brj-23254	275	15	680	680	NUM
brj-23254	275	16	-	-	SYM
brj-23254	275	17	2672	2672	NUM
brj-23254	275	18	.	.	PUNCT
brj-23254	276	1	doi	doi	NOUN
brj-23254	276	2	:	:	PUNCT
brj-23254	276	3	10.48550	10.48550	NUM
brj-23254	276	4	/	/	SYM
brj-23254	276	5	arxiv.1406.2661	arxiv.1406.2661	ADV
brj-23254	276	6	hafemann	hafemann	NOUN
brj-23254	276	7	,	,	PUNCT
brj-23254	276	8	l.	l.	PROPN
brj-23254	276	9	g.	g.	PROPN
brj-23254	276	10	,	,	PUNCT
brj-23254	276	11	oliveira	oliveira	PROPN
brj-23254	276	12	,	,	PUNCT
brj-23254	276	13	l.	l.	PROPN
brj-23254	276	14	s.	s.	PROPN
brj-23254	276	15	,	,	PUNCT
brj-23254	276	16	and	and	CCONJ
brj-23254	276	17	cavalin	cavalin	ADV
brj-23254	276	18	,	,	PUNCT
brj-23254	276	19	p.	p.	NOUN
brj-23254	276	20	(	(	PUNCT
brj-23254	276	21	2014	2014	NUM
brj-23254	276	22	)	)	PUNCT
brj-23254	276	23	.	.	PUNCT
brj-23254	277	1	“	"	PUNCT
brj-23254	277	2	forest	forest	NOUN
brj-23254	277	3	species	species	NOUN
brj-23254	277	4	recognition	recognition	NOUN
brj-23254	277	5	using	use	VERB
brj-23254	277	6	deep	deep	ADJ
brj-23254	277	7	convolutional	convolutional	ADJ
brj-23254	277	8	neural	neural	ADJ
brj-23254	277	9	networks	network	NOUN
brj-23254	277	10	,	,	PUNCT
brj-23254	277	11	”	"	PUNCT
brj-23254	277	12	paper	paper	NOUN
brj-23254	277	13	presented	present	VERB
brj-23254	277	14	at	at	ADP
brj-23254	277	15	:	:	PUNCT
brj-23254	277	16	22nd	22nd	ADJ
brj-23254	277	17	international	international	ADJ
brj-23254	277	18	conference	conference	NOUN
brj-23254	277	19	on	on	ADP
brj-23254	277	20	pattern	pattern	NOUN
brj-23254	277	21	recognition	recognition	NOUN
brj-23254	277	22	,	,	PUNCT
brj-23254	277	23	stockholm	stockholm	PROPN
brj-23254	277	24	,	,	PUNCT
brj-23254	277	25	sweden	sweden	PROPN
brj-23254	277	26	,	,	PUNCT
brj-23254	277	27	pp	pp	ADP
brj-23254	277	28	.	.	PUNCT
brj-23254	277	29	1103	1103	NUM
brj-23254	277	30	-	-	SYM
brj-23254	277	31	1107	1107	NUM
brj-23254	277	32	.	.	PUNCT
brj-23254	278	1	doi	doi	NOUN
brj-23254	278	2	:	:	PUNCT
brj-23254	278	3	10.1109	10.1109	NUM
brj-23254	278	4	/	/	SYM
brj-23254	278	5	icpr.2014.199	icpr.2014.199	VERB
brj-23254	278	6	he	he	PRON
brj-23254	278	7	,	,	PUNCT
brj-23254	278	8	t.	t.	PROPN
brj-23254	278	9	,	,	PUNCT
brj-23254	278	10	mu	mu	PROPN
brj-23254	278	11	,	,	PUNCT
brj-23254	278	12	s.	s.	PROPN
brj-23254	278	13	,	,	PUNCT
brj-23254	278	14	zhou	zhou	PROPN
brj-23254	278	15	,	,	PUNCT
brj-23254	278	16	h.	h.	PROPN
brj-23254	278	17	,	,	PUNCT
brj-23254	278	18	and	and	CCONJ
brj-23254	278	19	hu	hu	PROPN
brj-23254	278	20	,	,	PUNCT
brj-23254	278	21	j.	j.	PROPN
brj-23254	278	22	(	(	PUNCT
brj-23254	278	23	2021	2021	NUM
brj-23254	278	24	)	)	PUNCT
brj-23254	278	25	.	.	PUNCT
brj-23254	279	1	“	"	PUNCT
brj-23254	279	2	wood	wood	NOUN
brj-23254	279	3	species	species	NOUN
brj-23254	279	4	identification	identification	NOUN
brj-23254	279	5	based	base	VERB
brj-23254	279	6	on	on	ADP
brj-23254	279	7	an	an	DET
brj-23254	279	8	ensemble	ensemble	NOUN
brj-23254	279	9	of	of	ADP
brj-23254	279	10	deep	deep	ADJ
brj-23254	279	11	convolution	convolution	NOUN
brj-23254	279	12	neural	neural	ADJ
brj-23254	279	13	networks	network	NOUN
brj-23254	279	14	,	,	PUNCT
brj-23254	279	15	”	"	PUNCT
brj-23254	279	16	wood	wood	NOUN
brj-23254	279	17	res	re	NOUN
brj-23254	279	18	.	.	PUNCT
brj-23254	280	1	66	66	NUM
brj-23254	280	2	,	,	PUNCT
brj-23254	280	3	1	1	NUM
brj-23254	280	4	-	-	SYM
brj-23254	280	5	14	14	NUM
brj-23254	280	6	.	.	PUNCT
brj-23254	281	1	doi	doi	NOUN
brj-23254	281	2	:	:	PUNCT
brj-23254	281	3	10.37763	10.37763	NUM
brj-23254	281	4	/	/	SYM
brj-23254	281	5	wr.1336	wr.1336	VERB
brj-23254	281	6	-	-	SYM
brj-23254	281	7	4561/66.1.0114	4561/66.1.0114	NUM
brj-23254	281	8	hwang	hwang	PROPN
brj-23254	281	9	,	,	PUNCT
brj-23254	281	10	s.	s.	PROPN
brj-23254	281	11	w.	w.	PROPN
brj-23254	281	12	,	,	PUNCT
brj-23254	281	13	and	and	CCONJ
brj-23254	281	14	sugiyama	sugiyama	NOUN
brj-23254	281	15	,	,	PUNCT
brj-23254	281	16	j.	j.	PROPN
brj-23254	281	17	j.	j.	PROPN
brj-23254	281	18	(	(	PUNCT
brj-23254	281	19	2021	2021	NUM
brj-23254	281	20	)	)	PUNCT
brj-23254	281	21	.	.	PUNCT
brj-23254	282	1	“	"	PUNCT
brj-23254	282	2	computer	computer	NOUN
brj-23254	282	3	vision‑based	vision‑base	VERB
brj-23254	282	4	wood	wood	NOUN
brj-23254	282	5	identification	identification	NOUN
brj-23254	282	6	and	and	CCONJ
brj-23254	282	7	its	its	PRON
brj-23254	282	8	expansion	expansion	NOUN
brj-23254	282	9	and	and	CCONJ
brj-23254	282	10	contribution	contribution	NOUN
brj-23254	282	11	potentials	potential	VERB
brj-23254	282	12	in	in	ADP
brj-23254	282	13	wood	wood	NOUN
brj-23254	282	14	science	science	NOUN
brj-23254	282	15	:	:	PUNCT
brj-23254	282	16	a	a	DET
brj-23254	282	17	review	review	NOUN
brj-23254	282	18	,	,	PUNCT
brj-23254	282	19	”	"	PUNCT
brj-23254	282	20	plant	plant	NOUN
brj-23254	282	21	methods	method	NOUN
brj-23254	282	22	17	17	NUM
brj-23254	282	23	,	,	PUNCT
brj-23254	282	24	article	article	NOUN
brj-23254	282	25	47	47	NUM
brj-23254	282	26	.	.	PUNCT
brj-23254	283	1	doi	doi	NOUN
brj-23254	283	2	:	:	PUNCT
brj-23254	283	3	10.1186	10.1186	NUM
brj-23254	283	4	/	/	SYM
brj-23254	283	5	s13007	s13007	NOUN
brj-23254	283	6	-	-	PUNCT
brj-23254	283	7	021	021	NUM
brj-23254	283	8	-	-	PUNCT
brj-23254	283	9	00746	00746	NUM
brj-23254	283	10	-	-	SYM
brj-23254	283	11	1	1	NUM
brj-23254	283	12	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	PROPN
brj-23254	283	13	https://inatetsu2nd-woodspecrecog-01-home-f1zh5g.streamlit.app/	https://inatetsu2nd-woodspecrecog-01-home-f1zh5g.streamlit.app/	NOUN
brj-23254	283	14	https://inatetsu2nd-woodspecrecog-01-home-f1zh5g.streamlit.app/	https://inatetsu2nd-woodspecrecog-01-home-f1zh5g.streamlit.app/	NOUN
brj-23254	283	15	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	http://db.ffpri.affrc.go.jp/wooddb/twtwdb/home.php	ADJ
brj-23254	283	16	peer	peer	NOUN
brj-23254	283	17	-	-	PUNCT
brj-23254	283	18	reviewed	review	VERB
brj-23254	283	19	article	article	NOUN
brj-23254	283	20	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-23254	283	21	ma	ma	PROPN
brj-23254	283	22	et	et	PROPN
brj-23254	283	23	al	al	PROPN
brj-23254	283	24	.	.	PROPN
brj-23254	284	1	(	(	PUNCT
brj-23254	284	2	2024	2024	NUM
brj-23254	284	3	)	)	PUNCT
brj-23254	284	4	.	.	PUNCT
brj-23254	285	1	“	"	PUNCT
brj-23254	285	2	wood	wood	NOUN
brj-23254	285	3	i	i	X
brj-23254	285	4	d	d	PROPN
brj-23254	285	5	via	via	ADP
brj-23254	285	6	deep	deep	ADJ
brj-23254	285	7	learning	learning	NOUN
brj-23254	285	8	,	,	PUNCT
brj-23254	285	9	”	"	PUNCT
brj-23254	285	10	bioresources	bioresource	NOUN
brj-23254	285	11	19(3	19(3	NUM
brj-23254	285	12	)	)	PUNCT
brj-23254	285	13	,	,	PUNCT
brj-23254	285	14	4838	4838	NUM
brj-23254	285	15	-	-	SYM
brj-23254	285	16	4851	4851	NUM
brj-23254	285	17	.	.	PUNCT
brj-23254	286	1	4851	4851	NUM
brj-23254	286	2	kırbaş	kırbaş	PROPN
brj-23254	286	3	,	,	PUNCT
brj-23254	286	4	i̇.	i̇.	PROPN
brj-23254	286	5	,	,	PUNCT
brj-23254	286	6	and	and	CCONJ
brj-23254	286	7	çifci	çifci	ADJ
brj-23254	286	8	,	,	PUNCT
brj-23254	286	9	a.	a.	NOUN
brj-23254	286	10	(	(	PUNCT
brj-23254	286	11	2022	2022	NUM
brj-23254	286	12	)	)	PUNCT
brj-23254	286	13	.	.	PUNCT
brj-23254	287	1	“	"	PUNCT
brj-23254	287	2	an	an	DET
brj-23254	287	3	effective	effective	ADJ
brj-23254	287	4	and	and	CCONJ
brj-23254	287	5	fast	fast	ADJ
brj-23254	287	6	solution	solution	NOUN
brj-23254	287	7	for	for	ADP
brj-23254	287	8	classification	classification	NOUN
brj-23254	287	9	of	of	ADP
brj-23254	287	10	wood	wood	NOUN
brj-23254	287	11	species	specie	NOUN
brj-23254	287	12	:	:	PUNCT
brj-23254	287	13	a	a	DET
brj-23254	287	14	deep	deep	ADJ
brj-23254	287	15	transfer	transfer	NOUN
brj-23254	287	16	learning	learning	NOUN
brj-23254	287	17	approach	approach	NOUN
brj-23254	287	18	,	,	PUNCT
brj-23254	287	19	”	"	PUNCT
brj-23254	287	20	ecol	ecol	NOUN
brj-23254	287	21	.	.	PUNCT
brj-23254	288	1	inform	inform	NOUN
brj-23254	288	2	.	.	PUNCT
brj-23254	289	1	69	69	NUM
brj-23254	289	2	,	,	PUNCT
brj-23254	289	3	article	article	NOUN
brj-23254	289	4	101633	101633	NUM
brj-23254	289	5	.	.	PUNCT
brj-23254	290	1	doi	doi	NOUN
brj-23254	290	2	:	:	PUNCT
brj-23254	290	3	10.1016	10.1016	NUM
brj-23254	290	4	/	/	SYM
brj-23254	290	5	j.ecoinf.2022.101633	j.ecoinf.2022.101633	PROPN
brj-23254	290	6	kwon	kwon	PROPN
brj-23254	290	7	,	,	PUNCT
brj-23254	290	8	o.	o.	PROPN
brj-23254	290	9	,	,	PUNCT
brj-23254	290	10	lee	lee	PROPN
brj-23254	290	11	,	,	PUNCT
brj-23254	290	12	h.	h.	PROPN
brj-23254	290	13	g.	g.	PROPN
brj-23254	290	14	,	,	PUNCT
brj-23254	290	15	lee	lee	PROPN
brj-23254	290	16	,	,	PUNCT
brj-23254	290	17	m.	m.	PROPN
brj-23254	290	18	r.	r.	PROPN
brj-23254	290	19	,	,	PUNCT
brj-23254	290	20	jang	jang	PROPN
brj-23254	290	21	,	,	PUNCT
brj-23254	290	22	s.	s.	PROPN
brj-23254	290	23	,	,	PUNCT
brj-23254	290	24	yang	yang	PROPN
brj-23254	290	25	,	,	PUNCT
brj-23254	290	26	s.	s.	PROPN
brj-23254	290	27	y.	y.	PROPN
brj-23254	290	28	,	,	PUNCT
brj-23254	290	29	park	park	NOUN
brj-23254	290	30	,	,	PUNCT
brj-23254	290	31	s.	s.	PROPN
brj-23254	290	32	y.	y.	PROPN
brj-23254	290	33	,	,	PUNCT
brj-23254	290	34	choi	choi	NOUN
brj-23254	290	35	,	,	PUNCT
brj-23254	290	36	i.	i.	PROPN
brj-23254	290	37	g.	g.	PROPN
brj-23254	290	38	,	,	PUNCT
brj-23254	290	39	and	and	CCONJ
brj-23254	290	40	yeo	yeo	PROPN
brj-23254	290	41	,	,	PUNCT
brj-23254	290	42	h.	h.	PROPN
brj-23254	290	43	(	(	PUNCT
brj-23254	290	44	2017	2017	NUM
brj-23254	290	45	)	)	PUNCT
brj-23254	290	46	.	.	PUNCT
brj-23254	291	1	“	"	PUNCT
brj-23254	291	2	automatic	automatic	ADJ
brj-23254	291	3	wood	wood	NOUN
brj-23254	291	4	species	specie	NOUN
brj-23254	291	5	identification	identification	NOUN
brj-23254	291	6	of	of	ADP
brj-23254	291	7	korean	korean	ADJ
brj-23254	291	8	softwood	softwood	NOUN
brj-23254	291	9	based	base	VERB
brj-23254	291	10	on	on	ADP
brj-23254	291	11	convolutional	convolutional	ADJ
brj-23254	291	12	neural	neural	ADJ
brj-23254	291	13	networks	network	NOUN
brj-23254	291	14	,	,	PUNCT
brj-23254	291	15	”	"	PUNCT
brj-23254	291	16	journal	journal	NOUN
brj-23254	291	17	of	of	ADP
brj-23254	291	18	korean	korean	ADJ
brj-23254	291	19	wood	wood	NOUN
brj-23254	291	20	science	science	NOUN
brj-23254	291	21	technology	technology	NOUN
brj-23254	291	22	45(6	45(6	NOUN
brj-23254	291	23	)	)	PUNCT
brj-23254	291	24	,	,	PUNCT
brj-23254	291	25	797	797	NUM
brj-23254	291	26	-	-	SYM
brj-23254	291	27	808	808	NUM
brj-23254	291	28	.	.	PUNCT
brj-23254	291	29	doi	doi	NOUN
brj-23254	291	30	:	:	PUNCT
brj-23254	291	31	10.5658	10.5658	NUM
brj-23254	291	32	/	/	SYM
brj-23254	291	33	wood.2017.45.6.797	wood.2017.45.6.797	NOUN
brj-23254	291	34	lecun	lecun	NOUN
brj-23254	291	35	,	,	PUNCT
brj-23254	291	36	y.	y.	PROPN
brj-23254	291	37	,	,	PUNCT
brj-23254	291	38	bottou	bottou	PROPN
brj-23254	291	39	,	,	PUNCT
brj-23254	291	40	l.	l.	PROPN
brj-23254	291	41	,	,	PUNCT
brj-23254	291	42	bengio	bengio	PROPN
brj-23254	291	43	,	,	PUNCT
brj-23254	291	44	y.	y.	NOUN
brj-23254	291	45	,	,	PUNCT
brj-23254	291	46	and	and	CCONJ
brj-23254	291	47	haffner	haffner	NOUN
brj-23254	291	48	,	,	PUNCT
brj-23254	291	49	p.	p.	NOUN
brj-23254	291	50	(	(	PUNCT
brj-23254	291	51	1998	1998	NUM
brj-23254	291	52	)	)	PUNCT
brj-23254	291	53	.	.	PUNCT
brj-23254	292	1	“	"	PUNCT
brj-23254	292	2	gradient	gradient	NOUN
brj-23254	292	3	-	-	PUNCT
brj-23254	292	4	based	base	VERB
brj-23254	292	5	learning	learning	NOUN
brj-23254	292	6	applied	apply	VERB
brj-23254	292	7	to	to	ADP
brj-23254	292	8	document	document	NOUN
brj-23254	292	9	recognition	recognition	NOUN
brj-23254	292	10	,	,	PUNCT
brj-23254	292	11	”	"	PUNCT
brj-23254	292	12	proceedings	proceeding	NOUN
brj-23254	292	13	of	of	ADP
brj-23254	292	14	the	the	DET
brj-23254	292	15	ieee	ieee	NOUN
brj-23254	292	16	86(11	86(11	NUM
brj-23254	292	17	)	)	PUNCT
brj-23254	292	18	,	,	PUNCT
brj-23254	292	19	324	324	NUM
brj-23254	292	20	-	-	SYM
brj-23254	292	21	2278	2278	NUM
brj-23254	292	22	.	.	PUNCT
brj-23254	293	1	doi	doi	NOUN
brj-23254	293	2	:	:	PUNCT
brj-23254	293	3	10.1109/5.726791	10.1109/5.726791	NUM
brj-23254	293	4	lens	len	NOUN
brj-23254	293	5	,	,	PUNCT
brj-23254	293	6	f.	f.	PROPN
brj-23254	293	7	,	,	PUNCT
brj-23254	293	8	liang	liang	PROPN
brj-23254	293	9	,	,	PUNCT
brj-23254	293	10	c.	c.	PROPN
brj-23254	293	11	,	,	PUNCT
brj-23254	293	12	guo	guo	PROPN
brj-23254	293	13	,	,	PUNCT
brj-23254	293	14	y.	y.	PROPN
brj-23254	293	15	,	,	PUNCT
brj-23254	293	16	tang	tang	PROPN
brj-23254	293	17	,	,	PUNCT
brj-23254	293	18	x.	x.	NOUN
brj-23254	293	19	,	,	PUNCT
brj-23254	293	20	jahanbanifard	jahanbanifard	NOUN
brj-23254	293	21	,	,	PUNCT
brj-23254	293	22	m.	m.	NOUN
brj-23254	293	23	,	,	PUNCT
brj-23254	293	24	silva	silva	PROPN
brj-23254	293	25	,	,	PUNCT
brj-23254	293	26	f.	f.	PROPN
brj-23254	293	27	s.	s.	PROPN
brj-23254	293	28	c.	c.	PROPN
brj-23254	293	29	,	,	PUNCT
brj-23254	293	30	ceccantini	ceccantini	PROPN
brj-23254	293	31	,	,	PUNCT
brj-23254	293	32	g.	g.	PROPN
brj-23254	293	33	,	,	PUNCT
brj-23254	293	34	and	and	CCONJ
brj-23254	293	35	verbeek	verbeek	NOUN
brj-23254	293	36	,	,	PUNCT
brj-23254	293	37	f.	f.	PROPN
brj-23254	293	38	j.	j.	PROPN
brj-23254	293	39	(	(	PUNCT
brj-23254	293	40	2020	2020	NUM
brj-23254	293	41	)	)	PUNCT
brj-23254	293	42	.	.	PUNCT
brj-23254	294	1	“	"	PUNCT
brj-23254	294	2	computer	computer	NOUN
brj-23254	294	3	-	-	PUNCT
brj-23254	294	4	assisted	assist	VERB
brj-23254	294	5	timber	timber	NOUN
brj-23254	294	6	identification	identification	NOUN
brj-23254	294	7	based	base	VERB
brj-23254	294	8	on	on	ADP
brj-23254	294	9	features	feature	NOUN
brj-23254	294	10	extracted	extract	VERB
brj-23254	294	11	from	from	ADP
brj-23254	294	12	microscopic	microscopic	ADJ
brj-23254	294	13	wood	wood	NOUN
brj-23254	294	14	sections	section	NOUN
brj-23254	294	15	,	,	PUNCT
brj-23254	294	16	”	"	PUNCT
brj-23254	294	17	iawa	iawa	PROPN
brj-23254	294	18	journal	journal	PROPN
brj-23254	294	19	41(4	41(4	NUM
brj-23254	294	20	)	)	PUNCT
brj-23254	294	21	,	,	PUNCT
brj-23254	294	22	660	660	NUM
brj-23254	294	23	-	-	SYM
brj-23254	294	24	680	680	NUM
brj-23254	294	25	.	.	PUNCT
brj-23254	294	26	lopes	lopes	PROPN
brj-23254	294	27	,	,	PUNCT
brj-23254	294	28	d.	d.	PROPN
brj-23254	294	29	j.	j.	PROPN
brj-23254	294	30	v.	v.	PROPN
brj-23254	294	31	,	,	PUNCT
brj-23254	294	32	burgreen	burgreen	PROPN
brj-23254	294	33	,	,	PUNCT
brj-23254	294	34	g.	g.	PROPN
brj-23254	294	35	w.	w.	PROPN
brj-23254	294	36	,	,	PUNCT
brj-23254	294	37	and	and	CCONJ
brj-23254	294	38	entsminger	entsminger	NOUN
brj-23254	294	39	,	,	PUNCT
brj-23254	294	40	e.	e.	PROPN
brj-23254	294	41	d.	d.	PROPN
brj-23254	294	42	(	(	PUNCT
brj-23254	294	43	2020	2020	NUM
brj-23254	294	44	)	)	PUNCT
brj-23254	294	45	.	.	PUNCT
brj-23254	295	1	“	"	PUNCT
brj-23254	295	2	north	north	ADJ
brj-23254	295	3	american	american	ADJ
brj-23254	295	4	hardwoods	hardwood	NOUN
brj-23254	295	5	identification	identification	NOUN
brj-23254	295	6	using	use	VERB
brj-23254	295	7	machine	machine	NOUN
brj-23254	295	8	-	-	PUNCT
brj-23254	295	9	learning	learning	NOUN
brj-23254	295	10	,	,	PUNCT
brj-23254	295	11	”	"	PUNCT
brj-23254	295	12	forests	forest	NOUN
brj-23254	295	13	11(3	11(3	NUM
brj-23254	295	14	)	)	PUNCT
brj-23254	295	15	,	,	PUNCT
brj-23254	295	16	article	article	NOUN
brj-23254	295	17	298	298	NUM
brj-23254	295	18	.	.	PUNCT
brj-23254	296	1	doi	doi	NOUN
brj-23254	296	2	:	:	PUNCT
brj-23254	296	3	10.3390	10.3390	NUM
brj-23254	296	4	/	/	SYM
brj-23254	296	5	f11030298	f11030298	PROPN
brj-23254	296	6	moulin	moulin	PROPN
brj-23254	296	7	,	,	PUNCT
brj-23254	296	8	j.	j.	PROPN
brj-23254	296	9	c.	c.	PROPN
brj-23254	296	10	,	,	PUNCT
brj-23254	296	11	lopes	lopes	PROPN
brj-23254	296	12	,	,	PUNCT
brj-23254	296	13	d.	d.	PROPN
brj-23254	296	14	j.	j.	PROPN
brj-23254	296	15	v.	v.	PROPN
brj-23254	296	16	,	,	PUNCT
brj-23254	296	17	mulin	mulin	PROPN
brj-23254	296	18	,	,	PUNCT
brj-23254	296	19	l.	l.	PROPN
brj-23254	296	20	b.	b.	PROPN
brj-23254	296	21	,	,	PUNCT
brj-23254	296	22	bobadilha	bobadilha	NOUN
brj-23254	296	23	,	,	PUNCT
brj-23254	296	24	g.	g.	PROPN
brj-23254	296	25	d.	d.	PROPN
brj-23254	296	26	s.	s.	PROPN
brj-23254	296	27	,	,	PUNCT
brj-23254	296	28	and	and	CCONJ
brj-23254	296	29	oliveira	oliveira	PROPN
brj-23254	296	30	,	,	PUNCT
brj-23254	296	31	r.	r.	PROPN
brj-23254	296	32	f.	f.	PROPN
brj-23254	296	33	(	(	PUNCT
brj-23254	296	34	2022	2022	NUM
brj-23254	296	35	)	)	PUNCT
brj-23254	296	36	.	.	PUNCT
brj-23254	297	1	“	"	PUNCT
brj-23254	297	2	microscopic	microscopic	ADJ
brj-23254	297	3	identification	identification	NOUN
brj-23254	297	4	of	of	ADP
brj-23254	297	5	brazilian	brazilian	ADJ
brj-23254	297	6	commercial	commercial	ADJ
brj-23254	297	7	wood	wood	NOUN
brj-23254	297	8	species	specie	NOUN
brj-23254	297	9	via	via	ADP
brj-23254	297	10	machine	machine	NOUN
brj-23254	297	11	-	-	PUNCT
brj-23254	297	12	learning	learning	NOUN
brj-23254	297	13	,	,	PUNCT
brj-23254	297	14	”	"	PUNCT
brj-23254	297	15	cerne	cerne	NOUN
brj-23254	297	16	28	28	NUM
brj-23254	297	17	,	,	PUNCT
brj-23254	297	18	article	article	NOUN
brj-23254	297	19	e-102978	e-102978	PROPN
brj-23254	297	20	.	.	PROPN
brj-23254	297	21	doi	doi	PROPN
brj-23254	297	22	:	:	PUNCT
brj-23254	297	23	10.1590/01047760202228012978	10.1590/01047760202228012978	NUM
brj-23254	297	24	oktaria	oktaria	NOUN
brj-23254	297	25	,	,	PUNCT
brj-23254	297	26	a.	a.	PROPN
brj-23254	297	27	s.	s.	PROPN
brj-23254	297	28	,	,	PUNCT
brj-23254	297	29	prakasa	prakasa	PROPN
brj-23254	297	30	,	,	PUNCT
brj-23254	297	31	e.	e.	PROPN
brj-23254	297	32	,	,	PUNCT
brj-23254	297	33	suhartono	suhartono	PROPN
brj-23254	297	34	,	,	PUNCT
brj-23254	297	35	e.	e.	PROPN
brj-23254	297	36	,	,	PUNCT
brj-23254	297	37	sugiarto	sugiarto	PROPN
brj-23254	297	38	,	,	PUNCT
brj-23254	297	39	b.	b.	PROPN
brj-23254	297	40	,	,	PUNCT
brj-23254	297	41	prajitno	prajitno	PROPN
brj-23254	297	42	,	,	PUNCT
brj-23254	297	43	d.	d.	PROPN
brj-23254	297	44	r.	r.	PROPN
brj-23254	297	45	,	,	PUNCT
brj-23254	297	46	and	and	CCONJ
brj-23254	297	47	wardoyo	wardoyo	PROPN
brj-23254	297	48	,	,	PUNCT
brj-23254	297	49	r.	r.	PROPN
brj-23254	297	50	(	(	PUNCT
brj-23254	297	51	2019	2019	NUM
brj-23254	297	52	)	)	PUNCT
brj-23254	297	53	.	.	PUNCT
brj-23254	298	1	“	"	PUNCT
brj-23254	298	2	wood	wood	NOUN
brj-23254	298	3	species	species	NOUN
brj-23254	298	4	identification	identification	NOUN
brj-23254	298	5	using	use	VERB
brj-23254	298	6	convolutional	convolutional	ADJ
brj-23254	298	7	neural	neural	ADJ
brj-23254	298	8	network	network	NOUN
brj-23254	298	9	(	(	PUNCT
brj-23254	298	10	cnn	cnn	PROPN
brj-23254	298	11	)	)	PUNCT
brj-23254	298	12	architectures	architecture	NOUN
brj-23254	298	13	on	on	ADP
brj-23254	298	14	macroscopic	macroscopic	ADJ
brj-23254	298	15	images	image	NOUN
brj-23254	298	16	,	,	PUNCT
brj-23254	298	17	”	"	PUNCT
brj-23254	298	18	journal	journal	NOUN
brj-23254	298	19	of	of	ADP
brj-23254	298	20	information	information	NOUN
brj-23254	298	21	technology	technology	NOUN
brj-23254	298	22	and	and	CCONJ
brj-23254	298	23	computer	computer	NOUN
brj-23254	298	24	science	science	NOUN
brj-23254	298	25	4	4	NUM
brj-23254	298	26	,	,	PUNCT
brj-23254	298	27	274	274	NUM
brj-23254	298	28	-	-	SYM
brj-23254	298	29	283	283	NUM
brj-23254	298	30	.	.	PUNCT
brj-23254	299	1	doi	doi	NOUN
brj-23254	299	2	:	:	PUNCT
brj-23254	299	3	10.25126	10.25126	NUM
brj-23254	299	4	/	/	SYM
brj-23254	299	5	jitecs.201943155	jitecs.201943155	X
brj-23254	299	6	ravindran	ravindran	NOUN
brj-23254	299	7	,	,	PUNCT
brj-23254	299	8	p.	p.	PROPN
brj-23254	299	9	,	,	PUNCT
brj-23254	299	10	wade	wade	PROPN
brj-23254	299	11	,	,	PUNCT
brj-23254	299	12	a.	a.	PROPN
brj-23254	299	13	c.	c.	PROPN
brj-23254	299	14	,	,	PUNCT
brj-23254	299	15	owens	owens	PROPN
brj-23254	299	16	,	,	PUNCT
brj-23254	299	17	f.	f.	PROPN
brj-23254	299	18	c.	c.	PROPN
brj-23254	299	19	,	,	PUNCT
brj-23254	299	20	shmulsky	shmulsky	ADV
brj-23254	299	21	,	,	PUNCT
brj-23254	299	22	r.	r.	PROPN
brj-23254	299	23	,	,	PUNCT
brj-23254	299	24	and	and	CCONJ
brj-23254	299	25	wiedenhoeft	wiedenhoeft	VERB
brj-23254	299	26	,	,	PUNCT
brj-23254	299	27	a.	a.	PROPN
brj-23254	299	28	c.	c.	PROPN
brj-23254	299	29	(	(	PUNCT
brj-23254	299	30	2022	2022	NUM
brj-23254	299	31	)	)	PUNCT
brj-23254	299	32	.	.	PUNCT
brj-23254	300	1	“	"	PUNCT
brj-23254	300	2	towards	towards	ADP
brj-23254	300	3	sustainable	sustainable	ADJ
brj-23254	300	4	north	north	ADJ
brj-23254	300	5	american	american	ADJ
brj-23254	300	6	wood	wood	NOUN
brj-23254	300	7	product	product	NOUN
brj-23254	300	8	value	value	NOUN
brj-23254	300	9	chains	chain	NOUN
brj-23254	300	10	,	,	PUNCT
brj-23254	300	11	part	part	NOUN
brj-23254	300	12	2	2	NUM
brj-23254	300	13	:	:	PUNCT
brj-23254	300	14	computer	computer	NOUN
brj-23254	300	15	vision	vision	NOUN
brj-23254	300	16	identification	identification	NOUN
brj-23254	300	17	of	of	ADP
brj-23254	300	18	ring	ring	NOUN
brj-23254	300	19	-	-	PUNCT
brj-23254	300	20	porous	porous	ADJ
brj-23254	300	21	hardwood	hardwood	NOUN
brj-23254	300	22	,	,	PUNCT
brj-23254	300	23	”	"	PUNCT
brj-23254	300	24	canadian	canadian	ADJ
brj-23254	300	25	journal	journal	NOUN
brj-23254	300	26	of	of	ADP
brj-23254	300	27	forest	forest	PROPN
brj-23254	300	28	research	research	NOUN
brj-23254	300	29	52	52	NUM
brj-23254	300	30	,	,	PUNCT
brj-23254	300	31	1014	1014	NUM
brj-23254	300	32	-	-	SYM
brj-23254	300	33	1027	1027	NUM
brj-23254	300	34	.	.	PUNCT
brj-23254	301	1	doi	doi	NOUN
brj-23254	301	2	:	:	PUNCT
brj-23254	301	3	10.1139	10.1139	NUM
brj-23254	301	4	/	/	SYM
brj-23254	301	5	cjfr-2022	cjfr-2022	NOUN
brj-23254	301	6	-	-	PUNCT
brj-23254	301	7	0077	0077	NUM
brj-23254	301	8	sherstinsky	sherstinsky	NOUN
brj-23254	301	9	,	,	PUNCT
brj-23254	301	10	a.	a.	NOUN
brj-23254	301	11	(	(	PUNCT
brj-23254	301	12	2020	2020	NUM
brj-23254	301	13	)	)	PUNCT
brj-23254	301	14	.	.	PUNCT
brj-23254	302	1	“	"	PUNCT
brj-23254	302	2	fundamentals	fundamental	NOUN
brj-23254	302	3	of	of	ADP
brj-23254	302	4	recurrent	recurrent	ADJ
brj-23254	302	5	neural	neural	ADJ
brj-23254	302	6	network	network	NOUN
brj-23254	302	7	(	(	PUNCT
brj-23254	302	8	rnn	rnn	PROPN
brj-23254	302	9	)	)	PUNCT
brj-23254	302	10	and	and	CCONJ
brj-23254	302	11	long	long	ADJ
brj-23254	302	12	short	short	ADJ
brj-23254	302	13	-	-	PUNCT
brj-23254	302	14	term	term	NOUN
brj-23254	302	15	memory	memory	NOUN
brj-23254	302	16	(	(	PUNCT
brj-23254	302	17	lstm	lstm	NOUN
brj-23254	302	18	)	)	PUNCT
brj-23254	302	19	network	network	NOUN
brj-23254	302	20	,	,	PUNCT
brj-23254	302	21	”	"	PUNCT
brj-23254	302	22	physica	physica	NOUN
brj-23254	302	23	d	d	NOUN
brj-23254	302	24	:	:	PUNCT
brj-23254	302	25	nonlinear	nonlinear	ADJ
brj-23254	302	26	phenomena	phenomena	NOUN
brj-23254	302	27	404	404	NUM
brj-23254	302	28	,	,	PUNCT
brj-23254	302	29	article	article	NOUN
brj-23254	302	30	i	i	PROPN
brj-23254	302	31	d	d	PROPN
brj-23254	302	32	132306	132306	NUM
brj-23254	302	33	.	.	PUNCT
brj-23254	303	1	doi	doi	NOUN
brj-23254	303	2	:	:	PUNCT
brj-23254	303	3	10.1016	10.1016	NUM
brj-23254	303	4	/	/	SYM
brj-23254	303	5	j.physd.2019.132306	j.physd.2019.132306	PROPN
brj-23254	303	6	sun	sun	PROPN
brj-23254	303	7	,	,	PUNCT
brj-23254	303	8	y.	y.	PROPN
brj-23254	303	9	,	,	PUNCT
brj-23254	303	10	lin	lin	PROPN
brj-23254	303	11	,	,	PUNCT
brj-23254	303	12	q.	q.	PROPN
brj-23254	303	13	,	,	PUNCT
brj-23254	303	14	he	he	PRON
brj-23254	303	15	,	,	PUNCT
brj-23254	303	16	x.	x.	PROPN
brj-23254	303	17	,	,	PUNCT
brj-23254	303	18	zhao	zhao	PROPN
brj-23254	303	19	,	,	PUNCT
brj-23254	303	20	y.	y.	PROPN
brj-23254	303	21	,	,	PUNCT
brj-23254	303	22	dai	dai	PROPN
brj-23254	303	23	,	,	PUNCT
brj-23254	303	24	f.	f.	PROPN
brj-23254	303	25	,	,	PUNCT
brj-23254	303	26	qiu	qiu	PROPN
brj-23254	303	27	,	,	PUNCT
brj-23254	303	28	j.	j.	PROPN
brj-23254	303	29	,	,	PUNCT
brj-23254	303	30	and	and	CCONJ
brj-23254	303	31	cao	cao	PROPN
brj-23254	303	32	,	,	PUNCT
brj-23254	303	33	y.	y.	PROPN
brj-23254	303	34	(	(	PUNCT
brj-23254	303	35	2021	2021	NUM
brj-23254	303	36	)	)	PUNCT
brj-23254	303	37	.	.	PUNCT
brj-23254	304	1	“	"	PUNCT
brj-23254	304	2	wood	wood	NOUN
brj-23254	304	3	species	species	NOUN
brj-23254	304	4	recognition	recognition	NOUN
brj-23254	304	5	with	with	ADP
brj-23254	304	6	small	small	ADJ
brj-23254	304	7	data	datum	NOUN
brj-23254	304	8	:	:	PUNCT
brj-23254	304	9	a	a	DET
brj-23254	304	10	deep	deep	ADJ
brj-23254	304	11	learning	learning	NOUN
brj-23254	304	12	approach	approach	NOUN
brj-23254	304	13	,	,	PUNCT
brj-23254	304	14	”	"	PUNCT
brj-23254	304	15	international	international	ADJ
brj-23254	304	16	journal	journal	NOUN
brj-23254	304	17	of	of	ADP
brj-23254	304	18	computational	computational	ADJ
brj-23254	304	19	intelligence	intelligence	NOUN
brj-23254	304	20	systems	system	NOUN
brj-23254	304	21	14(1	14(1	NUM
brj-23254	304	22	)	)	PUNCT
brj-23254	304	23	,	,	PUNCT
brj-23254	304	24	1451–1460	1451–1460	NUM
brj-23254	304	25	.	.	PUNCT
brj-23254	305	1	doi	doi	NOUN
brj-23254	305	2	:	:	PUNCT
brj-23254	305	3	10.2991	10.2991	NUM
brj-23254	305	4	/	/	SYM
brj-23254	305	5	ijcis.d.210423.001	ijcis.d.210423.001	PROPN
brj-23254	305	6	article	article	NOUN
brj-23254	305	7	submitted	submit	VERB
brj-23254	305	8	:	:	PUNCT
brj-23254	305	9	january	january	PROPN
brj-23254	305	10	8	8	NUM
brj-23254	305	11	,	,	PUNCT
brj-23254	305	12	2024	2024	NUM
brj-23254	305	13	;	;	PUNCT
brj-23254	305	14	peer	peer	NOUN
brj-23254	305	15	review	review	NOUN
brj-23254	305	16	completed	complete	VERB
brj-23254	305	17	:	:	PUNCT
brj-23254	305	18	february	february	PROPN
brj-23254	305	19	11	11	NUM
brj-23254	305	20	,	,	PUNCT
brj-23254	305	21	2024	2024	NUM
brj-23254	305	22	;	;	PUNCT
brj-23254	305	23	revised	revise	VERB
brj-23254	305	24	version	version	NOUN
brj-23254	305	25	received	receive	VERB
brj-23254	305	26	and	and	CCONJ
brj-23254	305	27	accepted	accept	VERB
brj-23254	305	28	:	:	PUNCT
brj-23254	305	29	february	february	PROPN
brj-23254	305	30	25	25	NUM
brj-23254	305	31	,	,	PUNCT
brj-23254	305	32	2024	2024	NUM
brj-23254	305	33	;	;	PUNCT
brj-23254	305	34	published	publish	VERB
brj-23254	305	35	:	:	PUNCT
brj-23254	305	36	may	may	AUX
brj-23254	305	37	31	31	NUM
brj-23254	305	38	,	,	PUNCT
brj-23254	305	39	2024	2024	NUM
brj-23254	305	40	.	.	PUNCT
brj-23254	306	1	doi	doi	NOUN
brj-23254	306	2	:	:	PUNCT
brj-23254	306	3	10.15376	10.15376	NUM
brj-23254	306	4	/	/	SYM
brj-23254	306	5	biores.19.3.4838	biores.19.3.4838	PROPN
brj-23254	306	6	-	-	PUNCT
brj-23254	306	7	4851	4851	NUM