id	sid	tid	token	lemma	pos
brj-22966	1	1	peer	peer	NOUN
brj-22966	1	2	-	-	PUNCT
brj-22966	1	3	reviewed	review	VERB
brj-22966	1	4	article	article	NOUN
brj-22966	1	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	1	6	kim	kim	PROPN
brj-22966	1	7	et	et	PROPN
brj-22966	1	8	al	al	PROPN
brj-22966	1	9	.	.	PROPN
brj-22966	2	1	(	(	PUNCT
brj-22966	2	2	2024	2024	NUM
brj-22966	2	3	)	)	PUNCT
brj-22966	2	4	.	.	PUNCT
brj-22966	3	1	“	"	PUNCT
brj-22966	3	2	convolutional	convolutional	ADJ
brj-22966	3	3	neural	neural	ADJ
brj-22966	3	4	network	network	NOUN
brj-22966	3	5	,	,	PUNCT
brj-22966	3	6	”	"	PUNCT
brj-22966	3	7	bioresources	bioresource	NOUN
brj-22966	3	8	19(1	19(1	NUM
brj-22966	3	9	)	)	PUNCT
brj-22966	3	10	,	,	PUNCT
brj-22966	3	11	510	510	NUM
brj-22966	3	12	-	-	SYM
brj-22966	3	13	524	524	NUM
brj-22966	3	14	.	.	PUNCT
brj-22966	4	1	510	510	NUM
brj-22966	4	2	convolutional	convolutional	ADJ
brj-22966	4	3	neural	neural	ADJ
brj-22966	4	4	network	network	NOUN
brj-22966	4	5	performance	performance	NOUN
brj-22966	4	6	and	and	CCONJ
brj-22966	4	7	the	the	DET
brj-22966	4	8	factors	factor	NOUN
brj-22966	4	9	affecting	affect	VERB
brj-22966	4	10	performance	performance	NOUN
brj-22966	4	11	for	for	ADP
brj-22966	4	12	classification	classification	NOUN
brj-22966	4	13	of	of	ADP
brj-22966	4	14	seven	seven	NUM
brj-22966	4	15	quercus	quercus	ADJ
brj-22966	4	16	species	specie	NOUN
brj-22966	4	17	using	use	VERB
brj-22966	4	18	sclereid	sclereid	NOUN
brj-22966	4	19	characteristics	characteristic	NOUN
brj-22966	4	20	in	in	ADP
brj-22966	4	21	the	the	DET
brj-22966	4	22	bark	bark	NOUN
brj-22966	4	23	jong	jong	PROPN
brj-22966	4	24	ho	ho	PROPN
brj-22966	4	25	kim	kim	PROPN
brj-22966	4	26	,	,	PUNCT
brj-22966	4	27	a	a	DET
brj-22966	4	28	byantara	byantara	NOUN
brj-22966	4	29	darsan	darsan	ADJ
brj-22966	4	30	purusatama	purusatama	NOUN
brj-22966	4	31	,	,	PUNCT
brj-22966	4	32	b	b	PROPN
brj-22966	4	33	alvin	alvin	PROPN
brj-22966	4	34	muhammad	muhammad	PROPN
brj-22966	4	35	savero	savero	PROPN
brj-22966	4	36	,	,	PUNCT
brj-22966	4	37	a	a	DET
brj-22966	4	38	denni	denni	PROPN
brj-22966	4	39	prasetia	prasetia	NOUN
brj-22966	4	40	,	,	PUNCT
brj-22966	4	41	a	a	DET
brj-22966	4	42	jae	jae	PROPN
brj-22966	4	43	hyuk	hyuk	PROPN
brj-22966	4	44	jang	jang	PROPN
brj-22966	4	45	,	,	PUNCT
brj-22966	4	46	c	c	PROPN
brj-22966	4	47	se	se	PROPN
brj-22966	4	48	yeong	yeong	PROPN
brj-22966	4	49	park	park	PROPN
brj-22966	4	50	,	,	PUNCT
brj-22966	4	51	a	a	DET
brj-22966	4	52	seung	seung	PROPN
brj-22966	4	53	hwan	hwan	PROPN
brj-22966	4	54	lee	lee	PROPN
brj-22966	4	55	,	,	PUNCT
brj-22966	4	56	a	a	PRON
brj-22966	4	57	and	and	CCONJ
brj-22966	4	58	nam	nam	PROPN
brj-22966	4	59	hun	hun	PROPN
brj-22966	4	60	kim	kim	PROPN
brj-22966	4	61	a	a	PROPN
brj-22966	4	62	,	,	PUNCT
brj-22966	4	63	*	*	PUNCT
brj-22966	4	64	based	base	VERB
brj-22966	4	65	on	on	ADP
brj-22966	4	66	the	the	DET
brj-22966	4	67	sclereids	sclereid	NOUN
brj-22966	4	68	in	in	ADP
brj-22966	4	69	the	the	DET
brj-22966	4	70	bark	bark	NOUN
brj-22966	4	71	of	of	ADP
brj-22966	4	72	oak	oak	NOUN
brj-22966	4	73	species	specie	NOUN
brj-22966	4	74	,	,	PUNCT
brj-22966	4	75	a	a	DET
brj-22966	4	76	convolutional	convolutional	ADJ
brj-22966	4	77	neural	neural	ADJ
brj-22966	4	78	network	network	NOUN
brj-22966	4	79	(	(	PUNCT
brj-22966	4	80	cnn	cnn	PROPN
brj-22966	4	81	)	)	PUNCT
brj-22966	4	82	was	be	AUX
brj-22966	4	83	employed	employ	VERB
brj-22966	4	84	to	to	PART
brj-22966	4	85	validate	validate	VERB
brj-22966	4	86	species	specie	NOUN
brj-22966	4	87	classification	classification	NOUN
brj-22966	4	88	performance	performance	NOUN
brj-22966	4	89	and	and	CCONJ
brj-22966	4	90	its	its	PRON
brj-22966	4	91	influencing	influence	VERB
brj-22966	4	92	factors	factor	NOUN
brj-22966	4	93	.	.	PUNCT
brj-22966	5	1	three	three	NUM
brj-22966	5	2	optimizers	optimizer	NOUN
brj-22966	5	3	including	include	VERB
brj-22966	5	4	stochastic	stochastic	ADJ
brj-22966	5	5	gradient	gradient	ADJ
brj-22966	5	6	descent	descent	NOUN
brj-22966	5	7	(	(	PUNCT
brj-22966	5	8	sgd	sgd	PROPN
brj-22966	5	9	)	)	PUNCT
brj-22966	5	10	,	,	PUNCT
brj-22966	5	11	adaptive	adaptive	ADJ
brj-22966	5	12	moment	moment	NOUN
brj-22966	5	13	estimation	estimation	NOUN
brj-22966	5	14	(	(	PUNCT
brj-22966	5	15	adam	adam	PROPN
brj-22966	5	16	)	)	PUNCT
brj-22966	5	17	,	,	PUNCT
brj-22966	5	18	root	root	NOUN
brj-22966	5	19	mean	mean	VERB
brj-22966	5	20	square	square	ADJ
brj-22966	5	21	propagation	propagation	NOUN
brj-22966	5	22	(	(	PUNCT
brj-22966	5	23	rmsprop	rmsprop	NOUN
brj-22966	5	24	)	)	PUNCT
brj-22966	5	25	,	,	PUNCT
brj-22966	5	26	and	and	CCONJ
brj-22966	5	27	dataset	dataset	NOUN
brj-22966	5	28	augmentation	augmentation	NOUN
brj-22966	5	29	were	be	AUX
brj-22966	5	30	adopted	adopt	VERB
brj-22966	5	31	.	.	PUNCT
brj-22966	6	1	the	the	DET
brj-22966	6	2	accuracy	accuracy	NOUN
brj-22966	6	3	and	and	CCONJ
brj-22966	6	4	loss	loss	NOUN
brj-22966	6	5	stabilized	stabilize	VERB
brj-22966	6	6	at	at	ADP
brj-22966	6	7	approximately	approximately	ADV
brj-22966	6	8	15	15	NUM
brj-22966	6	9	to	to	PART
brj-22966	6	10	20	20	NUM
brj-22966	6	11	and	and	CCONJ
brj-22966	6	12	70	70	NUM
brj-22966	6	13	to	to	PART
brj-22966	6	14	80	80	NUM
brj-22966	6	15	epochs	epoch	NOUN
brj-22966	6	16	for	for	ADP
brj-22966	6	17	the	the	DET
brj-22966	6	18	augmented	augment	VERB
brj-22966	6	19	and	and	CCONJ
brj-22966	6	20	non	non	ADJ
brj-22966	6	21	-	-	ADJ
brj-22966	6	22	augmented	augmented	ADJ
brj-22966	6	23	condition	condition	NOUN
brj-22966	6	24	,	,	PUNCT
brj-22966	6	25	respectively	respectively	ADV
brj-22966	6	26	.	.	PUNCT
brj-22966	7	1	in	in	ADP
brj-22966	7	2	the	the	DET
brj-22966	7	3	last	last	ADJ
brj-22966	7	4	five	five	NUM
brj-22966	7	5	epochs	epoch	NOUN
brj-22966	7	6	,	,	PUNCT
brj-22966	7	7	the	the	DET
brj-22966	7	8	rmsprop	rmsprop	NOUN
brj-22966	7	9	-	-	PUNCT
brj-22966	7	10	augmented	augment	VERB
brj-22966	7	11	condition	condition	NOUN
brj-22966	7	12	achieved	achieve	VERB
brj-22966	7	13	the	the	DET
brj-22966	7	14	highest	high	ADJ
brj-22966	7	15	accuracy	accuracy	NOUN
brj-22966	7	16	of	of	ADP
brj-22966	7	17	89.8	89.8	NUM
brj-22966	7	18	%	%	NOUN
brj-22966	7	19	,	,	PUNCT
brj-22966	7	20	whereas	whereas	SCONJ
brj-22966	7	21	the	the	DET
brj-22966	7	22	adam	adam	NOUN
brj-22966	7	23	-	-	PUNCT
brj-22966	7	24	augmented	augment	VERB
brj-22966	7	25	condition	condition	NOUN
brj-22966	7	26	achieved	achieve	VERB
brj-22966	7	27	the	the	DET
brj-22966	7	28	lowest	low	ADJ
brj-22966	7	29	accuracy	accuracy	NOUN
brj-22966	7	30	of	of	ADP
brj-22966	7	31	73.8	73.8	NUM
brj-22966	7	32	%	%	NOUN
brj-22966	7	33	.	.	PUNCT
brj-22966	8	1	regarding	regard	VERB
brj-22966	8	2	the	the	DET
brj-22966	8	3	loss	loss	NOUN
brj-22966	8	4	,	,	PUNCT
brj-22966	8	5	sgd	sgd	NOUN
brj-22966	8	6	-	-	PUNCT
brj-22966	8	7	non	non	ADJ
brj-22966	8	8	-	-	ADJ
brj-22966	8	9	augmented	augmented	ADJ
brj-22966	8	10	condition	condition	NOUN
brj-22966	8	11	was	be	AUX
brj-22966	8	12	the	the	DET
brj-22966	8	13	lowest	low	ADJ
brj-22966	8	14	at	at	ADP
brj-22966	8	15	0.498	0.498	NUM
brj-22966	8	16	,	,	PUNCT
brj-22966	8	17	whereas	whereas	SCONJ
brj-22966	8	18	adamaugmented	adamaugmented	ADJ
brj-22966	8	19	condition	condition	NOUN
brj-22966	8	20	was	be	AUX
brj-22966	8	21	the	the	DET
brj-22966	8	22	highest	high	ADJ
brj-22966	8	23	at	at	ADP
brj-22966	8	24	2.740	2.740	NUM
brj-22966	8	25	.	.	PUNCT
brj-22966	9	1	the	the	DET
brj-22966	9	2	highest	high	ADJ
brj-22966	9	3	accuracy	accuracy	NOUN
brj-22966	9	4	was	be	AUX
brj-22966	9	5	influenced	influence	VERB
brj-22966	9	6	by	by	ADP
brj-22966	9	7	rmsprop	rmsprop	NOUN
brj-22966	9	8	at	at	ADP
brj-22966	9	9	0.194	0.194	NUM
brj-22966	9	10	.	.	PUNCT
brj-22966	10	1	dataset	dataset	NOUN
brj-22966	10	2	augmentation	augmentation	NOUN
brj-22966	10	3	had	have	VERB
brj-22966	10	4	a	a	DET
brj-22966	10	5	significant	significant	ADJ
brj-22966	10	6	influence	influence	NOUN
brj-22966	10	7	on	on	ADP
brj-22966	10	8	accuracy	accuracy	NOUN
brj-22966	10	9	at	at	ADP
brj-22966	10	10	0.456	0.456	NUM
brj-22966	10	11	.	.	PUNCT
brj-22966	11	1	homogeneous	homogeneous	ADJ
brj-22966	11	2	subsets	subset	NOUN
brj-22966	11	3	among	among	ADP
brj-22966	11	4	the	the	DET
brj-22966	11	5	validation	validation	NOUN
brj-22966	11	6	conditions	condition	NOUN
brj-22966	11	7	indicated	indicate	VERB
brj-22966	11	8	that	that	SCONJ
brj-22966	11	9	the	the	DET
brj-22966	11	10	accuracy	accuracy	NOUN
brj-22966	11	11	and	and	CCONJ
brj-22966	11	12	loss	loss	NOUN
brj-22966	11	13	were	be	AUX
brj-22966	11	14	classified	classify	VERB
brj-22966	11	15	into	into	ADP
brj-22966	11	16	the	the	DET
brj-22966	11	17	same	same	ADJ
brj-22966	11	18	subset	subset	NOUN
brj-22966	11	19	using	use	VERB
brj-22966	11	20	an	an	DET
brj-22966	11	21	augmented	augment	VERB
brj-22966	11	22	dataset	dataset	NOUN
brj-22966	11	23	during	during	ADP
brj-22966	11	24	the	the	DET
brj-22966	11	25	training	training	NOUN
brj-22966	11	26	,	,	PUNCT
brj-22966	11	27	regardless	regardless	ADV
brj-22966	11	28	of	of	ADP
brj-22966	11	29	the	the	DET
brj-22966	11	30	optimizer	optimizer	NOUN
brj-22966	11	31	.	.	PUNCT
brj-22966	12	1	only	only	ADV
brj-22966	12	2	adam	adam	PROPN
brj-22966	12	3	and	and	CCONJ
brj-22966	12	4	rmsprop	rmsprop	NOUN
brj-22966	12	5	with	with	ADP
brj-22966	12	6	nonaugmented	nonaugmented	ADJ
brj-22966	12	7	datasets	dataset	NOUN
brj-22966	12	8	were	be	AUX
brj-22966	12	9	categorized	categorize	VERB
brj-22966	12	10	into	into	ADP
brj-22966	12	11	the	the	DET
brj-22966	12	12	same	same	ADJ
brj-22966	12	13	subset	subset	NOUN
brj-22966	12	14	during	during	ADP
brj-22966	12	15	the	the	DET
brj-22966	12	16	test	test	NOUN
brj-22966	12	17	.	.	PUNCT
brj-22966	13	1	hence	hence	ADV
brj-22966	13	2	,	,	PUNCT
brj-22966	13	3	species	species	NOUN
brj-22966	13	4	classification	classification	NOUN
brj-22966	13	5	using	use	VERB
brj-22966	13	6	cnn	cnn	PROPN
brj-22966	13	7	and	and	CCONJ
brj-22966	13	8	sclereid	sclereid	NOUN
brj-22966	13	9	characteristics	characteristic	NOUN
brj-22966	13	10	in	in	ADP
brj-22966	13	11	the	the	DET
brj-22966	13	12	bark	bark	NOUN
brj-22966	13	13	was	be	AUX
brj-22966	13	14	feasible	feasible	ADJ
brj-22966	13	15	,	,	PUNCT
brj-22966	13	16	and	and	CCONJ
brj-22966	13	17	rmsprop	rmsprop	NOUN
brj-22966	13	18	with	with	ADP
brj-22966	13	19	augmented	augment	VERB
brj-22966	13	20	datasets	dataset	NOUN
brj-22966	13	21	showed	show	VERB
brj-22966	13	22	optimal	optimal	ADJ
brj-22966	13	23	performance	performance	NOUN
brj-22966	13	24	for	for	ADP
brj-22966	13	25	species	specie	NOUN
brj-22966	13	26	classification	classification	NOUN
brj-22966	13	27	.	.	PUNCT
brj-22966	14	1	doi	doi	NOUN
brj-22966	14	2	:	:	PUNCT
brj-22966	14	3	10.15376	10.15376	NUM
brj-22966	14	4	/	/	SYM
brj-22966	14	5	biores.19.1.510	biores.19.1.510	VERB
brj-22966	14	6	-	-	SYM
brj-22966	14	7	524	524	NUM
brj-22966	14	8	keywords	keyword	NOUN
brj-22966	14	9	:	:	PUNCT
brj-22966	14	10	bark	bark	NOUN
brj-22966	14	11	;	;	PUNCT
brj-22966	14	12	convolutional	convolutional	ADJ
brj-22966	14	13	neural	neural	ADJ
brj-22966	14	14	networks	network	NOUN
brj-22966	14	15	(	(	PUNCT
brj-22966	14	16	cnns	cnns	PROPN
brj-22966	14	17	)	)	PUNCT
brj-22966	14	18	;	;	PUNCT
brj-22966	14	19	oak	oak	NOUN
brj-22966	14	20	;	;	PUNCT
brj-22966	14	21	sclereids	sclereid	NOUN
brj-22966	14	22	;	;	PUNCT
brj-22966	14	23	species	specie	NOUN
brj-22966	14	24	classification	classification	NOUN
brj-22966	14	25	contact	contact	NOUN
brj-22966	14	26	information	information	NOUN
brj-22966	14	27	:	:	PUNCT
brj-22966	14	28	a	a	DET
brj-22966	14	29	:	:	PUNCT
brj-22966	14	30	department	department	NOUN
brj-22966	14	31	of	of	ADP
brj-22966	14	32	forest	forest	NOUN
brj-22966	14	33	biomaterials	biomaterial	NOUN
brj-22966	14	34	engineering	engineering	NOUN
brj-22966	14	35	,	,	PUNCT
brj-22966	14	36	college	college	NOUN
brj-22966	14	37	of	of	ADP
brj-22966	14	38	forest	forest	NOUN
brj-22966	14	39	and	and	CCONJ
brj-22966	14	40	environmental	environmental	ADJ
brj-22966	14	41	sciences	science	NOUN
brj-22966	14	42	,	,	PUNCT
brj-22966	14	43	kangwon	kangwon	VERB
brj-22966	14	44	national	national	PROPN
brj-22966	14	45	university	university	PROPN
brj-22966	14	46	,	,	PUNCT
brj-22966	14	47	chuncheon	chuncheon	NOUN
brj-22966	14	48	24341	24341	NUM
brj-22966	14	49	,	,	PUNCT
brj-22966	14	50	republic	republic	NOUN
brj-22966	14	51	of	of	ADP
brj-22966	14	52	korea	korea	PROPN
brj-22966	14	53	;	;	PUNCT
brj-22966	14	54	b	b	X
brj-22966	14	55	:	:	PUNCT
brj-22966	14	56	institute	institute	NOUN
brj-22966	14	57	of	of	ADP
brj-22966	14	58	forest	forest	PROPN
brj-22966	14	59	science	science	PROPN
brj-22966	14	60	,	,	PUNCT
brj-22966	14	61	kangwon	kangwon	VERB
brj-22966	14	62	national	national	PROPN
brj-22966	14	63	university	university	PROPN
brj-22966	14	64	,	,	PUNCT
brj-22966	14	65	chuncheon	chuncheon	NOUN
brj-22966	14	66	24341	24341	NUM
brj-22966	14	67	,	,	PUNCT
brj-22966	14	68	republic	republic	NOUN
brj-22966	14	69	of	of	ADP
brj-22966	14	70	korea	korea	PROPN
brj-22966	14	71	;	;	PUNCT
brj-22966	14	72	c	c	X
brj-22966	14	73	:	:	PUNCT
brj-22966	14	74	fc	fc	PROPN
brj-22966	14	75	korea	korea	PROPN
brj-22966	14	76	land	land	PROPN
brj-22966	14	77	co.	co.	PROPN
brj-22966	14	78	,	,	PUNCT
brj-22966	14	79	ltd	ltd	PROPN
brj-22966	14	80	.	.	PROPN
brj-22966	14	81	,	,	PUNCT
brj-22966	14	82	seoul	seoul	PROPN
brj-22966	14	83	07271	07271	NUM
brj-22966	14	84	,	,	PUNCT
brj-22966	14	85	republic	republic	NOUN
brj-22966	14	86	of	of	ADP
brj-22966	14	87	korea	korea	PROPN
brj-22966	14	88	;	;	PUNCT
brj-22966	14	89	*	*	PUNCT
brj-22966	14	90	corresponding	correspond	VERB
brj-22966	14	91	author	author	NOUN
brj-22966	14	92	:	:	PUNCT
brj-22966	14	93	kimnh@kangwon.ac.kr	kimnh@kangwon.ac.kr	ADJ
brj-22966	14	94	introduction	introduction	NOUN
brj-22966	14	95	globally	globally	ADV
brj-22966	14	96	,	,	PUNCT
brj-22966	14	97	there	there	PRON
brj-22966	14	98	is	be	VERB
brj-22966	14	99	excess	excess	ADJ
brj-22966	14	100	demand	demand	NOUN
brj-22966	14	101	for	for	ADP
brj-22966	14	102	wood	wood	NOUN
brj-22966	14	103	(	(	PUNCT
brj-22966	14	104	unece	unece	NOUN
brj-22966	14	105	2007	2007	NUM
brj-22966	14	106	)	)	PUNCT
brj-22966	14	107	,	,	PUNCT
brj-22966	14	108	resulting	result	VERB
brj-22966	14	109	in	in	ADP
brj-22966	14	110	a	a	DET
brj-22966	14	111	gradual	gradual	ADJ
brj-22966	14	112	appreciation	appreciation	NOUN
brj-22966	14	113	of	of	ADP
brj-22966	14	114	the	the	DET
brj-22966	14	115	value	value	NOUN
brj-22966	14	116	of	of	ADP
brj-22966	14	117	wood	wood	NOUN
brj-22966	14	118	as	as	ADP
brj-22966	14	119	a	a	DET
brj-22966	14	120	resource	resource	NOUN
brj-22966	14	121	in	in	ADP
brj-22966	14	122	various	various	ADJ
brj-22966	14	123	sectors	sector	NOUN
brj-22966	14	124	.	.	PUNCT
brj-22966	15	1	species	specie	NOUN
brj-22966	15	2	identification	identification	NOUN
brj-22966	15	3	is	be	AUX
brj-22966	15	4	increasingly	increasingly	ADV
brj-22966	15	5	recognized	recognize	VERB
brj-22966	15	6	as	as	ADP
brj-22966	15	7	a	a	DET
brj-22966	15	8	significant	significant	ADJ
brj-22966	15	9	process	process	NOUN
brj-22966	15	10	for	for	ADP
brj-22966	15	11	enhancing	enhance	VERB
brj-22966	15	12	value	value	NOUN
brj-22966	15	13	of	of	ADP
brj-22966	15	14	wood	wood	NOUN
brj-22966	15	15	resources	resource	NOUN
brj-22966	15	16	and	and	CCONJ
brj-22966	15	17	is	be	AUX
brj-22966	15	18	required	require	VERB
brj-22966	15	19	in	in	ADP
brj-22966	15	20	numerous	numerous	ADJ
brj-22966	15	21	fields	field	NOUN
brj-22966	15	22	such	such	ADJ
brj-22966	15	23	as	as	ADP
brj-22966	15	24	optimizing	optimize	VERB
brj-22966	15	25	the	the	DET
brj-22966	15	26	utilization	utilization	NOUN
brj-22966	15	27	of	of	ADP
brj-22966	15	28	conventional	conventional	ADJ
brj-22966	15	29	wood	wood	NOUN
brj-22966	15	30	resources	resource	NOUN
brj-22966	15	31	,	,	PUNCT
brj-22966	15	32	protecting	protect	VERB
brj-22966	15	33	endangered	endangered	ADJ
brj-22966	15	34	species	specie	NOUN
brj-22966	15	35	,	,	PUNCT
brj-22966	15	36	and	and	CCONJ
brj-22966	15	37	facilitating	facilitate	VERB
brj-22966	15	38	practical	practical	ADJ
brj-22966	15	39	customs	custom	NOUN
brj-22966	15	40	clearance	clearance	NOUN
brj-22966	15	41	operations	operation	NOUN
brj-22966	15	42	.	.	PUNCT
brj-22966	16	1	peer	peer	NOUN
brj-22966	16	2	-	-	PUNCT
brj-22966	16	3	reviewed	review	VERB
brj-22966	16	4	article	article	NOUN
brj-22966	16	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	16	6	kim	kim	PROPN
brj-22966	16	7	et	et	PROPN
brj-22966	16	8	al	al	PROPN
brj-22966	16	9	.	.	PROPN
brj-22966	17	1	(	(	PUNCT
brj-22966	17	2	2024	2024	NUM
brj-22966	17	3	)	)	PUNCT
brj-22966	17	4	.	.	PUNCT
brj-22966	18	1	“	"	PUNCT
brj-22966	18	2	convolutional	convolutional	ADJ
brj-22966	18	3	neural	neural	ADJ
brj-22966	18	4	network	network	NOUN
brj-22966	18	5	,	,	PUNCT
brj-22966	18	6	”	"	PUNCT
brj-22966	18	7	bioresources	bioresource	NOUN
brj-22966	18	8	19(1	19(1	NUM
brj-22966	18	9	)	)	PUNCT
brj-22966	18	10	,	,	PUNCT
brj-22966	18	11	510	510	NUM
brj-22966	18	12	-	-	SYM
brj-22966	18	13	524	524	NUM
brj-22966	18	14	.	.	PUNCT
brj-22966	18	15	511	511	NUM
brj-22966	18	16	recently	recently	ADV
brj-22966	18	17	,	,	PUNCT
brj-22966	18	18	there	there	PRON
brj-22966	18	19	has	have	AUX
brj-22966	18	20	been	be	AUX
brj-22966	18	21	a	a	DET
brj-22966	18	22	surge	surge	NOUN
brj-22966	18	23	in	in	ADP
brj-22966	18	24	research	research	NOUN
brj-22966	18	25	aimed	aim	VERB
brj-22966	18	26	at	at	ADP
brj-22966	18	27	automating	automate	VERB
brj-22966	18	28	the	the	DET
brj-22966	18	29	classification	classification	NOUN
brj-22966	18	30	of	of	ADP
brj-22966	18	31	wood	wood	NOUN
brj-22966	18	32	species	specie	NOUN
brj-22966	18	33	and	and	CCONJ
brj-22966	18	34	enhancing	enhance	VERB
brj-22966	18	35	their	their	PRON
brj-22966	18	36	precision	precision	NOUN
brj-22966	18	37	of	of	ADP
brj-22966	18	38	automated	automate	VERB
brj-22966	18	39	classification	classification	NOUN
brj-22966	18	40	.	.	PUNCT
brj-22966	19	1	these	these	DET
brj-22966	19	2	efforts	effort	NOUN
brj-22966	19	3	have	have	AUX
brj-22966	19	4	been	be	AUX
brj-22966	19	5	driven	drive	VERB
brj-22966	19	6	by	by	ADP
brj-22966	19	7	the	the	DET
brj-22966	19	8	objectives	objective	NOUN
brj-22966	19	9	of	of	ADP
brj-22966	19	10	streamlining	streamline	VERB
brj-22966	19	11	the	the	DET
brj-22966	19	12	process	process	NOUN
brj-22966	19	13	and	and	CCONJ
brj-22966	19	14	reducing	reduce	VERB
brj-22966	19	15	subjectivity	subjectivity	NOUN
brj-22966	19	16	.	.	PUNCT
brj-22966	20	1	ilic	ilic	NOUN
brj-22966	20	2	(	(	PUNCT
brj-22966	20	3	1993	1993	NUM
brj-22966	20	4	)	)	PUNCT
brj-22966	20	5	proposed	propose	VERB
brj-22966	20	6	the	the	DET
brj-22966	20	7	potential	potential	NOUN
brj-22966	20	8	for	for	ADP
brj-22966	20	9	computer	computer	NOUN
brj-22966	20	10	-	-	PUNCT
brj-22966	20	11	based	base	VERB
brj-22966	20	12	automated	automate	VERB
brj-22966	20	13	species	species	NOUN
brj-22966	20	14	identification	identification	NOUN
brj-22966	20	15	,	,	PUNCT
brj-22966	20	16	while	while	SCONJ
brj-22966	20	17	wheeler	wheeler	NOUN
brj-22966	20	18	and	and	CCONJ
brj-22966	20	19	baas	baas	NOUN
brj-22966	20	20	(	(	PUNCT
brj-22966	20	21	1998	1998	NUM
brj-22966	20	22	)	)	PUNCT
brj-22966	20	23	emphasized	emphasize	VERB
brj-22966	20	24	the	the	DET
brj-22966	20	25	importance	importance	NOUN
brj-22966	20	26	of	of	ADP
brj-22966	20	27	computer	computer	NOUN
brj-22966	20	28	-	-	PUNCT
brj-22966	20	29	aid	aid	NOUN
brj-22966	20	30	specification	specification	NOUN
brj-22966	20	31	identification	identification	NOUN
brj-22966	20	32	.	.	PUNCT
brj-22966	21	1	since	since	SCONJ
brj-22966	21	2	the	the	DET
brj-22966	21	3	2000s	2000s	NUM
brj-22966	21	4	,	,	PUNCT
brj-22966	21	5	studies	study	NOUN
brj-22966	21	6	applying	apply	VERB
brj-22966	21	7	computer	computer	NOUN
brj-22966	21	8	vision	vision	NOUN
brj-22966	21	9	to	to	PART
brj-22966	21	10	identify	identify	VERB
brj-22966	21	11	wood	wood	NOUN
brj-22966	21	12	species	specie	NOUN
brj-22966	21	13	have	have	AUX
brj-22966	21	14	been	be	AUX
brj-22966	21	15	conducted	conduct	VERB
brj-22966	21	16	in	in	ADP
brj-22966	21	17	earnest	earnest	NOUN
brj-22966	21	18	.	.	PUNCT
brj-22966	22	1	tou	tou	PROPN
brj-22966	22	2	et	et	PROPN
brj-22966	22	3	al	al	PROPN
brj-22966	22	4	.	.	PROPN
brj-22966	23	1	(	(	PUNCT
brj-22966	23	2	2007	2007	NUM
brj-22966	23	3	)	)	PUNCT
brj-22966	23	4	proposed	propose	VERB
brj-22966	23	5	a	a	DET
brj-22966	23	6	system	system	NOUN
brj-22966	23	7	to	to	PART
brj-22966	23	8	identify	identify	VERB
brj-22966	23	9	wood	wood	NOUN
brj-22966	23	10	species	specie	NOUN
brj-22966	23	11	in	in	ADP
brj-22966	23	12	real	real	ADJ
brj-22966	23	13	time	time	NOUN
brj-22966	23	14	using	use	VERB
brj-22966	23	15	macroscopic	macroscopic	ADJ
brj-22966	23	16	images	image	NOUN
brj-22966	23	17	of	of	ADP
brj-22966	23	18	wood	wood	NOUN
brj-22966	23	19	cross	cross	NOUN
brj-22966	23	20	sections	section	NOUN
brj-22966	23	21	.	.	PUNCT
brj-22966	24	1	bremananth	bremananth	PROPN
brj-22966	24	2	et	et	PROPN
brj-22966	24	3	al	al	PROPN
brj-22966	24	4	.	.	PROPN
brj-22966	24	5	(	(	PUNCT
brj-22966	24	6	2009	2009	NUM
brj-22966	24	7	)	)	PUNCT
brj-22966	24	8	attempted	attempt	VERB
brj-22966	24	9	to	to	PART
brj-22966	24	10	computerize	computerize	VERB
brj-22966	24	11	a	a	DET
brj-22966	24	12	wood	wood	NOUN
brj-22966	24	13	species	species	NOUN
brj-22966	24	14	recognition	recognition	NOUN
brj-22966	24	15	system	system	NOUN
brj-22966	24	16	using	use	VERB
brj-22966	24	17	computer	computer	NOUN
brj-22966	24	18	vision	vision	NOUN
brj-22966	24	19	technology	technology	NOUN
brj-22966	24	20	.	.	PUNCT
brj-22966	25	1	in	in	ADP
brj-22966	25	2	the	the	DET
brj-22966	25	3	2010s	2010s	NUM
brj-22966	25	4	,	,	PUNCT
brj-22966	25	5	research	research	NOUN
brj-22966	25	6	on	on	ADP
brj-22966	25	7	artificial	artificial	ADJ
brj-22966	25	8	intelligence	intelligence	NOUN
brj-22966	25	9	-	-	PUNCT
brj-22966	25	10	based	base	VERB
brj-22966	25	11	wood	wood	NOUN
brj-22966	25	12	species	species	NOUN
brj-22966	25	13	identification	identification	NOUN
brj-22966	25	14	increased	increase	VERB
brj-22966	25	15	explosively	explosively	ADV
brj-22966	25	16	,	,	PUNCT
brj-22966	25	17	owing	owe	VERB
brj-22966	25	18	to	to	ADP
brj-22966	25	19	the	the	DET
brj-22966	25	20	rapid	rapid	ADJ
brj-22966	25	21	development	development	NOUN
brj-22966	25	22	of	of	ADP
brj-22966	25	23	computing	compute	VERB
brj-22966	25	24	performance	performance	NOUN
brj-22966	25	25	and	and	CCONJ
brj-22966	25	26	machine	machine	NOUN
brj-22966	25	27	learning	learn	VERB
brj-22966	25	28	technology	technology	NOUN
brj-22966	25	29	.	.	PUNCT
brj-22966	26	1	as	as	ADP
brj-22966	26	2	a	a	DET
brj-22966	26	3	representative	representative	ADJ
brj-22966	26	4	example	example	NOUN
brj-22966	26	5	,	,	PUNCT
brj-22966	26	6	hermanson	hermanson	NOUN
brj-22966	26	7	and	and	CCONJ
brj-22966	26	8	wiedenhoeft	wiedenhoeft	NOUN
brj-22966	26	9	(	(	PUNCT
brj-22966	26	10	2011	2011	NUM
brj-22966	26	11	)	)	PUNCT
brj-22966	26	12	introduced	introduce	VERB
brj-22966	26	13	an	an	DET
brj-22966	26	14	overview	overview	NOUN
brj-22966	26	15	and	and	CCONJ
brj-22966	26	16	advantages	advantage	NOUN
brj-22966	26	17	of	of	ADP
brj-22966	26	18	species	specie	NOUN
brj-22966	26	19	identification	identification	NOUN
brj-22966	26	20	using	use	VERB
brj-22966	26	21	machine	machine	NOUN
brj-22966	26	22	vision	vision	NOUN
brj-22966	26	23	in	in	ADP
brj-22966	26	24	their	their	PRON
brj-22966	26	25	review	review	NOUN
brj-22966	26	26	paper	paper	NOUN
brj-22966	26	27	.	.	PUNCT
brj-22966	27	1	since	since	SCONJ
brj-22966	27	2	the	the	DET
brj-22966	27	3	first	first	ADJ
brj-22966	27	4	meeting	meeting	NOUN
brj-22966	27	5	of	of	ADP
brj-22966	27	6	the	the	DET
brj-22966	27	7	imagenet	imagenet	ADJ
brj-22966	27	8	largescale	largescale	ADJ
brj-22966	27	9	visual	visual	ADJ
brj-22966	27	10	recognition	recognition	NOUN
brj-22966	27	11	challenge	challenge	NOUN
brj-22966	27	12	(	(	PUNCT
brj-22966	27	13	ilsvrc	ilsvrc	PROPN
brj-22966	27	14	)	)	PUNCT
brj-22966	27	15	in	in	ADP
brj-22966	27	16	2010	2010	NUM
brj-22966	27	17	,	,	PUNCT
brj-22966	27	18	many	many	ADJ
brj-22966	27	19	high	high	ADJ
brj-22966	27	20	-	-	PUNCT
brj-22966	27	21	performance	performance	NOUN
brj-22966	27	22	convolutional	convolutional	ADJ
brj-22966	27	23	neural	neural	ADJ
brj-22966	27	24	network	network	NOUN
brj-22966	27	25	(	(	PUNCT
brj-22966	27	26	cnn	cnn	PROPN
brj-22966	27	27	)	)	PUNCT
brj-22966	27	28	models	model	NOUN
brj-22966	27	29	,	,	PUNCT
brj-22966	27	30	such	such	ADJ
brj-22966	27	31	as	as	ADP
brj-22966	27	32	vggnet	vggnet	NOUN
brj-22966	27	33	(	(	PUNCT
brj-22966	27	34	simonyan	simonyan	ADJ
brj-22966	27	35	and	and	CCONJ
brj-22966	27	36	zisserman	zisserman	NOUN
brj-22966	27	37	2015	2015	NUM
brj-22966	27	38	)	)	PUNCT
brj-22966	27	39	,	,	PUNCT
brj-22966	27	40	googlenet	googlenet	NOUN
brj-22966	27	41	(	(	PUNCT
brj-22966	27	42	szegedy	szegedy	VERB
brj-22966	27	43	et	et	PROPN
brj-22966	27	44	al	al	PROPN
brj-22966	27	45	.	.	PROPN
brj-22966	27	46	2015	2015	NUM
brj-22966	27	47	)	)	PUNCT
brj-22966	27	48	,	,	PUNCT
brj-22966	27	49	and	and	CCONJ
brj-22966	27	50	resnet	resnet	NOUN
brj-22966	27	51	(	(	PUNCT
brj-22966	27	52	he	he	PRON
brj-22966	27	53	et	et	PROPN
brj-22966	27	54	al	al	PROPN
brj-22966	27	55	.	.	PROPN
brj-22966	27	56	2016	2016	NUM
brj-22966	27	57	)	)	PUNCT
brj-22966	27	58	have	have	AUX
brj-22966	27	59	been	be	AUX
brj-22966	27	60	developed	develop	VERB
brj-22966	27	61	.	.	PUNCT
brj-22966	28	1	these	these	DET
brj-22966	28	2	inventions	invention	NOUN
brj-22966	28	3	have	have	AUX
brj-22966	28	4	led	lead	VERB
brj-22966	28	5	to	to	ADP
brj-22966	28	6	rapid	rapid	ADJ
brj-22966	28	7	developments	development	NOUN
brj-22966	28	8	in	in	ADP
brj-22966	28	9	image	image	NOUN
brj-22966	28	10	classification	classification	NOUN
brj-22966	28	11	using	use	VERB
brj-22966	28	12	cnn	cnn	PROPN
brj-22966	28	13	.	.	PUNCT
brj-22966	29	1	recently	recently	ADV
brj-22966	29	2	,	,	PUNCT
brj-22966	29	3	cnns	cnn	NOUN
brj-22966	29	4	have	have	AUX
brj-22966	29	5	been	be	AUX
brj-22966	29	6	employed	employ	VERB
brj-22966	29	7	to	to	PART
brj-22966	29	8	classify	classify	VERB
brj-22966	29	9	wood	wood	NOUN
brj-22966	29	10	species	specie	NOUN
brj-22966	29	11	using	use	VERB
brj-22966	29	12	datasets	dataset	NOUN
brj-22966	29	13	containing	contain	VERB
brj-22966	29	14	wood	wood	NOUN
brj-22966	29	15	images	image	NOUN
brj-22966	29	16	.	.	PUNCT
brj-22966	30	1	kwon	kwon	VERB
brj-22966	30	2	et	et	PROPN
brj-22966	30	3	al	al	PROPN
brj-22966	30	4	.	.	PROPN
brj-22966	31	1	(	(	PUNCT
brj-22966	31	2	2017	2017	NUM
brj-22966	31	3	)	)	PUNCT
brj-22966	31	4	reported	report	VERB
brj-22966	31	5	the	the	DET
brj-22966	31	6	possibility	possibility	NOUN
brj-22966	31	7	and	and	CCONJ
brj-22966	31	8	performance	performance	NOUN
brj-22966	31	9	of	of	ADP
brj-22966	31	10	softwood	softwood	NOUN
brj-22966	31	11	species	specie	NOUN
brj-22966	31	12	classification	classification	NOUN
brj-22966	31	13	using	use	VERB
brj-22966	31	14	cnn	cnn	PROPN
brj-22966	31	15	-	-	PUNCT
brj-22966	31	16	based	base	VERB
brj-22966	31	17	models	model	NOUN
brj-22966	31	18	,	,	PUNCT
brj-22966	31	19	such	such	ADJ
brj-22966	31	20	as	as	ADP
brj-22966	31	21	lenet	lenet	NOUN
brj-22966	31	22	and	and	CCONJ
brj-22966	31	23	minivggnet	minivggnet	NOUN
brj-22966	31	24	.	.	PUNCT
brj-22966	32	1	kwon	kwon	VERB
brj-22966	32	2	et	et	PROPN
brj-22966	32	3	al	al	PROPN
brj-22966	32	4	.	.	PROPN
brj-22966	33	1	(	(	PUNCT
brj-22966	33	2	2019	2019	NUM
brj-22966	33	3	)	)	PUNCT
brj-22966	33	4	improved	improve	VERB
brj-22966	33	5	the	the	DET
brj-22966	33	6	performance	performance	NOUN
brj-22966	33	7	of	of	ADP
brj-22966	33	8	automated	automate	VERB
brj-22966	33	9	species	species	NOUN
brj-22966	33	10	classification	classification	NOUN
brj-22966	33	11	by	by	ADP
brj-22966	33	12	using	use	VERB
brj-22966	33	13	a	a	DET
brj-22966	33	14	cnn	cnn	NOUN
brj-22966	33	15	with	with	ADP
brj-22966	33	16	ensemble	ensemble	ADJ
brj-22966	33	17	methods	method	NOUN
brj-22966	33	18	.	.	PUNCT
brj-22966	34	1	yang	yang	PROPN
brj-22966	34	2	et	et	PROPN
brj-22966	34	3	al	al	PROPN
brj-22966	34	4	.	.	PROPN
brj-22966	35	1	(	(	PUNCT
brj-22966	35	2	2019	2019	NUM
brj-22966	35	3	)	)	PUNCT
brj-22966	35	4	also	also	ADV
brj-22966	35	5	employed	employ	VERB
brj-22966	35	6	a	a	DET
brj-22966	35	7	cnn	cnn	NOUN
brj-22966	35	8	with	with	ADP
brj-22966	35	9	ensemble	ensemble	ADJ
brj-22966	35	10	methods	method	NOUN
brj-22966	35	11	for	for	ADP
brj-22966	35	12	classifying	classify	VERB
brj-22966	35	13	korean	korean	ADJ
brj-22966	35	14	softwood	softwood	NOUN
brj-22966	35	15	species	specie	NOUN
brj-22966	35	16	using	use	VERB
brj-22966	35	17	datasets	dataset	NOUN
brj-22966	35	18	from	from	ADP
brj-22966	35	19	near	near	ADV
brj-22966	35	20	-	-	PUNCT
brj-22966	35	21	infrared	infrared	ADJ
brj-22966	35	22	spectra	spectra	NOUN
brj-22966	35	23	(	(	PUNCT
brj-22966	35	24	nir	nir	NOUN
brj-22966	35	25	)	)	PUNCT
brj-22966	35	26	analysis	analysis	NOUN
brj-22966	35	27	results	result	NOUN
brj-22966	35	28	and	and	CCONJ
brj-22966	35	29	macroscopic	macroscopic	ADJ
brj-22966	35	30	images	image	NOUN
brj-22966	35	31	of	of	ADP
brj-22966	35	32	radial	radial	ADJ
brj-22966	35	33	sections	section	NOUN
brj-22966	35	34	.	.	PUNCT
brj-22966	36	1	hwang	hwang	PROPN
brj-22966	36	2	et	et	PROPN
brj-22966	36	3	al	al	PROPN
brj-22966	36	4	.	.	PROPN
brj-22966	36	5	(	(	PUNCT
brj-22966	36	6	2020	2020	NUM
brj-22966	36	7	)	)	PUNCT
brj-22966	36	8	attempted	attempt	VERB
brj-22966	36	9	to	to	PART
brj-22966	36	10	visualize	visualize	VERB
brj-22966	36	11	anatomical	anatomical	ADJ
brj-22966	36	12	features	feature	NOUN
brj-22966	36	13	using	use	VERB
brj-22966	36	14	machine	machine	NOUN
brj-22966	36	15	learning	learn	VERB
brj-22966	36	16	technology	technology	NOUN
brj-22966	36	17	for	for	ADP
brj-22966	36	18	quantitative	quantitative	ADJ
brj-22966	36	19	analysis	analysis	NOUN
brj-22966	36	20	.	.	PUNCT
brj-22966	37	1	zhao	zhao	PROPN
brj-22966	37	2	et	et	PROPN
brj-22966	37	3	al	al	PROPN
brj-22966	37	4	.	.	PROPN
brj-22966	38	1	(	(	PUNCT
brj-22966	38	2	2021	2021	NUM
brj-22966	38	3	)	)	PUNCT
brj-22966	38	4	demonstrated	demonstrate	VERB
brj-22966	38	5	the	the	DET
brj-22966	38	6	efficacy	efficacy	NOUN
brj-22966	38	7	of	of	ADP
brj-22966	38	8	a	a	DET
brj-22966	38	9	cnn	cnn	NOUN
brj-22966	38	10	for	for	ADP
brj-22966	38	11	accurately	accurately	ADV
brj-22966	38	12	classifying	classify	VERB
brj-22966	38	13	various	various	ADJ
brj-22966	38	14	wood	wood	NOUN
brj-22966	38	15	species	specie	NOUN
brj-22966	38	16	based	base	VERB
brj-22966	38	17	on	on	ADP
brj-22966	38	18	microscopic	microscopic	ADJ
brj-22966	38	19	image	image	NOUN
brj-22966	38	20	datasets	dataset	NOUN
brj-22966	38	21	.	.	PUNCT
brj-22966	39	1	huang	huang	PROPN
brj-22966	39	2	et	et	PROPN
brj-22966	39	3	al	al	PROPN
brj-22966	39	4	.	.	PROPN
brj-22966	39	5	(	(	PUNCT
brj-22966	39	6	2021	2021	NUM
brj-22966	39	7	)	)	PUNCT
brj-22966	39	8	demonstrated	demonstrate	VERB
brj-22966	39	9	the	the	DET
brj-22966	39	10	efficacy	efficacy	NOUN
brj-22966	39	11	of	of	ADP
brj-22966	39	12	a	a	DET
brj-22966	39	13	transfer	transfer	NOUN
brj-22966	39	14	-	-	PUNCT
brj-22966	39	15	learning	learn	VERB
brj-22966	39	16	model	model	NOUN
brj-22966	39	17	with	with	ADP
brj-22966	39	18	enhanced	enhance	VERB
brj-22966	39	19	pooling	pool	VERB
brj-22966	39	20	layers	layer	NOUN
brj-22966	39	21	for	for	ADP
brj-22966	39	22	enhanced	enhanced	ADJ
brj-22966	39	23	wood	wood	NOUN
brj-22966	39	24	identification	identification	NOUN
brj-22966	39	25	using	use	VERB
brj-22966	39	26	cross	cross	ADJ
brj-22966	39	27	-	-	ADJ
brj-22966	39	28	sectional	sectional	ADJ
brj-22966	39	29	wood	wood	NOUN
brj-22966	39	30	images	image	NOUN
brj-22966	39	31	.	.	PUNCT
brj-22966	40	1	hwang	hwang	PROPN
brj-22966	40	2	and	and	CCONJ
brj-22966	40	3	sugiyama	sugiyama	NOUN
brj-22966	40	4	(	(	PUNCT
brj-22966	40	5	2021	2021	NUM
brj-22966	40	6	)	)	PUNCT
brj-22966	40	7	conducted	conduct	VERB
brj-22966	40	8	a	a	DET
brj-22966	40	9	methodological	methodological	ADJ
brj-22966	40	10	examination	examination	NOUN
brj-22966	40	11	of	of	ADP
brj-22966	40	12	computer	computer	NOUN
brj-22966	40	13	-	-	PUNCT
brj-22966	40	14	vision	vision	NOUN
brj-22966	40	15	-	-	PUNCT
brj-22966	40	16	based	base	VERB
brj-22966	40	17	species	species	NOUN
brj-22966	40	18	identification	identification	NOUN
brj-22966	40	19	.	.	PUNCT
brj-22966	41	1	their	their	PRON
brj-22966	41	2	research	research	NOUN
brj-22966	41	3	anticipated	anticipate	VERB
brj-22966	41	4	the	the	DET
brj-22966	41	5	potential	potential	NOUN
brj-22966	41	6	of	of	ADP
brj-22966	41	7	computer	computer	NOUN
brj-22966	41	8	vision	vision	NOUN
brj-22966	41	9	to	to	PART
brj-22966	41	10	enhance	enhance	VERB
brj-22966	41	11	the	the	DET
brj-22966	41	12	accessibility	accessibility	NOUN
brj-22966	41	13	of	of	ADP
brj-22966	41	14	wood	wood	NOUN
brj-22966	41	15	identification	identification	NOUN
brj-22966	41	16	to	to	ADP
brj-22966	41	17	the	the	DET
brj-22966	41	18	public	public	NOUN
brj-22966	41	19	and	and	CCONJ
brj-22966	41	20	make	make	VERB
brj-22966	41	21	significant	significant	ADJ
brj-22966	41	22	contributions	contribution	NOUN
brj-22966	41	23	to	to	ADP
brj-22966	41	24	the	the	DET
brj-22966	41	25	field	field	NOUN
brj-22966	41	26	of	of	ADP
brj-22966	41	27	wood	wood	NOUN
brj-22966	41	28	science	science	NOUN
brj-22966	41	29	.	.	PUNCT
brj-22966	42	1	cao	cao	PROPN
brj-22966	42	2	et	et	PROPN
brj-22966	42	3	al	al	PROPN
brj-22966	42	4	.	.	PROPN
brj-22966	42	5	(	(	PUNCT
brj-22966	42	6	2022	2022	NUM
brj-22966	42	7	)	)	PUNCT
brj-22966	42	8	utilized	utilize	VERB
brj-22966	42	9	an	an	DET
brj-22966	42	10	artificial	artificial	ADJ
brj-22966	42	11	neural	neural	ADJ
brj-22966	42	12	network	network	NOUN
brj-22966	42	13	trained	train	VERB
brj-22966	42	14	using	use	VERB
brj-22966	42	15	species	specie	NOUN
brj-22966	42	16	-	-	PUNCT
brj-22966	42	17	specific	specific	ADJ
brj-22966	42	18	thermal	thermal	ADJ
brj-22966	42	19	conductivity	conductivity	NOUN
brj-22966	42	20	trends	trend	NOUN
brj-22966	42	21	to	to	PART
brj-22966	42	22	classify	classify	VERB
brj-22966	42	23	different	different	ADJ
brj-22966	42	24	species	specie	NOUN
brj-22966	42	25	.	.	PUNCT
brj-22966	43	1	most	most	ADJ
brj-22966	43	2	studies	study	NOUN
brj-22966	43	3	on	on	ADP
brj-22966	43	4	wood	wood	NOUN
brj-22966	43	5	species	specie	NOUN
brj-22966	43	6	identification	identification	NOUN
brj-22966	43	7	have	have	AUX
brj-22966	43	8	focused	focus	VERB
brj-22966	43	9	on	on	ADP
brj-22966	43	10	the	the	DET
brj-22966	43	11	xylem	xylem	PROPN
brj-22966	43	12	anatomical	anatomical	ADJ
brj-22966	43	13	characteristics	characteristic	NOUN
brj-22966	43	14	(	(	PUNCT
brj-22966	43	15	kim	kim	PROPN
brj-22966	43	16	et	et	PROPN
brj-22966	43	17	al	al	PROPN
brj-22966	43	18	.	.	PROPN
brj-22966	43	19	2021	2021	NUM
brj-22966	43	20	;	;	PUNCT
brj-22966	43	21	savero	savero	PROPN
brj-22966	43	22	et	et	PROPN
brj-22966	43	23	al	al	PROPN
brj-22966	43	24	.	.	PROPN
brj-22966	43	25	2022	2022	NUM
brj-22966	43	26	;	;	PUNCT
brj-22966	43	27	savero	savero	NOUN
brj-22966	43	28	et	et	PROPN
brj-22966	43	29	al	al	PROPN
brj-22966	43	30	.	.	PROPN
brj-22966	43	31	2023	2023	NUM
brj-22966	43	32	)	)	PUNCT
brj-22966	43	33	.	.	PUNCT
brj-22966	44	1	however	however	ADV
brj-22966	44	2	,	,	PUNCT
brj-22966	44	3	bark	bark	NOUN
brj-22966	44	4	also	also	ADV
brj-22966	44	5	displays	display	VERB
brj-22966	44	6	distinct	distinct	ADJ
brj-22966	44	7	characteristics	characteristic	NOUN
brj-22966	44	8	in	in	ADP
brj-22966	44	9	each	each	DET
brj-22966	44	10	species	specie	NOUN
brj-22966	44	11	,	,	PUNCT
brj-22966	44	12	rendering	render	VERB
brj-22966	44	13	it	it	PRON
brj-22966	44	14	a	a	DET
brj-22966	44	15	helpful	helpful	ADJ
brj-22966	44	16	tool	tool	NOUN
brj-22966	44	17	for	for	ADP
brj-22966	44	18	species	species	NOUN
brj-22966	44	19	identification	identification	NOUN
brj-22966	44	20	(	(	PUNCT
brj-22966	44	21	iawa	iawa	PROPN
brj-22966	44	22	committee	committee	PROPN
brj-22966	44	23	2016	2016	NUM
brj-22966	44	24	)	)	PUNCT
brj-22966	44	25	.	.	PUNCT
brj-22966	45	1	species	specie	NOUN
brj-22966	45	2	identification	identification	NOUN
brj-22966	45	3	using	use	VERB
brj-22966	45	4	bark	bark	NOUN
brj-22966	45	5	has	have	VERB
brj-22966	45	6	a	a	DET
brj-22966	45	7	notable	notable	ADJ
brj-22966	45	8	benefit	benefit	NOUN
brj-22966	45	9	because	because	SCONJ
brj-22966	45	10	bark	bark	NOUN
brj-22966	45	11	can	can	AUX
brj-22966	45	12	be	be	AUX
brj-22966	45	13	obtained	obtain	VERB
brj-22966	45	14	from	from	ADP
brj-22966	45	15	standing	stand	VERB
brj-22966	45	16	trees	tree	NOUN
brj-22966	45	17	without	without	ADP
brj-22966	45	18	timber	timber	NOUN
brj-22966	45	19	harvesting	harvesting	NOUN
brj-22966	45	20	.	.	PUNCT
brj-22966	46	1	a	a	DET
brj-22966	46	2	few	few	ADJ
brj-22966	46	3	studies	study	NOUN
brj-22966	46	4	(	(	PUNCT
brj-22966	46	5	fiel	fiel	NOUN
brj-22966	46	6	and	and	CCONJ
brj-22966	46	7	sablatnig	sablatnig	PROPN
brj-22966	46	8	2010	2010	NUM
brj-22966	46	9	;	;	PUNCT
brj-22966	46	10	bertrand	bertrand	PROPN
brj-22966	46	11	et	et	PROPN
brj-22966	46	12	al	al	PROPN
brj-22966	46	13	.	.	PROPN
brj-22966	46	14	2017	2017	NUM
brj-22966	46	15	;	;	PUNCT
brj-22966	46	16	carpentier	carpentier	NOUN
brj-22966	46	17	et	et	PROPN
brj-22966	46	18	al	al	PROPN
brj-22966	46	19	.	.	PROPN
brj-22966	46	20	2018	2018	NUM
brj-22966	46	21	;	;	PUNCT
brj-22966	46	22	kim	kim	PROPN
brj-22966	46	23	et	et	PROPN
brj-22966	46	24	al	al	PROPN
brj-22966	46	25	.	.	PROPN
brj-22966	46	26	2022	2022	NUM
brj-22966	46	27	)	)	PUNCT
brj-22966	46	28	have	have	AUX
brj-22966	46	29	attempted	attempt	VERB
brj-22966	46	30	to	to	PART
brj-22966	46	31	utilize	utilize	VERB
brj-22966	46	32	bark	bark	NOUN
brj-22966	46	33	for	for	ADP
brj-22966	46	34	automated	automate	VERB
brj-22966	46	35	species	species	NOUN
brj-22966	46	36	identification	identification	NOUN
brj-22966	46	37	using	use	VERB
brj-22966	46	38	artificial	artificial	ADJ
brj-22966	46	39	intelligence	intelligence	NOUN
brj-22966	46	40	.	.	PUNCT
brj-22966	47	1	they	they	PRON
brj-22966	47	2	focused	focus	VERB
brj-22966	47	3	only	only	ADV
brj-22966	47	4	on	on	ADP
brj-22966	47	5	the	the	DET
brj-22966	47	6	outer	outer	ADJ
brj-22966	47	7	appearance	appearance	NOUN
brj-22966	47	8	of	of	ADP
brj-22966	47	9	the	the	DET
brj-22966	47	10	bark	bark	NOUN
brj-22966	47	11	from	from	ADP
brj-22966	47	12	standing	stand	VERB
brj-22966	47	13	trees	tree	NOUN
brj-22966	47	14	for	for	ADP
brj-22966	47	15	dataset	dataset	ADJ
brj-22966	47	16	preparation	preparation	NOUN
brj-22966	47	17	.	.	PUNCT
brj-22966	48	1	however	however	ADV
brj-22966	48	2	,	,	PUNCT
brj-22966	48	3	the	the	DET
brj-22966	48	4	anatomical	anatomical	ADJ
brj-22966	48	5	features	feature	NOUN
brj-22966	48	6	of	of	ADP
brj-22966	48	7	the	the	DET
brj-22966	48	8	bark	bark	NOUN
brj-22966	48	9	could	could	AUX
brj-22966	48	10	be	be	AUX
brj-22966	48	11	more	more	ADV
brj-22966	48	12	systematic	systematic	ADJ
brj-22966	48	13	than	than	ADP
brj-22966	48	14	the	the	DET
brj-22966	48	15	surface	surface	NOUN
brj-22966	48	16	features	feature	VERB
brj-22966	48	17	,	,	PUNCT
brj-22966	48	18	showing	show	VERB
brj-22966	48	19	a	a	DET
brj-22966	48	20	higher	high	ADJ
brj-22966	48	21	efficiency	efficiency	NOUN
brj-22966	48	22	in	in	ADP
brj-22966	48	23	feature	feature	NOUN
brj-22966	48	24	selection	selection	NOUN
brj-22966	48	25	and	and	CCONJ
brj-22966	48	26	extraction	extraction	NOUN
brj-22966	48	27	,	,	PUNCT
brj-22966	48	28	which	which	PRON
brj-22966	48	29	affects	affect	VERB
brj-22966	48	30	species	species	NOUN
brj-22966	48	31	classification	classification	NOUN
brj-22966	48	32	performance	performance	NOUN
brj-22966	48	33	using	use	VERB
brj-22966	48	34	computer	computer	NOUN
brj-22966	48	35	vision	vision	NOUN
brj-22966	48	36	.	.	PUNCT
brj-22966	49	1	sclereids	sclereid	NOUN
brj-22966	49	2	are	be	AUX
brj-22966	49	3	peer	peer	NOUN
brj-22966	49	4	-	-	PUNCT
brj-22966	49	5	reviewed	review	VERB
brj-22966	49	6	article	article	NOUN
brj-22966	49	7	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	49	8	kim	kim	PROPN
brj-22966	49	9	et	et	PROPN
brj-22966	49	10	al	al	PROPN
brj-22966	49	11	.	.	PROPN
brj-22966	50	1	(	(	PUNCT
brj-22966	50	2	2024	2024	NUM
brj-22966	50	3	)	)	PUNCT
brj-22966	50	4	.	.	PUNCT
brj-22966	51	1	“	"	PUNCT
brj-22966	51	2	convolutional	convolutional	ADJ
brj-22966	51	3	neural	neural	ADJ
brj-22966	51	4	network	network	NOUN
brj-22966	51	5	,	,	PUNCT
brj-22966	51	6	”	"	PUNCT
brj-22966	51	7	bioresources	bioresource	NOUN
brj-22966	51	8	19(1	19(1	NUM
brj-22966	51	9	)	)	PUNCT
brj-22966	51	10	,	,	PUNCT
brj-22966	51	11	510	510	NUM
brj-22966	51	12	-	-	SYM
brj-22966	51	13	524	524	NUM
brj-22966	51	14	.	.	PUNCT
brj-22966	52	1	512	512	NUM
brj-22966	52	2	sclerenchyma	sclerenchyma	NOUN
brj-22966	52	3	cells	cell	NOUN
brj-22966	52	4	that	that	PRON
brj-22966	52	5	are	be	AUX
brj-22966	52	6	variable	variable	ADJ
brj-22966	52	7	in	in	ADP
brj-22966	52	8	form	form	NOUN
brj-22966	52	9	and	and	CCONJ
brj-22966	52	10	size	size	NOUN
brj-22966	52	11	,	,	PUNCT
brj-22966	52	12	but	but	CCONJ
brj-22966	52	13	typically	typically	ADV
brj-22966	52	14	not	not	PART
brj-22966	52	15	much	much	ADV
brj-22966	52	16	elongated	elongate	VERB
brj-22966	52	17	,	,	PUNCT
brj-22966	52	18	with	with	ADP
brj-22966	52	19	thick	thick	ADJ
brj-22966	52	20	,	,	PUNCT
brj-22966	52	21	often	often	ADV
brj-22966	52	22	polylamellate	polylamellate	VERB
brj-22966	52	23	,	,	PUNCT
brj-22966	52	24	lignified	lignify	VERB
brj-22966	52	25	secondary	secondary	ADJ
brj-22966	52	26	walls	wall	NOUN
brj-22966	52	27	with	with	ADP
brj-22966	52	28	many	many	ADJ
brj-22966	52	29	pits	pit	NOUN
brj-22966	52	30	.	.	PUNCT
brj-22966	53	1	they	they	PRON
brj-22966	53	2	develop	develop	VERB
brj-22966	53	3	mainly	mainly	ADV
brj-22966	53	4	in	in	ADP
brj-22966	53	5	the	the	DET
brj-22966	53	6	nonconducting	nonconducte	VERB
brj-22966	53	7	phloem	phloem	NOUN
brj-22966	53	8	,	,	PUNCT
brj-22966	53	9	cortex	cortex	NOUN
brj-22966	53	10	,	,	PUNCT
brj-22966	53	11	and	and	CCONJ
brj-22966	53	12	periderm	periderm	NOUN
brj-22966	53	13	by	by	ADP
brj-22966	53	14	modification	modification	NOUN
brj-22966	53	15	of	of	ADP
brj-22966	53	16	parenchyma	parenchyma	NOUN
brj-22966	53	17	cells	cell	NOUN
brj-22966	53	18	.	.	PUNCT
brj-22966	54	1	however	however	ADV
brj-22966	54	2	,	,	PUNCT
brj-22966	54	3	there	there	PRON
brj-22966	54	4	are	be	VERB
brj-22966	54	5	some	some	DET
brj-22966	54	6	examples	example	NOUN
brj-22966	54	7	of	of	ADP
brj-22966	54	8	earlier	early	ADJ
brj-22966	54	9	development	development	NOUN
brj-22966	54	10	directly	directly	ADV
brj-22966	54	11	from	from	ADP
brj-22966	54	12	cambial	cambial	ADJ
brj-22966	54	13	derivatives	derivative	NOUN
brj-22966	54	14	.	.	PUNCT
brj-22966	55	1	sclereids	sclereid	NOUN
brj-22966	55	2	are	be	AUX
brj-22966	55	3	extremely	extremely	ADV
brj-22966	55	4	variable	variable	ADJ
brj-22966	55	5	in	in	ADP
brj-22966	55	6	size	size	NOUN
brj-22966	55	7	and	and	CCONJ
brj-22966	55	8	shape	shape	NOUN
brj-22966	55	9	,	,	PUNCT
brj-22966	55	10	and	and	CCONJ
brj-22966	55	11	this	this	DET
brj-22966	55	12	diversity	diversity	NOUN
brj-22966	55	13	has	have	AUX
brj-22966	55	14	been	be	AUX
brj-22966	55	15	classified	classify	VERB
brj-22966	55	16	into	into	ADP
brj-22966	55	17	different	different	ADJ
brj-22966	55	18	sclereid	sclereid	NOUN
brj-22966	55	19	types	type	NOUN
brj-22966	55	20	for	for	ADP
brj-22966	55	21	the	the	DET
brj-22966	55	22	plant	plant	NOUN
brj-22966	55	23	body	body	NOUN
brj-22966	55	24	,	,	PUNCT
brj-22966	55	25	including	include	VERB
brj-22966	55	26	brachysclereids	brachysclereid	NOUN
brj-22966	55	27	,	,	PUNCT
brj-22966	55	28	columnar	columnar	ADJ
brj-22966	55	29	sclereids	sclereid	NOUN
brj-22966	55	30	,	,	PUNCT
brj-22966	55	31	osteosclereids	osteosclereid	NOUN
brj-22966	55	32	,	,	PUNCT
brj-22966	55	33	astrosclereids	astrosclereid	NOUN
brj-22966	55	34	,	,	PUNCT
brj-22966	55	35	and	and	CCONJ
brj-22966	55	36	filiform	filiform	NOUN
brj-22966	55	37	sclereids	sclereid	NOUN
brj-22966	55	38	.	.	PUNCT
brj-22966	56	1	thus	thus	ADV
brj-22966	56	2	,	,	PUNCT
brj-22966	56	3	sclereids	sclereid	NOUN
brj-22966	56	4	can	can	AUX
brj-22966	56	5	be	be	AUX
brj-22966	56	6	used	use	VERB
brj-22966	56	7	as	as	ADP
brj-22966	56	8	keys	key	NOUN
brj-22966	56	9	for	for	ADP
brj-22966	56	10	species	species	NOUN
brj-22966	56	11	differentiation	differentiation	NOUN
brj-22966	56	12	(	(	PUNCT
brj-22966	56	13	iawa	iawa	PROPN
brj-22966	56	14	committee	committee	PROPN
brj-22966	56	15	2016	2016	NUM
brj-22966	56	16	)	)	PUNCT
brj-22966	56	17	.	.	PUNCT
brj-22966	57	1	therefore	therefore	ADV
brj-22966	57	2	,	,	PUNCT
brj-22966	57	3	in	in	ADP
brj-22966	57	4	the	the	DET
brj-22966	57	5	present	present	ADJ
brj-22966	57	6	study	study	NOUN
brj-22966	57	7	,	,	PUNCT
brj-22966	57	8	the	the	DET
brj-22966	57	9	performance	performance	NOUN
brj-22966	57	10	and	and	CCONJ
brj-22966	57	11	performance	performance	NOUN
brj-22966	57	12	-	-	PUNCT
brj-22966	57	13	influencing	influence	VERB
brj-22966	57	14	factors	factor	NOUN
brj-22966	57	15	of	of	ADP
brj-22966	57	16	cnns	cnn	NOUN
brj-22966	57	17	using	use	VERB
brj-22966	57	18	sclereid	sclereid	NOUN
brj-22966	57	19	characteristics	characteristic	NOUN
brj-22966	57	20	in	in	ADP
brj-22966	57	21	the	the	DET
brj-22966	57	22	bark	bark	NOUN
brj-22966	57	23	to	to	PART
brj-22966	57	24	identify	identify	VERB
brj-22966	57	25	seven	seven	NUM
brj-22966	57	26	oak	oak	NOUN
brj-22966	57	27	species	specie	NOUN
brj-22966	57	28	were	be	AUX
brj-22966	57	29	investigated	investigate	VERB
brj-22966	57	30	.	.	PUNCT
brj-22966	58	1	three	three	NUM
brj-22966	58	2	optimizers	optimizer	NOUN
brj-22966	58	3	,	,	PUNCT
brj-22966	58	4	stochastic	stochastic	ADJ
brj-22966	58	5	gradient	gradient	ADJ
brj-22966	58	6	descent	descent	NOUN
brj-22966	58	7	(	(	PUNCT
brj-22966	58	8	sgd	sgd	PROPN
brj-22966	58	9	)	)	PUNCT
brj-22966	58	10	,	,	PUNCT
brj-22966	58	11	adaptive	adaptive	ADJ
brj-22966	58	12	moment	moment	NOUN
brj-22966	58	13	estimation	estimation	NOUN
brj-22966	58	14	(	(	PUNCT
brj-22966	58	15	adam	adam	PROPN
brj-22966	58	16	)	)	PUNCT
brj-22966	58	17	,	,	PUNCT
brj-22966	58	18	and	and	CCONJ
brj-22966	58	19	root	root	NOUN
brj-22966	58	20	mean	mean	ADJ
brj-22966	58	21	square	square	ADJ
brj-22966	58	22	propagation	propagation	NOUN
brj-22966	58	23	(	(	PUNCT
brj-22966	58	24	rmsprop	rmsprop	NOUN
brj-22966	58	25	)	)	PUNCT
brj-22966	58	26	,	,	PUNCT
brj-22966	58	27	were	be	AUX
brj-22966	58	28	used	use	VERB
brj-22966	58	29	to	to	PART
brj-22966	58	30	analyze	analyze	VERB
brj-22966	58	31	the	the	DET
brj-22966	58	32	feasibility	feasibility	NOUN
brj-22966	58	33	and	and	CCONJ
brj-22966	58	34	efficacy	efficacy	NOUN
brj-22966	58	35	of	of	ADP
brj-22966	58	36	the	the	DET
brj-22966	58	37	classification	classification	NOUN
brj-22966	58	38	performance	performance	NOUN
brj-22966	58	39	of	of	ADP
brj-22966	58	40	the	the	DET
brj-22966	58	41	wood	wood	NOUN
brj-22966	58	42	species	specie	NOUN
brj-22966	58	43	.	.	PUNCT
brj-22966	59	1	experimental	experimental	ADJ
brj-22966	59	2	materials	material	NOUN
brj-22966	59	3	the	the	DET
brj-22966	59	4	barks	bark	NOUN
brj-22966	59	5	of	of	ADP
brj-22966	59	6	six	six	NUM
brj-22966	59	7	domestic	domestic	ADJ
brj-22966	59	8	oak	oak	NOUN
brj-22966	59	9	species	specie	NOUN
brj-22966	59	10	obtained	obtain	VERB
brj-22966	59	11	from	from	ADP
brj-22966	59	12	the	the	DET
brj-22966	59	13	research	research	NOUN
brj-22966	59	14	forest	forest	NOUN
brj-22966	59	15	of	of	ADP
brj-22966	59	16	kangwon	kangwon	PROPN
brj-22966	59	17	national	national	PROPN
brj-22966	59	18	university	university	PROPN
brj-22966	59	19	,	,	PUNCT
brj-22966	59	20	and	and	CCONJ
brj-22966	59	21	quercus	quercus	ADJ
brj-22966	59	22	suber	suber	NOUN
brj-22966	59	23	,	,	PUNCT
brj-22966	59	24	donated	donate	VERB
brj-22966	59	25	by	by	ADP
brj-22966	59	26	fc	fc	PROPN
brj-22966	59	27	korea	korea	PROPN
brj-22966	59	28	land	land	PROPN
brj-22966	59	29	co.	co.	PROPN
brj-22966	59	30	,	,	PUNCT
brj-22966	59	31	ltd	ltd	PROPN
brj-22966	59	32	.	.	PROPN
brj-22966	59	33	(	(	PUNCT
brj-22966	59	34	seoul	seoul	PROPN
brj-22966	59	35	,	,	PUNCT
brj-22966	59	36	korea	korea	PROPN
brj-22966	59	37	)	)	PUNCT
brj-22966	59	38	,	,	PUNCT
brj-22966	59	39	were	be	AUX
brj-22966	59	40	used	use	VERB
brj-22966	59	41	in	in	ADP
brj-22966	59	42	this	this	DET
brj-22966	59	43	study	study	NOUN
brj-22966	59	44	.	.	PUNCT
brj-22966	60	1	three	three	NUM
brj-22966	60	2	stems	stem	NOUN
brj-22966	60	3	of	of	ADP
brj-22966	60	4	each	each	PRON
brj-22966	60	5	of	of	ADP
brj-22966	60	6	the	the	DET
brj-22966	60	7	six	six	NUM
brj-22966	60	8	domestic	domestic	ADJ
brj-22966	60	9	oak	oak	NOUN
brj-22966	60	10	species	specie	NOUN
brj-22966	60	11	were	be	AUX
brj-22966	60	12	harvested	harvest	VERB
brj-22966	60	13	,	,	PUNCT
brj-22966	60	14	and	and	CCONJ
brj-22966	60	15	bark	bark	NOUN
brj-22966	60	16	samples	sample	NOUN
brj-22966	60	17	were	be	AUX
brj-22966	60	18	collected	collect	VERB
brj-22966	60	19	from	from	ADP
brj-22966	60	20	the	the	DET
brj-22966	60	21	breast	breast	NOUN
brj-22966	60	22	height	height	NOUN
brj-22966	60	23	of	of	ADP
brj-22966	60	24	the	the	DET
brj-22966	60	25	stems	stem	NOUN
brj-22966	60	26	.	.	PUNCT
brj-22966	61	1	several	several	ADJ
brj-22966	61	2	q.	q.	PROPN
brj-22966	61	3	suber	suber	PROPN
brj-22966	61	4	bark	bark	NOUN
brj-22966	61	5	samples	sample	NOUN
brj-22966	61	6	with	with	ADP
brj-22966	61	7	dimensions	dimension	NOUN
brj-22966	61	8	of	of	ADP
brj-22966	61	9	60	60	NUM
brj-22966	61	10	×	×	NOUN
brj-22966	61	11	100	100	NUM
brj-22966	61	12	cm	cm	NOUN
brj-22966	61	13	were	be	AUX
brj-22966	61	14	also	also	ADV
brj-22966	61	15	used	use	VERB
brj-22966	61	16	.	.	PUNCT
brj-22966	62	1	comprehensive	comprehensive	ADJ
brj-22966	62	2	information	information	NOUN
brj-22966	62	3	about	about	ADP
brj-22966	62	4	the	the	DET
brj-22966	62	5	samples	sample	NOUN
brj-22966	62	6	is	be	AUX
brj-22966	62	7	presented	present	VERB
brj-22966	62	8	in	in	ADP
brj-22966	62	9	table	table	NOUN
brj-22966	62	10	1	1	NUM
brj-22966	62	11	.	.	PUNCT
brj-22966	62	12	table	table	NOUN
brj-22966	62	13	1	1	NUM
brj-22966	62	14	.	.	PUNCT
brj-22966	62	15	sample	sample	NOUN
brj-22966	62	16	information	information	NOUN
brj-22966	62	17	scientific	scientific	ADJ
brj-22966	62	18	name	name	NOUN
brj-22966	62	19	d.b.h	d.b.h	NOUN
brj-22966	62	20	.	.	PUNCT
brj-22966	63	1	(	(	PUNCT
brj-22966	63	2	cm	cm	NOUN
brj-22966	63	3	)	)	PUNCT
brj-22966	63	4	*	*	PUNCT
brj-22966	63	5	origin	origin	NOUN
brj-22966	63	6	quercus	quercus	ADJ
brj-22966	63	7	dentata	dentata	NOUN
brj-22966	63	8	thunb	thunb	NOUN
brj-22966	63	9	.	.	PUNCT
brj-22966	64	1	22.7	22.7	NUM
brj-22966	64	2	±	±	NUM
brj-22966	64	3	1.8	1.8	NUM
brj-22966	64	4	research	research	NOUN
brj-22966	64	5	forest	forest	NOUN
brj-22966	64	6	of	of	ADP
brj-22966	64	7	kangwon	kangwon	PROPN
brj-22966	64	8	national	national	PROPN
brj-22966	64	9	university	university	PROPN
brj-22966	64	10	(	(	PUNCT
brj-22966	64	11	chuncheon	chuncheon	PROPN
brj-22966	64	12	,	,	PUNCT
brj-22966	64	13	korea	korea	PROPN
brj-22966	64	14	n37.7748857	n37.7748857	NUM
brj-22966	64	15	,	,	PUNCT
brj-22966	64	16	e127.8134654	e127.8134654	ADJ
brj-22966	64	17	)	)	PUNCT
brj-22966	64	18	quercus	quercus	ADJ
brj-22966	64	19	serrata	serrata	NOUN
brj-22966	64	20	murray	murray	PROPN
brj-22966	64	21	27.7	27.7	NUM
brj-22966	64	22	±	±	NUM
brj-22966	64	23	3.7	3.7	NUM
brj-22966	64	24	quercus	quercus	ADJ
brj-22966	64	25	mongolica	mongolica	PROPN
brj-22966	64	26	fisch	fisch	PROPN
brj-22966	64	27	.	.	PUNCT
brj-22966	65	1	ex	ex	X
brj-22966	66	1	ledeb	ledeb	ADJ
brj-22966	66	2	.	.	PUNCT
brj-22966	67	1	25.4	25.4	NUM
brj-22966	67	2	±	±	NUM
brj-22966	67	3	2.3	2.3	NUM
brj-22966	67	4	quercus	quercus	ADJ
brj-22966	67	5	variabilis	variabilis	NOUN
brj-22966	67	6	blume	blume	PROPN
brj-22966	67	7	25.5	25.5	NUM
brj-22966	67	8	±	±	NUM
brj-22966	67	9	3.1	3.1	NUM
brj-22966	67	10	quercus	quercus	PROPN
brj-22966	67	11	aliena	aliena	PROPN
brj-22966	67	12	blume	blume	PROPN
brj-22966	67	13	20.7	20.7	NUM
brj-22966	67	14	±	±	NUM
brj-22966	67	15	4.9	4.9	NUM
brj-22966	67	16	quercus	quercus	ADJ
brj-22966	67	17	acutissima	acutissima	PROPN
brj-22966	67	18	carruth	carruth	PROPN
brj-22966	67	19	.	.	PUNCT
brj-22966	68	1	22.1	22.1	NUM
brj-22966	68	2	±	±	NUM
brj-22966	68	3	6.2	6.2	NUM
brj-22966	68	4	quercus	quercus	ADJ
brj-22966	68	5	suber	suber	NOUN
brj-22966	68	6	l.	l.	NOUN
brj-22966	68	7	*	*	PUNCT
brj-22966	68	8	*	*	PUNCT
brj-22966	68	9	planks	plank	NOUN
brj-22966	68	10	of	of	ADP
brj-22966	68	11	60	60	NUM
brj-22966	68	12	×	×	NOUN
brj-22966	68	13	100	100	NUM
brj-22966	68	14	cm	cm	NOUN
brj-22966	68	15	portugal	portugal	PROPN
brj-22966	68	16	cork	cork	NOUN
brj-22966	68	17	provided	provide	VERB
brj-22966	68	18	by	by	ADP
brj-22966	68	19	fc	fc	PROPN
brj-22966	68	20	korea	korea	PROPN
brj-22966	68	21	land	land	PROPN
brj-22966	68	22	co.	co.	PROPN
brj-22966	68	23	,	,	PUNCT
brj-22966	68	24	ltd	ltd	PROPN
brj-22966	68	25	.	.	PROPN
brj-22966	68	26	(	(	PUNCT
brj-22966	68	27	seoul	seoul	PROPN
brj-22966	68	28	,	,	PUNCT
brj-22966	68	29	korea	korea	PROPN
brj-22966	68	30	)	)	PUNCT
brj-22966	68	31	*	*	PUNCT
brj-22966	68	32	d.b.h	d.b.h	PROPN
brj-22966	68	33	.	.	PUNCT
brj-22966	68	34	:	:	PUNCT
brj-22966	69	1	diameter	diameter	NOUN
brj-22966	69	2	at	at	ADP
brj-22966	69	3	breast	breast	NOUN
brj-22966	69	4	height	height	NOUN
brj-22966	69	5	methods	method	NOUN
brj-22966	69	6	sample	sample	NOUN
brj-22966	69	7	preparation	preparation	NOUN
brj-22966	69	8	for	for	ADP
brj-22966	69	9	the	the	DET
brj-22966	69	10	dataset	dataset	NOUN
brj-22966	69	11	wood	wood	NOUN
brj-22966	69	12	discs	disc	NOUN
brj-22966	69	13	(	(	PUNCT
brj-22966	69	14	3	3	NUM
brj-22966	69	15	cm	cm	NOUN
brj-22966	69	16	thick	thick	ADJ
brj-22966	69	17	)	)	PUNCT
brj-22966	69	18	were	be	AUX
brj-22966	69	19	prepared	prepare	VERB
brj-22966	69	20	using	use	VERB
brj-22966	69	21	a	a	DET
brj-22966	69	22	chainsaw	chainsaw	NOUN
brj-22966	69	23	from	from	ADP
brj-22966	69	24	the	the	DET
brj-22966	69	25	breast	breast	NOUN
brj-22966	69	26	height	height	NOUN
brj-22966	69	27	of	of	ADP
brj-22966	69	28	each	each	DET
brj-22966	69	29	oak	oak	NOUN
brj-22966	69	30	trees	tree	NOUN
brj-22966	69	31	.	.	PUNCT
brj-22966	70	1	the	the	DET
brj-22966	70	2	barks	bark	NOUN
brj-22966	70	3	were	be	AUX
brj-22966	70	4	carefully	carefully	ADV
brj-22966	70	5	detached	detach	VERB
brj-22966	70	6	from	from	ADP
brj-22966	70	7	the	the	DET
brj-22966	70	8	discs	disc	NOUN
brj-22966	70	9	.	.	PUNCT
brj-22966	71	1	after	after	ADP
brj-22966	71	2	separating	separate	VERB
brj-22966	71	3	the	the	DET
brj-22966	71	4	bark	bark	NOUN
brj-22966	71	5	from	from	ADP
brj-22966	71	6	the	the	DET
brj-22966	71	7	disc	disc	NOUN
brj-22966	71	8	,	,	PUNCT
brj-22966	71	9	a	a	DET
brj-22966	71	10	table	table	NOUN
brj-22966	71	11	saw	see	VERB
brj-22966	71	12	(	(	PUNCT
brj-22966	71	13	professional	professional	ADJ
brj-22966	71	14	cabinet	cabinet	NOUN
brj-22966	71	15	saw	see	VERB
brj-22966	71	16	model	model	NOUN
brj-22966	71	17	with	with	ADP
brj-22966	71	18	100	100	NUM
brj-22966	71	19	-	-	PUNCT
brj-22966	71	20	teeth	tooth	NOUN
brj-22966	71	21	saw	see	VERB
brj-22966	71	22	blade	blade	NOUN
brj-22966	71	23	,	,	PUNCT
brj-22966	71	24	sawstop	sawstop	NOUN
brj-22966	71	25	,	,	PUNCT
brj-22966	71	26	oregon	oregon	PROPN
brj-22966	71	27	,	,	PUNCT
brj-22966	71	28	usa	usa	PROPN
brj-22966	71	29	)	)	PUNCT
brj-22966	71	30	was	be	AUX
brj-22966	71	31	used	use	VERB
brj-22966	71	32	to	to	PART
brj-22966	71	33	cut	cut	VERB
brj-22966	71	34	the	the	DET
brj-22966	71	35	top	top	NOUN
brj-22966	71	36	and	and	CCONJ
brj-22966	71	37	bottom	bottom	NOUN
brj-22966	71	38	of	of	ADP
brj-22966	71	39	the	the	DET
brj-22966	71	40	bark	bark	NOUN
brj-22966	71	41	specimen	speciman	NOUN
brj-22966	71	42	to	to	ADP
brj-22966	71	43	a	a	DET
brj-22966	71	44	uniform	uniform	ADJ
brj-22966	71	45	thickness	thickness	NOUN
brj-22966	71	46	of	of	ADP
brj-22966	71	47	about	about	ADV
brj-22966	71	48	1	1	NUM
brj-22966	71	49	cm	cm	NOUN
brj-22966	71	50	for	for	ADP
brj-22966	71	51	easier	easy	ADJ
brj-22966	71	52	microscopic	microscopic	ADJ
brj-22966	71	53	observation	observation	NOUN
brj-22966	71	54	.	.	PUNCT
brj-22966	72	1	transverse	transverse	NOUN
brj-22966	72	2	sections	section	NOUN
brj-22966	72	3	were	be	AUX
brj-22966	72	4	sanded	sand	VERB
brj-22966	72	5	using	use	VERB
brj-22966	72	6	a	a	DET
brj-22966	72	7	series	series	NOUN
brj-22966	72	8	of	of	ADP
brj-22966	72	9	progressively	progressively	ADV
brj-22966	72	10	finer	fine	ADJ
brj-22966	72	11	sandpapers	sandpaper	NOUN
brj-22966	72	12	:	:	PUNCT
brj-22966	72	13	#	#	SYM
brj-22966	72	14	80	80	NUM
brj-22966	72	15	,	,	PUNCT
brj-22966	72	16	#	#	SYM
brj-22966	72	17	120	120	NUM
brj-22966	72	18	,	,	PUNCT
brj-22966	72	19	#	#	SYM
brj-22966	72	20	220	220	NUM
brj-22966	72	21	,	,	PUNCT
brj-22966	72	22	and	and	CCONJ
brj-22966	72	23	#	#	SYM
brj-22966	72	24	400	400	NUM
brj-22966	72	25	.	.	PUNCT
brj-22966	73	1	after	after	ADP
brj-22966	73	2	the	the	DET
brj-22966	73	3	sanding	sanding	NOUN
brj-22966	73	4	treatment	treatment	NOUN
brj-22966	73	5	,	,	PUNCT
brj-22966	73	6	the	the	DET
brj-22966	73	7	surface	surface	NOUN
brj-22966	73	8	was	be	AUX
brj-22966	73	9	cleaned	clean	VERB
brj-22966	73	10	using	use	VERB
brj-22966	73	11	an	an	DET
brj-22966	73	12	air	air	NOUN
brj-22966	73	13	compressor	compressor	NOUN
brj-22966	73	14	.	.	PUNCT
brj-22966	74	1	twenty	twenty	NUM
brj-22966	74	2	specimens	specimen	NOUN
brj-22966	74	3	of	of	ADP
brj-22966	74	4	each	each	DET
brj-22966	74	5	species	specie	NOUN
brj-22966	74	6	were	be	AUX
brj-22966	74	7	examined	examine	VERB
brj-22966	74	8	using	use	VERB
brj-22966	74	9	a	a	DET
brj-22966	74	10	visual	visual	ADJ
brj-22966	74	11	microscope	microscope	NOUN
brj-22966	74	12	(	(	PUNCT
brj-22966	74	13	mm-40	mm-40	NOUN
brj-22966	74	14	,	,	PUNCT
brj-22966	74	15	nikon	nikon	PROPN
brj-22966	74	16	,	,	PUNCT
brj-22966	74	17	tokyo	tokyo	PROPN
brj-22966	74	18	,	,	PUNCT
brj-22966	74	19	japan	japan	PROPN
brj-22966	74	20	)	)	PUNCT
brj-22966	74	21	equipped	equip	VERB
brj-22966	74	22	with	with	ADP
brj-22966	74	23	a	a	DET
brj-22966	74	24	2.5x	2.5x	NUM
brj-22966	74	25	objective	objective	ADJ
brj-22966	74	26	lens	lens	NOUN
brj-22966	74	27	(	(	PUNCT
brj-22966	74	28	cf	cf	NOUN
brj-22966	74	29	plan	plan	NOUN
brj-22966	74	30	2.5x	2.5x	NUM
brj-22966	74	31	,	,	PUNCT
brj-22966	74	32	nikon	nikon	PROPN
brj-22966	74	33	,	,	PUNCT
brj-22966	74	34	tokyo	tokyo	PROPN
brj-22966	74	35	,	,	PUNCT
brj-22966	74	36	japan	japan	PROPN
brj-22966	74	37	)	)	PUNCT
brj-22966	74	38	.	.	PUNCT
brj-22966	75	1	peer	peer	NOUN
brj-22966	75	2	-	-	PUNCT
brj-22966	75	3	reviewed	review	VERB
brj-22966	75	4	article	article	NOUN
brj-22966	75	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	75	6	kim	kim	PROPN
brj-22966	75	7	et	et	PROPN
brj-22966	75	8	al	al	PROPN
brj-22966	75	9	.	.	PROPN
brj-22966	76	1	(	(	PUNCT
brj-22966	76	2	2024	2024	NUM
brj-22966	76	3	)	)	PUNCT
brj-22966	76	4	.	.	PUNCT
brj-22966	77	1	“	"	PUNCT
brj-22966	77	2	convolutional	convolutional	ADJ
brj-22966	77	3	neural	neural	ADJ
brj-22966	77	4	network	network	NOUN
brj-22966	77	5	,	,	PUNCT
brj-22966	77	6	”	"	PUNCT
brj-22966	77	7	bioresources	bioresource	NOUN
brj-22966	77	8	19(1	19(1	NUM
brj-22966	77	9	)	)	PUNCT
brj-22966	77	10	,	,	PUNCT
brj-22966	77	11	510	510	NUM
brj-22966	77	12	-	-	SYM
brj-22966	77	13	524	524	NUM
brj-22966	77	14	.	.	PUNCT
brj-22966	78	1	513	513	NUM
brj-22966	78	2	digital	digital	ADJ
brj-22966	78	3	micrographs	micrograph	NOUN
brj-22966	78	4	of	of	ADP
brj-22966	78	5	the	the	DET
brj-22966	78	6	inner	inner	ADJ
brj-22966	78	7	phloem	phloem	NOUN
brj-22966	78	8	of	of	ADP
brj-22966	78	9	the	the	DET
brj-22966	78	10	bark	bark	NOUN
brj-22966	78	11	specimens	specimen	NOUN
brj-22966	78	12	were	be	AUX
brj-22966	78	13	obtained	obtain	VERB
brj-22966	78	14	using	use	VERB
brj-22966	78	15	a	a	DET
brj-22966	78	16	microscope	microscope	NOUN
brj-22966	78	17	camera	camera	NOUN
brj-22966	78	18	(	(	PUNCT
brj-22966	78	19	imtcam	imtcam	VERB
brj-22966	78	20	;	;	PUNCT
brj-22966	78	21	imt	imt	PROPN
brj-22966	78	22	,	,	PUNCT
brj-22966	78	23	british	british	PROPN
brj-22966	78	24	columbia	columbia	PROPN
brj-22966	78	25	,	,	PUNCT
brj-22966	78	26	canada	canada	PROPN
brj-22966	78	27	)	)	PUNCT
brj-22966	78	28	and	and	CCONJ
brj-22966	78	29	subsequently	subsequently	ADV
brj-22966	78	30	used	use	VERB
brj-22966	78	31	as	as	ADP
brj-22966	78	32	a	a	DET
brj-22966	78	33	dataset	dataset	NOUN
brj-22966	78	34	.	.	PUNCT
brj-22966	79	1	the	the	DET
brj-22966	79	2	collection	collection	NOUN
brj-22966	79	3	contained	contain	VERB
brj-22966	79	4	1,400	1,400	NUM
brj-22966	79	5	(	(	PUNCT
brj-22966	79	6	200	200	NUM
brj-22966	79	7	for	for	ADP
brj-22966	79	8	each	each	DET
brj-22966	79	9	species	specie	NOUN
brj-22966	79	10	)	)	PUNCT
brj-22966	79	11	microscopic	microscopic	ADJ
brj-22966	79	12	images	image	NOUN
brj-22966	79	13	.	.	PUNCT
brj-22966	80	1	general	general	ADJ
brj-22966	80	2	macroscopic	macroscopic	NOUN
brj-22966	80	3	features	feature	VERB
brj-22966	80	4	sclereid	sclereid	NOUN
brj-22966	80	5	characteristics	characteristic	NOUN
brj-22966	80	6	,	,	PUNCT
brj-22966	80	7	which	which	PRON
brj-22966	80	8	are	be	AUX
brj-22966	80	9	representative	representative	ADJ
brj-22966	80	10	macroscopic	macroscopic	ADJ
brj-22966	80	11	anatomical	anatomical	ADJ
brj-22966	80	12	features	feature	NOUN
brj-22966	80	13	of	of	ADP
brj-22966	80	14	the	the	DET
brj-22966	80	15	seven	seven	NUM
brj-22966	80	16	oak	oak	NOUN
brj-22966	80	17	species	specie	NOUN
brj-22966	80	18	,	,	PUNCT
brj-22966	80	19	were	be	AUX
brj-22966	80	20	analyzed	analyze	VERB
brj-22966	80	21	using	use	VERB
brj-22966	80	22	micrographs	micrograph	NOUN
brj-22966	80	23	obtained	obtain	VERB
brj-22966	80	24	to	to	PART
brj-22966	80	25	prepare	prepare	VERB
brj-22966	80	26	a	a	DET
brj-22966	80	27	dataset	dataset	NOUN
brj-22966	80	28	.	.	PUNCT
brj-22966	81	1	five	five	NUM
brj-22966	81	2	micrographs	micrograph	NOUN
brj-22966	81	3	of	of	ADP
brj-22966	81	4	each	each	DET
brj-22966	81	5	species	specie	NOUN
brj-22966	81	6	were	be	AUX
brj-22966	81	7	analyzed	analyze	VERB
brj-22966	81	8	to	to	PART
brj-22966	81	9	determine	determine	VERB
brj-22966	81	10	the	the	DET
brj-22966	81	11	quantitative	quantitative	ADJ
brj-22966	81	12	characteristics	characteristic	NOUN
brj-22966	81	13	of	of	ADP
brj-22966	81	14	the	the	DET
brj-22966	81	15	sclereids	sclereid	NOUN
brj-22966	81	16	.	.	PUNCT
brj-22966	82	1	the	the	DET
brj-22966	82	2	number	number	NOUN
brj-22966	82	3	of	of	ADP
brj-22966	82	4	sclereids	sclereid	NOUN
brj-22966	82	5	within	within	ADP
brj-22966	82	6	one	one	NUM
brj-22966	82	7	micrograph	micrograph	NOUN
brj-22966	82	8	(	(	PUNCT
brj-22966	82	9	3.75	3.75	NUM
brj-22966	82	10	×	×	NOUN
brj-22966	82	11	2.50	2.50	NUM
brj-22966	82	12	mm	mm	NOUN
brj-22966	82	13	)	)	PUNCT
brj-22966	82	14	,	,	PUNCT
brj-22966	82	15	the	the	DET
brj-22966	82	16	area	area	NOUN
brj-22966	82	17	of	of	ADP
brj-22966	82	18	individual	individual	ADJ
brj-22966	82	19	sclereids	sclereid	NOUN
brj-22966	82	20	,	,	PUNCT
brj-22966	82	21	and	and	CCONJ
brj-22966	82	22	the	the	DET
brj-22966	82	23	minimum	minimum	ADJ
brj-22966	82	24	and	and	CCONJ
brj-22966	82	25	maximum	maximum	ADJ
brj-22966	82	26	area	area	NOUN
brj-22966	82	27	of	of	ADP
brj-22966	82	28	sclereids	sclereid	NOUN
brj-22966	82	29	for	for	ADP
brj-22966	82	30	each	each	DET
brj-22966	82	31	species	specie	NOUN
brj-22966	82	32	were	be	AUX
brj-22966	82	33	measured	measure	VERB
brj-22966	82	34	.	.	PUNCT
brj-22966	83	1	dataset	dataset	NOUN
brj-22966	83	2	pretreatment	pretreatment	NOUN
brj-22966	83	3	the	the	DET
brj-22966	83	4	training	training	NOUN
brj-22966	83	5	dataset	dataset	NOUN
brj-22966	83	6	was	be	AUX
brj-22966	83	7	augmented	augment	VERB
brj-22966	83	8	to	to	PART
brj-22966	83	9	examine	examine	VERB
brj-22966	83	10	the	the	DET
brj-22966	83	11	influence	influence	NOUN
brj-22966	83	12	of	of	ADP
brj-22966	83	13	the	the	DET
brj-22966	83	14	dataset	dataset	NOUN
brj-22966	83	15	size	size	NOUN
brj-22966	83	16	on	on	ADP
brj-22966	83	17	the	the	DET
brj-22966	83	18	training	training	NOUN
brj-22966	83	19	procedure	procedure	NOUN
brj-22966	83	20	for	for	ADP
brj-22966	83	21	the	the	DET
brj-22966	83	22	neural	neural	ADJ
brj-22966	83	23	network	network	NOUN
brj-22966	83	24	architecture	architecture	NOUN
brj-22966	83	25	.	.	PUNCT
brj-22966	84	1	several	several	ADJ
brj-22966	84	2	parameters	parameter	NOUN
brj-22966	84	3	were	be	AUX
brj-22966	84	4	applied	apply	VERB
brj-22966	84	5	to	to	ADP
brj-22966	84	6	quantitatively	quantitatively	ADV
brj-22966	84	7	pretreat	pretreat	VERB
brj-22966	84	8	and	and	CCONJ
brj-22966	84	9	augment	augment	VERB
brj-22966	84	10	the	the	DET
brj-22966	84	11	dataset	dataset	NOUN
brj-22966	84	12	images	image	NOUN
brj-22966	84	13	.	.	PUNCT
brj-22966	85	1	the	the	DET
brj-22966	85	2	parameters	parameter	NOUN
brj-22966	85	3	included	include	VERB
brj-22966	85	4	rescaling	rescale	VERB
brj-22966	85	5	the	the	DET
brj-22966	85	6	data	datum	NOUN
brj-22966	85	7	using	use	VERB
brj-22966	85	8	a	a	DET
brj-22966	85	9	ratio	ratio	NOUN
brj-22966	85	10	of	of	ADP
brj-22966	85	11	1/255	1/255	NUM
brj-22966	85	12	for	for	ADP
brj-22966	85	13	normalization	normalization	NOUN
brj-22966	85	14	,	,	PUNCT
brj-22966	85	15	10	10	NUM
brj-22966	85	16	°	°	NUM
brj-22966	85	17	rotation	rotation	NOUN
brj-22966	85	18	,	,	PUNCT
brj-22966	85	19	shifting	shift	VERB
brj-22966	85	20	the	the	DET
brj-22966	85	21	data	datum	NOUN
brj-22966	85	22	horizontally	horizontally	ADV
brj-22966	85	23	and	and	CCONJ
brj-22966	85	24	vertically	vertically	ADV
brj-22966	85	25	by	by	ADP
brj-22966	85	26	10	10	NUM
brj-22966	85	27	%	%	NOUN
brj-22966	85	28	,	,	PUNCT
brj-22966	85	29	zooming	zoom	VERB
brj-22966	85	30	the	the	DET
brj-22966	85	31	data	datum	NOUN
brj-22966	85	32	by	by	ADP
brj-22966	85	33	20	20	NUM
brj-22966	85	34	%	%	NOUN
brj-22966	85	35	,	,	PUNCT
brj-22966	85	36	and	and	CCONJ
brj-22966	85	37	performing	perform	VERB
brj-22966	85	38	horizontal	horizontal	ADJ
brj-22966	85	39	and	and	CCONJ
brj-22966	85	40	vertical	vertical	ADJ
brj-22966	85	41	flipping	flipping	NOUN
brj-22966	85	42	.	.	PUNCT
brj-22966	86	1	figure	figure	NOUN
brj-22966	86	2	1	1	NUM
brj-22966	86	3	illustrates	illustrate	VERB
brj-22966	86	4	the	the	DET
brj-22966	86	5	examples	example	NOUN
brj-22966	86	6	of	of	ADP
brj-22966	86	7	data	datum	NOUN
brj-22966	86	8	augmentation	augmentation	NOUN
brj-22966	86	9	.	.	PUNCT
brj-22966	87	1	fig	fig	NOUN
brj-22966	87	2	.	.	PUNCT
brj-22966	88	1	1	1	NUM
brj-22966	88	2	.	.	NOUN
brj-22966	88	3	example	example	NOUN
brj-22966	88	4	micrographs	micrograph	NOUN
brj-22966	88	5	of	of	ADP
brj-22966	88	6	quercus	quercus	ADJ
brj-22966	88	7	aliena	aliena	PROPN
brj-22966	88	8	:	:	PUNCT
brj-22966	88	9	(	(	PUNCT
brj-22966	88	10	a	a	X
brj-22966	88	11	)	)	PUNCT
brj-22966	88	12	original	original	ADJ
brj-22966	88	13	image	image	NOUN
brj-22966	88	14	;	;	PUNCT
brj-22966	88	15	(	(	PUNCT
brj-22966	88	16	b	b	X
brj-22966	88	17	-	-	PUNCT
brj-22966	88	18	k	k	NOUN
brj-22966	88	19	)	)	PUNCT
brj-22966	88	20	augmented	augment	VERB
brj-22966	88	21	images	image	NOUN
brj-22966	88	22	the	the	DET
brj-22966	88	23	dataset	dataset	NOUN
brj-22966	88	24	consisted	consist	VERB
brj-22966	88	25	of	of	ADP
brj-22966	88	26	1,400	1,400	NUM
brj-22966	88	27	images	image	NOUN
brj-22966	88	28	,	,	PUNCT
brj-22966	88	29	with	with	ADP
brj-22966	88	30	200	200	NUM
brj-22966	88	31	images	image	NOUN
brj-22966	88	32	per	per	ADP
brj-22966	88	33	species	specie	NOUN
brj-22966	88	34	.	.	PUNCT
brj-22966	89	1	the	the	DET
brj-22966	89	2	dataset	dataset	NOUN
brj-22966	89	3	was	be	AUX
brj-22966	89	4	divided	divide	VERB
brj-22966	89	5	into	into	ADP
brj-22966	89	6	80	80	NUM
brj-22966	89	7	%	%	NOUN
brj-22966	89	8	for	for	ADP
brj-22966	89	9	training	training	NOUN
brj-22966	89	10	and	and	CCONJ
brj-22966	89	11	20	20	NUM
brj-22966	89	12	%	%	NOUN
brj-22966	89	13	for	for	ADP
brj-22966	89	14	testing	testing	NOUN
brj-22966	89	15	.	.	PUNCT
brj-22966	90	1	the	the	DET
brj-22966	90	2	test	test	NOUN
brj-22966	90	3	dataset	dataset	NOUN
brj-22966	90	4	was	be	AUX
brj-22966	90	5	created	create	VERB
brj-22966	90	6	by	by	ADP
brj-22966	90	7	using	use	VERB
brj-22966	90	8	a	a	DET
brj-22966	90	9	file	file	NOUN
brj-22966	90	10	random	random	ADJ
brj-22966	90	11	extraction	extraction	NOUN
brj-22966	90	12	program	program	NOUN
brj-22966	90	13	to	to	PART
brj-22966	90	14	extract	extract	VERB
brj-22966	90	15	40	40	NUM
brj-22966	90	16	out	out	ADP
brj-22966	90	17	of	of	ADP
brj-22966	90	18	200	200	NUM
brj-22966	90	19	images	image	NOUN
brj-22966	90	20	of	of	ADP
brj-22966	90	21	each	each	DET
brj-22966	90	22	species	specie	NOUN
brj-22966	90	23	dataset	dataset	VERB
brj-22966	90	24	.	.	PUNCT
brj-22966	91	1	the	the	DET
brj-22966	91	2	selected	select	VERB
brj-22966	91	3	images	image	NOUN
brj-22966	91	4	were	be	AUX
brj-22966	91	5	then	then	ADV
brj-22966	91	6	saved	save	VERB
brj-22966	91	7	in	in	ADP
brj-22966	91	8	the	the	DET
brj-22966	91	9	separated	separate	VERB
brj-22966	91	10	paths	path	NOUN
brj-22966	91	11	with	with	ADP
brj-22966	91	12	the	the	DET
brj-22966	91	13	training	training	NOUN
brj-22966	91	14	dataset	dataset	NOUN
brj-22966	91	15	.	.	PUNCT
brj-22966	92	1	data	datum	NOUN
brj-22966	92	2	augmentation	augmentation	NOUN
brj-22966	92	3	was	be	AUX
brj-22966	92	4	exclusively	exclusively	ADV
brj-22966	92	5	implemented	implement	VERB
brj-22966	92	6	on	on	ADP
brj-22966	92	7	the	the	DET
brj-22966	92	8	training	training	NOUN
brj-22966	92	9	dataset	dataset	NOUN
brj-22966	92	10	.	.	PUNCT
brj-22966	93	1	table	table	NOUN
brj-22966	93	2	2	2	NUM
brj-22966	93	3	shows	show	VERB
brj-22966	93	4	the	the	DET
brj-22966	93	5	disparity	disparity	NOUN
brj-22966	93	6	in	in	ADP
brj-22966	93	7	quantity	quantity	NOUN
brj-22966	93	8	between	between	ADP
brj-22966	93	9	the	the	DET
brj-22966	93	10	preand	preand	NOUN
brj-22966	93	11	post	post	ADJ
brj-22966	93	12	-	-	ADJ
brj-22966	93	13	augmentation	augmentation	ADJ
brj-22966	93	14	data	datum	NOUN
brj-22966	93	15	.	.	PUNCT
brj-22966	94	1	peer	peer	NOUN
brj-22966	94	2	-	-	PUNCT
brj-22966	94	3	reviewed	review	VERB
brj-22966	94	4	article	article	NOUN
brj-22966	94	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	94	6	kim	kim	PROPN
brj-22966	94	7	et	et	PROPN
brj-22966	94	8	al	al	PROPN
brj-22966	94	9	.	.	PROPN
brj-22966	95	1	(	(	PUNCT
brj-22966	95	2	2024	2024	NUM
brj-22966	95	3	)	)	PUNCT
brj-22966	95	4	.	.	PUNCT
brj-22966	96	1	“	"	PUNCT
brj-22966	96	2	convolutional	convolutional	ADJ
brj-22966	96	3	neural	neural	ADJ
brj-22966	96	4	network	network	NOUN
brj-22966	96	5	,	,	PUNCT
brj-22966	96	6	”	"	PUNCT
brj-22966	96	7	bioresources	bioresource	NOUN
brj-22966	96	8	19(1	19(1	NUM
brj-22966	96	9	)	)	PUNCT
brj-22966	96	10	,	,	PUNCT
brj-22966	96	11	510	510	NUM
brj-22966	96	12	-	-	SYM
brj-22966	96	13	524	524	NUM
brj-22966	96	14	.	.	PUNCT
brj-22966	97	1	514	514	NUM
brj-22966	97	2	table	table	NOUN
brj-22966	97	3	2	2	NUM
brj-22966	97	4	.	.	PUNCT
brj-22966	97	5	composition	composition	NOUN
brj-22966	97	6	of	of	ADP
brj-22966	97	7	training	training	NOUN
brj-22966	97	8	and	and	CCONJ
brj-22966	97	9	test	test	NOUN
brj-22966	97	10	dataset	dataset	VERB
brj-22966	97	11	in	in	ADP
brj-22966	97	12	augmentation	augmentation	NOUN
brj-22966	97	13	scientific	scientific	ADJ
brj-22966	97	14	name	name	NOUN
brj-22966	97	15	non	non	ADJ
brj-22966	97	16	-	-	ADJ
brj-22966	97	17	augmented	augment	VERB
brj-22966	97	18	augmented	augment	VERB
brj-22966	97	19	train	train	NOUN
brj-22966	97	20	(	(	PUNCT
brj-22966	97	21	80	80	NUM
brj-22966	97	22	%	%	NOUN
brj-22966	97	23	)	)	PUNCT
brj-22966	97	24	test	test	NOUN
brj-22966	97	25	(	(	PUNCT
brj-22966	97	26	20	20	NUM
brj-22966	97	27	%	%	NOUN
brj-22966	97	28	)	)	PUNCT
brj-22966	97	29	sum	sum	NOUN
brj-22966	97	30	train	train	NOUN
brj-22966	97	31	test	test	NOUN
brj-22966	97	32	sum	sum	VERB
brj-22966	97	33	quercus	quercus	ADJ
brj-22966	97	34	dentata	dentata	NOUN
brj-22966	97	35	160	160	NUM
brj-22966	97	36	40	40	NUM
brj-22966	97	37	200	200	NUM
brj-22966	97	38	1,773	1,773	NUM
brj-22966	97	39	40	40	NUM
brj-22966	97	40	1,813	1,813	NUM
brj-22966	97	41	quercus	quercus	ADJ
brj-22966	97	42	serrata	serrata	NOUN
brj-22966	97	43	160	160	NUM
brj-22966	97	44	40	40	NUM
brj-22966	97	45	200	200	NUM
brj-22966	97	46	1,761	1,761	NUM
brj-22966	97	47	40	40	NUM
brj-22966	97	48	1,801	1,801	NUM
brj-22966	97	49	quercus	quercus	ADJ
brj-22966	97	50	mongolica	mongolica	NOUN
brj-22966	97	51	160	160	NUM
brj-22966	97	52	40	40	NUM
brj-22966	97	53	200	200	NUM
brj-22966	97	54	1,768	1,768	NUM
brj-22966	97	55	40	40	NUM
brj-22966	97	56	1,808	1,808	NUM
brj-22966	97	57	quercus	quercus	ADJ
brj-22966	97	58	variabilis	variabilis	NOUN
brj-22966	97	59	160	160	NUM
brj-22966	97	60	40	40	NUM
brj-22966	97	61	200	200	NUM
brj-22966	97	62	1,751	1,751	NUM
brj-22966	97	63	40	40	NUM
brj-22966	97	64	1,791	1,791	NUM
brj-22966	97	65	quercus	quercus	ADJ
brj-22966	97	66	aliena	aliena	PROPN
brj-22966	97	67	160	160	NUM
brj-22966	97	68	40	40	NUM
brj-22966	97	69	200	200	NUM
brj-22966	97	70	1,784	1,784	NUM
brj-22966	97	71	40	40	NUM
brj-22966	97	72	1,824	1,824	NUM
brj-22966	97	73	quercus	quercus	ADJ
brj-22966	97	74	acutissima	acutissima	NOUN
brj-22966	97	75	160	160	NUM
brj-22966	97	76	40	40	NUM
brj-22966	97	77	200	200	NUM
brj-22966	97	78	1,764	1,764	NUM
brj-22966	97	79	40	40	NUM
brj-22966	97	80	1,804	1,804	NUM
brj-22966	97	81	quercus	quercus	ADJ
brj-22966	97	82	suber	suber	NOUN
brj-22966	97	83	160	160	NUM
brj-22966	97	84	40	40	NUM
brj-22966	97	85	200	200	NUM
brj-22966	97	86	1,778	1,778	NUM
brj-22966	97	87	40	40	NUM
brj-22966	97	88	1,818	1,818	NUM
brj-22966	97	89	total	total	NOUN
brj-22966	97	90	1,120	1,120	NUM
brj-22966	97	91	280	280	NUM
brj-22966	97	92	1,400	1,400	NUM
brj-22966	97	93	12,379	12,379	NUM
brj-22966	97	94	280	280	NUM
brj-22966	97	95	12,659	12,659	NUM
brj-22966	97	96	verification	verification	NOUN
brj-22966	97	97	factors	factor	NOUN
brj-22966	97	98	influencing	influence	VERB
brj-22966	97	99	cnn	cnn	PROPN
brj-22966	97	100	classification	classification	NOUN
brj-22966	97	101	performance	performance	NOUN
brj-22966	97	102	and	and	CCONJ
brj-22966	97	103	the	the	DET
brj-22966	97	104	factors	factor	NOUN
brj-22966	97	105	influencing	influence	VERB
brj-22966	97	106	performance	performance	NOUN
brj-22966	97	107	were	be	AUX
brj-22966	97	108	analyzed	analyze	VERB
brj-22966	97	109	using	use	VERB
brj-22966	97	110	basic	basic	ADJ
brj-22966	97	111	cnn	cnn	NOUN
brj-22966	97	112	architecture	architecture	NOUN
brj-22966	97	113	,	,	PUNCT
brj-22966	97	114	as	as	SCONJ
brj-22966	97	115	depicted	depict	VERB
brj-22966	97	116	in	in	ADP
brj-22966	97	117	fig	fig	NOUN
brj-22966	97	118	.	.	PUNCT
brj-22966	98	1	2	2	X
brj-22966	98	2	.	.	X
brj-22966	98	3	the	the	DET
brj-22966	98	4	architecture	architecture	NOUN
brj-22966	98	5	of	of	ADP
brj-22966	98	6	the	the	DET
brj-22966	98	7	cnn	cnn	PROPN
brj-22966	98	8	was	be	AUX
brj-22966	98	9	designed	design	VERB
brj-22966	98	10	by	by	ADP
brj-22966	98	11	referring	refer	VERB
brj-22966	98	12	to	to	ADP
brj-22966	98	13	the	the	DET
brj-22966	98	14	general	general	ADJ
brj-22966	98	15	structure	structure	NOUN
brj-22966	98	16	reported	report	VERB
brj-22966	98	17	in	in	ADP
brj-22966	98	18	the	the	DET
brj-22966	98	19	past	past	NOUN
brj-22966	98	20	(	(	PUNCT
brj-22966	98	21	elgendy	elgendy	ADJ
brj-22966	98	22	2021	2021	NUM
brj-22966	98	23	;	;	PUNCT
brj-22966	98	24	loy	loy	PROPN
brj-22966	98	25	2020	2020	NUM
brj-22966	98	26	)	)	PUNCT
brj-22966	98	27	.	.	PUNCT
brj-22966	99	1	the	the	DET
brj-22966	99	2	cnn	cnn	PROPN
brj-22966	99	3	design	design	NOUN
brj-22966	99	4	comprised	comprise	VERB
brj-22966	99	5	four	four	NUM
brj-22966	99	6	convolutional	convolutional	ADJ
brj-22966	99	7	layers	layer	NOUN
brj-22966	99	8	,	,	PUNCT
brj-22966	99	9	four	four	NUM
brj-22966	99	10	maxpooling	maxpoole	VERB
brj-22966	99	11	layers	layer	NOUN
brj-22966	99	12	,	,	PUNCT
brj-22966	99	13	and	and	CCONJ
brj-22966	99	14	two	two	NUM
brj-22966	99	15	fully	fully	ADV
brj-22966	99	16	connected	connected	ADJ
brj-22966	99	17	layers	layer	NOUN
brj-22966	99	18	.	.	PUNCT
brj-22966	100	1	furthermore	furthermore	ADV
brj-22966	100	2	,	,	PUNCT
brj-22966	100	3	the	the	DET
brj-22966	100	4	model	model	NOUN
brj-22966	100	5	was	be	AUX
brj-22966	100	6	enhanced	enhance	VERB
brj-22966	100	7	by	by	ADP
brj-22966	100	8	incorporating	incorporate	VERB
brj-22966	100	9	two	two	NUM
brj-22966	100	10	dropout	dropout	NOUN
brj-22966	100	11	layers	layer	NOUN
brj-22966	100	12	and	and	CCONJ
brj-22966	100	13	a	a	DET
brj-22966	100	14	flattened	flatten	VERB
brj-22966	100	15	layer	layer	NOUN
brj-22966	100	16	.	.	PUNCT
brj-22966	101	1	finally	finally	ADV
brj-22966	101	2	,	,	PUNCT
brj-22966	101	3	the	the	DET
brj-22966	101	4	softmax	softmax	NOUN
brj-22966	101	5	activation	activation	NOUN
brj-22966	101	6	function	function	NOUN
brj-22966	101	7	was	be	AUX
brj-22966	101	8	applied	apply	VERB
brj-22966	101	9	.	.	PUNCT
brj-22966	102	1	fig	fig	NOUN
brj-22966	102	2	.	.	PUNCT
brj-22966	103	1	2	2	X
brj-22966	103	2	.	.	X
brj-22966	103	3	convolutional	convolutional	ADJ
brj-22966	103	4	neural	neural	ADJ
brj-22966	103	5	network	network	NOUN
brj-22966	103	6	architecture	architecture	NOUN
brj-22966	103	7	for	for	ADP
brj-22966	103	8	species	specie	NOUN
brj-22966	103	9	classification	classification	NOUN
brj-22966	103	10	in	in	ADP
brj-22966	103	11	the	the	DET
brj-22966	103	12	present	present	ADJ
brj-22966	103	13	study	study	NOUN
brj-22966	103	14	peer	peer	NOUN
brj-22966	103	15	-	-	PUNCT
brj-22966	103	16	reviewed	review	VERB
brj-22966	103	17	article	article	NOUN
brj-22966	103	18	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	103	19	kim	kim	PROPN
brj-22966	103	20	et	et	PROPN
brj-22966	103	21	al	al	PROPN
brj-22966	103	22	.	.	PROPN
brj-22966	104	1	(	(	PUNCT
brj-22966	104	2	2024	2024	NUM
brj-22966	104	3	)	)	PUNCT
brj-22966	104	4	.	.	PUNCT
brj-22966	105	1	“	"	PUNCT
brj-22966	105	2	convolutional	convolutional	ADJ
brj-22966	105	3	neural	neural	ADJ
brj-22966	105	4	network	network	NOUN
brj-22966	105	5	,	,	PUNCT
brj-22966	105	6	”	"	PUNCT
brj-22966	105	7	bioresources	bioresource	NOUN
brj-22966	105	8	19(1	19(1	NUM
brj-22966	105	9	)	)	PUNCT
brj-22966	105	10	,	,	PUNCT
brj-22966	105	11	510	510	NUM
brj-22966	105	12	-	-	SYM
brj-22966	105	13	524	524	NUM
brj-22966	105	14	.	.	PUNCT
brj-22966	106	1	515	515	NUM
brj-22966	106	2	the	the	DET
brj-22966	106	3	cnn	cnn	PROPN
brj-22966	106	4	architecture	architecture	NOUN
brj-22966	106	5	was	be	AUX
brj-22966	106	6	trained	train	VERB
brj-22966	106	7	using	use	VERB
brj-22966	106	8	a	a	DET
brj-22966	106	9	dataset	dataset	NOUN
brj-22966	106	10	comprising	comprise	VERB
brj-22966	106	11	seven	seven	NUM
brj-22966	106	12	oak	oak	NOUN
brj-22966	106	13	species	specie	NOUN
brj-22966	106	14	.	.	PUNCT
brj-22966	107	1	categorical	categorical	ADJ
brj-22966	107	2	cross	cross	NOUN
brj-22966	107	3	-	-	NOUN
brj-22966	107	4	entropy	entropy	NOUN
brj-22966	107	5	was	be	AUX
brj-22966	107	6	used	use	VERB
brj-22966	107	7	as	as	ADP
brj-22966	107	8	the	the	DET
brj-22966	107	9	loss	loss	NOUN
brj-22966	107	10	function	function	NOUN
brj-22966	107	11	for	for	ADP
brj-22966	107	12	the	the	DET
brj-22966	107	13	multiclass	multiclass	ADJ
brj-22966	107	14	classification	classification	NOUN
brj-22966	107	15	.	.	PUNCT
brj-22966	108	1	optimizers	optimizer	NOUN
brj-22966	108	2	are	be	AUX
brj-22966	108	3	tools	tool	NOUN
brj-22966	108	4	used	use	VERB
brj-22966	108	5	to	to	PART
brj-22966	108	6	optimize	optimize	VERB
brj-22966	108	7	the	the	DET
brj-22966	108	8	resources	resource	NOUN
brj-22966	108	9	used	use	VERB
brj-22966	108	10	during	during	ADP
brj-22966	108	11	weight	weight	NOUN
brj-22966	108	12	updates	update	NOUN
brj-22966	108	13	in	in	ADP
brj-22966	108	14	each	each	DET
brj-22966	108	15	training	training	NOUN
brj-22966	108	16	phase	phase	NOUN
brj-22966	108	17	(	(	PUNCT
brj-22966	108	18	cho	cho	NOUN
brj-22966	108	19	2018	2018	NUM
brj-22966	108	20	)	)	PUNCT
brj-22966	108	21	.	.	PUNCT
brj-22966	109	1	in	in	ADP
brj-22966	109	2	this	this	DET
brj-22966	109	3	study	study	NOUN
brj-22966	109	4	,	,	PUNCT
brj-22966	109	5	three	three	NUM
brj-22966	109	6	specific	specific	ADJ
brj-22966	109	7	optimizers	optimizer	NOUN
brj-22966	109	8	(	(	PUNCT
brj-22966	109	9	i.e.	i.e.	X
brj-22966	109	10	,	,	PUNCT
brj-22966	109	11	sgd	sgd	PROPN
brj-22966	109	12	,	,	PUNCT
brj-22966	109	13	adam	adam	PROPN
brj-22966	109	14	,	,	PUNCT
brj-22966	109	15	and	and	CCONJ
brj-22966	109	16	rmsprop	rmsprop	NOUN
brj-22966	109	17	)	)	PUNCT
brj-22966	109	18	were	be	AUX
brj-22966	109	19	used	use	VERB
brj-22966	109	20	and	and	CCONJ
brj-22966	109	21	compared	compare	VERB
brj-22966	109	22	to	to	PART
brj-22966	109	23	assess	assess	VERB
brj-22966	109	24	the	the	DET
brj-22966	109	25	influence	influence	NOUN
brj-22966	109	26	of	of	ADP
brj-22966	109	27	different	different	ADJ
brj-22966	109	28	optimizers	optimizer	NOUN
brj-22966	109	29	on	on	ADP
brj-22966	109	30	the	the	DET
brj-22966	109	31	efficiency	efficiency	NOUN
brj-22966	109	32	of	of	ADP
brj-22966	109	33	a	a	DET
brj-22966	109	34	cnn	cnn	PROPN
brj-22966	109	35	.	.	PUNCT
brj-22966	110	1	the	the	DET
brj-22966	110	2	learning	learning	NOUN
brj-22966	110	3	rates	rate	NOUN
brj-22966	110	4	for	for	ADP
brj-22966	110	5	each	each	DET
brj-22966	110	6	optimizer	optimizer	NOUN
brj-22966	110	7	were	be	AUX
brj-22966	110	8	set	set	VERB
brj-22966	110	9	to	to	ADP
brj-22966	110	10	sgd	sgd	PROPN
brj-22966	110	11	0.0001	0.0001	NUM
brj-22966	110	12	,	,	PUNCT
brj-22966	110	13	adam	adam	PROPN
brj-22966	110	14	0.001	0.001	NUM
brj-22966	110	15	(	(	PUNCT
brj-22966	110	16	default	default	NOUN
brj-22966	110	17	)	)	PUNCT
brj-22966	110	18	,	,	PUNCT
brj-22966	110	19	and	and	CCONJ
brj-22966	110	20	rmsprop	rmsprop	NOUN
brj-22966	110	21	0.00001	0.00001	NUM
brj-22966	110	22	,	,	PUNCT
brj-22966	110	23	respectively	respectively	ADV
brj-22966	110	24	.	.	PUNCT
brj-22966	111	1	statistical	statistical	ADJ
brj-22966	111	2	analysis	analysis	NOUN
brj-22966	111	3	of	of	ADP
brj-22966	111	4	factors	factor	NOUN
brj-22966	111	5	influencing	influence	VERB
brj-22966	111	6	cnn	cnn	PROPN
brj-22966	111	7	bivariate	bivariate	ADJ
brj-22966	111	8	correlation	correlation	NOUN
brj-22966	111	9	analysis	analysis	NOUN
brj-22966	111	10	(	(	PUNCT
brj-22966	111	11	spss	spss	PROPN
brj-22966	111	12	26.0	26.0	NUM
brj-22966	111	13	;	;	PUNCT
brj-22966	111	14	ibm	ibm	PROPN
brj-22966	111	15	,	,	PUNCT
brj-22966	111	16	new	new	PROPN
brj-22966	111	17	york	york	PROPN
brj-22966	111	18	,	,	PUNCT
brj-22966	111	19	usa	usa	PROPN
brj-22966	111	20	)	)	PUNCT
brj-22966	111	21	was	be	AUX
brj-22966	111	22	used	use	VERB
brj-22966	111	23	to	to	PART
brj-22966	111	24	examine	examine	VERB
brj-22966	111	25	the	the	DET
brj-22966	111	26	pearson	pearson	NOUN
brj-22966	111	27	correlation	correlation	NOUN
brj-22966	111	28	coefficients	coefficient	NOUN
brj-22966	111	29	between	between	ADP
brj-22966	111	30	the	the	DET
brj-22966	111	31	variables	variable	NOUN
brj-22966	111	32	.	.	PUNCT
brj-22966	112	1	the	the	DET
brj-22966	112	2	optimizer	optimizer	NOUN
brj-22966	112	3	type	type	NOUN
brj-22966	112	4	and	and	CCONJ
brj-22966	112	5	augmentation	augmentation	NOUN
brj-22966	112	6	for	for	ADP
brj-22966	112	7	the	the	DET
brj-22966	112	8	analysis	analysis	NOUN
brj-22966	112	9	were	be	AUX
brj-22966	112	10	used	use	VERB
brj-22966	112	11	as	as	ADP
brj-22966	112	12	nominal	nominal	ADJ
brj-22966	112	13	variables	variable	NOUN
brj-22966	112	14	,	,	PUNCT
brj-22966	112	15	whereas	whereas	SCONJ
brj-22966	112	16	the	the	DET
brj-22966	112	17	accuracy	accuracy	NOUN
brj-22966	112	18	and	and	CCONJ
brj-22966	112	19	loss	loss	NOUN
brj-22966	112	20	rate	rate	NOUN
brj-22966	112	21	were	be	AUX
brj-22966	112	22	used	use	VERB
brj-22966	112	23	as	as	ADP
brj-22966	112	24	scale	scale	NOUN
brj-22966	112	25	variables	variable	NOUN
brj-22966	112	26	.	.	PUNCT
brj-22966	113	1	additionally	additionally	ADV
brj-22966	113	2	,	,	PUNCT
brj-22966	113	3	a	a	DET
brj-22966	113	4	one	one	NUM
brj-22966	113	5	-	-	PUNCT
brj-22966	113	6	way	way	NOUN
brj-22966	113	7	anova	anova	PROPN
brj-22966	113	8	and	and	CCONJ
brj-22966	113	9	duncan	duncan	PROPN
brj-22966	113	10	’s	’s	PART
brj-22966	113	11	post	post	ADJ
brj-22966	113	12	-	-	ADJ
brj-22966	113	13	hoc	hoc	ADJ
brj-22966	113	14	analysis	analysis	NOUN
brj-22966	113	15	were	be	AUX
brj-22966	113	16	used	use	VERB
brj-22966	113	17	to	to	PART
brj-22966	113	18	examine	examine	VERB
brj-22966	113	19	the	the	DET
brj-22966	113	20	homogeneous	homogeneous	ADJ
brj-22966	113	21	subsets	subset	NOUN
brj-22966	113	22	of	of	ADP
brj-22966	113	23	the	the	DET
brj-22966	113	24	results	result	NOUN
brj-22966	113	25	.	.	PUNCT
brj-22966	114	1	results	result	NOUN
brj-22966	114	2	and	and	CCONJ
brj-22966	114	3	discussion	discussion	NOUN
brj-22966	114	4	figure	figure	NOUN
brj-22966	114	5	3	3	NUM
brj-22966	114	6	shows	show	VERB
brj-22966	114	7	cross	cross	ADJ
brj-22966	114	8	-	-	ADJ
brj-22966	114	9	sectional	sectional	ADJ
brj-22966	114	10	micrographs	micrograph	NOUN
brj-22966	114	11	of	of	ADP
brj-22966	114	12	the	the	DET
brj-22966	114	13	bark	bark	NOUN
brj-22966	114	14	of	of	ADP
brj-22966	114	15	the	the	DET
brj-22966	114	16	seven	seven	NUM
brj-22966	114	17	oak	oak	NOUN
brj-22966	114	18	species	specie	NOUN
brj-22966	114	19	in	in	ADP
brj-22966	114	20	the	the	DET
brj-22966	114	21	dataset	dataset	NOUN
brj-22966	114	22	.	.	PUNCT
brj-22966	115	1	except	except	SCONJ
brj-22966	115	2	for	for	ADP
brj-22966	115	3	q.	q.	PROPN
brj-22966	115	4	suber	suber	PROPN
brj-22966	115	5	bark	bark	NOUN
brj-22966	115	6	,	,	PUNCT
brj-22966	115	7	sclereids	sclereid	NOUN
brj-22966	115	8	were	be	AUX
brj-22966	115	9	found	find	VERB
brj-22966	115	10	in	in	ADP
brj-22966	115	11	the	the	DET
brj-22966	115	12	bark	bark	NOUN
brj-22966	115	13	of	of	ADP
brj-22966	115	14	all	all	DET
brj-22966	115	15	species	specie	NOUN
brj-22966	115	16	.	.	PUNCT
brj-22966	116	1	the	the	DET
brj-22966	116	2	sclereids	sclereid	NOUN
brj-22966	116	3	’	'	PUNCT
brj-22966	116	4	size	size	NOUN
brj-22966	116	5	,	,	PUNCT
brj-22966	116	6	shape	shape	NOUN
brj-22966	116	7	,	,	PUNCT
brj-22966	116	8	and	and	CCONJ
brj-22966	116	9	frequency	frequency	NOUN
brj-22966	116	10	varied	varied	ADJ
brj-22966	116	11	among	among	ADP
brj-22966	116	12	the	the	DET
brj-22966	116	13	species	specie	NOUN
brj-22966	116	14	.	.	PUNCT
brj-22966	117	1	table	table	NOUN
brj-22966	117	2	3	3	NUM
brj-22966	117	3	shows	show	VERB
brj-22966	117	4	a	a	DET
brj-22966	117	5	comparison	comparison	NOUN
brj-22966	117	6	of	of	ADP
brj-22966	117	7	the	the	DET
brj-22966	117	8	number	number	NOUN
brj-22966	117	9	of	of	ADP
brj-22966	117	10	sclereids	sclereid	NOUN
brj-22966	117	11	per	per	ADP
brj-22966	117	12	unit	unit	NOUN
brj-22966	117	13	area	area	NOUN
brj-22966	117	14	and	and	CCONJ
brj-22966	117	15	the	the	DET
brj-22966	117	16	size	size	NOUN
brj-22966	117	17	of	of	ADP
brj-22966	117	18	individual	individual	ADJ
brj-22966	117	19	sclereids	sclereid	NOUN
brj-22966	117	20	by	by	ADP
brj-22966	117	21	species	specie	NOUN
brj-22966	117	22	.	.	PUNCT
brj-22966	118	1	the	the	DET
brj-22966	118	2	sclereids	sclereid	NOUN
brj-22966	118	3	in	in	ADP
brj-22966	118	4	q.	q.	PROPN
brj-22966	118	5	variabilis	variabilis	PROPN
brj-22966	118	6	and	and	CCONJ
brj-22966	118	7	q.	q.	PROPN
brj-22966	118	8	aliena	aliena	PROPN
brj-22966	118	9	(	(	PUNCT
brj-22966	118	10	181.9	181.9	NUM
brj-22966	118	11	×	×	NOUN
brj-22966	118	12	103	103	NUM
brj-22966	118	13	µm2	µm2	NOUN
brj-22966	118	14	and	and	CCONJ
brj-22966	118	15	175.4	175.4	NUM
brj-22966	118	16	×	×	NOUN
brj-22966	118	17	103	103	NUM
brj-22966	118	18	µm2	µm2	NOUN
brj-22966	118	19	,	,	PUNCT
brj-22966	118	20	respectively	respectively	ADV
brj-22966	118	21	)	)	PUNCT
brj-22966	118	22	were	be	AUX
brj-22966	118	23	larger	large	ADJ
brj-22966	118	24	than	than	ADP
brj-22966	118	25	those	those	PRON
brj-22966	118	26	in	in	ADP
brj-22966	118	27	the	the	DET
brj-22966	118	28	other	other	ADJ
brj-22966	118	29	species	specie	NOUN
brj-22966	118	30	,	,	PUNCT
brj-22966	118	31	while	while	SCONJ
brj-22966	118	32	q.	q.	PROPN
brj-22966	118	33	serrata	serrata	PROPN
brj-22966	118	34	and	and	CCONJ
brj-22966	118	35	q.	q.	PROPN
brj-22966	118	36	acutissima	acutissima	PROPN
brj-22966	118	37	showed	show	VERB
brj-22966	118	38	smaller	small	ADJ
brj-22966	118	39	sizes	size	NOUN
brj-22966	118	40	(	(	PUNCT
brj-22966	118	41	52.7	52.7	NUM
brj-22966	118	42	×	×	NOUN
brj-22966	118	43	103	103	NUM
brj-22966	118	44	µm2	µm2	NOUN
brj-22966	118	45	and	and	CCONJ
brj-22966	118	46	65.4	65.4	NUM
brj-22966	118	47	×	×	NOUN
brj-22966	118	48	103	103	NUM
brj-22966	118	49	µm2	µm2	NOUN
brj-22966	118	50	,	,	PUNCT
brj-22966	118	51	respectively	respectively	ADV
brj-22966	118	52	)	)	PUNCT
brj-22966	118	53	compared	compare	VERB
brj-22966	118	54	to	to	ADP
brj-22966	118	55	other	other	ADJ
brj-22966	118	56	species	specie	NOUN
brj-22966	118	57	.	.	PUNCT
brj-22966	119	1	this	this	PRON
brj-22966	119	2	represented	represent	VERB
brj-22966	119	3	2to	2to	NOUN
brj-22966	119	4	4	4	NUM
brj-22966	119	5	-	-	ADJ
brj-22966	119	6	fold	fold	ADJ
brj-22966	119	7	differences	difference	NOUN
brj-22966	119	8	in	in	ADP
brj-22966	119	9	the	the	DET
brj-22966	119	10	sclereids	sclereid	NOUN
brj-22966	119	11	size	size	NOUN
brj-22966	119	12	between	between	ADP
brj-22966	119	13	species	specie	NOUN
brj-22966	119	14	.	.	PUNCT
brj-22966	120	1	q.	q.	PROPN
brj-22966	120	2	variabilis	variabilis	PROPN
brj-22966	120	3	and	and	CCONJ
brj-22966	120	4	q.	q.	PROPN
brj-22966	120	5	aliena	aliena	PROPN
brj-22966	120	6	showed	show	VERB
brj-22966	120	7	lower	low	ADJ
brj-22966	120	8	sclereid	sclereid	NOUN
brj-22966	120	9	frequencies	frequency	NOUN
brj-22966	120	10	than	than	ADP
brj-22966	120	11	other	other	ADJ
brj-22966	120	12	species	specie	NOUN
brj-22966	120	13	.	.	PUNCT
brj-22966	121	1	as	as	SCONJ
brj-22966	121	2	shown	show	VERB
brj-22966	121	3	in	in	ADP
brj-22966	121	4	fig	fig	NOUN
brj-22966	121	5	.	.	PUNCT
brj-22966	122	1	3f	3f	PROPN
brj-22966	122	2	,	,	PUNCT
brj-22966	122	3	sclereids	sclereids	PROPN
brj-22966	122	4	in	in	ADP
brj-22966	122	5	q.	q.	PROPN
brj-22966	122	6	acutissima	acutissima	PROPN
brj-22966	122	7	,	,	PUNCT
brj-22966	122	8	in	in	ADP
brj-22966	122	9	particular	particular	ADJ
brj-22966	122	10	,	,	PUNCT
brj-22966	122	11	had	have	VERB
brj-22966	122	12	a	a	DET
brj-22966	122	13	large	large	ADJ
brj-22966	122	14	variation	variation	NOUN
brj-22966	122	15	in	in	ADP
brj-22966	122	16	size	size	NOUN
brj-22966	122	17	.	.	PUNCT
brj-22966	123	1	prasetia	prasetia	PROPN
brj-22966	123	2	et	et	PROPN
brj-22966	123	3	al	al	PROPN
brj-22966	123	4	.	.	PROPN
brj-22966	124	1	(	(	PUNCT
brj-22966	124	2	2022	2022	NUM
brj-22966	124	3	)	)	PUNCT
brj-22966	124	4	previously	previously	ADV
brj-22966	124	5	reported	report	VERB
brj-22966	124	6	that	that	SCONJ
brj-22966	124	7	sclereids	sclereid	NOUN
brj-22966	124	8	were	be	AUX
brj-22966	124	9	frequently	frequently	ADV
brj-22966	124	10	found	find	VERB
brj-22966	124	11	in	in	ADP
brj-22966	124	12	the	the	DET
brj-22966	124	13	bark	bark	NOUN
brj-22966	124	14	of	of	ADP
brj-22966	124	15	q.	q.	PROPN
brj-22966	124	16	variabilis	variabilis	PROPN
brj-22966	124	17	and	and	CCONJ
brj-22966	124	18	were	be	AUX
brj-22966	124	19	absent	absent	ADJ
brj-22966	124	20	in	in	ADP
brj-22966	124	21	q.	q.	PROPN
brj-22966	124	22	suber	suber	PROPN
brj-22966	124	23	.	.	PUNCT
brj-22966	125	1	kim	kim	PROPN
brj-22966	125	2	(	(	PUNCT
brj-22966	125	3	1993	1993	NUM
brj-22966	125	4	)	)	PUNCT
brj-22966	125	5	conducted	conduct	VERB
brj-22966	125	6	a	a	DET
brj-22966	125	7	similar	similar	ADJ
brj-22966	125	8	study	study	NOUN
brj-22966	125	9	on	on	ADP
brj-22966	125	10	the	the	DET
brj-22966	125	11	anatomical	anatomical	ADJ
brj-22966	125	12	characteristics	characteristic	NOUN
brj-22966	125	13	of	of	ADP
brj-22966	125	14	q.	q.	PROPN
brj-22966	125	15	variabilis	variabilis	PROPN
brj-22966	125	16	and	and	CCONJ
brj-22966	125	17	q.	q.	PROPN
brj-22966	125	18	suber	suber	PROPN
brj-22966	125	19	and	and	CCONJ
brj-22966	125	20	reported	report	VERB
brj-22966	125	21	that	that	SCONJ
brj-22966	125	22	sclereids	sclereid	NOUN
brj-22966	125	23	were	be	AUX
brj-22966	125	24	rarely	rarely	ADV
brj-22966	125	25	present	present	ADJ
brj-22966	125	26	in	in	ADP
brj-22966	125	27	q.	q.	PROPN
brj-22966	125	28	suber	suber	PROPN
brj-22966	125	29	.	.	PUNCT
brj-22966	125	30	table	table	NOUN
brj-22966	126	1	3	3	NUM
brj-22966	126	2	.	.	PUNCT
brj-22966	126	3	quantitative	quantitative	ADJ
brj-22966	126	4	characteristics	characteristic	NOUN
brj-22966	126	5	of	of	ADP
brj-22966	126	6	sclereids	sclereid	NOUN
brj-22966	126	7	in	in	ADP
brj-22966	126	8	the	the	DET
brj-22966	126	9	six	six	NUM
brj-22966	126	10	oak	oak	NOUN
brj-22966	126	11	species	specie	NOUN
brj-22966	126	12	quantitative	quantitative	ADJ
brj-22966	126	13	factors	factor	NOUN
brj-22966	126	14	q.	q.	PROPN
brj-22966	126	15	dentata	dentata	PROPN
brj-22966	126	16	q.	q.	PROPN
brj-22966	126	17	serrata	serrata	PROPN
brj-22966	126	18	q.	q.	PROPN
brj-22966	126	19	mongolica	mongolica	PROPN
brj-22966	126	20	q.	q.	PROPN
brj-22966	126	21	variabilis	variabilis	PROPN
brj-22966	126	22	q.	q.	PROPN
brj-22966	126	23	aliena	aliena	PROPN
brj-22966	126	24	q.	q.	PROPN
brj-22966	126	25	acutissima	acutissima	PROPN
brj-22966	126	26	sclereids	sclereids	PROPN
brj-22966	126	27	number	number	NOUN
brj-22966	126	28	in	in	ADP
brj-22966	126	29	9.4	9.4	NUM
brj-22966	126	30	mm2	mm2	NOUN
brj-22966	126	31	35.0	35.0	NUM
brj-22966	126	32	±	±	NUM
brj-22966	126	33	2.6bc	2.6bc	NUM
brj-22966	126	34	10.0	10.0	NUM
brj-22966	126	35	±	±	NUM
brj-22966	126	36	2.6a	2.6a	NUM
brj-22966	126	37	26.0	26.0	NUM
brj-22966	126	38	±	±	NUM
brj-22966	126	39	3.6abc	3.6abc	NUM
brj-22966	126	40	19.3	19.3	NUM
brj-22966	126	41	±	±	NUM
brj-22966	126	42	10.2ab	10.2ab	NUM
brj-22966	126	43	20.7	20.7	NUM
brj-22966	126	44	±	±	NUM
brj-22966	126	45	4.0ab	4.0ab	NUM
brj-22966	126	46	39.3	39.3	NUM
brj-22966	126	47	±	±	NUM
brj-22966	126	48	16.9c	16.9c	NUM
brj-22966	126	49	area	area	NOUN
brj-22966	126	50	of	of	ADP
brj-22966	126	51	sclereids	sclereid	NOUN
brj-22966	126	52	(	(	PUNCT
brj-22966	126	53	1,000	1,000	NUM
brj-22966	126	54	µm2	µm2	NOUN
brj-22966	126	55	)	)	PUNCT
brj-22966	126	56	area	area	NOUN
brj-22966	126	57	range	range	NOUN
brj-22966	126	58	(	(	PUNCT
brj-22966	126	59	min	min	PROPN
brj-22966	126	60	–	–	PUNCT
brj-22966	126	61	max	max	NOUN
brj-22966	126	62	)	)	PUNCT
brj-22966	126	63	11.2	11.2	NUM
brj-22966	126	64	–	–	PUNCT
brj-22966	126	65	314.4	314.4	NUM
brj-22966	126	66	7.2	7.2	NUM
brj-22966	126	67	–	–	PUNCT
brj-22966	126	68	226.2	226.2	NUM
brj-22966	126	69	12.2	12.2	NUM
brj-22966	126	70	–	–	PUNCT
brj-22966	126	71	434.2	434.2	NUM
brj-22966	126	72	7.2	7.2	NUM
brj-22966	126	73	–	–	PUNCT
brj-22966	126	74	892.4	892.4	NUM
brj-22966	126	75	14.2	14.2	NUM
brj-22966	126	76	–	–	PUNCT
brj-22966	126	77	845.8	845.8	NUM
brj-22966	126	78	2.8–400.1	2.8–400.1	NUM
brj-22966	126	79	averag	averag	PROPN
brj-22966	126	80	e	e	PROPN
brj-22966	126	81	area	area	NOUN
brj-22966	126	82	72.7a	72.7a	NUM
brj-22966	126	83	52.7a	52.7a	NUM
brj-22966	127	1	125.3b	125.3b	NUM
brj-22966	127	2	181.9c	181.9c	NUM
brj-22966	127	3	175.4bc	175.4bc	NUM
brj-22966	127	4	65.4a	65.4a	NUM
brj-22966	127	5	note	note	NOUN
brj-22966	127	6	:	:	PUNCT
brj-22966	127	7	sclereids	sclereid	NOUN
brj-22966	127	8	were	be	AUX
brj-22966	127	9	not	not	PART
brj-22966	127	10	observed	observe	VERB
brj-22966	127	11	in	in	ADP
brj-22966	127	12	the	the	DET
brj-22966	127	13	bark	bark	NOUN
brj-22966	127	14	of	of	ADP
brj-22966	127	15	q.	q.	PROPN
brj-22966	127	16	suber	suber	PROPN
brj-22966	127	17	.	.	PUNCT
brj-22966	128	1	the	the	DET
brj-22966	128	2	same	same	ADJ
brj-22966	128	3	superscript	superscript	ADJ
brj-22966	128	4	lowercase	lowercase	NOUN
brj-22966	128	5	letters	letter	NOUN
brj-22966	128	6	beside	beside	ADP
brj-22966	128	7	the	the	DET
brj-22966	128	8	mean	mean	ADJ
brj-22966	128	9	values	value	NOUN
brj-22966	128	10	in	in	ADP
brj-22966	128	11	the	the	DET
brj-22966	128	12	same	same	ADJ
brj-22966	128	13	row	row	NOUN
brj-22966	128	14	denote	denote	NOUN
brj-22966	128	15	non	non	ADJ
brj-22966	128	16	-	-	ADJ
brj-22966	128	17	significant	significant	ADJ
brj-22966	128	18	outcomes	outcome	NOUN
brj-22966	128	19	at	at	ADP
brj-22966	128	20	the	the	DET
brj-22966	128	21	5	5	NUM
brj-22966	128	22	%	%	NOUN
brj-22966	128	23	significance	significance	NOUN
brj-22966	128	24	level	level	NOUN
brj-22966	128	25	for	for	ADP
brj-22966	128	26	comparisons	comparison	NOUN
brj-22966	128	27	between	between	ADP
brj-22966	128	28	species	specie	NOUN
brj-22966	128	29	.	.	PUNCT
brj-22966	129	1	peer	peer	NOUN
brj-22966	129	2	-	-	PUNCT
brj-22966	129	3	reviewed	review	VERB
brj-22966	129	4	article	article	NOUN
brj-22966	129	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	129	6	kim	kim	PROPN
brj-22966	129	7	et	et	PROPN
brj-22966	129	8	al	al	PROPN
brj-22966	129	9	.	.	PROPN
brj-22966	130	1	(	(	PUNCT
brj-22966	130	2	2024	2024	NUM
brj-22966	130	3	)	)	PUNCT
brj-22966	130	4	.	.	PUNCT
brj-22966	131	1	“	"	PUNCT
brj-22966	131	2	convolutional	convolutional	ADJ
brj-22966	131	3	neural	neural	ADJ
brj-22966	131	4	network	network	NOUN
brj-22966	131	5	,	,	PUNCT
brj-22966	131	6	”	"	PUNCT
brj-22966	131	7	bioresources	bioresource	NOUN
brj-22966	131	8	19(1	19(1	NUM
brj-22966	131	9	)	)	PUNCT
brj-22966	131	10	,	,	PUNCT
brj-22966	131	11	510	510	NUM
brj-22966	131	12	-	-	SYM
brj-22966	131	13	524	524	NUM
brj-22966	131	14	.	.	PUNCT
brj-22966	132	1	516	516	NUM
brj-22966	132	2	fig	fig	NOUN
brj-22966	132	3	.	.	PUNCT
brj-22966	133	1	3	3	X
brj-22966	133	2	.	.	X
brj-22966	133	3	cross	cross	ADJ
brj-22966	133	4	-	-	ADJ
brj-22966	133	5	section	section	NOUN
brj-22966	133	6	micrographs	micrograph	NOUN
brj-22966	133	7	of	of	ADP
brj-22966	133	8	the	the	DET
brj-22966	133	9	barks	bark	NOUN
brj-22966	133	10	from	from	ADP
brj-22966	133	11	seven	seven	NUM
brj-22966	133	12	quercus	quercus	ADJ
brj-22966	133	13	species	specie	NOUN
brj-22966	133	14	:	:	PUNCT
brj-22966	133	15	quercus	quercus	ADJ
brj-22966	133	16	dentata	dentata	NOUN
brj-22966	133	17	(	(	PUNCT
brj-22966	133	18	a	a	X
brj-22966	133	19	)	)	PUNCT
brj-22966	133	20	,	,	PUNCT
brj-22966	133	21	quercus	quercus	ADJ
brj-22966	133	22	serrata	serrata	NOUN
brj-22966	133	23	(	(	PUNCT
brj-22966	133	24	b	b	NOUN
brj-22966	133	25	)	)	PUNCT
brj-22966	133	26	,	,	PUNCT
brj-22966	133	27	quercus	quercus	ADJ
brj-22966	133	28	mongolica	mongolica	NOUN
brj-22966	133	29	(	(	PUNCT
brj-22966	133	30	c	c	NOUN
brj-22966	133	31	)	)	PUNCT
brj-22966	133	32	,	,	PUNCT
brj-22966	133	33	quercus	quercus	ADJ
brj-22966	133	34	variabilis	variabilis	NOUN
brj-22966	133	35	(	(	PUNCT
brj-22966	133	36	d	d	NOUN
brj-22966	133	37	)	)	PUNCT
brj-22966	133	38	,	,	PUNCT
brj-22966	133	39	quercus	quercus	ADJ
brj-22966	133	40	aliena	aliena	PROPN
brj-22966	133	41	(	(	PUNCT
brj-22966	133	42	e	e	NOUN
brj-22966	133	43	)	)	PUNCT
brj-22966	133	44	,	,	PUNCT
brj-22966	133	45	quercus	quercus	ADJ
brj-22966	133	46	acutissima	acutissima	NOUN
brj-22966	133	47	(	(	PUNCT
brj-22966	133	48	f	f	NOUN
brj-22966	133	49	)	)	PUNCT
brj-22966	133	50	,	,	PUNCT
brj-22966	133	51	and	and	CCONJ
brj-22966	133	52	quercus	quercus	ADJ
brj-22966	133	53	suber	suber	NOUN
brj-22966	133	54	(	(	PUNCT
brj-22966	133	55	g	g	NOUN
brj-22966	133	56	)	)	PUNCT
brj-22966	133	57	.	.	PUNCT
brj-22966	134	1	white	white	ADJ
brj-22966	134	2	arrows	arrow	NOUN
brj-22966	134	3	indicate	indicate	VERB
brj-22966	134	4	sclereids	sclereid	NOUN
brj-22966	134	5	.	.	PUNCT
brj-22966	135	1	scale	scale	NOUN
brj-22966	135	2	bars	bar	NOUN
brj-22966	135	3	:	:	PUNCT
brj-22966	135	4	1,000	1,000	NUM
brj-22966	135	5	µm	µm	ADP
brj-22966	135	6	peer	peer	NOUN
brj-22966	135	7	-	-	PUNCT
brj-22966	135	8	reviewed	review	VERB
brj-22966	135	9	article	article	NOUN
brj-22966	135	10	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	135	11	kim	kim	PROPN
brj-22966	135	12	et	et	PROPN
brj-22966	135	13	al	al	PROPN
brj-22966	135	14	.	.	PROPN
brj-22966	136	1	(	(	PUNCT
brj-22966	136	2	2024	2024	NUM
brj-22966	136	3	)	)	PUNCT
brj-22966	136	4	.	.	PUNCT
brj-22966	137	1	“	"	PUNCT
brj-22966	137	2	convolutional	convolutional	ADJ
brj-22966	137	3	neural	neural	ADJ
brj-22966	137	4	network	network	NOUN
brj-22966	137	5	,	,	PUNCT
brj-22966	137	6	”	"	PUNCT
brj-22966	137	7	bioresources	bioresource	NOUN
brj-22966	137	8	19(1	19(1	NUM
brj-22966	137	9	)	)	PUNCT
brj-22966	137	10	,	,	PUNCT
brj-22966	137	11	510	510	NUM
brj-22966	137	12	-	-	SYM
brj-22966	137	13	524	524	NUM
brj-22966	137	14	.	.	PUNCT
brj-22966	138	1	517	517	NUM
brj-22966	138	2	table	table	NOUN
brj-22966	138	3	4	4	NUM
brj-22966	138	4	.	.	PUNCT
brj-22966	138	5	comparison	comparison	NOUN
brj-22966	138	6	of	of	ADP
brj-22966	138	7	average	average	ADJ
brj-22966	138	8	loss	loss	NOUN
brj-22966	138	9	and	and	CCONJ
brj-22966	138	10	accuracy	accuracy	NOUN
brj-22966	138	11	on	on	ADP
brj-22966	138	12	the	the	DET
brj-22966	138	13	last	last	ADJ
brj-22966	138	14	five	five	NUM
brj-22966	138	15	steps	step	NOUN
brj-22966	138	16	per	per	ADP
brj-22966	138	17	optimizer	optimizer	NOUN
brj-22966	138	18	sgd	sgd	PROPN
brj-22966	138	19	adam	adam	PROPN
brj-22966	138	20	rmsprop	rmsprop	PROPN
brj-22966	138	21	non	non	PROPN
brj-22966	138	22	-	-	PROPN
brj-22966	138	23	aug	aug	PROPN
brj-22966	138	24	.	.	PROPN
brj-22966	139	1	augmented	augment	VERB
brj-22966	139	2	non	non	PROPN
brj-22966	139	3	-	-	PROPN
brj-22966	139	4	aug	aug	PROPN
brj-22966	139	5	.	.	PROPN
brj-22966	139	6	augmented	augment	VERB
brj-22966	139	7	non	non	PROPN
brj-22966	139	8	-	-	PROPN
brj-22966	139	9	aug	aug	PROPN
brj-22966	139	10	.	.	PROPN
brj-22966	139	11	augmented	augment	VERB
brj-22966	139	12	training	training	NOUN
brj-22966	139	13	process	process	NOUN
brj-22966	139	14	loss	loss	NOUN
brj-22966	139	15	0.430d	0.430d	PROPN
brj-22966	139	16	0.001a	0.001a	NOUN
brj-22966	139	17	0.020ab	0.020ab	NUM
brj-22966	139	18	0.032b	0.032b	NOUN
brj-22966	139	19	0.365c	0.365c	ADJ
brj-22966	139	20	0.031b	0.031b	ADJ
brj-22966	139	21	accuracy	accuracy	NOUN
brj-22966	139	22	0.833a	0.833a	NOUN
brj-22966	139	23	1.000c	1.000c	NUM
brj-22966	139	24	0.996c	0.996c	NOUN
brj-22966	139	25	0.995c	0.995c	ADJ
brj-22966	139	26	0.860b	0.860b	PROPN
brj-22966	139	27	0.996c	0.996c	NOUN
brj-22966	139	28	test	test	NOUN
brj-22966	139	29	process	process	NOUN
brj-22966	139	30	loss	loss	NOUN
brj-22966	139	31	0.498a	0.498a	ADV
brj-22966	139	32	0.855ab	0.855ab	NUM
brj-22966	139	33	0.843ab	0.843ab	NOUN
brj-22966	139	34	2.740c	2.740c	PROPN
brj-22966	139	35	0.623ab	0.623ab	NOUN
brj-22966	139	36	1.021b	1.021b	NUM
brj-22966	139	37	accuracy	accuracy	NOUN
brj-22966	139	38	0.820ab	0.820ab	NOUN
brj-22966	139	39	0.830ab	0.830ab	PROPN
brj-22966	139	40	0.798a	0.798a	NOUN
brj-22966	139	41	0.738a	0.738a	ADJ
brj-22966	139	42	0.795a	0.795a	NOUN
brj-22966	140	1	0.898b	0.898b	NUM
brj-22966	140	2	note	note	NOUN
brj-22966	140	3	:	:	PUNCT
brj-22966	140	4	the	the	DET
brj-22966	140	5	same	same	ADJ
brj-22966	140	6	superscript	superscript	ADJ
brj-22966	140	7	lowercase	lowercase	NOUN
brj-22966	140	8	letters	letter	NOUN
brj-22966	140	9	beside	beside	ADP
brj-22966	140	10	the	the	DET
brj-22966	140	11	mean	mean	ADJ
brj-22966	140	12	values	value	NOUN
brj-22966	140	13	in	in	ADP
brj-22966	140	14	the	the	DET
brj-22966	140	15	same	same	ADJ
brj-22966	140	16	row	row	NOUN
brj-22966	140	17	denote	denote	NOUN
brj-22966	140	18	nonsignificant	nonsignificant	ADJ
brj-22966	140	19	outcomes	outcome	NOUN
brj-22966	140	20	at	at	ADP
brj-22966	140	21	the	the	DET
brj-22966	140	22	5	5	NUM
brj-22966	140	23	%	%	NOUN
brj-22966	140	24	significance	significance	NOUN
brj-22966	140	25	level	level	NOUN
brj-22966	140	26	for	for	ADP
brj-22966	140	27	comparisons	comparison	NOUN
brj-22966	140	28	between	between	ADP
brj-22966	140	29	species	specie	NOUN
brj-22966	140	30	.	.	PUNCT
brj-22966	141	1	table	table	NOUN
brj-22966	141	2	4	4	NUM
brj-22966	141	3	lists	list	VERB
brj-22966	141	4	the	the	DET
brj-22966	141	5	average	average	ADJ
brj-22966	141	6	losses	loss	NOUN
brj-22966	141	7	and	and	CCONJ
brj-22966	141	8	classification	classification	NOUN
brj-22966	141	9	accuracies	accuracy	NOUN
brj-22966	141	10	during	during	ADP
brj-22966	141	11	the	the	DET
brj-22966	141	12	last	last	ADJ
brj-22966	141	13	five	five	NUM
brj-22966	141	14	stages	stage	NOUN
brj-22966	141	15	for	for	ADP
brj-22966	141	16	each	each	DET
brj-22966	141	17	validation	validation	NOUN
brj-22966	141	18	condition	condition	NOUN
brj-22966	141	19	.	.	PUNCT
brj-22966	142	1	during	during	ADP
brj-22966	142	2	the	the	DET
brj-22966	142	3	training	training	NOUN
brj-22966	142	4	phase	phase	NOUN
brj-22966	142	5	,	,	PUNCT
brj-22966	142	6	adam	adam	PROPN
brj-22966	142	7	produced	produce	VERB
brj-22966	142	8	the	the	DET
brj-22966	142	9	lowest	low	ADJ
brj-22966	142	10	loss	loss	NOUN
brj-22966	142	11	and	and	CCONJ
brj-22966	142	12	highest	high	ADJ
brj-22966	142	13	accuracy	accuracy	NOUN
brj-22966	142	14	,	,	PUNCT
brj-22966	142	15	suggesting	suggest	VERB
brj-22966	142	16	superior	superior	ADJ
brj-22966	142	17	performance	performance	NOUN
brj-22966	142	18	irrespective	irrespective	ADV
brj-22966	142	19	of	of	ADP
brj-22966	142	20	the	the	DET
brj-22966	142	21	implementation	implementation	NOUN
brj-22966	142	22	of	of	ADP
brj-22966	142	23	data	datum	NOUN
brj-22966	142	24	augmentation	augmentation	NOUN
brj-22966	142	25	.	.	PUNCT
brj-22966	143	1	however	however	ADV
brj-22966	143	2	,	,	PUNCT
brj-22966	143	3	adam	adam	PROPN
brj-22966	143	4	’s	’s	PART
brj-22966	143	5	performance	performance	NOUN
brj-22966	143	6	was	be	AUX
brj-22966	143	7	relatively	relatively	ADV
brj-22966	143	8	poor	poor	ADJ
brj-22966	143	9	compared	compare	VERB
brj-22966	143	10	to	to	ADP
brj-22966	143	11	the	the	DET
brj-22966	143	12	other	other	ADJ
brj-22966	143	13	optimizers	optimizer	NOUN
brj-22966	143	14	during	during	ADP
brj-22966	143	15	the	the	DET
brj-22966	143	16	test	test	NOUN
brj-22966	143	17	phase	phase	NOUN
brj-22966	143	18	.	.	PUNCT
brj-22966	144	1	sgd	sgd	PROPN
brj-22966	144	2	demonstrated	demonstrate	VERB
brj-22966	144	3	a	a	DET
brj-22966	144	4	classification	classification	NOUN
brj-22966	144	5	accuracy	accuracy	NOUN
brj-22966	144	6	of	of	ADP
brj-22966	144	7	approximately	approximately	ADV
brj-22966	144	8	83	83	NUM
brj-22966	144	9	%	%	NOUN
brj-22966	144	10	,	,	PUNCT
brj-22966	144	11	whereas	whereas	SCONJ
brj-22966	144	12	rmsprop	rmsprop	NOUN
brj-22966	144	13	achieved	achieve	VERB
brj-22966	144	14	a	a	DET
brj-22966	144	15	classification	classification	NOUN
brj-22966	144	16	accuracy	accuracy	NOUN
brj-22966	144	17	ranging	range	VERB
brj-22966	144	18	from	from	ADP
brj-22966	144	19	79	79	NUM
brj-22966	144	20	%	%	NOUN
brj-22966	144	21	to	to	PART
brj-22966	144	22	90	90	NUM
brj-22966	144	23	%	%	NOUN
brj-22966	144	24	.	.	PUNCT
brj-22966	145	1	sgd	sgd	PROPN
brj-22966	145	2	is	be	AUX
brj-22966	145	3	a	a	DET
brj-22966	145	4	function	function	NOUN
brj-22966	145	5	related	relate	VERB
brj-22966	145	6	to	to	ADP
brj-22966	145	7	the	the	DET
brj-22966	145	8	random	random	ADJ
brj-22966	145	9	extraction	extraction	NOUN
brj-22966	145	10	and	and	CCONJ
brj-22966	145	11	calculation	calculation	NOUN
brj-22966	145	12	of	of	ADP
brj-22966	145	13	partial	partial	ADJ
brj-22966	145	14	data	datum	NOUN
brj-22966	145	15	at	at	ADP
brj-22966	145	16	each	each	DET
brj-22966	145	17	learning	learning	NOUN
brj-22966	145	18	stage	stage	NOUN
brj-22966	145	19	and	and	CCONJ
brj-22966	145	20	updating	update	VERB
brj-22966	145	21	them	they	PRON
brj-22966	145	22	more	more	ADV
brj-22966	145	23	quickly	quickly	ADV
brj-22966	145	24	and	and	CCONJ
brj-22966	145	25	frequently	frequently	ADV
brj-22966	145	26	.	.	PUNCT
brj-22966	146	1	rmsprop	rmsprop	NOUN
brj-22966	146	2	is	be	AUX
brj-22966	146	3	a	a	DET
brj-22966	146	4	function	function	NOUN
brj-22966	146	5	of	of	ADP
brj-22966	146	6	applying	apply	VERB
brj-22966	146	7	an	an	DET
brj-22966	146	8	exponential	exponential	NOUN
brj-22966	146	9	moving	move	VERB
brj-22966	146	10	average	average	NOUN
brj-22966	146	11	to	to	PART
brj-22966	146	12	prevent	prevent	VERB
brj-22966	146	13	gradient	gradient	ADJ
brj-22966	146	14	loss	loss	NOUN
brj-22966	146	15	problems	problem	NOUN
brj-22966	146	16	,	,	PUNCT
brj-22966	146	17	which	which	PRON
brj-22966	146	18	can	can	AUX
brj-22966	146	19	be	be	AUX
brj-22966	146	20	obtained	obtain	VERB
brj-22966	146	21	by	by	ADP
brj-22966	146	22	lowering	lower	VERB
brj-22966	146	23	the	the	DET
brj-22966	146	24	reflection	reflection	NOUN
brj-22966	146	25	weight	weight	NOUN
brj-22966	146	26	of	of	ADP
brj-22966	146	27	the	the	DET
brj-22966	146	28	initial	initial	ADJ
brj-22966	146	29	training	training	NOUN
brj-22966	146	30	and	and	CCONJ
brj-22966	146	31	increasing	increase	VERB
brj-22966	146	32	the	the	DET
brj-22966	146	33	reflection	reflection	NOUN
brj-22966	146	34	weight	weight	NOUN
brj-22966	146	35	of	of	ADP
brj-22966	146	36	the	the	DET
brj-22966	146	37	recent	recent	ADJ
brj-22966	146	38	gradient	gradient	NOUN
brj-22966	146	39	,	,	PUNCT
brj-22966	146	40	thereby	thereby	ADV
brj-22966	146	41	preventing	prevent	VERB
brj-22966	146	42	the	the	DET
brj-22966	146	43	vanishing	vanish	VERB
brj-22966	146	44	gradient	gradient	NOUN
brj-22966	146	45	problem	problem	NOUN
brj-22966	146	46	during	during	ADP
brj-22966	146	47	early	early	ADJ
brj-22966	146	48	training	training	NOUN
brj-22966	146	49	(	(	PUNCT
brj-22966	146	50	géron	géron	NOUN
brj-22966	146	51	2020	2020	NUM
brj-22966	146	52	)	)	PUNCT
brj-22966	146	53	.	.	PUNCT
brj-22966	147	1	therefore	therefore	ADV
brj-22966	147	2	,	,	PUNCT
brj-22966	147	3	in	in	ADP
brj-22966	147	4	this	this	DET
brj-22966	147	5	study	study	NOUN
brj-22966	147	6	,	,	PUNCT
brj-22966	147	7	sgd	sgd	PROPN
brj-22966	147	8	demonstrated	demonstrate	VERB
brj-22966	147	9	superior	superior	ADJ
brj-22966	147	10	performance	performance	NOUN
brj-22966	147	11	in	in	ADP
brj-22966	147	12	high	high	ADJ
brj-22966	147	13	-	-	PUNCT
brj-22966	147	14	resolution	resolution	NOUN
brj-22966	147	15	microscopic	microscopic	ADJ
brj-22966	147	16	image	image	NOUN
brj-22966	147	17	analysis	analysis	NOUN
brj-22966	147	18	required	require	VERB
brj-22966	147	19	for	for	ADP
brj-22966	147	20	species	species	NOUN
brj-22966	147	21	classification	classification	NOUN
brj-22966	147	22	using	use	VERB
brj-22966	147	23	bark	bark	NOUN
brj-22966	147	24	,	,	PUNCT
brj-22966	147	25	while	while	SCONJ
brj-22966	147	26	rmsprop	rmsprop	NOUN
brj-22966	147	27	showed	show	VERB
brj-22966	147	28	excellent	excellent	ADJ
brj-22966	147	29	performance	performance	NOUN
brj-22966	147	30	in	in	ADP
brj-22966	147	31	microscopic	microscopic	ADJ
brj-22966	147	32	image	image	NOUN
brj-22966	147	33	analysis	analysis	NOUN
brj-22966	147	34	of	of	ADP
brj-22966	147	35	the	the	DET
brj-22966	147	36	bark	bark	NOUN
brj-22966	147	37	despite	despite	SCONJ
brj-22966	147	38	potential	potential	ADJ
brj-22966	147	39	variations	variation	NOUN
brj-22966	147	40	.	.	PUNCT
brj-22966	148	1	the	the	DET
brj-22966	148	2	classification	classification	NOUN
brj-22966	148	3	accuracy	accuracy	NOUN
brj-22966	148	4	and	and	CCONJ
brj-22966	148	5	loss	loss	NOUN
brj-22966	148	6	of	of	ADP
brj-22966	148	7	bark	bark	NOUN
brj-22966	148	8	for	for	ADP
brj-22966	148	9	the	the	DET
brj-22966	148	10	seven	seven	NUM
brj-22966	148	11	oak	oak	NOUN
brj-22966	148	12	species	specie	NOUN
brj-22966	148	13	using	use	VERB
brj-22966	148	14	a	a	DET
brj-22966	148	15	cnn	cnn	NOUN
brj-22966	148	16	are	be	AUX
brj-22966	148	17	shown	show	VERB
brj-22966	148	18	in	in	ADP
brj-22966	148	19	figs	fig	NOUN
brj-22966	148	20	.	.	PUNCT
brj-22966	149	1	4	4	NUM
brj-22966	149	2	and	and	CCONJ
brj-22966	149	3	5	5	NUM
brj-22966	149	4	.	.	PUNCT
brj-22966	150	1	under	under	ADP
brj-22966	150	2	most	most	ADJ
brj-22966	150	3	training	training	NOUN
brj-22966	150	4	and	and	CCONJ
brj-22966	150	5	test	test	NOUN
brj-22966	150	6	conditions	condition	NOUN
brj-22966	150	7	,	,	PUNCT
brj-22966	150	8	there	there	PRON
brj-22966	150	9	was	be	VERB
brj-22966	150	10	a	a	DET
brj-22966	150	11	notable	notable	ADJ
brj-22966	150	12	increase	increase	NOUN
brj-22966	150	13	in	in	ADP
brj-22966	150	14	accuracy	accuracy	NOUN
brj-22966	150	15	and	and	CCONJ
brj-22966	150	16	a	a	DET
brj-22966	150	17	decrease	decrease	NOUN
brj-22966	150	18	in	in	ADP
brj-22966	150	19	loss	loss	NOUN
brj-22966	150	20	as	as	SCONJ
brj-22966	150	21	the	the	DET
brj-22966	150	22	number	number	NOUN
brj-22966	150	23	of	of	ADP
brj-22966	150	24	epochs	epoch	NOUN
brj-22966	150	25	progressed	progress	VERB
brj-22966	150	26	.	.	PUNCT
brj-22966	151	1	nevertheless	nevertheless	ADV
brj-22966	151	2	,	,	PUNCT
brj-22966	151	3	a	a	DET
brj-22966	151	4	noteworthy	noteworthy	ADJ
brj-22966	151	5	anomaly	anomaly	NOUN
brj-22966	151	6	was	be	AUX
brj-22966	151	7	detected	detect	VERB
brj-22966	151	8	in	in	ADP
brj-22966	151	9	the	the	DET
brj-22966	151	10	training	training	NOUN
brj-22966	151	11	phase	phase	NOUN
brj-22966	151	12	when	when	SCONJ
brj-22966	151	13	the	the	DET
brj-22966	151	14	adam	adam	PROPN
brj-22966	151	15	optimizer	optimizer	NOUN
brj-22966	151	16	was	be	AUX
brj-22966	151	17	employed	employ	VERB
brj-22966	151	18	with	with	ADP
brj-22966	151	19	the	the	DET
brj-22966	151	20	augmented	augment	VERB
brj-22966	151	21	datasets	dataset	NOUN
brj-22966	151	22	.	.	PUNCT
brj-22966	152	1	in	in	ADP
brj-22966	152	2	this	this	DET
brj-22966	152	3	particular	particular	ADJ
brj-22966	152	4	instance	instance	NOUN
brj-22966	152	5	,	,	PUNCT
brj-22966	152	6	the	the	DET
brj-22966	152	7	observed	observe	VERB
brj-22966	152	8	loss	loss	NOUN
brj-22966	152	9	exhibited	exhibit	VERB
brj-22966	152	10	an	an	DET
brj-22966	152	11	increasing	increase	VERB
brj-22966	152	12	pattern	pattern	NOUN
brj-22966	152	13	as	as	SCONJ
brj-22966	152	14	the	the	DET
brj-22966	152	15	number	number	NOUN
brj-22966	152	16	of	of	ADP
brj-22966	152	17	epochs	epoch	NOUN
brj-22966	152	18	increased	increase	VERB
brj-22966	152	19	,	,	PUNCT
brj-22966	152	20	in	in	ADP
brj-22966	152	21	contrast	contrast	NOUN
brj-22966	152	22	to	to	ADP
brj-22966	152	23	the	the	DET
brj-22966	152	24	outcomes	outcome	NOUN
brj-22966	152	25	observed	observe	VERB
brj-22966	152	26	under	under	ADP
brj-22966	152	27	other	other	ADJ
brj-22966	152	28	conditions	condition	NOUN
brj-22966	152	29	.	.	PUNCT
brj-22966	153	1	the	the	DET
brj-22966	153	2	observed	observe	VERB
brj-22966	153	3	pattern	pattern	NOUN
brj-22966	153	4	indicates	indicate	VERB
brj-22966	153	5	overfitting	overfitte	VERB
brj-22966	153	6	,	,	PUNCT
brj-22966	153	7	a	a	DET
brj-22966	153	8	phenomenon	phenomenon	NOUN
brj-22966	153	9	in	in	ADP
brj-22966	153	10	which	which	PRON
brj-22966	153	11	the	the	DET
brj-22966	153	12	model	model	NOUN
brj-22966	153	13	demonstrates	demonstrate	VERB
brj-22966	153	14	high	high	ADJ
brj-22966	153	15	performance	performance	NOUN
brj-22966	153	16	on	on	ADP
brj-22966	153	17	data	datum	NOUN
brj-22966	153	18	that	that	PRON
brj-22966	153	19	closely	closely	ADV
brj-22966	153	20	resemble	resemble	VERB
brj-22966	153	21	the	the	DET
brj-22966	153	22	training	training	NOUN
brj-22966	153	23	set	set	NOUN
brj-22966	153	24	,	,	PUNCT
brj-22966	153	25	but	but	CCONJ
brj-22966	153	26	exhibits	exhibit	VERB
brj-22966	153	27	poor	poor	ADJ
brj-22966	153	28	performance	performance	NOUN
brj-22966	153	29	on	on	ADP
brj-22966	153	30	test	test	NOUN
brj-22966	153	31	or	or	CCONJ
brj-22966	153	32	validation	validation	NOUN
brj-22966	153	33	data	datum	NOUN
brj-22966	153	34	(	(	PUNCT
brj-22966	153	35	oh	oh	NOUN
brj-22966	153	36	2021	2021	NUM
brj-22966	153	37	)	)	PUNCT
brj-22966	153	38	.	.	PUNCT
brj-22966	154	1	this	this	PRON
brj-22966	154	2	was	be	AUX
brj-22966	154	3	because	because	SCONJ
brj-22966	154	4	the	the	DET
brj-22966	154	5	noise	noise	NOUN
brj-22966	154	6	generated	generate	VERB
brj-22966	154	7	during	during	ADP
brj-22966	154	8	the	the	DET
brj-22966	154	9	augmentation	augmentation	NOUN
brj-22966	154	10	process	process	NOUN
brj-22966	154	11	of	of	ADP
brj-22966	154	12	the	the	DET
brj-22966	154	13	dataset	dataset	NOUN
brj-22966	154	14	negatively	negatively	ADV
brj-22966	154	15	affected	affect	VERB
brj-22966	154	16	the	the	DET
brj-22966	154	17	learning	learning	NOUN
brj-22966	154	18	results	result	NOUN
brj-22966	154	19	and	and	CCONJ
brj-22966	154	20	only	only	ADV
brj-22966	154	21	caused	cause	VERB
brj-22966	154	22	overfitting	overfitting	NOUN
brj-22966	154	23	when	when	SCONJ
brj-22966	154	24	the	the	DET
brj-22966	154	25	adam	adam	PROPN
brj-22966	154	26	optimizer	optimizer	NOUN
brj-22966	154	27	with	with	ADP
brj-22966	154	28	an	an	DET
brj-22966	154	29	augmented	augment	VERB
brj-22966	154	30	dataset	dataset	NOUN
brj-22966	154	31	was	be	AUX
brj-22966	154	32	used	use	VERB
brj-22966	154	33	for	for	ADP
brj-22966	154	34	training	training	NOUN
brj-22966	154	35	.	.	PUNCT
brj-22966	155	1	in	in	ADP
brj-22966	155	2	this	this	DET
brj-22966	155	3	study	study	NOUN
brj-22966	155	4	,	,	PUNCT
brj-22966	155	5	all	all	DET
brj-22966	155	6	conditions	condition	NOUN
brj-22966	155	7	except	except	SCONJ
brj-22966	155	8	the	the	DET
brj-22966	155	9	adam	adam	NOUN
brj-22966	155	10	-	-	PUNCT
brj-22966	155	11	augmented	augment	VERB
brj-22966	155	12	dataset	dataset	NOUN
brj-22966	155	13	condition	condition	NOUN
brj-22966	155	14	exhibited	exhibit	VERB
brj-22966	155	15	a	a	DET
brj-22966	155	16	notable	notable	ADJ
brj-22966	155	17	trend	trend	NOUN
brj-22966	155	18	of	of	ADP
brj-22966	155	19	reduced	reduce	VERB
brj-22966	155	20	loss	loss	NOUN
brj-22966	155	21	and	and	CCONJ
brj-22966	155	22	enhanced	enhanced	ADJ
brj-22966	155	23	accuracy	accuracy	NOUN
brj-22966	155	24	as	as	SCONJ
brj-22966	155	25	the	the	DET
brj-22966	155	26	number	number	NOUN
brj-22966	155	27	of	of	ADP
brj-22966	155	28	epochs	epoch	NOUN
brj-22966	155	29	increased	increase	VERB
brj-22966	155	30	,	,	PUNCT
brj-22966	155	31	particularly	particularly	ADV
brj-22966	155	32	when	when	SCONJ
brj-22966	155	33	utilizing	utilize	VERB
brj-22966	155	34	the	the	DET
brj-22966	155	35	augmented	augment	VERB
brj-22966	155	36	dataset	dataset	NOUN
brj-22966	155	37	as	as	ADP
brj-22966	155	38	opposed	oppose	VERB
brj-22966	155	39	to	to	ADP
brj-22966	155	40	the	the	DET
brj-22966	155	41	non	non	ADJ
brj-22966	155	42	-	-	ADJ
brj-22966	155	43	augmented	augment	VERB
brj-22966	155	44	dataset	dataset	NOUN
brj-22966	155	45	.	.	PUNCT
brj-22966	156	1	the	the	DET
brj-22966	156	2	utilization	utilization	NOUN
brj-22966	156	3	of	of	ADP
brj-22966	156	4	the	the	DET
brj-22966	156	5	augmented	augment	VERB
brj-22966	156	6	dataset	dataset	NOUN
brj-22966	156	7	led	lead	VERB
brj-22966	156	8	to	to	ADP
brj-22966	156	9	the	the	DET
brj-22966	156	10	stability	stability	NOUN
brj-22966	156	11	of	of	ADP
brj-22966	156	12	both	both	CCONJ
brj-22966	156	13	the	the	DET
brj-22966	156	14	loss	loss	NOUN
brj-22966	156	15	and	and	CCONJ
brj-22966	156	16	classification	classification	NOUN
brj-22966	156	17	accuracy	accuracy	NOUN
brj-22966	156	18	after	after	ADP
brj-22966	156	19	roughly	roughly	ADV
brj-22966	156	20	15	15	NUM
brj-22966	156	21	to	to	PART
brj-22966	156	22	20	20	NUM
brj-22966	156	23	epochs	epoch	NOUN
brj-22966	156	24	,	,	PUNCT
brj-22966	156	25	whereas	whereas	SCONJ
brj-22966	156	26	the	the	DET
brj-22966	156	27	non	non	ADJ
brj-22966	156	28	-	-	ADJ
brj-22966	156	29	augmented	augment	VERB
brj-22966	156	30	dataset	dataset	NOUN
brj-22966	156	31	needed	need	VERB
brj-22966	156	32	approximately	approximately	ADV
brj-22966	156	33	70	70	NUM
brj-22966	156	34	to	to	PART
brj-22966	156	35	80	80	NUM
brj-22966	156	36	epochs	epoch	NOUN
brj-22966	156	37	for	for	ADP
brj-22966	156	38	stabilization	stabilization	NOUN
brj-22966	156	39	.	.	PUNCT
brj-22966	157	1	peer	peer	NOUN
brj-22966	157	2	-	-	PUNCT
brj-22966	157	3	reviewed	review	VERB
brj-22966	157	4	article	article	NOUN
brj-22966	157	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	157	6	kim	kim	PROPN
brj-22966	157	7	et	et	PROPN
brj-22966	157	8	al	al	PROPN
brj-22966	157	9	.	.	PROPN
brj-22966	158	1	(	(	PUNCT
brj-22966	158	2	2024	2024	NUM
brj-22966	158	3	)	)	PUNCT
brj-22966	158	4	.	.	PUNCT
brj-22966	159	1	“	"	PUNCT
brj-22966	159	2	convolutional	convolutional	ADJ
brj-22966	159	3	neural	neural	ADJ
brj-22966	159	4	network	network	NOUN
brj-22966	159	5	,	,	PUNCT
brj-22966	159	6	”	"	PUNCT
brj-22966	159	7	bioresources	bioresource	NOUN
brj-22966	159	8	19(1	19(1	NUM
brj-22966	159	9	)	)	PUNCT
brj-22966	159	10	,	,	PUNCT
brj-22966	159	11	510	510	NUM
brj-22966	159	12	-	-	SYM
brj-22966	159	13	524	524	NUM
brj-22966	159	14	.	.	NOUN
brj-22966	159	15	518	518	NUM
brj-22966	159	16	fig	fig	NOUN
brj-22966	159	17	.	.	PUNCT
brj-22966	160	1	4	4	X
brj-22966	160	2	.	.	X
brj-22966	160	3	verification	verification	NOUN
brj-22966	160	4	results	result	NOUN
brj-22966	160	5	of	of	ADP
brj-22966	160	6	convolutional	convolutional	ADJ
brj-22966	160	7	neural	neural	ADJ
brj-22966	160	8	networks	network	NOUN
brj-22966	160	9	(	(	PUNCT
brj-22966	160	10	cnns	cnns	NOUN
brj-22966	160	11	)	)	PUNCT
brj-22966	160	12	architecture	architecture	NOUN
brj-22966	160	13	for	for	ADP
brj-22966	160	14	the	the	DET
brj-22966	160	15	seven	seven	NUM
brj-22966	160	16	oak	oak	NOUN
brj-22966	160	17	species	species	NOUN
brj-22966	160	18	classification	classification	NOUN
brj-22966	160	19	using	use	VERB
brj-22966	160	20	the	the	DET
brj-22966	160	21	barks	bark	NOUN
brj-22966	160	22	in	in	ADP
brj-22966	160	23	training	training	NOUN
brj-22966	160	24	phase	phase	NOUN
brj-22966	160	25	peer	peer	NOUN
brj-22966	160	26	-	-	PUNCT
brj-22966	160	27	reviewed	review	VERB
brj-22966	160	28	article	article	NOUN
brj-22966	160	29	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	160	30	kim	kim	PROPN
brj-22966	160	31	et	et	PROPN
brj-22966	160	32	al	al	PROPN
brj-22966	160	33	.	.	PROPN
brj-22966	161	1	(	(	PUNCT
brj-22966	161	2	2024	2024	NUM
brj-22966	161	3	)	)	PUNCT
brj-22966	161	4	.	.	PUNCT
brj-22966	162	1	“	"	PUNCT
brj-22966	162	2	convolutional	convolutional	ADJ
brj-22966	162	3	neural	neural	ADJ
brj-22966	162	4	network	network	NOUN
brj-22966	162	5	,	,	PUNCT
brj-22966	162	6	”	"	PUNCT
brj-22966	162	7	bioresources	bioresource	NOUN
brj-22966	162	8	19(1	19(1	NUM
brj-22966	162	9	)	)	PUNCT
brj-22966	162	10	,	,	PUNCT
brj-22966	162	11	510	510	NUM
brj-22966	162	12	-	-	SYM
brj-22966	162	13	524	524	NUM
brj-22966	162	14	.	.	PUNCT
brj-22966	163	1	519	519	NUM
brj-22966	163	2	fig	fig	NOUN
brj-22966	163	3	.	.	PUNCT
brj-22966	164	1	5	5	X
brj-22966	164	2	.	.	X
brj-22966	164	3	verification	verification	NOUN
brj-22966	164	4	results	result	NOUN
brj-22966	164	5	of	of	ADP
brj-22966	164	6	convolutional	convolutional	ADJ
brj-22966	164	7	neural	neural	ADJ
brj-22966	164	8	networks	network	NOUN
brj-22966	164	9	(	(	PUNCT
brj-22966	164	10	cnns	cnns	NOUN
brj-22966	164	11	)	)	PUNCT
brj-22966	164	12	architecture	architecture	NOUN
brj-22966	164	13	for	for	ADP
brj-22966	164	14	the	the	DET
brj-22966	164	15	seven	seven	NUM
brj-22966	164	16	oak	oak	NOUN
brj-22966	164	17	species	species	NOUN
brj-22966	164	18	classification	classification	NOUN
brj-22966	164	19	using	use	VERB
brj-22966	164	20	the	the	DET
brj-22966	164	21	barks	bark	NOUN
brj-22966	164	22	in	in	ADP
brj-22966	164	23	test	test	NOUN
brj-22966	164	24	phase	phase	NOUN
brj-22966	164	25	peer	peer	NOUN
brj-22966	164	26	-	-	PUNCT
brj-22966	164	27	reviewed	review	VERB
brj-22966	164	28	article	article	NOUN
brj-22966	164	29	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	164	30	kim	kim	PROPN
brj-22966	164	31	et	et	PROPN
brj-22966	164	32	al	al	PROPN
brj-22966	164	33	.	.	PROPN
brj-22966	165	1	(	(	PUNCT
brj-22966	165	2	2024	2024	NUM
brj-22966	165	3	)	)	PUNCT
brj-22966	165	4	.	.	PUNCT
brj-22966	166	1	“	"	PUNCT
brj-22966	166	2	convolutional	convolutional	ADJ
brj-22966	166	3	neural	neural	ADJ
brj-22966	166	4	network	network	NOUN
brj-22966	166	5	,	,	PUNCT
brj-22966	166	6	”	"	PUNCT
brj-22966	166	7	bioresources	bioresource	NOUN
brj-22966	166	8	19(1	19(1	NUM
brj-22966	166	9	)	)	PUNCT
brj-22966	166	10	,	,	PUNCT
brj-22966	166	11	510	510	NUM
brj-22966	166	12	-	-	SYM
brj-22966	166	13	524	524	NUM
brj-22966	166	14	.	.	PUNCT
brj-22966	167	1	520	520	NUM
brj-22966	167	2	table	table	NOUN
brj-22966	167	3	5	5	NUM
brj-22966	167	4	.	.	PUNCT
brj-22966	167	5	correlation	correlation	NOUN
brj-22966	167	6	of	of	ADP
brj-22966	167	7	the	the	DET
brj-22966	167	8	factors	factor	NOUN
brj-22966	167	9	influencing	influence	VERB
brj-22966	167	10	convolutional	convolutional	ADJ
brj-22966	167	11	neural	neural	ADJ
brj-22966	167	12	networks	network	NOUN
brj-22966	167	13	n	n	NOUN
brj-22966	167	14	=	=	SYM
brj-22966	167	15	600	600	NUM
brj-22966	167	16	epochs	epoch	NOUN
brj-22966	167	17	loss	loss	NOUN
brj-22966	167	18	(	(	PUNCT
brj-22966	167	19	train	train	NOUN
brj-22966	167	20	)	)	PUNCT
brj-22966	167	21	accuracy	accuracy	NOUN
brj-22966	167	22	(	(	PUNCT
brj-22966	167	23	train	train	NOUN
brj-22966	167	24	)	)	PUNCT
brj-22966	167	25	loss	loss	NOUN
brj-22966	167	26	(	(	PUNCT
brj-22966	167	27	test	test	NOUN
brj-22966	167	28	)	)	PUNCT
brj-22966	167	29	accuracy	accuracy	NOUN
brj-22966	167	30	(	(	PUNCT
brj-22966	167	31	test	test	NOUN
brj-22966	167	32	)	)	PUNCT
brj-22966	167	33	optimizer	optimizer	NOUN
brj-22966	167	34	augmentation	augmentation	NOUN
brj-22966	167	35	(	(	PUNCT
brj-22966	167	36	sgd	sgd	NOUN
brj-22966	167	37	)	)	PUNCT
brj-22966	167	38	(	(	PUNCT
brj-22966	167	39	adam	adam	PROPN
brj-22966	167	40	)	)	PUNCT
brj-22966	167	41	(	(	PUNCT
brj-22966	167	42	rms	rm	NOUN
brj-22966	167	43	prop	prop	NOUN
brj-22966	167	44	)	)	PUNCT
brj-22966	167	45	(	(	PUNCT
brj-22966	167	46	no	no	INTJ
brj-22966	167	47	)	)	PUNCT
brj-22966	167	48	(	(	PUNCT
brj-22966	167	49	yes	yes	INTJ
brj-22966	167	50	)	)	PUNCT
brj-22966	167	51	epochs	epoch	VERB
brj-22966	167	52	1	1	NUM
brj-22966	167	53	−0.525	−0.525	NOUN
brj-22966	167	54	*	*	PUNCT
brj-22966	167	55	*	*	PUNCT
brj-22966	167	56	0.530	0.530	NUM
brj-22966	167	57	*	*	PUNCT
brj-22966	167	58	*	*	PUNCT
brj-22966	167	59	−0.031	−0.031	NOUN
brj-22966	167	60	0.493	0.493	NUM
brj-22966	167	61	*	*	PUNCT
brj-22966	167	62	*	*	PUNCT
brj-22966	168	1	0.000	0.000	NUM
brj-22966	168	2	0.000	0.000	NUM
brj-22966	168	3	0.000	0.000	NUM
brj-22966	168	4	0.000	0.000	NUM
brj-22966	168	5	0.000	0.000	NUM
brj-22966	168	6	p	p	NOUN
brj-22966	168	7	=	=	PUNCT
brj-22966	168	8	0.000	0.000	NUM
brj-22966	168	9	p	p	NOUN
brj-22966	168	10	=	=	NOUN
brj-22966	168	11	0.000	0.000	NUM
brj-22966	168	12	p	p	NOUN
brj-22966	168	13	=	=	PUNCT
brj-22966	168	14	0.443	0.443	NUM
brj-22966	168	15	p	p	NOUN
brj-22966	168	16	=	=	PUNCT
brj-22966	168	17	0.000	0.000	NUM
brj-22966	168	18	p	p	NOUN
brj-22966	168	19	=	=	NOUN
brj-22966	168	20	1.000	1.000	NUM
brj-22966	168	21	p	p	NOUN
brj-22966	168	22	=	=	NOUN
brj-22966	168	23	1.000	1.000	NUM
brj-22966	168	24	p	p	NOUN
brj-22966	168	25	=	=	NOUN
brj-22966	168	26	1.000	1.000	NUM
brj-22966	168	27	p	p	NOUN
brj-22966	168	28	=	=	NOUN
brj-22966	168	29	1.000	1.000	NUM
brj-22966	168	30	p	p	NOUN
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brj-22966	186	13	p	p	NOUN
brj-22966	186	14	=	=	PUNCT
brj-22966	186	15	0.000	0.000	NUM
brj-22966	186	16	p	p	NOUN
brj-22966	186	17	=	=	NOUN
brj-22966	186	18	1.000	1.000	NUM
brj-22966	186	19	p	p	NOUN
brj-22966	186	20	=	=	NOUN
brj-22966	186	21	1.000	1.000	NUM
brj-22966	186	22	p	p	NOUN
brj-22966	186	23	=	=	NOUN
brj-22966	186	24	1.000	1.000	NUM
brj-22966	186	25	p	p	NOUN
brj-22966	186	26	=	=	NOUN
brj-22966	186	27	0.000	0.000	NUM
brj-22966	186	28	augmentation	augmentation	NOUN
brj-22966	186	29	(	(	PUNCT
brj-22966	186	30	yes	yes	INTJ
brj-22966	186	31	)	)	PUNCT
brj-22966	186	32	0.000	0.000	NUM
brj-22966	186	33	−0.624	−0.624	NOUN
brj-22966	186	34	*	*	PUNCT
brj-22966	186	35	*	*	PUNCT
brj-22966	186	36	0.614	0.614	NUM
brj-22966	186	37	*	*	X
brj-22966	186	38	*	*	PUNCT
brj-22966	186	39	0.189	0.189	NUM
brj-22966	186	40	*	*	PUNCT
brj-22966	186	41	*	*	X
brj-22966	186	42	0.456	0.456	NUM
brj-22966	186	43	*	*	PUNCT
brj-22966	186	44	*	*	PUNCT
brj-22966	186	45	0.000	0.000	NUM
brj-22966	186	46	0.000	0.000	NUM
brj-22966	186	47	0.000	0.000	NUM
brj-22966	186	48	−1.000	−1.000	NUM
brj-22966	186	49	*	*	PUNCT
brj-22966	186	50	*	*	PROPN
brj-22966	186	51	1	1	NUM
brj-22966	186	52	p	p	NOUN
brj-22966	186	53	=	=	SYM
brj-22966	186	54	1.000	1.000	NUM
brj-22966	186	55	p	p	NOUN
brj-22966	186	56	=	=	NOUN
brj-22966	186	57	0.000	0.000	NUM
brj-22966	186	58	p	p	NOUN
brj-22966	186	59	=	=	NOUN
brj-22966	186	60	0.000	0.000	NUM
brj-22966	186	61	p	p	NOUN
brj-22966	186	62	=	=	NOUN
brj-22966	186	63	0.000	0.000	NUM
brj-22966	186	64	p	p	NOUN
brj-22966	186	65	=	=	PUNCT
brj-22966	186	66	0.000	0.000	NUM
brj-22966	186	67	p	p	NOUN
brj-22966	186	68	=	=	NOUN
brj-22966	186	69	1.000	1.000	NUM
brj-22966	186	70	p	p	NOUN
brj-22966	186	71	=	=	NOUN
brj-22966	186	72	1.000	1.000	NUM
brj-22966	186	73	p	p	NOUN
brj-22966	186	74	=	=	NOUN
brj-22966	186	75	1.000	1.000	NUM
brj-22966	186	76	p	p	NOUN
brj-22966	186	77	=	=	NOUN
brj-22966	186	78	0.000	0.000	NUM
brj-22966	186	79	*	*	PUNCT
brj-22966	186	80	*	*	PUNCT
brj-22966	186	81	the	the	DET
brj-22966	186	82	correlation	correlation	NOUN
brj-22966	186	83	is	be	AUX
brj-22966	186	84	significant	significant	ADJ
brj-22966	186	85	at	at	ADP
brj-22966	186	86	the	the	DET
brj-22966	186	87	0.01	0.01	NUM
brj-22966	186	88	level	level	NOUN
brj-22966	186	89	(	(	PUNCT
brj-22966	186	90	2	2	NUM
brj-22966	186	91	-	-	PUNCT
brj-22966	186	92	tailed	tailed	ADJ
brj-22966	186	93	)	)	PUNCT
brj-22966	186	94	.	.	PUNCT
brj-22966	187	1	table	table	NOUN
brj-22966	187	2	6	6	NUM
brj-22966	187	3	.	.	PUNCT
brj-22966	188	1	homogeneous	homogeneous	ADJ
brj-22966	188	2	subset	subset	ADJ
brj-22966	188	3	output	output	NOUN
brj-22966	188	4	of	of	ADP
brj-22966	188	5	the	the	DET
brj-22966	188	6	basic	basic	ADJ
brj-22966	188	7	cnn	cnn	PROPN
brj-22966	188	8	model	model	NOUN
brj-22966	188	9	process	process	NOUN
brj-22966	188	10	output	output	NOUN
brj-22966	188	11	sgd	sgd	PROPN
brj-22966	188	12	adam	adam	PROPN
brj-22966	188	13	rmsprop	rmsprop	PROPN
brj-22966	188	14	non	non	PROPN
brj-22966	188	15	-	-	PROPN
brj-22966	188	16	aug	aug	PROPN
brj-22966	188	17	.	.	PROPN
brj-22966	189	1	augmented	augment	VERB
brj-22966	189	2	non	non	PROPN
brj-22966	189	3	-	-	PROPN
brj-22966	189	4	aug	aug	PROPN
brj-22966	189	5	.	.	PROPN
brj-22966	189	6	augmented	augment	VERB
brj-22966	189	7	non	non	PROPN
brj-22966	189	8	-	-	PROPN
brj-22966	189	9	aug	aug	PROPN
brj-22966	189	10	.	.	PROPN
brj-22966	190	1	augmented	augment	VERB
brj-22966	190	2	training	training	NOUN
brj-22966	190	3	loss	loss	NOUN
brj-22966	190	4	1.106d	1.106d	NUM
brj-22966	190	5	0.142a	0.142a	NOUN
brj-22966	190	6	0.519b	0.519b	NOUN
brj-22966	190	7	0.059a	0.059a	VERB
brj-22966	190	8	0.772c	0.772c	ADJ
brj-22966	190	9	0.115a	0.115a	NOUN
brj-22966	190	10	accuracy	accuracy	NOUN
brj-22966	190	11	0.559a	0.559a	ADJ
brj-22966	190	12	0.946d	0.946d	NOUN
brj-22966	190	13	0.790c	0.790c	NOUN
brj-22966	190	14	0.979d	0.979d	ADJ
brj-22966	190	15	0.691b	0.691b	NOUN
brj-22966	190	16	0.961d	0.961d	ADJ
brj-22966	190	17	test	test	NOUN
brj-22966	190	18	loss	loss	NOUN
brj-22966	190	19	1.099c	1.099c	NUM
brj-22966	190	20	0.708a	0.708a	NOUN
brj-22966	191	1	0.908b	0.908b	SYM
brj-22966	191	2	2.128d	2.128d	NUM
brj-22966	191	3	0.807ab	0.807ab	ADJ
brj-22966	191	4	0.807ab	0.807ab	ADJ
brj-22966	191	5	accuracy	accuracy	NOUN
brj-22966	191	6	0.583a	0.583a	NOUN
brj-22966	192	1	0.818d	0.818d	NOUN
brj-22966	192	2	0.678b	0.678b	NUM
brj-22966	192	3	0.744c	0.744c	ADJ
brj-22966	192	4	0.687b	0.687b	PROPN
brj-22966	192	5	0.871e	0.871e	PROPN
brj-22966	192	6	note	note	VERB
brj-22966	192	7	:	:	PUNCT
brj-22966	192	8	the	the	DET
brj-22966	192	9	same	same	ADJ
brj-22966	192	10	superscript	superscript	ADJ
brj-22966	192	11	lowercase	lowercase	NOUN
brj-22966	192	12	letters	letter	NOUN
brj-22966	192	13	beside	beside	ADP
brj-22966	192	14	the	the	DET
brj-22966	192	15	mean	mean	ADJ
brj-22966	192	16	values	value	NOUN
brj-22966	192	17	in	in	ADP
brj-22966	192	18	the	the	DET
brj-22966	192	19	same	same	ADJ
brj-22966	192	20	row	row	NOUN
brj-22966	192	21	denote	denote	NOUN
brj-22966	192	22	non	non	ADJ
brj-22966	192	23	-	-	ADJ
brj-22966	192	24	significant	significant	ADJ
brj-22966	192	25	outcomes	outcome	NOUN
brj-22966	192	26	at	at	ADP
brj-22966	192	27	the	the	DET
brj-22966	192	28	5	5	NUM
brj-22966	192	29	%	%	NOUN
brj-22966	192	30	significance	significance	NOUN
brj-22966	192	31	level	level	NOUN
brj-22966	192	32	for	for	ADP
brj-22966	192	33	comparisons	comparison	NOUN
brj-22966	192	34	between	between	ADP
brj-22966	192	35	species	specie	NOUN
brj-22966	192	36	.	.	PUNCT
brj-22966	193	1	peer	peer	NOUN
brj-22966	193	2	-	-	PUNCT
brj-22966	193	3	reviewed	review	VERB
brj-22966	193	4	article	article	NOUN
brj-22966	193	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	193	6	kim	kim	PROPN
brj-22966	193	7	et	et	PROPN
brj-22966	193	8	al	al	PROPN
brj-22966	193	9	.	.	PROPN
brj-22966	194	1	(	(	PUNCT
brj-22966	194	2	2024	2024	NUM
brj-22966	194	3	)	)	PUNCT
brj-22966	194	4	.	.	PUNCT
brj-22966	195	1	“	"	PUNCT
brj-22966	195	2	convolutional	convolutional	ADJ
brj-22966	195	3	neural	neural	ADJ
brj-22966	195	4	network	network	NOUN
brj-22966	195	5	,	,	PUNCT
brj-22966	195	6	”	"	PUNCT
brj-22966	195	7	bioresources	bioresource	NOUN
brj-22966	195	8	19(1	19(1	NUM
brj-22966	195	9	)	)	PUNCT
brj-22966	195	10	,	,	PUNCT
brj-22966	195	11	510	510	NUM
brj-22966	195	12	-	-	SYM
brj-22966	195	13	524	524	NUM
brj-22966	195	14	.	.	NOUN
brj-22966	195	15	521	521	NUM
brj-22966	195	16	during	during	ADP
brj-22966	195	17	the	the	DET
brj-22966	195	18	test	test	NOUN
brj-22966	195	19	phase	phase	NOUN
brj-22966	195	20	,	,	PUNCT
brj-22966	195	21	when	when	SCONJ
brj-22966	195	22	the	the	DET
brj-22966	195	23	augmented	augment	VERB
brj-22966	195	24	dataset	dataset	NOUN
brj-22966	195	25	was	be	AUX
brj-22966	195	26	applied	apply	VERB
brj-22966	195	27	during	during	ADP
brj-22966	195	28	the	the	DET
brj-22966	195	29	training	training	NOUN
brj-22966	195	30	process	process	NOUN
brj-22966	195	31	,	,	PUNCT
brj-22966	195	32	the	the	DET
brj-22966	195	33	sgd	sgd	NOUN
brj-22966	195	34	and	and	CCONJ
brj-22966	195	35	rmsprop	rmsprop	NOUN
brj-22966	195	36	optimizer	optimizer	NOUN
brj-22966	195	37	conditions	condition	NOUN
brj-22966	195	38	reached	reach	VERB
brj-22966	195	39	a	a	DET
brj-22966	195	40	stable	stable	ADJ
brj-22966	195	41	state	state	NOUN
brj-22966	195	42	after	after	ADP
brj-22966	195	43	15	15	NUM
brj-22966	195	44	to	to	PART
brj-22966	195	45	20	20	NUM
brj-22966	195	46	epochs	epoch	NOUN
brj-22966	195	47	without	without	ADP
brj-22966	195	48	overfitting	overfitte	VERB
brj-22966	195	49	.	.	PUNCT
brj-22966	196	1	in	in	ADP
brj-22966	196	2	contrast	contrast	NOUN
brj-22966	196	3	,	,	PUNCT
brj-22966	196	4	the	the	DET
brj-22966	196	5	non	non	ADJ
brj-22966	196	6	-	-	ADJ
brj-22966	196	7	augmented	augmented	ADJ
brj-22966	196	8	dataset	dataset	NOUN
brj-22966	196	9	took	take	VERB
brj-22966	196	10	approximately	approximately	ADV
brj-22966	196	11	40	40	NUM
brj-22966	196	12	to	to	PART
brj-22966	196	13	50	50	NUM
brj-22966	196	14	epochs	epoch	NOUN
brj-22966	196	15	for	for	SCONJ
brj-22966	196	16	the	the	DET
brj-22966	196	17	optimizer	optimizer	NOUN
brj-22966	196	18	conditions	condition	NOUN
brj-22966	196	19	to	to	PART
brj-22966	196	20	reach	reach	VERB
brj-22966	196	21	a	a	DET
brj-22966	196	22	stable	stable	ADJ
brj-22966	196	23	state	state	NOUN
brj-22966	196	24	.	.	PUNCT
brj-22966	197	1	the	the	DET
brj-22966	197	2	results	result	NOUN
brj-22966	197	3	obtained	obtain	VERB
brj-22966	197	4	in	in	ADP
brj-22966	197	5	this	this	DET
brj-22966	197	6	study	study	NOUN
brj-22966	197	7	are	be	AUX
brj-22966	197	8	in	in	ADP
brj-22966	197	9	line	line	NOUN
brj-22966	197	10	with	with	ADP
brj-22966	197	11	previous	previous	ADJ
brj-22966	197	12	results	result	NOUN
brj-22966	197	13	from	from	ADP
brj-22966	197	14	the	the	DET
brj-22966	197	15	authors	author	NOUN
brj-22966	197	16	(	(	PUNCT
brj-22966	197	17	kim	kim	PROPN
brj-22966	197	18	et	et	PROPN
brj-22966	197	19	al	al	PROPN
brj-22966	197	20	.	.	PROPN
brj-22966	197	21	2023	2023	NUM
brj-22966	197	22	)	)	PUNCT
brj-22966	197	23	,	,	PUNCT
brj-22966	197	24	which	which	PRON
brj-22966	197	25	demonstrated	demonstrate	VERB
brj-22966	197	26	that	that	SCONJ
brj-22966	197	27	the	the	DET
brj-22966	197	28	utilization	utilization	NOUN
brj-22966	197	29	of	of	ADP
brj-22966	197	30	an	an	DET
brj-22966	197	31	augmented	augment	VERB
brj-22966	197	32	dataset	dataset	NOUN
brj-22966	197	33	resulted	result	VERB
brj-22966	197	34	in	in	ADP
brj-22966	197	35	a	a	DET
brj-22966	197	36	more	more	ADV
brj-22966	197	37	rapid	rapid	ADJ
brj-22966	197	38	stabilization	stabilization	NOUN
brj-22966	197	39	of	of	ADP
brj-22966	197	40	loss	loss	NOUN
brj-22966	197	41	and	and	CCONJ
brj-22966	197	42	classification	classification	NOUN
brj-22966	197	43	accuracy	accuracy	NOUN
brj-22966	197	44	compared	compare	VERB
brj-22966	197	45	to	to	ADP
brj-22966	197	46	the	the	DET
brj-22966	197	47	non−augmented	non−augmented	PROPN
brj-22966	197	48	dataset	dataset	PROPN
brj-22966	197	49	.	.	PUNCT
brj-22966	198	1	rapid	rapid	ADJ
brj-22966	198	2	stabilization	stabilization	NOUN
brj-22966	198	3	can	can	AUX
brj-22966	198	4	also	also	ADV
brj-22966	198	5	be	be	AUX
brj-22966	198	6	ascribed	ascribe	VERB
brj-22966	198	7	to	to	ADP
brj-22966	198	8	the	the	DET
brj-22966	198	9	advantages	advantage	NOUN
brj-22966	198	10	of	of	ADP
brj-22966	198	11	using	use	VERB
brj-22966	198	12	data	datum	NOUN
brj-22966	198	13	augmentation	augmentation	NOUN
brj-22966	198	14	,	,	PUNCT
brj-22966	198	15	which	which	PRON
brj-22966	198	16	includes	include	VERB
brj-22966	198	17	mitigating	mitigate	VERB
brj-22966	198	18	the	the	DET
brj-22966	198	19	occurrence	occurrence	NOUN
brj-22966	198	20	of	of	ADP
brj-22966	198	21	overfitting	overfitte	VERB
brj-22966	198	22	and	and	CCONJ
brj-22966	198	23	enhancing	enhance	VERB
brj-22966	198	24	the	the	DET
brj-22966	198	25	classification	classification	NOUN
brj-22966	198	26	accuracy	accuracy	NOUN
brj-22966	198	27	(	(	PUNCT
brj-22966	198	28	wong	wong	PROPN
brj-22966	198	29	et	et	PROPN
brj-22966	198	30	al	al	PROPN
brj-22966	198	31	.	.	PROPN
brj-22966	198	32	2016	2016	NUM
brj-22966	198	33	;	;	PUNCT
brj-22966	198	34	fujita	fujita	PROPN
brj-22966	198	35	and	and	CCONJ
brj-22966	198	36	takahara	takahara	PROPN
brj-22966	198	37	2017	2017	NUM
brj-22966	198	38	;	;	PUNCT
brj-22966	198	39	shorten	shorten	VERB
brj-22966	198	40	and	and	CCONJ
brj-22966	198	41	khoshgoftaar	khoshgoftaar	NOUN
brj-22966	198	42	2019	2019	NUM
brj-22966	198	43	)	)	PUNCT
brj-22966	198	44	.	.	PUNCT
brj-22966	199	1	however	however	ADV
brj-22966	199	2	,	,	PUNCT
brj-22966	199	3	it	it	PRON
brj-22966	199	4	should	should	AUX
brj-22966	199	5	be	be	AUX
brj-22966	199	6	noted	note	VERB
brj-22966	199	7	that	that	SCONJ
brj-22966	199	8	there	there	PRON
brj-22966	199	9	are	be	VERB
brj-22966	199	10	possibilities	possibility	NOUN
brj-22966	199	11	of	of	ADP
brj-22966	199	12	noise	noise	NOUN
brj-22966	199	13	influences	influence	NOUN
brj-22966	199	14	,	,	PUNCT
brj-22966	199	15	as	as	SCONJ
brj-22966	199	16	observed	observe	VERB
brj-22966	199	17	in	in	ADP
brj-22966	199	18	the	the	DET
brj-22966	199	19	adam	adam	PROPN
brj-22966	199	20	optimizer	optimizer	NOUN
brj-22966	199	21	.	.	PUNCT
brj-22966	200	1	table	table	NOUN
brj-22966	200	2	5	5	NUM
brj-22966	200	3	presents	present	VERB
brj-22966	200	4	the	the	DET
brj-22966	200	5	correlation	correlation	NOUN
brj-22966	200	6	between	between	ADP
brj-22966	200	7	the	the	DET
brj-22966	200	8	conditions	condition	NOUN
brj-22966	200	9	applied	apply	VERB
brj-22966	200	10	to	to	ADP
brj-22966	200	11	the	the	DET
brj-22966	200	12	training	training	NOUN
brj-22966	200	13	and	and	CCONJ
brj-22966	200	14	testing	testing	NOUN
brj-22966	200	15	of	of	ADP
brj-22966	200	16	the	the	DET
brj-22966	200	17	cnn	cnn	PROPN
brj-22966	200	18	.	.	PUNCT
brj-22966	201	1	in	in	ADP
brj-22966	201	2	the	the	DET
brj-22966	201	3	training	training	NOUN
brj-22966	201	4	phase	phase	NOUN
brj-22966	201	5	,	,	PUNCT
brj-22966	201	6	the	the	DET
brj-22966	201	7	loss	loss	NOUN
brj-22966	201	8	decreased	decrease	VERB
brj-22966	201	9	as	as	SCONJ
brj-22966	201	10	the	the	DET
brj-22966	201	11	number	number	NOUN
brj-22966	201	12	of	of	ADP
brj-22966	201	13	epochs	epoch	NOUN
brj-22966	201	14	increased	increase	VERB
brj-22966	201	15	;	;	PUNCT
brj-22966	201	16	however	however	ADV
brj-22966	201	17	,	,	PUNCT
brj-22966	201	18	no	no	DET
brj-22966	201	19	clear	clear	ADJ
brj-22966	201	20	relationship	relationship	NOUN
brj-22966	201	21	was	be	AUX
brj-22966	201	22	observed	observe	VERB
brj-22966	201	23	during	during	ADP
brj-22966	201	24	the	the	DET
brj-22966	201	25	test	test	NOUN
brj-22966	201	26	phase	phase	NOUN
brj-22966	201	27	.	.	PUNCT
brj-22966	202	1	however	however	ADV
brj-22966	202	2	,	,	PUNCT
brj-22966	202	3	in	in	ADP
brj-22966	202	4	both	both	CCONJ
brj-22966	202	5	the	the	DET
brj-22966	202	6	training	training	NOUN
brj-22966	202	7	and	and	CCONJ
brj-22966	202	8	test	test	NOUN
brj-22966	202	9	phases	phase	NOUN
brj-22966	202	10	,	,	PUNCT
brj-22966	202	11	the	the	DET
brj-22966	202	12	accuracy	accuracy	NOUN
brj-22966	202	13	showed	show	VERB
brj-22966	202	14	a	a	DET
brj-22966	202	15	proportional	proportional	ADJ
brj-22966	202	16	increase	increase	NOUN
brj-22966	202	17	with	with	ADP
brj-22966	202	18	the	the	DET
brj-22966	202	19	increasing	increase	VERB
brj-22966	202	20	number	number	NOUN
brj-22966	202	21	of	of	ADP
brj-22966	202	22	epochs	epoch	NOUN
brj-22966	202	23	.	.	PUNCT
brj-22966	203	1	notably	notably	ADV
brj-22966	203	2	,	,	PUNCT
brj-22966	203	3	in	in	ADP
brj-22966	203	4	both	both	CCONJ
brj-22966	203	5	the	the	DET
brj-22966	203	6	training	training	NOUN
brj-22966	203	7	and	and	CCONJ
brj-22966	203	8	test	test	NOUN
brj-22966	203	9	phases	phase	NOUN
brj-22966	203	10	,	,	PUNCT
brj-22966	203	11	the	the	DET
brj-22966	203	12	accuracy	accuracy	NOUN
brj-22966	203	13	displayed	display	VERB
brj-22966	203	14	a	a	DET
brj-22966	203	15	negative	negative	ADJ
brj-22966	203	16	trend	trend	NOUN
brj-22966	203	17	with	with	ADP
brj-22966	203	18	the	the	DET
brj-22966	203	19	epochs	epoch	NOUN
brj-22966	203	20	when	when	SCONJ
brj-22966	203	21	sgd	sgd	PROPN
brj-22966	203	22	was	be	AUX
brj-22966	203	23	used	use	VERB
brj-22966	203	24	.	.	PUNCT
brj-22966	204	1	however	however	ADV
brj-22966	204	2	,	,	PUNCT
brj-22966	204	3	the	the	DET
brj-22966	204	4	accuracy	accuracy	NOUN
brj-22966	204	5	increased	increase	VERB
brj-22966	204	6	with	with	ADP
brj-22966	204	7	the	the	DET
brj-22966	204	8	application	application	NOUN
brj-22966	204	9	of	of	ADP
brj-22966	204	10	rmsprop	rmsprop	NOUN
brj-22966	204	11	and	and	CCONJ
brj-22966	204	12	adam	adam	NOUN
brj-22966	204	13	during	during	ADP
brj-22966	204	14	the	the	DET
brj-22966	204	15	training	training	NOUN
brj-22966	204	16	and	and	CCONJ
brj-22966	204	17	test	test	NOUN
brj-22966	204	18	phases	phase	NOUN
brj-22966	204	19	.	.	PUNCT
brj-22966	205	1	during	during	ADP
brj-22966	205	2	the	the	DET
brj-22966	205	3	test	test	NOUN
brj-22966	205	4	phase	phase	NOUN
brj-22966	205	5	,	,	PUNCT
brj-22966	205	6	data	datum	NOUN
brj-22966	205	7	augmentation	augmentation	NOUN
brj-22966	205	8	improved	improve	VERB
brj-22966	205	9	the	the	DET
brj-22966	205	10	performance	performance	NOUN
brj-22966	205	11	in	in	ADP
brj-22966	205	12	terms	term	NOUN
brj-22966	205	13	of	of	ADP
brj-22966	205	14	both	both	DET
brj-22966	205	15	loss	loss	NOUN
brj-22966	205	16	and	and	CCONJ
brj-22966	205	17	accuracy	accuracy	NOUN
brj-22966	205	18	.	.	PUNCT
brj-22966	206	1	in	in	ADP
brj-22966	206	2	contrast	contrast	NOUN
brj-22966	206	3	,	,	PUNCT
brj-22966	206	4	it	it	PRON
brj-22966	206	5	tended	tend	VERB
brj-22966	206	6	to	to	PART
brj-22966	206	7	increase	increase	VERB
brj-22966	206	8	both	both	DET
brj-22966	206	9	loss	loss	NOUN
brj-22966	206	10	and	and	CCONJ
brj-22966	206	11	the	the	DET
brj-22966	206	12	accuracy	accuracy	NOUN
brj-22966	206	13	,	,	PUNCT
brj-22966	206	14	during	during	ADP
brj-22966	206	15	the	the	DET
brj-22966	206	16	training	training	NOUN
brj-22966	206	17	phase	phase	NOUN
brj-22966	206	18	.	.	PUNCT
brj-22966	207	1	accordingly	accordingly	ADV
brj-22966	207	2	,	,	PUNCT
brj-22966	207	3	the	the	DET
brj-22966	207	4	results	result	NOUN
brj-22966	207	5	showed	show	VERB
brj-22966	207	6	that	that	SCONJ
brj-22966	207	7	the	the	DET
brj-22966	207	8	number	number	NOUN
brj-22966	207	9	of	of	ADP
brj-22966	207	10	epochs	epoch	NOUN
brj-22966	207	11	and	and	CCONJ
brj-22966	207	12	optimizer	optimizer	NOUN
brj-22966	207	13	selection	selection	NOUN
brj-22966	207	14	affected	affect	VERB
brj-22966	207	15	the	the	DET
brj-22966	207	16	classification	classification	NOUN
brj-22966	207	17	accuracy	accuracy	NOUN
brj-22966	207	18	.	.	PUNCT
brj-22966	208	1	table	table	NOUN
brj-22966	208	2	6	6	NUM
brj-22966	208	3	presents	present	VERB
brj-22966	208	4	the	the	DET
brj-22966	208	5	results	result	NOUN
brj-22966	208	6	of	of	ADP
brj-22966	208	7	verifying	verify	VERB
brj-22966	208	8	the	the	DET
brj-22966	208	9	homogeneous	homogeneous	ADJ
brj-22966	208	10	subsets	subset	NOUN
brj-22966	208	11	for	for	ADP
brj-22966	208	12	each	each	DET
brj-22966	208	13	validation	validation	NOUN
brj-22966	208	14	condition	condition	NOUN
brj-22966	208	15	during	during	ADP
brj-22966	208	16	cnn	cnn	PROPN
brj-22966	208	17	training	training	NOUN
brj-22966	208	18	.	.	PUNCT
brj-22966	209	1	during	during	ADP
brj-22966	209	2	the	the	DET
brj-22966	209	3	training	training	NOUN
brj-22966	209	4	phase	phase	NOUN
brj-22966	209	5	,	,	PUNCT
brj-22966	209	6	the	the	DET
brj-22966	209	7	augmented	augment	VERB
brj-22966	209	8	dataset	dataset	NOUN
brj-22966	209	9	was	be	AUX
brj-22966	209	10	classified	classify	VERB
brj-22966	209	11	into	into	ADP
brj-22966	209	12	the	the	DET
brj-22966	209	13	same	same	ADJ
brj-22966	209	14	subset	subset	NOUN
brj-22966	209	15	for	for	ADP
brj-22966	209	16	loss	loss	NOUN
brj-22966	209	17	and	and	CCONJ
brj-22966	209	18	accuracy	accuracy	NOUN
brj-22966	209	19	regardless	regardless	ADV
brj-22966	209	20	of	of	ADP
brj-22966	209	21	the	the	DET
brj-22966	209	22	type	type	NOUN
brj-22966	209	23	of	of	ADP
brj-22966	209	24	optimizer	optimizer	NOUN
brj-22966	209	25	used	use	VERB
brj-22966	209	26	.	.	PUNCT
brj-22966	210	1	during	during	ADP
brj-22966	210	2	the	the	DET
brj-22966	210	3	testing	testing	NOUN
brj-22966	210	4	phase	phase	NOUN
brj-22966	210	5	,	,	PUNCT
brj-22966	210	6	the	the	DET
brj-22966	210	7	augmented	augment	VERB
brj-22966	210	8	dataset	dataset	NOUN
brj-22966	210	9	was	be	AUX
brj-22966	210	10	classified	classify	VERB
brj-22966	210	11	into	into	ADP
brj-22966	210	12	the	the	DET
brj-22966	210	13	same	same	ADJ
brj-22966	210	14	subset	subset	NOUN
brj-22966	210	15	of	of	ADP
brj-22966	210	16	losses	loss	NOUN
brj-22966	210	17	only	only	ADV
brj-22966	210	18	when	when	SCONJ
brj-22966	210	19	sgd	sgd	NOUN
brj-22966	210	20	and	and	CCONJ
brj-22966	210	21	rmsprop	rmsprop	NOUN
brj-22966	210	22	were	be	AUX
brj-22966	210	23	used	use	VERB
brj-22966	210	24	.	.	PUNCT
brj-22966	211	1	the	the	DET
brj-22966	211	2	non	non	ADJ
brj-22966	211	3	-	-	ADJ
brj-22966	211	4	augmented	augment	VERB
brj-22966	211	5	dataset	dataset	NOUN
brj-22966	211	6	revealed	reveal	VERB
brj-22966	211	7	independent	independent	ADJ
brj-22966	211	8	subsets	subset	NOUN
brj-22966	211	9	for	for	ADP
brj-22966	211	10	all	all	DET
brj-22966	211	11	validation	validation	NOUN
brj-22966	211	12	conditions	condition	NOUN
brj-22966	211	13	during	during	ADP
brj-22966	211	14	the	the	DET
brj-22966	211	15	training	training	NOUN
brj-22966	211	16	phase	phase	NOUN
brj-22966	211	17	.	.	PUNCT
brj-22966	212	1	only	only	ADV
brj-22966	212	2	the	the	DET
brj-22966	212	3	loss	loss	NOUN
brj-22966	212	4	and	and	CCONJ
brj-22966	212	5	accuracy	accuracy	NOUN
brj-22966	212	6	from	from	ADP
brj-22966	212	7	the	the	DET
brj-22966	212	8	non	non	ADJ
brj-22966	212	9	-	-	ADJ
brj-22966	212	10	augmented	augment	VERB
brj-22966	212	11	adam	adam	NOUN
brj-22966	212	12	and	and	CCONJ
brj-22966	212	13	rmsprop	rmsprop	NOUN
brj-22966	212	14	methods	method	NOUN
brj-22966	212	15	were	be	AUX
brj-22966	212	16	classified	classify	VERB
brj-22966	212	17	into	into	ADP
brj-22966	212	18	the	the	DET
brj-22966	212	19	same	same	ADJ
brj-22966	212	20	subset	subset	NOUN
brj-22966	212	21	during	during	ADP
brj-22966	212	22	the	the	DET
brj-22966	212	23	test	test	NOUN
brj-22966	212	24	phase	phase	NOUN
brj-22966	212	25	.	.	PUNCT
brj-22966	213	1	conclusions	conclusion	NOUN
brj-22966	213	2	1	1	X
brj-22966	213	3	.	.	PUNCT
brj-22966	214	1	the	the	DET
brj-22966	214	2	bark	bark	NOUN
brj-22966	214	3	of	of	ADP
brj-22966	214	4	the	the	DET
brj-22966	214	5	seven	seven	NUM
brj-22966	214	6	oak	oak	NOUN
brj-22966	214	7	species	specie	NOUN
brj-22966	214	8	exhibited	exhibit	VERB
brj-22966	214	9	distinct	distinct	ADJ
brj-22966	214	10	variations	variation	NOUN
brj-22966	214	11	in	in	ADP
brj-22966	214	12	the	the	DET
brj-22966	214	13	size	size	NOUN
brj-22966	214	14	,	,	PUNCT
brj-22966	214	15	shape	shape	NOUN
brj-22966	214	16	,	,	PUNCT
brj-22966	214	17	and	and	CCONJ
brj-22966	214	18	frequency	frequency	NOUN
brj-22966	214	19	of	of	ADP
brj-22966	214	20	sclereids	sclereid	NOUN
brj-22966	214	21	.	.	PUNCT
brj-22966	215	1	2	2	X
brj-22966	215	2	.	.	X
brj-22966	215	3	the	the	DET
brj-22966	215	4	classification	classification	NOUN
brj-22966	215	5	accuracy	accuracy	NOUN
brj-22966	215	6	of	of	ADP
brj-22966	215	7	species	specie	NOUN
brj-22966	215	8	based	base	VERB
brj-22966	215	9	on	on	ADP
brj-22966	215	10	the	the	DET
brj-22966	215	11	bark	bark	NOUN
brj-22966	215	12	was	be	AUX
brj-22966	215	13	significantly	significantly	ADV
brj-22966	215	14	improved	improve	VERB
brj-22966	215	15	when	when	SCONJ
brj-22966	215	16	using	use	VERB
brj-22966	215	17	data	data	NOUN
brj-22966	215	18	augmentation	augmentation	NOUN
brj-22966	215	19	(	(	PUNCT
brj-22966	215	20	0.456	0.456	NOUN
brj-22966	215	21	*	*	NOUN
brj-22966	215	22	*	*	PUNCT
brj-22966	215	23	)	)	PUNCT
brj-22966	215	24	and	and	CCONJ
brj-22966	215	25	the	the	DET
brj-22966	215	26	rmsprop	rmsprop	NOUN
brj-22966	215	27	optimizer	optimizer	NOUN
brj-22966	215	28	(	(	PUNCT
brj-22966	215	29	0.194	0.194	NUM
brj-22966	215	30	*	*	PUNCT
brj-22966	215	31	*	*	PUNCT
brj-22966	215	32	)	)	PUNCT
brj-22966	215	33	.	.	PUNCT
brj-22966	216	1	the	the	DET
brj-22966	216	2	loss	loss	NOUN
brj-22966	216	3	reduction	reduction	NOUN
brj-22966	216	4	was	be	AUX
brj-22966	216	5	pronounced	pronounce	VERB
brj-22966	216	6	when	when	SCONJ
brj-22966	216	7	using	use	VERB
brj-22966	216	8	rmsprop	rmsprop	NOUN
brj-22966	216	9	(	(	PUNCT
brj-22966	216	10	−0.260	−0.260	PROPN
brj-22966	216	11	*	*	PROPN
brj-22966	216	12	*	*	NOUN
brj-22966	216	13	)	)	PUNCT
brj-22966	216	14	,	,	PUNCT
brj-22966	216	15	data	datum	NOUN
brj-22966	216	16	augmentation	augmentation	NOUN
brj-22966	216	17	(	(	PUNCT
brj-22966	216	18	-0.189	-0.189	NOUN
brj-22966	216	19	*	*	PUNCT
brj-22966	216	20	*	*	NOUN
brj-22966	216	21	)	)	PUNCT
brj-22966	216	22	,	,	PUNCT
brj-22966	216	23	and	and	CCONJ
brj-22966	216	24	sgd	sgd	X
brj-22966	216	25	(	(	PUNCT
brj-22966	216	26	−0.167	−0.167	PROPN
brj-22966	216	27	*	*	PROPN
brj-22966	216	28	*	*	NOUN
brj-22966	216	29	)	)	PUNCT
brj-22966	216	30	.	.	PUNCT
brj-22966	217	1	consequently	consequently	ADV
brj-22966	217	2	,	,	PUNCT
brj-22966	217	3	the	the	DET
brj-22966	217	4	augmented	augment	VERB
brj-22966	217	5	dataset	dataset	NOUN
brj-22966	217	6	with	with	ADP
brj-22966	217	7	the	the	DET
brj-22966	217	8	rmsprop	rmsprop	NOUN
brj-22966	217	9	optimizer	optimizer	NOUN
brj-22966	217	10	exhibited	exhibit	VERB
brj-22966	217	11	optimal	optimal	ADJ
brj-22966	217	12	performance	performance	NOUN
brj-22966	217	13	,	,	PUNCT
brj-22966	217	14	reaching	reach	VERB
brj-22966	217	15	89.8	89.8	NUM
brj-22966	217	16	%	%	NOUN
brj-22966	217	17	.	.	PUNCT
brj-22966	218	1	3	3	X
brj-22966	218	2	.	.	X
brj-22966	218	3	homogeneous	homogeneous	ADJ
brj-22966	218	4	subsets	subset	NOUN
brj-22966	218	5	using	use	VERB
brj-22966	218	6	the	the	DET
brj-22966	218	7	augmented	augment	VERB
brj-22966	218	8	dataset	dataset	NOUN
brj-22966	218	9	among	among	ADP
brj-22966	218	10	the	the	DET
brj-22966	218	11	validation	validation	NOUN
brj-22966	218	12	conditions	condition	NOUN
brj-22966	218	13	were	be	AUX
brj-22966	218	14	classified	classify	VERB
brj-22966	218	15	into	into	ADP
brj-22966	218	16	the	the	DET
brj-22966	218	17	same	same	ADJ
brj-22966	218	18	subsets	subset	NOUN
brj-22966	218	19	for	for	ADP
brj-22966	218	20	accuracy	accuracy	NOUN
brj-22966	218	21	and	and	CCONJ
brj-22966	218	22	loss	loss	NOUN
brj-22966	218	23	during	during	ADP
brj-22966	218	24	the	the	DET
brj-22966	218	25	training	training	NOUN
brj-22966	218	26	phase	phase	NOUN
brj-22966	218	27	,	,	PUNCT
brj-22966	218	28	regardless	regardless	ADV
brj-22966	218	29	of	of	ADP
brj-22966	218	30	the	the	DET
brj-22966	218	31	optimizer	optimizer	NOUN
brj-22966	218	32	used	use	VERB
brj-22966	218	33	.	.	PUNCT
brj-22966	219	1	only	only	ADV
brj-22966	219	2	the	the	DET
brj-22966	219	3	conditions	condition	NOUN
brj-22966	219	4	with	with	ADP
brj-22966	219	5	the	the	DET
brj-22966	219	6	adam	adam	NOUN
brj-22966	219	7	and	and	CCONJ
brj-22966	219	8	rmsprop	rmsprop	NOUN
brj-22966	219	9	optimizers	optimizer	NOUN
brj-22966	219	10	for	for	ADP
brj-22966	219	11	the	the	DET
brj-22966	219	12	non	non	ADJ
brj-22966	219	13	-	-	ADJ
brj-22966	219	14	augmented	augment	VERB
brj-22966	219	15	dataset	dataset	NOUN
brj-22966	219	16	were	be	AUX
brj-22966	219	17	classified	classify	VERB
brj-22966	219	18	into	into	ADP
brj-22966	219	19	the	the	DET
brj-22966	219	20	same	same	ADJ
brj-22966	219	21	subsets	subset	NOUN
brj-22966	219	22	for	for	ADP
brj-22966	219	23	accuracy	accuracy	NOUN
brj-22966	219	24	and	and	CCONJ
brj-22966	219	25	loss	loss	NOUN
brj-22966	219	26	during	during	ADP
brj-22966	219	27	the	the	DET
brj-22966	219	28	testing	testing	NOUN
brj-22966	219	29	phase	phase	NOUN
brj-22966	219	30	.	.	PUNCT
brj-22966	220	1	peer	peer	NOUN
brj-22966	220	2	-	-	PUNCT
brj-22966	220	3	reviewed	review	VERB
brj-22966	220	4	article	article	NOUN
brj-22966	220	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	220	6	kim	kim	PROPN
brj-22966	220	7	et	et	PROPN
brj-22966	220	8	al	al	PROPN
brj-22966	220	9	.	.	PROPN
brj-22966	221	1	(	(	PUNCT
brj-22966	221	2	2024	2024	NUM
brj-22966	221	3	)	)	PUNCT
brj-22966	221	4	.	.	PUNCT
brj-22966	222	1	“	"	PUNCT
brj-22966	222	2	convolutional	convolutional	ADJ
brj-22966	222	3	neural	neural	ADJ
brj-22966	222	4	network	network	NOUN
brj-22966	222	5	,	,	PUNCT
brj-22966	222	6	”	"	PUNCT
brj-22966	222	7	bioresources	bioresource	NOUN
brj-22966	222	8	19(1	19(1	NUM
brj-22966	222	9	)	)	PUNCT
brj-22966	222	10	,	,	PUNCT
brj-22966	222	11	510	510	NUM
brj-22966	222	12	-	-	SYM
brj-22966	222	13	524	524	NUM
brj-22966	222	14	.	.	PUNCT
brj-22966	223	1	522	522	NUM
brj-22966	223	2	4	4	NUM
brj-22966	223	3	.	.	PUNCT
brj-22966	224	1	in	in	ADP
brj-22966	224	2	conclusion	conclusion	NOUN
brj-22966	224	3	,	,	PUNCT
brj-22966	224	4	cnns	cnn	NOUN
brj-22966	224	5	used	use	VERB
brj-22966	224	6	for	for	ADP
brj-22966	224	7	species	species	NOUN
brj-22966	224	8	classification	classification	NOUN
brj-22966	224	9	using	use	VERB
brj-22966	224	10	sclereid	sclereid	NOUN
brj-22966	224	11	characteristics	characteristic	NOUN
brj-22966	224	12	in	in	ADP
brj-22966	224	13	the	the	DET
brj-22966	224	14	bark	bark	NOUN
brj-22966	224	15	of	of	ADP
brj-22966	224	16	seven	seven	NUM
brj-22966	224	17	oak	oak	NOUN
brj-22966	224	18	species	specie	NOUN
brj-22966	224	19	showed	show	VERB
brj-22966	224	20	classification	classification	NOUN
brj-22966	224	21	accuracies	accuracy	NOUN
brj-22966	224	22	ranging	range	VERB
brj-22966	224	23	between	between	ADP
brj-22966	224	24	74	74	NUM
brj-22966	224	25	%	%	NOUN
brj-22966	224	26	and	and	CCONJ
brj-22966	224	27	90	90	NUM
brj-22966	224	28	%	%	NOUN
brj-22966	224	29	.	.	PUNCT
brj-22966	225	1	sclereid	sclereid	NOUN
brj-22966	225	2	characteristics	characteristic	NOUN
brj-22966	225	3	are	be	AUX
brj-22966	225	4	expected	expect	VERB
brj-22966	225	5	to	to	PART
brj-22966	225	6	serve	serve	VERB
brj-22966	225	7	as	as	ADP
brj-22966	225	8	useful	useful	ADJ
brj-22966	225	9	indicators	indicator	NOUN
brj-22966	225	10	for	for	ADP
brj-22966	225	11	facilitating	facilitate	VERB
brj-22966	225	12	species	specie	NOUN
brj-22966	225	13	classification	classification	NOUN
brj-22966	225	14	.	.	PUNCT
brj-22966	226	1	especially	especially	ADV
brj-22966	226	2	,	,	PUNCT
brj-22966	226	3	the	the	DET
brj-22966	226	4	relatively	relatively	ADV
brj-22966	226	5	simple	simple	ADJ
brj-22966	226	6	preprocessing	preprocessing	NOUN
brj-22966	226	7	and	and	CCONJ
brj-22966	226	8	inspection	inspection	NOUN
brj-22966	226	9	procedures	procedure	NOUN
brj-22966	226	10	in	in	ADP
brj-22966	226	11	the	the	DET
brj-22966	226	12	trade	trade	NOUN
brj-22966	226	13	and	and	CCONJ
brj-22966	226	14	quarantine	quarantine	NOUN
brj-22966	226	15	procedures	procedure	NOUN
brj-22966	226	16	of	of	ADP
brj-22966	226	17	commercial	commercial	ADJ
brj-22966	226	18	cork	cork	NOUN
brj-22966	226	19	resources	resource	NOUN
brj-22966	226	20	from	from	ADP
brj-22966	226	21	quercus	quercus	ADJ
brj-22966	226	22	suber	suber	NOUN
brj-22966	226	23	and	and	CCONJ
brj-22966	226	24	quercus	quercus	ADJ
brj-22966	226	25	variabilis	variabili	NOUN
brj-22966	226	26	are	be	AUX
brj-22966	226	27	expected	expect	VERB
brj-22966	226	28	.	.	PUNCT
brj-22966	227	1	acknowledgments	acknowledgment	NOUN
brj-22966	227	2	this	this	DET
brj-22966	227	3	research	research	NOUN
brj-22966	227	4	was	be	AUX
brj-22966	227	5	supported	support	VERB
brj-22966	227	6	by	by	ADP
brj-22966	227	7	the	the	DET
brj-22966	227	8	science	science	NOUN
brj-22966	227	9	and	and	CCONJ
brj-22966	227	10	technology	technology	NOUN
brj-22966	227	11	support	support	NOUN
brj-22966	227	12	program	program	NOUN
brj-22966	227	13	through	through	ADP
brj-22966	227	14	the	the	DET
brj-22966	227	15	national	national	PROPN
brj-22966	227	16	research	research	PROPN
brj-22966	227	17	foundation	foundation	PROPN
brj-22966	227	18	of	of	ADP
brj-22966	227	19	korea	korea	PROPN
brj-22966	227	20	(	(	PUNCT
brj-22966	227	21	nrf	nrf	NOUN
brj-22966	227	22	)	)	PUNCT
brj-22966	227	23	funded	fund	VERB
brj-22966	227	24	by	by	ADP
brj-22966	227	25	the	the	DET
brj-22966	227	26	ministry	ministry	PROPN
brj-22966	227	27	of	of	ADP
brj-22966	227	28	science	science	PROPN
brj-22966	227	29	and	and	CCONJ
brj-22966	227	30	ict	ict	PROPN
brj-22966	227	31	(	(	PUNCT
brj-22966	227	32	msit	msit	PROPN
brj-22966	227	33	)	)	PUNCT
brj-22966	227	34	(	(	PUNCT
brj-22966	227	35	no	no	INTJ
brj-22966	227	36	.	.	NOUN
brj-22966	227	37	2022r1a2c1006470	2022r1a2c1006470	NUM
brj-22966	227	38	)	)	PUNCT
brj-22966	227	39	,	,	PUNCT
brj-22966	227	40	the	the	DET
brj-22966	227	41	basic	basic	ADJ
brj-22966	227	42	science	science	NOUN
brj-22966	227	43	research	research	NOUN
brj-22966	227	44	program	program	NOUN
brj-22966	227	45	through	through	ADP
brj-22966	227	46	the	the	DET
brj-22966	227	47	nrf	nrf	NOUN
brj-22966	227	48	funded	fund	VERB
brj-22966	227	49	by	by	ADP
brj-22966	227	50	the	the	DET
brj-22966	227	51	ministry	ministry	PROPN
brj-22966	227	52	of	of	ADP
brj-22966	227	53	education	education	PROPN
brj-22966	227	54	(	(	PUNCT
brj-22966	227	55	no	no	INTJ
brj-22966	227	56	.	.	NOUN
brj-22966	227	57	2018r1a6a1a03025582	2018r1a6a1a03025582	NUM
brj-22966	227	58	)	)	PUNCT
brj-22966	227	59	,	,	PUNCT
brj-22966	227	60	and	and	CCONJ
brj-22966	227	61	the	the	DET
brj-22966	227	62	r&d	r&d	NOUN
brj-22966	227	63	program	program	NOUN
brj-22966	227	64	for	for	ADP
brj-22966	227	65	forest	forest	NOUN
brj-22966	227	66	science	science	NOUN
brj-22966	227	67	technology	technology	NOUN
brj-22966	227	68	(	(	PUNCT
brj-22966	227	69	project	project	NOUN
brj-22966	227	70	nos	nos	X
brj-22966	227	71	.	.	PUNCT
brj-22966	228	1	2021350c10	2021350c10	PROPN
brj-22966	228	2	-	-	PUNCT
brj-22966	228	3	2323	2323	NUM
brj-22966	228	4	-	-	PUNCT
brj-22966	228	5	ac03	ac03	PROPN
brj-22966	228	6	and	and	CCONJ
brj-22966	228	7	2021311a00	2021311a00	NOUN
brj-22966	228	8	-	-	ADJ
brj-22966	228	9	2122	2122	NUM
brj-22966	228	10	-	-	PUNCT
brj-22966	228	11	aa03	aa03	PROPN
brj-22966	228	12	)	)	PUNCT
brj-22966	228	13	provided	provide	VERB
brj-22966	228	14	by	by	ADP
brj-22966	228	15	the	the	DET
brj-22966	228	16	korea	korea	PROPN
brj-22966	228	17	forest	forest	PROPN
brj-22966	228	18	service	service	PROPN
brj-22966	228	19	(	(	PUNCT
brj-22966	228	20	korea	korea	PROPN
brj-22966	228	21	forestry	forestry	PROPN
brj-22966	228	22	promotion	promotion	PROPN
brj-22966	228	23	institute	institute	PROPN
brj-22966	228	24	)	)	PUNCT
brj-22966	228	25	.	.	PUNCT
brj-22966	229	1	references	reference	NOUN
brj-22966	229	2	cited	cite	VERB
brj-22966	229	3	bertrand	bertrand	PROPN
brj-22966	229	4	,	,	PUNCT
brj-22966	229	5	s.	s.	PROPN
brj-22966	229	6	,	,	PUNCT
brj-22966	229	7	cerutti	cerutti	PROPN
brj-22966	229	8	,	,	PUNCT
brj-22966	229	9	g.	g.	PROPN
brj-22966	229	10	,	,	PUNCT
brj-22966	229	11	and	and	CCONJ
brj-22966	229	12	tougne	tougne	NOUN
brj-22966	229	13	,	,	PUNCT
brj-22966	229	14	l.	l.	PROPN
brj-22966	229	15	(	(	PUNCT
brj-22966	229	16	2017	2017	NUM
brj-22966	229	17	)	)	PUNCT
brj-22966	229	18	.	.	PUNCT
brj-22966	230	1	“	"	PUNCT
brj-22966	230	2	bark	bark	NOUN
brj-22966	230	3	recognition	recognition	NOUN
brj-22966	230	4	to	to	PART
brj-22966	230	5	improve	improve	VERB
brj-22966	230	6	leaf	leaf	NOUN
brj-22966	230	7	-	-	PUNCT
brj-22966	230	8	based	base	VERB
brj-22966	230	9	classification	classification	NOUN
brj-22966	230	10	in	in	ADP
brj-22966	230	11	didactic	didactic	ADJ
brj-22966	230	12	tree	tree	NOUN
brj-22966	230	13	species	species	NOUN
brj-22966	230	14	identification	identification	NOUN
brj-22966	230	15	,	,	PUNCT
brj-22966	230	16	”	"	PUNCT
brj-22966	230	17	in	in	ADP
brj-22966	230	18	:	:	PUNCT
brj-22966	230	19	proceedings	proceeding	NOUN
brj-22966	230	20	of	of	ADP
brj-22966	230	21	the	the	DET
brj-22966	230	22	12th	12th	ADJ
brj-22966	230	23	international	international	ADJ
brj-22966	230	24	joint	joint	ADJ
brj-22966	230	25	conference	conference	NOUN
brj-22966	230	26	on	on	ADP
brj-22966	230	27	computer	computer	NOUN
brj-22966	230	28	vision	vision	NOUN
brj-22966	230	29	,	,	PUNCT
brj-22966	230	30	imaging	imaging	NOUN
brj-22966	230	31	and	and	CCONJ
brj-22966	230	32	computer	computer	NOUN
brj-22966	230	33	graphics	graphic	NOUN
brj-22966	230	34	theory	theory	NOUN
brj-22966	230	35	and	and	CCONJ
brj-22966	230	36	applications	application	NOUN
brj-22966	230	37	(	(	PUNCT
brj-22966	230	38	visigrapp	visigrapp	NOUN
brj-22966	230	39	2017	2017	NUM
brj-22966	230	40	)	)	PUNCT
brj-22966	230	41	,	,	PUNCT
brj-22966	230	42	porto	porto	PROPN
brj-22966	230	43	,	,	PUNCT
brj-22966	230	44	portugal	portugal	PROPN
brj-22966	230	45	,	,	PUNCT
brj-22966	230	46	pp	pp	X
brj-22966	230	47	.	.	PUNCT
brj-22966	231	1	435	435	NUM
brj-22966	231	2	-	-	SYM
brj-22966	231	3	442	442	NUM
brj-22966	231	4	.	.	PUNCT
brj-22966	232	1	bremananth	bremananth	PROPN
brj-22966	232	2	,	,	PUNCT
brj-22966	232	3	r.	r.	PROPN
brj-22966	232	4	,	,	PUNCT
brj-22966	232	5	nithya	nithya	PROPN
brj-22966	232	6	,	,	PUNCT
brj-22966	232	7	b.	b.	PROPN
brj-22966	232	8	,	,	PUNCT
brj-22966	232	9	and	and	CCONJ
brj-22966	232	10	saipriya	saipriya	PROPN
brj-22966	232	11	,	,	PUNCT
brj-22966	232	12	r.	r.	PROPN
brj-22966	232	13	(	(	PUNCT
brj-22966	232	14	2009	2009	NUM
brj-22966	232	15	)	)	PUNCT
brj-22966	232	16	.	.	PUNCT
brj-22966	233	1	“	"	PUNCT
brj-22966	233	2	wood	wood	NOUN
brj-22966	233	3	species	species	NOUN
brj-22966	233	4	recognition	recognition	NOUN
brj-22966	233	5	system	system	NOUN
brj-22966	233	6	,	,	PUNCT
brj-22966	233	7	”	"	PUNCT
brj-22966	233	8	world	world	NOUN
brj-22966	233	9	academy	academy	PROPN
brj-22966	233	10	of	of	ADP
brj-22966	233	11	science	science	PROPN
brj-22966	233	12	,	,	PUNCT
brj-22966	233	13	engineering	engineering	NOUN
brj-22966	233	14	and	and	CCONJ
brj-22966	233	15	technology	technology	NOUN
brj-22966	233	16	52	52	NUM
brj-22966	233	17	,	,	PUNCT
brj-22966	233	18	873	873	NUM
brj-22966	233	19	-	-	NUM
brj-22966	233	20	879	879	NUM
brj-22966	233	21	.	.	PUNCT
brj-22966	234	1	cao	cao	PROPN
brj-22966	234	2	,	,	PUNCT
brj-22966	234	3	s.	s.	PROPN
brj-22966	234	4	,	,	PUNCT
brj-22966	234	5	zhou	zhou	PROPN
brj-22966	234	6	,	,	PUNCT
brj-22966	234	7	s.	s.	PROPN
brj-22966	234	8	,	,	PUNCT
brj-22966	234	9	liu	liu	PROPN
brj-22966	234	10	,	,	PUNCT
brj-22966	234	11	j.	j.	PROPN
brj-22966	234	12	,	,	PUNCT
brj-22966	234	13	liu	liu	PROPN
brj-22966	234	14	,	,	PUNCT
brj-22966	234	15	x.	x.	NOUN
brj-22966	234	16	,	,	PUNCT
brj-22966	234	17	and	and	CCONJ
brj-22966	234	18	zhou	zhou	PROPN
brj-22966	234	19	,	,	PUNCT
brj-22966	234	20	y.	y.	PROPN
brj-22966	234	21	(	(	PUNCT
brj-22966	234	22	2022	2022	NUM
brj-22966	234	23	)	)	PUNCT
brj-22966	234	24	.	.	PUNCT
brj-22966	235	1	“	"	PUNCT
brj-22966	235	2	wood	wood	NOUN
brj-22966	235	3	classification	classification	NOUN
brj-22966	235	4	study	study	NOUN
brj-22966	235	5	based	base	VERB
brj-22966	235	6	on	on	ADP
brj-22966	235	7	thermal	thermal	ADJ
brj-22966	235	8	physical	physical	ADJ
brj-22966	235	9	parameters	parameter	NOUN
brj-22966	235	10	with	with	ADP
brj-22966	235	11	intelligent	intelligent	ADJ
brj-22966	235	12	method	method	NOUN
brj-22966	235	13	of	of	ADP
brj-22966	235	14	artificial	artificial	ADJ
brj-22966	235	15	neural	neural	ADJ
brj-22966	235	16	networks	network	NOUN
brj-22966	235	17	,	,	PUNCT
brj-22966	235	18	”	"	PUNCT
brj-22966	235	19	bioresources	bioresource	NOUN
brj-22966	235	20	17(1	17(1	NUM
brj-22966	235	21	)	)	PUNCT
brj-22966	235	22	,	,	PUNCT
brj-22966	235	23	1187	1187	NUM
brj-22966	235	24	-	-	SYM
brj-22966	235	25	1204	1204	NUM
brj-22966	235	26	.	.	PUNCT
brj-22966	236	1	doi	doi	NOUN
brj-22966	236	2	:	:	PUNCT
brj-22966	236	3	10.15376	10.15376	NUM
brj-22966	236	4	/	/	SYM
brj-22966	236	5	biores.17.1.1187	biores.17.1.1187	NOUN
brj-22966	236	6	-	-	PUNCT
brj-22966	236	7	1204	1204	NUM
brj-22966	236	8	carpentier	carpentier	NOUN
brj-22966	236	9	,	,	PUNCT
brj-22966	236	10	m.	m.	NOUN
brj-22966	236	11	,	,	PUNCT
brj-22966	236	12	giguere	giguere	NOUN
brj-22966	236	13	,	,	PUNCT
brj-22966	236	14	p.	p.	NOUN
brj-22966	236	15	,	,	PUNCT
brj-22966	236	16	and	and	CCONJ
brj-22966	236	17	gaudreault	gaudreault	PROPN
brj-22966	236	18	,	,	PUNCT
brj-22966	236	19	j.	j.	PROPN
brj-22966	236	20	(	(	PUNCT
brj-22966	236	21	2018	2018	NUM
brj-22966	236	22	)	)	PUNCT
brj-22966	236	23	.	.	PUNCT
brj-22966	237	1	“	"	PUNCT
brj-22966	237	2	tree	tree	NOUN
brj-22966	237	3	species	species	NOUN
brj-22966	237	4	identification	identification	NOUN
brj-22966	237	5	from	from	ADP
brj-22966	237	6	bark	bark	NOUN
brj-22966	237	7	images	image	NOUN
brj-22966	237	8	using	use	VERB
brj-22966	237	9	convolutional	convolutional	ADJ
brj-22966	237	10	neural	neural	ADJ
brj-22966	237	11	networks	network	NOUN
brj-22966	237	12	,	,	PUNCT
brj-22966	237	13	”	"	PUNCT
brj-22966	237	14	in	in	ADP
brj-22966	237	15	:	:	PUNCT
brj-22966	237	16	proceedings	proceeding	NOUN
brj-22966	237	17	of	of	ADP
brj-22966	237	18	the	the	DET
brj-22966	237	19	2018	2018	NUM
brj-22966	237	20	ieee	ieee	NOUN
brj-22966	237	21	/	/	SYM
brj-22966	237	22	rsj	rsj	NOUN
brj-22966	237	23	international	international	ADJ
brj-22966	237	24	conference	conference	NOUN
brj-22966	237	25	on	on	ADP
brj-22966	237	26	intelligent	intelligent	ADJ
brj-22966	237	27	robots	robot	NOUN
brj-22966	237	28	and	and	CCONJ
brj-22966	237	29	systems	system	NOUN
brj-22966	237	30	(	(	PUNCT
brj-22966	237	31	iros	iro	NOUN
brj-22966	237	32	)	)	PUNCT
brj-22966	237	33	,	,	PUNCT
brj-22966	237	34	madrid	madrid	PROPN
brj-22966	237	35	,	,	PUNCT
brj-22966	237	36	spain	spain	PROPN
brj-22966	237	37	,	,	PUNCT
brj-22966	237	38	pp	pp	ADP
brj-22966	237	39	.	.	PUNCT
brj-22966	238	1	1075	1075	NUM
brj-22966	238	2	-	-	SYM
brj-22966	238	3	1081	1081	NUM
brj-22966	238	4	.	.	PUNCT
brj-22966	239	1	cho	cho	PROPN
brj-22966	239	2	,	,	PUNCT
brj-22966	239	3	t.	t.	PROPN
brj-22966	239	4	h.	h.	PROPN
brj-22966	239	5	(	(	PUNCT
brj-22966	239	6	2018	2018	NUM
brj-22966	239	7	)	)	PUNCT
brj-22966	239	8	.	.	PUNCT
brj-22966	240	1	deep	deep	ADJ
brj-22966	240	2	-	-	PUNCT
brj-22966	240	3	learning	learning	NOUN
brj-22966	240	4	for	for	ADP
brj-22966	240	5	everybody	everybody	PRON
brj-22966	240	6	,	,	PUNCT
brj-22966	240	7	gilbut	gilbut	PROPN
brj-22966	240	8	publishing	publishing	PROPN
brj-22966	240	9	,	,	PUNCT
brj-22966	240	10	seoul	seoul	PROPN
brj-22966	240	11	,	,	PUNCT
brj-22966	240	12	republic	republic	NOUN
brj-22966	240	13	of	of	ADP
brj-22966	240	14	korea	korea	PROPN
brj-22966	240	15	.	.	PUNCT
brj-22966	241	1	elgendy	elgendy	ADJ
brj-22966	241	2	,	,	PUNCT
brj-22966	241	3	m.	m.	NOUN
brj-22966	241	4	(	(	PUNCT
brj-22966	241	5	2021	2021	NUM
brj-22966	241	6	)	)	PUNCT
brj-22966	241	7	.	.	PUNCT
brj-22966	242	1	deep	deep	ADJ
brj-22966	242	2	learning	learning	NOUN
brj-22966	242	3	for	for	ADP
brj-22966	242	4	vision	vision	NOUN
brj-22966	242	5	systems	system	NOUN
brj-22966	242	6	,	,	PUNCT
brj-22966	242	7	hanbit	hanbit	NOUN
brj-22966	242	8	media	medium	NOUN
brj-22966	242	9	,	,	PUNCT
brj-22966	242	10	seoul	seoul	PROPN
brj-22966	242	11	,	,	PUNCT
brj-22966	242	12	republic	republic	NOUN
brj-22966	242	13	of	of	ADP
brj-22966	242	14	korea	korea	PROPN
brj-22966	242	15	.	.	PUNCT
brj-22966	243	1	fiel	fiel	PROPN
brj-22966	243	2	,	,	PUNCT
brj-22966	243	3	s.	s.	PROPN
brj-22966	243	4	,	,	PUNCT
brj-22966	243	5	and	and	CCONJ
brj-22966	243	6	sablatnig	sablatnig	PROPN
brj-22966	243	7	,	,	PUNCT
brj-22966	243	8	r.	r.	PROPN
brj-22966	243	9	(	(	PUNCT
brj-22966	243	10	2010	2010	NUM
brj-22966	243	11	)	)	PUNCT
brj-22966	243	12	.	.	PUNCT
brj-22966	244	1	“	"	PUNCT
brj-22966	244	2	automated	automate	VERB
brj-22966	244	3	identification	identification	NOUN
brj-22966	244	4	of	of	ADP
brj-22966	244	5	tree	tree	NOUN
brj-22966	244	6	species	specie	NOUN
brj-22966	244	7	from	from	ADP
brj-22966	244	8	images	image	NOUN
brj-22966	244	9	of	of	ADP
brj-22966	244	10	the	the	DET
brj-22966	244	11	bark	bark	NOUN
brj-22966	244	12	,	,	PUNCT
brj-22966	244	13	leaves	leave	NOUN
brj-22966	244	14	and	and	CCONJ
brj-22966	244	15	needles	needle	NOUN
brj-22966	244	16	,	,	PUNCT
brj-22966	244	17	”	"	PUNCT
brj-22966	244	18	in	in	ADP
brj-22966	244	19	:	:	PUNCT
brj-22966	244	20	proceedings	proceeding	NOUN
brj-22966	244	21	of	of	ADP
brj-22966	244	22	the	the	DET
brj-22966	244	23	16th	16th	ADJ
brj-22966	244	24	computer	computer	NOUN
brj-22966	244	25	vision	vision	NOUN
brj-22966	244	26	winter	winter	NOUN
brj-22966	244	27	workshop	workshop	NOUN
brj-22966	244	28	,	,	PUNCT
brj-22966	244	29	mitterberg	mitterberg	PROPN
brj-22966	244	30	,	,	PUNCT
brj-22966	244	31	austria	austria	PROPN
brj-22966	244	32	,	,	PUNCT
brj-22966	244	33	pp	pp	ADJ
brj-22966	244	34	.	.	PUNCT
brj-22966	245	1	67	67	NUM
brj-22966	245	2	-	-	SYM
brj-22966	245	3	74	74	NUM
brj-22966	245	4	.	.	PUNCT
brj-22966	245	5	fujita	fujita	PROPN
brj-22966	245	6	,	,	PUNCT
brj-22966	245	7	k.	k.	PROPN
brj-22966	245	8	,	,	PUNCT
brj-22966	245	9	and	and	CCONJ
brj-22966	245	10	takahara	takahara	NOUN
brj-22966	245	11	,	,	PUNCT
brj-22966	245	12	a.	a.	NOUN
brj-22966	245	13	(	(	PUNCT
brj-22966	245	14	2017	2017	NUM
brj-22966	245	15	)	)	PUNCT
brj-22966	245	16	.	.	PUNCT
brj-22966	246	1	deep	deep	ADJ
brj-22966	246	2	learning	learning	NOUN
brj-22966	246	3	bootcamp	bootcamp	NOUN
brj-22966	246	4	with	with	ADP
brj-22966	246	5	keras	keras	PROPN
brj-22966	246	6	,	,	PUNCT
brj-22966	246	7	gilbut	gilbut	PROPN
brj-22966	246	8	publishing	publishing	PROPN
brj-22966	246	9	,	,	PUNCT
brj-22966	246	10	seoul	seoul	PROPN
brj-22966	246	11	,	,	PUNCT
brj-22966	246	12	republic	republic	NOUN
brj-22966	246	13	of	of	ADP
brj-22966	246	14	korea	korea	PROPN
brj-22966	246	15	.	.	PUNCT
brj-22966	247	1	géron	géron	PROPN
brj-22966	247	2	,	,	PUNCT
brj-22966	247	3	a.	a.	NOUN
brj-22966	247	4	(	(	PUNCT
brj-22966	247	5	2020	2020	NUM
brj-22966	247	6	)	)	PUNCT
brj-22966	247	7	.	.	PUNCT
brj-22966	248	1	hands	hand	NOUN
brj-22966	248	2	-	-	PUNCT
brj-22966	248	3	on	on	ADP
brj-22966	248	4	machine	machine	NOUN
brj-22966	248	5	learning	learn	VERB
brj-22966	248	6	with	with	ADP
brj-22966	248	7	scikit	scikit	NOUN
brj-22966	248	8	-	-	PUNCT
brj-22966	248	9	learn	learn	PROPN
brj-22966	248	10	,	,	PUNCT
brj-22966	248	11	keras	keras	PROPN
brj-22966	248	12	,	,	PUNCT
brj-22966	248	13	and	and	CCONJ
brj-22966	248	14	tensorflow	tensorflow	NOUN
brj-22966	248	15	,	,	PUNCT
brj-22966	248	16	hanbit	hanbit	NOUN
brj-22966	248	17	media	medium	NOUN
brj-22966	248	18	,	,	PUNCT
brj-22966	248	19	seoul	seoul	PROPN
brj-22966	248	20	,	,	PUNCT
brj-22966	248	21	republic	republic	NOUN
brj-22966	248	22	of	of	ADP
brj-22966	248	23	korea	korea	PROPN
brj-22966	248	24	.	.	PUNCT
brj-22966	249	1	he	he	PRON
brj-22966	249	2	,	,	PUNCT
brj-22966	249	3	k.	k.	PROPN
brj-22966	249	4	,	,	PUNCT
brj-22966	249	5	zhang	zhang	PROPN
brj-22966	249	6	,	,	PUNCT
brj-22966	249	7	x.	x.	PROPN
brj-22966	249	8	,	,	PUNCT
brj-22966	249	9	ren	ren	PROPN
brj-22966	249	10	,	,	PUNCT
brj-22966	249	11	s.	s.	PROPN
brj-22966	249	12	,	,	PUNCT
brj-22966	249	13	and	and	CCONJ
brj-22966	249	14	sun	sun	NOUN
brj-22966	249	15	,	,	PUNCT
brj-22966	249	16	j.	j.	PROPN
brj-22966	249	17	(	(	PUNCT
brj-22966	249	18	2016	2016	NUM
brj-22966	249	19	)	)	PUNCT
brj-22966	249	20	.	.	PUNCT
brj-22966	250	1	“	"	PUNCT
brj-22966	250	2	deep	deep	ADJ
brj-22966	250	3	residual	residual	ADJ
brj-22966	250	4	learning	learning	NOUN
brj-22966	250	5	for	for	ADP
brj-22966	250	6	image	image	NOUN
brj-22966	250	7	recognition	recognition	NOUN
brj-22966	250	8	,	,	PUNCT
brj-22966	250	9	”	"	PUNCT
brj-22966	250	10	in	in	ADP
brj-22966	250	11	:	:	PUNCT
brj-22966	250	12	proceeding	proceeding	NOUN
brj-22966	250	13	of	of	ADP
brj-22966	250	14	2016	2016	NUM
brj-22966	250	15	ieee	ieee	NOUN
brj-22966	250	16	conference	conference	NOUN
brj-22966	250	17	on	on	ADP
brj-22966	250	18	computer	computer	NOUN
brj-22966	250	19	vision	vision	NOUN
brj-22966	250	20	and	and	CCONJ
brj-22966	250	21	pattern	pattern	NOUN
brj-22966	250	22	recognition	recognition	NOUN
brj-22966	250	23	(	(	PUNCT
brj-22966	250	24	cvpr	cvpr	NOUN
brj-22966	250	25	)	)	PUNCT
brj-22966	250	26	,	,	PUNCT
brj-22966	250	27	las	las	PROPN
brj-22966	250	28	vegas	vegas	PROPN
brj-22966	250	29	,	,	PUNCT
brj-22966	250	30	usa	usa	PROPN
brj-22966	250	31	,	,	PUNCT
brj-22966	250	32	pp	pp	ADJ
brj-22966	250	33	.	.	PUNCT
brj-22966	251	1	770	770	NUM
brj-22966	251	2	-	-	SYM
brj-22966	251	3	778	778	NUM
brj-22966	251	4	.	.	PUNCT
brj-22966	251	5	peer	peer	NOUN
brj-22966	251	6	-	-	PUNCT
brj-22966	251	7	reviewed	review	VERB
brj-22966	251	8	article	article	NOUN
brj-22966	251	9	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	251	10	kim	kim	PROPN
brj-22966	251	11	et	et	PROPN
brj-22966	251	12	al	al	PROPN
brj-22966	251	13	.	.	PROPN
brj-22966	252	1	(	(	PUNCT
brj-22966	252	2	2024	2024	NUM
brj-22966	252	3	)	)	PUNCT
brj-22966	252	4	.	.	PUNCT
brj-22966	253	1	“	"	PUNCT
brj-22966	253	2	convolutional	convolutional	ADJ
brj-22966	253	3	neural	neural	ADJ
brj-22966	253	4	network	network	NOUN
brj-22966	253	5	,	,	PUNCT
brj-22966	253	6	”	"	PUNCT
brj-22966	253	7	bioresources	bioresource	NOUN
brj-22966	253	8	19(1	19(1	NUM
brj-22966	253	9	)	)	PUNCT
brj-22966	253	10	,	,	PUNCT
brj-22966	253	11	510	510	NUM
brj-22966	253	12	-	-	SYM
brj-22966	253	13	524	524	NUM
brj-22966	253	14	.	.	NOUN
brj-22966	253	15	523	523	NUM
brj-22966	253	16	hermanson	hermanson	NOUN
brj-22966	253	17	,	,	PUNCT
brj-22966	253	18	j.	j.	PROPN
brj-22966	253	19	c.	c.	PROPN
brj-22966	253	20	,	,	PUNCT
brj-22966	253	21	and	and	CCONJ
brj-22966	253	22	wiedenhoeft	wiedenhoeft	VERB
brj-22966	253	23	,	,	PUNCT
brj-22966	253	24	a.	a.	PROPN
brj-22966	253	25	c.	c.	PROPN
brj-22966	253	26	(	(	PUNCT
brj-22966	253	27	2011	2011	NUM
brj-22966	253	28	)	)	PUNCT
brj-22966	253	29	.	.	PUNCT
brj-22966	254	1	“	"	PUNCT
brj-22966	254	2	a	a	DET
brj-22966	254	3	brief	brief	ADJ
brj-22966	254	4	review	review	NOUN
brj-22966	254	5	of	of	ADP
brj-22966	254	6	machine	machine	NOUN
brj-22966	254	7	vision	vision	NOUN
brj-22966	254	8	in	in	ADP
brj-22966	254	9	the	the	DET
brj-22966	254	10	context	context	NOUN
brj-22966	254	11	of	of	ADP
brj-22966	254	12	automated	automate	VERB
brj-22966	254	13	wood	wood	NOUN
brj-22966	254	14	identification	identification	NOUN
brj-22966	254	15	systems	system	NOUN
brj-22966	254	16	,	,	PUNCT
brj-22966	254	17	”	"	PUNCT
brj-22966	254	18	iawa	iawa	PROPN
brj-22966	254	19	journal	journal	PROPN
brj-22966	254	20	32(2	32(2	NUM
brj-22966	254	21	)	)	PUNCT
brj-22966	254	22	,	,	PUNCT
brj-22966	254	23	233250	233250	NUM
brj-22966	254	24	.	.	PUNCT
brj-22966	255	1	doi	doi	NOUN
brj-22966	255	2	:	:	PUNCT
brj-22966	255	3	10.1163/22941932	10.1163/22941932	NUM
brj-22966	255	4	-	-	SYM
brj-22966	255	5	90000054	90000054	NUM
brj-22966	255	6	huang	huang	PROPN
brj-22966	255	7	,	,	PUNCT
brj-22966	255	8	p.	p.	PROPN
brj-22966	255	9	,	,	PUNCT
brj-22966	255	10	zhao	zhao	PROPN
brj-22966	255	11	,	,	PUNCT
brj-22966	255	12	f.	f.	PROPN
brj-22966	255	13	,	,	PUNCT
brj-22966	255	14	zhu	zhu	PROPN
brj-22966	255	15	,	,	PUNCT
brj-22966	255	16	z.	z.	PROPN
brj-22966	255	17	,	,	PUNCT
brj-22966	255	18	zhang	zhang	PROPN
brj-22966	255	19	,	,	PUNCT
brj-22966	255	20	y.	y.	PROPN
brj-22966	255	21	,	,	PUNCT
brj-22966	255	22	li	li	PROPN
brj-22966	255	23	,	,	PUNCT
brj-22966	255	24	x.	x.	NOUN
brj-22966	255	25	,	,	PUNCT
brj-22966	255	26	and	and	CCONJ
brj-22966	255	27	wu	wu	PROPN
brj-22966	255	28	,	,	PUNCT
brj-22966	255	29	z.	z.	PROPN
brj-22966	255	30	(	(	PUNCT
brj-22966	255	31	2021	2021	NUM
brj-22966	255	32	)	)	PUNCT
brj-22966	255	33	.	.	PUNCT
brj-22966	256	1	“	"	PUNCT
brj-22966	256	2	application	application	NOUN
brj-22966	256	3	of	of	ADP
brj-22966	256	4	variant	variant	ADJ
brj-22966	256	5	transfer	transfer	NOUN
brj-22966	256	6	learning	learning	NOUN
brj-22966	256	7	in	in	ADP
brj-22966	256	8	wood	wood	NOUN
brj-22966	256	9	recognition	recognition	NOUN
brj-22966	256	10	,	,	PUNCT
brj-22966	256	11	”	"	PUNCT
brj-22966	256	12	bioresources	bioresource	NOUN
brj-22966	256	13	16(2	16(2	NUM
brj-22966	256	14	)	)	PUNCT
brj-22966	256	15	,	,	PUNCT
brj-22966	256	16	2557	2557	NUM
brj-22966	256	17	-	-	SYM
brj-22966	256	18	2569	2569	NUM
brj-22966	256	19	.	.	PUNCT
brj-22966	257	1	doi	doi	NOUN
brj-22966	257	2	:	:	PUNCT
brj-22966	257	3	10.15376	10.15376	NUM
brj-22966	257	4	/	/	SYM
brj-22966	257	5	biores.16.2.2557	biores.16.2.2557	PROPN
brj-22966	257	6	-	-	PUNCT
brj-22966	257	7	2569	2569	NUM
brj-22966	257	8	hwang	hwang	PROPN
brj-22966	257	9	,	,	PUNCT
brj-22966	257	10	s.	s.	PROPN
brj-22966	257	11	w.	w.	PROPN
brj-22966	257	12	,	,	PUNCT
brj-22966	257	13	and	and	CCONJ
brj-22966	257	14	sugiyama	sugiyama	NOUN
brj-22966	257	15	,	,	PUNCT
brj-22966	257	16	j.	j.	PROPN
brj-22966	257	17	(	(	PUNCT
brj-22966	257	18	2021	2021	NUM
brj-22966	257	19	)	)	PUNCT
brj-22966	257	20	.	.	PUNCT
brj-22966	258	1	“	"	PUNCT
brj-22966	258	2	computer	computer	NOUN
brj-22966	258	3	vision	vision	NOUN
brj-22966	258	4	-	-	PUNCT
brj-22966	258	5	based	base	VERB
brj-22966	258	6	wood	wood	NOUN
brj-22966	258	7	identification	identification	NOUN
brj-22966	258	8	and	and	CCONJ
brj-22966	258	9	its	its	PRON
brj-22966	258	10	expansion	expansion	NOUN
brj-22966	258	11	and	and	CCONJ
brj-22966	258	12	contribution	contribution	NOUN
brj-22966	258	13	potentials	potential	VERB
brj-22966	258	14	in	in	ADP
brj-22966	258	15	wood	wood	NOUN
brj-22966	258	16	science	science	NOUN
brj-22966	258	17	:	:	PUNCT
brj-22966	258	18	a	a	DET
brj-22966	258	19	review	review	NOUN
brj-22966	258	20	,	,	PUNCT
brj-22966	258	21	”	"	PUNCT
brj-22966	258	22	plant	plant	NOUN
brj-22966	258	23	methods	method	NOUN
brj-22966	258	24	17(1	17(1	NUM
brj-22966	258	25	)	)	PUNCT
brj-22966	258	26	,	,	PUNCT
brj-22966	258	27	47	47	NUM
brj-22966	258	28	.	.	PUNCT
brj-22966	259	1	doi	doi	NOUN
brj-22966	259	2	:	:	PUNCT
brj-22966	259	3	10.1186	10.1186	NUM
brj-22966	259	4	/	/	SYM
brj-22966	259	5	s13007	s13007	NOUN
brj-22966	259	6	-	-	PUNCT
brj-22966	259	7	021	021	NUM
brj-22966	259	8	-	-	PUNCT
brj-22966	259	9	00746	00746	NUM
brj-22966	259	10	-	-	SYM
brj-22966	259	11	1	1	NUM
brj-22966	259	12	hwang	hwang	PROPN
brj-22966	259	13	,	,	PUNCT
brj-22966	259	14	s.	s.	PROPN
brj-22966	259	15	w.	w.	PROPN
brj-22966	259	16	,	,	PUNCT
brj-22966	259	17	kobayashi	kobayashi	PROPN
brj-22966	259	18	,	,	PUNCT
brj-22966	259	19	k.	k.	PROPN
brj-22966	259	20	,	,	PUNCT
brj-22966	259	21	and	and	CCONJ
brj-22966	259	22	sugiyama	sugiyama	NOUN
brj-22966	259	23	,	,	PUNCT
brj-22966	259	24	j.	j.	PROPN
brj-22966	259	25	(	(	PUNCT
brj-22966	259	26	2020	2020	NUM
brj-22966	259	27	)	)	PUNCT
brj-22966	259	28	.	.	PUNCT
brj-22966	260	1	“	"	PUNCT
brj-22966	260	2	detection	detection	NOUN
brj-22966	260	3	and	and	CCONJ
brj-22966	260	4	visualization	visualization	NOUN
brj-22966	260	5	of	of	ADP
brj-22966	260	6	encoded	encode	VERB
brj-22966	260	7	local	local	ADJ
brj-22966	260	8	features	feature	NOUN
brj-22966	260	9	as	as	ADP
brj-22966	260	10	anatomical	anatomical	ADJ
brj-22966	260	11	predictors	predictor	NOUN
brj-22966	260	12	in	in	ADP
brj-22966	260	13	cross	cross	ADJ
brj-22966	260	14	-	-	ADJ
brj-22966	260	15	sectional	sectional	ADJ
brj-22966	260	16	images	image	NOUN
brj-22966	260	17	of	of	ADP
brj-22966	260	18	lauraceae	lauraceae	ADJ
brj-22966	260	19	,	,	PUNCT
brj-22966	260	20	”	"	PUNCT
brj-22966	260	21	journal	journal	NOUN
brj-22966	260	22	of	of	ADP
brj-22966	260	23	wood	wood	NOUN
brj-22966	260	24	science	science	NOUN
brj-22966	260	25	66(1	66(1	NOUN
brj-22966	260	26	)	)	PUNCT
brj-22966	260	27	,	,	PUNCT
brj-22966	260	28	1	1	NUM
brj-22966	260	29	-	-	SYM
brj-22966	260	30	16	16	NUM
brj-22966	260	31	.	.	PUNCT
brj-22966	261	1	doi	doi	NOUN
brj-22966	261	2	:	:	PUNCT
brj-22966	261	3	10.1186	10.1186	NUM
brj-22966	261	4	/	/	SYM
brj-22966	261	5	s10086	s10086	PROPN
brj-22966	261	6	-	-	PUNCT
brj-22966	261	7	020	020	NUM
brj-22966	261	8	-	-	PUNCT
brj-22966	261	9	01864	01864	NUM
brj-22966	261	10	-	-	PUNCT
brj-22966	261	11	5	5	NUM
brj-22966	261	12	iawa	iawa	PROPN
brj-22966	261	13	committee	committee	NOUN
brj-22966	261	14	.	.	PUNCT
brj-22966	262	1	(	(	PUNCT
brj-22966	262	2	2016	2016	NUM
brj-22966	262	3	)	)	PUNCT
brj-22966	262	4	.	.	PUNCT
brj-22966	263	1	“	"	PUNCT
brj-22966	263	2	iawa	iawa	PROPN
brj-22966	263	3	list	list	NOUN
brj-22966	263	4	of	of	ADP
brj-22966	263	5	microscopic	microscopic	ADJ
brj-22966	263	6	bark	bark	NOUN
brj-22966	263	7	features	feature	NOUN
brj-22966	263	8	,	,	PUNCT
brj-22966	263	9	”	"	PUNCT
brj-22966	263	10	iawa	iawa	PROPN
brj-22966	263	11	journal	journal	VERB
brj-22966	263	12	37(4	37(4	PROPN
brj-22966	263	13	)	)	PUNCT
brj-22966	263	14	,	,	PUNCT
brj-22966	263	15	517	517	NUM
brj-22966	263	16	-	-	SYM
brj-22966	263	17	615	615	NUM
brj-22966	263	18	.	.	PUNCT
brj-22966	264	1	doi	doi	NOUN
brj-22966	264	2	:	:	PUNCT
brj-22966	264	3	10.1163/22941932	10.1163/22941932	NUM
brj-22966	264	4	-	-	SYM
brj-22966	264	5	20160151	20160151	NUM
brj-22966	264	6	ilic	ilic	NOUN
brj-22966	264	7	,	,	PUNCT
brj-22966	264	8	j.	j.	PROPN
brj-22966	264	9	(	(	PUNCT
brj-22966	264	10	1993	1993	NUM
brj-22966	264	11	)	)	PUNCT
brj-22966	264	12	.	.	PUNCT
brj-22966	265	1	“	"	PUNCT
brj-22966	265	2	computer	computer	NOUN
brj-22966	265	3	aided	aid	VERB
brj-22966	265	4	wood	wood	NOUN
brj-22966	265	5	identification	identification	NOUN
brj-22966	265	6	using	use	VERB
brj-22966	265	7	csiroid	csiroid	NOUN
brj-22966	265	8	,	,	PUNCT
brj-22966	265	9	”	"	PUNCT
brj-22966	265	10	iawa	iawa	PROPN
brj-22966	265	11	journal	journal	PROPN
brj-22966	265	12	14(4	14(4	NOUN
brj-22966	265	13	)	)	PUNCT
brj-22966	265	14	,	,	PUNCT
brj-22966	265	15	333	333	NUM
brj-22966	265	16	-	-	SYM
brj-22966	265	17	340	340	NUM
brj-22966	265	18	.	.	PUNCT
brj-22966	266	1	doi	doi	NOUN
brj-22966	266	2	:	:	PUNCT
brj-22966	266	3	10.1163/22941932	10.1163/22941932	NUM
brj-22966	266	4	-	-	SYM
brj-22966	266	5	90000587	90000587	NUM
brj-22966	266	6	kim	kim	PROPN
brj-22966	266	7	,	,	PUNCT
brj-22966	266	8	b.	b.	PROPN
brj-22966	266	9	r.	r.	PROPN
brj-22966	266	10	(	(	PUNCT
brj-22966	266	11	1993	1993	NUM
brj-22966	266	12	)	)	PUNCT
brj-22966	266	13	.	.	PUNCT
brj-22966	267	1	“	"	PUNCT
brj-22966	267	2	studies	study	NOUN
brj-22966	267	3	on	on	ADP
brj-22966	267	4	the	the	DET
brj-22966	267	5	physical	physical	ADJ
brj-22966	267	6	and	and	CCONJ
brj-22966	267	7	mechanical	mechanical	ADJ
brj-22966	267	8	properties	property	NOUN
brj-22966	267	9	of	of	ADP
brj-22966	267	10	imported	import	VERB
brj-22966	267	11	and	and	CCONJ
brj-22966	267	12	domestic	domestic	ADJ
brj-22966	267	13	corks	cork	NOUN
brj-22966	267	14	,	,	PUNCT
brj-22966	267	15	”	"	PUNCT
brj-22966	267	16	journal	journal	NOUN
brj-22966	267	17	of	of	ADP
brj-22966	267	18	the	the	DET
brj-22966	267	19	korean	korean	ADJ
brj-22966	267	20	wood	wood	NOUN
brj-22966	267	21	science	science	NOUN
brj-22966	267	22	and	and	CCONJ
brj-22966	267	23	technology	technology	NOUN
brj-22966	267	24	21(4	21(4	NUM
brj-22966	267	25	)	)	PUNCT
brj-22966	267	26	,	,	PUNCT
brj-22966	267	27	45	45	NUM
brj-22966	267	28	-	-	SYM
brj-22966	267	29	54	54	NUM
brj-22966	267	30	.	.	PUNCT
brj-22966	268	1	kim	kim	PROPN
brj-22966	268	2	,	,	PUNCT
brj-22966	268	3	j.	j.	PROPN
brj-22966	268	4	h.	h.	PROPN
brj-22966	268	5	,	,	PUNCT
brj-22966	268	6	kim	kim	PROPN
brj-22966	268	7	,	,	PUNCT
brj-22966	268	8	d.	d.	PROPN
brj-22966	268	9	h.	h.	PROPN
brj-22966	268	10	,	,	PUNCT
brj-22966	268	11	kim	kim	PROPN
brj-22966	268	12	,	,	PUNCT
brj-22966	268	13	s.	s.	PROPN
brj-22966	268	14	h.	h.	PROPN
brj-22966	268	15	,	,	PUNCT
brj-22966	268	16	suri	suri	PROPN
brj-22966	268	17	,	,	PUNCT
brj-22966	268	18	i.	i.	PROPN
brj-22966	268	19	f.	f.	PROPN
brj-22966	268	20	,	,	PUNCT
brj-22966	268	21	purusatama	purusatama	PROPN
brj-22966	268	22	,	,	PUNCT
brj-22966	268	23	b.	b.	PROPN
brj-22966	268	24	d.	d.	PROPN
brj-22966	268	25	,	,	PUNCT
brj-22966	268	26	jo	jo	PROPN
brj-22966	268	27	,	,	PUNCT
brj-22966	268	28	j.	j.	PROPN
brj-22966	268	29	i.	i.	PROPN
brj-22966	268	30	,	,	PUNCT
brj-22966	268	31	lee	lee	PROPN
brj-22966	268	32	,	,	PUNCT
brj-22966	268	33	h.	h.	PROPN
brj-22966	268	34	s.	s.	PROPN
brj-22966	268	35	,	,	PUNCT
brj-22966	268	36	hidayat	hidayat	PROPN
brj-22966	268	37	,	,	PUNCT
brj-22966	268	38	w.	w.	PROPN
brj-22966	268	39	,	,	PUNCT
brj-22966	268	40	febrianto	febrianto	PROPN
brj-22966	268	41	,	,	PUNCT
brj-22966	268	42	f.	f.	PROPN
brj-22966	268	43	,	,	PUNCT
brj-22966	268	44	lee	lee	PROPN
brj-22966	268	45	,	,	PUNCT
brj-22966	268	46	s.	s.	PROPN
brj-22966	268	47	h.	h.	PROPN
brj-22966	268	48	,	,	PUNCT
brj-22966	268	49	and	and	CCONJ
brj-22966	268	50	kim	kim	PROPN
brj-22966	268	51	,	,	PUNCT
brj-22966	268	52	n.	n.	PROPN
brj-22966	268	53	h.	h.	PROPN
brj-22966	268	54	(	(	PUNCT
brj-22966	268	55	2021	2021	NUM
brj-22966	268	56	)	)	PUNCT
brj-22966	268	57	.	.	PUNCT
brj-22966	269	1	“	"	PUNCT
brj-22966	269	2	comparison	comparison	NOUN
brj-22966	269	3	of	of	ADP
brj-22966	269	4	anatomical	anatomical	ADJ
brj-22966	269	5	features	feature	NOUN
brj-22966	269	6	in	in	ADP
brj-22966	269	7	the	the	DET
brj-22966	269	8	three	three	NUM
brj-22966	269	9	syzygium	syzygium	NOUN
brj-22966	269	10	species	specie	NOUN
brj-22966	269	11	,	,	PUNCT
brj-22966	269	12	”	"	PUNCT
brj-22966	269	13	bioresources	bioresource	NOUN
brj-22966	269	14	16(2	16(2	NUM
brj-22966	269	15	)	)	PUNCT
brj-22966	269	16	,	,	PUNCT
brj-22966	269	17	3631	3631	NUM
brj-22966	269	18	-	-	SYM
brj-22966	269	19	3642	3642	NUM
brj-22966	269	20	.	.	PUNCT
brj-22966	270	1	doi	doi	NOUN
brj-22966	270	2	:	:	PUNCT
brj-22966	270	3	10.15376	10.15376	NUM
brj-22966	270	4	/	/	SYM
brj-22966	270	5	biores.16.2.3631	biores.16.2.3631	PROPN
brj-22966	270	6	-	-	PUNCT
brj-22966	270	7	3642	3642	NUM
brj-22966	270	8	kim	kim	PROPN
brj-22966	270	9	,	,	PUNCT
brj-22966	270	10	j.	j.	PROPN
brj-22966	270	11	h.	h.	PROPN
brj-22966	270	12	,	,	PUNCT
brj-22966	270	13	purusatama	purusatama	PROPN
brj-22966	270	14	,	,	PUNCT
brj-22966	270	15	b.	b.	PROPN
brj-22966	270	16	d.	d.	PROPN
brj-22966	270	17	,	,	PUNCT
brj-22966	270	18	savero	savero	PROPN
brj-22966	270	19	,	,	PUNCT
brj-22966	270	20	a.	a.	NOUN
brj-22966	270	21	m.	m.	NOUN
brj-22966	270	22	,	,	PUNCT
brj-22966	270	23	prasetia	prasetia	PROPN
brj-22966	270	24	,	,	PUNCT
brj-22966	270	25	d.	d.	PROPN
brj-22966	270	26	,	,	PUNCT
brj-22966	270	27	yang	yang	PROPN
brj-22966	270	28	,	,	PUNCT
brj-22966	270	29	g.	g.	PROPN
brj-22966	270	30	u.	u.	PROPN
brj-22966	270	31	,	,	PUNCT
brj-22966	270	32	han	han	PROPN
brj-22966	270	33	,	,	PUNCT
brj-22966	270	34	s.	s.	PROPN
brj-22966	270	35	y.	y.	PROPN
brj-22966	270	36	,	,	PUNCT
brj-22966	270	37	lee	lee	PROPN
brj-22966	270	38	,	,	PUNCT
brj-22966	270	39	s.	s.	PROPN
brj-22966	270	40	h.	h.	PROPN
brj-22966	270	41	,	,	PUNCT
brj-22966	270	42	and	and	CCONJ
brj-22966	270	43	kim	kim	PROPN
brj-22966	270	44	,	,	PUNCT
brj-22966	270	45	n.	n.	PROPN
brj-22966	270	46	h.	h.	PROPN
brj-22966	270	47	(	(	PUNCT
brj-22966	270	48	2023	2023	NUM
brj-22966	270	49	)	)	PUNCT
brj-22966	270	50	.	.	PUNCT
brj-22966	271	1	“	"	PUNCT
brj-22966	271	2	performance	performance	NOUN
brj-22966	271	3	influencing	influence	VERB
brj-22966	271	4	factors	factor	NOUN
brj-22966	271	5	of	of	ADP
brj-22966	271	6	convolutional	convolutional	ADJ
brj-22966	271	7	neural	neural	ADJ
brj-22966	271	8	network	network	NOUN
brj-22966	271	9	models	model	NOUN
brj-22966	271	10	for	for	ADP
brj-22966	271	11	classifying	classify	VERB
brj-22966	271	12	certain	certain	ADJ
brj-22966	271	13	softwood	softwood	NOUN
brj-22966	271	14	species	specie	NOUN
brj-22966	271	15	,	,	PUNCT
brj-22966	271	16	”	"	PUNCT
brj-22966	271	17	forests	forest	NOUN
brj-22966	271	18	14(6	14(6	NOUN
brj-22966	271	19	)	)	PUNCT
brj-22966	271	20	,	,	PUNCT
brj-22966	271	21	article	article	NOUN
brj-22966	271	22	1249	1249	NUM
brj-22966	271	23	.	.	PUNCT
brj-22966	272	1	doi	doi	NOUN
brj-22966	272	2	:	:	PUNCT
brj-22966	272	3	10.3390	10.3390	NUM
brj-22966	272	4	/	/	SYM
brj-22966	272	5	f14061249	f14061249	NUM
brj-22966	272	6	kim	kim	PROPN
brj-22966	272	7	,	,	PUNCT
brj-22966	272	8	t.	t.	PROPN
brj-22966	272	9	k.	k.	PROPN
brj-22966	272	10	,	,	PUNCT
brj-22966	272	11	hong	hong	PROPN
brj-22966	272	12	,	,	PUNCT
brj-22966	272	13	j.	j.	PROPN
brj-22966	272	14	h.	h.	PROPN
brj-22966	272	15	,	,	PUNCT
brj-22966	272	16	ryu	ryu	PROPN
brj-22966	272	17	,	,	PUNCT
brj-22966	272	18	d.	d.	PROPN
brj-22966	272	19	,	,	PUNCT
brj-22966	272	20	kim	kim	PROPN
brj-22966	272	21	,	,	PUNCT
brj-22966	272	22	s.	s.	PROPN
brj-22966	272	23	k.	k.	PROPN
brj-22966	272	24	,	,	PUNCT
brj-22966	272	25	byeon	byeon	PROPN
brj-22966	272	26	,	,	PUNCT
brj-22966	272	27	s.	s.	PROPN
brj-22966	272	28	y.	y.	PROPN
brj-22966	272	29	,	,	PUNCT
brj-22966	272	30	huh	huh	PROPN
brj-22966	272	31	,	,	PUNCT
brj-22966	272	32	w.	w.	PROPN
brj-22966	272	33	j.	j.	PROPN
brj-22966	272	34	,	,	PUNCT
brj-22966	272	35	kim	kim	PROPN
brj-22966	272	36	,	,	PUNCT
brj-22966	272	37	k.	k.	PROPN
brj-22966	272	38	h.	h.	PROPN
brj-22966	272	39	,	,	PUNCT
brj-22966	272	40	baek	baek	PROPN
brj-22966	272	41	,	,	PUNCT
brj-22966	272	42	g.	g.	PROPN
brj-22966	272	43	h.	h.	PROPN
brj-22966	272	44	,	,	PUNCT
brj-22966	272	45	and	and	CCONJ
brj-22966	272	46	kim	kim	PROPN
brj-22966	272	47	,	,	PUNCT
brj-22966	272	48	h.	h.	PROPN
brj-22966	272	49	s.	s.	PROPN
brj-22966	272	50	(	(	PUNCT
brj-22966	272	51	2022	2022	NUM
brj-22966	272	52	)	)	PUNCT
brj-22966	272	53	.	.	PUNCT
brj-22966	273	1	“	"	PUNCT
brj-22966	273	2	identifying	identify	VERB
brj-22966	273	3	and	and	CCONJ
brj-22966	273	4	extracting	extract	VERB
brj-22966	273	5	bark	bark	NOUN
brj-22966	273	6	key	key	ADJ
brj-22966	273	7	features	feature	NOUN
brj-22966	273	8	of	of	ADP
brj-22966	273	9	42	42	NUM
brj-22966	273	10	tree	tree	NOUN
brj-22966	273	11	species	specie	NOUN
brj-22966	273	12	using	use	VERB
brj-22966	273	13	convolutional	convolutional	ADJ
brj-22966	273	14	neural	neural	ADJ
brj-22966	273	15	networks	network	NOUN
brj-22966	273	16	and	and	CCONJ
brj-22966	273	17	class	class	NOUN
brj-22966	273	18	activation	activation	NOUN
brj-22966	273	19	mapping	mapping	NOUN
brj-22966	273	20	,	,	PUNCT
brj-22966	273	21	”	"	PUNCT
brj-22966	273	22	scientific	scientific	ADJ
brj-22966	273	23	report	report	NOUN
brj-22966	273	24	12(1	12(1	NUM
brj-22966	273	25	)	)	PUNCT
brj-22966	273	26	,	,	PUNCT
brj-22966	273	27	article	article	NOUN
brj-22966	273	28	4772	4772	NUM
brj-22966	273	29	.	.	PUNCT
brj-22966	274	1	doi	doi	NOUN
brj-22966	274	2	:	:	PUNCT
brj-22966	274	3	10.1038	10.1038	NUM
brj-22966	274	4	/	/	SYM
brj-22966	274	5	s41598	s41598	NOUN
brj-22966	274	6	-	-	PUNCT
brj-22966	274	7	022	022	NOUN
brj-22966	274	8	-	-	PUNCT
brj-22966	274	9	08571	08571	NUM
brj-22966	274	10	-	-	SYM
brj-22966	274	11	9	9	NUM
brj-22966	274	12	kwon	kwon	NOUN
brj-22966	274	13	,	,	PUNCT
brj-22966	274	14	o.	o.	PROPN
brj-22966	274	15	k.	k.	PROPN
brj-22966	274	16	,	,	PUNCT
brj-22966	274	17	lee	lee	PROPN
brj-22966	274	18	,	,	PUNCT
brj-22966	274	19	h.	h.	PROPN
brj-22966	274	20	g.	g.	PROPN
brj-22966	274	21	,	,	PUNCT
brj-22966	274	22	lee	lee	PROPN
brj-22966	274	23	,	,	PUNCT
brj-22966	274	24	m.	m.	PROPN
brj-22966	274	25	r.	r.	PROPN
brj-22966	274	26	,	,	PUNCT
brj-22966	274	27	jang	jang	PROPN
brj-22966	274	28	,	,	PUNCT
brj-22966	274	29	s.	s.	PROPN
brj-22966	274	30	j.	j.	PROPN
brj-22966	274	31	,	,	PUNCT
brj-22966	274	32	yang	yang	PROPN
brj-22966	274	33	,	,	PUNCT
brj-22966	274	34	s.	s.	PROPN
brj-22966	274	35	y.	y.	PROPN
brj-22966	274	36	,	,	PUNCT
brj-22966	274	37	park	park	NOUN
brj-22966	274	38	,	,	PUNCT
brj-22966	274	39	s.	s.	PROPN
brj-22966	274	40	y.	y.	PROPN
brj-22966	274	41	,	,	PUNCT
brj-22966	274	42	choi	choi	NOUN
brj-22966	274	43	,	,	PUNCT
brj-22966	274	44	i.	i.	PROPN
brj-22966	274	45	g.	g.	PROPN
brj-22966	274	46	,	,	PUNCT
brj-22966	274	47	and	and	CCONJ
brj-22966	274	48	yeo	yeo	PROPN
brj-22966	274	49	,	,	PUNCT
brj-22966	274	50	h.	h.	PROPN
brj-22966	274	51	m.	m.	PROPN
brj-22966	274	52	(	(	PUNCT
brj-22966	274	53	2017	2017	NUM
brj-22966	274	54	)	)	PUNCT
brj-22966	274	55	.	.	PUNCT
brj-22966	275	1	“	"	PUNCT
brj-22966	275	2	automatic	automatic	ADJ
brj-22966	275	3	wood	wood	NOUN
brj-22966	275	4	species	specie	NOUN
brj-22966	275	5	identification	identification	NOUN
brj-22966	275	6	of	of	ADP
brj-22966	275	7	korean	korean	ADJ
brj-22966	275	8	softwood	softwood	NOUN
brj-22966	275	9	based	base	VERB
brj-22966	275	10	on	on	ADP
brj-22966	275	11	convolutional	convolutional	ADJ
brj-22966	275	12	neural	neural	ADJ
brj-22966	275	13	networks	network	NOUN
brj-22966	275	14	,	,	PUNCT
brj-22966	275	15	”	"	PUNCT
brj-22966	275	16	journal	journal	NOUN
brj-22966	275	17	of	of	ADP
brj-22966	275	18	the	the	DET
brj-22966	275	19	korean	korean	ADJ
brj-22966	275	20	wood	wood	NOUN
brj-22966	275	21	science	science	NOUN
brj-22966	275	22	and	and	CCONJ
brj-22966	275	23	technology	technology	NOUN
brj-22966	275	24	45(6	45(6	NOUN
brj-22966	275	25	)	)	PUNCT
brj-22966	275	26	,	,	PUNCT
brj-22966	275	27	797	797	NUM
brj-22966	275	28	-	-	SYM
brj-22966	275	29	808	808	NUM
brj-22966	275	30	.	.	PUNCT
brj-22966	275	31	doi	doi	NOUN
brj-22966	275	32	:	:	PUNCT
brj-22966	275	33	10.5658	10.5658	NUM
brj-22966	275	34	/	/	SYM
brj-22966	275	35	wood.2017.45.6.797	wood.2017.45.6.797	NOUN
brj-22966	275	36	.	.	PUNCT
brj-22966	276	1	kwon	kwon	PROPN
brj-22966	276	2	,	,	PUNCT
brj-22966	276	3	o.	o.	PROPN
brj-22966	276	4	k.	k.	PROPN
brj-22966	276	5	,	,	PUNCT
brj-22966	276	6	lee	lee	PROPN
brj-22966	276	7	,	,	PUNCT
brj-22966	276	8	h.	h.	PROPN
brj-22966	276	9	g.	g.	PROPN
brj-22966	276	10	,	,	PUNCT
brj-22966	276	11	yang	yang	PROPN
brj-22966	276	12	,	,	PUNCT
brj-22966	276	13	s.	s.	PROPN
brj-22966	276	14	y.	y.	PROPN
brj-22966	276	15	,	,	PUNCT
brj-22966	276	16	kim	kim	PROPN
brj-22966	276	17	,	,	PUNCT
brj-22966	276	18	h.	h.	PROPN
brj-22966	276	19	b.	b.	PROPN
brj-22966	276	20	,	,	PUNCT
brj-22966	276	21	park	park	PROPN
brj-22966	276	22	,	,	PUNCT
brj-22966	276	23	s.	s.	PROPN
brj-22966	276	24	y.	y.	PROPN
brj-22966	276	25	,	,	PUNCT
brj-22966	276	26	choi	choi	NOUN
brj-22966	276	27	,	,	PUNCT
brj-22966	276	28	i.	i.	PROPN
brj-22966	276	29	g.	g.	PROPN
brj-22966	276	30	,	,	PUNCT
brj-22966	276	31	and	and	CCONJ
brj-22966	276	32	yeo	yeo	PROPN
brj-22966	276	33	,	,	PUNCT
brj-22966	276	34	h.	h.	PROPN
brj-22966	276	35	m.	m.	PROPN
brj-22966	276	36	(	(	PUNCT
brj-22966	276	37	2019	2019	NUM
brj-22966	276	38	)	)	PUNCT
brj-22966	276	39	.	.	PUNCT
brj-22966	277	1	“	"	PUNCT
brj-22966	277	2	performance	performance	NOUN
brj-22966	277	3	enhancement	enhancement	NOUN
brj-22966	277	4	of	of	ADP
brj-22966	277	5	automatic	automatic	ADJ
brj-22966	277	6	wood	wood	NOUN
brj-22966	277	7	classification	classification	NOUN
brj-22966	277	8	of	of	ADP
brj-22966	277	9	korean	korean	ADJ
brj-22966	277	10	softwood	softwood	NOUN
brj-22966	277	11	by	by	ADP
brj-22966	277	12	ensembles	ensemble	NOUN
brj-22966	277	13	of	of	ADP
brj-22966	277	14	convolutional	convolutional	ADJ
brj-22966	277	15	neural	neural	ADJ
brj-22966	277	16	networks	network	NOUN
brj-22966	277	17	,	,	PUNCT
brj-22966	277	18	”	"	PUNCT
brj-22966	277	19	journal	journal	NOUN
brj-22966	277	20	of	of	ADP
brj-22966	277	21	the	the	DET
brj-22966	277	22	korean	korean	ADJ
brj-22966	277	23	wood	wood	NOUN
brj-22966	277	24	science	science	NOUN
brj-22966	277	25	and	and	CCONJ
brj-22966	277	26	technology	technology	NOUN
brj-22966	277	27	47(3	47(3	NOUN
brj-22966	277	28	)	)	PUNCT
brj-22966	277	29	,	,	PUNCT
brj-22966	277	30	265	265	NUM
brj-22966	277	31	-	-	SYM
brj-22966	277	32	276	276	NUM
brj-22966	277	33	.	.	PUNCT
brj-22966	278	1	doi	doi	NOUN
brj-22966	278	2	:	:	PUNCT
brj-22966	278	3	10.5658	10.5658	NUM
brj-22966	278	4	/	/	SYM
brj-22966	278	5	wood.2019.47.3.265	wood.2019.47.3.265	PROPN
brj-22966	278	6	loy	loy	PROPN
brj-22966	278	7	,	,	PUNCT
brj-22966	278	8	j.	j.	PROPN
brj-22966	278	9	(	(	PUNCT
brj-22966	278	10	2020	2020	NUM
brj-22966	278	11	)	)	PUNCT
brj-22966	278	12	.	.	PUNCT
brj-22966	279	1	neural	neural	ADJ
brj-22966	279	2	network	network	NOUN
brj-22966	279	3	projects	project	NOUN
brj-22966	279	4	with	with	ADP
brj-22966	279	5	python	python	PROPN
brj-22966	279	6	,	,	PUNCT
brj-22966	279	7	gilbut	gilbut	NOUN
brj-22966	279	8	publishing	publishing	NOUN
brj-22966	279	9	,	,	PUNCT
brj-22966	279	10	seoul	seoul	PROPN
brj-22966	279	11	,	,	PUNCT
brj-22966	279	12	republic	republic	NOUN
brj-22966	279	13	of	of	ADP
brj-22966	279	14	korea	korea	PROPN
brj-22966	279	15	.	.	PUNCT
brj-22966	280	1	oh	oh	INTJ
brj-22966	280	2	,	,	PUNCT
brj-22966	280	3	s.	s.	PROPN
brj-22966	280	4	h.	h.	PROPN
brj-22966	280	5	(	(	PUNCT
brj-22966	280	6	2021	2021	NUM
brj-22966	280	7	)	)	PUNCT
brj-22966	280	8	.	.	PUNCT
brj-22966	281	1	python	python	PROPN
brj-22966	281	2	deep	deep	ADJ
brj-22966	281	3	learning	learning	NOUN
brj-22966	281	4	machine	machine	NOUN
brj-22966	281	5	learning	learning	NOUN
brj-22966	281	6	,	,	PUNCT
brj-22966	281	7	information	information	NOUN
brj-22966	281	8	publishing	publishing	NOUN
brj-22966	281	9	group	group	NOUN
brj-22966	281	10	,	,	PUNCT
brj-22966	281	11	seoul	seoul	PROPN
brj-22966	281	12	,	,	PUNCT
brj-22966	281	13	republic	republic	NOUN
brj-22966	281	14	of	of	ADP
brj-22966	281	15	korea	korea	PROPN
brj-22966	281	16	.	.	PUNCT
brj-22966	282	1	prasetia	prasetia	PROPN
brj-22966	282	2	,	,	PUNCT
brj-22966	282	3	d.	d.	PROPN
brj-22966	282	4	,	,	PUNCT
brj-22966	282	5	purusatama	purusatama	PROPN
brj-22966	282	6	,	,	PUNCT
brj-22966	282	7	b.	b.	PROPN
brj-22966	282	8	d.	d.	PROPN
brj-22966	282	9	,	,	PUNCT
brj-22966	282	10	kim	kim	PROPN
brj-22966	282	11	,	,	PUNCT
brj-22966	282	12	j.	j.	PROPN
brj-22966	282	13	h.	h.	PROPN
brj-22966	282	14	,	,	PUNCT
brj-22966	282	15	jang	jang	PROPN
brj-22966	282	16	,	,	PUNCT
brj-22966	282	17	j.	j.	PROPN
brj-22966	282	18	h.	h.	PROPN
brj-22966	282	19	,	,	PUNCT
brj-22966	282	20	park	park	PROPN
brj-22966	282	21	,	,	PUNCT
brj-22966	282	22	s.	s.	PROPN
brj-22966	282	23	y.	y.	PROPN
brj-22966	282	24	,	,	PUNCT
brj-22966	282	25	and	and	CCONJ
brj-22966	282	26	kim	kim	PROPN
brj-22966	282	27	,	,	PUNCT
brj-22966	282	28	n.	n.	PROPN
brj-22966	282	29	h.	h.	PROPN
brj-22966	282	30	(	(	PUNCT
brj-22966	282	31	2022	2022	NUM
brj-22966	282	32	)	)	PUNCT
brj-22966	282	33	.	.	PUNCT
brj-22966	283	1	“	"	PUNCT
brj-22966	283	2	qualitative	qualitative	ADJ
brj-22966	283	3	anatomical	anatomical	ADJ
brj-22966	283	4	characteristics	characteristic	NOUN
brj-22966	283	5	of	of	ADP
brj-22966	283	6	the	the	DET
brj-22966	283	7	virgin	virgin	ADJ
brj-22966	283	8	cork	cork	NOUN
brj-22966	283	9	in	in	ADP
brj-22966	283	10	quercus	quercus	ADJ
brj-22966	283	11	variabilis	variabilis	NOUN
brj-22966	283	12	grown	grow	VERB
brj-22966	283	13	in	in	ADP
brj-22966	283	14	korea	korea	PROPN
brj-22966	283	15	,	,	PUNCT
brj-22966	283	16	”	"	PUNCT
brj-22966	283	17	bioresources	bioresource	NOUN
brj-22966	283	18	18(1	18(1	NOUN
brj-22966	283	19	)	)	PUNCT
brj-22966	283	20	,	,	PUNCT
brj-22966	283	21	884	884	NUM
brj-22966	283	22	-	-	SYM
brj-22966	283	23	898	898	NUM
brj-22966	283	24	.	.	PUNCT
brj-22966	284	1	doi	doi	NOUN
brj-22966	284	2	:	:	PUNCT
brj-22966	284	3	10.15376	10.15376	NUM
brj-22966	284	4	/	/	SYM
brj-22966	284	5	biores.18.1.884	biores.18.1.884	NUM
brj-22966	284	6	-	-	PUNCT
brj-22966	284	7	898	898	NUM
brj-22966	284	8	peer	peer	NOUN
brj-22966	284	9	-	-	PUNCT
brj-22966	284	10	reviewed	review	VERB
brj-22966	284	11	article	article	NOUN
brj-22966	284	12	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-22966	284	13	kim	kim	PROPN
brj-22966	284	14	et	et	PROPN
brj-22966	284	15	al	al	PROPN
brj-22966	284	16	.	.	PROPN
brj-22966	285	1	(	(	PUNCT
brj-22966	285	2	2024	2024	NUM
brj-22966	285	3	)	)	PUNCT
brj-22966	285	4	.	.	PUNCT
brj-22966	286	1	“	"	PUNCT
brj-22966	286	2	convolutional	convolutional	ADJ
brj-22966	286	3	neural	neural	ADJ
brj-22966	286	4	network	network	NOUN
brj-22966	286	5	,	,	PUNCT
brj-22966	286	6	”	"	PUNCT
brj-22966	286	7	bioresources	bioresource	NOUN
brj-22966	286	8	19(1	19(1	NUM
brj-22966	286	9	)	)	PUNCT
brj-22966	286	10	,	,	PUNCT
brj-22966	286	11	510	510	NUM
brj-22966	286	12	-	-	SYM
brj-22966	286	13	524	524	NUM
brj-22966	286	14	.	.	PUNCT
brj-22966	287	1	524	524	NUM
brj-22966	287	2	savero	savero	NOUN
brj-22966	287	3	,	,	PUNCT
brj-22966	287	4	a.	a.	NOUN
brj-22966	287	5	m.	m.	NOUN
brj-22966	287	6	,	,	PUNCT
brj-22966	287	7	kim	kim	PROPN
brj-22966	287	8	,	,	PUNCT
brj-22966	287	9	j.	j.	PROPN
brj-22966	287	10	h.	h.	PROPN
brj-22966	287	11	,	,	PUNCT
brj-22966	287	12	purusatama	purusatama	PROPN
brj-22966	287	13	,	,	PUNCT
brj-22966	287	14	b.	b.	PROPN
brj-22966	287	15	d.	d.	PROPN
brj-22966	287	16	,	,	PUNCT
brj-22966	287	17	prasetia	prasetia	PROPN
brj-22966	287	18	,	,	PUNCT
brj-22966	287	19	d.	d.	PROPN
brj-22966	287	20	,	,	PUNCT
brj-22966	287	21	park	park	PROPN
brj-22966	287	22	,	,	PUNCT
brj-22966	287	23	s.	s.	PROPN
brj-22966	287	24	h.	h.	PROPN
brj-22966	287	25	,	,	PUNCT
brj-22966	287	26	and	and	CCONJ
brj-22966	287	27	kim	kim	PROPN
brj-22966	287	28	,	,	PUNCT
brj-22966	287	29	n.	n.	PROPN
brj-22966	287	30	h.	h.	PROPN
brj-22966	287	31	(	(	PUNCT
brj-22966	287	32	2022	2022	NUM
brj-22966	287	33	)	)	PUNCT
brj-22966	287	34	.	.	PUNCT
brj-22966	288	1	“	"	PUNCT
brj-22966	288	2	a	a	DET
brj-22966	288	3	comparative	comparative	ADJ
brj-22966	288	4	study	study	NOUN
brj-22966	288	5	on	on	ADP
brj-22966	288	6	the	the	DET
brj-22966	288	7	anatomical	anatomical	ADJ
brj-22966	288	8	characteristics	characteristic	NOUN
brj-22966	288	9	of	of	ADP
brj-22966	288	10	acacia	acacia	NOUN
brj-22966	288	11	mangium	mangium	NOUN
brj-22966	288	12	and	and	CCONJ
brj-22966	288	13	acacia	acacia	NOUN
brj-22966	288	14	hybrid	hybrid	NOUN
brj-22966	288	15	grown	grow	VERB
brj-22966	288	16	in	in	ADP
brj-22966	288	17	vietnam	vietnam	PROPN
brj-22966	288	18	,	,	PUNCT
brj-22966	288	19	”	"	PUNCT
brj-22966	288	20	forests	forest	NOUN
brj-22966	288	21	13(10	13(10	NUM
brj-22966	288	22	)	)	PUNCT
brj-22966	288	23	,	,	PUNCT
brj-22966	288	24	1700	1700	NUM
brj-22966	288	25	.	.	PUNCT
brj-22966	289	1	doi	doi	NOUN
brj-22966	289	2	:	:	PUNCT
brj-22966	289	3	10.3390	10.3390	NUM
brj-22966	289	4	/	/	SYM
brj-22966	289	5	f13101700	f13101700	NUM
brj-22966	289	6	savero	savero	NOUN
brj-22966	289	7	,	,	PUNCT
brj-22966	289	8	a.	a.	NOUN
brj-22966	289	9	m.	m.	NOUN
brj-22966	289	10	,	,	PUNCT
brj-22966	289	11	kim	kim	PROPN
brj-22966	289	12	,	,	PUNCT
brj-22966	289	13	j.	j.	PROPN
brj-22966	289	14	h.	h.	PROPN
brj-22966	289	15	,	,	PUNCT
brj-22966	289	16	purusatama	purusatama	PROPN
brj-22966	289	17	,	,	PUNCT
brj-22966	289	18	b.	b.	PROPN
brj-22966	289	19	d.	d.	PROPN
brj-22966	289	20	,	,	PUNCT
brj-22966	289	21	prasetia	prasetia	PROPN
brj-22966	289	22	,	,	PUNCT
brj-22966	289	23	d.	d.	PROPN
brj-22966	289	24	,	,	PUNCT
brj-22966	289	25	park	park	PROPN
brj-22966	289	26	,	,	PUNCT
brj-22966	289	27	s.	s.	PROPN
brj-22966	289	28	h.	h.	PROPN
brj-22966	289	29	,	,	PUNCT
brj-22966	289	30	van	van	PROPN
brj-22966	289	31	duong	duong	PROPN
brj-22966	289	32	,	,	PUNCT
brj-22966	289	33	d.	d.	PROPN
brj-22966	289	34	,	,	PUNCT
brj-22966	289	35	and	and	CCONJ
brj-22966	289	36	kim	kim	PROPN
brj-22966	289	37	,	,	PUNCT
brj-22966	289	38	n.	n.	PROPN
brj-22966	289	39	h.	h.	PROPN
brj-22966	289	40	(	(	PUNCT
brj-22966	289	41	2023	2023	NUM
brj-22966	289	42	)	)	PUNCT
brj-22966	289	43	.	.	PUNCT
brj-22966	290	1	“	"	PUNCT
brj-22966	290	2	characterization	characterization	NOUN
brj-22966	290	3	of	of	ADP
brj-22966	290	4	anatomical	anatomical	ADJ
brj-22966	290	5	and	and	CCONJ
brj-22966	290	6	non	non	ADJ
brj-22966	290	7	-	-	ADJ
brj-22966	290	8	anatomical	anatomical	ADJ
brj-22966	290	9	properties	property	NOUN
brj-22966	290	10	for	for	ADP
brj-22966	290	11	the	the	DET
brj-22966	290	12	identification	identification	NOUN
brj-22966	290	13	of	of	ADP
brj-22966	290	14	six	six	NUM
brj-22966	290	15	commercial	commercial	ADJ
brj-22966	290	16	wood	wood	NOUN
brj-22966	290	17	species	specie	NOUN
brj-22966	290	18	from	from	ADP
brj-22966	290	19	vietnamese	vietnamese	ADJ
brj-22966	290	20	plantation	plantation	NOUN
brj-22966	290	21	forests	forest	NOUN
brj-22966	290	22	,	,	PUNCT
brj-22966	290	23	”	"	PUNCT
brj-22966	290	24	forests	forest	VERB
brj-22966	290	25	14(3	14(3	NUM
brj-22966	290	26	)	)	PUNCT
brj-22966	290	27	,	,	PUNCT
brj-22966	290	28	article	article	NOUN
brj-22966	290	29	496	496	NUM
brj-22966	290	30	.	.	PUNCT
brj-22966	291	1	doi	doi	NOUN
brj-22966	291	2	:	:	PUNCT
brj-22966	291	3	10.3390	10.3390	NUM
brj-22966	291	4	/	/	SYM
brj-22966	291	5	f14030496	f14030496	NOUN
brj-22966	291	6	shorten	shorten	ADJ
brj-22966	291	7	,	,	PUNCT
brj-22966	291	8	c.	c.	NOUN
brj-22966	291	9	,	,	PUNCT
brj-22966	291	10	and	and	CCONJ
brj-22966	291	11	khoshgoftaar	khoshgoftaar	NOUN
brj-22966	291	12	,	,	PUNCT
brj-22966	291	13	t.	t.	NOUN
brj-22966	291	14	m.	m.	NOUN
brj-22966	291	15	(	(	PUNCT
brj-22966	291	16	2019	2019	NUM
brj-22966	291	17	)	)	PUNCT
brj-22966	291	18	.	.	PUNCT
brj-22966	292	1	“	"	PUNCT
brj-22966	292	2	a	a	DET
brj-22966	292	3	survey	survey	NOUN
brj-22966	292	4	on	on	ADP
brj-22966	292	5	image	image	NOUN
brj-22966	292	6	data	datum	NOUN
brj-22966	292	7	augmentation	augmentation	NOUN
brj-22966	292	8	for	for	ADP
brj-22966	292	9	deep	deep	ADJ
brj-22966	292	10	learning	learning	NOUN
brj-22966	292	11	,	,	PUNCT
brj-22966	292	12	”	"	PUNCT
brj-22966	292	13	journal	journal	NOUN
brj-22966	292	14	of	of	ADP
brj-22966	292	15	big	big	ADJ
brj-22966	292	16	data	datum	NOUN
brj-22966	292	17	6(1	6(1	NUM
brj-22966	292	18	)	)	PUNCT
brj-22966	292	19	,	,	PUNCT
brj-22966	292	20	1	1	NUM
brj-22966	292	21	-	-	SYM
brj-22966	292	22	48	48	NUM
brj-22966	292	23	.	.	PUNCT
brj-22966	293	1	doi	doi	NOUN
brj-22966	293	2	:	:	PUNCT
brj-22966	293	3	10.1186	10.1186	NUM
brj-22966	293	4	/	/	SYM
brj-22966	293	5	s40537	s40537	NOUN
brj-22966	293	6	-	-	PUNCT
brj-22966	293	7	019	019	NUM
brj-22966	293	8	-	-	PUNCT
brj-22966	293	9	0197	0197	NUM
brj-22966	293	10	-	-	SYM
brj-22966	293	11	0	0	NUM
brj-22966	293	12	simonyan	simonyan	ADJ
brj-22966	293	13	,	,	PUNCT
brj-22966	293	14	k.	k.	PROPN
brj-22966	293	15	,	,	PUNCT
brj-22966	293	16	and	and	CCONJ
brj-22966	293	17	zisserman	zisserman	NOUN
brj-22966	293	18	,	,	PUNCT
brj-22966	293	19	a.	a.	NOUN
brj-22966	293	20	(	(	PUNCT
brj-22966	293	21	2015	2015	NUM
brj-22966	293	22	)	)	PUNCT
brj-22966	293	23	.	.	PUNCT
brj-22966	294	1	“	"	PUNCT
brj-22966	294	2	very	very	ADV
brj-22966	294	3	deep	deep	ADJ
brj-22966	294	4	convolutional	convolutional	ADJ
brj-22966	294	5	for	for	ADP
brj-22966	294	6	large	large	ADJ
brj-22966	294	7	-	-	PUNCT
brj-22966	294	8	scale	scale	NOUN
brj-22966	294	9	image	image	NOUN
brj-22966	294	10	recognition	recognition	NOUN
brj-22966	294	11	,	,	PUNCT
brj-22966	294	12	”	"	PUNCT
brj-22966	294	13	in	in	ADP
brj-22966	294	14	:	:	PUNCT
brj-22966	294	15	proceeding	proceeding	NOUN
brj-22966	294	16	of	of	ADP
brj-22966	294	17	the	the	DET
brj-22966	294	18	international	international	ADJ
brj-22966	294	19	conference	conference	NOUN
brj-22966	294	20	on	on	ADP
brj-22966	294	21	learning	learn	VERB
brj-22966	294	22	representations	representation	NOUN
brj-22966	294	23	(	(	PUNCT
brj-22966	294	24	iclr	iclr	NOUN
brj-22966	294	25	)	)	PUNCT
brj-22966	294	26	2015	2015	NUM
brj-22966	294	27	,	,	PUNCT
brj-22966	294	28	san	san	PROPN
brj-22966	294	29	diego	diego	PROPN
brj-22966	294	30	,	,	PUNCT
brj-22966	294	31	usa	usa	PROPN
brj-22966	294	32	,	,	PUNCT
brj-22966	294	33	pp	pp	NOUN
brj-22966	294	34	.	.	PUNCT
brj-22966	295	1	1	1	NUM
brj-22966	295	2	-	-	SYM
brj-22966	295	3	14	14	NUM
brj-22966	295	4	.	.	PUNCT
brj-22966	296	1	szegedy	szegedy	PROPN
brj-22966	296	2	,	,	PUNCT
brj-22966	296	3	c.	c.	PROPN
brj-22966	296	4	,	,	PUNCT
brj-22966	296	5	liu	liu	PROPN
brj-22966	296	6	,	,	PUNCT
brj-22966	296	7	w.	w.	PROPN
brj-22966	296	8	,	,	PUNCT
brj-22966	296	9	jia	jia	PROPN
brj-22966	296	10	,	,	PUNCT
brj-22966	296	11	y.	y.	PROPN
brj-22966	296	12	,	,	PUNCT
brj-22966	296	13	sermanet	sermanet	NOUN
brj-22966	296	14	,	,	PUNCT
brj-22966	296	15	p.	p.	PROPN
brj-22966	296	16	,	,	PUNCT
brj-22966	296	17	reed	reed	PROPN
brj-22966	296	18	,	,	PUNCT
brj-22966	296	19	s.	s.	PROPN
brj-22966	296	20	,	,	PUNCT
brj-22966	296	21	anguelov	anguelov	PROPN
brj-22966	296	22	,	,	PUNCT
brj-22966	296	23	d.	d.	PROPN
brj-22966	296	24	,	,	PUNCT
brj-22966	296	25	erhan	erhan	PROPN
brj-22966	296	26	,	,	PUNCT
brj-22966	296	27	d.	d.	PROPN
brj-22966	296	28	,	,	PUNCT
brj-22966	296	29	vanhoucke	vanhoucke	PROPN
brj-22966	296	30	,	,	PUNCT
brj-22966	296	31	v.	v.	ADV
brj-22966	296	32	,	,	PUNCT
brj-22966	296	33	and	and	CCONJ
brj-22966	296	34	rabinovich	rabinovich	NOUN
brj-22966	296	35	,	,	PUNCT
brj-22966	296	36	a.	a.	NOUN
brj-22966	296	37	(	(	PUNCT
brj-22966	296	38	2015	2015	NUM
brj-22966	296	39	)	)	PUNCT
brj-22966	296	40	.	.	PUNCT
brj-22966	297	1	“	"	PUNCT
brj-22966	297	2	going	go	VERB
brj-22966	297	3	deeper	deeply	ADV
brj-22966	297	4	with	with	ADP
brj-22966	297	5	convolutions	convolution	NOUN
brj-22966	297	6	,	,	PUNCT
brj-22966	297	7	”	"	PUNCT
brj-22966	297	8	in	in	ADP
brj-22966	297	9	:	:	PUNCT
brj-22966	297	10	proceeding	proceed	VERB
brj-22966	297	11	2015	2015	NUM
brj-22966	297	12	ieee	ieee	NOUN
brj-22966	297	13	conference	conference	NOUN
brj-22966	297	14	on	on	ADP
brj-22966	297	15	computer	computer	NOUN
brj-22966	297	16	vision	vision	NOUN
brj-22966	297	17	and	and	CCONJ
brj-22966	297	18	pattern	pattern	NOUN
brj-22966	297	19	recognition	recognition	NOUN
brj-22966	297	20	(	(	PUNCT
brj-22966	297	21	cvpr	cvpr	NOUN
brj-22966	297	22	)	)	PUNCT
brj-22966	297	23	,	,	PUNCT
brj-22966	297	24	boston	boston	PROPN
brj-22966	297	25	,	,	PUNCT
brj-22966	297	26	usa	usa	PROPN
brj-22966	297	27	,	,	PUNCT
brj-22966	297	28	pp	pp	NOUN
brj-22966	297	29	.	.	PUNCT
brj-22966	298	1	1	1	NUM
brj-22966	298	2	-	-	SYM
brj-22966	298	3	9	9	NUM
brj-22966	298	4	.	.	PUNCT
brj-22966	298	5	tou	tou	PROPN
brj-22966	298	6	,	,	PUNCT
brj-22966	298	7	j.	j.	PROPN
brj-22966	298	8	y.	y.	PROPN
brj-22966	298	9	,	,	PUNCT
brj-22966	298	10	lau	lau	PROPN
brj-22966	298	11	,	,	PUNCT
brj-22966	298	12	p.	p.	PROPN
brj-22966	298	13	y.	y.	PROPN
brj-22966	298	14	,	,	PUNCT
brj-22966	298	15	and	and	CCONJ
brj-22966	298	16	tay	tay	NOUN
brj-22966	298	17	,	,	PUNCT
brj-22966	298	18	y.	y.	PROPN
brj-22966	298	19	h.	h.	PROPN
brj-22966	298	20	(	(	PUNCT
brj-22966	298	21	2007	2007	NUM
brj-22966	298	22	)	)	PUNCT
brj-22966	298	23	.	.	PUNCT
brj-22966	299	1	“	"	PUNCT
brj-22966	299	2	computer	computer	NOUN
brj-22966	299	3	vision	vision	NOUN
brj-22966	299	4	-	-	PUNCT
brj-22966	299	5	based	base	VERB
brj-22966	299	6	wood	wood	NOUN
brj-22966	299	7	recognition	recognition	NOUN
brj-22966	299	8	system	system	NOUN
brj-22966	299	9	,	,	PUNCT
brj-22966	299	10	”	"	PUNCT
brj-22966	299	11	in	in	ADP
brj-22966	299	12	:	:	PUNCT
brj-22966	299	13	proceedings	proceeding	NOUN
brj-22966	299	14	of	of	ADP
brj-22966	299	15	the	the	DET
brj-22966	299	16	international	international	ADJ
brj-22966	299	17	workshop	workshop	NOUN
brj-22966	299	18	on	on	ADP
brj-22966	299	19	advanced	advanced	ADJ
brj-22966	299	20	image	image	NOUN
brj-22966	299	21	technology	technology	NOUN
brj-22966	299	22	,	,	PUNCT
brj-22966	299	23	bangkok	bangkok	PROPN
brj-22966	299	24	,	,	PUNCT
brj-22966	299	25	thailand	thailand	PROPN
brj-22966	299	26	,	,	PUNCT
brj-22966	299	27	pp	pp	ADJ
brj-22966	299	28	.	.	PUNCT
brj-22966	300	1	1	1	NUM
brj-22966	300	2	-	-	SYM
brj-22966	300	3	6	6	NUM
brj-22966	300	4	.	.	PUNCT
brj-22966	300	5	united	united	PROPN
brj-22966	300	6	nations	nations	PROPN
brj-22966	300	7	economic	economic	PROPN
brj-22966	300	8	commission	commission	PROPN
brj-22966	300	9	for	for	ADP
brj-22966	300	10	europe	europe	PROPN
brj-22966	300	11	(	(	PUNCT
brj-22966	300	12	2007	2007	NUM
brj-22966	300	13	)	)	PUNCT
brj-22966	300	14	.	.	PUNCT
brj-22966	301	1	wood	wood	NOUN
brj-22966	301	2	resources	resource	NOUN
brj-22966	301	3	availability	availability	NOUN
brj-22966	301	4	and	and	CCONJ
brj-22966	301	5	demands	demand	VERB
brj-22966	301	6	implications	implication	NOUN
brj-22966	301	7	of	of	ADP
brj-22966	301	8	renewable	renewable	ADJ
brj-22966	301	9	energy	energy	NOUN
brj-22966	301	10	policies	policy	NOUN
brj-22966	301	11	,	,	PUNCT
brj-22966	301	12	united	united	PROPN
brj-22966	301	13	nations	nations	PROPN
brj-22966	301	14	economic	economic	PROPN
brj-22966	301	15	commission	commission	PROPN
brj-22966	301	16	for	for	ADP
brj-22966	301	17	europe	europe	PROPN
brj-22966	301	18	,	,	PUNCT
brj-22966	301	19	geneva	geneva	PROPN
brj-22966	301	20	,	,	PUNCT
brj-22966	301	21	switzerland	switzerland	PROPN
brj-22966	301	22	.	.	PUNCT
brj-22966	301	23	wheeler	wheeler	NOUN
brj-22966	301	24	,	,	PUNCT
brj-22966	301	25	e.	e.	PROPN
brj-22966	301	26	a.	a.	PROPN
brj-22966	301	27	,	,	PUNCT
brj-22966	301	28	and	and	CCONJ
brj-22966	301	29	baas	baas	NOUN
brj-22966	301	30	,	,	PUNCT
brj-22966	301	31	p.	p.	NOUN
brj-22966	301	32	(	(	PUNCT
brj-22966	301	33	1998	1998	NUM
brj-22966	301	34	)	)	PUNCT
brj-22966	301	35	.	.	PUNCT
brj-22966	302	1	“	"	PUNCT
brj-22966	302	2	wood	wood	NOUN
brj-22966	302	3	identification	identification	NOUN
brj-22966	302	4	–	–	PUNCT
brj-22966	302	5	a	a	DET
brj-22966	302	6	review	review	NOUN
brj-22966	302	7	,	,	PUNCT
brj-22966	302	8	”	"	PUNCT
brj-22966	302	9	iawa	iawa	PROPN
brj-22966	302	10	journal	journal	PROPN
brj-22966	302	11	19(3	19(3	NUM
brj-22966	302	12	)	)	PUNCT
brj-22966	302	13	,	,	PUNCT
brj-22966	302	14	241	241	NUM
brj-22966	302	15	-	-	SYM
brj-22966	302	16	264	264	NUM
brj-22966	302	17	.	.	PUNCT
brj-22966	303	1	doi	doi	NOUN
brj-22966	303	2	:	:	PUNCT
brj-22966	303	3	10.1163/22941932	10.1163/22941932	NUM
brj-22966	303	4	-	-	SYM
brj-22966	303	5	90001528	90001528	NUM
brj-22966	303	6	wong	wong	PROPN
brj-22966	303	7	,	,	PUNCT
brj-22966	303	8	s.	s.	PROPN
brj-22966	303	9	c.	c.	PROPN
brj-22966	303	10	,	,	PUNCT
brj-22966	303	11	gatt	gatt	PROPN
brj-22966	303	12	,	,	PUNCT
brj-22966	303	13	a.	a.	NOUN
brj-22966	303	14	,	,	PUNCT
brj-22966	303	15	stamatescu	stamatescu	NOUN
brj-22966	303	16	,	,	PUNCT
brj-22966	303	17	v.	v.	ADV
brj-22966	303	18	,	,	PUNCT
brj-22966	303	19	and	and	CCONJ
brj-22966	303	20	mcdonnell	mcdonnell	PROPN
brj-22966	303	21	,	,	PUNCT
brj-22966	303	22	m.	m.	PROPN
brj-22966	303	23	d.	d.	PROPN
brj-22966	303	24	(	(	PUNCT
brj-22966	303	25	2016	2016	NUM
brj-22966	303	26	)	)	PUNCT
brj-22966	303	27	.	.	PUNCT
brj-22966	304	1	“	"	PUNCT
brj-22966	304	2	understanding	understand	VERB
brj-22966	304	3	data	datum	NOUN
brj-22966	304	4	augmentation	augmentation	NOUN
brj-22966	304	5	for	for	ADP
brj-22966	304	6	classification	classification	NOUN
brj-22966	304	7	:	:	PUNCT
brj-22966	304	8	when	when	SCONJ
brj-22966	304	9	to	to	PART
brj-22966	304	10	warp	warp	VERB
brj-22966	304	11	?	?	PUNCT
brj-22966	304	12	,	,	PUNCT
brj-22966	304	13	”	"	PUNCT
brj-22966	304	14	in	in	ADP
brj-22966	304	15	:	:	PUNCT
brj-22966	304	16	2016	2016	NUM
brj-22966	304	17	international	international	ADJ
brj-22966	304	18	conference	conference	NOUN
brj-22966	304	19	on	on	ADP
brj-22966	304	20	digital	digital	ADJ
brj-22966	304	21	image	image	NOUN
brj-22966	304	22	computing	computing	NOUN
brj-22966	304	23	,	,	PUNCT
brj-22966	304	24	gold	gold	NOUN
brj-22966	304	25	coast	coast	NOUN
brj-22966	304	26	,	,	PUNCT
brj-22966	304	27	australia	australia	PROPN
brj-22966	304	28	,	,	PUNCT
brj-22966	304	29	pp	pp	ADJ
brj-22966	304	30	.	.	PUNCT
brj-22966	305	1	1	1	NUM
brj-22966	305	2	-	-	SYM
brj-22966	305	3	6	6	NUM
brj-22966	305	4	.	.	PUNCT
brj-22966	305	5	yang	yang	PROPN
brj-22966	305	6	,	,	PUNCT
brj-22966	305	7	s.	s.	PROPN
brj-22966	305	8	y.	y.	PROPN
brj-22966	305	9	,	,	PUNCT
brj-22966	305	10	lee	lee	PROPN
brj-22966	305	11	,	,	PUNCT
brj-22966	305	12	h.	h.	PROPN
brj-22966	305	13	g.	g.	PROPN
brj-22966	305	14	,	,	PUNCT
brj-22966	305	15	park	park	NOUN
brj-22966	305	16	,	,	PUNCT
brj-22966	305	17	y.	y.	PROPN
brj-22966	305	18	g.	g.	PROPN
brj-22966	305	19	,	,	PUNCT
brj-22966	305	20	chung	chung	PROPN
brj-22966	305	21	,	,	PUNCT
brj-22966	305	22	h.	h.	PROPN
brj-22966	305	23	w.	w.	PROPN
brj-22966	305	24	,	,	PUNCT
brj-22966	305	25	kim	kim	PROPN
brj-22966	305	26	,	,	PUNCT
brj-22966	305	27	h.	h.	PROPN
brj-22966	305	28	b.	b.	PROPN
brj-22966	305	29	,	,	PUNCT
brj-22966	305	30	park	park	PROPN
brj-22966	305	31	,	,	PUNCT
brj-22966	305	32	s.	s.	PROPN
brj-22966	305	33	y.	y.	PROPN
brj-22966	305	34	,	,	PUNCT
brj-22966	305	35	choi	choi	NOUN
brj-22966	305	36	,	,	PUNCT
brj-22966	305	37	i.	i.	PROPN
brj-22966	305	38	g.	g.	PROPN
brj-22966	305	39	,	,	PUNCT
brj-22966	305	40	kwon	kwon	PROPN
brj-22966	305	41	,	,	PUNCT
brj-22966	305	42	o.	o.	PROPN
brj-22966	305	43	k.	k.	PROPN
brj-22966	305	44	,	,	PUNCT
brj-22966	305	45	and	and	CCONJ
brj-22966	305	46	yeo	yeo	PROPN
brj-22966	305	47	,	,	PUNCT
brj-22966	305	48	h.	h.	PROPN
brj-22966	305	49	m.	m.	PROPN
brj-22966	305	50	(	(	PUNCT
brj-22966	305	51	2019	2019	NUM
brj-22966	305	52	)	)	PUNCT
brj-22966	305	53	.	.	PUNCT
brj-22966	306	1	“	"	PUNCT
brj-22966	306	2	wood	wood	NOUN
brj-22966	306	3	species	species	NOUN
brj-22966	306	4	classification	classification	NOUN
brj-22966	306	5	utilizing	utilize	VERB
brj-22966	306	6	ensembles	ensemble	NOUN
brj-22966	306	7	of	of	ADP
brj-22966	306	8	convolutional	convolutional	ADJ
brj-22966	306	9	neural	neural	ADJ
brj-22966	306	10	networks	network	NOUN
brj-22966	306	11	established	establish	VERB
brj-22966	306	12	by	by	ADP
brj-22966	306	13	near	near	ADV
brj-22966	306	14	-	-	PUNCT
brj-22966	306	15	infrared	infrared	ADJ
brj-22966	306	16	spectra	spectra	NOUN
brj-22966	306	17	and	and	CCONJ
brj-22966	306	18	images	image	NOUN
brj-22966	306	19	acquired	acquire	VERB
brj-22966	306	20	from	from	ADP
brj-22966	306	21	korean	korean	ADJ
brj-22966	306	22	softwood	softwood	PROPN
brj-22966	306	23	lumber	lumber	PROPN
brj-22966	306	24	,	,	PUNCT
brj-22966	306	25	”	"	PUNCT
brj-22966	306	26	journal	journal	NOUN
brj-22966	306	27	of	of	ADP
brj-22966	306	28	the	the	DET
brj-22966	306	29	korean	korean	ADJ
brj-22966	306	30	wood	wood	NOUN
brj-22966	306	31	science	science	NOUN
brj-22966	306	32	and	and	CCONJ
brj-22966	306	33	technology	technology	NOUN
brj-22966	306	34	47(4	47(4	NOUN
brj-22966	306	35	)	)	PUNCT
brj-22966	306	36	,	,	PUNCT
brj-22966	306	37	385	385	NUM
brj-22966	306	38	-	-	SYM
brj-22966	306	39	392	392	NUM
brj-22966	306	40	.	.	PUNCT
brj-22966	307	1	doi	doi	NOUN
brj-22966	307	2	:	:	PUNCT
brj-22966	307	3	10.5658	10.5658	NUM
brj-22966	307	4	/	/	SYM
brj-22966	307	5	wood.2019.47.4.385	wood.2019.47.4.385	NOUN
brj-22966	307	6	zhao	zhao	PROPN
brj-22966	307	7	,	,	PUNCT
brj-22966	307	8	z.	z.	PROPN
brj-22966	307	9	,	,	PUNCT
brj-22966	307	10	yang	yang	PROPN
brj-22966	307	11	,	,	PUNCT
brj-22966	307	12	x.	x.	PROPN
brj-22966	307	13	,	,	PUNCT
brj-22966	307	14	ge	ge	PROPN
brj-22966	307	15	,	,	PUNCT
brj-22966	307	16	z.	z.	PROPN
brj-22966	307	17	,	,	PUNCT
brj-22966	307	18	guo	guo	PROPN
brj-22966	307	19	,	,	PUNCT
brj-22966	307	20	h.	h.	PROPN
brj-22966	307	21	,	,	PUNCT
brj-22966	307	22	and	and	CCONJ
brj-22966	307	23	zhou	zhou	PROPN
brj-22966	307	24	,	,	PUNCT
brj-22966	307	25	y.	y.	PROPN
brj-22966	307	26	(	(	PUNCT
brj-22966	307	27	2021	2021	NUM
brj-22966	307	28	)	)	PUNCT
brj-22966	307	29	.	.	PUNCT
brj-22966	308	1	“	"	PUNCT
brj-22966	308	2	wood	wood	NOUN
brj-22966	308	3	microscopic	microscopic	ADJ
brj-22966	308	4	image	image	NOUN
brj-22966	308	5	identification	identification	NOUN
brj-22966	308	6	method	method	NOUN
brj-22966	308	7	based	base	VERB
brj-22966	308	8	on	on	ADP
brj-22966	308	9	convolution	convolution	NOUN
brj-22966	308	10	neural	neural	ADJ
brj-22966	308	11	network	network	NOUN
brj-22966	308	12	,	,	PUNCT
brj-22966	308	13	”	"	PUNCT
brj-22966	308	14	bioresources	bioresource	NOUN
brj-22966	308	15	16(3	16(3	NUM
brj-22966	308	16	)	)	PUNCT
brj-22966	308	17	,	,	PUNCT
brj-22966	308	18	4986	4986	NUM
brj-22966	308	19	-	-	SYM
brj-22966	308	20	4999	4999	NUM
brj-22966	308	21	.	.	PUNCT
brj-22966	309	1	doi	doi	NOUN
brj-22966	309	2	:	:	PUNCT
brj-22966	309	3	10.15376	10.15376	NUM
brj-22966	309	4	/	/	SYM
brj-22966	309	5	biores.16.3.4986	biores.16.3.4986	PROPN
brj-22966	309	6	-	-	PUNCT
brj-22966	309	7	4999	4999	NUM
brj-22966	309	8	article	article	NOUN
brj-22966	309	9	submitted	submit	VERB
brj-22966	309	10	:	:	PUNCT
brj-22966	309	11	september	september	PROPN
brj-22966	309	12	12	12	NUM
brj-22966	309	13	,	,	PUNCT
brj-22966	309	14	2023	2023	NUM
brj-22966	309	15	;	;	PUNCT
brj-22966	309	16	peer	peer	NOUN
brj-22966	309	17	review	review	NOUN
brj-22966	309	18	completed	complete	VERB
brj-22966	309	19	:	:	PUNCT
brj-22966	309	20	november	november	PROPN
brj-22966	309	21	11	11	NUM
brj-22966	309	22	,	,	PUNCT
brj-22966	309	23	2023	2023	NUM
brj-22966	309	24	;	;	PUNCT
brj-22966	309	25	revised	revise	VERB
brj-22966	309	26	version	version	NOUN
brj-22966	309	27	received	receive	VERB
brj-22966	309	28	and	and	CCONJ
brj-22966	309	29	accepted	accept	VERB
brj-22966	309	30	:	:	PUNCT
brj-22966	309	31	november	november	PROPN
brj-22966	309	32	14	14	NUM
brj-22966	309	33	,	,	PUNCT
brj-22966	309	34	2023	2023	NUM
brj-22966	309	35	;	;	PUNCT
brj-22966	309	36	published	publish	VERB
brj-22966	309	37	:	:	PUNCT
brj-22966	309	38	november	november	PROPN
brj-22966	309	39	27	27	NUM
brj-22966	309	40	,	,	PUNCT
brj-22966	309	41	2023	2023	NUM
brj-22966	309	42	.	.	PUNCT
brj-22966	310	1	doi	doi	NOUN
brj-22966	310	2	:	:	PUNCT
brj-22966	310	3	10.15376	10.15376	NUM
brj-22966	310	4	/	/	SYM
brj-22966	310	5	biores.19.1.510	biores.19.1.510	NOUN
brj-22966	310	6	-	-	X
brj-22966	310	7	524	524	NUM