id	sid	tid	token	lemma	pos
brj-22232	1	1	peer	peer	NOUN
brj-22232	1	2	-	-	PUNCT
brj-22232	1	3	review	review	NOUN
brj-22232	1	4	article	article	NOUN
brj-22232	1	5	peer	peer	NOUN
brj-22232	1	6	-	-	PUNCT
brj-22232	1	7	reviewed	review	VERB
brj-22232	1	8	article	article	NOUN
brj-22232	1	9	bioresources.com	bioresources.com	X
brj-22232	1	10	li	li	PROPN
brj-22232	1	11	et	et	PROPN
brj-22232	1	12	al	al	PROPN
brj-22232	1	13	.	.	PROPN
brj-22232	1	14	(	(	PUNCT
brj-22232	1	15	2023	2023	NUM
brj-22232	1	16	)	)	PUNCT
brj-22232	1	17	.	.	PUNCT
brj-22232	2	1	“	"	PUNCT
brj-22232	2	2	tree	tree	NOUN
brj-22232	2	3	root	root	NOUN
brj-22232	2	4	detection	detection	NOUN
brj-22232	2	5	training	training	NOUN
brj-22232	2	6	,	,	PUNCT
brj-22232	2	7	”	"	PUNCT
brj-22232	2	8	bioresources	bioresource	NOUN
brj-22232	2	9	18(1	18(1	NOUN
brj-22232	2	10	)	)	PUNCT
brj-22232	2	11	,	,	PUNCT
brj-22232	2	12	484	484	NUM
brj-22232	2	13	-	-	SYM
brj-22232	2	14	504	504	NUM
brj-22232	2	15	.	.	PUNCT
brj-22232	3	1	484	484	NUM
brj-22232	3	2	training	training	NOUN
brj-22232	3	3	data	datum	NOUN
brj-22232	3	4	augmentations	augmentation	NOUN
brj-22232	3	5	for	for	ADP
brj-22232	3	6	improving	improve	VERB
brj-22232	3	7	hyperbola	hyperbola	PROPN
brj-22232	3	8	recognition	recognition	PROPN
brj-22232	3	9	in	in	ADP
brj-22232	3	10	ground	ground	NOUN
brj-22232	3	11	penetrating	penetrate	VERB
brj-22232	3	12	radar	radar	NOUN
brj-22232	3	13	b	b	X
brj-22232	3	14	-	-	ADJ
brj-22232	3	15	scan	scan	ADJ
brj-22232	3	16	image	image	NOUN
brj-22232	3	17	for	for	ADP
brj-22232	3	18	tree	tree	NOUN
brj-22232	3	19	roots	root	NOUN
brj-22232	3	20	detection	detection	NOUN
brj-22232	3	21	zeqing	zeqing	PROPN
brj-22232	3	22	li	li	PROPN
brj-22232	3	23	,	,	PUNCT
brj-22232	3	24	a	a	PRON
brj-22232	3	25	,	,	PUNCT
brj-22232	3	26	b	b	PROPN
brj-22232	3	27	xiaowei	xiaowei	PROPN
brj-22232	3	28	zhang	zhang	PROPN
brj-22232	3	29	,	,	PUNCT
brj-22232	3	30	a	a	PRON
brj-22232	3	31	,	,	PUNCT
brj-22232	3	32	b	b	PROPN
brj-22232	3	33	haibin	haibin	PROPN
brj-22232	3	34	li	li	PROPN
brj-22232	3	35	,	,	PUNCT
brj-22232	3	36	a	a	PRON
brj-22232	3	37	,	,	PUNCT
brj-22232	3	38	b	b	PROPN
brj-22232	3	39	zepeng	zepeng	PROPN
brj-22232	3	40	wang	wang	PROPN
brj-22232	3	41	,	,	PUNCT
brj-22232	3	42	a	a	DET
brj-22232	3	43	,	,	PUNCT
brj-22232	3	44	b	b	NOUN
brj-22232	3	45	and	and	CCONJ
brj-22232	3	46	jian	jian	PROPN
brj-22232	3	47	wen	wen	PROPN
brj-22232	3	48	a	a	DET
brj-22232	3	49	,	,	PUNCT
brj-22232	3	50	b	b	NOUN
brj-22232	3	51	,	,	PUNCT
brj-22232	3	52	*	*	PUNCT
brj-22232	3	53	improving	improve	VERB
brj-22232	3	54	the	the	DET
brj-22232	3	55	detection	detection	NOUN
brj-22232	3	56	accuracy	accuracy	NOUN
brj-22232	3	57	of	of	ADP
brj-22232	3	58	hyperbola	hyperbola	PROPN
brj-22232	3	59	in	in	ADP
brj-22232	3	60	b	b	PROPN
brj-22232	3	61	-	-	PUNCT
brj-22232	3	62	scan	scan	ADJ
brj-22232	3	63	images	image	NOUN
brj-22232	3	64	has	have	AUX
brj-22232	3	65	been	be	AUX
brj-22232	3	66	a	a	DET
brj-22232	3	67	considerable	considerable	ADJ
brj-22232	3	68	challenge	challenge	NOUN
brj-22232	3	69	for	for	ADP
brj-22232	3	70	ground	ground	NOUN
brj-22232	3	71	penetrating	penetrate	VERB
brj-22232	3	72	radar	radar	NOUN
brj-22232	3	73	(	(	PUNCT
brj-22232	3	74	gpr	gpr	PROPN
brj-22232	3	75	)	)	PUNCT
brj-22232	3	76	to	to	PART
brj-22232	3	77	detect	detect	VERB
brj-22232	3	78	tree	tree	NOUN
brj-22232	3	79	roots	root	NOUN
brj-22232	3	80	.	.	PUNCT
brj-22232	4	1	in	in	ADP
brj-22232	4	2	this	this	DET
brj-22232	4	3	paper	paper	NOUN
brj-22232	4	4	,	,	PUNCT
brj-22232	4	5	a	a	DET
brj-22232	4	6	method	method	NOUN
brj-22232	4	7	for	for	ADP
brj-22232	4	8	data	data	NOUN
brj-22232	4	9	enhancement	enhancement	NOUN
brj-22232	4	10	and	and	CCONJ
brj-22232	4	11	target	target	NOUN
brj-22232	4	12	detection	detection	NOUN
brj-22232	4	13	,	,	PUNCT
brj-22232	4	14	both	both	PRON
brj-22232	4	15	based	base	VERB
brj-22232	4	16	on	on	ADP
brj-22232	4	17	deep	deep	ADJ
brj-22232	4	18	learning	learning	NOUN
brj-22232	4	19	was	be	AUX
brj-22232	4	20	proposed	propose	VERB
brj-22232	4	21	to	to	PART
brj-22232	4	22	identify	identify	VERB
brj-22232	4	23	hyperbolas	hyperbola	NOUN
brj-22232	4	24	in	in	ADP
brj-22232	4	25	gpr	gpr	PROPN
brj-22232	4	26	b	b	PROPN
brj-22232	4	27	-	-	PUNCT
brj-22232	4	28	scan	scan	ADJ
brj-22232	4	29	images	image	NOUN
brj-22232	4	30	.	.	PUNCT
brj-22232	5	1	first	first	ADV
brj-22232	5	2	,	,	PUNCT
brj-22232	5	3	the	the	DET
brj-22232	5	4	authors	author	NOUN
brj-22232	5	5	used	use	VERB
brj-22232	5	6	a	a	DET
brj-22232	5	7	cyclic	cyclic	ADJ
brj-22232	5	8	consistent	consistent	ADJ
brj-22232	5	9	adversarial	adversarial	ADJ
brj-22232	5	10	network	network	NOUN
brj-22232	5	11	(	(	PUNCT
brj-22232	5	12	cyclegan	cyclegan	NOUN
brj-22232	5	13	)	)	PUNCT
brj-22232	5	14	to	to	PART
brj-22232	5	15	augment	augment	VERB
brj-22232	5	16	the	the	DET
brj-22232	5	17	original	original	ADJ
brj-22232	5	18	data	datum	NOUN
brj-22232	5	19	.	.	PUNCT
brj-22232	6	1	in	in	ADP
brj-22232	6	2	this	this	DET
brj-22232	6	3	procedure	procedure	NOUN
brj-22232	6	4	,	,	PUNCT
brj-22232	6	5	the	the	DET
brj-22232	6	6	hyperbolic	hyperbolic	ADJ
brj-22232	6	7	features	feature	NOUN
brj-22232	6	8	of	of	ADP
brj-22232	6	9	the	the	DET
brj-22232	6	10	images	image	NOUN
brj-22232	6	11	were	be	AUX
brj-22232	6	12	preserved	preserve	VERB
brj-22232	6	13	and	and	CCONJ
brj-22232	6	14	created	create	VERB
brj-22232	6	15	a	a	DET
brj-22232	6	16	wider	wide	ADJ
brj-22232	6	17	variety	variety	NOUN
brj-22232	6	18	of	of	ADP
brj-22232	6	19	training	training	NOUN
brj-22232	6	20	samples	sample	NOUN
brj-22232	6	21	.	.	PUNCT
brj-22232	7	1	then	then	ADV
brj-22232	7	2	,	,	PUNCT
brj-22232	7	3	the	the	DET
brj-22232	7	4	authors	author	NOUN
brj-22232	7	5	could	could	AUX
brj-22232	7	6	apply	apply	VERB
brj-22232	7	7	the	the	DET
brj-22232	7	8	enhanced	enhance	VERB
brj-22232	7	9	dataset	dataset	NOUN
brj-22232	7	10	to	to	ADP
brj-22232	7	11	the	the	DET
brj-22232	7	12	yolov5	yolov5	NOUN
brj-22232	7	13	detection	detection	NOUN
brj-22232	7	14	model	model	NOUN
brj-22232	7	15	to	to	PART
brj-22232	7	16	evaluate	evaluate	VERB
brj-22232	7	17	the	the	DET
brj-22232	7	18	effectiveness	effectiveness	NOUN
brj-22232	7	19	of	of	ADP
brj-22232	7	20	their	their	PRON
brj-22232	7	21	method	method	NOUN
brj-22232	7	22	.	.	PUNCT
brj-22232	8	1	meanwhile	meanwhile	ADV
brj-22232	8	2	,	,	PUNCT
brj-22232	8	3	the	the	DET
brj-22232	8	4	detection	detection	NOUN
brj-22232	8	5	effects	effect	NOUN
brj-22232	8	6	of	of	ADP
brj-22232	8	7	yolov3	yolov3	PROPN
brj-22232	8	8	,	,	PUNCT
brj-22232	8	9	yolov5	yolov5	NOUN
brj-22232	8	10	,	,	PUNCT
brj-22232	8	11	faster	fast	ADJ
brj-22232	8	12	r	r	NOUN
brj-22232	8	13	-	-	PUNCT
brj-22232	8	14	cnn	cnn	PROPN
brj-22232	8	15	,	,	PUNCT
brj-22232	8	16	and	and	CCONJ
brj-22232	8	17	centernet	centernet	NOUN
brj-22232	8	18	detection	detection	NOUN
brj-22232	8	19	models	model	NOUN
brj-22232	8	20	on	on	ADP
brj-22232	8	21	the	the	DET
brj-22232	8	22	enhanced	enhanced	ADJ
brj-22232	8	23	dataset	dataset	NOUN
brj-22232	8	24	were	be	AUX
brj-22232	8	25	compared	compare	VERB
brj-22232	8	26	.	.	PUNCT
brj-22232	9	1	the	the	DET
brj-22232	9	2	results	result	NOUN
brj-22232	9	3	showed	show	VERB
brj-22232	9	4	that	that	SCONJ
brj-22232	9	5	applying	apply	VERB
brj-22232	9	6	the	the	DET
brj-22232	9	7	enhanced	enhance	VERB
brj-22232	9	8	dataset	dataset	NOUN
brj-22232	9	9	to	to	ADP
brj-22232	9	10	the	the	DET
brj-22232	9	11	yolov5	yolov5	NOUN
brj-22232	9	12	detection	detection	NOUN
brj-22232	9	13	model	model	NOUN
brj-22232	9	14	exhibited	exhibit	VERB
brj-22232	9	15	better	well	ADJ
brj-22232	9	16	detection	detection	NOUN
brj-22232	9	17	accuracy	accuracy	NOUN
brj-22232	9	18	compared	compare	VERB
brj-22232	9	19	to	to	ADP
brj-22232	9	20	other	other	ADJ
brj-22232	9	21	combinations	combination	NOUN
brj-22232	9	22	of	of	ADP
brj-22232	9	23	datasets	dataset	NOUN
brj-22232	9	24	and	and	CCONJ
brj-22232	9	25	detection	detection	NOUN
brj-22232	9	26	models	model	NOUN
brj-22232	9	27	.	.	PUNCT
brj-22232	10	1	the	the	DET
brj-22232	10	2	authors	author	NOUN
brj-22232	10	3	demonstrate	demonstrate	VERB
brj-22232	10	4	that	that	SCONJ
brj-22232	10	5	the	the	DET
brj-22232	10	6	proposed	propose	VERB
brj-22232	10	7	method	method	NOUN
brj-22232	10	8	increases	increase	VERB
brj-22232	10	9	data	datum	NOUN
brj-22232	10	10	diversity	diversity	NOUN
brj-22232	10	11	and	and	CCONJ
brj-22232	10	12	the	the	DET
brj-22232	10	13	number	number	NOUN
brj-22232	10	14	of	of	ADP
brj-22232	10	15	samples	sample	NOUN
brj-22232	10	16	,	,	PUNCT
brj-22232	10	17	improving	improve	VERB
brj-22232	10	18	the	the	DET
brj-22232	10	19	precision	precision	NOUN
brj-22232	10	20	and	and	CCONJ
brj-22232	10	21	recall	recall	NOUN
brj-22232	10	22	of	of	ADP
brj-22232	10	23	hyperbolic	hyperbolic	ADJ
brj-22232	10	24	curves	curve	NOUN
brj-22232	10	25	.	.	PUNCT
brj-22232	11	1	these	these	DET
brj-22232	11	2	results	result	NOUN
brj-22232	11	3	provide	provide	VERB
brj-22232	11	4	a	a	DET
brj-22232	11	5	new	new	ADJ
brj-22232	11	6	method	method	NOUN
brj-22232	11	7	for	for	ADP
brj-22232	11	8	tree	tree	NOUN
brj-22232	11	9	root	root	NOUN
brj-22232	11	10	localization	localization	NOUN
brj-22232	11	11	with	with	ADP
brj-22232	11	12	important	important	ADJ
brj-22232	11	13	effects	effect	NOUN
brj-22232	11	14	.	.	PUNCT
brj-22232	12	1	doi	doi	NOUN
brj-22232	12	2	:	:	PUNCT
brj-22232	12	3	10.15376	10.15376	NUM
brj-22232	12	4	/	/	SYM
brj-22232	12	5	biores.18.1.484	biores.18.1.484	NOUN
brj-22232	12	6	-	-	PUNCT
brj-22232	12	7	504	504	NUM
brj-22232	12	8	keywords	keyword	NOUN
brj-22232	12	9	:	:	PUNCT
brj-22232	12	10	ground	ground	NOUN
brj-22232	12	11	-	-	PUNCT
brj-22232	12	12	penetrating	penetrate	VERB
brj-22232	12	13	radar	radar	NOUN
brj-22232	12	14	(	(	PUNCT
brj-22232	12	15	gpr	gpr	PROPN
brj-22232	12	16	)	)	PUNCT
brj-22232	12	17	;	;	PUNCT
brj-22232	12	18	data	datum	NOUN
brj-22232	12	19	enhancement	enhancement	NOUN
brj-22232	12	20	;	;	PUNCT
brj-22232	12	21	yolov5	yolov5	NOUN
brj-22232	12	22	;	;	PUNCT
brj-22232	12	23	cycle	cycle	NOUN
brj-22232	12	24	-	-	PUNCT
brj-22232	12	25	consistent	consistent	ADJ
brj-22232	12	26	adversarial	adversarial	ADJ
brj-22232	12	27	networks	network	NOUN
brj-22232	12	28	(	(	PUNCT
brj-22232	12	29	cyclegan	cyclegan	PROPN
brj-22232	12	30	)	)	PUNCT
brj-22232	12	31	;	;	PUNCT
brj-22232	12	32	tree	tree	NOUN
brj-22232	12	33	root	root	NOUN
brj-22232	12	34	detection	detection	NOUN
brj-22232	12	35	contact	contact	NOUN
brj-22232	12	36	information	information	NOUN
brj-22232	12	37	:	:	PUNCT
brj-22232	12	38	a	a	DET
brj-22232	12	39	:	:	PUNCT
brj-22232	12	40	school	school	NOUN
brj-22232	12	41	of	of	ADP
brj-22232	12	42	technology	technology	NOUN
brj-22232	12	43	,	,	PUNCT
brj-22232	12	44	beijing	beijing	PROPN
brj-22232	12	45	forestry	forestry	PROPN
brj-22232	12	46	university	university	PROPN
brj-22232	12	47	,	,	PUNCT
brj-22232	12	48	beijing	beijing	PROPN
brj-22232	12	49	100083	100083	NUM
brj-22232	12	50	,	,	PUNCT
brj-22232	12	51	p.	p.	PROPN
brj-22232	12	52	r.	r.	PROPN
brj-22232	12	53	china	china	PROPN
brj-22232	12	54	;	;	PUNCT
brj-22232	12	55	b	b	X
brj-22232	12	56	:	:	PUNCT
brj-22232	12	57	joint	joint	ADJ
brj-22232	12	58	international	international	PROPN
brj-22232	12	59	research	research	PROPN
brj-22232	12	60	institute	institute	PROPN
brj-22232	12	61	of	of	ADP
brj-22232	12	62	wood	wood	NOUN
brj-22232	12	63	nondestructive	nondestructive	ADJ
brj-22232	12	64	testing	testing	NOUN
brj-22232	12	65	and	and	CCONJ
brj-22232	12	66	evaluation	evaluation	NOUN
brj-22232	12	67	,	,	PUNCT
brj-22232	12	68	beijing	beijing	PROPN
brj-22232	12	69	forestry	forestry	PROPN
brj-22232	12	70	university	university	PROPN
brj-22232	12	71	,	,	PUNCT
brj-22232	12	72	beijing	beijing	PROPN
brj-22232	12	73	100083	100083	NUM
brj-22232	12	74	,	,	PUNCT
brj-22232	12	75	p.	p.	PROPN
brj-22232	12	76	r.	r.	PROPN
brj-22232	12	77	china	china	PROPN
brj-22232	12	78	;	;	PUNCT
brj-22232	12	79	*	*	PUNCT
brj-22232	12	80	corresponding	correspond	VERB
brj-22232	12	81	author	author	NOUN
brj-22232	12	82	:	:	PUNCT
brj-22232	12	83	wenjian@bjfu.edu.cn	wenjian@bjfu.edu.cn	ADJ
brj-22232	12	84	introduction	introduction	NOUN
brj-22232	12	85	as	as	ADP
brj-22232	12	86	a	a	DET
brj-22232	12	87	vital	vital	ADJ
brj-22232	12	88	organ	organ	NOUN
brj-22232	12	89	for	for	ADP
brj-22232	12	90	tree	tree	NOUN
brj-22232	12	91	growth	growth	NOUN
brj-22232	12	92	and	and	CCONJ
brj-22232	12	93	development	development	NOUN
brj-22232	12	94	,	,	PUNCT
brj-22232	12	95	roots	root	NOUN
brj-22232	12	96	have	have	VERB
brj-22232	12	97	a	a	DET
brj-22232	12	98	significant	significant	ADJ
brj-22232	12	99	effect	effect	NOUN
brj-22232	12	100	on	on	ADP
brj-22232	12	101	the	the	DET
brj-22232	12	102	entire	entire	ADJ
brj-22232	12	103	life	life	NOUN
brj-22232	12	104	cycle	cycle	NOUN
brj-22232	12	105	of	of	ADP
brj-22232	12	106	trees	tree	NOUN
brj-22232	12	107	and	and	CCONJ
brj-22232	12	108	also	also	ADV
brj-22232	12	109	play	play	VERB
brj-22232	12	110	an	an	DET
brj-22232	12	111	equally	equally	ADV
brj-22232	12	112	important	important	ADJ
brj-22232	12	113	role	role	NOUN
brj-22232	12	114	in	in	ADP
brj-22232	12	115	the	the	DET
brj-22232	12	116	material	material	NOUN
brj-22232	12	117	cycle	cycle	NOUN
brj-22232	12	118	and	and	CCONJ
brj-22232	12	119	energy	energy	NOUN
brj-22232	12	120	flow	flow	NOUN
brj-22232	12	121	of	of	ADP
brj-22232	12	122	the	the	DET
brj-22232	12	123	soil	soil	NOUN
brj-22232	12	124	(	(	PUNCT
brj-22232	12	125	gill	gill	NOUN
brj-22232	12	126	and	and	CCONJ
brj-22232	12	127	jackson	jackson	PROPN
brj-22232	12	128	2000	2000	NUM
brj-22232	12	129	;	;	PUNCT
brj-22232	12	130	reubens	reuben	NOUN
brj-22232	12	131	et	et	PROPN
brj-22232	12	132	al	al	PROPN
brj-22232	12	133	.	.	PROPN
brj-22232	12	134	2007	2007	NUM
brj-22232	12	135	)	)	PUNCT
brj-22232	12	136	.	.	PUNCT
brj-22232	13	1	the	the	DET
brj-22232	13	2	specific	specific	ADJ
brj-22232	13	3	structure	structure	NOUN
brj-22232	13	4	of	of	ADP
brj-22232	13	5	the	the	DET
brj-22232	13	6	tree	tree	NOUN
brj-22232	13	7	root	root	NOUN
brj-22232	13	8	system	system	NOUN
brj-22232	13	9	can	can	AUX
brj-22232	13	10	be	be	AUX
brj-22232	13	11	determined	determine	VERB
brj-22232	13	12	through	through	ADP
brj-22232	13	13	intensive	intensive	ADJ
brj-22232	13	14	analysis	analysis	NOUN
brj-22232	13	15	of	of	ADP
brj-22232	13	16	parameters	parameter	NOUN
brj-22232	13	17	such	such	ADJ
brj-22232	13	18	as	as	ADP
brj-22232	13	19	root	root	NOUN
brj-22232	13	20	diameter	diameter	NOUN
brj-22232	13	21	,	,	PUNCT
brj-22232	13	22	orientation	orientation	NOUN
brj-22232	13	23	,	,	PUNCT
brj-22232	13	24	burial	burial	NOUN
brj-22232	13	25	depth	depth	NOUN
brj-22232	13	26	,	,	PUNCT
brj-22232	13	27	root	root	NOUN
brj-22232	13	28	water	water	NOUN
brj-22232	13	29	content	content	NOUN
brj-22232	13	30	,	,	PUNCT
brj-22232	13	31	and	and	CCONJ
brj-22232	13	32	root	root	NOUN
brj-22232	13	33	distribution	distribution	NOUN
brj-22232	13	34	(	(	PUNCT
brj-22232	13	35	danjon	danjon	NOUN
brj-22232	13	36	and	and	CCONJ
brj-22232	13	37	reubens	reuben	NOUN
brj-22232	13	38	2008	2008	NUM
brj-22232	13	39	)	)	PUNCT
brj-22232	13	40	.	.	PUNCT
brj-22232	14	1	detection	detection	NOUN
brj-22232	14	2	of	of	ADP
brj-22232	14	3	subsurface	subsurface	NOUN
brj-22232	14	4	root	root	NOUN
brj-22232	14	5	distribution	distribution	NOUN
brj-22232	14	6	and	and	CCONJ
brj-22232	14	7	study	study	NOUN
brj-22232	14	8	of	of	ADP
brj-22232	14	9	the	the	DET
brj-22232	14	10	specifics	specific	NOUN
brj-22232	14	11	of	of	ADP
brj-22232	14	12	root	root	NOUN
brj-22232	14	13	parameters	parameter	NOUN
brj-22232	14	14	are	be	AUX
brj-22232	14	15	often	often	ADV
brj-22232	14	16	performed	perform	VERB
brj-22232	14	17	using	use	VERB
brj-22232	14	18	excavation	excavation	NOUN
brj-22232	14	19	methods	method	NOUN
brj-22232	14	20	,	,	PUNCT
brj-22232	14	21	monoliths	monolith	NOUN
brj-22232	14	22	,	,	PUNCT
brj-22232	14	23	etc	etc	X
brj-22232	14	24	.	.	X
brj-22232	15	1	(	(	PUNCT
brj-22232	15	2	guo	guo	PROPN
brj-22232	15	3	et	et	PROPN
brj-22232	15	4	al	al	PROPN
brj-22232	15	5	.	.	PROPN
brj-22232	15	6	2013	2013	NUM
brj-22232	15	7	;	;	PUNCT
brj-22232	15	8	riedell	riedell	PROPN
brj-22232	15	9	and	and	CCONJ
brj-22232	15	10	osborne	osborne	PROPN
brj-22232	15	11	2017	2017	NUM
brj-22232	15	12	)	)	PUNCT
brj-22232	15	13	,	,	PUNCT
brj-22232	15	14	which	which	PRON
brj-22232	15	15	are	be	AUX
brj-22232	15	16	complex	complex	ADJ
brj-22232	15	17	to	to	PART
brj-22232	15	18	operate	operate	VERB
brj-22232	15	19	and	and	CCONJ
brj-22232	15	20	can	can	AUX
brj-22232	15	21	cause	cause	VERB
brj-22232	15	22	irreversible	irreversible	ADJ
brj-22232	15	23	damage	damage	NOUN
brj-22232	15	24	to	to	ADP
brj-22232	15	25	the	the	DET
brj-22232	15	26	soil	soil	NOUN
brj-22232	15	27	environment	environment	NOUN
brj-22232	15	28	and	and	CCONJ
brj-22232	15	29	trees	tree	NOUN
brj-22232	15	30	.	.	PUNCT
brj-22232	16	1	therefore	therefore	ADV
brj-22232	16	2	,	,	PUNCT
brj-22232	16	3	the	the	DET
brj-22232	16	4	nondestructive	nondestructive	ADJ
brj-22232	16	5	detection	detection	NOUN
brj-22232	16	6	of	of	ADP
brj-22232	16	7	tree	tree	NOUN
brj-22232	16	8	roots	root	NOUN
brj-22232	16	9	is	be	AUX
brj-22232	16	10	a	a	DET
brj-22232	16	11	challenging	challenging	ADJ
brj-22232	16	12	task	task	NOUN
brj-22232	16	13	.	.	PUNCT
brj-22232	17	1	ground	ground	NOUN
brj-22232	17	2	penetrating	penetrate	VERB
brj-22232	17	3	radar	radar	NOUN
brj-22232	17	4	(	(	PUNCT
brj-22232	17	5	gpr	gpr	PROPN
brj-22232	17	6	)	)	PUNCT
brj-22232	17	7	,	,	PUNCT
brj-22232	17	8	a	a	DET
brj-22232	17	9	nondestructive	nondestructive	ADJ
brj-22232	17	10	testing	testing	NOUN
brj-22232	17	11	technique	technique	NOUN
brj-22232	17	12	(	(	PUNCT
brj-22232	17	13	ndt	ndt	NOUN
brj-22232	17	14	)	)	PUNCT
brj-22232	17	15	has	have	AUX
brj-22232	17	16	been	be	AUX
brj-22232	17	17	widely	widely	ADV
brj-22232	17	18	used	use	VERB
brj-22232	17	19	in	in	ADP
brj-22232	17	20	tree	tree	NOUN
brj-22232	17	21	roots	root	NOUN
brj-22232	17	22	research	research	NOUN
brj-22232	17	23	.	.	PUNCT
brj-22232	18	1	compared	compare	VERB
brj-22232	18	2	with	with	ADP
brj-22232	18	3	traditional	traditional	ADJ
brj-22232	18	4	tree	tree	NOUN
brj-22232	18	5	root	root	NOUN
brj-22232	18	6	ndt	ndt	PROPN
brj-22232	18	7	methods	method	NOUN
brj-22232	18	8	,	,	PUNCT
brj-22232	18	9	such	such	ADJ
brj-22232	18	10	as	as	ADP
brj-22232	18	11	ultrasonic	ultrasonic	ADJ
brj-22232	18	12	pulse	pulse	NOUN
brj-22232	18	13	velocity	velocity	NOUN
brj-22232	18	14	(	(	PUNCT
brj-22232	18	15	upv	upv	PROPN
brj-22232	18	16	)	)	PUNCT
brj-22232	18	17	analysis	analysis	NOUN
brj-22232	18	18	(	(	PUNCT
brj-22232	18	19	wang	wang	PROPN
brj-22232	18	20	and	and	CCONJ
brj-22232	18	21	li	li	PROPN
brj-22232	18	22	2015	2015	NUM
brj-22232	18	23	;	;	PUNCT
brj-22232	18	24	sarro	sarro	PROPN
brj-22232	18	25	et	et	PROPN
brj-22232	18	26	al	al	PROPN
brj-22232	18	27	.	.	PROPN
brj-22232	18	28	2021	2021	NUM
brj-22232	18	29	)	)	PUNCT
brj-22232	18	30	and	and	CCONJ
brj-22232	18	31	electrical	electrical	ADJ
brj-22232	18	32	resistance	resistance	NOUN
brj-22232	18	33	tomography	tomography	NOUN
brj-22232	18	34	(	(	PUNCT
brj-22232	18	35	ert	ert	PROPN
brj-22232	18	36	)	)	PUNCT
brj-22232	18	37	(	(	PUNCT
brj-22232	18	38	labrecque	labrecque	ADJ
brj-22232	18	39	and	and	CCONJ
brj-22232	18	40	yang	yang	PROPN
brj-22232	18	41	2001	2001	NUM
brj-22232	18	42	;	;	PUNCT
brj-22232	18	43	kemna	kemna	PROPN
brj-22232	18	44	et	et	PROPN
brj-22232	18	45	al	al	PROPN
brj-22232	18	46	.	.	PROPN
brj-22232	18	47	peer	peer	NOUN
brj-22232	18	48	-	-	PUNCT
brj-22232	18	49	reviewed	review	VERB
brj-22232	18	50	article	article	NOUN
brj-22232	18	51	bioresources.com	bioresources.com	X
brj-22232	18	52	li	li	PROPN
brj-22232	18	53	et	et	PROPN
brj-22232	18	54	al	al	PROPN
brj-22232	18	55	.	.	PROPN
brj-22232	18	56	(	(	PUNCT
brj-22232	18	57	2023	2023	NUM
brj-22232	18	58	)	)	PUNCT
brj-22232	18	59	.	.	PUNCT
brj-22232	19	1	“	"	PUNCT
brj-22232	19	2	tree	tree	NOUN
brj-22232	19	3	root	root	NOUN
brj-22232	19	4	detection	detection	NOUN
brj-22232	19	5	training	training	NOUN
brj-22232	19	6	,	,	PUNCT
brj-22232	19	7	”	"	PUNCT
brj-22232	19	8	bioresources	bioresource	NOUN
brj-22232	19	9	18(1	18(1	NOUN
brj-22232	19	10	)	)	PUNCT
brj-22232	19	11	,	,	PUNCT
brj-22232	19	12	484	484	NUM
brj-22232	19	13	-	-	SYM
brj-22232	19	14	504	504	NUM
brj-22232	19	15	.	.	PUNCT
brj-22232	19	16	485	485	NUM
brj-22232	19	17	2002	2002	NUM
brj-22232	19	18	)	)	PUNCT
brj-22232	19	19	,	,	PUNCT
brj-22232	19	20	gpr	gpr	PROPN
brj-22232	19	21	has	have	VERB
brj-22232	19	22	the	the	DET
brj-22232	19	23	advantages	advantage	NOUN
brj-22232	19	24	of	of	ADP
brj-22232	19	25	high	high	ADJ
brj-22232	19	26	efficiency	efficiency	NOUN
brj-22232	19	27	,	,	PUNCT
brj-22232	19	28	safety	safety	NOUN
brj-22232	19	29	,	,	PUNCT
brj-22232	19	30	and	and	CCONJ
brj-22232	19	31	high	high	ADJ
brj-22232	19	32	interference	interference	NOUN
brj-22232	19	33	resistance	resistance	NOUN
brj-22232	19	34	(	(	PUNCT
brj-22232	19	35	alani	alani	PROPN
brj-22232	19	36	et	et	PROPN
brj-22232	19	37	al	al	PROPN
brj-22232	19	38	.	.	PROPN
brj-22232	19	39	2018	2018	NUM
brj-22232	19	40	;	;	PUNCT
brj-22232	19	41	mihai	mihai	PROPN
brj-22232	19	42	et	et	PROPN
brj-22232	19	43	al	al	PROPN
brj-22232	19	44	.	.	PROPN
brj-22232	19	45	2019	2019	NUM
brj-22232	19	46	;	;	PUNCT
brj-22232	19	47	aboudourib	aboudourib	PROPN
brj-22232	19	48	et	et	PROPN
brj-22232	19	49	al	al	PROPN
brj-22232	19	50	.	.	PROPN
brj-22232	19	51	2021	2021	NUM
brj-22232	19	52	)	)	PUNCT
brj-22232	19	53	.	.	PUNCT
brj-22232	20	1	the	the	DET
brj-22232	20	2	method	method	NOUN
brj-22232	20	3	gpr	gpr	PROPN
brj-22232	20	4	can	can	AUX
brj-22232	20	5	accurately	accurately	ADV
brj-22232	20	6	detect	detect	VERB
brj-22232	20	7	targets	target	NOUN
brj-22232	20	8	based	base	VERB
brj-22232	20	9	on	on	ADP
brj-22232	20	10	the	the	DET
brj-22232	20	11	relative	relative	ADJ
brj-22232	20	12	permittivity	permittivity	NOUN
brj-22232	20	13	between	between	ADP
brj-22232	20	14	the	the	DET
brj-22232	20	15	targets	target	NOUN
brj-22232	20	16	and	and	CCONJ
brj-22232	20	17	other	other	ADJ
brj-22232	20	18	media	medium	NOUN
brj-22232	20	19	.	.	PUNCT
brj-22232	21	1	this	this	PRON
brj-22232	21	2	is	be	AUX
brj-22232	21	3	because	because	SCONJ
brj-22232	21	4	the	the	DET
brj-22232	21	5	water	water	NOUN
brj-22232	21	6	content	content	NOUN
brj-22232	21	7	in	in	ADP
brj-22232	21	8	the	the	DET
brj-22232	21	9	tree	tree	NOUN
brj-22232	21	10	root	root	NOUN
brj-22232	21	11	system	system	NOUN
brj-22232	21	12	is	be	AUX
brj-22232	21	13	vastly	vastly	ADV
brj-22232	21	14	different	different	ADJ
brj-22232	21	15	from	from	ADP
brj-22232	21	16	the	the	DET
brj-22232	21	17	water	water	NOUN
brj-22232	21	18	content	content	NOUN
brj-22232	21	19	in	in	ADP
brj-22232	21	20	the	the	DET
brj-22232	21	21	adjacent	adjacent	ADJ
brj-22232	21	22	soil	soil	NOUN
brj-22232	21	23	(	(	PUNCT
brj-22232	21	24	pettinelli	pettinelli	NOUN
brj-22232	21	25	et	et	PROPN
brj-22232	21	26	al	al	PROPN
brj-22232	21	27	.	.	PROPN
brj-22232	21	28	2014	2014	NUM
brj-22232	21	29	;	;	PUNCT
brj-22232	21	30	tanoli	tanoli	PROPN
brj-22232	21	31	et	et	PROPN
brj-22232	21	32	al	al	PROPN
brj-22232	21	33	.	.	PROPN
brj-22232	21	34	2019	2019	NUM
brj-22232	21	35	)	)	PUNCT
brj-22232	21	36	,	,	PUNCT
brj-22232	21	37	resulting	result	VERB
brj-22232	21	38	in	in	ADP
brj-22232	21	39	a	a	DET
brj-22232	21	40	noticeable	noticeable	ADJ
brj-22232	21	41	difference	difference	NOUN
brj-22232	21	42	in	in	ADP
brj-22232	21	43	relative	relative	ADJ
brj-22232	21	44	permittivity	permittivity	NOUN
brj-22232	21	45	.	.	PUNCT
brj-22232	22	1	therefore	therefore	ADV
brj-22232	22	2	,	,	PUNCT
brj-22232	22	3	it	it	PRON
brj-22232	22	4	is	be	AUX
brj-22232	22	5	feasible	feasible	ADJ
brj-22232	22	6	to	to	PART
brj-22232	22	7	use	use	VERB
brj-22232	22	8	gpr	gpr	PROPN
brj-22232	22	9	to	to	PART
brj-22232	22	10	detect	detect	VERB
brj-22232	22	11	root	root	NOUN
brj-22232	22	12	structure	structure	NOUN
brj-22232	22	13	.	.	PUNCT
brj-22232	23	1	the	the	DET
brj-22232	23	2	use	use	NOUN
brj-22232	23	3	of	of	ADP
brj-22232	23	4	ground	ground	NOUN
brj-22232	23	5	penetrating	penetrate	VERB
brj-22232	23	6	radar	radar	NOUN
brj-22232	23	7	to	to	PART
brj-22232	23	8	detect	detect	VERB
brj-22232	23	9	the	the	DET
brj-22232	23	10	size	size	NOUN
brj-22232	23	11	of	of	ADP
brj-22232	23	12	plant	plant	NOUN
brj-22232	23	13	roots	root	NOUN
brj-22232	23	14	is	be	AUX
brj-22232	23	15	one	one	NUM
brj-22232	23	16	of	of	ADP
brj-22232	23	17	the	the	DET
brj-22232	23	18	important	important	ADJ
brj-22232	23	19	directions	direction	NOUN
brj-22232	23	20	of	of	ADP
brj-22232	23	21	current	current	ADJ
brj-22232	23	22	research	research	NOUN
brj-22232	23	23	.	.	PUNCT
brj-22232	24	1	zhou	zhou	PROPN
brj-22232	24	2	et	et	PROPN
brj-22232	24	3	al	al	PROPN
brj-22232	24	4	.	.	PROPN
brj-22232	25	1	(	(	PUNCT
brj-22232	25	2	2019	2019	NUM
brj-22232	25	3	)	)	PUNCT
brj-22232	25	4	proposed	propose	VERB
brj-22232	25	5	a	a	DET
brj-22232	25	6	model	model	NOUN
brj-22232	25	7	combining	combine	VERB
brj-22232	25	8	ground	ground	NOUN
brj-22232	25	9	penetrating	penetrate	VERB
brj-22232	25	10	radar	radar	NOUN
brj-22232	25	11	with	with	ADP
brj-22232	25	12	electric	electric	ADJ
brj-22232	25	13	field	field	NOUN
brj-22232	25	14	methods	method	NOUN
brj-22232	25	15	,	,	PUNCT
brj-22232	25	16	which	which	PRON
brj-22232	25	17	could	could	AUX
brj-22232	25	18	automatically	automatically	ADV
brj-22232	25	19	and	and	CCONJ
brj-22232	25	20	quickly	quickly	ADV
brj-22232	25	21	fit	fit	VERB
brj-22232	25	22	a	a	DET
brj-22232	25	23	hyperbola	hyperbola	NOUN
brj-22232	25	24	in	in	ADP
brj-22232	25	25	the	the	DET
brj-22232	25	26	retained	retain	VERB
brj-22232	25	27	image	image	NOUN
brj-22232	25	28	area	area	NOUN
brj-22232	25	29	and	and	CCONJ
brj-22232	25	30	could	could	AUX
brj-22232	25	31	effectively	effectively	ADV
brj-22232	25	32	obtain	obtain	VERB
brj-22232	25	33	the	the	DET
brj-22232	25	34	depth	depth	NOUN
brj-22232	25	35	and	and	CCONJ
brj-22232	25	36	radius	radius	NOUN
brj-22232	25	37	of	of	ADP
brj-22232	25	38	buried	bury	VERB
brj-22232	25	39	objects	object	NOUN
brj-22232	25	40	.	.	PUNCT
brj-22232	26	1	when	when	SCONJ
brj-22232	26	2	the	the	DET
brj-22232	26	3	root	root	NOUN
brj-22232	26	4	system	system	NOUN
brj-22232	26	5	is	be	AUX
brj-22232	26	6	detected	detect	VERB
brj-22232	26	7	,	,	PUNCT
brj-22232	26	8	the	the	DET
brj-22232	26	9	general	general	ADJ
brj-22232	26	10	distribution	distribution	NOUN
brj-22232	26	11	of	of	ADP
brj-22232	26	12	the	the	DET
brj-22232	26	13	root	root	NOUN
brj-22232	26	14	system	system	NOUN
brj-22232	26	15	can	can	AUX
brj-22232	26	16	be	be	AUX
brj-22232	26	17	observed	observe	VERB
brj-22232	26	18	visually	visually	ADV
brj-22232	26	19	,	,	PUNCT
brj-22232	26	20	and	and	CCONJ
brj-22232	26	21	further	further	ADJ
brj-22232	26	22	information	information	NOUN
brj-22232	26	23	such	such	ADJ
brj-22232	26	24	as	as	ADP
brj-22232	26	25	the	the	DET
brj-22232	26	26	location	location	NOUN
brj-22232	26	27	,	,	PUNCT
brj-22232	26	28	size	size	NOUN
brj-22232	26	29	and	and	CCONJ
brj-22232	26	30	orientation	orientation	NOUN
brj-22232	26	31	of	of	ADP
brj-22232	26	32	the	the	DET
brj-22232	26	33	root	root	NOUN
brj-22232	26	34	system	system	NOUN
brj-22232	26	35	can	can	AUX
brj-22232	26	36	be	be	AUX
brj-22232	26	37	obtained	obtain	VERB
brj-22232	26	38	,	,	PUNCT
brj-22232	26	39	and	and	CCONJ
brj-22232	26	40	the	the	DET
brj-22232	26	41	specific	specific	ADJ
brj-22232	26	42	structure	structure	NOUN
brj-22232	26	43	of	of	ADP
brj-22232	26	44	the	the	DET
brj-22232	26	45	root	root	NOUN
brj-22232	26	46	system	system	NOUN
brj-22232	26	47	of	of	ADP
brj-22232	26	48	the	the	DET
brj-22232	26	49	tree	tree	NOUN
brj-22232	26	50	can	can	AUX
brj-22232	26	51	be	be	AUX
brj-22232	26	52	established	establish	VERB
brj-22232	26	53	.	.	PUNCT
brj-22232	27	1	this	this	DET
brj-22232	27	2	information	information	NOUN
brj-22232	27	3	can	can	AUX
brj-22232	27	4	better	well	ADV
brj-22232	27	5	analyze	analyze	VERB
brj-22232	27	6	the	the	DET
brj-22232	27	7	growth	growth	NOUN
brj-22232	27	8	and	and	CCONJ
brj-22232	27	9	health	health	NOUN
brj-22232	27	10	of	of	ADP
brj-22232	27	11	the	the	DET
brj-22232	27	12	tree	tree	NOUN
brj-22232	27	13	,	,	PUNCT
brj-22232	27	14	the	the	DET
brj-22232	27	15	roots	root	NOUN
brj-22232	27	16	usually	usually	ADV
brj-22232	27	17	appear	appear	VERB
brj-22232	27	18	as	as	ADP
brj-22232	27	19	hyperbolas	hyperbola	NOUN
brj-22232	27	20	in	in	ADP
brj-22232	27	21	the	the	DET
brj-22232	27	22	radar	radar	NOUN
brj-22232	27	23	b	b	NOUN
brj-22232	27	24	-	-	PUNCT
brj-22232	27	25	scan	scan	ADJ
brj-22232	27	26	image	image	NOUN
brj-22232	27	27	.	.	PUNCT
brj-22232	28	1	automatic	automatic	ADJ
brj-22232	28	2	detection	detection	NOUN
brj-22232	28	3	of	of	ADP
brj-22232	28	4	hyperbolic	hyperbolic	ADJ
brj-22232	28	5	features	feature	NOUN
brj-22232	28	6	in	in	ADP
brj-22232	28	7	the	the	DET
brj-22232	28	8	images	image	NOUN
brj-22232	28	9	can	can	AUX
brj-22232	28	10	improve	improve	VERB
brj-22232	28	11	efficiency	efficiency	NOUN
brj-22232	28	12	and	and	CCONJ
brj-22232	28	13	recognition	recognition	NOUN
brj-22232	28	14	accuracy	accuracy	NOUN
brj-22232	28	15	.	.	PUNCT
brj-22232	29	1	before	before	SCONJ
brj-22232	29	2	the	the	DET
brj-22232	29	3	b	b	NOUN
brj-22232	29	4	-	-	PUNCT
brj-22232	29	5	scan	scan	ADJ
brj-22232	29	6	image	image	NOUN
brj-22232	29	7	hyperbolas	hyperbola	NOUN
brj-22232	29	8	can	can	AUX
brj-22232	29	9	be	be	AUX
brj-22232	29	10	identified	identify	VERB
brj-22232	29	11	,	,	PUNCT
brj-22232	29	12	the	the	DET
brj-22232	29	13	image	image	NOUN
brj-22232	29	14	first	first	ADV
brj-22232	29	15	has	have	VERB
brj-22232	29	16	to	to	PART
brj-22232	29	17	be	be	AUX
brj-22232	29	18	preprocessed	preprocesse	VERB
brj-22232	29	19	.	.	PUNCT
brj-22232	30	1	however	however	ADV
brj-22232	30	2	,	,	PUNCT
brj-22232	30	3	in	in	ADP
brj-22232	30	4	the	the	DET
brj-22232	30	5	actual	actual	ADJ
brj-22232	30	6	detection	detection	NOUN
brj-22232	30	7	environment	environment	NOUN
brj-22232	30	8	,	,	PUNCT
brj-22232	30	9	because	because	SCONJ
brj-22232	30	10	of	of	ADP
brj-22232	30	11	the	the	DET
brj-22232	30	12	random	random	ADJ
brj-22232	30	13	nature	nature	NOUN
brj-22232	30	14	of	of	ADP
brj-22232	30	15	soil	soil	NOUN
brj-22232	30	16	distribution	distribution	NOUN
brj-22232	30	17	,	,	PUNCT
brj-22232	30	18	radar	radar	NOUN
brj-22232	30	19	hardware	hardware	NOUN
brj-22232	30	20	,	,	PUNCT
brj-22232	30	21	wave	wave	NOUN
brj-22232	30	22	interactions	interaction	NOUN
brj-22232	30	23	,	,	PUNCT
brj-22232	30	24	and	and	CCONJ
brj-22232	30	25	different	different	ADJ
brj-22232	30	26	underground	underground	ADJ
brj-22232	30	27	media	medium	NOUN
brj-22232	30	28	(	(	PUNCT
brj-22232	30	29	daniel	daniel	PROPN
brj-22232	30	30	et	et	PROPN
brj-22232	30	31	al	al	PROPN
brj-22232	30	32	.	.	PROPN
brj-22232	30	33	2016	2016	NUM
brj-22232	30	34	)	)	PUNCT
brj-22232	30	35	,	,	PUNCT
brj-22232	30	36	there	there	PRON
brj-22232	30	37	are	be	VERB
brj-22232	30	38	various	various	ADJ
brj-22232	30	39	noises	noise	NOUN
brj-22232	30	40	existing	exist	VERB
brj-22232	30	41	in	in	ADP
brj-22232	30	42	the	the	DET
brj-22232	30	43	detected	detected	ADJ
brj-22232	30	44	b	b	X
brj-22232	30	45	-	-	PUNCT
brj-22232	30	46	scan	scan	ADJ
brj-22232	30	47	images	image	NOUN
brj-22232	30	48	.	.	PUNCT
brj-22232	31	1	therefore	therefore	ADV
brj-22232	31	2	,	,	PUNCT
brj-22232	31	3	b	b	X
brj-22232	31	4	-	-	PUNCT
brj-22232	31	5	scan	scan	ADJ
brj-22232	31	6	images	image	NOUN
brj-22232	31	7	are	be	AUX
brj-22232	31	8	often	often	ADV
brj-22232	31	9	pre	pre	VERB
brj-22232	31	10	-	-	VERB
brj-22232	31	11	processed	process	VERB
brj-22232	31	12	by	by	ADP
brj-22232	31	13	several	several	ADJ
brj-22232	31	14	signal	signal	NOUN
brj-22232	31	15	and	and	CCONJ
brj-22232	31	16	image	image	NOUN
brj-22232	31	17	processing	processing	NOUN
brj-22232	31	18	methods	method	NOUN
brj-22232	31	19	.	.	PUNCT
brj-22232	32	1	wen	wen	PROPN
brj-22232	32	2	et	et	PROPN
brj-22232	32	3	al	al	PROPN
brj-22232	32	4	.	.	PROPN
brj-22232	32	5	(	(	PUNCT
brj-22232	32	6	2020	2020	NUM
brj-22232	32	7	)	)	PUNCT
brj-22232	32	8	proposed	propose	VERB
brj-22232	32	9	a	a	DET
brj-22232	32	10	shearlet	shearlet	NOUN
brj-22232	32	11	transform	transform	NOUN
brj-22232	32	12	to	to	PART
brj-22232	32	13	perform	perform	VERB
brj-22232	32	14	noise	noise	NOUN
brj-22232	32	15	removal	removal	NOUN
brj-22232	32	16	from	from	ADP
brj-22232	32	17	b	b	X
brj-22232	32	18	-	-	PUNCT
brj-22232	32	19	scan	scan	ADJ
brj-22232	32	20	images	image	NOUN
brj-22232	32	21	and	and	CCONJ
brj-22232	32	22	achieved	achieve	VERB
brj-22232	32	23	better	well	ADJ
brj-22232	32	24	denoising	denoising	NOUN
brj-22232	32	25	results	result	NOUN
brj-22232	32	26	in	in	ADP
brj-22232	32	27	some	some	DET
brj-22232	32	28	image	image	NOUN
brj-22232	32	29	evaluation	evaluation	NOUN
brj-22232	32	30	metrics	metric	NOUN
brj-22232	32	31	.	.	PUNCT
brj-22232	33	1	deep	deep	ADJ
brj-22232	33	2	learning	learning	NOUN
brj-22232	33	3	models	model	NOUN
brj-22232	33	4	are	be	AUX
brj-22232	33	5	being	be	AUX
brj-22232	33	6	widely	widely	ADV
brj-22232	33	7	used	use	VERB
brj-22232	33	8	to	to	PART
brj-22232	33	9	detect	detect	VERB
brj-22232	33	10	the	the	DET
brj-22232	33	11	internal	internal	ADJ
brj-22232	33	12	structure	structure	NOUN
brj-22232	33	13	of	of	ADP
brj-22232	33	14	tree	tree	NOUN
brj-22232	33	15	root	root	NOUN
brj-22232	33	16	systems	system	NOUN
brj-22232	33	17	(	(	PUNCT
brj-22232	33	18	xiang	xiang	PROPN
brj-22232	33	19	et	et	PROPN
brj-22232	33	20	al	al	PROPN
brj-22232	33	21	.	.	PROPN
brj-22232	33	22	2019	2019	NUM
brj-22232	33	23	;	;	PUNCT
brj-22232	33	24	hou	hou	PROPN
brj-22232	33	25	et	et	PROPN
brj-22232	33	26	al	al	PROPN
brj-22232	33	27	.	.	PROPN
brj-22232	33	28	2021	2021	NUM
brj-22232	33	29	;	;	PUNCT
brj-22232	33	30	zhang	zhang	PROPN
brj-22232	33	31	et	et	PROPN
brj-22232	33	32	al	al	PROPN
brj-22232	33	33	.	.	PROPN
brj-22232	33	34	2021	2021	NUM
brj-22232	33	35	)	)	PUNCT
brj-22232	33	36	.	.	PUNCT
brj-22232	34	1	hou	hou	PROPN
brj-22232	34	2	et	et	PROPN
brj-22232	34	3	al	al	PROPN
brj-22232	34	4	.	.	PROPN
brj-22232	34	5	(	(	PUNCT
brj-22232	34	6	2021	2021	NUM
brj-22232	34	7	)	)	PUNCT
brj-22232	34	8	proposed	propose	VERB
brj-22232	34	9	using	use	VERB
brj-22232	34	10	ms	ms	PROPN
brj-22232	34	11	r	r	PROPN
brj-22232	34	12	-	-	PUNCT
brj-22232	34	13	cnn	cnn	NOUN
brj-22232	34	14	architecture	architecture	NOUN
brj-22232	34	15	for	for	ADP
brj-22232	34	16	the	the	DET
brj-22232	34	17	detection	detection	NOUN
brj-22232	34	18	of	of	ADP
brj-22232	34	19	gpr	gpr	PROPN
brj-22232	34	20	subsurface	subsurface	NOUN
brj-22232	34	21	scanned	scan	VERB
brj-22232	34	22	objects	object	NOUN
brj-22232	34	23	,	,	PUNCT
brj-22232	34	24	while	while	SCONJ
brj-22232	34	25	using	use	VERB
brj-22232	34	26	the	the	DET
brj-22232	34	27	transfer	transfer	NOUN
brj-22232	34	28	learning	learning	NOUN
brj-22232	34	29	technique	technique	NOUN
brj-22232	34	30	to	to	PART
brj-22232	34	31	obtain	obtain	VERB
brj-22232	34	32	pre	pre	ADJ
brj-22232	34	33	-	-	ADJ
brj-22232	34	34	trained	train	VERB
brj-22232	34	35	models	model	NOUN
brj-22232	34	36	to	to	PART
brj-22232	34	37	solve	solve	VERB
brj-22232	34	38	the	the	DET
brj-22232	34	39	problem	problem	NOUN
brj-22232	34	40	of	of	ADP
brj-22232	34	41	the	the	DET
brj-22232	34	42	insufficient	insufficient	ADJ
brj-22232	34	43	model	model	NOUN
brj-22232	34	44	training	training	NOUN
brj-22232	34	45	set	set	NOUN
brj-22232	34	46	(	(	PUNCT
brj-22232	34	47	93	93	NUM
brj-22232	34	48	gpr	gpr	PROPN
brj-22232	34	49	root	root	NOUN
brj-22232	34	50	scans	scan	NOUN
brj-22232	34	51	)	)	PUNCT
brj-22232	34	52	.	.	PUNCT
brj-22232	35	1	zhang	zhang	PROPN
brj-22232	35	2	et	et	PROPN
brj-22232	35	3	al	al	PROPN
brj-22232	35	4	.	.	PROPN
brj-22232	35	5	(	(	PUNCT
brj-22232	35	6	2021	2021	NUM
brj-22232	35	7	)	)	PUNCT
brj-22232	35	8	used	use	VERB
brj-22232	35	9	the	the	DET
brj-22232	35	10	faster	fast	ADJ
brj-22232	35	11	r	r	NOUN
brj-22232	35	12	-	-	PUNCT
brj-22232	35	13	cnn	cnn	NOUN
brj-22232	35	14	to	to	PART
brj-22232	35	15	train	train	VERB
brj-22232	35	16	1442	1442	NUM
brj-22232	35	17	gpr	gpr	PROPN
brj-22232	35	18	b	b	X
brj-22232	35	19	-	-	PUNCT
brj-22232	35	20	scan	scan	ADJ
brj-22232	35	21	images	image	NOUN
brj-22232	35	22	(	(	PUNCT
brj-22232	35	23	282	282	NUM
brj-22232	35	24	for	for	ADP
brj-22232	35	25	real	real	ADJ
brj-22232	35	26	images	image	NOUN
brj-22232	35	27	and	and	CCONJ
brj-22232	35	28	1160	1160	NUM
brj-22232	35	29	for	for	ADP
brj-22232	35	30	simulation	simulation	NOUN
brj-22232	35	31	images	image	NOUN
brj-22232	35	32	)	)	PUNCT
brj-22232	35	33	to	to	PART
brj-22232	35	34	achieve	achieve	VERB
brj-22232	35	35	automatic	automatic	ADJ
brj-22232	35	36	recognition	recognition	NOUN
brj-22232	35	37	and	and	CCONJ
brj-22232	35	38	localization	localization	NOUN
brj-22232	35	39	of	of	ADP
brj-22232	35	40	hyperbolas	hyperbola	NOUN
brj-22232	35	41	in	in	ADP
brj-22232	35	42	gpr	gpr	PROPN
brj-22232	35	43	images	image	NOUN
brj-22232	35	44	.	.	PUNCT
brj-22232	36	1	it	it	PRON
brj-22232	36	2	is	be	AUX
brj-22232	36	3	not	not	PART
brj-22232	36	4	easy	easy	ADJ
brj-22232	36	5	to	to	PART
brj-22232	36	6	perform	perform	VERB
brj-22232	36	7	effective	effective	ADJ
brj-22232	36	8	automatic	automatic	ADJ
brj-22232	36	9	detection	detection	NOUN
brj-22232	36	10	of	of	ADP
brj-22232	36	11	tree	tree	NOUN
brj-22232	36	12	root	root	NOUN
brj-22232	36	13	systems	system	NOUN
brj-22232	36	14	with	with	ADP
brj-22232	36	15	these	these	DET
brj-22232	36	16	methods	method	NOUN
brj-22232	36	17	.	.	PUNCT
brj-22232	37	1	the	the	DET
brj-22232	37	2	main	main	ADJ
brj-22232	37	3	obstacle	obstacle	NOUN
brj-22232	37	4	is	be	AUX
brj-22232	37	5	the	the	DET
brj-22232	37	6	single	single	ADJ
brj-22232	37	7	type	type	NOUN
brj-22232	37	8	and	and	CCONJ
brj-22232	37	9	an	an	DET
brj-22232	37	10	insufficient	insufficient	ADJ
brj-22232	37	11	number	number	NOUN
brj-22232	37	12	of	of	ADP
brj-22232	37	13	datasets	dataset	NOUN
brj-22232	37	14	.	.	PUNCT
brj-22232	38	1	to	to	PART
brj-22232	38	2	overcome	overcome	VERB
brj-22232	38	3	this	this	DET
brj-22232	38	4	obstacle	obstacle	NOUN
brj-22232	38	5	,	,	PUNCT
brj-22232	38	6	data	datum	NOUN
brj-22232	38	7	augmentation	augmentation	NOUN
brj-22232	38	8	was	be	AUX
brj-22232	38	9	performed	perform	VERB
brj-22232	38	10	on	on	ADP
brj-22232	38	11	the	the	DET
brj-22232	38	12	tree	tree	NOUN
brj-22232	38	13	root	root	NOUN
brj-22232	38	14	system	system	NOUN
brj-22232	38	15	dataset	dataset	NOUN
brj-22232	38	16	.	.	PUNCT
brj-22232	39	1	the	the	DET
brj-22232	39	2	traditional	traditional	ADJ
brj-22232	39	3	image	image	NOUN
brj-22232	39	4	augmentation	augmentation	NOUN
brj-22232	39	5	of	of	ADP
brj-22232	39	6	the	the	DET
brj-22232	39	7	tree	tree	NOUN
brj-22232	39	8	root	root	NOUN
brj-22232	39	9	system	system	NOUN
brj-22232	39	10	uses	use	VERB
brj-22232	39	11	scales	scale	NOUN
brj-22232	39	12	,	,	PUNCT
brj-22232	39	13	stretches	stretch	NOUN
brj-22232	39	14	,	,	PUNCT
brj-22232	39	15	flips	flip	NOUN
brj-22232	39	16	,	,	PUNCT
brj-22232	39	17	crops	crop	NOUN
brj-22232	39	18	,	,	PUNCT
brj-22232	39	19	and	and	CCONJ
brj-22232	39	20	obtains	obtain	VERB
brj-22232	39	21	the	the	DET
brj-22232	39	22	gpr	gpr	PROPN
brj-22232	39	23	b	b	PROPN
brj-22232	39	24	-	-	PUNCT
brj-22232	39	25	scan	scan	ADJ
brj-22232	39	26	images	image	NOUN
brj-22232	39	27	,	,	PUNCT
brj-22232	39	28	increasing	increase	VERB
brj-22232	39	29	the	the	DET
brj-22232	39	30	number	number	NOUN
brj-22232	39	31	of	of	ADP
brj-22232	39	32	training	training	NOUN
brj-22232	39	33	data	datum	NOUN
brj-22232	39	34	by	by	ADP
brj-22232	39	35	changing	change	VERB
brj-22232	39	36	the	the	DET
brj-22232	39	37	original	original	ADJ
brj-22232	39	38	data	datum	NOUN
brj-22232	39	39	without	without	ADP
brj-22232	39	40	expanding	expand	VERB
brj-22232	39	41	the	the	DET
brj-22232	39	42	number	number	NOUN
brj-22232	39	43	of	of	ADP
brj-22232	39	44	a	a	DET
brj-22232	39	45	real	real	ADJ
brj-22232	39	46	dataset	dataset	NOUN
brj-22232	39	47	.	.	PUNCT
brj-22232	40	1	the	the	DET
brj-22232	40	2	method	method	NOUN
brj-22232	40	3	of	of	ADP
brj-22232	40	4	using	use	VERB
brj-22232	40	5	gprmax	gprmax	PROPN
brj-22232	40	6	3.0	3.0	NUM
brj-22232	40	7	software	software	NOUN
brj-22232	40	8	(	(	PUNCT
brj-22232	40	9	university	university	NOUN
brj-22232	40	10	of	of	ADP
brj-22232	40	11	edinburgh	edinburgh	PROPN
brj-22232	40	12	,	,	PUNCT
brj-22232	40	13	dr	dr	PROPN
brj-22232	40	14	.	.	PROPN
brj-22232	40	15	antonis	antonis	PROPN
brj-22232	40	16	giannopoulos	giannopoulos	PROPN
brj-22232	40	17	,	,	PUNCT
brj-22232	40	18	uk	uk	PROPN
brj-22232	40	19	)	)	PUNCT
brj-22232	40	20	to	to	PART
brj-22232	40	21	generate	generate	VERB
brj-22232	40	22	simulation	simulation	NOUN
brj-22232	40	23	images	image	NOUN
brj-22232	40	24	to	to	PART
brj-22232	40	25	extend	extend	VERB
brj-22232	40	26	the	the	DET
brj-22232	40	27	dataset	dataset	NOUN
brj-22232	40	28	has	have	AUX
brj-22232	40	29	been	be	AUX
brj-22232	40	30	widely	widely	ADV
brj-22232	40	31	used	use	VERB
brj-22232	40	32	(	(	PUNCT
brj-22232	40	33	todkar	todkar	NOUN
brj-22232	40	34	et	et	PROPN
brj-22232	40	35	al	al	PROPN
brj-22232	40	36	.	.	PROPN
brj-22232	40	37	2021	2021	NUM
brj-22232	40	38	;	;	PUNCT
brj-22232	40	39	dewantara	dewantara	NOUN
brj-22232	40	40	and	and	CCONJ
brj-22232	40	41	parnadi	parnadi	NOUN
brj-22232	40	42	2022	2022	NUM
brj-22232	40	43	)	)	PUNCT
brj-22232	40	44	,	,	PUNCT
brj-22232	40	45	and	and	CCONJ
brj-22232	40	46	the	the	DET
brj-22232	40	47	dataset	dataset	NOUN
brj-22232	40	48	composition	composition	NOUN
brj-22232	40	49	has	have	AUX
brj-22232	40	50	been	be	AUX
brj-22232	40	51	expanded	expand	VERB
brj-22232	40	52	from	from	ADP
brj-22232	40	53	real	real	ADJ
brj-22232	40	54	images	image	NOUN
brj-22232	40	55	to	to	ADP
brj-22232	40	56	a	a	DET
brj-22232	40	57	joint	joint	ADJ
brj-22232	40	58	composition	composition	NOUN
brj-22232	40	59	of	of	ADP
brj-22232	40	60	simulation	simulation	NOUN
brj-22232	40	61	images	image	NOUN
brj-22232	40	62	based	base	VERB
brj-22232	40	63	on	on	ADP
brj-22232	40	64	gprmax	gprmax	PROPN
brj-22232	40	65	3.0	3.0	NUM
brj-22232	40	66	and	and	CCONJ
brj-22232	40	67	real	real	ADJ
brj-22232	40	68	images	image	NOUN
brj-22232	40	69	.	.	PUNCT
brj-22232	41	1	this	this	PRON
brj-22232	41	2	enabled	enable	VERB
brj-22232	41	3	the	the	DET
brj-22232	41	4	expansion	expansion	NOUN
brj-22232	41	5	of	of	ADP
brj-22232	41	6	the	the	DET
brj-22232	41	7	quantity	quantity	NOUN
brj-22232	41	8	and	and	CCONJ
brj-22232	41	9	variety	variety	NOUN
brj-22232	41	10	of	of	ADP
brj-22232	41	11	training	training	NOUN
brj-22232	41	12	data	datum	NOUN
brj-22232	41	13	.	.	PUNCT
brj-22232	42	1	however	however	ADV
brj-22232	42	2	,	,	PUNCT
brj-22232	42	3	the	the	DET
brj-22232	42	4	problem	problem	NOUN
brj-22232	42	5	of	of	ADP
brj-22232	42	6	the	the	DET
brj-22232	42	7	limited	limited	ADJ
brj-22232	42	8	number	number	NOUN
brj-22232	42	9	of	of	ADP
brj-22232	42	10	real	real	ADJ
brj-22232	42	11	datasets	dataset	NOUN
brj-22232	42	12	remains	remain	VERB
brj-22232	42	13	unresolved	unresolved	ADJ
brj-22232	42	14	.	.	PUNCT
brj-22232	43	1	therefore	therefore	ADV
brj-22232	43	2	,	,	PUNCT
brj-22232	43	3	this	this	DET
brj-22232	43	4	paper	paper	NOUN
brj-22232	43	5	used	use	VERB
brj-22232	43	6	cyclegan	cyclegan	NOUN
brj-22232	43	7	(	(	PUNCT
brj-22232	43	8	zhu	zhu	X
brj-22232	43	9	et	et	PROPN
brj-22232	43	10	al	al	PROPN
brj-22232	43	11	.	.	PROPN
brj-22232	43	12	2017	2017	NUM
brj-22232	43	13	)	)	PUNCT
brj-22232	43	14	to	to	PART
brj-22232	43	15	transform	transform	VERB
brj-22232	43	16	the	the	DET
brj-22232	43	17	simulation	simulation	NOUN
brj-22232	43	18	images	image	NOUN
brj-22232	43	19	generated	generate	VERB
brj-22232	43	20	by	by	ADP
brj-22232	43	21	gprmax3.0	gprmax3.0	NOUN
brj-22232	43	22	into	into	ADP
brj-22232	43	23	the	the	DET
brj-22232	43	24	corresponding	corresponding	ADJ
brj-22232	43	25	generated	generate	VERB
brj-22232	43	26	images	image	NOUN
brj-22232	43	27	with	with	ADP
brj-22232	43	28	high	high	ADJ
brj-22232	43	29	similarity	similarity	NOUN
brj-22232	43	30	to	to	ADP
brj-22232	43	31	the	the	DET
brj-22232	43	32	real	real	ADJ
brj-22232	43	33	images	image	NOUN
brj-22232	43	34	,	,	PUNCT
brj-22232	43	35	which	which	PRON
brj-22232	43	36	achieved	achieve	VERB
brj-22232	43	37	the	the	DET
brj-22232	43	38	augmentation	augmentation	NOUN
brj-22232	43	39	of	of	ADP
brj-22232	43	40	the	the	DET
brj-22232	43	41	real	real	ADJ
brj-22232	43	42	dataset	dataset	NOUN
brj-22232	43	43	.	.	PUNCT
brj-22232	44	1	this	this	DET
brj-22232	44	2	method	method	NOUN
brj-22232	44	3	provides	provide	VERB
brj-22232	44	4	an	an	DET
brj-22232	44	5	effective	effective	ADJ
brj-22232	44	6	expansion	expansion	NOUN
brj-22232	44	7	of	of	ADP
brj-22232	44	8	real	real	ADJ
brj-22232	44	9	data	datum	NOUN
brj-22232	44	10	with	with	ADP
brj-22232	44	11	insufficient	insufficient	ADJ
brj-22232	44	12	diversity	diversity	NOUN
brj-22232	44	13	and	and	CCONJ
brj-22232	44	14	helps	help	VERB
brj-22232	44	15	to	to	PART
brj-22232	44	16	improve	improve	VERB
brj-22232	44	17	the	the	DET
brj-22232	44	18	accuracy	accuracy	NOUN
brj-22232	44	19	of	of	ADP
brj-22232	44	20	target	target	NOUN
brj-22232	44	21	detection	detection	NOUN
brj-22232	44	22	methods	method	NOUN
brj-22232	44	23	.	.	PUNCT
brj-22232	45	1	peer	peer	NOUN
brj-22232	45	2	-	-	PUNCT
brj-22232	45	3	reviewed	review	VERB
brj-22232	45	4	article	article	NOUN
brj-22232	45	5	bioresources.com	bioresources.com	X
brj-22232	45	6	li	li	PROPN
brj-22232	45	7	et	et	PROPN
brj-22232	45	8	al	al	PROPN
brj-22232	45	9	.	.	PROPN
brj-22232	45	10	(	(	PUNCT
brj-22232	45	11	2023	2023	NUM
brj-22232	45	12	)	)	PUNCT
brj-22232	45	13	.	.	PUNCT
brj-22232	46	1	“	"	PUNCT
brj-22232	46	2	tree	tree	NOUN
brj-22232	46	3	root	root	NOUN
brj-22232	46	4	detection	detection	NOUN
brj-22232	46	5	training	training	NOUN
brj-22232	46	6	,	,	PUNCT
brj-22232	46	7	”	"	PUNCT
brj-22232	46	8	bioresources	bioresource	NOUN
brj-22232	46	9	18(1	18(1	NOUN
brj-22232	46	10	)	)	PUNCT
brj-22232	46	11	,	,	PUNCT
brj-22232	46	12	484	484	NUM
brj-22232	46	13	-	-	SYM
brj-22232	46	14	504	504	NUM
brj-22232	46	15	.	.	PUNCT
brj-22232	47	1	486	486	NUM
brj-22232	47	2	yolov3	yolov3	NOUN
brj-22232	47	3	and	and	CCONJ
brj-22232	47	4	faster	fast	ADJ
brj-22232	47	5	r	r	X
brj-22232	47	6	-	-	PUNCT
brj-22232	47	7	cnn	cnn	PROPN
brj-22232	47	8	(	(	PUNCT
brj-22232	47	9	ren	ren	NOUN
brj-22232	47	10	et	et	PROPN
brj-22232	47	11	al	al	PROPN
brj-22232	47	12	.	.	PROPN
brj-22232	47	13	2017	2017	NUM
brj-22232	47	14	)	)	PUNCT
brj-22232	47	15	with	with	ADP
brj-22232	47	16	anchor	anchor	NOUN
brj-22232	47	17	-	-	PUNCT
brj-22232	47	18	base	base	NOUN
brj-22232	47	19	are	be	AUX
brj-22232	47	20	the	the	DET
brj-22232	47	21	most	most	ADV
brj-22232	47	22	versatile	versatile	ADJ
brj-22232	47	23	target	target	NOUN
brj-22232	47	24	detection	detection	NOUN
brj-22232	47	25	methods	method	NOUN
brj-22232	47	26	.	.	PUNCT
brj-22232	48	1	yolov3	yolov3	PROPN
brj-22232	48	2	and	and	CCONJ
brj-22232	48	3	faster	fast	ADJ
brj-22232	48	4	r	r	NOUN
brj-22232	48	5	-	-	PUNCT
brj-22232	48	6	cnn	cnn	PROPN
brj-22232	48	7	have	have	AUX
brj-22232	48	8	been	be	AUX
brj-22232	48	9	successfully	successfully	ADV
brj-22232	48	10	applied	apply	VERB
brj-22232	48	11	in	in	ADP
brj-22232	48	12	agriculture	agriculture	NOUN
brj-22232	48	13	(	(	PUNCT
brj-22232	48	14	liu	liu	PROPN
brj-22232	48	15	et	et	PROPN
brj-22232	48	16	al	al	PROPN
brj-22232	48	17	.	.	PROPN
brj-22232	48	18	2020	2020	NUM
brj-22232	48	19	;	;	PUNCT
brj-22232	48	20	thanh	thanh	PROPN
brj-22232	48	21	le	le	X
brj-22232	48	22	et	et	PROPN
brj-22232	48	23	al	al	PROPN
brj-22232	48	24	.	.	PROPN
brj-22232	48	25	2021	2021	NUM
brj-22232	48	26	)	)	PUNCT
brj-22232	48	27	,	,	PUNCT
brj-22232	48	28	geology	geology	NOUN
brj-22232	48	29	(	(	PUNCT
brj-22232	48	30	ma	ma	PROPN
brj-22232	48	31	et	et	PROPN
brj-22232	48	32	al	al	PROPN
brj-22232	48	33	.	.	PROPN
brj-22232	48	34	2019	2019	NUM
brj-22232	48	35	;	;	PUNCT
brj-22232	48	36	davletshin	davletshin	PROPN
brj-22232	48	37	et	et	PROPN
brj-22232	48	38	al	al	PROPN
brj-22232	48	39	.	.	PROPN
brj-22232	48	40	2021	2021	NUM
brj-22232	48	41	)	)	PUNCT
brj-22232	48	42	,	,	PUNCT
brj-22232	48	43	remote	remote	ADJ
brj-22232	48	44	sensing	sensing	NOUN
brj-22232	48	45	(	(	PUNCT
brj-22232	48	46	zhou	zhou	PROPN
brj-22232	48	47	et	et	PROPN
brj-22232	48	48	al	al	PROPN
brj-22232	48	49	.	.	PROPN
brj-22232	48	50	2019	2019	NUM
brj-22232	48	51	;	;	PUNCT
brj-22232	48	52	li	li	PROPN
brj-22232	48	53	et	et	PROPN
brj-22232	48	54	al	al	PROPN
brj-22232	48	55	.	.	PROPN
brj-22232	48	56	2022	2022	NUM
brj-22232	48	57	)	)	PUNCT
brj-22232	48	58	,	,	PUNCT
brj-22232	48	59	and	and	CCONJ
brj-22232	48	60	medicine	medicine	NOUN
brj-22232	48	61	(	(	PUNCT
brj-22232	48	62	rosati	rosati	PROPN
brj-22232	48	63	et	et	PROPN
brj-22232	48	64	al	al	PROPN
brj-22232	48	65	.	.	PROPN
brj-22232	48	66	2020	2020	NUM
brj-22232	48	67	;	;	PUNCT
brj-22232	48	68	yao	yao	PROPN
brj-22232	48	69	et	et	PROPN
brj-22232	48	70	al	al	PROPN
brj-22232	48	71	.	.	PROPN
brj-22232	48	72	2020	2020	NUM
brj-22232	48	73	)	)	PUNCT
brj-22232	48	74	.	.	PUNCT
brj-22232	49	1	yolov3	yolov3	PROPN
brj-22232	49	2	is	be	AUX
brj-22232	49	3	widely	widely	ADV
brj-22232	49	4	used	use	VERB
brj-22232	49	5	in	in	ADP
brj-22232	49	6	forestry	forestry	NOUN
brj-22232	49	7	fields	field	NOUN
brj-22232	49	8	,	,	PUNCT
brj-22232	49	9	such	such	ADJ
brj-22232	49	10	as	as	ADP
brj-22232	49	11	tree	tree	NOUN
brj-22232	49	12	health	health	NOUN
brj-22232	49	13	classification	classification	NOUN
brj-22232	49	14	(	(	PUNCT
brj-22232	49	15	yarak	yarak	PROPN
brj-22232	49	16	et	et	PROPN
brj-22232	49	17	al	al	PROPN
brj-22232	49	18	.	.	PROPN
brj-22232	49	19	2021	2021	NUM
brj-22232	49	20	)	)	PUNCT
brj-22232	49	21	,	,	PUNCT
brj-22232	49	22	forest	forest	NOUN
brj-22232	49	23	census	census	NOUN
brj-22232	49	24	(	(	PUNCT
brj-22232	49	25	zheng	zheng	PROPN
brj-22232	49	26	et	et	PROPN
brj-22232	49	27	al	al	PROPN
brj-22232	49	28	.	.	PROPN
brj-22232	49	29	2019	2019	NUM
brj-22232	49	30	)	)	PUNCT
brj-22232	49	31	,	,	PUNCT
brj-22232	49	32	and	and	CCONJ
brj-22232	49	33	tree	tree	NOUN
brj-22232	49	34	species	specie	NOUN
brj-22232	49	35	identification	identification	NOUN
brj-22232	49	36	for	for	ADP
brj-22232	49	37	detection	detection	NOUN
brj-22232	49	38	.	.	PUNCT
brj-22232	50	1	yolo	yolo	PROPN
brj-22232	50	2	series	series	PROPN
brj-22232	50	3	continues	continue	VERB
brj-22232	50	4	to	to	PART
brj-22232	50	5	evolve	evolve	VERB
brj-22232	50	6	and	and	CCONJ
brj-22232	50	7	improve	improve	VERB
brj-22232	50	8	in	in	ADP
brj-22232	50	9	both	both	PRON
brj-22232	50	10	detection	detection	NOUN
brj-22232	50	11	accuracy	accuracy	NOUN
brj-22232	50	12	and	and	CCONJ
brj-22232	50	13	detection	detection	NOUN
brj-22232	50	14	speed	speed	NOUN
brj-22232	50	15	.	.	PUNCT
brj-22232	51	1	recently	recently	ADV
brj-22232	51	2	,	,	PUNCT
brj-22232	51	3	yolov5	yolov5	NOUN
brj-22232	51	4	and	and	CCONJ
brj-22232	51	5	anchor	anchor	NOUN
brj-22232	51	6	-	-	PUNCT
brj-22232	51	7	free	free	ADJ
brj-22232	51	8	based	base	VERB
brj-22232	51	9	centernet	centernet	NOUN
brj-22232	51	10	are	be	AUX
brj-22232	51	11	being	be	AUX
brj-22232	51	12	used	use	VERB
brj-22232	51	13	in	in	ADP
brj-22232	51	14	a	a	DET
brj-22232	51	15	wide	wide	ADJ
brj-22232	51	16	variety	variety	NOUN
brj-22232	51	17	of	of	ADP
brj-22232	51	18	fields	field	NOUN
brj-22232	51	19	.	.	PUNCT
brj-22232	52	1	in	in	ADP
brj-22232	52	2	this	this	DET
brj-22232	52	3	study	study	NOUN
brj-22232	52	4	,	,	PUNCT
brj-22232	52	5	the	the	DET
brj-22232	52	6	real	real	ADJ
brj-22232	52	7	data	datum	NOUN
brj-22232	52	8	were	be	AUX
brj-22232	52	9	augmented	augment	VERB
brj-22232	52	10	by	by	ADP
brj-22232	52	11	cyclegan	cyclegan	NOUN
brj-22232	52	12	to	to	PART
brj-22232	52	13	obtain	obtain	VERB
brj-22232	52	14	a	a	DET
brj-22232	52	15	mixture	mixture	NOUN
brj-22232	52	16	dataset	dataset	NOUN
brj-22232	52	17	,	,	PUNCT
brj-22232	52	18	and	and	CCONJ
brj-22232	52	19	the	the	DET
brj-22232	52	20	three	three	NUM
brj-22232	52	21	kinds	kind	NOUN
brj-22232	52	22	of	of	ADP
brj-22232	52	23	data	datum	NOUN
brj-22232	52	24	in	in	ADP
brj-22232	52	25	the	the	DET
brj-22232	52	26	mixture	mixture	NOUN
brj-22232	52	27	dataset	dataset	NOUN
brj-22232	52	28	were	be	AUX
brj-22232	52	29	combined	combine	VERB
brj-22232	52	30	to	to	PART
brj-22232	52	31	obtain	obtain	VERB
brj-22232	52	32	seven	seven	NUM
brj-22232	52	33	datasets	dataset	NOUN
brj-22232	52	34	,	,	PUNCT
brj-22232	52	35	while	while	SCONJ
brj-22232	52	36	comparing	compare	VERB
brj-22232	52	37	the	the	DET
brj-22232	52	38	effect	effect	NOUN
brj-22232	52	39	of	of	ADP
brj-22232	52	40	different	different	ADJ
brj-22232	52	41	datasets	dataset	NOUN
brj-22232	52	42	trained	train	VERB
brj-22232	52	43	with	with	ADP
brj-22232	52	44	yolov5	yolov5	NOUN
brj-22232	52	45	.	.	PUNCT
brj-22232	53	1	the	the	DET
brj-22232	53	2	results	result	NOUN
brj-22232	53	3	show	show	VERB
brj-22232	53	4	that	that	SCONJ
brj-22232	53	5	enhanced	enhanced	ADJ
brj-22232	53	6	datasets	dataset	NOUN
brj-22232	53	7	have	have	VERB
brj-22232	53	8	better	well	ADJ
brj-22232	53	9	training	training	NOUN
brj-22232	53	10	and	and	CCONJ
brj-22232	53	11	recognition	recognition	NOUN
brj-22232	53	12	results	result	NOUN
brj-22232	53	13	.	.	PUNCT
brj-22232	54	1	meanwhile	meanwhile	ADV
brj-22232	54	2	,	,	PUNCT
brj-22232	54	3	the	the	DET
brj-22232	54	4	detection	detection	NOUN
brj-22232	54	5	results	result	NOUN
brj-22232	54	6	of	of	ADP
brj-22232	54	7	four	four	NUM
brj-22232	54	8	models	model	NOUN
brj-22232	54	9	,	,	PUNCT
brj-22232	54	10	yolov3	yolov3	PROPN
brj-22232	54	11	,	,	PUNCT
brj-22232	54	12	yolov5	yolov5	NOUN
brj-22232	54	13	,	,	PUNCT
brj-22232	54	14	faster	fast	ADJ
brj-22232	54	15	r	r	NOUN
brj-22232	54	16	-	-	PUNCT
brj-22232	54	17	cnn	cnn	PROPN
brj-22232	54	18	,	,	PUNCT
brj-22232	54	19	and	and	CCONJ
brj-22232	54	20	centernet	centernet	NOUN
brj-22232	54	21	,	,	PUNCT
brj-22232	54	22	were	be	AUX
brj-22232	54	23	compared	compare	VERB
brj-22232	54	24	on	on	ADP
brj-22232	54	25	the	the	DET
brj-22232	54	26	same	same	ADJ
brj-22232	54	27	dataset	dataset	NOUN
brj-22232	54	28	.	.	PUNCT
brj-22232	55	1	the	the	DET
brj-22232	55	2	results	result	NOUN
brj-22232	55	3	show	show	VERB
brj-22232	55	4	that	that	SCONJ
brj-22232	55	5	yolov5	yolov5	NOUN
brj-22232	55	6	was	be	AUX
brj-22232	55	7	highly	highly	ADV
brj-22232	55	8	accurate	accurate	ADJ
brj-22232	55	9	in	in	ADP
brj-22232	55	10	detecting	detect	VERB
brj-22232	55	11	tree	tree	NOUN
brj-22232	55	12	roots	root	NOUN
brj-22232	55	13	.	.	PUNCT
brj-22232	56	1	experimental	experimental	ADJ
brj-22232	56	2	working	working	PROPN
brj-22232	56	3	principle	principle	NOUN
brj-22232	56	4	of	of	ADP
brj-22232	56	5	gpr	gpr	PROPN
brj-22232	56	6	the	the	DET
brj-22232	56	7	principle	principle	NOUN
brj-22232	56	8	of	of	ADP
brj-22232	56	9	gpr	gpr	PROPN
brj-22232	56	10	is	be	AUX
brj-22232	56	11	based	base	VERB
brj-22232	56	12	on	on	ADP
brj-22232	56	13	the	the	DET
brj-22232	56	14	phenomenon	phenomenon	NOUN
brj-22232	56	15	that	that	SCONJ
brj-22232	56	16	electromagnetic	electromagnetic	ADJ
brj-22232	56	17	waves	wave	NOUN
brj-22232	56	18	produce	produce	VERB
brj-22232	56	19	different	different	ADJ
brj-22232	56	20	reflections	reflection	NOUN
brj-22232	56	21	when	when	SCONJ
brj-22232	56	22	they	they	PRON
brj-22232	56	23	act	act	VERB
brj-22232	56	24	on	on	ADP
brj-22232	56	25	materials	material	NOUN
brj-22232	56	26	with	with	ADP
brj-22232	56	27	different	different	ADJ
brj-22232	56	28	dielectric	dielectric	ADJ
brj-22232	56	29	constants	constant	NOUN
brj-22232	56	30	.	.	PUNCT
brj-22232	57	1	figure	figure	NOUN
brj-22232	57	2	1	1	NUM
brj-22232	57	3	shows	show	VERB
brj-22232	57	4	the	the	DET
brj-22232	57	5	"	"	PUNCT
brj-22232	57	6	scan	scan	NOUN
brj-22232	57	7	"	"	PUNCT
brj-22232	57	8	(	(	PUNCT
brj-22232	57	9	a	a	DET
brj-22232	57	10	series	series	NOUN
brj-22232	57	11	of	of	ADP
brj-22232	57	12	reflected	reflect	VERB
brj-22232	57	13	signals	signal	NOUN
brj-22232	57	14	detected	detect	VERB
brj-22232	57	15	)	)	PUNCT
brj-22232	57	16	during	during	ADP
brj-22232	57	17	tree	tree	NOUN
brj-22232	57	18	roots	root	NOUN
brj-22232	57	19	detection	detection	NOUN
brj-22232	57	20	.	.	PUNCT
brj-22232	58	1	the	the	DET
brj-22232	58	2	gpr	gpr	PROPN
brj-22232	58	3	equipment	equipment	NOUN
brj-22232	58	4	moves	move	NOUN
brj-22232	58	5	in	in	ADP
brj-22232	58	6	a	a	DET
brj-22232	58	7	preconfigured	preconfigured	ADJ
brj-22232	58	8	trajectory	trajectory	NOUN
brj-22232	58	9	and	and	CCONJ
brj-22232	58	10	emits	emit	VERB
brj-22232	58	11	electromagnetic	electromagnetic	ADJ
brj-22232	58	12	waves	wave	NOUN
brj-22232	58	13	to	to	ADP
brj-22232	58	14	the	the	DET
brj-22232	58	15	ground	ground	NOUN
brj-22232	58	16	,	,	PUNCT
brj-22232	58	17	the	the	DET
brj-22232	58	18	electromagnetic	electromagnetic	ADJ
brj-22232	58	19	waves	wave	NOUN
brj-22232	58	20	are	be	AUX
brj-22232	58	21	partially	partially	ADV
brj-22232	58	22	reflected	reflect	VERB
brj-22232	58	23	at	at	ADP
brj-22232	58	24	the	the	DET
brj-22232	58	25	roots	root	NOUN
brj-22232	58	26	and	and	CCONJ
brj-22232	58	27	soil	soil	NOUN
brj-22232	58	28	interface	interface	NOUN
brj-22232	58	29	,	,	PUNCT
brj-22232	58	30	and	and	CCONJ
brj-22232	58	31	the	the	DET
brj-22232	58	32	rest	rest	NOUN
brj-22232	58	33	of	of	ADP
brj-22232	58	34	the	the	DET
brj-22232	58	35	electromagnetic	electromagnetic	ADJ
brj-22232	58	36	waves	wave	NOUN
brj-22232	58	37	continue	continue	VERB
brj-22232	58	38	to	to	PART
brj-22232	58	39	propagate	propagate	VERB
brj-22232	58	40	downward	downward	ADV
brj-22232	58	41	until	until	SCONJ
brj-22232	58	42	the	the	DET
brj-22232	58	43	signal	signal	NOUN
brj-22232	58	44	is	be	AUX
brj-22232	58	45	fully	fully	ADV
brj-22232	58	46	attenuated	attenuate	VERB
brj-22232	58	47	,	,	PUNCT
brj-22232	58	48	as	as	ADP
brj-22232	58	49	in	in	ADP
brj-22232	58	50	fig	fig	NOUN
brj-22232	58	51	.	.	PUNCT
brj-22232	59	1	1a	1a	PROPN
brj-22232	59	2	.	.	PUNCT
brj-22232	60	1	after	after	ADP
brj-22232	60	2	receiving	receive	VERB
brj-22232	60	3	the	the	DET
brj-22232	60	4	reflected	reflect	VERB
brj-22232	60	5	electromagnetic	electromagnetic	ADJ
brj-22232	60	6	waves	wave	NOUN
brj-22232	60	7	from	from	ADP
brj-22232	60	8	the	the	DET
brj-22232	60	9	roots	root	NOUN
brj-22232	60	10	,	,	PUNCT
brj-22232	60	11	the	the	DET
brj-22232	60	12	receiving	receive	VERB
brj-22232	60	13	antenna	antenna	NOUN
brj-22232	60	14	records	record	VERB
brj-22232	60	15	the	the	DET
brj-22232	60	16	electric	electric	ADJ
brj-22232	60	17	field	field	NOUN
brj-22232	60	18	intensity	intensity	NOUN
brj-22232	60	19	change	change	NOUN
brj-22232	60	20	of	of	ADP
brj-22232	60	21	the	the	DET
brj-22232	60	22	reflected	reflect	VERB
brj-22232	60	23	waves	wave	NOUN
brj-22232	60	24	in	in	ADP
brj-22232	60	25	the	the	DET
brj-22232	60	26	time	time	NOUN
brj-22232	60	27	domain	domain	NOUN
brj-22232	60	28	,	,	PUNCT
brj-22232	60	29	forming	form	VERB
brj-22232	60	30	an	an	DET
brj-22232	60	31	a	a	PRON
brj-22232	60	32	-	-	PUNCT
brj-22232	60	33	scan	scan	ADJ
brj-22232	60	34	curve	curve	NOUN
brj-22232	60	35	of	of	ADP
brj-22232	60	36	the	the	DET
brj-22232	60	37	field	field	NOUN
brj-22232	60	38	intensity	intensity	NOUN
brj-22232	60	39	change	change	NOUN
brj-22232	60	40	with	with	ADP
brj-22232	60	41	time	time	NOUN
brj-22232	60	42	as	as	ADP
brj-22232	60	43	in	in	ADP
brj-22232	60	44	fig	fig	NOUN
brj-22232	60	45	.	.	PUNCT
brj-22232	61	1	2a	2a	NUM
brj-22232	61	2	.	.	PUNCT
brj-22232	62	1	fig	fig	NOUN
brj-22232	62	2	.	.	PUNCT
brj-22232	63	1	1	1	X
brj-22232	63	2	.	.	X
brj-22232	63	3	ground	ground	NOUN
brj-22232	63	4	-	-	PUNCT
brj-22232	63	5	penetrating	penetrate	VERB
brj-22232	63	6	radar	radar	NOUN
brj-22232	63	7	object	object	NOUN
brj-22232	63	8	detection	detection	NOUN
brj-22232	63	9	imaging	image	VERB
brj-22232	63	10	principle	principle	NOUN
brj-22232	63	11	graph	graph	NOUN
brj-22232	63	12	(	(	PUNCT
brj-22232	63	13	a	a	X
brj-22232	63	14	)	)	PUNCT
brj-22232	63	15	the	the	DET
brj-22232	63	16	radar	radar	NOUN
brj-22232	63	17	signal	signal	NOUN
brj-22232	63	18	is	be	AUX
brj-22232	63	19	reflected	reflect	VERB
brj-22232	63	20	by	by	ADP
brj-22232	63	21	the	the	DET
brj-22232	63	22	buried	bury	VERB
brj-22232	63	23	object	object	NOUN
brj-22232	63	24	at	at	ADP
brj-22232	63	25	positions	position	NOUN
brj-22232	63	26	(	(	PUNCT
brj-22232	63	27	x0	x0	PROPN
brj-22232	63	28	,	,	PUNCT
brj-22232	63	29	x1	x1	PROPN
brj-22232	63	30	,	,	PUNCT
brj-22232	63	31	and	and	CCONJ
brj-22232	63	32	x2	x2	NUM
brj-22232	63	33	)	)	PUNCT
brj-22232	63	34	,	,	PUNCT
brj-22232	63	35	and	and	CCONJ
brj-22232	63	36	the	the	DET
brj-22232	63	37	reflection	reflection	NOUN
brj-22232	63	38	time(t1	time(t1	NOUN
brj-22232	63	39	,	,	PUNCT
brj-22232	63	40	t2	t2	NOUN
brj-22232	63	41	,	,	PUNCT
brj-22232	63	42	and	and	CCONJ
brj-22232	63	43	t3	t3	PROPN
brj-22232	63	44	)	)	PUNCT
brj-22232	63	45	is	be	AUX
brj-22232	63	46	recorded	record	VERB
brj-22232	63	47	and	and	CCONJ
brj-22232	63	48	plotted	plot	VERB
brj-22232	63	49	below	below	ADP
brj-22232	63	50	the	the	DET
brj-22232	63	51	radar	radar	NOUN
brj-22232	63	52	.	.	PUNCT
brj-22232	64	1	(	(	PUNCT
brj-22232	64	2	b	b	X
brj-22232	64	3	)	)	PUNCT
brj-22232	64	4	different	different	ADJ
brj-22232	64	5	a	a	DET
brj-22232	64	6	-	-	PUNCT
brj-22232	64	7	scans	scan	NOUN
brj-22232	64	8	form	form	VERB
brj-22232	64	9	a	a	DET
brj-22232	64	10	reflection	reflection	NOUN
brj-22232	64	11	hyperbola	hyperbola	NOUN
brj-22232	64	12	during	during	ADP
brj-22232	64	13	the	the	DET
brj-22232	64	14	movement	movement	NOUN
brj-22232	64	15	.	.	PUNCT
brj-22232	65	1	peer	peer	NOUN
brj-22232	65	2	-	-	PUNCT
brj-22232	65	3	reviewed	review	VERB
brj-22232	65	4	article	article	NOUN
brj-22232	65	5	bioresources.com	bioresources.com	X
brj-22232	65	6	li	li	PROPN
brj-22232	65	7	et	et	PROPN
brj-22232	65	8	al	al	PROPN
brj-22232	65	9	.	.	PROPN
brj-22232	65	10	(	(	PUNCT
brj-22232	65	11	2023	2023	NUM
brj-22232	65	12	)	)	PUNCT
brj-22232	65	13	.	.	PUNCT
brj-22232	66	1	“	"	PUNCT
brj-22232	66	2	tree	tree	NOUN
brj-22232	66	3	root	root	NOUN
brj-22232	66	4	detection	detection	NOUN
brj-22232	66	5	training	training	NOUN
brj-22232	66	6	,	,	PUNCT
brj-22232	66	7	”	"	PUNCT
brj-22232	66	8	bioresources	bioresource	NOUN
brj-22232	66	9	18(1	18(1	NOUN
brj-22232	66	10	)	)	PUNCT
brj-22232	66	11	,	,	PUNCT
brj-22232	66	12	484	484	NUM
brj-22232	66	13	-	-	SYM
brj-22232	66	14	504	504	NUM
brj-22232	66	15	.	.	PUNCT
brj-22232	67	1	487	487	NUM
brj-22232	67	2	fig	fig	NOUN
brj-22232	67	3	.	.	PUNCT
brj-22232	68	1	2	2	X
brj-22232	68	2	.	.	X
brj-22232	68	3	a	a	DET
brj-22232	68	4	sample	sample	NOUN
brj-22232	68	5	of	of	ADP
brj-22232	68	6	real	real	ADJ
brj-22232	68	7	data	datum	NOUN
brj-22232	68	8	:	:	PUNCT
brj-22232	68	9	(	(	PUNCT
brj-22232	68	10	a	a	X
brj-22232	68	11	)	)	PUNCT
brj-22232	68	12	an	an	DET
brj-22232	68	13	a	a	PRON
brj-22232	68	14	-	-	PUNCT
brj-22232	68	15	scan	scan	ADJ
brj-22232	68	16	signal	signal	NOUN
brj-22232	68	17	curve	curve	NOUN
brj-22232	68	18	(	(	PUNCT
brj-22232	68	19	b	b	NOUN
brj-22232	68	20	)	)	PUNCT
brj-22232	68	21	a	a	DET
brj-22232	68	22	real	real	ADJ
brj-22232	68	23	b	b	NOUN
brj-22232	68	24	-	-	PUNCT
brj-22232	68	25	scan	scan	ADJ
brj-22232	68	26	image	image	NOUN
brj-22232	68	27	when	when	SCONJ
brj-22232	68	28	the	the	DET
brj-22232	68	29	transmitting	transmitting	NOUN
brj-22232	68	30	and	and	CCONJ
brj-22232	68	31	receiving	receive	VERB
brj-22232	68	32	antennas	antenna	NOUN
brj-22232	68	33	transmit	transmit	VERB
brj-22232	68	34	electromagnetic	electromagnetic	ADJ
brj-22232	68	35	waves	wave	NOUN
brj-22232	68	36	to	to	ADP
brj-22232	68	37	the	the	DET
brj-22232	68	38	ground	ground	NOUN
brj-22232	68	39	once	once	ADV
brj-22232	68	40	at	at	ADP
brj-22232	68	41	x0	x0	PROPN
brj-22232	68	42	of	of	ADP
brj-22232	68	43	fig	fig	NOUN
brj-22232	68	44	.	.	PUNCT
brj-22232	69	1	1a	1a	NOUN
brj-22232	69	2	,	,	PUNCT
brj-22232	69	3	the	the	DET
brj-22232	69	4	a	a	PRON
brj-22232	69	5	-	-	PUNCT
brj-22232	69	6	scan	scan	ADJ
brj-22232	69	7	plot	plot	NOUN
brj-22232	69	8	of	of	ADP
brj-22232	69	9	the	the	DET
brj-22232	69	10	x0	x0	PROPN
brj-22232	69	11	in	in	ADP
brj-22232	69	12	fig	fig	NOUN
brj-22232	69	13	.	.	PUNCT
brj-22232	70	1	1b	1b	PROPN
brj-22232	70	2	is	be	AUX
brj-22232	70	3	recorded	record	VERB
brj-22232	70	4	by	by	ADP
brj-22232	70	5	the	the	DET
brj-22232	70	6	receiving	receive	VERB
brj-22232	70	7	antenna	antenna	NOUN
brj-22232	70	8	.	.	PUNCT
brj-22232	71	1	when	when	SCONJ
brj-22232	71	2	the	the	DET
brj-22232	71	3	gpr	gpr	PROPN
brj-22232	71	4	moves	move	VERB
brj-22232	71	5	backward	backward	ADV
brj-22232	71	6	in	in	ADP
brj-22232	71	7	equal	equal	ADJ
brj-22232	71	8	steps	step	NOUN
brj-22232	71	9	and	and	CCONJ
brj-22232	71	10	transmits	transmit	VERB
brj-22232	71	11	electromagnetic	electromagnetic	ADJ
brj-22232	71	12	waves	wave	NOUN
brj-22232	71	13	to	to	ADP
brj-22232	71	14	the	the	DET
brj-22232	71	15	ground	ground	NOUN
brj-22232	71	16	,	,	PUNCT
brj-22232	71	17	a	a	DET
brj-22232	71	18	set	set	NOUN
brj-22232	71	19	of	of	ADP
brj-22232	71	20	a	a	DET
brj-22232	71	21	-	-	PUNCT
brj-22232	71	22	scan	scan	ADJ
brj-22232	71	23	curves	curve	NOUN
brj-22232	71	24	of	of	ADP
brj-22232	71	25	the	the	DET
brj-22232	71	26	field	field	NOUN
brj-22232	71	27	intensity	intensity	NOUN
brj-22232	71	28	change	change	NOUN
brj-22232	71	29	caused	cause	VERB
brj-22232	71	30	by	by	ADP
brj-22232	71	31	the	the	DET
brj-22232	71	32	reflected	reflect	VERB
brj-22232	71	33	electromagnetic	electromagnetic	ADJ
brj-22232	71	34	waves	wave	NOUN
brj-22232	71	35	from	from	ADP
brj-22232	71	36	the	the	DET
brj-22232	71	37	tree	tree	NOUN
brj-22232	71	38	roots	root	NOUN
brj-22232	71	39	is	be	AUX
brj-22232	71	40	recorded	record	VERB
brj-22232	71	41	.	.	PUNCT
brj-22232	72	1	merging	merge	VERB
brj-22232	72	2	this	this	DET
brj-22232	72	3	set	set	NOUN
brj-22232	72	4	of	of	ADP
brj-22232	72	5	a	a	DET
brj-22232	72	6	-	-	PUNCT
brj-22232	72	7	scan	scan	ADJ
brj-22232	72	8	curves	curve	NOUN
brj-22232	72	9	to	to	PART
brj-22232	72	10	form	form	VERB
brj-22232	72	11	the	the	DET
brj-22232	72	12	curve	curve	NOUN
brj-22232	72	13	in	in	ADP
brj-22232	72	14	fig	fig	NOUN
brj-22232	72	15	.	.	PUNCT
brj-22232	73	1	1b	1b	NUM
brj-22232	73	2	,	,	PUNCT
brj-22232	73	3	which	which	PRON
brj-22232	73	4	is	be	AUX
brj-22232	73	5	the	the	DET
brj-22232	73	6	b	b	PROPN
brj-22232	73	7	-	-	PUNCT
brj-22232	73	8	scan	scan	ADJ
brj-22232	73	9	image	image	NOUN
brj-22232	73	10	,	,	PUNCT
brj-22232	73	11	and	and	CCONJ
brj-22232	73	12	a	a	DET
brj-22232	73	13	true	true	ADJ
brj-22232	73	14	bscan	bscan	NOUN
brj-22232	73	15	image	image	NOUN
brj-22232	73	16	is	be	AUX
brj-22232	73	17	displayed	display	VERB
brj-22232	73	18	in	in	ADP
brj-22232	73	19	fig	fig	NOUN
brj-22232	73	20	.	.	PUNCT
brj-22232	74	1	2b	2b	NUM
brj-22232	74	2	.	.	PUNCT
brj-22232	75	1	image	image	NOUN
brj-22232	75	2	acquisition	acquisition	NOUN
brj-22232	75	3	the	the	DET
brj-22232	75	4	trees	tree	NOUN
brj-22232	75	5	detected	detect	VERB
brj-22232	75	6	in	in	ADP
brj-22232	75	7	this	this	DET
brj-22232	75	8	paper	paper	NOUN
brj-22232	75	9	were	be	AUX
brj-22232	75	10	mainly	mainly	ADV
brj-22232	75	11	distributed	distribute	VERB
brj-22232	75	12	in	in	ADP
brj-22232	75	13	beijing	beijing	PROPN
brj-22232	75	14	,	,	PUNCT
brj-22232	75	15	shandong	shandong	PROPN
brj-22232	75	16	,	,	PUNCT
brj-22232	75	17	zhejiang	zhejiang	PROPN
brj-22232	75	18	,	,	PUNCT
brj-22232	75	19	etc	etc	X
brj-22232	75	20	.	.	X
brj-22232	76	1	the	the	DET
brj-22232	76	2	detection	detection	NOUN
brj-22232	76	3	species	specie	NOUN
brj-22232	76	4	mainly	mainly	ADV
brj-22232	76	5	include	include	VERB
brj-22232	76	6	willow	willow	NOUN
brj-22232	76	7	,	,	PUNCT
brj-22232	76	8	pine	pine	NOUN
brj-22232	76	9	,	,	PUNCT
brj-22232	76	10	cypress	cypress	PROPN
brj-22232	76	11	,	,	PUNCT
brj-22232	76	12	etc	etc	X
brj-22232	76	13	.	.	X
brj-22232	77	1	the	the	DET
brj-22232	77	2	measured	measure	VERB
brj-22232	77	3	trees	tree	NOUN
brj-22232	77	4	were	be	AUX
brj-22232	77	5	all	all	PRON
brj-22232	77	6	isolated	isolate	VERB
brj-22232	77	7	trees	tree	NOUN
brj-22232	77	8	within	within	ADP
brj-22232	77	9	a	a	DET
brj-22232	77	10	5	5	NUM
brj-22232	77	11	m	m	NOUN
brj-22232	77	12	radius	radius	NOUN
brj-22232	77	13	,	,	PUNCT
brj-22232	77	14	ensuring	ensure	VERB
brj-22232	77	15	that	that	SCONJ
brj-22232	77	16	the	the	DET
brj-22232	77	17	detected	detect	VERB
brj-22232	77	18	roots	root	NOUN
brj-22232	77	19	were	be	AUX
brj-22232	77	20	all	all	PRON
brj-22232	77	21	associated	associate	VERB
brj-22232	77	22	with	with	ADP
brj-22232	77	23	specific	specific	ADJ
brj-22232	77	24	trees	tree	NOUN
brj-22232	77	25	.	.	PUNCT
brj-22232	78	1	the	the	DET
brj-22232	78	2	tree	tree	NOUN
brj-22232	78	3	information	information	NOUN
brj-22232	78	4	was	be	AUX
brj-22232	78	5	uploaded	upload	VERB
brj-22232	78	6	to	to	ADP
brj-22232	78	7	the	the	DET
brj-22232	78	8	built	build	VERB
brj-22232	78	9	website	website	NOUN
brj-22232	78	10	as	as	SCONJ
brj-22232	78	11	shown	show	VERB
brj-22232	78	12	in	in	ADP
brj-22232	78	13	fig	fig	NOUN
brj-22232	78	14	.	.	PUNCT
brj-22232	79	1	3	3	X
brj-22232	79	2	.	.	X
brj-22232	79	3	fig	fig	NOUN
brj-22232	79	4	.	.	PUNCT
brj-22232	80	1	3	3	X
brj-22232	80	2	.	.	X
brj-22232	81	1	all	all	DET
brj-22232	81	2	trees	tree	NOUN
brj-22232	81	3	displayed	display	VERB
brj-22232	81	4	on	on	ADP
brj-22232	81	5	the	the	DET
brj-22232	81	6	map	map	NOUN
brj-22232	81	7	the	the	DET
brj-22232	81	8	detection	detection	NOUN
brj-22232	81	9	images	image	NOUN
brj-22232	81	10	of	of	ADP
brj-22232	81	11	nearly	nearly	ADV
brj-22232	81	12	one	one	NUM
brj-22232	81	13	hundred	hundred	NUM
brj-22232	81	14	trees	tree	NOUN
brj-22232	81	15	'	'	PART
brj-22232	81	16	root	root	NOUN
brj-22232	81	17	systems	system	NOUN
brj-22232	81	18	were	be	AUX
brj-22232	81	19	selected	select	VERB
brj-22232	81	20	as	as	ADP
brj-22232	81	21	the	the	DET
brj-22232	81	22	real	real	ADJ
brj-22232	81	23	dataset	dataset	NOUN
brj-22232	81	24	in	in	ADP
brj-22232	81	25	the	the	DET
brj-22232	81	26	experiment	experiment	NOUN
brj-22232	81	27	.	.	PUNCT
brj-22232	82	1	tru	tru	PROPN
brj-22232	82	2	tree	tree	PROPN
brj-22232	82	3	radar	radar	NOUN
brj-22232	82	4	,	,	PUNCT
brj-22232	82	5	which	which	PRON
brj-22232	82	6	is	be	AUX
brj-22232	82	7	more	more	ADV
brj-22232	82	8	compatible	compatible	ADJ
brj-22232	82	9	with	with	ADP
brj-22232	82	10	the	the	DET
brj-22232	82	11	characteristics	characteristic	NOUN
brj-22232	82	12	of	of	ADP
brj-22232	82	13	tree	tree	NOUN
brj-22232	82	14	roots	root	NOUN
brj-22232	82	15	,	,	PUNCT
brj-22232	82	16	was	be	AUX
brj-22232	82	17	chosen	choose	VERB
brj-22232	82	18	as	as	ADP
brj-22232	82	19	the	the	DET
brj-22232	82	20	collection	collection	NOUN
brj-22232	82	21	equipment	equipment	NOUN
brj-22232	82	22	(	(	PUNCT
brj-22232	82	23	sir3000	sir3000	PROPN
brj-22232	82	24	t	t	PROPN
brj-22232	82	25	,	,	PUNCT
brj-22232	82	26	gssi	gssi	NOUN
brj-22232	82	27	,	,	PUNCT
brj-22232	82	28	peer	peer	NOUN
brj-22232	82	29	-	-	PUNCT
brj-22232	82	30	reviewed	review	VERB
brj-22232	82	31	article	article	NOUN
brj-22232	82	32	bioresources.com	bioresources.com	X
brj-22232	82	33	li	li	PROPN
brj-22232	82	34	et	et	PROPN
brj-22232	82	35	al	al	PROPN
brj-22232	82	36	.	.	PROPN
brj-22232	83	1	(	(	PUNCT
brj-22232	83	2	2023	2023	NUM
brj-22232	83	3	)	)	PUNCT
brj-22232	83	4	.	.	PUNCT
brj-22232	84	1	“	"	PUNCT
brj-22232	84	2	tree	tree	NOUN
brj-22232	84	3	root	root	NOUN
brj-22232	84	4	detection	detection	NOUN
brj-22232	84	5	training	training	NOUN
brj-22232	84	6	,	,	PUNCT
brj-22232	84	7	”	"	PUNCT
brj-22232	84	8	bioresources	bioresource	NOUN
brj-22232	84	9	18(1	18(1	NOUN
brj-22232	84	10	)	)	PUNCT
brj-22232	84	11	,	,	PUNCT
brj-22232	84	12	484	484	NUM
brj-22232	84	13	-	-	SYM
brj-22232	84	14	504	504	NUM
brj-22232	84	15	.	.	PUNCT
brj-22232	85	1	488	488	NUM
brj-22232	85	2	usa	usa	NOUN
brj-22232	85	3	)	)	PUNCT
brj-22232	85	4	.	.	PUNCT
brj-22232	86	1	in	in	ADP
brj-22232	86	2	practical	practical	ADJ
brj-22232	86	3	applications	application	NOUN
brj-22232	86	4	,	,	PUNCT
brj-22232	86	5	the	the	DET
brj-22232	86	6	antenna	antenna	NOUN
brj-22232	86	7	frequency	frequency	NOUN
brj-22232	86	8	of	of	ADP
brj-22232	86	9	900	900	NUM
brj-22232	86	10	mhz	mhz	NOUN
brj-22232	86	11	was	be	AUX
brj-22232	86	12	selected	select	VERB
brj-22232	86	13	,	,	PUNCT
brj-22232	86	14	its	its	PRON
brj-22232	86	15	maximal	maximal	ADJ
brj-22232	86	16	depth	depth	NOUN
brj-22232	86	17	of	of	ADP
brj-22232	86	18	detection	detection	NOUN
brj-22232	86	19	was	be	AUX
brj-22232	86	20	approximately	approximately	ADV
brj-22232	86	21	1	1	NUM
brj-22232	86	22	m	m	NOUN
brj-22232	86	23	,	,	PUNCT
brj-22232	86	24	and	and	CCONJ
brj-22232	86	25	the	the	DET
brj-22232	86	26	tracking	tracking	NOUN
brj-22232	86	27	interval	interval	NOUN
brj-22232	86	28	and	and	CCONJ
brj-22232	86	29	number	number	NOUN
brj-22232	86	30	of	of	ADP
brj-22232	86	31	samples	sample	NOUN
brj-22232	86	32	were	be	AUX
brj-22232	86	33	5	5	NUM
brj-22232	86	34	mm	mm	NOUN
brj-22232	86	35	and	and	CCONJ
brj-22232	86	36	512	512	NUM
brj-22232	86	37	,	,	PUNCT
brj-22232	86	38	respectively	respectively	ADV
brj-22232	86	39	.	.	PUNCT
brj-22232	87	1	meanwhile	meanwhile	ADV
brj-22232	87	2	,	,	PUNCT
brj-22232	87	3	the	the	DET
brj-22232	87	4	authors	author	NOUN
brj-22232	87	5	used	use	VERB
brj-22232	87	6	a	a	DET
brj-22232	87	7	detection	detection	NOUN
brj-22232	87	8	radius	radius	NOUN
brj-22232	87	9	between	between	ADP
brj-22232	87	10	0.1	0.1	NUM
brj-22232	87	11	m	m	NOUN
brj-22232	87	12	and	and	CCONJ
brj-22232	87	13	3.8	3.8	NUM
brj-22232	87	14	m	m	NOUN
brj-22232	87	15	,	,	PUNCT
brj-22232	87	16	detection	detection	NOUN
brj-22232	87	17	depth	depth	NOUN
brj-22232	87	18	of	of	ADP
brj-22232	87	19	0.6	0.6	NUM
brj-22232	87	20	m	m	NOUN
brj-22232	87	21	,	,	PUNCT
brj-22232	87	22	and	and	CCONJ
brj-22232	87	23	0.75	0.75	NUM
brj-22232	87	24	m	m	VERB
brj-22232	87	25	for	for	ADP
brj-22232	87	26	on	on	ADP
brj-22232	87	27	-	-	PUNCT
brj-22232	87	28	site	site	NOUN
brj-22232	87	29	detection	detection	NOUN
brj-22232	87	30	.	.	PUNCT
brj-22232	88	1	dataset	dataset	NOUN
brj-22232	88	2	construction	construction	NOUN
brj-22232	88	3	the	the	DET
brj-22232	88	4	composition	composition	NOUN
brj-22232	88	5	of	of	ADP
brj-22232	88	6	gpr	gpr	PROPN
brj-22232	88	7	image	image	NOUN
brj-22232	88	8	dataset	dataset	NOUN
brj-22232	88	9	consisted	consist	VERB
brj-22232	88	10	of	of	ADP
brj-22232	88	11	four	four	NUM
brj-22232	88	12	parts	part	NOUN
brj-22232	88	13	:	:	PUNCT
brj-22232	88	14	acquisition	acquisition	NOUN
brj-22232	88	15	of	of	ADP
brj-22232	88	16	real	real	ADJ
brj-22232	88	17	data	datum	NOUN
brj-22232	88	18	,	,	PUNCT
brj-22232	88	19	simulated	simulate	VERB
brj-22232	88	20	data	data	NOUN
brj-22232	88	21	generation	generation	NOUN
brj-22232	88	22	,	,	PUNCT
brj-22232	88	23	enhanced	enhance	VERB
brj-22232	88	24	data	data	NOUN
brj-22232	88	25	generation	generation	NOUN
brj-22232	88	26	,	,	PUNCT
brj-22232	88	27	and	and	CCONJ
brj-22232	88	28	data	datum	NOUN
brj-22232	88	29	combination	combination	NOUN
brj-22232	88	30	.	.	PUNCT
brj-22232	89	1	the	the	DET
brj-22232	89	2	whole	whole	ADJ
brj-22232	89	3	process	process	NOUN
brj-22232	89	4	is	be	AUX
brj-22232	89	5	shown	show	VERB
brj-22232	89	6	in	in	ADP
brj-22232	89	7	fig	fig	NOUN
brj-22232	89	8	.	.	PUNCT
brj-22232	90	1	4	4	X
brj-22232	90	2	.	.	X
brj-22232	90	3	fig	fig	NOUN
brj-22232	90	4	.	.	PUNCT
brj-22232	91	1	4	4	X
brj-22232	91	2	.	.	X
brj-22232	92	1	the	the	DET
brj-22232	92	2	four	four	NUM
brj-22232	92	3	parts	part	NOUN
brj-22232	92	4	of	of	ADP
brj-22232	92	5	the	the	DET
brj-22232	92	6	dataset	dataset	NOUN
brj-22232	92	7	construction	construction	NOUN
brj-22232	92	8	.	.	PUNCT
brj-22232	93	1	the	the	DET
brj-22232	93	2	first	first	ADJ
brj-22232	93	3	section	section	NOUN
brj-22232	93	4	is	be	AUX
brj-22232	93	5	the	the	DET
brj-22232	93	6	real	real	ADJ
brj-22232	93	7	data	datum	NOUN
brj-22232	93	8	acquisition	acquisition	NOUN
brj-22232	93	9	,	,	PUNCT
brj-22232	93	10	which	which	PRON
brj-22232	93	11	introduces	introduce	VERB
brj-22232	93	12	the	the	DET
brj-22232	93	13	way	way	NOUN
brj-22232	93	14	to	to	PART
brj-22232	93	15	acquire	acquire	VERB
brj-22232	93	16	gpr	gpr	PROPN
brj-22232	93	17	b	b	X
brj-22232	93	18	-	-	PUNCT
brj-22232	93	19	scan	scan	ADJ
brj-22232	93	20	images	image	NOUN
brj-22232	93	21	.	.	PUNCT
brj-22232	94	1	the	the	DET
brj-22232	94	2	second	second	ADJ
brj-22232	94	3	section	section	NOUN
brj-22232	94	4	is	be	AUX
brj-22232	94	5	the	the	DET
brj-22232	94	6	generation	generation	NOUN
brj-22232	94	7	of	of	ADP
brj-22232	94	8	simulation	simulation	NOUN
brj-22232	94	9	data	datum	NOUN
brj-22232	94	10	by	by	ADP
brj-22232	94	11	gprmax	gprmax	PROPN
brj-22232	94	12	.	.	PUNCT
brj-22232	95	1	the	the	DET
brj-22232	95	2	third	third	ADJ
brj-22232	95	3	section	section	NOUN
brj-22232	95	4	is	be	AUX
brj-22232	95	5	data	datum	NOUN
brj-22232	95	6	augmentation	augmentation	NOUN
brj-22232	95	7	.	.	PUNCT
brj-22232	96	1	the	the	DET
brj-22232	96	2	fourth	fourth	ADJ
brj-22232	96	3	section	section	NOUN
brj-22232	96	4	utilizes	utilize	VERB
brj-22232	96	5	the	the	DET
brj-22232	96	6	three	three	NUM
brj-22232	96	7	kinds	kind	NOUN
brj-22232	96	8	of	of	ADP
brj-22232	96	9	data	datum	NOUN
brj-22232	96	10	and	and	CCONJ
brj-22232	96	11	constructs	construct	VERB
brj-22232	96	12	a	a	DET
brj-22232	96	13	hybrid	hybrid	ADJ
brj-22232	96	14	dataset	dataset	NOUN
brj-22232	96	15	.	.	PUNCT
brj-22232	97	1	acquisition	acquisition	NOUN
brj-22232	97	2	of	of	ADP
brj-22232	97	3	real	real	ADJ
brj-22232	97	4	data	datum	NOUN
brj-22232	97	5	to	to	PART
brj-22232	97	6	ensure	ensure	VERB
brj-22232	97	7	the	the	DET
brj-22232	97	8	quality	quality	NOUN
brj-22232	97	9	of	of	ADP
brj-22232	97	10	the	the	DET
brj-22232	97	11	real	real	ADJ
brj-22232	97	12	dataset	dataset	NOUN
brj-22232	97	13	,	,	PUNCT
brj-22232	97	14	the	the	DET
brj-22232	97	15	obtained	obtain	VERB
brj-22232	97	16	real	real	ADJ
brj-22232	97	17	images	image	NOUN
brj-22232	97	18	were	be	AUX
brj-22232	97	19	preprocessed	preprocesse	VERB
brj-22232	97	20	.	.	PUNCT
brj-22232	98	1	nearly	nearly	ADV
brj-22232	98	2	one	one	NUM
brj-22232	98	3	thousand	thousand	NUM
brj-22232	98	4	b	b	NOUN
brj-22232	98	5	-	-	PUNCT
brj-22232	98	6	scan	scan	ADJ
brj-22232	98	7	images	image	NOUN
brj-22232	98	8	of	of	ADP
brj-22232	98	9	tree	tree	NOUN
brj-22232	98	10	roots	root	NOUN
brj-22232	98	11	were	be	AUX
brj-22232	98	12	screened	screen	VERB
brj-22232	98	13	,	,	PUNCT
brj-22232	98	14	all	all	PRON
brj-22232	98	15	with	with	ADP
brj-22232	98	16	a	a	DET
brj-22232	98	17	height	height	NOUN
brj-22232	98	18	of	of	ADP
brj-22232	98	19	512	512	NUM
brj-22232	98	20	pixels	pixel	NOUN
brj-22232	98	21	and	and	CCONJ
brj-22232	98	22	a	a	DET
brj-22232	98	23	width	width	NOUN
brj-22232	98	24	ranging	range	VERB
brj-22232	98	25	from	from	ADP
brj-22232	98	26	148	148	NUM
brj-22232	98	27	to	to	ADP
brj-22232	98	28	3816	3816	NUM
brj-22232	98	29	pixels	pixel	NOUN
brj-22232	98	30	.	.	PUNCT
brj-22232	99	1	to	to	PART
brj-22232	99	2	ensure	ensure	VERB
brj-22232	99	3	the	the	DET
brj-22232	99	4	consistency	consistency	NOUN
brj-22232	99	5	of	of	ADP
brj-22232	99	6	data	datum	NOUN
brj-22232	99	7	size	size	NOUN
brj-22232	99	8	,	,	PUNCT
brj-22232	99	9	336	336	NUM
brj-22232	99	10	high	high	ADJ
brj-22232	99	11	-	-	PUNCT
brj-22232	99	12	quality	quality	NOUN
brj-22232	99	13	data	datum	NOUN
brj-22232	99	14	images	image	NOUN
brj-22232	99	15	were	be	AUX
brj-22232	99	16	obtained	obtain	VERB
brj-22232	99	17	by	by	ADP
brj-22232	99	18	discarding	discard	VERB
brj-22232	99	19	images	image	NOUN
brj-22232	99	20	with	with	ADP
brj-22232	99	21	widths	width	NOUN
brj-22232	99	22	less	less	ADJ
brj-22232	99	23	than	than	ADP
brj-22232	99	24	512	512	NUM
brj-22232	99	25	pixels	pixel	NOUN
brj-22232	99	26	and	and	CCONJ
brj-22232	99	27	blurred	blurred	ADJ
brj-22232	99	28	images	image	NOUN
brj-22232	99	29	.	.	PUNCT
brj-22232	100	1	based	base	VERB
brj-22232	100	2	on	on	ADP
brj-22232	100	3	these	these	DET
brj-22232	100	4	images	image	NOUN
brj-22232	100	5	,	,	PUNCT
brj-22232	100	6	the	the	DET
brj-22232	100	7	images	image	NOUN
brj-22232	100	8	with	with	ADP
brj-22232	100	9	a	a	DET
brj-22232	100	10	width	width	NOUN
brj-22232	100	11	more	more	ADJ
brj-22232	100	12	than	than	ADP
brj-22232	100	13	512	512	NUM
brj-22232	100	14	pixels	pixel	NOUN
brj-22232	100	15	were	be	AUX
brj-22232	100	16	cropped	crop	VERB
brj-22232	100	17	to	to	PART
brj-22232	100	18	obtain	obtain	VERB
brj-22232	100	19	759	759	NUM
brj-22232	100	20	b	b	NOUN
brj-22232	100	21	-	-	PUNCT
brj-22232	100	22	scan	scan	ADJ
brj-22232	100	23	images	image	NOUN
brj-22232	100	24	with	with	ADP
brj-22232	100	25	a	a	DET
brj-22232	100	26	resolution	resolution	NOUN
brj-22232	100	27	of	of	ADP
brj-22232	100	28	512	512	NUM
brj-22232	100	29	×	×	NOUN
brj-22232	100	30	512	512	NUM
brj-22232	100	31	pixels	pixel	NOUN
brj-22232	100	32	.	.	PUNCT
brj-22232	101	1	simulated	simulate	VERB
brj-22232	101	2	data	datum	NOUN
brj-22232	101	3	generating	generate	VERB
brj-22232	101	4	in	in	ADP
brj-22232	101	5	this	this	DET
brj-22232	101	6	study	study	NOUN
brj-22232	101	7	,	,	PUNCT
brj-22232	101	8	the	the	DET
brj-22232	101	9	simulation	simulation	NOUN
brj-22232	101	10	data	datum	NOUN
brj-22232	101	11	had	have	VERB
brj-22232	101	12	a	a	DET
brj-22232	101	13	crucial	crucial	ADJ
brj-22232	101	14	role	role	NOUN
brj-22232	101	15	in	in	ADP
brj-22232	101	16	extending	extend	VERB
brj-22232	101	17	the	the	DET
brj-22232	101	18	diversity	diversity	NOUN
brj-22232	101	19	of	of	ADP
brj-22232	101	20	the	the	DET
brj-22232	101	21	dataset	dataset	NOUN
brj-22232	101	22	.	.	PUNCT
brj-22232	102	1	when	when	SCONJ
brj-22232	102	2	generating	generate	VERB
brj-22232	102	3	simulated	simulated	ADJ
brj-22232	102	4	data	datum	NOUN
brj-22232	102	5	,	,	PUNCT
brj-22232	102	6	the	the	DET
brj-22232	102	7	parameter	parameter	NOUN
brj-22232	102	8	variables	variable	NOUN
brj-22232	102	9	were	be	AUX
brj-22232	102	10	controlled	control	VERB
brj-22232	102	11	so	so	SCONJ
brj-22232	102	12	that	that	SCONJ
brj-22232	102	13	the	the	DET
brj-22232	102	14	gprmax	gprmax	ADJ
brj-22232	102	15	software	software	NOUN
brj-22232	102	16	parameters	parameter	NOUN
brj-22232	102	17	remained	remain	VERB
brj-22232	102	18	consistent	consistent	ADJ
brj-22232	102	19	with	with	ADP
brj-22232	102	20	the	the	DET
brj-22232	102	21	ground	ground	NOUN
brj-22232	102	22	penetrating	penetrate	VERB
brj-22232	102	23	radar	radar	NOUN
brj-22232	102	24	equipment	equipment	NOUN
brj-22232	102	25	parameters	parameter	NOUN
brj-22232	102	26	,	,	PUNCT
brj-22232	102	27	where	where	SCONJ
brj-22232	102	28	:	:	PUNCT
brj-22232	102	29	the	the	DET
brj-22232	102	30	depth	depth	NOUN
brj-22232	102	31	of	of	ADP
brj-22232	102	32	the	the	DET
brj-22232	102	33	domain	domain	NOUN
brj-22232	102	34	was	be	AUX
brj-22232	102	35	0.6	0.6	NUM
brj-22232	102	36	m	m	NOUN
brj-22232	102	37	,	,	PUNCT
brj-22232	102	38	the	the	DET
brj-22232	102	39	lateral	lateral	ADJ
brj-22232	102	40	length	length	NOUN
brj-22232	102	41	was	be	AUX
brj-22232	102	42	6	6	NUM
brj-22232	102	43	m	m	NOUN
brj-22232	102	44	,	,	PUNCT
brj-22232	102	45	the	the	DET
brj-22232	102	46	root	root	NOUN
brj-22232	102	47	had	have	VERB
brj-22232	102	48	a	a	DET
brj-22232	102	49	radius	radius	NOUN
brj-22232	102	50	from	from	ADP
brj-22232	102	51	0.01	0.01	NUM
brj-22232	102	52	to	to	ADP
brj-22232	102	53	0.035	0.035	NUM
brj-22232	102	54	m	m	NOUN
brj-22232	102	55	,	,	PUNCT
brj-22232	102	56	the	the	DET
brj-22232	102	57	soil	soil	NOUN
brj-22232	102	58	and	and	CCONJ
brj-22232	102	59	root	root	NOUN
brj-22232	102	60	system	system	NOUN
brj-22232	102	61	have	have	VERB
brj-22232	102	62	relative	relative	ADJ
brj-22232	102	63	dielectric	dielectric	ADJ
brj-22232	102	64	constants	constant	NOUN
brj-22232	102	65	of	of	ADP
brj-22232	102	66	6	6	NUM
brj-22232	102	67	and	and	CCONJ
brj-22232	102	68	12	12	NUM
brj-22232	102	69	(	(	PUNCT
brj-22232	102	70	attia	attia	PROPN
brj-22232	102	71	al	al	PROPN
brj-22232	102	72	hagrey	hagrey	PROPN
brj-22232	102	73	2007	2007	NUM
brj-22232	102	74	;	;	PUNCT
brj-22232	102	75	liang	liang	PROPN
brj-22232	102	76	et	et	PROPN
brj-22232	102	77	al	al	PROPN
brj-22232	102	78	.	.	PROPN
brj-22232	102	79	2021	2021	NUM
brj-22232	102	80	)	)	PUNCT
brj-22232	102	81	,	,	PUNCT
brj-22232	102	82	respectively	respectively	ADV
brj-22232	102	83	,	,	PUNCT
brj-22232	102	84	and	and	CCONJ
brj-22232	102	85	the	the	DET
brj-22232	102	86	sampling	sample	VERB
brj-22232	102	87	number	number	NOUN
brj-22232	102	88	was	be	AUX
brj-22232	102	89	512	512	NUM
brj-22232	102	90	,	,	PUNCT
brj-22232	102	91	the	the	DET
brj-22232	102	92	antenna	antenna	NOUN
brj-22232	102	93	frequency	frequency	NOUN
brj-22232	102	94	of	of	ADP
brj-22232	102	95	the	the	DET
brj-22232	102	96	gpr	gpr	PROPN
brj-22232	102	97	setting	setting	NOUN
brj-22232	102	98	was	be	AUX
brj-22232	102	99	900	900	NUM
brj-22232	102	100	mhz	mhz	NOUN
brj-22232	102	101	,	,	PUNCT
brj-22232	102	102	and	and	CCONJ
brj-22232	102	103	a	a	DET
brj-22232	102	104	total	total	NOUN
brj-22232	102	105	of	of	ADP
brj-22232	102	106	759	759	NUM
brj-22232	102	107	simulated	simulate	VERB
brj-22232	102	108	images	image	NOUN
brj-22232	102	109	were	be	AUX
brj-22232	102	110	generated	generate	VERB
brj-22232	102	111	.	.	PUNCT
brj-22232	103	1	peer	peer	NOUN
brj-22232	103	2	-	-	PUNCT
brj-22232	103	3	reviewed	review	VERB
brj-22232	103	4	article	article	NOUN
brj-22232	103	5	bioresources.com	bioresources.com	X
brj-22232	103	6	li	li	PROPN
brj-22232	103	7	et	et	PROPN
brj-22232	103	8	al	al	PROPN
brj-22232	103	9	.	.	PROPN
brj-22232	103	10	(	(	PUNCT
brj-22232	103	11	2023	2023	NUM
brj-22232	103	12	)	)	PUNCT
brj-22232	103	13	.	.	PUNCT
brj-22232	104	1	“	"	PUNCT
brj-22232	104	2	tree	tree	NOUN
brj-22232	104	3	root	root	NOUN
brj-22232	104	4	detection	detection	NOUN
brj-22232	104	5	training	training	NOUN
brj-22232	104	6	,	,	PUNCT
brj-22232	104	7	”	"	PUNCT
brj-22232	104	8	bioresources	bioresource	NOUN
brj-22232	104	9	18(1	18(1	NOUN
brj-22232	104	10	)	)	PUNCT
brj-22232	104	11	,	,	PUNCT
brj-22232	104	12	484	484	NUM
brj-22232	104	13	-	-	SYM
brj-22232	104	14	504	504	NUM
brj-22232	104	15	.	.	PUNCT
brj-22232	105	1	489	489	NUM
brj-22232	105	2	enhanced	enhance	VERB
brj-22232	105	3	data	data	NOUN
brj-22232	105	4	generation	generation	NOUN
brj-22232	105	5	the	the	DET
brj-22232	105	6	above	above	ADJ
brj-22232	105	7	analysis	analysis	NOUN
brj-22232	105	8	of	of	ADP
brj-22232	105	9	the	the	DET
brj-22232	105	10	gpr	gpr	PROPN
brj-22232	105	11	target	target	NOUN
brj-22232	105	12	imaging	imaging	NOUN
brj-22232	105	13	process	process	NOUN
brj-22232	105	14	found	find	VERB
brj-22232	105	15	that	that	SCONJ
brj-22232	105	16	the	the	DET
brj-22232	105	17	tree	tree	NOUN
brj-22232	105	18	roots	root	NOUN
brj-22232	105	19	showed	show	VERB
brj-22232	105	20	hyperbolic	hyperbolic	ADJ
brj-22232	105	21	structural	structural	ADJ
brj-22232	105	22	features	feature	NOUN
brj-22232	105	23	on	on	ADP
brj-22232	105	24	the	the	DET
brj-22232	105	25	b	b	NOUN
brj-22232	105	26	-	-	PUNCT
brj-22232	105	27	scan	scan	ADJ
brj-22232	105	28	images	image	NOUN
brj-22232	105	29	,	,	PUNCT
brj-22232	105	30	while	while	SCONJ
brj-22232	105	31	different	different	ADJ
brj-22232	105	32	soil	soil	NOUN
brj-22232	105	33	environments	environment	NOUN
brj-22232	105	34	showed	show	VERB
brj-22232	105	35	various	various	ADJ
brj-22232	105	36	background	background	NOUN
brj-22232	105	37	and	and	CCONJ
brj-22232	105	38	noise	noise	NOUN
brj-22232	105	39	features	feature	NOUN
brj-22232	105	40	on	on	ADP
brj-22232	105	41	the	the	DET
brj-22232	105	42	b	b	NOUN
brj-22232	105	43	-	-	PUNCT
brj-22232	105	44	scan	scan	ADJ
brj-22232	105	45	images	image	NOUN
brj-22232	105	46	.	.	PUNCT
brj-22232	106	1	a	a	DET
brj-22232	106	2	gpr	gpr	PROPN
brj-22232	106	3	b	b	X
brj-22232	106	4	-	-	PUNCT
brj-22232	106	5	scan	scan	ADJ
brj-22232	106	6	image	image	NOUN
brj-22232	106	7	was	be	AUX
brj-22232	106	8	composed	compose	VERB
brj-22232	106	9	of	of	ADP
brj-22232	106	10	three	three	NUM
brj-22232	106	11	elements	element	NOUN
brj-22232	106	12	:	:	PUNCT
brj-22232	106	13	hyperbolic	hyperbolic	ADJ
brj-22232	106	14	structure	structure	NOUN
brj-22232	106	15	,	,	PUNCT
brj-22232	106	16	background	background	NOUN
brj-22232	106	17	,	,	PUNCT
brj-22232	106	18	and	and	CCONJ
brj-22232	106	19	noise	noise	NOUN
brj-22232	106	20	features	feature	NOUN
brj-22232	106	21	.	.	PUNCT
brj-22232	107	1	when	when	SCONJ
brj-22232	107	2	performing	perform	VERB
brj-22232	107	3	the	the	DET
brj-22232	107	4	conversion	conversion	NOUN
brj-22232	107	5	of	of	ADP
brj-22232	107	6	a	a	DET
brj-22232	107	7	simulation	simulation	NOUN
brj-22232	107	8	image	image	NOUN
brj-22232	107	9	to	to	ADP
brj-22232	107	10	a	a	DET
brj-22232	107	11	generated	generate	VERB
brj-22232	107	12	image	image	NOUN
brj-22232	107	13	,	,	PUNCT
brj-22232	107	14	the	the	DET
brj-22232	107	15	complete	complete	ADJ
brj-22232	107	16	hyperbolic	hyperbolic	ADJ
brj-22232	107	17	structure	structure	NOUN
brj-22232	107	18	features	feature	NOUN
brj-22232	107	19	and	and	CCONJ
brj-22232	107	20	nearly	nearly	ADV
brj-22232	107	21	realistic	realistic	ADJ
brj-22232	107	22	background	background	NOUN
brj-22232	107	23	and	and	CCONJ
brj-22232	107	24	noise	noise	NOUN
brj-22232	107	25	features	feature	NOUN
brj-22232	107	26	should	should	AUX
brj-22232	107	27	be	be	AUX
brj-22232	107	28	retained	retain	VERB
brj-22232	107	29	in	in	ADP
brj-22232	107	30	the	the	DET
brj-22232	107	31	generated	generate	VERB
brj-22232	107	32	image	image	NOUN
brj-22232	107	33	.	.	PUNCT
brj-22232	108	1	the	the	DET
brj-22232	108	2	tree	tree	NOUN
brj-22232	108	3	environments	environment	NOUN
brj-22232	108	4	in	in	ADP
brj-22232	108	5	the	the	DET
brj-22232	108	6	experiment	experiment	NOUN
brj-22232	108	7	were	be	AUX
brj-22232	108	8	different	different	ADJ
brj-22232	108	9	,	,	PUNCT
brj-22232	108	10	which	which	PRON
brj-22232	108	11	allowed	allow	VERB
brj-22232	108	12	the	the	DET
brj-22232	108	13	cyclegan	cyclegan	NOUN
brj-22232	108	14	model	model	NOUN
brj-22232	108	15	to	to	PART
brj-22232	108	16	generate	generate	VERB
brj-22232	108	17	richer	rich	ADJ
brj-22232	108	18	images	image	NOUN
brj-22232	108	19	,	,	PUNCT
brj-22232	108	20	and	and	CCONJ
brj-22232	108	21	the	the	DET
brj-22232	108	22	hyperbola	hyperbola	PROPN
brj-22232	108	23	,	,	PUNCT
brj-22232	108	24	background	background	NOUN
brj-22232	108	25	,	,	PUNCT
brj-22232	108	26	and	and	CCONJ
brj-22232	108	27	noise	noise	NOUN
brj-22232	108	28	features	feature	NOUN
brj-22232	108	29	of	of	ADP
brj-22232	108	30	the	the	DET
brj-22232	108	31	generated	generate	VERB
brj-22232	108	32	images	image	NOUN
brj-22232	108	33	were	be	AUX
brj-22232	108	34	closer	close	ADJ
brj-22232	108	35	to	to	ADP
brj-22232	108	36	the	the	DET
brj-22232	108	37	real	real	ADJ
brj-22232	108	38	images	image	NOUN
brj-22232	108	39	.	.	PUNCT
brj-22232	109	1	specifically	specifically	ADV
brj-22232	109	2	,	,	PUNCT
brj-22232	109	3	the	the	DET
brj-22232	109	4	hyperbolic	hyperbolic	ADJ
brj-22232	109	5	feature	feature	NOUN
brj-22232	109	6	information	information	NOUN
brj-22232	109	7	was	be	AUX
brj-22232	109	8	fused	fuse	VERB
brj-22232	109	9	with	with	ADP
brj-22232	109	10	the	the	DET
brj-22232	109	11	background	background	NOUN
brj-22232	109	12	and	and	CCONJ
brj-22232	109	13	noise	noise	NOUN
brj-22232	109	14	for	for	ADP
brj-22232	109	15	the	the	DET
brj-22232	109	16	real	real	ADJ
brj-22232	109	17	acquired	acquire	VERB
brj-22232	109	18	gpr	gpr	PROPN
brj-22232	109	19	b	b	PROPN
brj-22232	109	20	-	-	PUNCT
brj-22232	109	21	scan	scan	ADJ
brj-22232	109	22	images	image	NOUN
brj-22232	109	23	,	,	PUNCT
brj-22232	109	24	and	and	CCONJ
brj-22232	109	25	it	it	PRON
brj-22232	109	26	was	be	AUX
brj-22232	109	27	difficult	difficult	ADJ
brj-22232	109	28	to	to	PART
brj-22232	109	29	distinguish	distinguish	VERB
brj-22232	109	30	the	the	DET
brj-22232	109	31	hyperbolic	hyperbolic	ADJ
brj-22232	109	32	curve	curve	NOUN
brj-22232	109	33	.	.	PUNCT
brj-22232	110	1	therefore	therefore	ADV
brj-22232	110	2	,	,	PUNCT
brj-22232	110	3	the	the	DET
brj-22232	110	4	hyperbolic	hyperbolic	ADJ
brj-22232	110	5	image	image	NOUN
brj-22232	110	6	without	without	ADP
brj-22232	110	7	background	background	NOUN
brj-22232	110	8	and	and	CCONJ
brj-22232	110	9	noise	noise	NOUN
brj-22232	110	10	was	be	AUX
brj-22232	110	11	generated	generate	VERB
brj-22232	110	12	by	by	ADP
brj-22232	110	13	style	style	NOUN
brj-22232	110	14	transformation	transformation	NOUN
brj-22232	110	15	,	,	PUNCT
brj-22232	110	16	which	which	PRON
brj-22232	110	17	could	could	AUX
brj-22232	110	18	clearly	clearly	ADV
brj-22232	110	19	show	show	VERB
brj-22232	110	20	the	the	DET
brj-22232	110	21	hyperbolic	hyperbolic	ADJ
brj-22232	110	22	structure	structure	NOUN
brj-22232	110	23	and	and	CCONJ
brj-22232	110	24	facilitate	facilitate	VERB
brj-22232	110	25	further	further	ADJ
brj-22232	110	26	study	study	NOUN
brj-22232	110	27	.	.	PUNCT
brj-22232	111	1	at	at	ADP
brj-22232	111	2	the	the	DET
brj-22232	111	3	same	same	ADJ
brj-22232	111	4	time	time	NOUN
brj-22232	111	5	,	,	PUNCT
brj-22232	111	6	the	the	DET
brj-22232	111	7	generated	generate	VERB
brj-22232	111	8	images	image	NOUN
brj-22232	111	9	with	with	ADP
brj-22232	111	10	different	different	ADJ
brj-22232	111	11	background	background	NOUN
brj-22232	111	12	and	and	CCONJ
brj-22232	111	13	noise	noise	NOUN
brj-22232	111	14	were	be	AUX
brj-22232	111	15	generated	generate	VERB
brj-22232	111	16	through	through	ADP
brj-22232	111	17	style	style	NOUN
brj-22232	111	18	transformation	transformation	NOUN
brj-22232	111	19	on	on	ADP
brj-22232	111	20	the	the	DET
brj-22232	111	21	basis	basis	NOUN
brj-22232	111	22	of	of	ADP
brj-22232	111	23	retaining	retain	VERB
brj-22232	111	24	the	the	DET
brj-22232	111	25	simulation	simulation	NOUN
brj-22232	111	26	image	image	NOUN
brj-22232	111	27	hyperbolic	hyperbolic	ADJ
brj-22232	111	28	features	feature	NOUN
brj-22232	111	29	,	,	PUNCT
brj-22232	111	30	increasing	increase	VERB
brj-22232	111	31	the	the	DET
brj-22232	111	32	diversity	diversity	NOUN
brj-22232	111	33	of	of	ADP
brj-22232	111	34	the	the	DET
brj-22232	111	35	real	real	ADJ
brj-22232	111	36	dataset	dataset	NOUN
brj-22232	111	37	.	.	PUNCT
brj-22232	112	1	the	the	DET
brj-22232	112	2	different	different	ADJ
brj-22232	112	3	backgrounds	background	NOUN
brj-22232	112	4	and	and	CCONJ
brj-22232	112	5	noise	noise	NOUN
brj-22232	112	6	were	be	AUX
brj-22232	112	7	appended	append	VERB
brj-22232	112	8	to	to	ADP
brj-22232	112	9	the	the	DET
brj-22232	112	10	simulation	simulation	NOUN
brj-22232	112	11	images	image	NOUN
brj-22232	112	12	,	,	PUNCT
brj-22232	112	13	making	make	VERB
brj-22232	112	14	the	the	DET
brj-22232	112	15	generated	generate	VERB
brj-22232	112	16	images	image	NOUN
brj-22232	112	17	closer	close	ADV
brj-22232	112	18	to	to	ADP
brj-22232	112	19	the	the	DET
brj-22232	112	20	measured	measured	ADJ
brj-22232	112	21	data	datum	NOUN
brj-22232	112	22	.	.	PUNCT
brj-22232	113	1	the	the	DET
brj-22232	113	2	transformation	transformation	NOUN
brj-22232	113	3	of	of	ADP
brj-22232	113	4	simulation	simulation	NOUN
brj-22232	113	5	images	image	NOUN
brj-22232	113	6	to	to	ADP
brj-22232	113	7	generated	generate	VERB
brj-22232	113	8	images	image	NOUN
brj-22232	113	9	followed	follow	VERB
brj-22232	113	10	the	the	DET
brj-22232	113	11	cyclegan	cyclegan	NOUN
brj-22232	113	12	architecture	architecture	NOUN
brj-22232	113	13	.	.	PUNCT
brj-22232	114	1	the	the	DET
brj-22232	114	2	structure	structure	NOUN
brj-22232	114	3	of	of	ADP
brj-22232	114	4	this	this	DET
brj-22232	114	5	network	network	NOUN
brj-22232	114	6	consisted	consist	VERB
brj-22232	114	7	of	of	ADP
brj-22232	114	8	two	two	NUM
brj-22232	114	9	pairs	pair	NOUN
brj-22232	114	10	of	of	ADP
brj-22232	114	11	generators	generator	NOUN
brj-22232	114	12	and	and	CCONJ
brj-22232	114	13	discriminators	discriminator	NOUN
brj-22232	114	14	.	.	PUNCT
brj-22232	115	1	generator	generator	PROPN
brj-22232	115	2	a	a	PRON
brj-22232	115	3	transformed	transform	VERB
brj-22232	115	4	the	the	DET
brj-22232	115	5	real	real	ADJ
brj-22232	115	6	image	image	NOUN
brj-22232	115	7	with	with	ADP
brj-22232	115	8	features	feature	NOUN
brj-22232	115	9	and	and	CCONJ
brj-22232	115	10	generated	generate	VERB
brj-22232	115	11	the	the	DET
brj-22232	115	12	corresponding	corresponding	ADJ
brj-22232	115	13	simulation	simulation	NOUN
brj-22232	115	14	image	image	NOUN
brj-22232	115	15	a	a	DET
brj-22232	115	16	'	'	NOUN
brj-22232	115	17	.	.	PUNCT
brj-22232	116	1	the	the	DET
brj-22232	116	2	generated	generate	VERB
brj-22232	116	3	-	-	PUNCT
brj-22232	116	4	simulation	simulation	NOUN
brj-22232	116	5	image	image	NOUN
brj-22232	116	6	a	a	PRON
brj-22232	116	7	'	'	PUNCT
brj-22232	116	8	was	be	AUX
brj-22232	116	9	compared	compare	VERB
brj-22232	116	10	with	with	ADP
brj-22232	116	11	the	the	DET
brj-22232	116	12	simulation	simulation	NOUN
brj-22232	116	13	image	image	NOUN
brj-22232	116	14	,	,	PUNCT
brj-22232	116	15	expecting	expect	VERB
brj-22232	116	16	to	to	PART
brj-22232	116	17	obtain	obtain	VERB
brj-22232	116	18	a	a	DET
brj-22232	116	19	generated	generate	VERB
brj-22232	116	20	-	-	PUNCT
brj-22232	116	21	simulation	simulation	NOUN
brj-22232	116	22	image	image	NOUN
brj-22232	116	23	that	that	PRON
brj-22232	116	24	could	could	AUX
brj-22232	116	25	be	be	AUX
brj-22232	116	26	faked	fake	VERB
brj-22232	116	27	as	as	ADP
brj-22232	116	28	real	real	ADJ
brj-22232	116	29	,	,	PUNCT
brj-22232	116	30	which	which	PRON
brj-22232	116	31	could	could	AUX
brj-22232	116	32	also	also	ADV
brj-22232	116	33	be	be	AUX
brj-22232	116	34	considered	consider	VERB
brj-22232	116	35	as	as	ADP
brj-22232	116	36	a	a	DET
brj-22232	116	37	b	b	NOUN
brj-22232	116	38	-	-	PUNCT
brj-22232	116	39	scan	scan	ADJ
brj-22232	116	40	image	image	NOUN
brj-22232	116	41	with	with	ADP
brj-22232	116	42	the	the	DET
brj-22232	116	43	background	background	NOUN
brj-22232	116	44	and	and	CCONJ
brj-22232	116	45	noise	noise	NOUN
brj-22232	116	46	removed	remove	VERB
brj-22232	116	47	.	.	PUNCT
brj-22232	117	1	the	the	DET
brj-22232	117	2	specific	specific	ADJ
brj-22232	117	3	architecture	architecture	NOUN
brj-22232	117	4	is	be	AUX
brj-22232	117	5	shown	show	VERB
brj-22232	117	6	in	in	ADP
brj-22232	117	7	fig	fig	NOUN
brj-22232	117	8	.	.	PUNCT
brj-22232	118	1	5	5	NUM
brj-22232	118	2	,	,	PUNCT
brj-22232	118	3	which	which	PRON
brj-22232	118	4	consists	consist	VERB
brj-22232	118	5	of	of	ADP
brj-22232	118	6	two	two	NUM
brj-22232	118	7	generators	generator	NOUN
brj-22232	118	8	,	,	PUNCT
brj-22232	118	9	ga	ga	PROPN
brj-22232	118	10	and	and	CCONJ
brj-22232	118	11	gb	gb	NOUN
brj-22232	118	12	,	,	PUNCT
brj-22232	118	13	and	and	CCONJ
brj-22232	118	14	two	two	NUM
brj-22232	118	15	discriminators	discriminator	NOUN
brj-22232	118	16	,	,	PUNCT
brj-22232	118	17	da	da	NOUN
brj-22232	118	18	and	and	CCONJ
brj-22232	118	19	db	db	PROPN
brj-22232	118	20	.	.	PROPN
brj-22232	118	21	fig	fig	PROPN
brj-22232	118	22	.	.	PUNCT
brj-22232	119	1	5	5	NUM
brj-22232	119	2	.	.	X
brj-22232	119	3	overall	overall	ADJ
brj-22232	119	4	architecture	architecture	NOUN
brj-22232	119	5	of	of	ADP
brj-22232	119	6	the	the	DET
brj-22232	119	7	proposed	propose	VERB
brj-22232	119	8	cyclegan	cyclegan	NOUN
brj-22232	119	9	architecture	architecture	NOUN
brj-22232	119	10	for	for	ADP
brj-22232	119	11	background	background	NOUN
brj-22232	119	12	and	and	CCONJ
brj-22232	119	13	noise	noise	NOUN
brj-22232	119	14	conversion	conversion	NOUN
brj-22232	119	15	of	of	ADP
brj-22232	119	16	a	a	DET
brj-22232	119	17	single	single	ADJ
brj-22232	119	18	image	image	NOUN
brj-22232	119	19	in	in	ADP
brj-22232	119	20	particular	particular	ADJ
brj-22232	119	21	,	,	PUNCT
brj-22232	119	22	generator	generator	PROPN
brj-22232	119	23	ga	ga	PROPN
brj-22232	119	24	was	be	AUX
brj-22232	119	25	used	use	VERB
brj-22232	119	26	to	to	PART
brj-22232	119	27	generate	generate	VERB
brj-22232	119	28	b	b	NUM
brj-22232	119	29	-	-	PUNCT
brj-22232	119	30	domain	domain	NOUN
brj-22232	119	31	style	style	NOUN
brj-22232	119	32	images	image	NOUN
brj-22232	119	33	from	from	ADP
brj-22232	119	34	adomain	adomain	NOUN
brj-22232	119	35	,	,	PUNCT
brj-22232	119	36	and	and	CCONJ
brj-22232	119	37	generator	generator	NOUN
brj-22232	119	38	gb	gb	PRON
brj-22232	119	39	reverted	revert	VERB
brj-22232	119	40	the	the	DET
brj-22232	119	41	generated	generate	VERB
brj-22232	119	42	b	b	NOUN
brj-22232	119	43	-	-	PUNCT
brj-22232	119	44	domain	domain	NOUN
brj-22232	119	45	images	image	NOUN
brj-22232	119	46	to	to	ADP
brj-22232	119	47	a	a	DET
brj-22232	119	48	-	-	PUNCT
brj-22232	119	49	domain	domain	NOUN
brj-22232	119	50	images	image	NOUN
brj-22232	119	51	.	.	PUNCT
brj-22232	120	1	the	the	DET
brj-22232	120	2	discriminator	discriminator	NOUN
brj-22232	120	3	db	db	PROPN
brj-22232	120	4	was	be	AUX
brj-22232	120	5	used	use	VERB
brj-22232	120	6	to	to	PART
brj-22232	120	7	make	make	VERB
brj-22232	120	8	the	the	DET
brj-22232	120	9	image	image	NOUN
brj-22232	120	10	generated	generate	VERB
brj-22232	120	11	by	by	ADP
brj-22232	120	12	the	the	DET
brj-22232	120	13	generator	generator	PROPN
brj-22232	120	14	ga	ga	PROPN
brj-22232	120	15	as	as	ADP
brj-22232	120	16	close	close	ADJ
brj-22232	120	17	peer	peer	NOUN
brj-22232	120	18	-	-	PUNCT
brj-22232	120	19	reviewed	review	VERB
brj-22232	120	20	article	article	NOUN
brj-22232	120	21	bioresources.com	bioresources.com	X
brj-22232	120	22	li	li	PROPN
brj-22232	120	23	et	et	PROPN
brj-22232	120	24	al	al	PROPN
brj-22232	120	25	.	.	PROPN
brj-22232	121	1	(	(	PUNCT
brj-22232	121	2	2023	2023	NUM
brj-22232	121	3	)	)	PUNCT
brj-22232	121	4	.	.	PUNCT
brj-22232	122	1	“	"	PUNCT
brj-22232	122	2	tree	tree	NOUN
brj-22232	122	3	root	root	NOUN
brj-22232	122	4	detection	detection	NOUN
brj-22232	122	5	training	training	NOUN
brj-22232	122	6	,	,	PUNCT
brj-22232	122	7	”	"	PUNCT
brj-22232	122	8	bioresources	bioresource	NOUN
brj-22232	122	9	18(1	18(1	NOUN
brj-22232	122	10	)	)	PUNCT
brj-22232	122	11	,	,	PUNCT
brj-22232	122	12	484	484	NUM
brj-22232	122	13	-	-	SYM
brj-22232	122	14	504	504	NUM
brj-22232	122	15	.	.	NOUN
brj-22232	122	16	490	490	NUM
brj-22232	122	17	as	as	ADP
brj-22232	122	18	possible	possible	ADJ
brj-22232	122	19	to	to	ADP
brj-22232	122	20	the	the	DET
brj-22232	122	21	b	b	NOUN
brj-22232	122	22	-	-	PUNCT
brj-22232	122	23	domain	domain	NOUN
brj-22232	122	24	style	style	NOUN
brj-22232	122	25	image	image	NOUN
brj-22232	122	26	,	,	PUNCT
brj-22232	122	27	and	and	CCONJ
brj-22232	122	28	the	the	DET
brj-22232	122	29	discriminator	discriminator	NOUN
brj-22232	122	30	da	da	PROPN
brj-22232	122	31	was	be	AUX
brj-22232	122	32	used	use	VERB
brj-22232	122	33	to	to	PART
brj-22232	122	34	make	make	VERB
brj-22232	122	35	the	the	DET
brj-22232	122	36	image	image	NOUN
brj-22232	122	37	generated	generate	VERB
brj-22232	122	38	by	by	ADP
brj-22232	122	39	the	the	DET
brj-22232	122	40	generator	generator	NOUN
brj-22232	122	41	gb	gb	ADP
brj-22232	122	42	as	as	ADV
brj-22232	122	43	similar	similar	ADJ
brj-22232	122	44	as	as	ADP
brj-22232	122	45	possible	possible	ADJ
brj-22232	122	46	to	to	ADP
brj-22232	122	47	the	the	DET
brj-22232	122	48	original	original	ADJ
brj-22232	122	49	b	b	NOUN
brj-22232	122	50	-	-	PUNCT
brj-22232	122	51	domain	domain	NOUN
brj-22232	122	52	original	original	ADJ
brj-22232	122	53	image	image	NOUN
brj-22232	122	54	,	,	PUNCT
brj-22232	122	55	ensuring	ensure	VERB
brj-22232	122	56	that	that	SCONJ
brj-22232	122	57	when	when	SCONJ
brj-22232	122	58	the	the	DET
brj-22232	122	59	image	image	NOUN
brj-22232	122	60	style	style	NOUN
brj-22232	122	61	was	be	AUX
brj-22232	122	62	migrated	migrate	VERB
brj-22232	122	63	,	,	PUNCT
brj-22232	122	64	there	there	PRON
brj-22232	122	65	is	be	VERB
brj-22232	122	66	not	not	PART
brj-22232	122	67	only	only	ADV
brj-22232	122	68	a	a	DET
brj-22232	122	69	change	change	NOUN
brj-22232	122	70	in	in	ADP
brj-22232	122	71	style	style	NOUN
brj-22232	122	72	from	from	ADP
brj-22232	122	73	the	the	DET
brj-22232	122	74	b	b	NOUN
brj-22232	122	75	-	-	PUNCT
brj-22232	122	76	domain	domain	NOUN
brj-22232	122	77	to	to	ADP
brj-22232	122	78	the	the	DET
brj-22232	122	79	a	a	DET
brj-22232	122	80	-	-	PUNCT
brj-22232	122	81	domain	domain	NOUN
brj-22232	122	82	but	but	CCONJ
brj-22232	122	83	also	also	ADV
brj-22232	122	84	the	the	DET
brj-22232	122	85	features	feature	NOUN
brj-22232	122	86	of	of	ADP
brj-22232	122	87	the	the	DET
brj-22232	122	88	original	original	ADJ
brj-22232	122	89	b	b	NOUN
brj-22232	122	90	-	-	PUNCT
brj-22232	122	91	domain	domain	NOUN
brj-22232	122	92	original	original	ADJ
brj-22232	122	93	image	image	NOUN
brj-22232	122	94	still	still	ADV
brj-22232	122	95	exist	exist	VERB
brj-22232	122	96	.	.	PUNCT
brj-22232	123	1	the	the	DET
brj-22232	123	2	cyclic	cyclic	ADJ
brj-22232	123	3	consistency	consistency	NOUN
brj-22232	123	4	loss	loss	NOUN
brj-22232	123	5	allows	allow	VERB
brj-22232	123	6	us	we	PRON
brj-22232	123	7	to	to	PART
brj-22232	123	8	train	train	VERB
brj-22232	123	9	a	a	DET
brj-22232	123	10	model	model	NOUN
brj-22232	123	11	that	that	PRON
brj-22232	123	12	does	do	AUX
brj-22232	123	13	not	not	PART
brj-22232	123	14	require	require	VERB
brj-22232	123	15	pairs	pair	NOUN
brj-22232	123	16	of	of	ADP
brj-22232	123	17	image	image	NOUN
brj-22232	123	18	instances	instance	NOUN
brj-22232	123	19	with	with	ADP
brj-22232	123	20	or	or	CCONJ
brj-22232	123	21	without	without	ADP
brj-22232	123	22	background	background	NOUN
brj-22232	123	23	and	and	CCONJ
brj-22232	123	24	noise	noise	NOUN
brj-22232	123	25	features	feature	NOUN
brj-22232	123	26	.	.	PUNCT
brj-22232	124	1	the	the	DET
brj-22232	124	2	real	real	ADJ
brj-22232	124	3	dataset	dataset	NOUN
brj-22232	124	4	and	and	CCONJ
brj-22232	124	5	the	the	DET
brj-22232	124	6	simulated	simulate	VERB
brj-22232	124	7	dataset	dataset	NOUN
brj-22232	124	8	were	be	AUX
brj-22232	124	9	used	use	VERB
brj-22232	124	10	as	as	ADP
brj-22232	124	11	a	a	DET
brj-22232	124	12	-	-	PUNCT
brj-22232	124	13	domain	domain	NOUN
brj-22232	124	14	and	and	CCONJ
brj-22232	124	15	b	b	NOUN
brj-22232	124	16	-	-	PUNCT
brj-22232	124	17	domain	domain	NOUN
brj-22232	124	18	in	in	ADP
brj-22232	124	19	the	the	DET
brj-22232	124	20	structure	structure	NOUN
brj-22232	124	21	of	of	ADP
brj-22232	124	22	cyclegan	cyclegan	NOUN
brj-22232	124	23	,	,	PUNCT
brj-22232	124	24	respectively	respectively	ADV
brj-22232	124	25	.	.	PUNCT
brj-22232	125	1	during	during	ADP
brj-22232	125	2	training	training	NOUN
brj-22232	125	3	,	,	PUNCT
brj-22232	125	4	the	the	DET
brj-22232	125	5	real	real	ADJ
brj-22232	125	6	image	image	NOUN
brj-22232	125	7	a	a	PRON
brj-22232	125	8	in	in	ADP
brj-22232	125	9	the	the	DET
brj-22232	125	10	a	a	DET
brj-22232	125	11	-	-	PUNCT
brj-22232	125	12	domain	domain	NOUN
brj-22232	125	13	was	be	AUX
brj-22232	125	14	transformed	transform	VERB
brj-22232	125	15	into	into	ADP
brj-22232	125	16	the	the	DET
brj-22232	125	17	corresponding	corresponding	ADJ
brj-22232	125	18	generated	generate	VERB
brj-22232	125	19	image	image	NOUN
brj-22232	125	20	a	a	PRON
brj-22232	125	21	'	'	PUNCT
brj-22232	125	22	after	after	ADP
brj-22232	125	23	the	the	DET
brj-22232	125	24	generator	generator	PROPN
brj-22232	125	25	ga	ga	PROPN
brj-22232	125	26	.	.	PROPN
brj-22232	126	1	a	a	PRON
brj-22232	126	2	'	'	PUNCT
brj-22232	126	3	had	have	VERB
brj-22232	126	4	similar	similar	ADJ
brj-22232	126	5	hyperbolic	hyperbolic	ADJ
brj-22232	126	6	features	feature	NOUN
brj-22232	126	7	as	as	ADP
brj-22232	126	8	the	the	DET
brj-22232	126	9	real	real	ADJ
brj-22232	126	10	image	image	NOUN
brj-22232	126	11	.	.	PUNCT
brj-22232	127	1	there	there	PRON
brj-22232	127	2	was	be	VERB
brj-22232	127	3	no	no	DET
brj-22232	127	4	noise	noise	NOUN
brj-22232	127	5	and	and	CCONJ
brj-22232	127	6	background	background	NOUN
brj-22232	127	7	,	,	PUNCT
brj-22232	127	8	and	and	CCONJ
brj-22232	127	9	the	the	DET
brj-22232	127	10	hyperbola	hyperbola	PROPN
brj-22232	127	11	was	be	AUX
brj-22232	127	12	clearer	clear	ADJ
brj-22232	127	13	,	,	PUNCT
brj-22232	127	14	which	which	PRON
brj-22232	127	15	could	could	AUX
brj-22232	127	16	be	be	AUX
brj-22232	127	17	used	use	VERB
brj-22232	127	18	as	as	ADP
brj-22232	127	19	the	the	DET
brj-22232	127	20	initial	initial	ADJ
brj-22232	127	21	noise	noise	NOUN
brj-22232	127	22	reduction	reduction	NOUN
brj-22232	127	23	of	of	ADP
brj-22232	127	24	the	the	DET
brj-22232	127	25	real	real	ADJ
brj-22232	127	26	image	image	NOUN
brj-22232	127	27	,	,	PUNCT
brj-22232	127	28	and	and	CCONJ
brj-22232	127	29	a	a	PRON
brj-22232	127	30	'	'	PUNCT
brj-22232	127	31	was	be	AUX
brj-22232	127	32	compared	compare	VERB
brj-22232	127	33	with	with	ADP
brj-22232	127	34	the	the	DET
brj-22232	127	35	b	b	NOUN
brj-22232	127	36	-	-	PUNCT
brj-22232	127	37	domain	domain	NOUN
brj-22232	127	38	simulation	simulation	NOUN
brj-22232	127	39	image	image	NOUN
brj-22232	127	40	by	by	ADP
brj-22232	127	41	db	db	PROPN
brj-22232	127	42	to	to	PART
brj-22232	127	43	discriminate	discriminate	VERB
brj-22232	127	44	whether	whether	SCONJ
brj-22232	127	45	a	a	DET
brj-22232	127	46	'	'	PUNCT
brj-22232	127	47	satisfies	satisfie	NOUN
brj-22232	127	48	the	the	DET
brj-22232	127	49	conditions	condition	NOUN
brj-22232	127	50	of	of	ADP
brj-22232	127	51	the	the	DET
brj-22232	127	52	b	b	NOUN
brj-22232	127	53	-	-	PUNCT
brj-22232	127	54	domain	domain	NOUN
brj-22232	127	55	images	image	NOUN
brj-22232	127	56	.	.	PUNCT
brj-22232	128	1	similarly	similarly	ADV
brj-22232	128	2	,	,	PUNCT
brj-22232	128	3	the	the	DET
brj-22232	128	4	simulation	simulation	NOUN
brj-22232	128	5	image	image	PROPN
brj-22232	128	6	b	b	PROPN
brj-22232	128	7	in	in	ADP
brj-22232	128	8	the	the	DET
brj-22232	128	9	b	b	NOUN
brj-22232	128	10	-	-	PUNCT
brj-22232	128	11	domain	domain	NOUN
brj-22232	128	12	was	be	AUX
brj-22232	128	13	transformed	transform	VERB
brj-22232	128	14	into	into	ADP
brj-22232	128	15	the	the	DET
brj-22232	128	16	corresponding	corresponding	ADJ
brj-22232	128	17	generated	generate	VERB
brj-22232	128	18	image	image	NOUN
brj-22232	128	19	b	b	NOUN
brj-22232	128	20	'	'	PUNCT
brj-22232	128	21	.	.	PUNCT
brj-22232	129	1	b	b	X
brj-22232	129	2	'	'	PUNCT
brj-22232	129	3	retained	retain	VERB
brj-22232	129	4	the	the	DET
brj-22232	129	5	hyperbolic	hyperbolic	ADJ
brj-22232	129	6	features	feature	NOUN
brj-22232	129	7	of	of	ADP
brj-22232	129	8	b	b	NOUN
brj-22232	129	9	and	and	CCONJ
brj-22232	129	10	added	add	VERB
brj-22232	129	11	noise	noise	NOUN
brj-22232	129	12	and	and	CCONJ
brj-22232	129	13	background	background	NOUN
brj-22232	129	14	.	.	PUNCT
brj-22232	130	1	b	b	X
brj-22232	130	2	'	'	PUNCT
brj-22232	130	3	was	be	AUX
brj-22232	130	4	compared	compare	VERB
brj-22232	130	5	with	with	ADP
brj-22232	130	6	the	the	DET
brj-22232	130	7	real	real	ADJ
brj-22232	130	8	image	image	NOUN
brj-22232	130	9	in	in	ADP
brj-22232	130	10	the	the	DET
brj-22232	130	11	a	a	DET
brj-22232	130	12	-	-	PUNCT
brj-22232	130	13	domain	domain	NOUN
brj-22232	130	14	by	by	ADP
brj-22232	130	15	da	da	PROPN
brj-22232	130	16	to	to	PART
brj-22232	130	17	discern	discern	VERB
brj-22232	130	18	whether	whether	SCONJ
brj-22232	130	19	b	b	X
brj-22232	130	20	'	'	PUNCT
brj-22232	130	21	satisfied	satisfy	VERB
brj-22232	130	22	the	the	DET
brj-22232	130	23	a	a	DET
brj-22232	130	24	-	-	PUNCT
brj-22232	130	25	domain	domain	NOUN
brj-22232	130	26	image	image	NOUN
brj-22232	130	27	.	.	PUNCT
brj-22232	131	1	meanwhile	meanwhile	ADV
brj-22232	131	2	,	,	PUNCT
brj-22232	131	3	a	a	PRON
brj-22232	131	4	'	'	PUNCT
brj-22232	131	5	was	be	AUX
brj-22232	131	6	input	input	NOUN
brj-22232	131	7	to	to	PART
brj-22232	131	8	generator	generator	VERB
brj-22232	131	9	gb	gb	ADP
brj-22232	131	10	to	to	PART
brj-22232	131	11	generate	generate	VERB
brj-22232	131	12	the	the	DET
brj-22232	131	13	reduced	reduce	VERB
brj-22232	131	14	image	image	NOUN
brj-22232	131	15	a	a	PRON
brj-22232	131	16	''	''	PUNCT
brj-22232	131	17	,	,	PUNCT
brj-22232	131	18	and	and	CCONJ
brj-22232	131	19	b	b	X
brj-22232	131	20	'	'	PUNCT
brj-22232	131	21	was	be	AUX
brj-22232	131	22	input	input	NOUN
brj-22232	131	23	to	to	ADP
brj-22232	131	24	generator	generator	PROPN
brj-22232	131	25	ga	ga	PROPN
brj-22232	131	26	to	to	PART
brj-22232	131	27	generate	generate	VERB
brj-22232	131	28	the	the	DET
brj-22232	131	29	reduced	reduced	ADJ
brj-22232	131	30	image	image	NOUN
brj-22232	131	31	b	b	NOUN
brj-22232	131	32	''	''	PUNCT
brj-22232	131	33	,	,	PUNCT
brj-22232	131	34	and	and	CCONJ
brj-22232	131	35	the	the	DET
brj-22232	131	36	cyclic	cyclic	ADJ
brj-22232	131	37	consistency	consistency	NOUN
brj-22232	131	38	loss	loss	NOUN
brj-22232	131	39	of	of	ADP
brj-22232	131	40	a	a	PRON
brj-22232	131	41	''	''	PUNCT
brj-22232	131	42	with	with	ADP
brj-22232	131	43	a	a	PRON
brj-22232	131	44	and	and	CCONJ
brj-22232	131	45	b	b	NOUN
brj-22232	131	46	''	''	PUNCT
brj-22232	131	47	with	with	ADP
brj-22232	131	48	b	b	PROPN
brj-22232	131	49	was	be	AUX
brj-22232	131	50	calculated	calculate	VERB
brj-22232	131	51	so	so	SCONJ
brj-22232	131	52	that	that	SCONJ
brj-22232	131	53	the	the	DET
brj-22232	131	54	hyperbolic	hyperbolic	ADJ
brj-22232	131	55	features	feature	NOUN
brj-22232	131	56	of	of	ADP
brj-22232	131	57	the	the	DET
brj-22232	131	58	original	original	ADJ
brj-22232	131	59	image	image	NOUN
brj-22232	131	60	were	be	AUX
brj-22232	131	61	still	still	ADV
brj-22232	131	62	retained	retain	VERB
brj-22232	131	63	while	while	SCONJ
brj-22232	131	64	the	the	DET
brj-22232	131	65	background	background	NOUN
brj-22232	131	66	and	and	CCONJ
brj-22232	131	67	noise	noise	NOUN
brj-22232	131	68	of	of	ADP
brj-22232	131	69	the	the	DET
brj-22232	131	70	generated	generate	VERB
brj-22232	131	71	image	image	NOUN
brj-22232	131	72	were	be	AUX
brj-22232	131	73	changed	change	VERB
brj-22232	131	74	.	.	PUNCT
brj-22232	132	1	fig	fig	NOUN
brj-22232	132	2	.	.	PUNCT
brj-22232	133	1	6	6	NUM
brj-22232	133	2	.	.	X
brj-22232	133	3	image	image	NOUN
brj-22232	133	4	style	style	NOUN
brj-22232	133	5	conversion	conversion	NOUN
brj-22232	133	6	diagram	diagram	NOUN
brj-22232	133	7	the	the	DET
brj-22232	133	8	conversion	conversion	NOUN
brj-22232	133	9	of	of	ADP
brj-22232	133	10	the	the	DET
brj-22232	133	11	real	real	ADJ
brj-22232	133	12	image	image	NOUN
brj-22232	133	13	to	to	ADP
brj-22232	133	14	the	the	DET
brj-22232	133	15	simulation	simulation	NOUN
brj-22232	133	16	image	image	NOUN
brj-22232	133	17	is	be	AUX
brj-22232	133	18	shown	show	VERB
brj-22232	133	19	in	in	ADP
brj-22232	133	20	fig	fig	NOUN
brj-22232	133	21	.	.	PUNCT
brj-22232	134	1	6	6	NUM
brj-22232	134	2	,	,	PUNCT
brj-22232	134	3	and	and	CCONJ
brj-22232	134	4	it	it	PRON
brj-22232	134	5	could	could	AUX
brj-22232	134	6	be	be	AUX
brj-22232	134	7	observed	observe	VERB
brj-22232	134	8	that	that	SCONJ
brj-22232	134	9	the	the	DET
brj-22232	134	10	generated	generate	VERB
brj-22232	134	11	image	image	NOUN
brj-22232	134	12	retained	retain	VERB
brj-22232	134	13	most	most	ADJ
brj-22232	134	14	of	of	ADP
brj-22232	134	15	the	the	DET
brj-22232	134	16	hyperbolic	hyperbolic	ADJ
brj-22232	134	17	features	feature	NOUN
brj-22232	134	18	in	in	ADP
brj-22232	134	19	the	the	DET
brj-22232	134	20	real	real	ADJ
brj-22232	134	21	image	image	NOUN
brj-22232	134	22	.	.	PUNCT
brj-22232	135	1	the	the	DET
brj-22232	135	2	converted	convert	VERB
brj-22232	135	3	image	image	NOUN
brj-22232	135	4	facilitated	facilitate	VERB
brj-22232	135	5	the	the	DET
brj-22232	135	6	next	next	ADJ
brj-22232	135	7	step	step	NOUN
brj-22232	135	8	of	of	ADP
brj-22232	135	9	hyperbolic	hyperbolic	ADJ
brj-22232	135	10	positioning	positioning	NOUN
brj-22232	135	11	and	and	CCONJ
brj-22232	135	12	research	research	NOUN
brj-22232	135	13	.	.	PUNCT
brj-22232	136	1	the	the	DET
brj-22232	136	2	disadvantage	disadvantage	NOUN
brj-22232	136	3	was	be	AUX
brj-22232	136	4	that	that	SCONJ
brj-22232	136	5	the	the	DET
brj-22232	136	6	generated	generate	VERB
brj-22232	136	7	images	image	NOUN
brj-22232	136	8	still	still	ADV
brj-22232	136	9	had	have	VERB
brj-22232	136	10	some	some	DET
brj-22232	136	11	missing	miss	VERB
brj-22232	136	12	features	feature	NOUN
brj-22232	136	13	,	,	PUNCT
brj-22232	136	14	and	and	CCONJ
brj-22232	136	15	the	the	DET
brj-22232	136	16	hyperbolic	hyperbolic	ADJ
brj-22232	136	17	features	feature	NOUN
brj-22232	136	18	were	be	AUX
brj-22232	136	19	more	more	ADV
brj-22232	136	20	complex	complex	ADJ
brj-22232	136	21	and	and	CCONJ
brj-22232	136	22	less	less	ADV
brj-22232	136	23	clear	clear	ADJ
brj-22232	136	24	than	than	ADP
brj-22232	136	25	the	the	DET
brj-22232	136	26	simulated	simulate	VERB
brj-22232	136	27	images	image	NOUN
brj-22232	136	28	generated	generate	VERB
brj-22232	136	29	by	by	ADP
brj-22232	136	30	gprmax	gprmax	PROPN
brj-22232	136	31	.	.	PUNCT
brj-22232	137	1	such	such	ADJ
brj-22232	137	2	images	image	NOUN
brj-22232	137	3	were	be	AUX
brj-22232	137	4	not	not	PART
brj-22232	137	5	convenient	convenient	ADJ
brj-22232	137	6	for	for	ADP
brj-22232	137	7	hyperbolic	hyperbolic	ADJ
brj-22232	137	8	labeling	labeling	NOUN
brj-22232	137	9	.	.	PUNCT
brj-22232	138	1	therefore	therefore	ADV
brj-22232	138	2	,	,	PUNCT
brj-22232	138	3	the	the	DET
brj-22232	138	4	real	real	ADJ
brj-22232	138	5	b	b	NOUN
brj-22232	138	6	-	-	PUNCT
brj-22232	138	7	scan	scan	ADJ
brj-22232	138	8	images	image	NOUN
brj-22232	138	9	,	,	PUNCT
brj-22232	138	10	the	the	DET
brj-22232	138	11	generated	generate	VERB
brj-22232	138	12	b	b	PROPN
brj-22232	138	13	-	-	PUNCT
brj-22232	138	14	scan	scan	ADJ
brj-22232	138	15	images	image	NOUN
brj-22232	138	16	,	,	PUNCT
brj-22232	138	17	and	and	CCONJ
brj-22232	138	18	the	the	DET
brj-22232	138	19	simulation	simulation	NOUN
brj-22232	138	20	images	image	NOUN
brj-22232	138	21	generated	generate	VERB
brj-22232	138	22	by	by	ADP
brj-22232	138	23	gprmax	gprmax	PROPN
brj-22232	138	24	were	be	AUX
brj-22232	138	25	used	use	VERB
brj-22232	138	26	to	to	PART
brj-22232	138	27	build	build	VERB
brj-22232	138	28	the	the	DET
brj-22232	138	29	hybrid	hybrid	NOUN
brj-22232	138	30	dataset	dataset	NOUN
brj-22232	138	31	in	in	ADP
brj-22232	138	32	the	the	DET
brj-22232	138	33	experiment	experiment	NOUN
brj-22232	138	34	.	.	PUNCT
brj-22232	139	1	to	to	PART
brj-22232	139	2	validate	validate	VERB
brj-22232	139	3	the	the	DET
brj-22232	139	4	feasibility	feasibility	NOUN
brj-22232	139	5	of	of	ADP
brj-22232	139	6	generating	generate	VERB
brj-22232	139	7	the	the	DET
brj-22232	139	8	b	b	NOUN
brj-22232	139	9	-	-	PUNCT
brj-22232	139	10	scan	scan	ADJ
brj-22232	139	11	dataset	dataset	NOUN
brj-22232	139	12	.	.	PUNCT
brj-22232	140	1	both	both	DET
brj-22232	140	2	cosine	cosine	NOUN
brj-22232	140	3	similarity	similarity	NOUN
brj-22232	140	4	and	and	CCONJ
brj-22232	140	5	ssim	ssim	NOUN
brj-22232	140	6	were	be	AUX
brj-22232	140	7	used	use	VERB
brj-22232	140	8	to	to	PART
brj-22232	140	9	evaluate	evaluate	VERB
brj-22232	140	10	the	the	DET
brj-22232	140	11	similar	similar	ADJ
brj-22232	140	12	relationship	relationship	NOUN
brj-22232	140	13	between	between	ADP
brj-22232	140	14	the	the	DET
brj-22232	140	15	real	real	ADJ
brj-22232	140	16	image	image	NOUN
brj-22232	140	17	a	a	PRON
brj-22232	140	18	and	and	CCONJ
brj-22232	140	19	the	the	DET
brj-22232	140	20	restored	restore	VERB
brj-22232	140	21	image	image	NOUN
brj-22232	140	22	a	a	PRON
brj-22232	140	23	''	''	PUNCT
brj-22232	140	24	.	.	PUNCT
brj-22232	141	1	peer	peer	NOUN
brj-22232	141	2	-	-	PUNCT
brj-22232	141	3	reviewed	review	VERB
brj-22232	141	4	article	article	NOUN
brj-22232	141	5	bioresources.com	bioresources.com	X
brj-22232	141	6	li	li	PROPN
brj-22232	141	7	et	et	PROPN
brj-22232	141	8	al	al	PROPN
brj-22232	141	9	.	.	PROPN
brj-22232	141	10	(	(	PUNCT
brj-22232	141	11	2023	2023	NUM
brj-22232	141	12	)	)	PUNCT
brj-22232	141	13	.	.	PUNCT
brj-22232	142	1	“	"	PUNCT
brj-22232	142	2	tree	tree	NOUN
brj-22232	142	3	root	root	NOUN
brj-22232	142	4	detection	detection	NOUN
brj-22232	142	5	training	training	NOUN
brj-22232	142	6	,	,	PUNCT
brj-22232	142	7	”	"	PUNCT
brj-22232	142	8	bioresources	bioresource	NOUN
brj-22232	142	9	18(1	18(1	NOUN
brj-22232	142	10	)	)	PUNCT
brj-22232	142	11	,	,	PUNCT
brj-22232	142	12	484	484	NUM
brj-22232	142	13	-	-	SYM
brj-22232	142	14	504	504	NUM
brj-22232	142	15	.	.	PUNCT
brj-22232	143	1	491	491	NUM
brj-22232	143	2	structural	structural	ADJ
brj-22232	143	3	similarity	similarity	NOUN
brj-22232	143	4	index	index	NOUN
brj-22232	143	5	measure	measure	NOUN
brj-22232	143	6	(	(	PUNCT
brj-22232	143	7	ssim	ssim	NOUN
brj-22232	143	8	)	)	PUNCT
brj-22232	143	9	is	be	AUX
brj-22232	143	10	a	a	DET
brj-22232	143	11	single	single	ADJ
brj-22232	143	12	-	-	PUNCT
brj-22232	143	13	scale	scale	NOUN
brj-22232	143	14	image	image	NOUN
brj-22232	143	15	structural	structural	ADJ
brj-22232	143	16	similarity	similarity	NOUN
brj-22232	143	17	,	,	PUNCT
brj-22232	143	18	which	which	PRON
brj-22232	143	19	is	be	AUX
brj-22232	143	20	widely	widely	ADV
brj-22232	143	21	used	use	VERB
brj-22232	143	22	as	as	ADP
brj-22232	143	23	a	a	DET
brj-22232	143	24	measure	measure	NOUN
brj-22232	143	25	of	of	ADP
brj-22232	143	26	structural	structural	ADJ
brj-22232	143	27	similarity	similarity	NOUN
brj-22232	143	28	between	between	ADP
brj-22232	143	29	images	image	NOUN
brj-22232	143	30	.	.	PUNCT
brj-22232	144	1	its	its	PRON
brj-22232	144	2	value	value	NOUN
brj-22232	144	3	is	be	AUX
brj-22232	144	4	distributed	distribute	VERB
brj-22232	144	5	in	in	ADP
brj-22232	144	6	range	range	NOUN
brj-22232	144	7	of	of	ADP
brj-22232	144	8	0	0	NUM
brj-22232	144	9	to	to	PART
brj-22232	144	10	1	1	NUM
brj-22232	144	11	,	,	PUNCT
brj-22232	144	12	and	and	CCONJ
brj-22232	144	13	a	a	DET
brj-22232	144	14	value	value	NOUN
brj-22232	144	15	closer	close	ADV
brj-22232	144	16	to	to	PART
brj-22232	144	17	1	1	NUM
brj-22232	144	18	translates	translate	VERB
brj-22232	144	19	to	to	ADP
brj-22232	144	20	more	more	ADJ
brj-22232	144	21	similarity	similarity	NOUN
brj-22232	144	22	between	between	ADP
brj-22232	144	23	the	the	DET
brj-22232	144	24	two	two	NUM
brj-22232	144	25	images	image	NOUN
brj-22232	144	26	,	,	PUNCT
brj-22232	144	27	and	and	CCONJ
brj-22232	144	28	a	a	DET
brj-22232	144	29	value	value	NOUN
brj-22232	144	30	closer	close	ADV
brj-22232	144	31	to	to	ADP
brj-22232	144	32	0	0	NUM
brj-22232	144	33	means	mean	VERB
brj-22232	144	34	there	there	PRON
brj-22232	144	35	is	be	VERB
brj-22232	144	36	less	less	ADJ
brj-22232	144	37	similarity	similarity	NOUN
brj-22232	144	38	between	between	ADP
brj-22232	144	39	the	the	DET
brj-22232	144	40	two	two	NUM
brj-22232	144	41	images	image	NOUN
brj-22232	144	42	.	.	PUNCT
brj-22232	145	1	the	the	DET
brj-22232	145	2	brightness	brightness	NOUN
brj-22232	145	3	,	,	PUNCT
brj-22232	145	4	contrast	contrast	NOUN
brj-22232	145	5	,	,	PUNCT
brj-22232	145	6	and	and	CCONJ
brj-22232	145	7	structural	structural	ADJ
brj-22232	145	8	similarity	similarity	NOUN
brj-22232	145	9	of	of	ADP
brj-22232	145	10	the	the	DET
brj-22232	145	11	two	two	NUM
brj-22232	145	12	images	image	NOUN
brj-22232	145	13	are	be	AUX
brj-22232	145	14	reflected	reflect	VERB
brj-22232	145	15	by	by	ADP
brj-22232	145	16	the	the	DET
brj-22232	145	17	mean	mean	ADJ
brj-22232	145	18	,	,	PUNCT
brj-22232	145	19	standard	standard	ADJ
brj-22232	145	20	deviation	deviation	NOUN
brj-22232	145	21	,	,	PUNCT
brj-22232	145	22	and	and	CCONJ
brj-22232	145	23	covariance	covariance	NOUN
brj-22232	145	24	of	of	ADP
brj-22232	145	25	the	the	DET
brj-22232	145	26	images	image	NOUN
brj-22232	145	27	,	,	PUNCT
brj-22232	145	28	which	which	PRON
brj-22232	145	29	are	be	AUX
brj-22232	145	30	calculated	calculate	VERB
brj-22232	145	31	as	as	SCONJ
brj-22232	145	32	follows	follow	VERB
brj-22232	145	33	.	.	PUNCT
brj-22232	146	1			ADJ
brj-22232	146	2			ADP
brj-22232	146	3			ADJ
brj-22232	146	4			PUNCT
brj-22232	146	5			PROPN
brj-22232	146	6			PROPN
brj-22232	146	7	(	(	PUNCT
brj-22232	146	8	,	,	PUNCT
brj-22232	146	9	)	)	PUNCT
brj-22232	146	10	(	(	PUNCT
brj-22232	146	11	,	,	PUNCT
brj-22232	146	12	)	)	PUNCT
brj-22232	146	13	(	(	PUNCT
brj-22232	146	14	,	,	PUNCT
brj-22232	146	15	)	)	PUNCT
brj-22232	146	16	(	(	PUNCT
brj-22232	146	17	,	,	PUNCT
brj-22232	146	18	)	)	PUNCT
brj-22232	146	19	ssim	ssim	NOUN
brj-22232	147	1	x	x	X
brj-22232	147	2	y	y	NOUN
brj-22232	147	3	l	l	NOUN
brj-22232	147	4	x	x	PUNCT
brj-22232	147	5	y	y	NOUN
brj-22232	147	6	c	c	NOUN
brj-22232	147	7	x	x	VERB
brj-22232	147	8	y	y	NOUN
brj-22232	147	9	s	s	PROPN
brj-22232	147	10	x	x	VERB
brj-22232	147	11	y	y	PROPN
brj-22232	147	12			NUM
brj-22232	147	13			PROPN
brj-22232	147	14			NUM
brj-22232	147	15	=	=	PUNCT
brj-22232	147	16	(	(	PUNCT
brj-22232	147	17	1	1	NUM
brj-22232	147	18	)	)	SYM
brj-22232	147	19	2	2	NUM
brj-22232	147	20	2	2	NUM
brj-22232	147	21	1	1	NUM
brj-22232	147	22	1	1	NUM
brj-22232	147	23	(	(	PUNCT
brj-22232	147	24	,	,	PUNCT
brj-22232	147	25	)	)	PUNCT
brj-22232	147	26	(	(	PUNCT
brj-22232	147	27	2	2	X
brj-22232	147	28	)	)	PUNCT
brj-22232	147	29	(	(	PUNCT
brj-22232	147	30	)	)	PUNCT
brj-22232	147	31	x	x	SYM
brj-22232	147	32	y	y	NOUN
brj-22232	147	33	x	x	SYM
brj-22232	147	34	yl	yl	NOUN
brj-22232	147	35	x	x	PUNCT
brj-22232	147	36	y	y	VERB
brj-22232	147	37	u	u	X
brj-22232	148	1	u	u	VERB
brj-22232	148	2	c	c	NOUN
brj-22232	148	3	u	u	NOUN
brj-22232	148	4	u	u	NOUN
brj-22232	148	5	c=	c=	NOUN
brj-22232	148	6	+	+	X
brj-22232	149	1	+	+	CCONJ
brj-22232	149	2	+	+	CCONJ
brj-22232	149	3	(	(	PUNCT
brj-22232	149	4	2	2	NUM
brj-22232	149	5	)	)	SYM
brj-22232	149	6	2	2	NUM
brj-22232	149	7	2	2	NUM
brj-22232	149	8	2	2	NUM
brj-22232	149	9	2	2	NUM
brj-22232	149	10	(	(	PUNCT
brj-22232	149	11	,	,	PUNCT
brj-22232	149	12	)	)	PUNCT
brj-22232	149	13	(	(	PUNCT
brj-22232	149	14	2	2	X
brj-22232	149	15	)	)	PUNCT
brj-22232	149	16	(	(	PUNCT
brj-22232	149	17	)	)	PUNCT
brj-22232	149	18	x	x	SYM
brj-22232	150	1	y	y	NOUN
brj-22232	150	2	x	x	PUNCT
brj-22232	150	3	yc	yc	X
brj-22232	150	4	x	x	VERB
brj-22232	150	5	y	y	PROPN
brj-22232	150	6	c	c	PROPN
brj-22232	150	7	c	c	PROPN
brj-22232	150	8			X
brj-22232	150	9			PROPN
brj-22232	150	10	=	=	NOUN
brj-22232	150	11	+	+	X
brj-22232	151	1	+	+	PUNCT
brj-22232	151	2	+	+	CCONJ
brj-22232	151	3	(	(	PUNCT
brj-22232	151	4	3	3	NUM
brj-22232	151	5	)	)	PUNCT
brj-22232	151	6	3	3	NUM
brj-22232	151	7	3	3	NUM
brj-22232	151	8	(	(	PUNCT
brj-22232	151	9	,	,	PUNCT
brj-22232	151	10	)	)	PUNCT
brj-22232	151	11	xy	xy	PUNCT
brj-22232	152	1	x	x	PUNCT
brj-22232	152	2	ys	ys	VERB
brj-22232	152	3	y	y	PROPN
brj-22232	152	4	c	c	PROPN
brj-22232	152	5	cx	cx	PROPN
brj-22232	152	6			PROPN
brj-22232	152	7			X
brj-22232	152	8			X
brj-22232	152	9	+	+	NOUN
brj-22232	152	10	=	=	X
brj-22232	152	11	+	+	CCONJ
brj-22232	152	12	(	(	PUNCT
brj-22232	152	13	4	4	NUM
brj-22232	152	14	)	)	PUNCT
brj-22232	152	15	where	where	SCONJ
brj-22232	152	16	𝑢𝑥	𝑢𝑥	ADP
brj-22232	152	17	and	and	CCONJ
brj-22232	152	18	𝑢𝑦	𝑢𝑦	PRON
brj-22232	152	19	indicate	indicate	VERB
brj-22232	152	20	the	the	DET
brj-22232	152	21	average	average	ADJ
brj-22232	152	22	value	value	NOUN
brj-22232	152	23	of	of	ADP
brj-22232	152	24	image	image	NOUN
brj-22232	152	25	𝑥	𝑥	PROPN
brj-22232	152	26	and	and	CCONJ
brj-22232	152	27	𝑦	𝑦	NOUN
brj-22232	152	28	,	,	PUNCT
brj-22232	152	29	respectively	respectively	ADV
brj-22232	152	30	,	,	PUNCT
brj-22232	152	31	x	x	PROPN
brj-22232	152	32	and	and	CCONJ
brj-22232	152	33	y	y	PROPN
brj-22232	152	34	indicate	indicate	VERB
brj-22232	152	35	the	the	DET
brj-22232	152	36	standard	standard	ADJ
brj-22232	152	37	deviation	deviation	NOUN
brj-22232	152	38	of	of	ADP
brj-22232	152	39	image	image	NOUN
brj-22232	152	40	𝑥	𝑥	PROPN
brj-22232	152	41	and	and	CCONJ
brj-22232	152	42	𝑦	𝑦	NOUN
brj-22232	152	43	,	,	PUNCT
brj-22232	152	44	respectively	respectively	ADV
brj-22232	152	45	,	,	PUNCT
brj-22232	152	46	and	and	CCONJ
brj-22232	152	47	xy	xy	INTJ
brj-22232	152	48	indicates	indicate	VERB
brj-22232	152	49	the	the	DET
brj-22232	152	50	covariance	covariance	NOUN
brj-22232	152	51	of	of	ADP
brj-22232	152	52	image	image	NOUN
brj-22232	152	53	𝑥	𝑥	PROPN
brj-22232	152	54	and	and	CCONJ
brj-22232	152	55	𝑦.	𝑦.	PROPN
brj-22232	152	56	then	then	ADV
brj-22232	152	57	𝑐1	𝑐1	NOUN
brj-22232	152	58	,	,	PUNCT
brj-22232	152	59	𝑐2	𝑐2	NOUN
brj-22232	152	60	,	,	PUNCT
brj-22232	152	61	and	and	CCONJ
brj-22232	152	62	𝑐3	𝑐3	NOUN
brj-22232	152	63	are	be	AUX
brj-22232	152	64	the	the	DET
brj-22232	152	65	very	very	ADV
brj-22232	152	66	small	small	ADJ
brj-22232	152	67	numbers	number	NOUN
brj-22232	152	68	,	,	PUNCT
brj-22232	152	69	which	which	PRON
brj-22232	152	70	are	be	AUX
brj-22232	152	71	designed	design	VERB
brj-22232	152	72	to	to	PART
brj-22232	152	73	avoid	avoid	VERB
brj-22232	152	74	the	the	DET
brj-22232	152	75	case	case	NOUN
brj-22232	152	76	of	of	ADP
brj-22232	152	77	zero	zero	NUM
brj-22232	152	78	denominator	denominator	NOUN
brj-22232	152	79	in	in	ADP
brj-22232	152	80	the	the	DET
brj-22232	152	81	above	above	ADJ
brj-22232	152	82	equation	equation	NOUN
brj-22232	152	83	.	.	PUNCT
brj-22232	153	1	cosine	cosine	NOUN
brj-22232	153	2	similarity	similarity	NOUN
brj-22232	153	3	is	be	AUX
brj-22232	153	4	also	also	ADV
brj-22232	153	5	called	call	VERB
brj-22232	153	6	cosine	cosine	NOUN
brj-22232	153	7	distance	distance	NOUN
brj-22232	153	8	.	.	PUNCT
brj-22232	154	1	this	this	DET
brj-22232	154	2	method	method	NOUN
brj-22232	154	3	uses	use	VERB
brj-22232	154	4	the	the	DET
brj-22232	154	5	cosine	cosine	NOUN
brj-22232	154	6	of	of	ADP
brj-22232	154	7	the	the	DET
brj-22232	154	8	angle	angle	NOUN
brj-22232	154	9	between	between	ADP
brj-22232	154	10	two	two	NUM
brj-22232	154	11	vectors	vector	NOUN
brj-22232	154	12	in	in	ADP
brj-22232	154	13	vector	vector	NOUN
brj-22232	154	14	space	space	NOUN
brj-22232	154	15	to	to	PART
brj-22232	154	16	evaluate	evaluate	VERB
brj-22232	154	17	the	the	DET
brj-22232	154	18	difference	difference	NOUN
brj-22232	154	19	between	between	ADP
brj-22232	154	20	two	two	NUM
brj-22232	154	21	images	image	NOUN
brj-22232	154	22	.	.	PUNCT
brj-22232	155	1	the	the	DET
brj-22232	155	2	similarity	similarity	NOUN
brj-22232	155	3	(	(	PUNCT
brj-22232	155	4	eq	eq	NOUN
brj-22232	155	5	.	.	NOUN
brj-22232	155	6	5	5	NUM
brj-22232	155	7	)	)	PUNCT
brj-22232	155	8	is	be	AUX
brj-22232	155	9	as	as	SCONJ
brj-22232	155	10	follows	follow	VERB
brj-22232	155	11	,	,	PUNCT
brj-22232	155	12	2	2	NUM
brj-22232	155	13	2	2	NUM
brj-22232	155	14	(	(	PUNCT
brj-22232	155	15	1	1	NUM
brj-22232	155	16	)	)	PUNCT
brj-22232	155	17	(	(	PUNCT
brj-22232	155	18	1	1	X
brj-22232	155	19	)	)	PUNCT
brj-22232	155	20	(	(	PUNCT
brj-22232	155	21	1	1	X
brj-22232	155	22	)	)	PUNCT
brj-22232	155	23	(	(	PUNCT
brj-22232	155	24	,	,	PUNCT
brj-22232	155	25	)	)	PUNCT
brj-22232	155	26	||	||	PUNCT
brj-22232	156	1	||	||	NOUN
brj-22232	157	1	||	||	NOUN
brj-22232	158	1	||	||	PROPN
brj-22232	159	1	(	(	PUNCT
brj-22232	159	2	)	)	PUNCT
brj-22232	159	3	n	n	CCONJ
brj-22232	159	4	n	n	CCONJ
brj-22232	159	5	n	n	NOUN
brj-22232	160	1	i	i	PRON
brj-22232	160	2	i	i	PRON
brj-22232	161	1	i	i	PRON
brj-22232	161	2	i	i	PRON
brj-22232	162	1	i	i	PRON
brj-22232	162	2	i	i	PRON
brj-22232	163	1	i	i	PRON
brj-22232	163	2	similarity	similarity	VERB
brj-22232	163	3	a	a	DET
brj-22232	163	4	b	b	NOUN
brj-22232	163	5	a	a	DET
brj-22232	163	6	b	b	NOUN
brj-22232	163	7	a	a	DET
brj-22232	163	8	b	b	NOUN
brj-22232	163	9	a	a	DET
brj-22232	163	10	b	b	NOUN
brj-22232	163	11	ba	ba	NOUN
brj-22232	163	12	=	=	PUNCT
brj-22232	164	1	=	=	PUNCT
brj-22232	164	2	=	=	PUNCT
brj-22232	164	3			NOUN
brj-22232	164	4			NOUN
brj-22232	164	5	=	=	PUNCT
brj-22232	164	6			NUM
brj-22232	164	7			NOUN
brj-22232	164	8	=	=	PROPN
brj-22232	164	9			PROPN
brj-22232	164	10			PROPN
brj-22232	164	11			PROPN
brj-22232	164	12			PROPN
brj-22232	165	1			PROPN
brj-22232	165	2			NOUN
brj-22232	165	3			NOUN
brj-22232	165	4			X
brj-22232	165	5			X
brj-22232	165	6			X
brj-22232	165	7	(	(	PUNCT
brj-22232	165	8	5	5	NUM
brj-22232	165	9	)	)	PUNCT
brj-22232	165	10	where	where	SCONJ
brj-22232	165	11	𝐴	𝐴	PROPN
brj-22232	165	12	and	and	CCONJ
brj-22232	165	13	𝐵	𝐵	PROPN
brj-22232	165	14	represent	represent	VERB
brj-22232	165	15	two	two	NUM
brj-22232	165	16	vectors	vector	NOUN
brj-22232	165	17	,	,	PUNCT
brj-22232	165	18	the	the	PRON
brj-22232	165	19	closer	close	ADV
brj-22232	165	20	the	the	DET
brj-22232	165	21	angle	angle	NOUN
brj-22232	165	22	is	be	AUX
brj-22232	165	23	to	to	ADP
brj-22232	165	24	0	0	NUM
brj-22232	165	25	°	°	NUM
brj-22232	165	26	,	,	PUNCT
brj-22232	165	27	the	the	PRON
brj-22232	165	28	closer	close	ADV
brj-22232	165	29	the	the	DET
brj-22232	165	30	cosine	cosine	NOUN
brj-22232	165	31	value	value	NOUN
brj-22232	165	32	is	be	AUX
brj-22232	165	33	to	to	ADP
brj-22232	165	34	1	1	NUM
brj-22232	165	35	,	,	PUNCT
brj-22232	165	36	which	which	PRON
brj-22232	165	37	means	mean	VERB
brj-22232	165	38	the	the	DET
brj-22232	165	39	more	more	ADV
brj-22232	165	40	similar	similar	ADJ
brj-22232	165	41	the	the	PRON
brj-22232	165	42	between	between	ADP
brj-22232	165	43	two	two	NUM
brj-22232	165	44	vectors	vector	NOUN
brj-22232	165	45	.	.	PUNCT
brj-22232	166	1	the	the	DET
brj-22232	166	2	authors	author	NOUN
brj-22232	166	3	calculated	calculate	VERB
brj-22232	166	4	the	the	DET
brj-22232	166	5	cosine	cosine	NOUN
brj-22232	166	6	similarity	similarity	NOUN
brj-22232	166	7	between	between	ADP
brj-22232	166	8	images	image	NOUN
brj-22232	166	9	in	in	ADP
brj-22232	166	10	the	the	DET
brj-22232	166	11	a	a	DET
brj-22232	166	12	-	-	PUNCT
brj-22232	166	13	domain	domain	NOUN
brj-22232	166	14	and	and	CCONJ
brj-22232	166	15	the	the	DET
brj-22232	166	16	corresponding	corresponding	ADJ
brj-22232	166	17	reduced	reduce	VERB
brj-22232	166	18	images	image	NOUN
brj-22232	166	19	a	a	PRON
brj-22232	166	20	''	''	PUNCT
brj-22232	166	21	to	to	PART
brj-22232	166	22	be	be	AUX
brj-22232	166	23	0.923	0.923	NUM
brj-22232	166	24	,	,	PUNCT
brj-22232	166	25	and	and	CCONJ
brj-22232	166	26	the	the	DET
brj-22232	166	27	ssim	ssim	NOUN
brj-22232	166	28	was	be	AUX
brj-22232	166	29	0.894	0.894	NUM
brj-22232	166	30	.	.	PUNCT
brj-22232	167	1	the	the	DET
brj-22232	167	2	results	result	NOUN
brj-22232	167	3	showed	show	VERB
brj-22232	167	4	that	that	SCONJ
brj-22232	167	5	the	the	DET
brj-22232	167	6	generated	generate	VERB
brj-22232	167	7	b	b	NOUN
brj-22232	167	8	-	-	PUNCT
brj-22232	167	9	scan	scan	ADJ
brj-22232	167	10	images	image	NOUN
brj-22232	167	11	retained	retain	VERB
brj-22232	167	12	the	the	DET
brj-22232	167	13	hyperbolic	hyperbolic	ADJ
brj-22232	167	14	features	feature	NOUN
brj-22232	167	15	of	of	ADP
brj-22232	167	16	the	the	DET
brj-22232	167	17	real	real	ADJ
brj-22232	167	18	images	image	NOUN
brj-22232	167	19	and	and	CCONJ
brj-22232	167	20	generated	generate	VERB
brj-22232	167	21	the	the	DET
brj-22232	167	22	background	background	NOUN
brj-22232	167	23	and	and	CCONJ
brj-22232	167	24	noise	noise	NOUN
brj-22232	167	25	features	feature	NOUN
brj-22232	167	26	similar	similar	ADJ
brj-22232	167	27	to	to	ADP
brj-22232	167	28	the	the	DET
brj-22232	167	29	real	real	ADJ
brj-22232	167	30	images	image	NOUN
brj-22232	167	31	.	.	PUNCT
brj-22232	168	1	extending	extend	VERB
brj-22232	168	2	the	the	DET
brj-22232	168	3	real	real	ADJ
brj-22232	168	4	dataset	dataset	NOUN
brj-22232	168	5	was	be	AUX
brj-22232	168	6	feasible	feasible	ADJ
brj-22232	168	7	by	by	ADP
brj-22232	168	8	generating	generate	VERB
brj-22232	168	9	b	b	X
brj-22232	168	10	-	-	PUNCT
brj-22232	168	11	scan	scan	ADJ
brj-22232	168	12	images	image	NOUN
brj-22232	168	13	with	with	ADP
brj-22232	168	14	cyclegan	cyclegan	NOUN
brj-22232	168	15	.	.	PUNCT
brj-22232	169	1	the	the	DET
brj-22232	169	2	759	759	NUM
brj-22232	169	3	data	datum	NOUN
brj-22232	169	4	of	of	ADP
brj-22232	169	5	the	the	DET
brj-22232	169	6	simulation	simulation	NOUN
brj-22232	169	7	images	image	NOUN
brj-22232	169	8	were	be	AUX
brj-22232	169	9	transformed	transform	VERB
brj-22232	169	10	by	by	ADP
brj-22232	169	11	cyclegan	cyclegan	NOUN
brj-22232	169	12	to	to	PART
brj-22232	169	13	obtain	obtain	VERB
brj-22232	169	14	the	the	DET
brj-22232	169	15	generated	generate	VERB
brj-22232	169	16	image	image	NOUN
brj-22232	169	17	data	datum	NOUN
brj-22232	169	18	,	,	PUNCT
brj-22232	169	19	and	and	CCONJ
brj-22232	169	20	original	original	ADJ
brj-22232	169	21	data	datum	NOUN
brj-22232	169	22	of	of	ADP
brj-22232	169	23	the	the	DET
brj-22232	169	24	three	three	NUM
brj-22232	169	25	types	type	NOUN
brj-22232	169	26	of	of	ADP
brj-22232	169	27	images	image	NOUN
brj-22232	169	28	were	be	AUX
brj-22232	169	29	annotated	annotate	VERB
brj-22232	169	30	using	use	VERB
brj-22232	169	31	labelimg	labelimg	NOUN
brj-22232	169	32	,	,	PUNCT
brj-22232	169	33	where	where	SCONJ
brj-22232	169	34	yolov5	yolov5	NOUN
brj-22232	169	35	used	use	VERB
brj-22232	169	36	txt	txt	PROPN
brj-22232	169	37	format	format	NOUN
brj-22232	169	38	,	,	PUNCT
brj-22232	169	39	faster	fast	ADJ
brj-22232	169	40	r	r	NOUN
brj-22232	169	41	-	-	PUNCT
brj-22232	169	42	cnn	cnn	PROPN
brj-22232	169	43	and	and	CCONJ
brj-22232	169	44	yolov3	yolov3	PROPN
brj-22232	169	45	used	use	VERB
brj-22232	169	46	xml	xml	NOUN
brj-22232	169	47	format	format	NOUN
brj-22232	169	48	for	for	ADP
brj-22232	169	49	annotation	annotation	NOUN
brj-22232	169	50	,	,	PUNCT
brj-22232	169	51	and	and	CCONJ
brj-22232	169	52	centernet	centernet	NOUN
brj-22232	169	53	used	use	VERB
brj-22232	169	54	json	json	NOUN
brj-22232	169	55	format	format	NOUN
brj-22232	169	56	.	.	PUNCT
brj-22232	170	1	the	the	DET
brj-22232	170	2	annotation	annotation	NOUN
brj-22232	170	3	information	information	NOUN
brj-22232	170	4	could	could	AUX
brj-22232	170	5	indicate	indicate	VERB
brj-22232	170	6	the	the	DET
brj-22232	170	7	location	location	NOUN
brj-22232	170	8	and	and	CCONJ
brj-22232	170	9	size	size	NOUN
brj-22232	170	10	of	of	ADP
brj-22232	170	11	the	the	DET
brj-22232	170	12	tree	tree	NOUN
brj-22232	170	13	roots	root	NOUN
brj-22232	170	14	.	.	PUNCT
brj-22232	171	1	traditional	traditional	ADJ
brj-22232	171	2	offline	offline	ADJ
brj-22232	171	3	data	datum	NOUN
brj-22232	171	4	augmentation	augmentation	NOUN
brj-22232	171	5	(	(	PUNCT
brj-22232	171	6	random	random	ADJ
brj-22232	171	7	horizontal	horizontal	ADJ
brj-22232	171	8	flip	flip	NOUN
brj-22232	171	9	,	,	PUNCT
brj-22232	171	10	random	random	ADJ
brj-22232	171	11	distortion	distortion	NOUN
brj-22232	171	12	,	,	PUNCT
brj-22232	171	13	gaussian	gaussian	NOUN
brj-22232	171	14	blur	blur	NOUN
brj-22232	171	15	,	,	PUNCT
brj-22232	171	16	and	and	CCONJ
brj-22232	171	17	random	random	ADJ
brj-22232	171	18	stretching	stretching	NOUN
brj-22232	171	19	)	)	PUNCT
brj-22232	171	20	was	be	AUX
brj-22232	171	21	performed	perform	VERB
brj-22232	171	22	on	on	ADP
brj-22232	171	23	each	each	DET
brj-22232	171	24	type	type	NOUN
brj-22232	171	25	of	of	ADP
brj-22232	171	26	labeled	label	VERB
brj-22232	171	27	image	image	NOUN
brj-22232	171	28	,	,	PUNCT
brj-22232	171	29	as	as	SCONJ
brj-22232	171	30	shown	show	VERB
brj-22232	171	31	in	in	ADP
brj-22232	171	32	table	table	NOUN
brj-22232	171	33	1	1	NUM
brj-22232	171	34	.	.	PUNCT
brj-22232	171	35	table	table	NOUN
brj-22232	171	36	1	1	NUM
brj-22232	171	37	.	.	PUNCT
brj-22232	171	38	data	datum	NOUN
brj-22232	171	39	distribution	distribution	NOUN
brj-22232	171	40	image	image	NOUN
brj-22232	171	41	original	original	ADJ
brj-22232	171	42	quantity	quantity	NOUN
brj-22232	171	43	enhanced	enhance	VERB
brj-22232	171	44	multipliers	multiplier	NOUN
brj-22232	171	45	enhanced	enhance	VERB
brj-22232	171	46	quantity	quantity	NOUN
brj-22232	171	47	training	training	NOUN
brj-22232	171	48	images	image	NOUN
brj-22232	171	49	validation	validation	NOUN
brj-22232	171	50	images	image	NOUN
brj-22232	171	51	testing	testing	NOUN
brj-22232	171	52	images	image	NOUN
brj-22232	171	53	real	real	ADJ
brj-22232	171	54	images	image	NOUN
brj-22232	171	55	759	759	NUM
brj-22232	171	56	15	15	NUM
brj-22232	171	57	12144	12144	NUM
brj-22232	171	58	10000	10000	NUM
brj-22232	171	59	1144	1144	NUM
brj-22232	171	60	1000	1000	NUM
brj-22232	171	61	simulation	simulation	NOUN
brj-22232	171	62	images	image	VERB
brj-22232	171	63	759	759	NUM
brj-22232	171	64	15	15	NUM
brj-22232	171	65	12144	12144	NUM
brj-22232	171	66	10000	10000	NUM
brj-22232	171	67	1144	1144	NUM
brj-22232	171	68	1000	1000	NUM
brj-22232	171	69	generate	generate	VERB
brj-22232	171	70	images	image	NOUN
brj-22232	171	71	759	759	NUM
brj-22232	171	72	15	15	NUM
brj-22232	171	73	12144	12144	NUM
brj-22232	171	74	10000	10000	NUM
brj-22232	171	75	1144	1144	NUM
brj-22232	171	76	1000	1000	NUM
brj-22232	171	77	peer	peer	NOUN
brj-22232	171	78	-	-	PUNCT
brj-22232	171	79	reviewed	review	VERB
brj-22232	171	80	article	article	NOUN
brj-22232	171	81	bioresources.com	bioresources.com	X
brj-22232	171	82	li	li	PROPN
brj-22232	171	83	et	et	PROPN
brj-22232	171	84	al	al	PROPN
brj-22232	171	85	.	.	PROPN
brj-22232	172	1	(	(	PUNCT
brj-22232	172	2	2023	2023	NUM
brj-22232	172	3	)	)	PUNCT
brj-22232	172	4	.	.	PUNCT
brj-22232	173	1	“	"	PUNCT
brj-22232	173	2	tree	tree	NOUN
brj-22232	173	3	root	root	NOUN
brj-22232	173	4	detection	detection	NOUN
brj-22232	173	5	training	training	NOUN
brj-22232	173	6	,	,	PUNCT
brj-22232	173	7	”	"	PUNCT
brj-22232	173	8	bioresources	bioresource	NOUN
brj-22232	173	9	18(1	18(1	NOUN
brj-22232	173	10	)	)	PUNCT
brj-22232	173	11	,	,	PUNCT
brj-22232	173	12	484	484	NUM
brj-22232	173	13	-	-	SYM
brj-22232	173	14	504	504	NUM
brj-22232	173	15	.	.	PUNCT
brj-22232	173	16	492	492	NUM
brj-22232	173	17	as	as	SCONJ
brj-22232	173	18	shown	show	VERB
brj-22232	173	19	in	in	ADP
brj-22232	173	20	fig	fig	NOUN
brj-22232	173	21	.	.	PUNCT
brj-22232	174	1	7	7	NUM
brj-22232	174	2	,	,	PUNCT
brj-22232	174	3	the	the	DET
brj-22232	174	4	authors	author	NOUN
brj-22232	174	5	deployed	deploy	VERB
brj-22232	174	6	the	the	DET
brj-22232	174	7	noise	noise	NOUN
brj-22232	174	8	reduction	reduction	NOUN
brj-22232	174	9	function	function	NOUN
brj-22232	174	10	of	of	ADP
brj-22232	174	11	cyclegan	cyclegan	NOUN
brj-22232	174	12	to	to	ADP
brj-22232	174	13	the	the	DET
brj-22232	174	14	designed	design	VERB
brj-22232	174	15	tree	tree	NOUN
brj-22232	174	16	management	management	NOUN
brj-22232	174	17	information	information	NOUN
brj-22232	174	18	system	system	NOUN
brj-22232	174	19	,	,	PUNCT
brj-22232	174	20	and	and	CCONJ
brj-22232	174	21	the	the	DET
brj-22232	174	22	developed	develop	VERB
brj-22232	174	23	tree	tree	NOUN
brj-22232	174	24	management	management	NOUN
brj-22232	174	25	information	information	NOUN
brj-22232	174	26	system	system	NOUN
brj-22232	174	27	is	be	AUX
brj-22232	174	28	able	able	ADJ
brj-22232	174	29	to	to	PART
brj-22232	174	30	process	process	VERB
brj-22232	174	31	and	and	CCONJ
brj-22232	174	32	analyze	analyze	VERB
brj-22232	174	33	the	the	DET
brj-22232	174	34	gpr	gpr	PROPN
brj-22232	174	35	b	b	PROPN
brj-22232	174	36	-	-	PUNCT
brj-22232	174	37	scan	scan	ADJ
brj-22232	174	38	images	image	NOUN
brj-22232	174	39	online	online	ADV
brj-22232	174	40	,	,	PUNCT
brj-22232	174	41	which	which	PRON
brj-22232	174	42	reduces	reduce	VERB
brj-22232	174	43	the	the	DET
brj-22232	174	44	user	user	NOUN
brj-22232	174	45	's	's	PART
brj-22232	174	46	operation	operation	NOUN
brj-22232	174	47	difficulty	difficulty	NOUN
brj-22232	174	48	and	and	CCONJ
brj-22232	174	49	improves	improve	VERB
brj-22232	174	50	the	the	DET
brj-22232	174	51	work	work	NOUN
brj-22232	174	52	efficiency	efficiency	NOUN
brj-22232	174	53	.	.	PUNCT
brj-22232	175	1	fig	fig	NOUN
brj-22232	175	2	.	.	PUNCT
brj-22232	176	1	7	7	X
brj-22232	176	2	.	.	X
brj-22232	176	3	deployment	deployment	NOUN
brj-22232	176	4	of	of	ADP
brj-22232	176	5	cyclegan	cyclegan	NOUN
brj-22232	176	6	to	to	ADP
brj-22232	176	7	a	a	DET
brj-22232	176	8	designed	design	VERB
brj-22232	176	9	tree	tree	NOUN
brj-22232	176	10	management	management	NOUN
brj-22232	176	11	information	information	NOUN
brj-22232	176	12	system	system	NOUN
brj-22232	176	13	data	datum	NOUN
brj-22232	176	14	combination	combination	NOUN
brj-22232	176	15	after	after	SCONJ
brj-22232	176	16	the	the	DET
brj-22232	176	17	above	above	ADJ
brj-22232	176	18	steps	step	NOUN
brj-22232	176	19	are	be	AUX
brj-22232	176	20	completed	complete	VERB
brj-22232	176	21	,	,	PUNCT
brj-22232	176	22	the	the	DET
brj-22232	176	23	combination	combination	NOUN
brj-22232	176	24	of	of	ADP
brj-22232	176	25	datasets	dataset	NOUN
brj-22232	176	26	is	be	AUX
brj-22232	176	27	performed	perform	VERB
brj-22232	176	28	,	,	PUNCT
brj-22232	176	29	a	a	DET
brj-22232	176	30	total	total	NOUN
brj-22232	176	31	of	of	ADP
brj-22232	176	32	seven	seven	NUM
brj-22232	176	33	datasets	dataset	NOUN
brj-22232	176	34	are	be	AUX
brj-22232	176	35	constituted	constitute	VERB
brj-22232	176	36	,	,	PUNCT
brj-22232	176	37	and	and	CCONJ
brj-22232	176	38	the	the	DET
brj-22232	176	39	composition	composition	NOUN
brj-22232	176	40	of	of	ADP
brj-22232	176	41	the	the	DET
brj-22232	176	42	datasets	dataset	NOUN
brj-22232	176	43	is	be	AUX
brj-22232	176	44	shown	show	VERB
brj-22232	176	45	in	in	ADP
brj-22232	176	46	table	table	NOUN
brj-22232	176	47	2	2	NUM
brj-22232	176	48	.	.	PUNCT
brj-22232	176	49	table	table	NOUN
brj-22232	176	50	2	2	NUM
brj-22232	176	51	.	.	PUNCT
brj-22232	177	1	composition	composition	NOUN
brj-22232	177	2	of	of	ADP
brj-22232	177	3	the	the	DET
brj-22232	177	4	datasets	dataset	NOUN
brj-22232	177	5	dataset	dataset	AUX
brj-22232	177	6	training	training	NOUN
brj-22232	177	7	dataset	dataset	NOUN
brj-22232	177	8	validation	validation	NOUN
brj-22232	177	9	dataset	dataset	NOUN
brj-22232	177	10	testing	testing	NOUN
brj-22232	177	11	dataset	dataset	VERB
brj-22232	177	12	real	real	ADJ
brj-22232	177	13	(	(	PUNCT
brj-22232	177	14	r	r	NOUN
brj-22232	177	15	)	)	PUNCT
brj-22232	177	16	10000	10000	NUM
brj-22232	177	17	1000	1000	NUM
brj-22232	177	18	1200	1200	NUM
brj-22232	177	19	simulation	simulation	NOUN
brj-22232	177	20	(	(	PUNCT
brj-22232	177	21	s	s	NOUN
brj-22232	177	22	)	)	PUNCT
brj-22232	177	23	10000	10000	NUM
brj-22232	177	24	1000	1000	NUM
brj-22232	177	25	generation	generation	NOUN
brj-22232	177	26	(	(	PUNCT
brj-22232	177	27	g	g	NOUN
brj-22232	177	28	)	)	PUNCT
brj-22232	177	29	10000	10000	NUM
brj-22232	177	30	1000	1000	NUM
brj-22232	177	31	real	real	ADJ
brj-22232	177	32	generation	generation	NOUN
brj-22232	177	33	(	(	PUNCT
brj-22232	177	34	rg	rg	NOUN
brj-22232	177	35	)	)	PUNCT
brj-22232	177	36	10000	10000	NUM
brj-22232	177	37	1000	1000	NUM
brj-22232	177	38	real	real	ADJ
brj-22232	177	39	simulation	simulation	NOUN
brj-22232	177	40	(	(	PUNCT
brj-22232	177	41	rs	rs	NOUN
brj-22232	177	42	)	)	PUNCT
brj-22232	177	43	10000	10000	NUM
brj-22232	177	44	1000	1000	NUM
brj-22232	177	45	generation	generation	NOUN
brj-22232	177	46	simulation	simulation	NOUN
brj-22232	177	47	(	(	PUNCT
brj-22232	177	48	gs	gs	NOUN
brj-22232	177	49	)	)	PUNCT
brj-22232	177	50	10000	10000	NUM
brj-22232	177	51	1000	1000	NUM
brj-22232	177	52	real	real	ADJ
brj-22232	177	53	generation	generation	NOUN
brj-22232	177	54	simulation	simulation	NOUN
brj-22232	177	55	(	(	PUNCT
brj-22232	177	56	rgs	rgs	PROPN
brj-22232	177	57	)	)	PUNCT
brj-22232	177	58	10000	10000	NUM
brj-22232	177	59	1000	1000	NUM
brj-22232	177	60	except	except	SCONJ
brj-22232	177	61	for	for	ADP
brj-22232	177	62	the	the	DET
brj-22232	177	63	rgs	rgs	PROPN
brj-22232	177	64	training	training	NOUN
brj-22232	177	65	dataset	dataset	NOUN
brj-22232	177	66	consisting	consist	VERB
brj-22232	177	67	of	of	ADP
brj-22232	177	68	4000	4000	NUM
brj-22232	177	69	real	real	ADJ
brj-22232	177	70	images	image	NOUN
brj-22232	177	71	,	,	PUNCT
brj-22232	177	72	3000	3000	NUM
brj-22232	177	73	simulation	simulation	NOUN
brj-22232	177	74	images	image	NOUN
brj-22232	177	75	,	,	PUNCT
brj-22232	177	76	and	and	CCONJ
brj-22232	177	77	3000	3000	NUM
brj-22232	177	78	generated	generate	VERB
brj-22232	177	79	images	image	NOUN
brj-22232	177	80	,	,	PUNCT
brj-22232	177	81	the	the	DET
brj-22232	177	82	remaining	remain	VERB
brj-22232	177	83	training	training	NOUN
brj-22232	177	84	datasets	dataset	NOUN
brj-22232	177	85	consisting	consist	VERB
brj-22232	177	86	of	of	ADP
brj-22232	177	87	two	two	NUM
brj-22232	177	88	types	type	NOUN
brj-22232	177	89	of	of	ADP
brj-22232	177	90	data	datum	NOUN
brj-22232	177	91	are	be	AUX
brj-22232	177	92	each	each	PRON
brj-22232	177	93	taken	take	VERB
brj-22232	177	94	the	the	DET
brj-22232	177	95	first	first	ADJ
brj-22232	177	96	5000	5000	NUM
brj-22232	177	97	images	image	NOUN
brj-22232	177	98	of	of	ADP
brj-22232	177	99	each	each	DET
brj-22232	177	100	data	datum	NOUN
brj-22232	177	101	to	to	PART
brj-22232	177	102	form	form	VERB
brj-22232	177	103	the	the	DET
brj-22232	177	104	final	final	ADJ
brj-22232	177	105	training	training	NOUN
brj-22232	177	106	datasets	dataset	NOUN
brj-22232	177	107	.	.	PUNCT
brj-22232	178	1	to	to	PART
brj-22232	178	2	measure	measure	VERB
brj-22232	178	3	the	the	DET
brj-22232	178	4	training	training	NOUN
brj-22232	178	5	effects	effect	NOUN
brj-22232	178	6	of	of	ADP
brj-22232	178	7	all	all	DET
brj-22232	178	8	training	training	NOUN
brj-22232	178	9	datasets	dataset	NOUN
brj-22232	178	10	,	,	PUNCT
brj-22232	178	11	400	400	NUM
brj-22232	178	12	images	image	NOUN
brj-22232	178	13	from	from	ADP
brj-22232	178	14	each	each	PRON
brj-22232	178	15	of	of	ADP
brj-22232	178	16	the	the	DET
brj-22232	178	17	three	three	NUM
brj-22232	178	18	types	type	NOUN
brj-22232	178	19	of	of	ADP
brj-22232	178	20	data	datum	NOUN
brj-22232	178	21	are	be	AUX
brj-22232	178	22	taken	take	VERB
brj-22232	178	23	to	to	PART
brj-22232	178	24	form	form	VERB
brj-22232	178	25	the	the	DET
brj-22232	178	26	final	final	ADJ
brj-22232	178	27	testing	testing	NOUN
brj-22232	178	28	dataset	dataset	NOUN
brj-22232	178	29	,	,	PUNCT
brj-22232	178	30	and	and	CCONJ
brj-22232	178	31	all	all	DET
brj-22232	178	32	training	training	NOUN
brj-22232	178	33	models	model	NOUN
brj-22232	178	34	are	be	AUX
brj-22232	178	35	tested	test	VERB
brj-22232	178	36	with	with	ADP
brj-22232	178	37	it	it	PRON
brj-22232	178	38	.	.	PUNCT
brj-22232	179	1	peer	peer	NOUN
brj-22232	179	2	-	-	PUNCT
brj-22232	179	3	reviewed	review	VERB
brj-22232	179	4	article	article	NOUN
brj-22232	179	5	bioresources.com	bioresources.com	X
brj-22232	179	6	li	li	PROPN
brj-22232	179	7	et	et	PROPN
brj-22232	179	8	al	al	PROPN
brj-22232	179	9	.	.	PROPN
brj-22232	179	10	(	(	PUNCT
brj-22232	179	11	2023	2023	NUM
brj-22232	179	12	)	)	PUNCT
brj-22232	179	13	.	.	PUNCT
brj-22232	180	1	“	"	PUNCT
brj-22232	180	2	tree	tree	NOUN
brj-22232	180	3	root	root	NOUN
brj-22232	180	4	detection	detection	NOUN
brj-22232	180	5	training	training	NOUN
brj-22232	180	6	,	,	PUNCT
brj-22232	180	7	”	"	PUNCT
brj-22232	180	8	bioresources	bioresource	NOUN
brj-22232	180	9	18(1	18(1	NOUN
brj-22232	180	10	)	)	PUNCT
brj-22232	180	11	,	,	PUNCT
brj-22232	180	12	484	484	NUM
brj-22232	180	13	-	-	SYM
brj-22232	180	14	504	504	NUM
brj-22232	180	15	.	.	PUNCT
brj-22232	180	16	493	493	NUM
brj-22232	180	17	hyperbolic	hyperbolic	ADJ
brj-22232	180	18	detection	detection	NOUN
brj-22232	180	19	model	model	NOUN
brj-22232	180	20	yolov5	yolov5	NOUN
brj-22232	180	21	network	network	NOUN
brj-22232	180	22	architecture	architecture	NOUN
brj-22232	180	23	with	with	ADP
brj-22232	180	24	the	the	DET
brj-22232	180	25	development	development	NOUN
brj-22232	180	26	of	of	ADP
brj-22232	180	27	target	target	NOUN
brj-22232	180	28	detection	detection	NOUN
brj-22232	180	29	technology	technology	NOUN
brj-22232	180	30	,	,	PUNCT
brj-22232	180	31	the	the	DET
brj-22232	180	32	yolo	yolo	ADJ
brj-22232	180	33	series	series	NOUN
brj-22232	180	34	has	have	AUX
brj-22232	180	35	been	be	AUX
brj-22232	180	36	pursuing	pursue	VERB
brj-22232	180	37	the	the	DET
brj-22232	180	38	best	good	ADJ
brj-22232	180	39	balance	balance	NOUN
brj-22232	180	40	of	of	ADP
brj-22232	180	41	speed	speed	NOUN
brj-22232	180	42	and	and	CCONJ
brj-22232	180	43	accuracy	accuracy	NOUN
brj-22232	180	44	in	in	ADP
brj-22232	180	45	real	real	ADJ
brj-22232	180	46	-	-	PUNCT
brj-22232	180	47	time	time	NOUN
brj-22232	180	48	detection	detection	NOUN
brj-22232	180	49	applications	application	NOUN
brj-22232	180	50	.	.	PUNCT
brj-22232	181	1	yolov5	yolov5	NOUN
brj-22232	181	2	,	,	PUNCT
brj-22232	181	3	the	the	DET
brj-22232	181	4	latest	late	ADJ
brj-22232	181	5	achievement	achievement	NOUN
brj-22232	181	6	in	in	ADP
brj-22232	181	7	recent	recent	ADJ
brj-22232	181	8	years	year	NOUN
brj-22232	181	9	,	,	PUNCT
brj-22232	181	10	has	have	AUX
brj-22232	181	11	dramatically	dramatically	ADV
brj-22232	181	12	improved	improve	VERB
brj-22232	181	13	speed	speed	NOUN
brj-22232	181	14	and	and	CCONJ
brj-22232	181	15	accuracy	accuracy	NOUN
brj-22232	181	16	compared	compare	VERB
brj-22232	181	17	to	to	ADP
brj-22232	181	18	the	the	DET
brj-22232	181	19	previous	previous	ADJ
brj-22232	181	20	series	series	NOUN
brj-22232	181	21	and	and	CCONJ
brj-22232	181	22	has	have	AUX
brj-22232	181	23	been	be	AUX
brj-22232	181	24	applied	apply	VERB
brj-22232	181	25	to	to	ADP
brj-22232	181	26	various	various	ADJ
brj-22232	181	27	fields	field	NOUN
brj-22232	181	28	with	with	ADP
brj-22232	181	29	better	well	ADJ
brj-22232	181	30	results	result	NOUN
brj-22232	181	31	.	.	PUNCT
brj-22232	182	1	yolov5	yolov5	NOUN
brj-22232	182	2	consists	consist	VERB
brj-22232	182	3	of	of	ADP
brj-22232	182	4	backbone	backbone	NOUN
brj-22232	182	5	(	(	PUNCT
brj-22232	182	6	cspdarknet	cspdarknet	NOUN
brj-22232	182	7	)	)	PUNCT
brj-22232	182	8	,	,	PUNCT
brj-22232	182	9	neck	neck	NOUN
brj-22232	182	10	(	(	PUNCT
brj-22232	182	11	panet	panet	NOUN
brj-22232	182	12	)	)	PUNCT
brj-22232	182	13	,	,	PUNCT
brj-22232	182	14	and	and	CCONJ
brj-22232	182	15	head	head	NOUN
brj-22232	182	16	(	(	PUNCT
brj-22232	182	17	yolo	yolo	ADJ
brj-22232	182	18	layer	layer	NOUN
brj-22232	182	19	)	)	PUNCT
brj-22232	182	20	parts	part	NOUN
brj-22232	182	21	as	as	SCONJ
brj-22232	182	22	shown	show	VERB
brj-22232	182	23	in	in	ADP
brj-22232	182	24	fig	fig	NOUN
brj-22232	182	25	.	.	PUNCT
brj-22232	183	1	8	8	NUM
brj-22232	183	2	.	.	X
brj-22232	183	3	fig	fig	NOUN
brj-22232	183	4	.	.	PUNCT
brj-22232	184	1	8	8	NUM
brj-22232	184	2	.	.	PUNCT
brj-22232	185	1	yolov5	yolov5	NOUN
brj-22232	185	2	architecture	architecture	NOUN
brj-22232	185	3	cspdarknet	cspdarknet	NOUN
brj-22232	185	4	reduces	reduce	VERB
brj-22232	185	5	the	the	DET
brj-22232	185	6	parameters	parameter	NOUN
brj-22232	185	7	and	and	CCONJ
brj-22232	185	8	computation	computation	NOUN
brj-22232	185	9	of	of	ADP
brj-22232	185	10	the	the	DET
brj-22232	185	11	model	model	NOUN
brj-22232	185	12	and	and	CCONJ
brj-22232	185	13	the	the	DET
brj-22232	185	14	model	model	NOUN
brj-22232	185	15	's	's	PART
brj-22232	185	16	size	size	NOUN
brj-22232	185	17	,	,	PUNCT
brj-22232	185	18	ensuring	ensure	VERB
brj-22232	185	19	the	the	DET
brj-22232	185	20	operation	operation	NOUN
brj-22232	185	21	speed	speed	NOUN
brj-22232	185	22	and	and	CCONJ
brj-22232	185	23	accuracy	accuracy	NOUN
brj-22232	185	24	.	.	PUNCT
brj-22232	186	1	the	the	DET
brj-22232	186	2	sppf	sppf	ADJ
brj-22232	186	3	(	(	PUNCT
brj-22232	186	4	spatial	spatial	ADJ
brj-22232	186	5	pyramid	pyramid	NOUN
brj-22232	186	6	pooling	pool	VERB
brj-22232	186	7	fast	fast	ADJ
brj-22232	186	8	)	)	PUNCT
brj-22232	186	9	network	network	NOUN
brj-22232	186	10	is	be	AUX
brj-22232	186	11	used	use	VERB
brj-22232	186	12	to	to	PART
brj-22232	186	13	increase	increase	VERB
brj-22232	186	14	the	the	DET
brj-22232	186	15	receiver	receiver	ADJ
brj-22232	186	16	domain	domain	NOUN
brj-22232	186	17	of	of	ADP
brj-22232	186	18	the	the	DET
brj-22232	186	19	network	network	NOUN
brj-22232	186	20	,	,	PUNCT
brj-22232	186	21	as	as	SCONJ
brj-22232	186	22	shown	show	VERB
brj-22232	186	23	in	in	ADP
brj-22232	186	24	fig	fig	NOUN
brj-22232	186	25	.	.	PUNCT
brj-22232	187	1	9	9	X
brj-22232	187	2	.	.	X
brj-22232	188	1	the	the	DET
brj-22232	188	2	network	network	NOUN
brj-22232	188	3	uses	use	VERB
brj-22232	188	4	multiple	multiple	ADJ
brj-22232	188	5	5	5	NUM
brj-22232	188	6	×	×	NOUN
brj-22232	188	7	5	5	NUM
brj-22232	188	8	-	-	PUNCT
brj-22232	188	9	sized	sized	ADJ
brj-22232	188	10	maxpool	maxpool	ADJ
brj-22232	188	11	layers	layer	NOUN
brj-22232	188	12	to	to	PART
brj-22232	188	13	obtain	obtain	VERB
brj-22232	188	14	richer	rich	ADJ
brj-22232	188	15	features	feature	NOUN
brj-22232	188	16	.	.	PUNCT
brj-22232	189	1	compared	compare	VERB
brj-22232	189	2	to	to	ADP
brj-22232	189	3	the	the	DET
brj-22232	189	4	spp	spp	NOUN
brj-22232	189	5	(	(	PUNCT
brj-22232	189	6	spatial	spatial	ADJ
brj-22232	189	7	pyramid	pyramid	NOUN
brj-22232	189	8	pooling	pooling	NOUN
brj-22232	189	9	)	)	PUNCT
brj-22232	189	10	,	,	PUNCT
brj-22232	189	11	the	the	DET
brj-22232	189	12	sppf	sppf	NOUN
brj-22232	189	13	serially	serially	ADV
brj-22232	189	14	passes	pass	VERB
brj-22232	189	15	the	the	DET
brj-22232	189	16	input	input	NOUN
brj-22232	189	17	through	through	ADP
brj-22232	189	18	multiple	multiple	ADJ
brj-22232	189	19	maxpool	maxpool	ADJ
brj-22232	189	20	layers	layer	NOUN
brj-22232	189	21	,	,	PUNCT
brj-22232	189	22	obtaining	obtain	VERB
brj-22232	189	23	the	the	DET
brj-22232	189	24	same	same	ADJ
brj-22232	189	25	computational	computational	ADJ
brj-22232	189	26	results	result	NOUN
brj-22232	189	27	as	as	ADP
brj-22232	189	28	the	the	DET
brj-22232	189	29	spp	spp	NOUN
brj-22232	189	30	but	but	CCONJ
brj-22232	189	31	more	more	ADV
brj-22232	189	32	efficiently	efficiently	ADV
brj-22232	189	33	.	.	PUNCT
brj-22232	190	1	then	then	ADV
brj-22232	190	2	,	,	PUNCT
brj-22232	190	3	using	use	VERB
brj-22232	190	4	panet	panet	PROPN
brj-22232	190	5	(	(	PUNCT
brj-22232	190	6	path	path	NOUN
brj-22232	190	7	aggregation	aggregation	NOUN
brj-22232	190	8	network	network	NOUN
brj-22232	190	9	)	)	PUNCT
brj-22232	190	10	as	as	SCONJ
brj-22232	190	11	a	a	DET
brj-22232	190	12	neck	neck	NOUN
brj-22232	190	13	network	network	NOUN
brj-22232	190	14	can	can	AUX
brj-22232	190	15	preserve	preserve	VERB
brj-22232	190	16	the	the	DET
brj-22232	190	17	spatial	spatial	ADJ
brj-22232	190	18	information	information	NOUN
brj-22232	190	19	accurately	accurately	ADV
brj-22232	190	20	.	.	PUNCT
brj-22232	191	1	this	this	DET
brj-22232	191	2	network	network	NOUN
brj-22232	191	3	contributes	contribute	VERB
brj-22232	191	4	to	to	ADP
brj-22232	191	5	the	the	DET
brj-22232	191	6	correct	correct	ADJ
brj-22232	191	7	positioning	positioning	NOUN
brj-22232	191	8	of	of	ADP
brj-22232	191	9	pixels	pixel	NOUN
brj-22232	191	10	and	and	CCONJ
brj-22232	191	11	forms	form	VERB
brj-22232	191	12	a	a	DET
brj-22232	191	13	mask	mask	NOUN
brj-22232	191	14	to	to	PART
brj-22232	191	15	better	well	ADV
brj-22232	191	16	utilize	utilize	VERB
brj-22232	191	17	the	the	DET
brj-22232	191	18	extracted	extract	VERB
brj-22232	191	19	features	feature	NOUN
brj-22232	191	20	.	.	PUNCT
brj-22232	192	1	when	when	SCONJ
brj-22232	192	2	the	the	DET
brj-22232	192	3	image	image	NOUN
brj-22232	192	4	passes	pass	VERB
brj-22232	192	5	through	through	ADP
brj-22232	192	6	each	each	DET
brj-22232	192	7	layer	layer	NOUN
brj-22232	192	8	of	of	ADP
brj-22232	192	9	the	the	DET
brj-22232	192	10	neural	neural	ADJ
brj-22232	192	11	network	network	NOUN
brj-22232	192	12	,	,	PUNCT
brj-22232	192	13	the	the	DET
brj-22232	192	14	feature	feature	NOUN
brj-22232	192	15	complexity	complexity	NOUN
brj-22232	192	16	increases	increase	NOUN
brj-22232	192	17	,	,	PUNCT
brj-22232	192	18	while	while	SCONJ
brj-22232	192	19	reducing	reduce	VERB
brj-22232	192	20	the	the	DET
brj-22232	192	21	spatial	spatial	ADJ
brj-22232	192	22	resolution	resolution	NOUN
brj-22232	192	23	of	of	ADP
brj-22232	192	24	the	the	DET
brj-22232	192	25	image	image	NOUN
brj-22232	192	26	.	.	PUNCT
brj-22232	193	1	thus	thus	ADV
brj-22232	193	2	,	,	PUNCT
brj-22232	193	3	the	the	DET
brj-22232	193	4	pixel	pixel	ADJ
brj-22232	193	5	-	-	PUNCT
brj-22232	193	6	level	level	NOUN
brj-22232	193	7	masks	mask	NOUN
brj-22232	193	8	are	be	AUX
brj-22232	193	9	not	not	PART
brj-22232	193	10	accurately	accurately	ADV
brj-22232	193	11	recognized	recognize	VERB
brj-22232	193	12	by	by	ADP
brj-22232	193	13	the	the	DET
brj-22232	193	14	high	high	ADJ
brj-22232	193	15	-	-	PUNCT
brj-22232	193	16	level	level	NOUN
brj-22232	193	17	features	feature	NOUN
brj-22232	193	18	.	.	PUNCT
brj-22232	194	1	the	the	DET
brj-22232	194	2	fpn	fpn	NOUN
brj-22232	194	3	(	(	PUNCT
brj-22232	194	4	feature	feature	NOUN
brj-22232	194	5	pyramid	pyramid	NOUN
brj-22232	194	6	network	network	NOUN
brj-22232	194	7	)	)	PUNCT
brj-22232	194	8	uses	use	VERB
brj-22232	194	9	a	a	DET
brj-22232	194	10	top	top	ADJ
brj-22232	194	11	-	-	PUNCT
brj-22232	194	12	down	down	ADP
brj-22232	194	13	path	path	NOUN
brj-22232	194	14	to	to	PART
brj-22232	194	15	extract	extract	VERB
brj-22232	194	16	semantic	semantic	ADJ
brj-22232	194	17	-	-	PUNCT
brj-22232	194	18	rich	rich	ADJ
brj-22232	194	19	features	feature	NOUN
brj-22232	194	20	and	and	CCONJ
brj-22232	194	21	combines	combine	VERB
brj-22232	194	22	them	they	PRON
brj-22232	194	23	with	with	ADP
brj-22232	194	24	accurate	accurate	ADJ
brj-22232	194	25	location	location	NOUN
brj-22232	194	26	information	information	NOUN
brj-22232	194	27	.	.	PUNCT
brj-22232	195	1	meanwhile	meanwhile	ADV
brj-22232	195	2	,	,	PUNCT
brj-22232	195	3	cbl	cbl	PROPN
brj-22232	195	4	(	(	PUNCT
brj-22232	195	5	convolution	convolution	NOUN
brj-22232	195	6	,	,	PUNCT
brj-22232	195	7	batch	batch	NOUN
brj-22232	195	8	normalization	normalization	NOUN
brj-22232	195	9	,	,	PUNCT
brj-22232	195	10	and	and	CCONJ
brj-22232	195	11	leaky	leaky	ADJ
brj-22232	195	12	-	-	PUNCT
brj-22232	195	13	relu	relu	NOUN
brj-22232	195	14	)	)	PUNCT
brj-22232	195	15	is	be	AUX
brj-22232	195	16	replaced	replace	VERB
brj-22232	195	17	by	by	ADP
brj-22232	195	18	cbs	cbs	PROPN
brj-22232	195	19	(	(	PUNCT
brj-22232	195	20	convolution	convolution	NOUN
brj-22232	195	21	,	,	PUNCT
brj-22232	195	22	batch	batch	NOUN
brj-22232	195	23	normalization	normalization	NOUN
brj-22232	195	24	,	,	PUNCT
brj-22232	195	25	and	and	CCONJ
brj-22232	195	26	silu	silu	NOUN
brj-22232	195	27	)	)	PUNCT
brj-22232	195	28	,	,	PUNCT
brj-22232	195	29	and	and	CCONJ
brj-22232	195	30	the	the	DET
brj-22232	195	31	silu	silu	ADJ
brj-22232	195	32	activation	activation	NOUN
brj-22232	195	33	function	function	NOUN
brj-22232	195	34	has	have	VERB
brj-22232	195	35	better	well	ADJ
brj-22232	195	36	nonlinear	nonlinear	ADJ
brj-22232	195	37	capabilities	capability	NOUN
brj-22232	195	38	.	.	PUNCT
brj-22232	196	1	the	the	DET
brj-22232	196	2	head	head	NOUN
brj-22232	196	3	part	part	NOUN
brj-22232	196	4	uses	use	VERB
brj-22232	196	5	the	the	DET
brj-22232	196	6	head	head	NOUN
brj-22232	196	7	network	network	NOUN
brj-22232	196	8	of	of	ADP
brj-22232	196	9	yolov3	yolov3	PROPN
brj-22232	196	10	to	to	PART
brj-22232	196	11	predict	predict	VERB
brj-22232	196	12	the	the	DET
brj-22232	196	13	obtained	obtain	VERB
brj-22232	196	14	features	feature	NOUN
brj-22232	196	15	.	.	PUNCT
brj-22232	197	1	peer	peer	NOUN
brj-22232	197	2	-	-	PUNCT
brj-22232	197	3	reviewed	review	VERB
brj-22232	197	4	article	article	NOUN
brj-22232	197	5	bioresources.com	bioresources.com	X
brj-22232	197	6	li	li	PROPN
brj-22232	197	7	et	et	PROPN
brj-22232	197	8	al	al	PROPN
brj-22232	197	9	.	.	PROPN
brj-22232	197	10	(	(	PUNCT
brj-22232	197	11	2023	2023	NUM
brj-22232	197	12	)	)	PUNCT
brj-22232	197	13	.	.	PUNCT
brj-22232	198	1	“	"	PUNCT
brj-22232	198	2	tree	tree	NOUN
brj-22232	198	3	root	root	NOUN
brj-22232	198	4	detection	detection	NOUN
brj-22232	198	5	training	training	NOUN
brj-22232	198	6	,	,	PUNCT
brj-22232	198	7	”	"	PUNCT
brj-22232	198	8	bioresources	bioresource	NOUN
brj-22232	198	9	18(1	18(1	NOUN
brj-22232	198	10	)	)	PUNCT
brj-22232	198	11	,	,	PUNCT
brj-22232	198	12	484	484	NUM
brj-22232	198	13	-	-	SYM
brj-22232	198	14	504	504	NUM
brj-22232	198	15	.	.	PUNCT
brj-22232	199	1	494	494	NUM
brj-22232	199	2	fig	fig	NOUN
brj-22232	199	3	.	.	PUNCT
brj-22232	200	1	9	9	X
brj-22232	200	2	.	.	X
brj-22232	200	3	comparison	comparison	NOUN
brj-22232	200	4	between	between	ADP
brj-22232	200	5	spp	spp	NOUN
brj-22232	200	6	and	and	CCONJ
brj-22232	200	7	sppf	sppf	ADJ
brj-22232	200	8	training	training	NOUN
brj-22232	200	9	setup	setup	NOUN
brj-22232	200	10	the	the	DET
brj-22232	200	11	training	training	NOUN
brj-22232	200	12	environment	environment	NOUN
brj-22232	200	13	was	be	AUX
brj-22232	200	14	on	on	ADP
brj-22232	200	15	the	the	DET
brj-22232	200	16	basis	basis	NOUN
brj-22232	200	17	of	of	ADP
brj-22232	200	18	python	python	PROPN
brj-22232	200	19	3.8.6	3.8.6	NUM
brj-22232	200	20	,	,	PUNCT
brj-22232	200	21	pytorch	pytorch	NOUN
brj-22232	200	22	1.7	1.7	NUM
brj-22232	200	23	(	(	PUNCT
brj-22232	200	24	used	use	VERB
brj-22232	200	25	in	in	ADP
brj-22232	200	26	centernet	centernet	NOUN
brj-22232	200	27	,	,	PUNCT
brj-22232	200	28	yolov3	yolov3	PROPN
brj-22232	200	29	,	,	PUNCT
brj-22232	200	30	and	and	CCONJ
brj-22232	200	31	yolov5	yolov5	NOUN
brj-22232	200	32	models	model	NOUN
brj-22232	200	33	)	)	PUNCT
brj-22232	200	34	,	,	PUNCT
brj-22232	200	35	and	and	CCONJ
brj-22232	200	36	python	python	NOUN
brj-22232	200	37	3.6.13	3.6.13	NUM
brj-22232	200	38	,	,	PUNCT
brj-22232	200	39	tensorflow	tensorflow	NOUN
brj-22232	200	40	1.11.0	1.11.0	NUM
brj-22232	200	41	(	(	PUNCT
brj-22232	200	42	used	use	VERB
brj-22232	200	43	in	in	ADP
brj-22232	200	44	faster	fast	ADJ
brj-22232	200	45	r	r	NOUN
brj-22232	200	46	-	-	PUNCT
brj-22232	200	47	cnn	cnn	PROPN
brj-22232	200	48	models	model	NOUN
brj-22232	200	49	)	)	PUNCT
brj-22232	200	50	.	.	PUNCT
brj-22232	201	1	the	the	DET
brj-22232	201	2	computers	computer	NOUN
brj-22232	201	3	used	use	VERB
brj-22232	201	4	in	in	ADP
brj-22232	201	5	all	all	DET
brj-22232	201	6	experiments	experiment	NOUN
brj-22232	201	7	were	be	AUX
brj-22232	201	8	equipped	equip	VERB
brj-22232	201	9	with	with	ADP
brj-22232	201	10	the	the	DET
brj-22232	201	11	following	follow	VERB
brj-22232	201	12	features	feature	NOUN
brj-22232	201	13	:	:	PUNCT
brj-22232	201	14	intel(r	intel(r	NOUN
brj-22232	201	15	)	)	PUNCT
brj-22232	201	16	core(tm	core(tm	NOUN
brj-22232	201	17	)	)	PUNCT
brj-22232	201	18	i5	i5	PROPN
brj-22232	201	19	-	-	PUNCT
brj-22232	201	20	9400	9400	NUM
brj-22232	201	21	cpu	cpu	NOUN
brj-22232	201	22	,	,	PUNCT
brj-22232	201	23	16	16	NUM
brj-22232	201	24	gb	gb	NOUN
brj-22232	201	25	ram	ram	NOUN
brj-22232	201	26	,	,	PUNCT
brj-22232	201	27	nvidia	nvidia	PROPN
brj-22232	201	28	geforce	geforce	NOUN
brj-22232	201	29	gtx	gtx	PROPN
brj-22232	201	30	1660	1660	NUM
brj-22232	201	31	ti	ti	PROPN
brj-22232	201	32	gpu	gpu	PROPN
brj-22232	201	33	,	,	PUNCT
brj-22232	201	34	and	and	CCONJ
brj-22232	201	35	a	a	DET
brj-22232	201	36	samsung	samsung	NOUN
brj-22232	201	37	250	250	NUM
brj-22232	201	38	g	g	PROPN
brj-22232	201	39	ssd	ssd	NOUN
brj-22232	201	40	hard	hard	ADJ
brj-22232	201	41	drive	drive	NOUN
brj-22232	201	42	.	.	PUNCT
brj-22232	202	1	this	this	DET
brj-22232	202	2	paper	paper	NOUN
brj-22232	202	3	compares	compare	VERB
brj-22232	202	4	four	four	NUM
brj-22232	202	5	different	different	ADJ
brj-22232	202	6	models	model	NOUN
brj-22232	202	7	,	,	PUNCT
brj-22232	202	8	yolov3	yolov3	PROPN
brj-22232	202	9	,	,	PUNCT
brj-22232	202	10	yolov5	yolov5	NOUN
brj-22232	202	11	,	,	PUNCT
brj-22232	202	12	faster	fast	ADJ
brj-22232	202	13	r	r	NOUN
brj-22232	202	14	-	-	PUNCT
brj-22232	202	15	cnn	cnn	PROPN
brj-22232	202	16	,	,	PUNCT
brj-22232	202	17	and	and	CCONJ
brj-22232	202	18	centernet	centernet	NOUN
brj-22232	202	19	.	.	PUNCT
brj-22232	203	1	yolov5	yolov5	NOUN
brj-22232	203	2	has	have	VERB
brj-22232	203	3	four	four	NUM
brj-22232	203	4	models	model	NOUN
brj-22232	203	5	(	(	PUNCT
brj-22232	203	6	s	s	X
brj-22232	203	7	,	,	PUNCT
brj-22232	203	8	m	m	PROPN
brj-22232	203	9	,	,	PUNCT
brj-22232	203	10	l	l	NOUN
brj-22232	203	11	,	,	PUNCT
brj-22232	203	12	and	and	CCONJ
brj-22232	203	13	x	x	X
brj-22232	203	14	)	)	PUNCT
brj-22232	203	15	with	with	ADP
brj-22232	203	16	different	different	ADJ
brj-22232	203	17	depths	depth	NOUN
brj-22232	203	18	,	,	PUNCT
brj-22232	203	19	and	and	CCONJ
brj-22232	203	20	the	the	DET
brj-22232	203	21	s	s	NOUN
brj-22232	203	22	model	model	NOUN
brj-22232	203	23	was	be	AUX
brj-22232	203	24	selected	select	VERB
brj-22232	203	25	for	for	ADP
brj-22232	203	26	training	training	NOUN
brj-22232	203	27	.	.	PUNCT
brj-22232	204	1	the	the	DET
brj-22232	204	2	suitable	suitable	ADJ
brj-22232	204	3	model	model	NOUN
brj-22232	204	4	parameters	parameter	NOUN
brj-22232	204	5	were	be	AUX
brj-22232	204	6	selected	select	VERB
brj-22232	204	7	after	after	ADP
brj-22232	204	8	a	a	DET
brj-22232	204	9	comprehensive	comprehensive	ADJ
brj-22232	204	10	consideration	consideration	NOUN
brj-22232	204	11	of	of	ADP
brj-22232	204	12	the	the	DET
brj-22232	204	13	dataset	dataset	NOUN
brj-22232	204	14	and	and	CCONJ
brj-22232	204	15	hardware	hardware	NOUN
brj-22232	204	16	.	.	PUNCT
brj-22232	205	1	the	the	DET
brj-22232	205	2	hyperparameters	hyperparameter	NOUN
brj-22232	205	3	of	of	ADP
brj-22232	205	4	the	the	DET
brj-22232	205	5	model	model	NOUN
brj-22232	205	6	were	be	AUX
brj-22232	205	7	set	set	VERB
brj-22232	205	8	as	as	SCONJ
brj-22232	205	9	follows	follow	VERB
brj-22232	205	10	:	:	PUNCT
brj-22232	205	11	batch	batch	NOUN
brj-22232	205	12	size	size	NOUN
brj-22232	205	13	was	be	AUX
brj-22232	205	14	16	16	NUM
brj-22232	205	15	;	;	PUNCT
brj-22232	205	16	momentum	momentum	NOUN
brj-22232	205	17	decay	decay	NOUN
brj-22232	205	18	and	and	CCONJ
brj-22232	205	19	weight	weight	NOUN
brj-22232	205	20	decay	decay	NOUN
brj-22232	205	21	were	be	AUX
brj-22232	205	22	0.8	0.8	NUM
brj-22232	205	23	and	and	CCONJ
brj-22232	205	24	0.0005	0.0005	NUM
brj-22232	205	25	,	,	PUNCT
brj-22232	205	26	respectively	respectively	ADV
brj-22232	205	27	;	;	PUNCT
brj-22232	205	28	input	input	NOUN
brj-22232	205	29	size	size	NOUN
brj-22232	205	30	was	be	AUX
brj-22232	205	31	256	256	NUM
brj-22232	205	32	×	×	NOUN
brj-22232	205	33	256	256	NUM
brj-22232	205	34	;	;	PUNCT
brj-22232	205	35	initial	initial	ADJ
brj-22232	205	36	learning	learning	NOUN
brj-22232	205	37	rate	rate	NOUN
brj-22232	205	38	was	be	AUX
brj-22232	205	39	0.002	0.002	NUM
brj-22232	205	40	;	;	PUNCT
brj-22232	205	41	the	the	DET
brj-22232	205	42	epoch	epoch	NOUN
brj-22232	205	43	of	of	ADP
brj-22232	205	44	yolov3	yolov3	PROPN
brj-22232	205	45	,	,	PUNCT
brj-22232	205	46	yolov5	yolov5	PROPN
brj-22232	205	47	,	,	PUNCT
brj-22232	205	48	and	and	CCONJ
brj-22232	205	49	centernet	centernet	NOUN
brj-22232	205	50	models	model	NOUN
brj-22232	205	51	was	be	AUX
brj-22232	205	52	100	100	NUM
brj-22232	205	53	;	;	PUNCT
brj-22232	205	54	iteration	iteration	NOUN
brj-22232	205	55	of	of	ADP
brj-22232	205	56	faster	fast	ADJ
brj-22232	205	57	r	r	NOUN
brj-22232	205	58	-	-	PUNCT
brj-22232	205	59	cnn	cnn	PROPN
brj-22232	205	60	model	model	NOUN
brj-22232	205	61	was	be	AUX
brj-22232	205	62	10,000	10,000	NUM
brj-22232	205	63	iterations	iteration	NOUN
brj-22232	205	64	,	,	PUNCT
brj-22232	205	65	which	which	PRON
brj-22232	205	66	was	be	AUX
brj-22232	205	67	approximately	approximately	ADV
brj-22232	205	68	equal	equal	ADJ
brj-22232	205	69	to	to	ADP
brj-22232	205	70	325	325	NUM
brj-22232	205	71	epochs	epoch	NOUN
brj-22232	205	72	,	,	PUNCT
brj-22232	205	73	satisfying	satisfy	VERB
brj-22232	205	74	the	the	DET
brj-22232	205	75	basic	basic	ADJ
brj-22232	205	76	training	training	NOUN
brj-22232	205	77	requirements	requirement	NOUN
brj-22232	205	78	;	;	PUNCT
brj-22232	205	79	other	other	ADJ
brj-22232	205	80	default	default	NOUN
brj-22232	205	81	values	value	NOUN
brj-22232	205	82	were	be	AUX
brj-22232	205	83	used	use	VERB
brj-22232	205	84	.	.	PUNCT
brj-22232	206	1	model	model	NOUN
brj-22232	206	2	evaluation	evaluation	NOUN
brj-22232	206	3	indicators	indicator	NOUN
brj-22232	206	4	in	in	ADP
brj-22232	206	5	this	this	DET
brj-22232	206	6	paper	paper	NOUN
brj-22232	206	7	,	,	PUNCT
brj-22232	206	8	several	several	ADJ
brj-22232	206	9	quantifiable	quantifiable	ADJ
brj-22232	206	10	metrics	metric	NOUN
brj-22232	206	11	were	be	AUX
brj-22232	206	12	employed	employ	VERB
brj-22232	206	13	to	to	PART
brj-22232	206	14	evaluate	evaluate	VERB
brj-22232	206	15	the	the	DET
brj-22232	206	16	performance	performance	NOUN
brj-22232	206	17	of	of	ADP
brj-22232	206	18	the	the	DET
brj-22232	206	19	selected	select	VERB
brj-22232	206	20	model	model	NOUN
brj-22232	206	21	quantitatively	quantitatively	ADV
brj-22232	206	22	,	,	PUNCT
brj-22232	206	23	including	include	VERB
brj-22232	206	24	mean	mean	PROPN
brj-22232	206	25	precision	precision	NOUN
brj-22232	206	26	(	(	PUNCT
brj-22232	206	27	map	map	NOUN
brj-22232	206	28	)	)	PUNCT
brj-22232	206	29	,	,	PUNCT
brj-22232	206	30	precision	precision	NOUN
brj-22232	206	31	(	(	PUNCT
brj-22232	206	32	p	p	NOUN
brj-22232	206	33	)	)	PUNCT
brj-22232	206	34	,	,	PUNCT
brj-22232	206	35	recall	recall	INTJ
brj-22232	206	36	(	(	PUNCT
brj-22232	206	37	r	r	NOUN
brj-22232	206	38	)	)	PUNCT
brj-22232	206	39	,	,	PUNCT
brj-22232	206	40	and	and	CCONJ
brj-22232	206	41	f1	f1	PROPN
brj-22232	206	42	score	score	NOUN
brj-22232	206	43	.	.	PUNCT
brj-22232	207	1	the	the	DET
brj-22232	207	2	precision	precision	NOUN
brj-22232	207	3	and	and	CCONJ
brj-22232	207	4	recall	recall	NOUN
brj-22232	207	5	rate	rate	NOUN
brj-22232	207	6	in	in	ADP
brj-22232	207	7	the	the	DET
brj-22232	207	8	object	object	NOUN
brj-22232	207	9	detection	detection	NOUN
brj-22232	207	10	model	model	NOUN
brj-22232	207	11	,	,	PUNCT
brj-22232	207	12	precision	precision	NOUN
brj-22232	207	13	and	and	CCONJ
brj-22232	207	14	recall	recall	NOUN
brj-22232	207	15	are	be	AUX
brj-22232	207	16	the	the	DET
brj-22232	207	17	two	two	NUM
brj-22232	207	18	most	most	ADV
brj-22232	207	19	basic	basic	ADJ
brj-22232	207	20	evaluation	evaluation	NOUN
brj-22232	207	21	indicators	indicator	NOUN
brj-22232	207	22	.	.	PUNCT
brj-22232	208	1	precision	precision	NOUN
brj-22232	208	2	is	be	AUX
brj-22232	208	3	defined	define	VERB
brj-22232	208	4	as	as	ADP
brj-22232	208	5	the	the	DET
brj-22232	208	6	percentage	percentage	NOUN
brj-22232	208	7	of	of	ADP
brj-22232	208	8	all	all	DET
brj-22232	208	9	detected	detect	VERB
brj-22232	208	10	objects	object	NOUN
brj-22232	208	11	that	that	PRON
brj-22232	208	12	are	be	AUX
brj-22232	208	13	correctly	correctly	ADV
brj-22232	208	14	detected	detect	VERB
brj-22232	208	15	,	,	PUNCT
brj-22232	208	16	while	while	SCONJ
brj-22232	208	17	recall	recall	NOUN
brj-22232	208	18	is	be	AUX
brj-22232	208	19	defined	define	VERB
brj-22232	208	20	as	as	ADP
brj-22232	208	21	the	the	DET
brj-22232	208	22	percentage	percentage	NOUN
brj-22232	208	23	of	of	ADP
brj-22232	208	24	all	all	PRON
brj-22232	208	25	detected	detect	VERB
brj-22232	208	26	positive	positive	ADJ
brj-22232	208	27	samples	sample	NOUN
brj-22232	208	28	that	that	PRON
brj-22232	208	29	are	be	AUX
brj-22232	208	30	correctly	correctly	ADV
brj-22232	208	31	detected	detect	VERB
brj-22232	208	32	.	.	PUNCT
brj-22232	209	1	the	the	DET
brj-22232	209	2	equations	equation	NOUN
brj-22232	209	3	for	for	ADP
brj-22232	209	4	these	these	DET
brj-22232	209	5	two	two	NUM
brj-22232	209	6	metrics	metric	NOUN
brj-22232	209	7	are	be	AUX
brj-22232	209	8	as	as	SCONJ
brj-22232	209	9	follows	follow	VERB
brj-22232	209	10	,	,	PUNCT
brj-22232	209	11	p	p	NOUN
brj-22232	209	12	tp	tp	ADP
brj-22232	209	13	fp	fp	PROPN
brj-22232	209	14	tp=	tp=	PROPN
brj-22232	209	15	+	+	CCONJ
brj-22232	209	16	(	(	PUNCT
brj-22232	209	17	6	6	NUM
brj-22232	209	18	)	)	PUNCT
brj-22232	209	19	r	r	NOUN
brj-22232	209	20	tp	tp	NOUN
brj-22232	209	21	fn	fn	NOUN
brj-22232	209	22	tp=	tp=	NOUN
brj-22232	209	23	+	+	CCONJ
brj-22232	209	24	(	(	PUNCT
brj-22232	209	25	7	7	X
brj-22232	209	26	)	)	PUNCT
brj-22232	209	27	where	where	SCONJ
brj-22232	209	28	𝑇𝑃	𝑇𝑃	PROPN
brj-22232	209	29	is	be	AUX
brj-22232	209	30	the	the	DET
brj-22232	209	31	number	number	NOUN
brj-22232	209	32	of	of	ADP
brj-22232	209	33	correctly	correctly	ADV
brj-22232	209	34	detected	detect	VERB
brj-22232	209	35	hyperbolas	hyperbola	NOUN
brj-22232	209	36	,	,	PUNCT
brj-22232	209	37	𝐹𝑃	𝐹𝑃	PROPN
brj-22232	209	38	is	be	AUX
brj-22232	209	39	the	the	DET
brj-22232	209	40	number	number	NOUN
brj-22232	209	41	of	of	ADP
brj-22232	209	42	nonhyperbolas	nonhyperbola	NOUN
brj-22232	209	43	treated	treat	VERB
brj-22232	209	44	as	as	ADP
brj-22232	209	45	hyperbolas	hyperbola	NOUN
brj-22232	209	46	,	,	PUNCT
brj-22232	209	47	and	and	CCONJ
brj-22232	209	48	𝐹𝑁	𝐹𝑁	PROPN
brj-22232	209	49	is	be	AUX
brj-22232	209	50	the	the	DET
brj-22232	209	51	number	number	NOUN
brj-22232	209	52	of	of	ADP
brj-22232	209	53	hyperbolic	hyperbolic	ADJ
brj-22232	209	54	selections	selection	NOUN
brj-22232	209	55	treated	treat	VERB
brj-22232	209	56	as	as	ADP
brj-22232	209	57	non	non	NOUN
brj-22232	209	58	-	-	NOUN
brj-22232	209	59	hyperbolas	hyperbola	NOUN
brj-22232	209	60	.	.	PUNCT
brj-22232	210	1	peer	peer	NOUN
brj-22232	210	2	-	-	PUNCT
brj-22232	210	3	reviewed	review	VERB
brj-22232	210	4	article	article	NOUN
brj-22232	210	5	bioresources.com	bioresources.com	X
brj-22232	210	6	li	li	PROPN
brj-22232	210	7	et	et	PROPN
brj-22232	210	8	al	al	PROPN
brj-22232	210	9	.	.	PROPN
brj-22232	210	10	(	(	PUNCT
brj-22232	210	11	2023	2023	NUM
brj-22232	210	12	)	)	PUNCT
brj-22232	210	13	.	.	PUNCT
brj-22232	211	1	“	"	PUNCT
brj-22232	211	2	tree	tree	NOUN
brj-22232	211	3	root	root	NOUN
brj-22232	211	4	detection	detection	NOUN
brj-22232	211	5	training	training	NOUN
brj-22232	211	6	,	,	PUNCT
brj-22232	211	7	”	"	PUNCT
brj-22232	211	8	bioresources	bioresource	NOUN
brj-22232	211	9	18(1	18(1	NOUN
brj-22232	211	10	)	)	PUNCT
brj-22232	211	11	,	,	PUNCT
brj-22232	211	12	484	484	NUM
brj-22232	211	13	-	-	SYM
brj-22232	211	14	504	504	NUM
brj-22232	211	15	.	.	PUNCT
brj-22232	212	1	495	495	NUM
brj-22232	212	2	the	the	DET
brj-22232	212	3	map	map	NOUN
brj-22232	212	4	and	and	CCONJ
brj-22232	212	5	f1	f1	NOUN
brj-22232	212	6	score	score	NOUN
brj-22232	212	7	the	the	DET
brj-22232	212	8	mean	mean	ADJ
brj-22232	212	9	average	average	ADJ
brj-22232	212	10	precision	precision	NOUN
brj-22232	212	11	is	be	AUX
brj-22232	212	12	a	a	DET
brj-22232	212	13	composite	composite	ADJ
brj-22232	212	14	metric	metric	NOUN
brj-22232	212	15	that	that	PRON
brj-22232	212	16	combines	combine	VERB
brj-22232	212	17	precision	precision	NOUN
brj-22232	212	18	and	and	CCONJ
brj-22232	212	19	recall	recall	NOUN
brj-22232	212	20	.	.	PUNCT
brj-22232	213	1	it	it	PRON
brj-22232	213	2	is	be	AUX
brj-22232	213	3	the	the	DET
brj-22232	213	4	average	average	ADJ
brj-22232	213	5	value	value	NOUN
brj-22232	213	6	of	of	ADP
brj-22232	213	7	the	the	DET
brj-22232	213	8	average	average	ADJ
brj-22232	213	9	precision	precision	NOUN
brj-22232	213	10	(	(	PUNCT
brj-22232	213	11	ap	ap	PROPN
brj-22232	213	12	)	)	PUNCT
brj-22232	213	13	of	of	ADP
brj-22232	213	14	all	all	DET
brj-22232	213	15	categories	category	NOUN
brj-22232	213	16	.	.	PUNCT
brj-22232	214	1	in	in	ADP
brj-22232	214	2	this	this	DET
brj-22232	214	3	study	study	NOUN
brj-22232	214	4	,	,	PUNCT
brj-22232	214	5	map	map	NOUN
brj-22232	214	6	is	be	AUX
brj-22232	214	7	equivalent	equivalent	ADJ
brj-22232	214	8	to	to	AUX
brj-22232	214	9	ap	ap	VERB
brj-22232	214	10	because	because	SCONJ
brj-22232	214	11	only	only	ADV
brj-22232	214	12	one	one	NUM
brj-22232	214	13	object	object	NOUN
brj-22232	214	14	(	(	PUNCT
brj-22232	214	15	hyperbola	hyperbola	PROPN
brj-22232	214	16	)	)	PUNCT
brj-22232	214	17	is	be	AUX
brj-22232	214	18	available	available	ADJ
brj-22232	214	19	.	.	PUNCT
brj-22232	215	1	the	the	DET
brj-22232	215	2	𝑚𝐴𝑃	𝑚𝐴𝑃	NOUN
brj-22232	215	3	can	can	AUX
brj-22232	215	4	be	be	AUX
brj-22232	215	5	expressed	express	VERB
brj-22232	215	6	as	as	ADP
brj-22232	215	7	the	the	DET
brj-22232	215	8	area	area	NOUN
brj-22232	215	9	enclosed	enclose	VERB
brj-22232	215	10	by	by	ADP
brj-22232	215	11	the	the	DET
brj-22232	215	12	accuracy	accuracy	NOUN
brj-22232	215	13	and	and	CCONJ
brj-22232	215	14	recall	recall	NOUN
brj-22232	215	15	curves	curve	NOUN
brj-22232	215	16	,	,	PUNCT
brj-22232	215	17	as	as	SCONJ
brj-22232	215	18	in	in	ADP
brj-22232	215	19	eq	eq	NOUN
brj-22232	215	20	.	.	PROPN
brj-22232	215	21	8	8	NUM
brj-22232	215	22	:	:	SYM
brj-22232	215	23	1	1	NUM
brj-22232	215	24	0	0	NUM
brj-22232	215	25	(	(	PUNCT
brj-22232	215	26	)	)	PUNCT
brj-22232	215	27	map	map	NOUN
brj-22232	215	28	p	p	NOUN
brj-22232	215	29	r	r	NOUN
brj-22232	215	30	dr=	dr=	VERB
brj-22232	215	31			X
brj-22232	215	32	(	(	PUNCT
brj-22232	215	33	8)	8)	X
brj-22232	215	34	the	the	DET
brj-22232	215	35	𝐹1	𝐹1	PROPN
brj-22232	215	36	score	score	NOUN
brj-22232	215	37	is	be	AUX
brj-22232	215	38	used	use	VERB
brj-22232	215	39	to	to	PART
brj-22232	215	40	assess	assess	VERB
brj-22232	215	41	the	the	DET
brj-22232	215	42	overall	overall	ADJ
brj-22232	215	43	performance	performance	NOUN
brj-22232	215	44	of	of	ADP
brj-22232	215	45	the	the	DET
brj-22232	215	46	model	model	NOUN
brj-22232	215	47	.	.	PUNCT
brj-22232	216	1	the	the	DET
brj-22232	216	2	calculation	calculation	NOUN
brj-22232	216	3	formula	formula	NOUN
brj-22232	216	4	is	be	AUX
brj-22232	216	5	shown	show	VERB
brj-22232	216	6	in	in	ADP
brj-22232	216	7	eq	eq	ADJ
brj-22232	216	8	.	.	PROPN
brj-22232	216	9	9	9	NUM
brj-22232	216	10	:	:	SYM
brj-22232	216	11	1	1	NUM
brj-22232	216	12	2f	2f	NUM
brj-22232	216	13	p	p	NOUN
brj-22232	216	14	r	r	NOUN
brj-22232	216	15	p	p	X
brj-22232	216	16	r=	r=	ADJ
brj-22232	216	17			PROPN
brj-22232	216	18	+	+	CCONJ
brj-22232	216	19	(	(	PUNCT
brj-22232	216	20	9	9	X
brj-22232	216	21	)	)	PUNCT
brj-22232	216	22	results	result	NOUN
brj-22232	216	23	and	and	CCONJ
brj-22232	216	24	discussion	discussion	NOUN
brj-22232	216	25	analysis	analysis	NOUN
brj-22232	216	26	of	of	ADP
brj-22232	216	27	training	training	NOUN
brj-22232	216	28	results	result	VERB
brj-22232	216	29	the	the	DET
brj-22232	216	30	value	value	NOUN
brj-22232	216	31	of	of	ADP
brj-22232	216	32	loss	loss	NOUN
brj-22232	216	33	indicates	indicate	VERB
brj-22232	216	34	the	the	DET
brj-22232	216	35	difference	difference	NOUN
brj-22232	216	36	between	between	ADP
brj-22232	216	37	the	the	DET
brj-22232	216	38	predicted	predict	VERB
brj-22232	216	39	value	value	NOUN
brj-22232	216	40	and	and	CCONJ
brj-22232	216	41	the	the	DET
brj-22232	216	42	true	true	ADJ
brj-22232	216	43	value	value	NOUN
brj-22232	216	44	.	.	PUNCT
brj-22232	217	1	a	a	DET
brj-22232	217	2	low	low	ADJ
brj-22232	217	3	value	value	NOUN
brj-22232	217	4	of	of	ADP
brj-22232	217	5	loss	loss	NOUN
brj-22232	217	6	corresponds	correspond	VERB
brj-22232	217	7	to	to	ADP
brj-22232	217	8	a	a	DET
brj-22232	217	9	well	well	ADV
brj-22232	217	10	-	-	PUNCT
brj-22232	217	11	trained	train	VERB
brj-22232	217	12	effect	effect	NOUN
brj-22232	217	13	.	.	PUNCT
brj-22232	218	1	at	at	ADP
brj-22232	218	2	the	the	DET
brj-22232	218	3	same	same	ADJ
brj-22232	218	4	time	time	NOUN
brj-22232	218	5	,	,	PUNCT
brj-22232	218	6	a	a	DET
brj-22232	218	7	higher	high	ADJ
brj-22232	218	8	map	map	NOUN
brj-22232	218	9	value	value	NOUN
brj-22232	218	10	also	also	ADV
brj-22232	218	11	indicates	indicate	VERB
brj-22232	218	12	that	that	SCONJ
brj-22232	218	13	the	the	DET
brj-22232	218	14	trained	train	VERB
brj-22232	218	15	model	model	NOUN
brj-22232	218	16	has	have	VERB
brj-22232	218	17	a	a	DET
brj-22232	218	18	better	well	ADJ
brj-22232	218	19	performance	performance	NOUN
brj-22232	218	20	.	.	PUNCT
brj-22232	219	1	the	the	DET
brj-22232	219	2	loss	loss	NOUN
brj-22232	219	3	curve	curve	NOUN
brj-22232	219	4	and	and	CCONJ
brj-22232	219	5	map	map	VERB
brj-22232	219	6	curve	curve	NOUN
brj-22232	219	7	of	of	ADP
brj-22232	219	8	the	the	DET
brj-22232	219	9	model	model	NOUN
brj-22232	219	10	were	be	AUX
brj-22232	219	11	compared	compare	VERB
brj-22232	219	12	,	,	PUNCT
brj-22232	219	13	as	as	SCONJ
brj-22232	219	14	shown	show	VERB
brj-22232	219	15	in	in	ADP
brj-22232	219	16	fig	fig	NOUN
brj-22232	219	17	.	.	PUNCT
brj-22232	220	1	10	10	NUM
brj-22232	220	2	.	.	PUNCT
brj-22232	221	1	in	in	ADP
brj-22232	221	2	fig	fig	NOUN
brj-22232	221	3	.	.	PUNCT
brj-22232	222	1	10(a	10(a	NUM
brj-22232	222	2	,	,	PUNCT
brj-22232	222	3	b	b	NOUN
brj-22232	222	4	)	)	PUNCT
brj-22232	222	5	,	,	PUNCT
brj-22232	222	6	training	training	NOUN
brj-22232	222	7	on	on	ADP
brj-22232	222	8	the	the	DET
brj-22232	222	9	use	use	NOUN
brj-22232	222	10	of	of	ADP
brj-22232	222	11	yolov5	yolov5	NOUN
brj-22232	222	12	for	for	ADP
brj-22232	222	13	the	the	DET
brj-22232	222	14	selected	select	VERB
brj-22232	222	15	seven	seven	NUM
brj-22232	222	16	datasets	dataset	NOUN
brj-22232	222	17	,	,	PUNCT
brj-22232	222	18	the	the	DET
brj-22232	222	19	simulated	simulate	VERB
brj-22232	222	20	dataset	dataset	NOUN
brj-22232	222	21	had	have	VERB
brj-22232	222	22	the	the	DET
brj-22232	222	23	lowest	low	ADJ
brj-22232	222	24	loss	loss	NOUN
brj-22232	222	25	and	and	CCONJ
brj-22232	222	26	the	the	DET
brj-22232	222	27	highest	high	ADJ
brj-22232	222	28	map	map	NOUN
brj-22232	222	29	,	,	PUNCT
brj-22232	222	30	which	which	PRON
brj-22232	222	31	was	be	AUX
brj-22232	222	32	due	due	ADJ
brj-22232	222	33	to	to	ADP
brj-22232	222	34	the	the	DET
brj-22232	222	35	absence	absence	NOUN
brj-22232	222	36	of	of	ADP
brj-22232	222	37	a	a	DET
brj-22232	222	38	noisy	noisy	ADJ
brj-22232	222	39	background	background	NOUN
brj-22232	222	40	from	from	ADP
brj-22232	222	41	the	the	DET
brj-22232	222	42	simulation	simulation	NOUN
brj-22232	222	43	image	image	NOUN
brj-22232	222	44	,	,	PUNCT
brj-22232	222	45	making	make	VERB
brj-22232	222	46	it	it	PRON
brj-22232	222	47	easier	easy	ADJ
brj-22232	222	48	to	to	PART
brj-22232	222	49	detect	detect	VERB
brj-22232	222	50	and	and	CCONJ
brj-22232	222	51	identify	identify	VERB
brj-22232	222	52	.	.	PUNCT
brj-22232	223	1	however	however	ADV
brj-22232	223	2	,	,	PUNCT
brj-22232	223	3	the	the	DET
brj-22232	223	4	worst	bad	ADJ
brj-22232	223	5	results	result	NOUN
brj-22232	223	6	were	be	AUX
brj-22232	223	7	obtained	obtain	VERB
brj-22232	223	8	when	when	SCONJ
brj-22232	223	9	detecting	detect	VERB
brj-22232	223	10	real	real	ADJ
brj-22232	223	11	images	image	NOUN
brj-22232	223	12	,	,	PUNCT
brj-22232	223	13	and	and	CCONJ
brj-22232	223	14	it	it	PRON
brj-22232	223	15	was	be	AUX
brj-22232	223	16	almost	almost	ADV
brj-22232	223	17	impossible	impossible	ADJ
brj-22232	223	18	to	to	PART
brj-22232	223	19	recognize	recognize	VERB
brj-22232	223	20	hyperbolas	hyperbola	NOUN
brj-22232	223	21	.	.	PUNCT
brj-22232	224	1	compared	compare	VERB
brj-22232	224	2	with	with	ADP
brj-22232	224	3	the	the	DET
brj-22232	224	4	r	r	NOUN
brj-22232	224	5	and	and	CCONJ
brj-22232	224	6	rs	rs	NOUN
brj-22232	224	7	training	training	NOUN
brj-22232	224	8	models	model	NOUN
brj-22232	224	9	,	,	PUNCT
brj-22232	224	10	the	the	DET
brj-22232	224	11	rg	rg	PROPN
brj-22232	224	12	training	training	NOUN
brj-22232	224	13	model	model	NOUN
brj-22232	224	14	and	and	CCONJ
brj-22232	224	15	the	the	DET
brj-22232	224	16	rgs	rgs	PROPN
brj-22232	224	17	training	training	NOUN
brj-22232	224	18	model	model	NOUN
brj-22232	224	19	had	have	VERB
brj-22232	224	20	worse	bad	ADJ
brj-22232	224	21	convergence	convergence	NOUN
brj-22232	224	22	loss	loss	NOUN
brj-22232	224	23	and	and	CCONJ
brj-22232	224	24	map	map	NOUN
brj-22232	224	25	after	after	ADP
brj-22232	224	26	training	training	NOUN
brj-22232	224	27	.	.	PUNCT
brj-22232	225	1	both	both	CCONJ
brj-22232	225	2	the	the	DET
brj-22232	225	3	g	g	NOUN
brj-22232	225	4	and	and	CCONJ
brj-22232	225	5	gs	gs	PROPN
brj-22232	225	6	training	training	NOUN
brj-22232	225	7	models	model	NOUN
brj-22232	225	8	without	without	ADP
brj-22232	225	9	adding	add	VERB
brj-22232	225	10	real	real	ADJ
brj-22232	225	11	b	b	NOUN
brj-22232	225	12	-	-	PUNCT
brj-22232	225	13	scan	scan	ADJ
brj-22232	225	14	images	image	NOUN
brj-22232	225	15	had	have	VERB
brj-22232	225	16	poorer	poor	ADJ
brj-22232	225	17	loss	loss	NOUN
brj-22232	225	18	and	and	CCONJ
brj-22232	225	19	map	map	NOUN
brj-22232	225	20	,	,	PUNCT
brj-22232	225	21	and	and	CCONJ
brj-22232	225	22	map	map	NOUN
brj-22232	225	23	was	be	AUX
brj-22232	225	24	49.25	49.25	NUM
brj-22232	225	25	%	%	NOUN
brj-22232	225	26	and	and	CCONJ
brj-22232	225	27	33.78	33.78	NUM
brj-22232	225	28	%	%	NOUN
brj-22232	225	29	lower	low	ADJ
brj-22232	225	30	for	for	ADP
brj-22232	225	31	the	the	DET
brj-22232	225	32	g	g	PROPN
brj-22232	225	33	training	training	NOUN
brj-22232	225	34	model	model	NOUN
brj-22232	225	35	compared	compare	VERB
brj-22232	225	36	to	to	ADP
brj-22232	225	37	the	the	DET
brj-22232	225	38	rg	rg	PROPN
brj-22232	225	39	training	training	NOUN
brj-22232	225	40	model	model	NOUN
brj-22232	225	41	and	and	CCONJ
brj-22232	225	42	the	the	DET
brj-22232	225	43	gs	gs	PROPN
brj-22232	225	44	training	training	NOUN
brj-22232	225	45	model	model	NOUN
brj-22232	225	46	compared	compare	VERB
brj-22232	225	47	to	to	ADP
brj-22232	225	48	the	the	DET
brj-22232	225	49	rgs	rgs	PROPN
brj-22232	225	50	training	training	NOUN
brj-22232	225	51	model	model	NOUN
brj-22232	225	52	,	,	PUNCT
brj-22232	225	53	respectively	respectively	ADV
brj-22232	225	54	.	.	PUNCT
brj-22232	226	1	therefore	therefore	ADV
brj-22232	226	2	,	,	PUNCT
brj-22232	226	3	the	the	DET
brj-22232	226	4	involvement	involvement	NOUN
brj-22232	226	5	of	of	ADP
brj-22232	226	6	real	real	ADJ
brj-22232	226	7	b	b	NOUN
brj-22232	226	8	-	-	PUNCT
brj-22232	226	9	scan	scan	ADJ
brj-22232	226	10	images	image	NOUN
brj-22232	226	11	is	be	AUX
brj-22232	226	12	necessary	necessary	ADJ
brj-22232	226	13	to	to	PART
brj-22232	226	14	obtain	obtain	VERB
brj-22232	226	15	better	well	ADJ
brj-22232	226	16	training	training	NOUN
brj-22232	226	17	results	result	NOUN
brj-22232	226	18	.	.	PUNCT
brj-22232	227	1	comparing	compare	VERB
brj-22232	227	2	the	the	DET
brj-22232	227	3	results	result	NOUN
brj-22232	227	4	of	of	ADP
brj-22232	227	5	the	the	DET
brj-22232	227	6	r	r	NOUN
brj-22232	227	7	training	training	NOUN
brj-22232	227	8	model	model	NOUN
brj-22232	227	9	and	and	CCONJ
brj-22232	227	10	the	the	DET
brj-22232	227	11	rs	rs	PROPN
brj-22232	227	12	training	training	NOUN
brj-22232	227	13	model	model	NOUN
brj-22232	227	14	,	,	PUNCT
brj-22232	227	15	as	as	ADV
brj-22232	227	16	well	well	ADV
brj-22232	227	17	as	as	ADP
brj-22232	227	18	the	the	DET
brj-22232	227	19	rg	rg	NOUN
brj-22232	227	20	training	training	NOUN
brj-22232	227	21	model	model	NOUN
brj-22232	227	22	and	and	CCONJ
brj-22232	227	23	the	the	DET
brj-22232	227	24	rgs	rgs	PROPN
brj-22232	227	25	training	training	NOUN
brj-22232	227	26	model	model	NOUN
brj-22232	227	27	,	,	PUNCT
brj-22232	227	28	it	it	PRON
brj-22232	227	29	can	can	AUX
brj-22232	227	30	be	be	AUX
brj-22232	227	31	seen	see	VERB
brj-22232	227	32	that	that	SCONJ
brj-22232	227	33	the	the	DET
brj-22232	227	34	map	map	NOUN
brj-22232	227	35	decreased	decrease	VERB
brj-22232	227	36	1.76	1.76	NUM
brj-22232	227	37	%	%	NOUN
brj-22232	227	38	to	to	ADP
brj-22232	227	39	6.75	6.75	NUM
brj-22232	227	40	%	%	NOUN
brj-22232	227	41	after	after	ADP
brj-22232	227	42	adding	add	VERB
brj-22232	227	43	the	the	DET
brj-22232	227	44	simulated	simulated	ADJ
brj-22232	227	45	data	datum	NOUN
brj-22232	227	46	to	to	ADP
brj-22232	227	47	the	the	DET
brj-22232	227	48	corresponding	correspond	VERB
brj-22232	227	49	real	real	ADJ
brj-22232	227	50	b	b	NOUN
brj-22232	227	51	-	-	PUNCT
brj-22232	227	52	scan	scan	ADJ
brj-22232	227	53	dataset	dataset	NOUN
brj-22232	227	54	.	.	PUNCT
brj-22232	228	1	this	this	PRON
brj-22232	228	2	is	be	AUX
brj-22232	228	3	because	because	SCONJ
brj-22232	228	4	the	the	DET
brj-22232	228	5	number	number	NOUN
brj-22232	228	6	of	of	ADP
brj-22232	228	7	dataset	dataset	NOUN
brj-22232	228	8	is	be	AUX
brj-22232	228	9	sufficient	sufficient	ADJ
brj-22232	228	10	to	to	PART
brj-22232	228	11	achieve	achieve	VERB
brj-22232	228	12	good	good	ADJ
brj-22232	228	13	results	result	NOUN
brj-22232	228	14	when	when	SCONJ
brj-22232	228	15	using	use	VERB
brj-22232	228	16	r	r	NOUN
brj-22232	228	17	or	or	CCONJ
brj-22232	228	18	rg	rg	PROPN
brj-22232	228	19	dataset	dataset	VERB
brj-22232	228	20	for	for	ADP
brj-22232	228	21	training	training	NOUN
brj-22232	228	22	.	.	PUNCT
brj-22232	229	1	if	if	SCONJ
brj-22232	229	2	simulated	simulate	VERB
brj-22232	229	3	data	datum	NOUN
brj-22232	229	4	are	be	AUX
brj-22232	229	5	added	add	VERB
brj-22232	229	6	,	,	PUNCT
brj-22232	229	7	the	the	DET
brj-22232	229	8	number	number	NOUN
brj-22232	229	9	of	of	ADP
brj-22232	229	10	real	real	ADJ
brj-22232	229	11	data	datum	NOUN
brj-22232	229	12	is	be	AUX
brj-22232	229	13	reduced	reduce	VERB
brj-22232	229	14	,	,	PUNCT
brj-22232	229	15	while	while	SCONJ
brj-22232	229	16	simulated	simulated	ADJ
brj-22232	229	17	data	datum	NOUN
brj-22232	229	18	will	will	AUX
brj-22232	229	19	disturb	disturb	VERB
brj-22232	229	20	the	the	DET
brj-22232	229	21	judgment	judgment	NOUN
brj-22232	229	22	of	of	ADP
brj-22232	229	23	the	the	DET
brj-22232	229	24	real	real	ADJ
brj-22232	229	25	data	datum	NOUN
brj-22232	229	26	and	and	CCONJ
brj-22232	229	27	affect	affect	VERB
brj-22232	229	28	the	the	DET
brj-22232	229	29	training	training	NOUN
brj-22232	229	30	effect	effect	NOUN
brj-22232	229	31	.	.	PUNCT
brj-22232	230	1	the	the	DET
brj-22232	230	2	better	well	ADJ
brj-22232	230	3	training	training	NOUN
brj-22232	230	4	effect	effect	NOUN
brj-22232	230	5	of	of	ADP
brj-22232	230	6	the	the	DET
brj-22232	230	7	rg	rg	PROPN
brj-22232	230	8	dataset	dataset	NOUN
brj-22232	230	9	than	than	ADP
brj-22232	230	10	the	the	DET
brj-22232	230	11	r	r	NOUN
brj-22232	230	12	dataset	dataset	NOUN
brj-22232	230	13	indicates	indicate	VERB
brj-22232	230	14	that	that	SCONJ
brj-22232	230	15	the	the	DET
brj-22232	230	16	addition	addition	NOUN
brj-22232	230	17	of	of	ADP
brj-22232	230	18	the	the	DET
brj-22232	230	19	generated	generate	VERB
brj-22232	230	20	data	datum	NOUN
brj-22232	230	21	helps	help	VERB
brj-22232	230	22	to	to	PART
brj-22232	230	23	increase	increase	VERB
brj-22232	230	24	the	the	DET
brj-22232	230	25	convergence	convergence	NOUN
brj-22232	230	26	effect	effect	NOUN
brj-22232	230	27	of	of	ADP
brj-22232	230	28	the	the	DET
brj-22232	230	29	model	model	NOUN
brj-22232	230	30	and	and	CCONJ
brj-22232	230	31	improve	improve	VERB
brj-22232	230	32	the	the	DET
brj-22232	230	33	recognition	recognition	NOUN
brj-22232	230	34	ability	ability	NOUN
brj-22232	230	35	of	of	ADP
brj-22232	230	36	the	the	DET
brj-22232	230	37	model	model	NOUN
brj-22232	230	38	,	,	PUNCT
brj-22232	230	39	map	map	NOUN
brj-22232	230	40	is	be	AUX
brj-22232	230	41	improved	improve	VERB
brj-22232	230	42	7.14	7.14	NUM
brj-22232	230	43	%	%	NOUN
brj-22232	230	44	.	.	PUNCT
brj-22232	231	1	due	due	ADP
brj-22232	231	2	to	to	ADP
brj-22232	231	3	the	the	DET
brj-22232	231	4	small	small	ADJ
brj-22232	231	5	amount	amount	NOUN
brj-22232	231	6	of	of	ADP
brj-22232	231	7	real	real	ADJ
brj-22232	231	8	data	datum	NOUN
brj-22232	231	9	,	,	PUNCT
brj-22232	231	10	the	the	DET
brj-22232	231	11	traditional	traditional	ADJ
brj-22232	231	12	way	way	NOUN
brj-22232	231	13	of	of	ADP
brj-22232	231	14	training	training	NOUN
brj-22232	231	15	using	use	VERB
brj-22232	231	16	the	the	DET
brj-22232	231	17	rs	rs	ADJ
brj-22232	231	18	dataset	dataset	NOUN
brj-22232	231	19	keeps	keep	VERB
brj-22232	231	20	its	its	PRON
brj-22232	231	21	map	map	NOUN
brj-22232	231	22	value	value	NOUN
brj-22232	231	23	at	at	ADP
brj-22232	231	24	approximately	approximately	ADV
brj-22232	231	25	71.53	71.53	NUM
brj-22232	231	26	%	%	NOUN
brj-22232	231	27	.	.	PUNCT
brj-22232	232	1	adding	add	VERB
brj-22232	232	2	generated	generate	VERB
brj-22232	232	3	data	datum	NOUN
brj-22232	232	4	to	to	ADP
brj-22232	232	5	the	the	DET
brj-22232	232	6	rs	rs	ADJ
brj-22232	232	7	dataset	dataset	NOUN
brj-22232	232	8	and	and	CCONJ
brj-22232	232	9	training	training	NOUN
brj-22232	232	10	using	use	VERB
brj-22232	232	11	the	the	DET
brj-22232	232	12	rgs	rgs	PROPN
brj-22232	232	13	dataset	dataset	PROPN
brj-22232	232	14	keeps	keep	VERB
brj-22232	232	15	its	its	PRON
brj-22232	232	16	map	map	NOUN
brj-22232	232	17	at	at	ADP
brj-22232	232	18	approximately	approximately	ADV
brj-22232	232	19	82.78	82.78	NUM
brj-22232	232	20	%	%	NOUN
brj-22232	232	21	,	,	PUNCT
brj-22232	232	22	with	with	ADP
brj-22232	232	23	an	an	DET
brj-22232	232	24	11.25	11.25	NUM
brj-22232	232	25	%	%	NOUN
brj-22232	232	26	increase	increase	NOUN
brj-22232	232	27	in	in	ADP
brj-22232	232	28	map	map	NOUN
brj-22232	232	29	,	,	PUNCT
brj-22232	232	30	which	which	PRON
brj-22232	232	31	is	be	AUX
brj-22232	232	32	noticeable	noticeable	ADJ
brj-22232	232	33	.	.	PUNCT
brj-22232	233	1	the	the	DET
brj-22232	233	2	results	result	NOUN
brj-22232	233	3	show	show	VERB
brj-22232	233	4	that	that	SCONJ
brj-22232	233	5	the	the	DET
brj-22232	233	6	generated	generate	VERB
brj-22232	233	7	data	datum	NOUN
brj-22232	233	8	can	can	AUX
brj-22232	233	9	both	both	PRON
brj-22232	233	10	expand	expand	VERB
brj-22232	233	11	the	the	DET
brj-22232	233	12	real	real	ADJ
brj-22232	233	13	b	b	NOUN
brj-22232	233	14	-	-	PUNCT
brj-22232	233	15	scan	scan	ADJ
brj-22232	233	16	dataset	dataset	NOUN
brj-22232	233	17	and	and	CCONJ
brj-22232	233	18	increase	increase	VERB
brj-22232	233	19	the	the	DET
brj-22232	233	20	performance	performance	NOUN
brj-22232	233	21	and	and	CCONJ
brj-22232	233	22	detection	detection	NOUN
brj-22232	233	23	accuracy	accuracy	NOUN
brj-22232	233	24	of	of	ADP
brj-22232	233	25	the	the	DET
brj-22232	233	26	trained	train	VERB
brj-22232	233	27	model	model	NOUN
brj-22232	233	28	.	.	PUNCT
brj-22232	234	1	to	to	PART
brj-22232	234	2	further	far	ADV
brj-22232	234	3	validate	validate	VERB
brj-22232	234	4	the	the	DET
brj-22232	234	5	effect	effect	NOUN
brj-22232	234	6	of	of	ADP
brj-22232	234	7	the	the	DET
brj-22232	234	8	generated	generate	VERB
brj-22232	234	9	data	datum	NOUN
brj-22232	234	10	on	on	ADP
brj-22232	234	11	the	the	DET
brj-22232	234	12	training	training	NOUN
brj-22232	234	13	effect	effect	NOUN
brj-22232	234	14	,	,	PUNCT
brj-22232	234	15	yolov3	yolov3	PROPN
brj-22232	234	16	,	,	PUNCT
brj-22232	234	17	faster	fast	ADV
brj-22232	234	18	r	r	NOUN
brj-22232	234	19	-	-	PUNCT
brj-22232	234	20	cnn	cnn	PROPN
brj-22232	234	21	,	,	PUNCT
brj-22232	234	22	and	and	CCONJ
brj-22232	234	23	centernet	centernet	NOUN
brj-22232	234	24	networks	network	NOUN
brj-22232	234	25	are	be	AUX
brj-22232	234	26	used	use	VERB
brj-22232	234	27	to	to	PART
brj-22232	234	28	train	train	VERB
brj-22232	234	29	the	the	DET
brj-22232	234	30	rg	rg	PROPN
brj-22232	234	31	dataset	dataset	PROPN
brj-22232	234	32	and	and	CCONJ
brj-22232	234	33	rgs	rgs	PROPN
brj-22232	234	34	dataset	dataset	PROPN
brj-22232	234	35	.	.	PUNCT
brj-22232	235	1	peer	peer	NOUN
brj-22232	235	2	-	-	PUNCT
brj-22232	235	3	reviewed	review	VERB
brj-22232	235	4	article	article	NOUN
brj-22232	235	5	bioresources.com	bioresources.com	X
brj-22232	235	6	li	li	PROPN
brj-22232	235	7	et	et	PROPN
brj-22232	235	8	al	al	PROPN
brj-22232	235	9	.	.	PROPN
brj-22232	235	10	(	(	PUNCT
brj-22232	235	11	2023	2023	NUM
brj-22232	235	12	)	)	PUNCT
brj-22232	235	13	.	.	PUNCT
brj-22232	236	1	“	"	PUNCT
brj-22232	236	2	tree	tree	NOUN
brj-22232	236	3	root	root	NOUN
brj-22232	236	4	detection	detection	NOUN
brj-22232	236	5	training	training	NOUN
brj-22232	236	6	,	,	PUNCT
brj-22232	236	7	”	"	PUNCT
brj-22232	236	8	bioresources	bioresource	NOUN
brj-22232	236	9	18(1	18(1	NOUN
brj-22232	236	10	)	)	PUNCT
brj-22232	236	11	,	,	PUNCT
brj-22232	236	12	484	484	NUM
brj-22232	236	13	-	-	SYM
brj-22232	236	14	504	504	NUM
brj-22232	236	15	.	.	PUNCT
brj-22232	237	1	496	496	NUM
brj-22232	237	2	figure	figure	NOUN
brj-22232	237	3	10(c	10(c	NUM
brj-22232	237	4	,	,	PUNCT
brj-22232	237	5	d	d	NOUN
brj-22232	237	6	,	,	PUNCT
brj-22232	237	7	e	e	NOUN
brj-22232	237	8	)	)	PUNCT
brj-22232	237	9	corresponds	correspond	VERB
brj-22232	237	10	to	to	ADP
brj-22232	237	11	the	the	DET
brj-22232	237	12	loss	loss	NOUN
brj-22232	237	13	curves	curve	NOUN
brj-22232	237	14	of	of	ADP
brj-22232	237	15	the	the	DET
brj-22232	237	16	three	three	NUM
brj-22232	237	17	networks	network	NOUN
brj-22232	237	18	after	after	ADP
brj-22232	237	19	training	training	NOUN
brj-22232	237	20	.	.	PUNCT
brj-22232	238	1	the	the	DET
brj-22232	238	2	loss	loss	NOUN
brj-22232	238	3	values	value	NOUN
brj-22232	238	4	of	of	ADP
brj-22232	238	5	three	three	NUM
brj-22232	238	6	networks	network	NOUN
brj-22232	238	7	after	after	ADP
brj-22232	238	8	training	training	NOUN
brj-22232	238	9	were	be	AUX
brj-22232	238	10	lower	low	ADJ
brj-22232	238	11	than	than	ADP
brj-22232	238	12	1.5	1.5	NUM
brj-22232	238	13	,	,	PUNCT
brj-22232	238	14	and	and	CCONJ
brj-22232	238	15	the	the	DET
brj-22232	238	16	loss	loss	NOUN
brj-22232	238	17	value	value	NOUN
brj-22232	238	18	of	of	ADP
brj-22232	238	19	the	the	DET
brj-22232	238	20	rg	rg	PROPN
brj-22232	238	21	model	model	NOUN
brj-22232	238	22	was	be	AUX
brj-22232	238	23	lower	low	ADJ
brj-22232	238	24	than	than	ADP
brj-22232	238	25	that	that	PRON
brj-22232	238	26	of	of	ADP
brj-22232	238	27	the	the	DET
brj-22232	238	28	rgs	rgs	PROPN
brj-22232	238	29	model	model	NOUN
brj-22232	238	30	,	,	PUNCT
brj-22232	238	31	verifying	verify	VERB
brj-22232	238	32	that	that	SCONJ
brj-22232	238	33	the	the	DET
brj-22232	238	34	simulation	simulation	NOUN
brj-22232	238	35	images	image	NOUN
brj-22232	238	36	increase	increase	VERB
brj-22232	238	37	the	the	DET
brj-22232	238	38	loss	loss	NOUN
brj-22232	238	39	value	value	NOUN
brj-22232	238	40	of	of	ADP
brj-22232	238	41	its	its	PRON
brj-22232	238	42	model	model	NOUN
brj-22232	238	43	and	and	CCONJ
brj-22232	238	44	decrease	decrease	VERB
brj-22232	238	45	its	its	PRON
brj-22232	238	46	map	map	NOUN
brj-22232	238	47	value	value	NOUN
brj-22232	238	48	.	.	PUNCT
brj-22232	239	1	the	the	DET
brj-22232	239	2	map	map	NOUN
brj-22232	239	3	curves	curve	VERB
brj-22232	239	4	after	after	SCONJ
brj-22232	239	5	training	training	NOUN
brj-22232	239	6	using	use	VERB
brj-22232	239	7	different	different	ADJ
brj-22232	239	8	deep	deep	ADJ
brj-22232	239	9	learning	learning	NOUN
brj-22232	239	10	methods	method	NOUN
brj-22232	239	11	for	for	ADP
brj-22232	239	12	the	the	DET
brj-22232	239	13	rg	rg	PROPN
brj-22232	239	14	and	and	CCONJ
brj-22232	239	15	rgs	rgs	PROPN
brj-22232	239	16	datasets	dataset	NOUN
brj-22232	239	17	are	be	AUX
brj-22232	239	18	shown	show	VERB
brj-22232	239	19	in	in	ADP
brj-22232	239	20	fig	fig	NOUN
brj-22232	239	21	.	.	PUNCT
brj-22232	240	1	10f	10f	PROPN
brj-22232	240	2	.	.	PUNCT
brj-22232	241	1	the	the	DET
brj-22232	241	2	yolov5	yolov5	NOUN
brj-22232	241	3	model	model	NOUN
brj-22232	241	4	outperforms	outperform	VERB
brj-22232	241	5	the	the	DET
brj-22232	241	6	yolov3	yolov3	PROPN
brj-22232	241	7	,	,	PUNCT
brj-22232	241	8	faster	fast	ADJ
brj-22232	241	9	r	r	NOUN
brj-22232	241	10	-	-	PUNCT
brj-22232	241	11	cnn	cnn	PROPN
brj-22232	241	12	,	,	PUNCT
brj-22232	241	13	and	and	CCONJ
brj-22232	241	14	centernet	centernet	NOUN
brj-22232	241	15	models	model	NOUN
brj-22232	241	16	in	in	ADP
brj-22232	241	17	terms	term	NOUN
brj-22232	241	18	of	of	ADP
brj-22232	241	19	map	map	NOUN
brj-22232	241	20	during	during	ADP
brj-22232	241	21	training	training	NOUN
brj-22232	241	22	(	(	PUNCT
brj-22232	241	23	fig	fig	NOUN
brj-22232	241	24	.	.	PUNCT
brj-22232	241	25	10f	10f	NOUN
brj-22232	241	26	)	)	PUNCT
brj-22232	241	27	.	.	PUNCT
brj-22232	242	1	the	the	DET
brj-22232	242	2	map	map	NOUN
brj-22232	242	3	of	of	ADP
brj-22232	242	4	the	the	DET
brj-22232	242	5	yolov5	yolov5	NOUN
brj-22232	242	6	model	model	NOUN
brj-22232	242	7	exceeds	exceed	VERB
brj-22232	242	8	80	80	NUM
brj-22232	242	9	%	%	NOUN
brj-22232	242	10	on	on	ADP
brj-22232	242	11	both	both	DET
brj-22232	242	12	datasets	dataset	NOUN
brj-22232	242	13	.	.	PUNCT
brj-22232	243	1	the	the	DET
brj-22232	243	2	map	map	NOUN
brj-22232	243	3	values	value	NOUN
brj-22232	243	4	of	of	ADP
brj-22232	243	5	both	both	CCONJ
brj-22232	243	6	faster	fast	ADJ
brj-22232	243	7	r	r	NOUN
brj-22232	243	8	-	-	PUNCT
brj-22232	243	9	cnn	cnn	PROPN
brj-22232	243	10	and	and	CCONJ
brj-22232	243	11	yolov3	yolov3	PROPN
brj-22232	243	12	remain	remain	VERB
brj-22232	243	13	between	between	ADP
brj-22232	243	14	70	70	NUM
brj-22232	243	15	%	%	NOUN
brj-22232	243	16	and	and	CCONJ
brj-22232	243	17	80	80	NUM
brj-22232	243	18	%	%	NOUN
brj-22232	243	19	,	,	PUNCT
brj-22232	243	20	and	and	CCONJ
brj-22232	243	21	the	the	DET
brj-22232	243	22	map	map	NOUN
brj-22232	243	23	value	value	NOUN
brj-22232	243	24	of	of	ADP
brj-22232	243	25	faster	fast	ADJ
brj-22232	243	26	r	r	NOUN
brj-22232	243	27	-	-	PUNCT
brj-22232	243	28	cnn	cnn	PROPN
brj-22232	243	29	is	be	AUX
brj-22232	243	30	slightly	slightly	ADV
brj-22232	243	31	higher	high	ADJ
brj-22232	243	32	than	than	ADP
brj-22232	243	33	that	that	PRON
brj-22232	243	34	of	of	ADP
brj-22232	243	35	yolov3	yolov3	PROPN
brj-22232	243	36	.	.	PUNCT
brj-22232	244	1	centernet	centernet	PROPN
brj-22232	244	2	has	have	VERB
brj-22232	244	3	the	the	DET
brj-22232	244	4	worst	bad	ADJ
brj-22232	244	5	training	training	NOUN
brj-22232	244	6	results	result	NOUN
brj-22232	244	7	,	,	PUNCT
brj-22232	244	8	with	with	ADP
brj-22232	244	9	map	map	NOUN
brj-22232	244	10	below	below	ADP
brj-22232	244	11	70	70	NUM
brj-22232	244	12	%	%	NOUN
brj-22232	244	13	.	.	PUNCT
brj-22232	245	1	combining	combine	VERB
brj-22232	245	2	the	the	DET
brj-22232	245	3	loss	loss	NOUN
brj-22232	245	4	and	and	CCONJ
brj-22232	245	5	map	map	VERB
brj-22232	245	6	values	value	NOUN
brj-22232	245	7	yields	yield	NOUN
brj-22232	245	8	that	that	PRON
brj-22232	245	9	yolov5	yolov5	NOUN
brj-22232	245	10	model	model	NOUN
brj-22232	245	11	has	have	VERB
brj-22232	245	12	an	an	DET
brj-22232	245	13	impressive	impressive	ADJ
brj-22232	245	14	training	training	NOUN
brj-22232	245	15	performance	performance	NOUN
brj-22232	245	16	.	.	PUNCT
brj-22232	246	1	peer	peer	NOUN
brj-22232	246	2	-	-	PUNCT
brj-22232	246	3	reviewed	review	VERB
brj-22232	246	4	article	article	NOUN
brj-22232	246	5	bioresources.com	bioresources.com	X
brj-22232	246	6	li	li	PROPN
brj-22232	246	7	et	et	PROPN
brj-22232	246	8	al	al	PROPN
brj-22232	246	9	.	.	PROPN
brj-22232	246	10	(	(	PUNCT
brj-22232	246	11	2023	2023	NUM
brj-22232	246	12	)	)	PUNCT
brj-22232	246	13	.	.	PUNCT
brj-22232	247	1	“	"	PUNCT
brj-22232	247	2	tree	tree	NOUN
brj-22232	247	3	root	root	NOUN
brj-22232	247	4	detection	detection	NOUN
brj-22232	247	5	training	training	NOUN
brj-22232	247	6	,	,	PUNCT
brj-22232	247	7	”	"	PUNCT
brj-22232	247	8	bioresources	bioresource	NOUN
brj-22232	247	9	18(1	18(1	NOUN
brj-22232	247	10	)	)	PUNCT
brj-22232	247	11	,	,	PUNCT
brj-22232	247	12	484	484	NUM
brj-22232	247	13	-	-	SYM
brj-22232	247	14	504	504	NUM
brj-22232	247	15	.	.	PUNCT
brj-22232	248	1	497	497	NUM
brj-22232	248	2	peer	peer	NOUN
brj-22232	248	3	-	-	PUNCT
brj-22232	248	4	reviewed	review	VERB
brj-22232	248	5	article	article	NOUN
brj-22232	248	6	bioresources.com	bioresources.com	X
brj-22232	248	7	li	li	PROPN
brj-22232	248	8	et	et	PROPN
brj-22232	248	9	al	al	PROPN
brj-22232	248	10	.	.	PROPN
brj-22232	248	11	(	(	PUNCT
brj-22232	248	12	2023	2023	NUM
brj-22232	248	13	)	)	PUNCT
brj-22232	248	14	.	.	PUNCT
brj-22232	249	1	“	"	PUNCT
brj-22232	249	2	tree	tree	NOUN
brj-22232	249	3	root	root	NOUN
brj-22232	249	4	detection	detection	NOUN
brj-22232	249	5	training	training	NOUN
brj-22232	249	6	,	,	PUNCT
brj-22232	249	7	”	"	PUNCT
brj-22232	249	8	bioresources	bioresource	NOUN
brj-22232	249	9	18(1	18(1	NOUN
brj-22232	249	10	)	)	PUNCT
brj-22232	249	11	,	,	PUNCT
brj-22232	249	12	484	484	NUM
brj-22232	249	13	-	-	SYM
brj-22232	249	14	504	504	NUM
brj-22232	249	15	.	.	PUNCT
brj-22232	250	1	498	498	NUM
brj-22232	250	2	fig	fig	NOUN
brj-22232	250	3	.	.	PUNCT
brj-22232	251	1	10	10	NUM
brj-22232	251	2	.	.	PUNCT
brj-22232	251	3	training	training	NOUN
brj-22232	251	4	results	result	NOUN
brj-22232	251	5	of	of	ADP
brj-22232	251	6	the	the	DET
brj-22232	251	7	model	model	NOUN
brj-22232	251	8	:	:	PUNCT
brj-22232	251	9	(	(	PUNCT
brj-22232	251	10	a	a	X
brj-22232	251	11	)	)	PUNCT
brj-22232	251	12	the	the	DET
brj-22232	251	13	map	map	NOUN
brj-22232	251	14	values	value	NOUN
brj-22232	251	15	of	of	ADP
brj-22232	251	16	the	the	DET
brj-22232	251	17	training	training	NOUN
brj-22232	251	18	process	process	NOUN
brj-22232	251	19	using	use	VERB
brj-22232	251	20	yolov5	yolov5	NOUN
brj-22232	251	21	for	for	ADP
brj-22232	251	22	7	7	NUM
brj-22232	251	23	datasets	dataset	NOUN
brj-22232	251	24	.	.	PUNCT
brj-22232	252	1	(	(	PUNCT
brj-22232	252	2	b	b	X
brj-22232	252	3	)	)	PUNCT
brj-22232	252	4	training	training	NOUN
brj-22232	252	5	loss	loss	NOUN
brj-22232	252	6	values	value	NOUN
brj-22232	252	7	for	for	ADP
brj-22232	252	8	7	7	NUM
brj-22232	252	9	datasets	dataset	NOUN
brj-22232	252	10	.	.	PUNCT
brj-22232	253	1	(	(	PUNCT
brj-22232	253	2	c	c	X
brj-22232	253	3	)	)	PUNCT
brj-22232	253	4	loss	loss	NOUN
brj-22232	253	5	curves	curve	NOUN
brj-22232	253	6	of	of	ADP
brj-22232	253	7	the	the	DET
brj-22232	253	8	yolov3	yolov3	PROPN
brj-22232	253	9	model	model	PROPN
brj-22232	253	10	.	.	PUNCT
brj-22232	254	1	(	(	PUNCT
brj-22232	254	2	d	d	X
brj-22232	254	3	)	)	PUNCT
brj-22232	254	4	loss	loss	NOUN
brj-22232	254	5	curves	curve	NOUN
brj-22232	254	6	of	of	ADP
brj-22232	254	7	the	the	DET
brj-22232	254	8	faster	fast	ADJ
brj-22232	254	9	r	r	NOUN
brj-22232	254	10	-	-	PUNCT
brj-22232	254	11	cnn	cnn	PROPN
brj-22232	254	12	model	model	NOUN
brj-22232	254	13	.	.	PUNCT
brj-22232	255	1	(	(	PUNCT
brj-22232	255	2	e	e	NOUN
brj-22232	255	3	)	)	PUNCT
brj-22232	255	4	loss	loss	NOUN
brj-22232	255	5	curves	curve	NOUN
brj-22232	255	6	of	of	ADP
brj-22232	255	7	the	the	DET
brj-22232	255	8	centernet	centernet	NOUN
brj-22232	255	9	model	model	NOUN
brj-22232	255	10	.	.	PUNCT
brj-22232	256	1	(	(	PUNCT
brj-22232	256	2	f	f	X
brj-22232	256	3	)	)	PUNCT
brj-22232	256	4	the	the	DET
brj-22232	256	5	map	map	NOUN
brj-22232	256	6	values	value	NOUN
brj-22232	256	7	of	of	ADP
brj-22232	256	8	the	the	DET
brj-22232	256	9	different	different	ADJ
brj-22232	256	10	methods	method	NOUN
brj-22232	256	11	on	on	ADP
brj-22232	256	12	each	each	PRON
brj-22232	256	13	of	of	ADP
brj-22232	256	14	the	the	DET
brj-22232	256	15	two	two	NUM
brj-22232	256	16	datasets	dataset	NOUN
brj-22232	256	17	.	.	PUNCT
brj-22232	257	1	table	table	NOUN
brj-22232	257	2	3	3	NUM
brj-22232	257	3	summarizes	summarize	NOUN
brj-22232	257	4	all	all	DET
brj-22232	257	5	training	training	NOUN
brj-22232	257	6	results	result	NOUN
brj-22232	257	7	for	for	ADP
brj-22232	257	8	the	the	DET
brj-22232	257	9	four	four	NUM
brj-22232	257	10	networks	network	NOUN
brj-22232	257	11	corresponding	correspond	VERB
brj-22232	257	12	to	to	ADP
brj-22232	257	13	the	the	DET
brj-22232	257	14	eight	eight	NUM
brj-22232	257	15	models	model	NOUN
brj-22232	257	16	.	.	PUNCT
brj-22232	258	1	the	the	DET
brj-22232	258	2	values	value	NOUN
brj-22232	258	3	of	of	ADP
brj-22232	258	4	the	the	DET
brj-22232	258	5	evaluation	evaluation	NOUN
brj-22232	258	6	indicators	indicator	NOUN
brj-22232	258	7	of	of	ADP
brj-22232	258	8	the	the	DET
brj-22232	258	9	yolov5	yolov5	NOUN
brj-22232	258	10	model	model	NOUN
brj-22232	258	11	exceed	exceed	VERB
brj-22232	258	12	the	the	DET
brj-22232	258	13	other	other	ADJ
brj-22232	258	14	models	model	NOUN
brj-22232	258	15	by	by	ADP
brj-22232	258	16	5	5	NUM
brj-22232	258	17	%	%	NOUN
brj-22232	258	18	to	to	PART
brj-22232	258	19	15	15	NUM
brj-22232	258	20	%	%	NOUN
brj-22232	258	21	in	in	ADP
brj-22232	258	22	terms	term	NOUN
brj-22232	258	23	of	of	ADP
brj-22232	258	24	f1	f1	NOUN
brj-22232	258	25	scores	score	NOUN
brj-22232	258	26	and	and	CCONJ
brj-22232	258	27	map	map	VERB
brj-22232	258	28	values	value	NOUN
brj-22232	258	29	.	.	PUNCT
brj-22232	259	1	table	table	NOUN
brj-22232	259	2	3	3	NUM
brj-22232	259	3	.	.	PUNCT
brj-22232	260	1	training	training	NOUN
brj-22232	260	2	results	result	NOUN
brj-22232	260	3	of	of	ADP
brj-22232	260	4	the	the	DET
brj-22232	260	5	eight	eight	NUM
brj-22232	260	6	models	model	NOUN
brj-22232	260	7	model	model	NOUN
brj-22232	260	8	dataset	dataset	VERB
brj-22232	260	9	rg	rg	PROPN
brj-22232	260	10	rgs	rgs	PROPN
brj-22232	260	11	p	p	PROPN
brj-22232	260	12	r	r	NOUN
brj-22232	260	13	map	map	NOUN
brj-22232	260	14	f1	f1	NOUN
brj-22232	260	15	p	p	NOUN
brj-22232	260	16	r	r	NOUN
brj-22232	260	17	map	map	NOUN
brj-22232	260	18	f1	f1	NOUN
brj-22232	260	19	yolov3	yolov3	PROPN
brj-22232	260	20	0.76	0.76	NUM
brj-22232	260	21	0.72	0.72	NUM
brj-22232	260	22	0.74	0.74	NUM
brj-22232	260	23	0.77	0.77	NUM
brj-22232	260	24	0.77	0.77	NUM
brj-22232	260	25	0.68	0.68	NUM
brj-22232	260	26	0.72	0.72	NUM
brj-22232	260	27	0.74	0.74	NUM
brj-22232	260	28	yolov5	yolov5	NOUN
brj-22232	260	29	0.84	0.84	NUM
brj-22232	260	30	0.81	0.81	NUM
brj-22232	260	31	0.85	0.85	NUM
brj-22232	260	32	0.83	0.83	NUM
brj-22232	260	33	0.88	0.88	NUM
brj-22232	260	34	0.75	0.75	NUM
brj-22232	260	35	0.82	0.82	NUM
brj-22232	260	36	0.81	0.81	NUM
brj-22232	260	37	faster	fast	ADJ
brj-22232	260	38	r	r	NOUN
brj-22232	260	39	-	-	PUNCT
brj-22232	260	40	cnn	cnn	PROPN
brj-22232	260	41	0.79	0.79	NUM
brj-22232	260	42	0.78	0.78	NUM
brj-22232	260	43	0.79	0.79	NUM
brj-22232	260	44	0.81	0.81	NUM
brj-22232	260	45	0.81	0.81	NUM
brj-22232	260	46	0.73	0.73	NUM
brj-22232	260	47	0.77	0.77	NUM
brj-22232	260	48	0.76	0.76	NUM
brj-22232	260	49	centernet	centernet	NOUN
brj-22232	260	50	0.70	0.70	NUM
brj-22232	260	51	0.71	0.71	NUM
brj-22232	260	52	0.69	0.69	NUM
brj-22232	260	53	0.71	0.71	NUM
brj-22232	260	54	0.73	0.73	NUM
brj-22232	260	55	0.67	0.67	NUM
brj-22232	260	56	0.68	0.68	NUM
brj-22232	260	57	0.70	0.70	NUM
brj-22232	260	58	analysis	analysis	NOUN
brj-22232	260	59	of	of	ADP
brj-22232	260	60	testing	testing	NOUN
brj-22232	260	61	and	and	CCONJ
brj-22232	260	62	test	test	NOUN
brj-22232	260	63	results	result	NOUN
brj-22232	260	64	in	in	ADP
brj-22232	260	65	this	this	DET
brj-22232	260	66	paper	paper	NOUN
brj-22232	260	67	,	,	PUNCT
brj-22232	260	68	all	all	DET
brj-22232	260	69	dataset	dataset	NOUN
brj-22232	260	70	models	model	NOUN
brj-22232	260	71	were	be	AUX
brj-22232	260	72	tested	test	VERB
brj-22232	260	73	with	with	ADP
brj-22232	260	74	the	the	DET
brj-22232	260	75	same	same	ADJ
brj-22232	260	76	testset	testset	NOUN
brj-22232	260	77	,	,	PUNCT
brj-22232	260	78	and	and	CCONJ
brj-22232	260	79	the	the	DET
brj-22232	260	80	test	test	NOUN
brj-22232	260	81	results	result	NOUN
brj-22232	260	82	are	be	AUX
brj-22232	260	83	shown	show	VERB
brj-22232	260	84	in	in	ADP
brj-22232	260	85	fig	fig	NOUN
brj-22232	260	86	.	.	PUNCT
brj-22232	261	1	11	11	NUM
brj-22232	261	2	.	.	PUNCT
brj-22232	262	1	the	the	DET
brj-22232	262	2	rgs	rgs	PROPN
brj-22232	262	3	training	training	NOUN
brj-22232	262	4	model	model	NOUN
brj-22232	262	5	testing	testing	NOUN
brj-22232	262	6	results	result	NOUN
brj-22232	262	7	are	be	AUX
brj-22232	262	8	the	the	DET
brj-22232	262	9	best	good	ADJ
brj-22232	262	10	,	,	PUNCT
brj-22232	262	11	with	with	ADP
brj-22232	262	12	better	well	ADJ
brj-22232	262	13	detection	detection	NOUN
brj-22232	262	14	for	for	ADP
brj-22232	262	15	real	real	ADJ
brj-22232	262	16	data	datum	NOUN
brj-22232	262	17	,	,	PUNCT
brj-22232	262	18	simulated	simulated	ADJ
brj-22232	262	19	data	datum	NOUN
brj-22232	262	20	,	,	PUNCT
brj-22232	262	21	and	and	CCONJ
brj-22232	262	22	generated	generate	VERB
brj-22232	262	23	data	datum	NOUN
brj-22232	262	24	.	.	PUNCT
brj-22232	263	1	the	the	DET
brj-22232	263	2	map	map	NOUN
brj-22232	263	3	value	value	NOUN
brj-22232	263	4	is	be	AUX
brj-22232	263	5	improved	improve	VERB
brj-22232	263	6	approximately	approximately	ADV
brj-22232	263	7	10	10	NUM
brj-22232	263	8	%	%	NOUN
brj-22232	263	9	compared	compare	VERB
brj-22232	263	10	to	to	ADP
brj-22232	263	11	the	the	DET
brj-22232	263	12	rs	rs	PROPN
brj-22232	263	13	training	training	NOUN
brj-22232	263	14	model	model	NOUN
brj-22232	263	15	,	,	PUNCT
brj-22232	263	16	while	while	SCONJ
brj-22232	263	17	the	the	DET
brj-22232	263	18	rg	rg	NOUN
brj-22232	263	19	training	training	NOUN
brj-22232	263	20	model	model	NOUN
brj-22232	263	21	outperforms	outperform	VERB
brj-22232	263	22	the	the	DET
brj-22232	263	23	r	r	NOUN
brj-22232	263	24	training	training	NOUN
brj-22232	263	25	model	model	NOUN
brj-22232	263	26	in	in	ADP
brj-22232	263	27	terms	term	NOUN
brj-22232	263	28	of	of	ADP
brj-22232	263	29	recall	recall	NOUN
brj-22232	263	30	and	and	CCONJ
brj-22232	263	31	map	map	NOUN
brj-22232	263	32	,	,	PUNCT
brj-22232	263	33	confirming	confirm	VERB
brj-22232	263	34	the	the	DET
brj-22232	263	35	reliability	reliability	NOUN
brj-22232	263	36	of	of	ADP
brj-22232	263	37	the	the	DET
brj-22232	263	38	training	training	NOUN
brj-22232	263	39	results	result	NOUN
brj-22232	263	40	.	.	PUNCT
brj-22232	264	1	it	it	PRON
brj-22232	264	2	was	be	AUX
brj-22232	264	3	shown	show	VERB
brj-22232	264	4	that	that	SCONJ
brj-22232	264	5	the	the	DET
brj-22232	264	6	generated	generate	VERB
brj-22232	264	7	data	datum	NOUN
brj-22232	264	8	may	may	AUX
brj-22232	264	9	improve	improve	VERB
brj-22232	264	10	the	the	DET
brj-22232	264	11	comprehensive	comprehensive	ADJ
brj-22232	264	12	performance	performance	NOUN
brj-22232	264	13	of	of	ADP
brj-22232	264	14	the	the	DET
brj-22232	264	15	training	training	NOUN
brj-22232	264	16	model	model	NOUN
brj-22232	264	17	.	.	PUNCT
brj-22232	265	1	peer	peer	NOUN
brj-22232	265	2	-	-	PUNCT
brj-22232	265	3	reviewed	review	VERB
brj-22232	265	4	article	article	NOUN
brj-22232	265	5	bioresources.com	bioresources.com	X
brj-22232	265	6	li	li	PROPN
brj-22232	265	7	et	et	PROPN
brj-22232	265	8	al	al	PROPN
brj-22232	265	9	.	.	PROPN
brj-22232	265	10	(	(	PUNCT
brj-22232	265	11	2023	2023	NUM
brj-22232	265	12	)	)	PUNCT
brj-22232	265	13	.	.	PUNCT
brj-22232	266	1	“	"	PUNCT
brj-22232	266	2	tree	tree	NOUN
brj-22232	266	3	root	root	NOUN
brj-22232	266	4	detection	detection	NOUN
brj-22232	266	5	training	training	NOUN
brj-22232	266	6	,	,	PUNCT
brj-22232	266	7	”	"	PUNCT
brj-22232	266	8	bioresources	bioresource	NOUN
brj-22232	266	9	18(1	18(1	NOUN
brj-22232	266	10	)	)	PUNCT
brj-22232	266	11	,	,	PUNCT
brj-22232	266	12	484	484	NUM
brj-22232	266	13	-	-	SYM
brj-22232	266	14	504	504	NUM
brj-22232	266	15	.	.	PUNCT
brj-22232	267	1	499	499	NUM
brj-22232	267	2	fig	fig	NOUN
brj-22232	267	3	.	.	PUNCT
brj-22232	268	1	11	11	NUM
brj-22232	268	2	.	.	X
brj-22232	269	1	effect	effect	NOUN
brj-22232	269	2	of	of	ADP
brj-22232	269	3	testing	testing	NOUN
brj-22232	269	4	set	set	VERB
brj-22232	269	5	on	on	ADP
brj-22232	269	6	seven	seven	NUM
brj-22232	269	7	dataset	dataset	ADJ
brj-22232	269	8	models(rgs	models(rg	NOUN
brj-22232	269	9	:	:	PUNCT
brj-22232	269	10	real	real	ADJ
brj-22232	269	11	generation	generation	NOUN
brj-22232	269	12	simulation;g	simulation;g	VERB
brj-22232	269	13	:	:	PUNCT
brj-22232	269	14	generation;gs	generation;gs	NOUN
brj-22232	269	15	:	:	PUNCT
brj-22232	269	16	generation	generation	NOUN
brj-22232	269	17	simulation;r	simulation;r	NOUN
brj-22232	269	18	:	:	PUNCT
brj-22232	269	19	real;rs	real;rs	NOUN
brj-22232	269	20	:	:	PUNCT
brj-22232	269	21	real	real	ADJ
brj-22232	269	22	simulation;s	simulation;s	NOUN
brj-22232	269	23	:	:	PUNCT
brj-22232	269	24	simulation;rg	simulation;rg	NUM
brj-22232	269	25	:	:	PUNCT
brj-22232	269	26	real	real	ADJ
brj-22232	269	27	generation	generation	NOUN
brj-22232	269	28	)	)	PUNCT
brj-22232	269	29	fig	fig	NOUN
brj-22232	269	30	.	.	PUNCT
brj-22232	270	1	12	12	NUM
brj-22232	270	2	.	.	PUNCT
brj-22232	271	1	testing	testing	NOUN
brj-22232	271	2	results	result	NOUN
brj-22232	271	3	of	of	ADP
brj-22232	271	4	the	the	DET
brj-22232	271	5	data	datum	NOUN
brj-22232	271	6	set	set	VERB
brj-22232	271	7	:	:	PUNCT
brj-22232	271	8	(	(	PUNCT
brj-22232	271	9	a	a	X
brj-22232	271	10	)	)	PUNCT
brj-22232	271	11	detection	detection	NOUN
brj-22232	271	12	results	result	NOUN
brj-22232	271	13	of	of	ADP
brj-22232	271	14	seven	seven	NUM
brj-22232	271	15	dataset	dataset	NOUN
brj-22232	271	16	models	model	NOUN
brj-22232	271	17	using	use	VERB
brj-22232	271	18	yolov5	yolov5	NOUN
brj-22232	271	19	;	;	PUNCT
brj-22232	271	20	(	(	PUNCT
brj-22232	271	21	b	b	X
brj-22232	271	22	)	)	PUNCT
brj-22232	271	23	detection	detection	NOUN
brj-22232	271	24	results	result	NOUN
brj-22232	271	25	of	of	ADP
brj-22232	271	26	images	image	NOUN
brj-22232	271	27	under	under	ADP
brj-22232	271	28	complex	complex	ADJ
brj-22232	271	29	conditions	condition	NOUN
brj-22232	271	30	peer	peer	NOUN
brj-22232	271	31	-	-	PUNCT
brj-22232	271	32	reviewed	review	VERB
brj-22232	271	33	article	article	NOUN
brj-22232	271	34	bioresources.com	bioresources.com	X
brj-22232	271	35	li	li	PROPN
brj-22232	271	36	et	et	PROPN
brj-22232	271	37	al	al	PROPN
brj-22232	271	38	.	.	PROPN
brj-22232	272	1	(	(	PUNCT
brj-22232	272	2	2023	2023	NUM
brj-22232	272	3	)	)	PUNCT
brj-22232	272	4	.	.	PUNCT
brj-22232	273	1	“	"	PUNCT
brj-22232	273	2	tree	tree	NOUN
brj-22232	273	3	root	root	NOUN
brj-22232	273	4	detection	detection	NOUN
brj-22232	273	5	training	training	NOUN
brj-22232	273	6	,	,	PUNCT
brj-22232	273	7	”	"	PUNCT
brj-22232	273	8	bioresources	bioresource	NOUN
brj-22232	273	9	18(1	18(1	NOUN
brj-22232	273	10	)	)	PUNCT
brj-22232	273	11	,	,	PUNCT
brj-22232	273	12	484	484	NUM
brj-22232	273	13	-	-	SYM
brj-22232	273	14	504	504	NUM
brj-22232	273	15	.	.	PUNCT
brj-22232	274	1	500	500	NUM
brj-22232	274	2	figure	figure	NOUN
brj-22232	274	3	12a	12a	NOUN
brj-22232	274	4	shows	show	VERB
brj-22232	274	5	the	the	DET
brj-22232	274	6	partial	partial	ADJ
brj-22232	274	7	detection	detection	NOUN
brj-22232	274	8	results	result	NOUN
brj-22232	274	9	of	of	ADP
brj-22232	274	10	yolov5	yolov5	NOUN
brj-22232	274	11	training	train	VERB
brj-22232	274	12	seven	seven	NUM
brj-22232	274	13	dataset	dataset	NOUN
brj-22232	274	14	models	model	NOUN
brj-22232	274	15	on	on	ADP
brj-22232	274	16	real	real	ADJ
brj-22232	274	17	b	b	NOUN
brj-22232	274	18	-	-	PUNCT
brj-22232	274	19	scan	scan	ADJ
brj-22232	274	20	images	image	NOUN
brj-22232	274	21	.	.	PUNCT
brj-22232	275	1	there	there	PRON
brj-22232	275	2	are	be	VERB
brj-22232	275	3	three	three	NUM
brj-22232	275	4	hyperbolic	hyperbolic	ADJ
brj-22232	275	5	features	feature	NOUN
brj-22232	275	6	in	in	ADP
brj-22232	275	7	the	the	DET
brj-22232	275	8	real	real	ADJ
brj-22232	275	9	b	b	NOUN
brj-22232	275	10	-	-	PUNCT
brj-22232	275	11	scan	scan	ADJ
brj-22232	275	12	image	image	NOUN
brj-22232	275	13	,	,	PUNCT
brj-22232	275	14	except	except	SCONJ
brj-22232	275	15	for	for	ADP
brj-22232	275	16	the	the	DET
brj-22232	275	17	s	s	X
brj-22232	275	18	dataset	dataset	NOUN
brj-22232	275	19	training	training	NOUN
brj-22232	275	20	model	model	NOUN
brj-22232	275	21	,	,	PUNCT
brj-22232	275	22	which	which	PRON
brj-22232	275	23	is	be	AUX
brj-22232	275	24	not	not	PART
brj-22232	275	25	detected	detect	VERB
brj-22232	275	26	completely	completely	ADV
brj-22232	275	27	,	,	PUNCT
brj-22232	275	28	the	the	DET
brj-22232	275	29	rest	rest	NOUN
brj-22232	275	30	of	of	ADP
brj-22232	275	31	the	the	DET
brj-22232	275	32	dataset	dataset	NOUN
brj-22232	275	33	training	training	NOUN
brj-22232	275	34	models	model	NOUN
brj-22232	275	35	are	be	AUX
brj-22232	275	36	detected	detect	VERB
brj-22232	275	37	completely	completely	ADV
brj-22232	275	38	,	,	PUNCT
brj-22232	275	39	and	and	CCONJ
brj-22232	275	40	the	the	DET
brj-22232	275	41	rg	rg	PROPN
brj-22232	275	42	training	training	NOUN
brj-22232	275	43	model	model	NOUN
brj-22232	275	44	has	have	VERB
brj-22232	275	45	the	the	DET
brj-22232	275	46	lowest	low	ADJ
brj-22232	275	47	confidence	confidence	NOUN
brj-22232	275	48	in	in	ADP
brj-22232	275	49	detection	detection	NOUN
brj-22232	275	50	with	with	ADP
brj-22232	275	51	the	the	DET
brj-22232	275	52	mean	mean	ADJ
brj-22232	275	53	value	value	NOUN
brj-22232	275	54	of	of	ADP
brj-22232	275	55	only	only	ADV
brj-22232	275	56	0.68	0.68	NUM
brj-22232	275	57	.	.	PUNCT
brj-22232	276	1	the	the	DET
brj-22232	276	2	training	training	NOUN
brj-22232	276	3	model	model	NOUN
brj-22232	276	4	for	for	ADP
brj-22232	276	5	the	the	DET
brj-22232	276	6	g	g	PROPN
brj-22232	276	7	dataset	dataset	NOUN
brj-22232	276	8	improved	improve	VERB
brj-22232	276	9	slightly	slightly	ADV
brj-22232	276	10	with	with	ADP
brj-22232	276	11	a	a	DET
brj-22232	276	12	confidence	confidence	NOUN
brj-22232	276	13	mean	mean	NOUN
brj-22232	276	14	value	value	NOUN
brj-22232	276	15	of	of	ADP
brj-22232	276	16	0.74	0.74	NUM
brj-22232	276	17	.	.	PUNCT
brj-22232	277	1	the	the	DET
brj-22232	277	2	confidence	confidence	NOUN
brj-22232	277	3	mean	mean	VERB
brj-22232	277	4	values	value	NOUN
brj-22232	277	5	for	for	ADP
brj-22232	277	6	the	the	DET
brj-22232	277	7	rs	rs	NOUN
brj-22232	277	8	,	,	PUNCT
brj-22232	277	9	r	r	NOUN
brj-22232	277	10	,	,	PUNCT
brj-22232	277	11	rg	rg	NOUN
brj-22232	277	12	,	,	PUNCT
brj-22232	277	13	and	and	CCONJ
brj-22232	277	14	the	the	DET
brj-22232	277	15	rgs	rgs	PROPN
brj-22232	277	16	training	training	NOUN
brj-22232	277	17	models	model	NOUN
brj-22232	277	18	were	be	AUX
brj-22232	277	19	above	above	ADP
brj-22232	277	20	0.8	0.8	NUM
brj-22232	277	21	,	,	PUNCT
brj-22232	277	22	and	and	CCONJ
brj-22232	277	23	the	the	DET
brj-22232	277	24	rg	rg	NOUN
brj-22232	277	25	training	training	NOUN
brj-22232	277	26	models	model	NOUN
brj-22232	277	27	had	have	VERB
brj-22232	277	28	the	the	DET
brj-22232	277	29	highest	high	ADJ
brj-22232	277	30	confidence	confidence	NOUN
brj-22232	277	31	mean	mean	NOUN
brj-22232	277	32	value	value	NOUN
brj-22232	277	33	of	of	ADP
brj-22232	277	34	0.92	0.92	NUM
brj-22232	277	35	.	.	PUNCT
brj-22232	278	1	to	to	PART
brj-22232	278	2	further	far	ADV
brj-22232	278	3	verify	verify	VERB
brj-22232	278	4	the	the	DET
brj-22232	278	5	effect	effect	NOUN
brj-22232	278	6	of	of	ADP
brj-22232	278	7	various	various	ADJ
brj-22232	278	8	datasets	dataset	NOUN
brj-22232	278	9	,	,	PUNCT
brj-22232	278	10	images	image	NOUN
brj-22232	278	11	with	with	ADP
brj-22232	278	12	more	more	ADJ
brj-22232	278	13	complex	complex	ADJ
brj-22232	278	14	backgrounds	background	NOUN
brj-22232	278	15	and	and	CCONJ
brj-22232	278	16	hyperbolas	hyperbola	NOUN
brj-22232	278	17	with	with	ADP
brj-22232	278	18	crossover	crossover	NOUN
brj-22232	278	19	cases	case	NOUN
brj-22232	278	20	for	for	ADP
brj-22232	278	21	recognition	recognition	NOUN
brj-22232	278	22	were	be	AUX
brj-22232	278	23	selected	select	VERB
brj-22232	278	24	,	,	PUNCT
brj-22232	278	25	with	with	ADP
brj-22232	278	26	recognition	recognition	NOUN
brj-22232	278	27	confidence	confidence	NOUN
brj-22232	278	28	thresholds	threshold	NOUN
brj-22232	278	29	of	of	ADP
brj-22232	278	30	0.2	0.2	NUM
brj-22232	278	31	and	and	CCONJ
brj-22232	278	32	0.01	0.01	NUM
brj-22232	278	33	,	,	PUNCT
brj-22232	278	34	respectively	respectively	ADV
brj-22232	278	35	,	,	PUNCT
brj-22232	278	36	and	and	CCONJ
brj-22232	278	37	the	the	DET
brj-22232	278	38	recognition	recognition	NOUN
brj-22232	278	39	results	result	NOUN
brj-22232	278	40	are	be	AUX
brj-22232	278	41	shown	show	VERB
brj-22232	278	42	in	in	ADP
brj-22232	278	43	fig	fig	NOUN
brj-22232	278	44	.	.	PUNCT
brj-22232	278	45	12b	12b	NOUN
brj-22232	278	46	.	.	PUNCT
brj-22232	279	1	the	the	DET
brj-22232	279	2	recognition	recognition	NOUN
brj-22232	279	3	results	result	VERB
brj-22232	279	4	show	show	VERB
brj-22232	279	5	that	that	SCONJ
brj-22232	279	6	the	the	DET
brj-22232	279	7	rgs	rgs	PROPN
brj-22232	279	8	training	training	NOUN
brj-22232	279	9	model	model	NOUN
brj-22232	279	10	had	have	VERB
brj-22232	279	11	the	the	DET
brj-22232	279	12	best	good	ADJ
brj-22232	279	13	robustness	robustness	NOUN
brj-22232	279	14	and	and	CCONJ
brj-22232	279	15	good	good	ADJ
brj-22232	279	16	recognition	recognition	NOUN
brj-22232	279	17	effect	effect	NOUN
brj-22232	279	18	for	for	ADP
brj-22232	279	19	various	various	ADJ
brj-22232	279	20	pairs	pair	NOUN
brj-22232	279	21	of	of	ADP
brj-22232	279	22	hyperbolic	hyperbolic	ADJ
brj-22232	279	23	cases	case	NOUN
brj-22232	279	24	with	with	ADP
brj-22232	279	25	a	a	DET
brj-22232	279	26	high	high	ADJ
brj-22232	279	27	recall	recall	NOUN
brj-22232	279	28	rate	rate	NOUN
brj-22232	279	29	.	.	PUNCT
brj-22232	280	1	especially	especially	ADV
brj-22232	280	2	for	for	ADP
brj-22232	280	3	the	the	DET
brj-22232	280	4	hyperbolic	hyperbolic	ADJ
brj-22232	280	5	images	image	NOUN
brj-22232	280	6	with	with	ADP
brj-22232	280	7	a	a	DET
brj-22232	280	8	complex	complex	ADJ
brj-22232	280	9	background	background	NOUN
brj-22232	280	10	,	,	PUNCT
brj-22232	280	11	the	the	DET
brj-22232	280	12	recognition	recognition	NOUN
brj-22232	280	13	confidence	confidence	NOUN
brj-22232	280	14	of	of	ADP
brj-22232	280	15	the	the	DET
brj-22232	280	16	rgs	rgs	PROPN
brj-22232	280	17	training	training	NOUN
brj-22232	280	18	model	model	NOUN
brj-22232	280	19	still	still	ADV
brj-22232	280	20	reached	reach	VERB
brj-22232	280	21	0.65	0.65	NUM
brj-22232	280	22	,	,	PUNCT
brj-22232	280	23	while	while	SCONJ
brj-22232	280	24	the	the	DET
brj-22232	280	25	other	other	ADJ
brj-22232	280	26	dataset	dataset	NOUN
brj-22232	280	27	models	model	NOUN
brj-22232	280	28	can	can	AUX
brj-22232	280	29	barely	barely	ADV
brj-22232	280	30	recognize	recognize	VERB
brj-22232	280	31	the	the	DET
brj-22232	280	32	hyperbolas	hyperbola	NOUN
brj-22232	280	33	with	with	ADP
brj-22232	280	34	complex	complex	ADJ
brj-22232	280	35	backgrounds	background	NOUN
brj-22232	280	36	.	.	PUNCT
brj-22232	281	1	the	the	DET
brj-22232	281	2	r	r	NOUN
brj-22232	281	3	,	,	PUNCT
brj-22232	281	4	rs	rs	NOUN
brj-22232	281	5	,	,	PUNCT
brj-22232	281	6	and	and	CCONJ
brj-22232	281	7	rg	rg	PROPN
brj-22232	281	8	training	training	NOUN
brj-22232	281	9	models	model	NOUN
brj-22232	281	10	have	have	VERB
brj-22232	281	11	high	high	ADJ
brj-22232	281	12	confidence	confidence	NOUN
brj-22232	281	13	in	in	ADP
brj-22232	281	14	the	the	DET
brj-22232	281	15	recognition	recognition	NOUN
brj-22232	281	16	of	of	ADP
brj-22232	281	17	identifiable	identifiable	ADJ
brj-22232	281	18	curves	curve	NOUN
brj-22232	281	19	when	when	SCONJ
brj-22232	281	20	recognizing	recognize	VERB
brj-22232	281	21	the	the	DET
brj-22232	281	22	presence	presence	NOUN
brj-22232	281	23	of	of	ADP
brj-22232	281	24	crossed	cross	VERB
brj-22232	281	25	hyperbolas	hyperbola	NOUN
brj-22232	281	26	,	,	PUNCT
brj-22232	281	27	maintaining	maintain	VERB
brj-22232	281	28	approximately	approximately	ADV
brj-22232	281	29	0.9	0.9	NUM
brj-22232	281	30	with	with	ADP
brj-22232	281	31	a	a	DET
brj-22232	281	32	high	high	ADJ
brj-22232	281	33	accuracy	accuracy	NOUN
brj-22232	281	34	rate	rate	NOUN
brj-22232	281	35	,	,	PUNCT
brj-22232	281	36	but	but	CCONJ
brj-22232	281	37	half	half	NOUN
brj-22232	281	38	of	of	ADP
brj-22232	281	39	the	the	DET
brj-22232	281	40	hyperbolas	hyperbola	NOUN
brj-22232	281	41	were	be	AUX
brj-22232	281	42	not	not	PART
brj-22232	281	43	identified	identify	VERB
brj-22232	281	44	and	and	CCONJ
brj-22232	281	45	the	the	DET
brj-22232	281	46	recall	recall	NOUN
brj-22232	281	47	rate	rate	NOUN
brj-22232	281	48	was	be	AUX
brj-22232	281	49	low	low	ADJ
brj-22232	281	50	.	.	PUNCT
brj-22232	282	1	fig	fig	NOUN
brj-22232	282	2	.	.	PUNCT
brj-22232	283	1	13	13	NUM
brj-22232	283	2	.	.	PUNCT
brj-22232	284	1	detection	detection	NOUN
brj-22232	284	2	results	result	NOUN
brj-22232	284	3	of	of	ADP
brj-22232	284	4	four	four	NUM
brj-22232	284	5	methods	method	NOUN
brj-22232	284	6	for	for	ADP
brj-22232	284	7	two	two	NUM
brj-22232	284	8	datasets	dataset	NOUN
brj-22232	284	9	figure	figure	VERB
brj-22232	284	10	13	13	NUM
brj-22232	284	11	shows	show	VERB
brj-22232	284	12	the	the	DET
brj-22232	284	13	detection	detection	NOUN
brj-22232	284	14	results	result	NOUN
brj-22232	284	15	of	of	ADP
brj-22232	284	16	four	four	NUM
brj-22232	284	17	deep	deep	ADJ
brj-22232	284	18	learning	learning	NOUN
brj-22232	284	19	methods	method	NOUN
brj-22232	284	20	for	for	ADP
brj-22232	284	21	the	the	DET
brj-22232	284	22	rg	rg	PROPN
brj-22232	284	23	dataset	dataset	NOUN
brj-22232	284	24	and	and	CCONJ
brj-22232	284	25	the	the	DET
brj-22232	284	26	rgs	rgs	PROPN
brj-22232	284	27	dataset	dataset	NOUN
brj-22232	284	28	,	,	PUNCT
brj-22232	284	29	all	all	DET
brj-22232	284	30	eight	eight	NUM
brj-22232	284	31	models	model	NOUN
brj-22232	284	32	identified	identify	VERB
brj-22232	284	33	and	and	CCONJ
brj-22232	284	34	localized	localize	VERB
brj-22232	284	35	the	the	DET
brj-22232	284	36	three	three	NUM
brj-22232	284	37	hyperbolas	hyperbola	NOUN
brj-22232	284	38	,	,	PUNCT
brj-22232	284	39	but	but	CCONJ
brj-22232	284	40	there	there	PRON
brj-22232	284	41	were	be	VERB
brj-22232	284	42	large	large	ADJ
brj-22232	284	43	differences	difference	NOUN
brj-22232	284	44	in	in	ADP
brj-22232	284	45	confidence	confidence	NOUN
brj-22232	284	46	levels	level	NOUN
brj-22232	284	47	.	.	PUNCT
brj-22232	285	1	the	the	DET
brj-22232	285	2	centernet	centernet	NOUN
brj-22232	285	3	model	model	NOUN
brj-22232	285	4	had	have	VERB
brj-22232	285	5	a	a	DET
brj-22232	285	6	minimum	minimum	ADJ
brj-22232	285	7	confidence	confidence	NOUN
brj-22232	285	8	value	value	NOUN
brj-22232	285	9	of	of	ADP
brj-22232	285	10	0.5	0.5	NUM
brj-22232	285	11	,	,	PUNCT
brj-22232	285	12	while	while	SCONJ
brj-22232	285	13	in	in	ADP
brj-22232	285	14	the	the	DET
brj-22232	285	15	faster	fast	ADJ
brj-22232	285	16	r	r	NOUN
brj-22232	285	17	-	-	PUNCT
brj-22232	285	18	cnn	cnn	PROPN
brj-22232	285	19	,	,	PUNCT
brj-22232	285	20	the	the	DET
brj-22232	285	21	maximum	maximum	ADJ
brj-22232	285	22	value	value	NOUN
brj-22232	285	23	was	be	AUX
brj-22232	285	24	0.94	0.94	NUM
brj-22232	285	25	.	.	PUNCT
brj-22232	286	1	the	the	DET
brj-22232	286	2	yolov3	yolov3	PROPN
brj-22232	286	3	confidence	confidence	NOUN
brj-22232	286	4	value	value	NOUN
brj-22232	286	5	ranged	range	VERB
brj-22232	286	6	from	from	ADP
brj-22232	286	7	0.62	0.62	NUM
brj-22232	286	8	to	to	ADP
brj-22232	286	9	0.76	0.76	NUM
brj-22232	286	10	.	.	PUNCT
brj-22232	287	1	the	the	DET
brj-22232	287	2	yolov5	yolov5	NOUN
brj-22232	287	3	and	and	CCONJ
brj-22232	287	4	the	the	DET
brj-22232	287	5	faster	fast	ADJ
brj-22232	287	6	r	r	NOUN
brj-22232	287	7	-	-	PUNCT
brj-22232	287	8	cnn	cnn	PROPN
brj-22232	287	9	had	have	VERB
brj-22232	287	10	similar	similar	ADJ
brj-22232	287	11	results	result	NOUN
brj-22232	287	12	,	,	PUNCT
brj-22232	287	13	with	with	ADP
brj-22232	287	14	the	the	DET
brj-22232	287	15	mean	mean	ADJ
brj-22232	287	16	confidence	confidence	NOUN
brj-22232	287	17	values	value	NOUN
brj-22232	287	18	reaching	reach	VERB
brj-22232	287	19	0.9	0.9	NUM
brj-22232	287	20	or	or	CCONJ
brj-22232	287	21	higher	high	ADJ
brj-22232	287	22	,	,	PUNCT
brj-22232	287	23	and	and	CCONJ
brj-22232	287	24	yolov5	yolov5	NOUN
brj-22232	287	25	was	be	AUX
brj-22232	287	26	slightly	slightly	ADV
brj-22232	287	27	higher	high	ADJ
brj-22232	287	28	than	than	ADP
brj-22232	287	29	faster	fast	ADJ
brj-22232	287	30	r	r	NOUN
brj-22232	287	31	-	-	PUNCT
brj-22232	287	32	cnn	cnn	NOUN
brj-22232	287	33	.	.	PUNCT
brj-22232	288	1	the	the	DET
brj-22232	288	2	above	above	ADJ
brj-22232	288	3	results	result	NOUN
brj-22232	288	4	show	show	VERB
brj-22232	288	5	that	that	SCONJ
brj-22232	288	6	yolov5	yolov5	NOUN
brj-22232	288	7	model	model	NOUN
brj-22232	288	8	detection	detection	NOUN
brj-22232	288	9	recognition	recognition	NOUN
brj-22232	288	10	performance	performance	NOUN
brj-22232	288	11	using	use	VERB
brj-22232	288	12	the	the	DET
brj-22232	288	13	enhanced	enhanced	ADJ
brj-22232	288	14	dataset	dataset	NOUN
brj-22232	288	15	is	be	AUX
brj-22232	288	16	the	the	DET
brj-22232	288	17	best	good	ADJ
brj-22232	288	18	.	.	PUNCT
brj-22232	289	1	peer	peer	NOUN
brj-22232	289	2	-	-	PUNCT
brj-22232	289	3	reviewed	review	VERB
brj-22232	289	4	article	article	NOUN
brj-22232	289	5	bioresources.com	bioresources.com	X
brj-22232	289	6	li	li	PROPN
brj-22232	289	7	et	et	PROPN
brj-22232	289	8	al	al	PROPN
brj-22232	289	9	.	.	PROPN
brj-22232	289	10	(	(	PUNCT
brj-22232	289	11	2023	2023	NUM
brj-22232	289	12	)	)	PUNCT
brj-22232	289	13	.	.	PUNCT
brj-22232	290	1	“	"	PUNCT
brj-22232	290	2	tree	tree	NOUN
brj-22232	290	3	root	root	NOUN
brj-22232	290	4	detection	detection	NOUN
brj-22232	290	5	training	training	NOUN
brj-22232	290	6	,	,	PUNCT
brj-22232	290	7	”	"	PUNCT
brj-22232	290	8	bioresources	bioresource	NOUN
brj-22232	290	9	18(1	18(1	NOUN
brj-22232	290	10	)	)	PUNCT
brj-22232	290	11	,	,	PUNCT
brj-22232	290	12	484	484	NUM
brj-22232	290	13	-	-	SYM
brj-22232	290	14	504	504	NUM
brj-22232	290	15	.	.	PUNCT
brj-22232	290	16	501	501	NUM
brj-22232	290	17	conclusions	conclusion	NOUN
brj-22232	290	18	1	1	NUM
brj-22232	290	19	.	.	PUNCT
brj-22232	290	20	based	base	VERB
brj-22232	290	21	on	on	ADP
brj-22232	290	22	the	the	DET
brj-22232	290	23	deep	deep	ADJ
brj-22232	290	24	learning	learning	NOUN
brj-22232	290	25	method	method	NOUN
brj-22232	290	26	to	to	PART
brj-22232	290	27	achieve	achieve	VERB
brj-22232	290	28	automatic	automatic	ADJ
brj-22232	290	29	recognition	recognition	NOUN
brj-22232	290	30	and	and	CCONJ
brj-22232	290	31	localization	localization	NOUN
brj-22232	290	32	of	of	ADP
brj-22232	290	33	hyperbolas	hyperbola	NOUN
brj-22232	290	34	,	,	PUNCT
brj-22232	290	35	the	the	DET
brj-22232	290	36	yolov5	yolov5	NOUN
brj-22232	290	37	model	model	NOUN
brj-22232	290	38	had	have	VERB
brj-22232	290	39	the	the	DET
brj-22232	290	40	best	good	ADJ
brj-22232	290	41	detection	detection	NOUN
brj-22232	290	42	results	result	NOUN
brj-22232	290	43	compared	compare	VERB
brj-22232	290	44	to	to	ADP
brj-22232	290	45	yolov3	yolov3	PROPN
brj-22232	290	46	,	,	PUNCT
brj-22232	290	47	faster	fast	ADJ
brj-22232	290	48	r	r	NOUN
brj-22232	290	49	-	-	PUNCT
brj-22232	290	50	cnn	cnn	PROPN
brj-22232	290	51	,	,	PUNCT
brj-22232	290	52	and	and	CCONJ
brj-22232	290	53	centernet	centernet	NOUN
brj-22232	290	54	.	.	PUNCT
brj-22232	291	1	the	the	DET
brj-22232	291	2	average	average	ADJ
brj-22232	291	3	accuracy	accuracy	NOUN
brj-22232	291	4	of	of	ADP
brj-22232	291	5	the	the	DET
brj-22232	291	6	models	model	NOUN
brj-22232	291	7	all	all	PRON
brj-22232	291	8	amounted	amount	VERB
brj-22232	291	9	more	more	ADJ
brj-22232	291	10	than	than	ADP
brj-22232	291	11	80	80	NUM
brj-22232	291	12	%	%	NOUN
brj-22232	291	13	,	,	PUNCT
brj-22232	291	14	and	and	CCONJ
brj-22232	291	15	the	the	DET
brj-22232	291	16	recognition	recognition	NOUN
brj-22232	291	17	rate	rate	NOUN
brj-22232	291	18	and	and	CCONJ
brj-22232	291	19	recall	recall	NOUN
brj-22232	291	20	rate	rate	NOUN
brj-22232	291	21	of	of	ADP
brj-22232	291	22	the	the	DET
brj-22232	291	23	yolov5	yolov5	NOUN
brj-22232	291	24	training	training	NOUN
brj-22232	291	25	model	model	NOUN
brj-22232	291	26	reached	reach	VERB
brj-22232	291	27	84.45	84.45	NUM
brj-22232	291	28	%	%	NOUN
brj-22232	291	29	and	and	CCONJ
brj-22232	291	30	81.23	81.23	NUM
brj-22232	291	31	%	%	NOUN
brj-22232	291	32	,	,	PUNCT
brj-22232	291	33	respectively	respectively	ADV
brj-22232	291	34	,	,	PUNCT
brj-22232	291	35	and	and	CCONJ
brj-22232	291	36	the	the	DET
brj-22232	291	37	target	target	NOUN
brj-22232	291	38	hyperbolas	hyperbola	NOUN
brj-22232	291	39	had	have	VERB
brj-22232	291	40	strong	strong	ADJ
brj-22232	291	41	detection	detection	NOUN
brj-22232	291	42	for	for	ADP
brj-22232	291	43	different	different	ADJ
brj-22232	291	44	detection	detection	NOUN
brj-22232	291	45	tasks	task	NOUN
brj-22232	291	46	and	and	CCONJ
brj-22232	291	47	recognition	recognition	NOUN
brj-22232	291	48	capability	capability	NOUN
brj-22232	291	49	for	for	ADP
brj-22232	291	50	different	different	ADJ
brj-22232	291	51	detection	detection	NOUN
brj-22232	291	52	tasks	task	NOUN
brj-22232	291	53	.	.	PUNCT
brj-22232	292	1	2	2	X
brj-22232	292	2	.	.	X
brj-22232	292	3	the	the	DET
brj-22232	292	4	real	real	ADJ
brj-22232	292	5	dataset	dataset	NOUN
brj-22232	292	6	was	be	AUX
brj-22232	292	7	enhanced	enhance	VERB
brj-22232	292	8	by	by	ADP
brj-22232	292	9	cyclegan	cyclegan	NOUN
brj-22232	292	10	,	,	PUNCT
brj-22232	292	11	and	and	CCONJ
brj-22232	292	12	the	the	DET
brj-22232	292	13	enhanced	enhance	VERB
brj-22232	292	14	image	image	NOUN
brj-22232	292	15	had	have	VERB
brj-22232	292	16	high	high	ADJ
brj-22232	292	17	similarity	similarity	NOUN
brj-22232	292	18	with	with	ADP
brj-22232	292	19	the	the	DET
brj-22232	292	20	real	real	ADJ
brj-22232	292	21	images	image	NOUN
brj-22232	292	22	.	.	PUNCT
brj-22232	293	1	in	in	ADP
brj-22232	293	2	addition	addition	NOUN
brj-22232	293	3	,	,	PUNCT
brj-22232	293	4	the	the	DET
brj-22232	293	5	hyperbolic	hyperbolic	ADJ
brj-22232	293	6	features	feature	NOUN
brj-22232	293	7	were	be	AUX
brj-22232	293	8	kept	keep	VERB
brj-22232	293	9	intact	intact	ADJ
brj-22232	293	10	.	.	PUNCT
brj-22232	294	1	at	at	ADP
brj-22232	294	2	the	the	DET
brj-22232	294	3	same	same	ADJ
brj-22232	294	4	time	time	NOUN
brj-22232	294	5	,	,	PUNCT
brj-22232	294	6	the	the	DET
brj-22232	294	7	background	background	NOUN
brj-22232	294	8	and	and	CCONJ
brj-22232	294	9	noise	noise	NOUN
brj-22232	294	10	of	of	ADP
brj-22232	294	11	the	the	DET
brj-22232	294	12	real	real	ADJ
brj-22232	294	13	images	image	NOUN
brj-22232	294	14	could	could	AUX
brj-22232	294	15	be	be	AUX
brj-22232	294	16	removed	remove	VERB
brj-22232	294	17	.	.	PUNCT
brj-22232	295	1	the	the	DET
brj-22232	295	2	removed	remove	VERB
brj-22232	295	3	image	image	NOUN
brj-22232	295	4	was	be	AUX
brj-22232	295	5	similar	similar	ADJ
brj-22232	295	6	to	to	ADP
brj-22232	295	7	the	the	DET
brj-22232	295	8	simulation	simulation	NOUN
brj-22232	295	9	image	image	NOUN
brj-22232	295	10	,	,	PUNCT
brj-22232	295	11	and	and	CCONJ
brj-22232	295	12	only	only	ADV
brj-22232	295	13	a	a	DET
brj-22232	295	14	few	few	ADJ
brj-22232	295	15	hyperbolic	hyperbolic	ADJ
brj-22232	295	16	features	feature	NOUN
brj-22232	295	17	were	be	AUX
brj-22232	295	18	lost	lose	VERB
brj-22232	295	19	,	,	PUNCT
brj-22232	295	20	resulting	result	VERB
brj-22232	295	21	in	in	ADP
brj-22232	295	22	a	a	DET
brj-22232	295	23	good	good	ADJ
brj-22232	295	24	overall	overall	ADJ
brj-22232	295	25	effect	effect	NOUN
brj-22232	295	26	for	for	ADP
brj-22232	295	27	the	the	DET
brj-22232	295	28	next	next	ADJ
brj-22232	295	29	step	step	NOUN
brj-22232	295	30	of	of	ADP
brj-22232	295	31	the	the	DET
brj-22232	295	32	study	study	NOUN
brj-22232	295	33	.	.	PUNCT
brj-22232	296	1	3	3	X
brj-22232	296	2	.	.	PUNCT
brj-22232	296	3	compared	compare	VERB
brj-22232	296	4	with	with	ADP
brj-22232	296	5	the	the	DET
brj-22232	296	6	traditional	traditional	ADJ
brj-22232	296	7	rs	rs	NOUN
brj-22232	296	8	dataset	dataset	NOUN
brj-22232	296	9	,	,	PUNCT
brj-22232	296	10	the	the	DET
brj-22232	296	11	rgs	rgs	PROPN
brj-22232	296	12	dataset	dataset	VERB
brj-22232	296	13	and	and	CCONJ
brj-22232	296	14	the	the	DET
brj-22232	296	15	rg	rg	PROPN
brj-22232	296	16	dataset	dataset	PROPN
brj-22232	296	17	train	train	VERB
brj-22232	296	18	the	the	DET
brj-22232	296	19	model	model	NOUN
brj-22232	296	20	better	well	ADV
brj-22232	296	21	,	,	PUNCT
brj-22232	296	22	the	the	DET
brj-22232	296	23	loss	loss	NOUN
brj-22232	296	24	and	and	CCONJ
brj-22232	296	25	map	map	NOUN
brj-22232	296	26	of	of	ADP
brj-22232	296	27	the	the	DET
brj-22232	296	28	training	training	NOUN
brj-22232	296	29	process	process	NOUN
brj-22232	296	30	were	be	AUX
brj-22232	296	31	higher	high	ADJ
brj-22232	296	32	than	than	ADP
brj-22232	296	33	in	in	ADP
brj-22232	296	34	other	other	ADJ
brj-22232	296	35	datasets	dataset	NOUN
brj-22232	296	36	,	,	PUNCT
brj-22232	296	37	and	and	CCONJ
brj-22232	296	38	the	the	DET
brj-22232	296	39	actual	actual	ADJ
brj-22232	296	40	detection	detection	NOUN
brj-22232	296	41	effect	effect	NOUN
brj-22232	296	42	was	be	AUX
brj-22232	296	43	the	the	DET
brj-22232	296	44	best	good	ADJ
brj-22232	296	45	,	,	PUNCT
brj-22232	296	46	with	with	ADP
brj-22232	296	47	the	the	DET
brj-22232	296	48	highest	high	ADJ
brj-22232	296	49	confidence	confidence	NOUN
brj-22232	296	50	of	of	ADP
brj-22232	296	51	detecting	detect	VERB
brj-22232	296	52	hyperbola	hyperbola	PROPN
brj-22232	296	53	.	.	PUNCT
brj-22232	297	1	4	4	X
brj-22232	297	2	.	.	X
brj-22232	297	3	when	when	SCONJ
brj-22232	297	4	constructing	construct	VERB
brj-22232	297	5	the	the	DET
brj-22232	297	6	gpr	gpr	PROPN
brj-22232	297	7	b	b	PROPN
brj-22232	297	8	-	-	PUNCT
brj-22232	297	9	scan	scan	ADJ
brj-22232	297	10	training	training	NOUN
brj-22232	297	11	dataset	dataset	NOUN
brj-22232	297	12	,	,	PUNCT
brj-22232	297	13	there	there	PRON
brj-22232	297	14	must	must	AUX
brj-22232	297	15	be	be	AUX
brj-22232	297	16	a	a	DET
brj-22232	297	17	large	large	ADJ
brj-22232	297	18	amount	amount	NOUN
brj-22232	297	19	of	of	ADP
brj-22232	297	20	real	real	ADJ
brj-22232	297	21	data	datum	NOUN
brj-22232	297	22	,	,	PUNCT
brj-22232	297	23	and	and	CCONJ
brj-22232	297	24	less	less	ADV
brj-22232	297	25	real	real	ADJ
brj-22232	297	26	data	datum	NOUN
brj-22232	297	27	would	would	AUX
brj-22232	297	28	lead	lead	VERB
brj-22232	297	29	to	to	ADP
brj-22232	297	30	poor	poor	ADJ
brj-22232	297	31	actual	actual	ADJ
brj-22232	297	32	results	result	NOUN
brj-22232	297	33	;	;	PUNCT
brj-22232	297	34	generating	generate	VERB
brj-22232	297	35	b	b	X
brj-22232	297	36	-	-	PUNCT
brj-22232	297	37	scan	scan	ADJ
brj-22232	297	38	data	datum	NOUN
brj-22232	297	39	had	have	VERB
brj-22232	297	40	similar	similar	ADJ
brj-22232	297	41	background	background	NOUN
brj-22232	297	42	and	and	CCONJ
brj-22232	297	43	noise	noise	NOUN
brj-22232	297	44	and	and	CCONJ
brj-22232	297	45	hyperbolic	hyperbolic	ADJ
brj-22232	297	46	features	feature	NOUN
brj-22232	297	47	as	as	ADP
brj-22232	297	48	the	the	DET
brj-22232	297	49	real	real	ADJ
brj-22232	297	50	data	datum	NOUN
brj-22232	297	51	,	,	PUNCT
brj-22232	297	52	and	and	CCONJ
brj-22232	297	53	the	the	DET
brj-22232	297	54	expansion	expansion	NOUN
brj-22232	297	55	of	of	ADP
brj-22232	297	56	the	the	DET
brj-22232	297	57	real	real	ADJ
brj-22232	297	58	dataset	dataset	NOUN
brj-22232	297	59	,	,	PUNCT
brj-22232	297	60	while	while	SCONJ
brj-22232	297	61	being	be	AUX
brj-22232	297	62	able	able	ADJ
brj-22232	297	63	to	to	PART
brj-22232	297	64	improve	improve	VERB
brj-22232	297	65	the	the	DET
brj-22232	297	66	effectiveness	effectiveness	NOUN
brj-22232	297	67	of	of	ADP
brj-22232	297	68	the	the	DET
brj-22232	297	69	training	training	NOUN
brj-22232	297	70	model	model	NOUN
brj-22232	297	71	,	,	PUNCT
brj-22232	297	72	the	the	DET
brj-22232	297	73	map	map	NOUN
brj-22232	297	74	improvement	improvement	NOUN
brj-22232	297	75	reached	reach	VERB
brj-22232	297	76	more	more	ADJ
brj-22232	297	77	than	than	ADP
brj-22232	297	78	3	3	NUM
brj-22232	297	79	%	%	NOUN
brj-22232	297	80	.	.	PUNCT
brj-22232	298	1	5	5	X
brj-22232	298	2	.	.	X
brj-22232	298	3	the	the	DET
brj-22232	298	4	extracted	extract	VERB
brj-22232	298	5	method	method	NOUN
brj-22232	298	6	was	be	AUX
brj-22232	298	7	applied	apply	VERB
brj-22232	298	8	to	to	ADP
brj-22232	298	9	the	the	DET
brj-22232	298	10	web	web	NOUN
brj-22232	298	11	-	-	PUNCT
brj-22232	298	12	based	base	VERB
brj-22232	298	13	management	management	NOUN
brj-22232	298	14	information	information	NOUN
brj-22232	298	15	system	system	NOUN
brj-22232	298	16	,	,	PUNCT
brj-22232	298	17	simplifying	simplify	VERB
brj-22232	298	18	the	the	DET
brj-22232	298	19	operation	operation	NOUN
brj-22232	298	20	process	process	NOUN
brj-22232	298	21	and	and	CCONJ
brj-22232	298	22	making	make	VERB
brj-22232	298	23	the	the	DET
brj-22232	298	24	processing	processing	NOUN
brj-22232	298	25	results	result	NOUN
brj-22232	298	26	easy	easy	ADJ
brj-22232	298	27	to	to	PART
brj-22232	298	28	observe	observe	VERB
brj-22232	298	29	.	.	PUNCT
brj-22232	299	1	6	6	X
brj-22232	299	2	.	.	X
brj-22232	299	3	by	by	ADP
brj-22232	299	4	the	the	DET
brj-22232	299	5	method	method	NOUN
brj-22232	299	6	in	in	ADP
brj-22232	299	7	this	this	DET
brj-22232	299	8	paper	paper	NOUN
brj-22232	299	9	,	,	PUNCT
brj-22232	299	10	the	the	DET
brj-22232	299	11	user	user	NOUN
brj-22232	299	12	can	can	AUX
brj-22232	299	13	clearly	clearly	ADV
brj-22232	299	14	observe	observe	VERB
brj-22232	299	15	the	the	DET
brj-22232	299	16	number	number	NOUN
brj-22232	299	17	of	of	ADP
brj-22232	299	18	roots	root	NOUN
brj-22232	299	19	,	,	PUNCT
brj-22232	299	20	root	root	NOUN
brj-22232	299	21	density	density	NOUN
brj-22232	299	22	,	,	PUNCT
brj-22232	299	23	and	and	CCONJ
brj-22232	299	24	root	root	NOUN
brj-22232	299	25	distribution	distribution	NOUN
brj-22232	299	26	,	,	PUNCT
brj-22232	299	27	which	which	PRON
brj-22232	299	28	is	be	AUX
brj-22232	299	29	useful	useful	ADJ
brj-22232	299	30	for	for	ADP
brj-22232	299	31	predicting	predict	VERB
brj-22232	299	32	root	root	NOUN
brj-22232	299	33	diameter	diameter	NOUN
brj-22232	299	34	and	and	CCONJ
brj-22232	299	35	other	other	ADJ
brj-22232	299	36	information	information	NOUN
brj-22232	299	37	.	.	PUNCT
brj-22232	300	1	in	in	ADP
brj-22232	300	2	the	the	DET
brj-22232	300	3	future	future	NOUN
brj-22232	300	4	,	,	PUNCT
brj-22232	300	5	such	such	ADJ
brj-22232	300	6	information	information	NOUN
brj-22232	300	7	can	can	AUX
brj-22232	300	8	be	be	AUX
brj-22232	300	9	used	use	VERB
brj-22232	300	10	for	for	ADP
brj-22232	300	11	assessment	assessment	NOUN
brj-22232	300	12	of	of	ADP
brj-22232	300	13	tree	tree	NOUN
brj-22232	300	14	growth	growth	NOUN
brj-22232	300	15	and	and	CCONJ
brj-22232	300	16	health	health	NOUN
brj-22232	300	17	.	.	PUNCT
brj-22232	301	1	acknowledgements	acknowledgement	NOUN
brj-22232	301	2	this	this	DET
brj-22232	301	3	study	study	NOUN
brj-22232	301	4	was	be	AUX
brj-22232	301	5	supported	support	VERB
brj-22232	301	6	by	by	ADP
brj-22232	301	7	the	the	DET
brj-22232	301	8	national	national	ADJ
brj-22232	301	9	natural	natural	PROPN
brj-22232	301	10	science	science	PROPN
brj-22232	301	11	foundation	foundation	PROPN
brj-22232	301	12	of	of	ADP
brj-22232	301	13	china	china	PROPN
brj-22232	301	14	(	(	PUNCT
brj-22232	301	15	grant	grant	VERB
brj-22232	301	16	no	no	NOUN
brj-22232	301	17	.	.	NOUN
brj-22232	301	18	32071679	32071679	NUM
brj-22232	301	19	)	)	PUNCT
brj-22232	301	20	and	and	CCONJ
brj-22232	301	21	the	the	DET
brj-22232	301	22	beijing	beijing	PROPN
brj-22232	301	23	municipal	municipal	ADJ
brj-22232	301	24	natural	natural	PROPN
brj-22232	301	25	science	science	PROPN
brj-22232	301	26	foundation	foundation	NOUN
brj-22232	301	27	(	(	PUNCT
brj-22232	301	28	grant	grant	VERB
brj-22232	301	29	no	no	NOUN
brj-22232	301	30	.	.	NOUN
brj-22232	301	31	6202023	6202023	NUM
brj-22232	301	32	)	)	PUNCT
brj-22232	301	33	.	.	PUNCT
brj-22232	302	1	references	reference	NOUN
brj-22232	302	2	cited	cite	VERB
brj-22232	302	3	aboudourib	aboudourib	PROPN
brj-22232	302	4	,	,	PUNCT
brj-22232	302	5	a.	a.	PROPN
brj-22232	302	6	,	,	PUNCT
brj-22232	302	7	serhir	serhir	NOUN
brj-22232	302	8	,	,	PUNCT
brj-22232	302	9	m.	m.	NOUN
brj-22232	302	10	,	,	PUNCT
brj-22232	302	11	and	and	CCONJ
brj-22232	302	12	lesselier	lesselier	NOUN
brj-22232	302	13	,	,	PUNCT
brj-22232	302	14	d.	d.	PROPN
brj-22232	302	15	(	(	PUNCT
brj-22232	302	16	2021	2021	NUM
brj-22232	302	17	)	)	PUNCT
brj-22232	302	18	.	.	PUNCT
brj-22232	303	1	“	"	PUNCT
brj-22232	303	2	a	a	DET
brj-22232	303	3	processing	processing	NOUN
brj-22232	303	4	framework	framework	NOUN
brj-22232	303	5	for	for	ADP
brj-22232	303	6	treeroot	treeroot	NOUN
brj-22232	303	7	reconstruction	reconstruction	NOUN
brj-22232	303	8	using	use	VERB
brj-22232	303	9	ground	ground	NOUN
brj-22232	303	10	-	-	PUNCT
brj-22232	303	11	penetrating	penetrate	VERB
brj-22232	303	12	radar	radar	NOUN
brj-22232	303	13	under	under	ADP
brj-22232	303	14	heterogeneous	heterogeneous	ADJ
brj-22232	303	15	soil	soil	NOUN
brj-22232	303	16	conditions	condition	NOUN
brj-22232	303	17	,	,	PUNCT
brj-22232	303	18	”	"	PUNCT
brj-22232	303	19	ieee	ieee	NOUN
brj-22232	303	20	transactions	transaction	NOUN
brj-22232	303	21	on	on	ADP
brj-22232	303	22	geoscience	geoscience	NOUN
brj-22232	303	23	and	and	CCONJ
brj-22232	303	24	remote	remote	ADJ
brj-22232	303	25	sensing	sense	VERB
brj-22232	303	26	59(1	59(1	NUM
brj-22232	303	27	)	)	PUNCT
brj-22232	303	28	,	,	PUNCT
brj-22232	303	29	208	208	NUM
brj-22232	303	30	-	-	SYM
brj-22232	303	31	219	219	NUM
brj-22232	303	32	.	.	PUNCT
brj-22232	304	1	doi	doi	NOUN
brj-22232	304	2	:	:	PUNCT
brj-22232	304	3	10.1109	10.1109	NUM
brj-22232	304	4	/	/	SYM
brj-22232	304	5	tgrs.2020.2993719	tgrs.2020.2993719	NOUN
brj-22232	304	6	peer	peer	NOUN
brj-22232	304	7	-	-	PUNCT
brj-22232	304	8	reviewed	review	VERB
brj-22232	304	9	article	article	NOUN
brj-22232	304	10	bioresources.com	bioresources.com	X
brj-22232	304	11	li	li	PROPN
brj-22232	304	12	et	et	PROPN
brj-22232	304	13	al	al	PROPN
brj-22232	304	14	.	.	PROPN
brj-22232	304	15	(	(	PUNCT
brj-22232	304	16	2023	2023	NUM
brj-22232	304	17	)	)	PUNCT
brj-22232	304	18	.	.	PUNCT
brj-22232	305	1	“	"	PUNCT
brj-22232	305	2	tree	tree	NOUN
brj-22232	305	3	root	root	NOUN
brj-22232	305	4	detection	detection	NOUN
brj-22232	305	5	training	training	NOUN
brj-22232	305	6	,	,	PUNCT
brj-22232	305	7	”	"	PUNCT
brj-22232	305	8	bioresources	bioresource	NOUN
brj-22232	305	9	18(1	18(1	NOUN
brj-22232	305	10	)	)	PUNCT
brj-22232	305	11	,	,	PUNCT
brj-22232	305	12	484	484	NUM
brj-22232	305	13	-	-	SYM
brj-22232	305	14	504	504	NUM
brj-22232	305	15	.	.	PUNCT
brj-22232	306	1	502	502	NUM
brj-22232	306	2	alani	alani	NOUN
brj-22232	306	3	,	,	PUNCT
brj-22232	306	4	a.	a.	NOUN
brj-22232	306	5	m.	m.	NOUN
brj-22232	306	6	,	,	PUNCT
brj-22232	306	7	ciampoli	ciampoli	PROPN
brj-22232	306	8	,	,	PUNCT
brj-22232	306	9	l.	l.	PROPN
brj-22232	306	10	b.	b.	PROPN
brj-22232	306	11	,	,	PUNCT
brj-22232	306	12	lantini	lantini	PROPN
brj-22232	306	13	,	,	PUNCT
brj-22232	306	14	l.	l.	PROPN
brj-22232	306	15	,	,	PUNCT
brj-22232	306	16	tosti	tosti	PROPN
brj-22232	306	17	,	,	PUNCT
brj-22232	306	18	f.	f.	PROPN
brj-22232	306	19	,	,	PUNCT
brj-22232	306	20	and	and	CCONJ
brj-22232	306	21	benedetto	benedetto	PROPN
brj-22232	306	22	,	,	PUNCT
brj-22232	306	23	a.	a.	NOUN
brj-22232	306	24	(	(	PUNCT
brj-22232	306	25	2018	2018	NUM
brj-22232	306	26	)	)	PUNCT
brj-22232	306	27	.	.	PUNCT
brj-22232	307	1	“	"	PUNCT
brj-22232	307	2	mapping	map	VERB
brj-22232	307	3	the	the	DET
brj-22232	307	4	root	root	NOUN
brj-22232	307	5	system	system	NOUN
brj-22232	307	6	of	of	ADP
brj-22232	307	7	matured	mature	VERB
brj-22232	307	8	trees	tree	NOUN
brj-22232	307	9	using	use	VERB
brj-22232	307	10	ground	ground	NOUN
brj-22232	307	11	penetrating	penetrate	VERB
brj-22232	307	12	radar	radar	NOUN
brj-22232	307	13	,	,	PUNCT
brj-22232	307	14	”	"	PUNCT
brj-22232	307	15	in	in	ADP
brj-22232	307	16	:	:	PUNCT
brj-22232	307	17	17th	17th	ADJ
brj-22232	307	18	international	international	ADJ
brj-22232	307	19	conference	conference	NOUN
brj-22232	307	20	on	on	ADP
brj-22232	307	21	ground	ground	NOUN
brj-22232	307	22	penetrating	penetrate	VERB
brj-22232	307	23	radar	radar	NOUN
brj-22232	307	24	(	(	PUNCT
brj-22232	307	25	gpr	gpr	PROPN
brj-22232	307	26	)	)	PUNCT
brj-22232	307	27	,	,	PUNCT
brj-22232	307	28	ieee	ieee	NOUN
brj-22232	307	29	,	,	PUNCT
brj-22232	307	30	rapperswil	rapperswil	PROPN
brj-22232	307	31	,	,	PUNCT
brj-22232	307	32	switzerland	switzerland	PROPN
brj-22232	307	33	,	,	PUNCT
brj-22232	307	34	pp	pp	ADJ
brj-22232	307	35	.	.	PUNCT
brj-22232	308	1	1	1	NUM
brj-22232	308	2	-	-	SYM
brj-22232	308	3	6	6	NUM
brj-22232	308	4	.	.	PUNCT
brj-22232	308	5	doi	doi	NOUN
brj-22232	308	6	:	:	PUNCT
brj-22232	308	7	10.1109	10.1109	NUM
brj-22232	308	8	/	/	SYM
brj-22232	308	9	icgpr.2018.8441535	icgpr.2018.8441535	ADJ
brj-22232	308	10	attia	attia	NOUN
brj-22232	308	11	al	al	PROPN
brj-22232	308	12	hagrey	hagrey	PROPN
brj-22232	308	13	,	,	PUNCT
brj-22232	308	14	s.	s.	PROPN
brj-22232	308	15	(	(	PUNCT
brj-22232	308	16	2007	2007	NUM
brj-22232	308	17	)	)	PUNCT
brj-22232	308	18	.	.	PUNCT
brj-22232	309	1	“	"	PUNCT
brj-22232	309	2	geophysical	geophysical	ADJ
brj-22232	309	3	imaging	imaging	NOUN
brj-22232	309	4	of	of	ADP
brj-22232	309	5	root	root	NOUN
brj-22232	309	6	-	-	PUNCT
brj-22232	309	7	zone	zone	NOUN
brj-22232	309	8	,	,	PUNCT
brj-22232	309	9	trunk	trunk	NOUN
brj-22232	309	10	,	,	PUNCT
brj-22232	309	11	and	and	CCONJ
brj-22232	309	12	moisture	moisture	NOUN
brj-22232	309	13	heterogeneity	heterogeneity	NOUN
brj-22232	309	14	,	,	PUNCT
brj-22232	309	15	”	"	PUNCT
brj-22232	309	16	journal	journal	NOUN
brj-22232	309	17	of	of	ADP
brj-22232	309	18	experimental	experimental	ADJ
brj-22232	309	19	botany	botany	NOUN
brj-22232	309	20	58(4	58(4	NUM
brj-22232	309	21	)	)	PUNCT
brj-22232	309	22	,	,	PUNCT
brj-22232	309	23	839	839	NUM
brj-22232	309	24	-	-	SYM
brj-22232	309	25	854	854	NUM
brj-22232	309	26	.	.	PUNCT
brj-22232	309	27	doi	doi	NOUN
brj-22232	309	28	:	:	PUNCT
brj-22232	309	29	10.1093	10.1093	NUM
brj-22232	309	30	/	/	SYM
brj-22232	309	31	jxb	jxb	PROPN
brj-22232	309	32	/	/	SYM
brj-22232	309	33	erl237	erl237	PROPN
brj-22232	309	34	danjon	danjon	PROPN
brj-22232	309	35	,	,	PUNCT
brj-22232	309	36	f.	f.	PROPN
brj-22232	309	37	,	,	PUNCT
brj-22232	309	38	and	and	CCONJ
brj-22232	309	39	reubens	reuben	NOUN
brj-22232	309	40	,	,	PUNCT
brj-22232	309	41	b.	b.	PROPN
brj-22232	309	42	(	(	PUNCT
brj-22232	309	43	2008	2008	NUM
brj-22232	309	44	)	)	PUNCT
brj-22232	309	45	.	.	PUNCT
brj-22232	310	1	“	"	PUNCT
brj-22232	310	2	assessing	assess	VERB
brj-22232	310	3	and	and	CCONJ
brj-22232	310	4	analyzing	analyze	VERB
brj-22232	310	5	3d	3d	NUM
brj-22232	310	6	architecture	architecture	NOUN
brj-22232	310	7	of	of	ADP
brj-22232	310	8	woody	woody	NOUN
brj-22232	310	9	root	root	NOUN
brj-22232	310	10	systems	system	NOUN
brj-22232	310	11	,	,	PUNCT
brj-22232	310	12	a	a	DET
brj-22232	310	13	review	review	NOUN
brj-22232	310	14	of	of	ADP
brj-22232	310	15	methods	method	NOUN
brj-22232	310	16	and	and	CCONJ
brj-22232	310	17	applications	application	NOUN
brj-22232	310	18	in	in	ADP
brj-22232	310	19	tree	tree	NOUN
brj-22232	310	20	and	and	CCONJ
brj-22232	310	21	soil	soil	NOUN
brj-22232	310	22	stability	stability	NOUN
brj-22232	310	23	,	,	PUNCT
brj-22232	310	24	resource	resource	NOUN
brj-22232	310	25	acquisition	acquisition	NOUN
brj-22232	310	26	and	and	CCONJ
brj-22232	310	27	allocation	allocation	NOUN
brj-22232	310	28	,	,	PUNCT
brj-22232	310	29	”	"	PUNCT
brj-22232	310	30	plant	plant	NOUN
brj-22232	310	31	and	and	CCONJ
brj-22232	310	32	soil	soil	NOUN
brj-22232	310	33	303(1–2	303(1–2	NUM
brj-22232	310	34	)	)	PUNCT
brj-22232	310	35	,	,	PUNCT
brj-22232	310	36	1	1	NUM
brj-22232	310	37	-	-	SYM
brj-22232	310	38	34	34	NUM
brj-22232	310	39	.	.	PUNCT
brj-22232	311	1	doi	doi	NOUN
brj-22232	311	2	:	:	PUNCT
brj-22232	311	3	10.1007	10.1007	NUM
brj-22232	311	4	/	/	SYM
brj-22232	311	5	s11104007	s11104007	NOUN
brj-22232	311	6	-	-	PUNCT
brj-22232	311	7	9470	9470	NUM
brj-22232	311	8	-	-	SYM
brj-22232	311	9	7	7	NUM
brj-22232	311	10	davletshin	davletshin	PROPN
brj-22232	311	11	,	,	PUNCT
brj-22232	311	12	a.	a.	PROPN
brj-22232	311	13	,	,	PUNCT
brj-22232	311	14	ko	ko	PROPN
brj-22232	311	15	,	,	PUNCT
brj-22232	311	16	l.	l.	PROPN
brj-22232	311	17	t.	t.	PROPN
brj-22232	311	18	,	,	PUNCT
brj-22232	311	19	milliken	milliken	PROPN
brj-22232	311	20	,	,	PUNCT
brj-22232	311	21	k.	k.	PROPN
brj-22232	311	22	,	,	PUNCT
brj-22232	311	23	periwal	periwal	PROPN
brj-22232	311	24	,	,	PUNCT
brj-22232	311	25	p.	p.	PROPN
brj-22232	311	26	,	,	PUNCT
brj-22232	311	27	wang	wang	PROPN
brj-22232	311	28	,	,	PUNCT
brj-22232	311	29	c.-c	c.-c	PROPN
brj-22232	311	30	.	.	PUNCT
brj-22232	311	31	,	,	PUNCT
brj-22232	311	32	and	and	CCONJ
brj-22232	311	33	song	song	NOUN
brj-22232	311	34	,	,	PUNCT
brj-22232	311	35	w.	w.	NOUN
brj-22232	311	36	(	(	PUNCT
brj-22232	311	37	2021	2021	NUM
brj-22232	311	38	)	)	PUNCT
brj-22232	311	39	.	.	PUNCT
brj-22232	312	1	“	"	PUNCT
brj-22232	312	2	detection	detection	NOUN
brj-22232	312	3	of	of	ADP
brj-22232	312	4	framboidal	framboidal	ADJ
brj-22232	312	5	pyrite	pyrite	NOUN
brj-22232	312	6	size	size	NOUN
brj-22232	312	7	distributions	distribution	NOUN
brj-22232	312	8	using	use	VERB
brj-22232	312	9	convolutional	convolutional	ADJ
brj-22232	312	10	neural	neural	ADJ
brj-22232	312	11	networks	network	NOUN
brj-22232	312	12	,	,	PUNCT
brj-22232	312	13	”	"	PUNCT
brj-22232	312	14	marine	marine	ADJ
brj-22232	312	15	and	and	CCONJ
brj-22232	312	16	petroleum	petroleum	NOUN
brj-22232	312	17	geology	geology	NOUN
brj-22232	312	18	132	132	NUM
brj-22232	312	19	,	,	PUNCT
brj-22232	312	20	article	article	NOUN
brj-22232	312	21	i	i	PROPN
brj-22232	312	22	d	d	PROPN
brj-22232	312	23	105159	105159	NUM
brj-22232	312	24	.	.	PUNCT
brj-22232	313	1	doi	doi	NOUN
brj-22232	313	2	:	:	PUNCT
brj-22232	313	3	10.1016	10.1016	NUM
brj-22232	313	4	/	/	SYM
brj-22232	313	5	j.marpetgeo.2021.105159	j.marpetgeo.2021.105159	PROPN
brj-22232	313	6	dewantara	dewantara	PROPN
brj-22232	313	7	,	,	PUNCT
brj-22232	313	8	d.	d.	PROPN
brj-22232	313	9	,	,	PUNCT
brj-22232	313	10	and	and	CCONJ
brj-22232	313	11	parnadi	parnadi	NOUN
brj-22232	313	12	,	,	PUNCT
brj-22232	313	13	w.	w.	PROPN
brj-22232	313	14	w.	w.	PROPN
brj-22232	313	15	(	(	PUNCT
brj-22232	313	16	2022	2022	NUM
brj-22232	313	17	)	)	PUNCT
brj-22232	313	18	.	.	PUNCT
brj-22232	314	1	“	"	PUNCT
brj-22232	314	2	automatic	automatic	ADJ
brj-22232	314	3	hyperbola	hyperbola	PROPN
brj-22232	314	4	detection	detection	PROPN
brj-22232	314	5	and	and	CCONJ
brj-22232	314	6	apex	apex	NOUN
brj-22232	314	7	extraction	extraction	NOUN
brj-22232	314	8	using	use	VERB
brj-22232	314	9	convolutional	convolutional	ADJ
brj-22232	314	10	neural	neural	ADJ
brj-22232	314	11	network	network	NOUN
brj-22232	314	12	on	on	ADP
brj-22232	314	13	gpr	gpr	PROPN
brj-22232	314	14	data	datum	NOUN
brj-22232	314	15	,	,	PUNCT
brj-22232	314	16	”	"	PUNCT
brj-22232	314	17	journal	journal	NOUN
brj-22232	314	18	of	of	ADP
brj-22232	314	19	physics	physics	PROPN
brj-22232	314	20	:	:	PUNCT
brj-22232	314	21	conference	conference	NOUN
brj-22232	314	22	series	series	NOUN
brj-22232	314	23	2243(1	2243(1	PROPN
brj-22232	314	24	)	)	PUNCT
brj-22232	314	25	,	,	PUNCT
brj-22232	314	26	article	article	NOUN
brj-22232	314	27	i	i	PROPN
brj-22232	314	28	d	d	PROPN
brj-22232	314	29	012027	012027	NUM
brj-22232	314	30	.	.	PUNCT
brj-22232	315	1	doi	doi	NOUN
brj-22232	315	2	:	:	PUNCT
brj-22232	315	3	10.1088/17426596/2243/1/012027	10.1088/17426596/2243/1/012027	NUM
brj-22232	315	4	gill	gill	NOUN
brj-22232	315	5	,	,	PUNCT
brj-22232	315	6	r.	r.	PROPN
brj-22232	315	7	a.	a.	PROPN
brj-22232	315	8	,	,	PUNCT
brj-22232	315	9	and	and	CCONJ
brj-22232	315	10	jackson	jackson	PROPN
brj-22232	315	11	,	,	PUNCT
brj-22232	315	12	r.	r.	PROPN
brj-22232	315	13	b.	b.	PROPN
brj-22232	315	14	(	(	PUNCT
brj-22232	315	15	2000	2000	NUM
brj-22232	315	16	)	)	PUNCT
brj-22232	315	17	.	.	PUNCT
brj-22232	316	1	“	"	PUNCT
brj-22232	316	2	global	global	ADJ
brj-22232	316	3	patterns	pattern	NOUN
brj-22232	316	4	of	of	ADP
brj-22232	316	5	root	root	NOUN
brj-22232	316	6	turnover	turnover	NOUN
brj-22232	316	7	for	for	ADP
brj-22232	316	8	terrestrial	terrestrial	ADJ
brj-22232	316	9	ecosystems	ecosystem	NOUN
brj-22232	316	10	:	:	PUNCT
brj-22232	316	11	research	research	NOUN
brj-22232	316	12	root	root	NOUN
brj-22232	316	13	turnover	turnover	NOUN
brj-22232	316	14	in	in	ADP
brj-22232	316	15	terrestrial	terrestrial	ADJ
brj-22232	316	16	ecosystems	ecosystem	NOUN
brj-22232	316	17	,	,	PUNCT
brj-22232	316	18	”	"	PUNCT
brj-22232	316	19	new	new	ADJ
brj-22232	316	20	phytologist	phytologist	NOUN
brj-22232	316	21	147(1	147(1	NUM
brj-22232	316	22	)	)	PUNCT
brj-22232	316	23	,	,	PUNCT
brj-22232	316	24	13	13	NUM
brj-22232	316	25	-	-	SYM
brj-22232	316	26	31	31	NUM
brj-22232	316	27	.	.	PUNCT
brj-22232	317	1	doi	doi	NOUN
brj-22232	317	2	:	:	PUNCT
brj-22232	317	3	10.1046	10.1046	NUM
brj-22232	317	4	/	/	SYM
brj-22232	317	5	j.1469	j.1469	PROPN
brj-22232	317	6	-	-	PUNCT
brj-22232	317	7	8137.2000.00681.x	8137.2000.00681.x	NUM
brj-22232	317	8	guo	guo	PROPN
brj-22232	317	9	,	,	PUNCT
brj-22232	317	10	l.	l.	PROPN
brj-22232	317	11	,	,	PUNCT
brj-22232	317	12	chen	chen	PROPN
brj-22232	317	13	,	,	PUNCT
brj-22232	317	14	j.	j.	PROPN
brj-22232	317	15	,	,	PUNCT
brj-22232	317	16	cui	cui	PROPN
brj-22232	317	17	,	,	PUNCT
brj-22232	317	18	x.	x.	PROPN
brj-22232	317	19	,	,	PUNCT
brj-22232	317	20	fan	fan	PROPN
brj-22232	317	21	,	,	PUNCT
brj-22232	317	22	b.	b.	PROPN
brj-22232	317	23	,	,	PUNCT
brj-22232	317	24	and	and	CCONJ
brj-22232	317	25	lin	lin	PROPN
brj-22232	317	26	,	,	PUNCT
brj-22232	317	27	h.	h.	PROPN
brj-22232	317	28	(	(	PUNCT
brj-22232	317	29	2013	2013	NUM
brj-22232	317	30	)	)	PUNCT
brj-22232	317	31	.	.	PUNCT
brj-22232	318	1	“	"	PUNCT
brj-22232	318	2	application	application	NOUN
brj-22232	318	3	of	of	ADP
brj-22232	318	4	ground	ground	NOUN
brj-22232	318	5	penetrating	penetrate	VERB
brj-22232	318	6	radar	radar	NOUN
brj-22232	318	7	for	for	ADP
brj-22232	318	8	coarse	coarse	ADJ
brj-22232	318	9	root	root	NOUN
brj-22232	318	10	detection	detection	NOUN
brj-22232	318	11	and	and	CCONJ
brj-22232	318	12	quantification	quantification	NOUN
brj-22232	318	13	:	:	PUNCT
brj-22232	318	14	a	a	DET
brj-22232	318	15	review	review	NOUN
brj-22232	318	16	,	,	PUNCT
brj-22232	318	17	”	"	PUNCT
brj-22232	318	18	plant	plant	NOUN
brj-22232	318	19	and	and	CCONJ
brj-22232	318	20	soil	soil	NOUN
brj-22232	318	21	362(1–2	362(1–2	NUM
brj-22232	318	22	)	)	PUNCT
brj-22232	318	23	,	,	PUNCT
brj-22232	318	24	1	1	NUM
brj-22232	318	25	-	-	SYM
brj-22232	318	26	23	23	NUM
brj-22232	318	27	.	.	PUNCT
brj-22232	319	1	doi	doi	NOUN
brj-22232	319	2	:	:	PUNCT
brj-22232	319	3	10.1007	10.1007	NUM
brj-22232	319	4	/	/	SYM
brj-22232	319	5	s11104	s11104	PROPN
brj-22232	319	6	-	-	PUNCT
brj-22232	319	7	012	012	NUM
brj-22232	319	8	-	-	PUNCT
brj-22232	319	9	1455	1455	NUM
brj-22232	319	10	-	-	SYM
brj-22232	319	11	5	5	NUM
brj-22232	319	12	hou	hou	NOUN
brj-22232	319	13	,	,	PUNCT
brj-22232	319	14	f.	f.	PROPN
brj-22232	319	15	,	,	PUNCT
brj-22232	319	16	lei	lei	PROPN
brj-22232	319	17	,	,	PUNCT
brj-22232	319	18	w.	w.	PROPN
brj-22232	319	19	,	,	PUNCT
brj-22232	319	20	li	li	PROPN
brj-22232	319	21	,	,	PUNCT
brj-22232	319	22	s.	s.	PROPN
brj-22232	319	23	,	,	PUNCT
brj-22232	319	24	and	and	CCONJ
brj-22232	319	25	xi	xi	PROPN
brj-22232	319	26	,	,	PUNCT
brj-22232	319	27	j.	j.	PROPN
brj-22232	319	28	(	(	PUNCT
brj-22232	319	29	2021	2021	NUM
brj-22232	319	30	)	)	PUNCT
brj-22232	319	31	.	.	PUNCT
brj-22232	320	1	“	"	PUNCT
brj-22232	320	2	deep	deep	ADJ
brj-22232	320	3	learning	learning	NOUN
brj-22232	320	4	-	-	PUNCT
brj-22232	320	5	based	base	VERB
brj-22232	320	6	subsurface	subsurface	NOUN
brj-22232	320	7	target	target	NOUN
brj-22232	320	8	detection	detection	NOUN
brj-22232	320	9	from	from	ADP
brj-22232	320	10	gpr	gpr	PROPN
brj-22232	320	11	scans	scan	NOUN
brj-22232	320	12	,	,	PUNCT
brj-22232	320	13	”	"	PUNCT
brj-22232	320	14	ieee	ieee	NOUN
brj-22232	320	15	sensors	sensor	NOUN
brj-22232	320	16	journal	journal	PROPN
brj-22232	320	17	21(6	21(6	PROPN
brj-22232	320	18	)	)	PUNCT
brj-22232	320	19	,	,	PUNCT
brj-22232	320	20	8161	8161	NUM
brj-22232	320	21	-	-	SYM
brj-22232	320	22	8171	8171	NUM
brj-22232	320	23	.	.	PUNCT
brj-22232	321	1	doi	doi	NOUN
brj-22232	321	2	:	:	PUNCT
brj-22232	321	3	10.1109	10.1109	NUM
brj-22232	321	4	/	/	SYM
brj-22232	321	5	jsen.2021.3050262	jsen.2021.3050262	ADP
brj-22232	321	6	kemna	kemna	PROPN
brj-22232	321	7	,	,	PUNCT
brj-22232	321	8	a.	a.	NOUN
brj-22232	321	9	,	,	PUNCT
brj-22232	321	10	vanderborght	vanderborght	NOUN
brj-22232	321	11	,	,	PUNCT
brj-22232	321	12	j.	j.	PROPN
brj-22232	321	13	,	,	PUNCT
brj-22232	321	14	kulessa	kulessa	PROPN
brj-22232	321	15	,	,	PUNCT
brj-22232	321	16	b.	b.	PROPN
brj-22232	321	17	,	,	PUNCT
brj-22232	321	18	and	and	CCONJ
brj-22232	321	19	vereecken	vereecken	VERB
brj-22232	321	20	,	,	PUNCT
brj-22232	321	21	h.	h.	PROPN
brj-22232	321	22	(	(	PUNCT
brj-22232	321	23	2002	2002	NUM
brj-22232	321	24	)	)	PUNCT
brj-22232	321	25	.	.	PUNCT
brj-22232	322	1	“	"	PUNCT
brj-22232	322	2	imaging	imaging	NOUN
brj-22232	322	3	and	and	CCONJ
brj-22232	322	4	characterisation	characterisation	NOUN
brj-22232	322	5	of	of	ADP
brj-22232	322	6	subsurface	subsurface	NOUN
brj-22232	322	7	solute	solute	NOUN
brj-22232	322	8	transport	transport	NOUN
brj-22232	322	9	using	use	VERB
brj-22232	322	10	electrical	electrical	ADJ
brj-22232	322	11	resistivity	resistivity	NOUN
brj-22232	322	12	tomography	tomography	NOUN
brj-22232	322	13	(	(	PUNCT
brj-22232	322	14	ert	ert	PROPN
brj-22232	322	15	)	)	PUNCT
brj-22232	322	16	and	and	CCONJ
brj-22232	322	17	equivalent	equivalent	ADJ
brj-22232	322	18	transport	transport	NOUN
brj-22232	322	19	models	model	NOUN
brj-22232	322	20	,	,	PUNCT
brj-22232	322	21	”	"	PUNCT
brj-22232	322	22	journal	journal	NOUN
brj-22232	322	23	of	of	ADP
brj-22232	322	24	hydrology	hydrology	NOUN
brj-22232	322	25	267(3–4	267(3–4	NUM
brj-22232	322	26	)	)	PUNCT
brj-22232	322	27	,	,	PUNCT
brj-22232	322	28	125	125	NUM
brj-22232	322	29	-	-	SYM
brj-22232	322	30	146	146	NUM
brj-22232	322	31	.	.	PUNCT
brj-22232	323	1	doi	doi	NOUN
brj-22232	323	2	:	:	PUNCT
brj-22232	323	3	10.1016	10.1016	NUM
brj-22232	323	4	/	/	SYM
brj-22232	323	5	s0022	s0022	NOUN
brj-22232	323	6	-	-	PUNCT
brj-22232	323	7	1694(02)00145	1694(02)00145	NUM
brj-22232	323	8	-	-	SYM
brj-22232	323	9	2	2	NUM
brj-22232	323	10	labrecque	labrecque	NOUN
brj-22232	323	11	,	,	PUNCT
brj-22232	323	12	d.	d.	PROPN
brj-22232	323	13	j.	j.	PROPN
brj-22232	323	14	,	,	PUNCT
brj-22232	323	15	and	and	CCONJ
brj-22232	323	16	yang	yang	PROPN
brj-22232	323	17	,	,	PUNCT
brj-22232	323	18	x.	x.	NOUN
brj-22232	323	19	(	(	PUNCT
brj-22232	323	20	2001	2001	NUM
brj-22232	323	21	)	)	PUNCT
brj-22232	323	22	.	.	PUNCT
brj-22232	324	1	“	"	PUNCT
brj-22232	324	2	difference	difference	NOUN
brj-22232	324	3	inversion	inversion	NOUN
brj-22232	324	4	of	of	ADP
brj-22232	324	5	ert	ert	PROPN
brj-22232	324	6	data	data	PROPN
brj-22232	324	7	:	:	PUNCT
brj-22232	324	8	a	a	DET
brj-22232	324	9	fast	fast	ADJ
brj-22232	324	10	inversion	inversion	NOUN
brj-22232	324	11	method	method	NOUN
brj-22232	324	12	for	for	ADP
brj-22232	324	13	3	3	NUM
brj-22232	324	14	-	-	SYM
brj-22232	324	15	d	d	NOUN
brj-22232	324	16	in	in	ADP
brj-22232	324	17	situ	situ	ADJ
brj-22232	324	18	monitoring	monitoring	NOUN
brj-22232	324	19	,	,	PUNCT
brj-22232	324	20	”	"	PUNCT
brj-22232	324	21	journal	journal	NOUN
brj-22232	324	22	of	of	ADP
brj-22232	324	23	environmental	environmental	ADJ
brj-22232	324	24	and	and	CCONJ
brj-22232	324	25	engineering	engineering	NOUN
brj-22232	324	26	geophysics	geophysic	NOUN
brj-22232	324	27	6(2	6(2	NUM
brj-22232	324	28	)	)	PUNCT
brj-22232	324	29	,	,	PUNCT
brj-22232	324	30	83	83	NUM
brj-22232	324	31	-	-	SYM
brj-22232	324	32	89	89	NUM
brj-22232	324	33	.	.	PUNCT
brj-22232	325	1	doi	doi	NOUN
brj-22232	325	2	:	:	PUNCT
brj-22232	325	3	10.4133	10.4133	NUM
brj-22232	325	4	/	/	SYM
brj-22232	325	5	jeeg6.2.83	jeeg6.2.83	PROPN
brj-22232	325	6	li	li	PROPN
brj-22232	325	7	,	,	PUNCT
brj-22232	325	8	s.	s.	PROPN
brj-22232	325	9	,	,	PUNCT
brj-22232	325	10	fu	fu	PROPN
brj-22232	325	11	,	,	PUNCT
brj-22232	325	12	s.	s.	PROPN
brj-22232	325	13	,	,	PUNCT
brj-22232	325	14	and	and	CCONJ
brj-22232	325	15	zheng	zheng	PROPN
brj-22232	325	16	,	,	PUNCT
brj-22232	325	17	d.	d.	PROPN
brj-22232	325	18	(	(	PUNCT
brj-22232	325	19	2022	2022	NUM
brj-22232	325	20	)	)	PUNCT
brj-22232	325	21	.	.	PUNCT
brj-22232	326	1	“	"	PUNCT
brj-22232	326	2	rural	rural	ADJ
brj-22232	326	3	built	build	VERB
brj-22232	326	4	-	-	PUNCT
brj-22232	326	5	up	up	ADP
brj-22232	326	6	area	area	NOUN
brj-22232	326	7	extraction	extraction	NOUN
brj-22232	326	8	from	from	ADP
brj-22232	326	9	remote	remote	ADJ
brj-22232	326	10	sensing	sensing	NOUN
brj-22232	326	11	images	image	NOUN
brj-22232	326	12	using	use	VERB
brj-22232	326	13	spectral	spectral	ADJ
brj-22232	326	14	residual	residual	ADJ
brj-22232	326	15	methods	method	NOUN
brj-22232	326	16	with	with	ADP
brj-22232	326	17	embedded	embed	VERB
brj-22232	326	18	deep	deep	ADJ
brj-22232	326	19	neural	neural	ADJ
brj-22232	326	20	network	network	NOUN
brj-22232	326	21	,	,	PUNCT
brj-22232	326	22	”	"	PUNCT
brj-22232	326	23	sustainability	sustainability	NOUN
brj-22232	326	24	14(3	14(3	NUM
brj-22232	326	25	)	)	PUNCT
brj-22232	326	26	,	,	PUNCT
brj-22232	326	27	article	article	NOUN
brj-22232	326	28	i	i	PROPN
brj-22232	326	29	d	d	PROPN
brj-22232	326	30	1272	1272	NUM
brj-22232	326	31	.	.	PUNCT
brj-22232	327	1	doi	doi	NOUN
brj-22232	327	2	:	:	PUNCT
brj-22232	327	3	10.3390	10.3390	NUM
brj-22232	327	4	/	/	SYM
brj-22232	327	5	su14031272	su14031272	PROPN
brj-22232	327	6	liang	liang	PROPN
brj-22232	327	7	,	,	PUNCT
brj-22232	327	8	h.	h.	PROPN
brj-22232	327	9	,	,	PUNCT
brj-22232	327	10	fan	fan	PROPN
brj-22232	327	11	,	,	PUNCT
brj-22232	327	12	g.	g.	PROPN
brj-22232	327	13	,	,	PUNCT
brj-22232	327	14	li	li	PROPN
brj-22232	327	15	,	,	PUNCT
brj-22232	327	16	y.	y.	PROPN
brj-22232	327	17	,	,	PUNCT
brj-22232	327	18	and	and	CCONJ
brj-22232	327	19	zhao	zhao	PROPN
brj-22232	327	20	,	,	PUNCT
brj-22232	327	21	y.	y.	PROPN
brj-22232	327	22	(	(	PUNCT
brj-22232	327	23	2021	2021	NUM
brj-22232	327	24	)	)	PUNCT
brj-22232	327	25	.	.	PUNCT
brj-22232	328	1	“	"	PUNCT
brj-22232	328	2	theoretical	theoretical	ADJ
brj-22232	328	3	development	development	NOUN
brj-22232	328	4	of	of	ADP
brj-22232	328	5	plant	plant	NOUN
brj-22232	328	6	root	root	NOUN
brj-22232	328	7	diameter	diameter	NOUN
brj-22232	328	8	estimation	estimation	NOUN
brj-22232	328	9	based	base	VERB
brj-22232	328	10	on	on	ADP
brj-22232	328	11	gprmax	gprmax	ADJ
brj-22232	328	12	data	datum	NOUN
brj-22232	328	13	and	and	CCONJ
brj-22232	328	14	neural	neural	ADJ
brj-22232	328	15	network	network	NOUN
brj-22232	328	16	modelling	modelling	NOUN
brj-22232	328	17	,	,	PUNCT
brj-22232	328	18	”	"	PUNCT
brj-22232	328	19	forests	forest	NOUN
brj-22232	328	20	12(5	12(5	NOUN
brj-22232	328	21	)	)	PUNCT
brj-22232	328	22	,	,	PUNCT
brj-22232	328	23	article	article	NOUN
brj-22232	328	24	no	no	NOUN
brj-22232	328	25	.	.	PUNCT
brj-22232	328	26	615	615	NUM
brj-22232	328	27	.	.	PUNCT
brj-22232	329	1	doi	doi	NOUN
brj-22232	329	2	:	:	PUNCT
brj-22232	329	3	10.3390	10.3390	NUM
brj-22232	329	4	/	/	SYM
brj-22232	329	5	f12050615	f12050615	PROPN
brj-22232	329	6	liu	liu	PROPN
brj-22232	329	7	,	,	PUNCT
brj-22232	329	8	g.	g.	PROPN
brj-22232	329	9	,	,	PUNCT
brj-22232	329	10	nouaze	nouaze	PROPN
brj-22232	329	11	,	,	PUNCT
brj-22232	329	12	j.	j.	PROPN
brj-22232	329	13	c.	c.	PROPN
brj-22232	329	14	,	,	PUNCT
brj-22232	329	15	touko	touko	PROPN
brj-22232	329	16	mbouembe	mbouembe	NOUN
brj-22232	329	17	,	,	PUNCT
brj-22232	329	18	p.	p.	PROPN
brj-22232	329	19	l.	l.	PROPN
brj-22232	329	20	,	,	PUNCT
brj-22232	329	21	and	and	CCONJ
brj-22232	329	22	kim	kim	PROPN
brj-22232	329	23	,	,	PUNCT
brj-22232	329	24	j.	j.	PROPN
brj-22232	329	25	h.	h.	PROPN
brj-22232	329	26	(	(	PUNCT
brj-22232	329	27	2020	2020	NUM
brj-22232	329	28	)	)	PUNCT
brj-22232	329	29	.	.	PUNCT
brj-22232	330	1	“	"	PUNCT
brj-22232	330	2	yolo	yolo	NOUN
brj-22232	330	3	-	-	PUNCT
brj-22232	330	4	tomato	tomato	NOUN
brj-22232	330	5	:	:	PUNCT
brj-22232	330	6	a	a	DET
brj-22232	330	7	robust	robust	ADJ
brj-22232	330	8	algorithm	algorithm	NOUN
brj-22232	330	9	for	for	ADP
brj-22232	330	10	tomato	tomato	NOUN
brj-22232	330	11	detection	detection	NOUN
brj-22232	330	12	based	base	VERB
brj-22232	330	13	on	on	ADP
brj-22232	330	14	yolov3	yolov3	PROPN
brj-22232	330	15	,	,	PUNCT
brj-22232	330	16	”	"	PUNCT
brj-22232	330	17	sensors	sensor	NOUN
brj-22232	330	18	20(7	20(7	NUM
brj-22232	330	19	)	)	PUNCT
brj-22232	330	20	,	,	PUNCT
brj-22232	330	21	article	article	NOUN
brj-22232	330	22	no	no	NOUN
brj-22232	330	23	.	.	NOUN
brj-22232	330	24	2145	2145	NUM
brj-22232	330	25	.	.	PUNCT
brj-22232	331	1	doi	doi	NOUN
brj-22232	331	2	:	:	PUNCT
brj-22232	331	3	10.3390	10.3390	NUM
brj-22232	331	4	/	/	SYM
brj-22232	331	5	s20072145	s20072145	PROPN
brj-22232	331	6	ma	ma	PROPN
brj-22232	331	7	,	,	PUNCT
brj-22232	331	8	h.	h.	PROPN
brj-22232	331	9	,	,	PUNCT
brj-22232	331	10	liu	liu	PROPN
brj-22232	331	11	,	,	PUNCT
brj-22232	331	12	y.	y.	PROPN
brj-22232	331	13	,	,	PUNCT
brj-22232	331	14	ren	ren	PROPN
brj-22232	331	15	,	,	PUNCT
brj-22232	331	16	y.	y.	PROPN
brj-22232	331	17	,	,	PUNCT
brj-22232	331	18	and	and	CCONJ
brj-22232	331	19	yu	yu	PROPN
brj-22232	331	20	,	,	PUNCT
brj-22232	331	21	j.	j.	PROPN
brj-22232	331	22	(	(	PUNCT
brj-22232	331	23	2019	2019	NUM
brj-22232	331	24	)	)	PUNCT
brj-22232	331	25	.	.	PUNCT
brj-22232	332	1	“	"	PUNCT
brj-22232	332	2	detection	detection	NOUN
brj-22232	332	3	of	of	ADP
brj-22232	332	4	collapsed	collapse	VERB
brj-22232	332	5	buildings	building	NOUN
brj-22232	332	6	in	in	ADP
brj-22232	332	7	postearthquake	postearthquake	NOUN
brj-22232	332	8	remote	remote	ADJ
brj-22232	332	9	sensing	sensing	NOUN
brj-22232	332	10	images	image	NOUN
brj-22232	332	11	based	base	VERB
brj-22232	332	12	on	on	ADP
brj-22232	332	13	the	the	DET
brj-22232	332	14	improved	improved	ADJ
brj-22232	332	15	yolov3	yolov3	PROPN
brj-22232	332	16	,	,	PUNCT
brj-22232	332	17	”	"	PUNCT
brj-22232	332	18	remote	remote	ADJ
brj-22232	332	19	sensing	sensing	NOUN
brj-22232	332	20	12(1	12(1	NUM
brj-22232	332	21	)	)	PUNCT
brj-22232	332	22	,	,	PUNCT
brj-22232	332	23	article	article	NOUN
brj-22232	332	24	no	no	NOUN
brj-22232	332	25	.	.	PROPN
brj-22232	332	26	44	44	NUM
brj-22232	332	27	.	.	PUNCT
brj-22232	333	1	doi	doi	NOUN
brj-22232	333	2	:	:	PUNCT
brj-22232	333	3	10.3390	10.3390	NUM
brj-22232	333	4	/	/	SYM
brj-22232	334	1	rs12010044	rs12010044	VERB
brj-22232	334	2	http://dx.doi.org/10.4133/jeeg6.2.83	http://dx.doi.org/10.4133/jeeg6.2.83	ADJ
brj-22232	334	3	peer	peer	NOUN
brj-22232	334	4	-	-	PUNCT
brj-22232	334	5	reviewed	review	VERB
brj-22232	334	6	article	article	NOUN
brj-22232	334	7	bioresources.com	bioresources.com	X
brj-22232	334	8	li	li	PROPN
brj-22232	334	9	et	et	PROPN
brj-22232	334	10	al	al	PROPN
brj-22232	334	11	.	.	PROPN
brj-22232	334	12	(	(	PUNCT
brj-22232	334	13	2023	2023	NUM
brj-22232	334	14	)	)	PUNCT
brj-22232	334	15	.	.	PUNCT
brj-22232	335	1	“	"	PUNCT
brj-22232	335	2	tree	tree	NOUN
brj-22232	335	3	root	root	NOUN
brj-22232	335	4	detection	detection	NOUN
brj-22232	335	5	training	training	NOUN
brj-22232	335	6	,	,	PUNCT
brj-22232	335	7	”	"	PUNCT
brj-22232	335	8	bioresources	bioresource	NOUN
brj-22232	335	9	18(1	18(1	NOUN
brj-22232	335	10	)	)	PUNCT
brj-22232	335	11	,	,	PUNCT
brj-22232	335	12	484	484	NUM
brj-22232	335	13	-	-	SYM
brj-22232	335	14	504	504	NUM
brj-22232	335	15	.	.	PUNCT
brj-22232	336	1	503	503	NUM
brj-22232	336	2	mihai	mihai	PROPN
brj-22232	336	3	,	,	PUNCT
brj-22232	336	4	a.	a.	PROPN
brj-22232	336	5	e.	e.	PROPN
brj-22232	336	6	,	,	PUNCT
brj-22232	336	7	gerea	gerea	PROPN
brj-22232	336	8	,	,	PUNCT
brj-22232	336	9	a.	a.	NOUN
brj-22232	336	10	g.	g.	PROPN
brj-22232	336	11	,	,	PUNCT
brj-22232	336	12	curioni	curioni	PROPN
brj-22232	336	13	,	,	PUNCT
brj-22232	336	14	g.	g.	PROPN
brj-22232	336	15	,	,	PUNCT
brj-22232	336	16	atkins	atkins	PROPN
brj-22232	336	17	,	,	PUNCT
brj-22232	336	18	p.	p.	NOUN
brj-22232	336	19	,	,	PUNCT
brj-22232	336	20	and	and	CCONJ
brj-22232	336	21	hayati	hayati	NOUN
brj-22232	336	22	,	,	PUNCT
brj-22232	336	23	f.	f.	PROPN
brj-22232	336	24	(	(	PUNCT
brj-22232	336	25	2019	2019	NUM
brj-22232	336	26	)	)	PUNCT
brj-22232	336	27	.	.	PUNCT
brj-22232	337	1	“	"	PUNCT
brj-22232	337	2	direct	direct	ADJ
brj-22232	337	3	measurements	measurement	NOUN
brj-22232	337	4	of	of	ADP
brj-22232	337	5	tree	tree	NOUN
brj-22232	337	6	root	root	NOUN
brj-22232	337	7	relative	relative	ADJ
brj-22232	337	8	permittivity	permittivity	NOUN
brj-22232	337	9	for	for	ADP
brj-22232	337	10	the	the	DET
brj-22232	337	11	aid	aid	NOUN
brj-22232	337	12	of	of	ADP
brj-22232	337	13	gpr	gpr	PROPN
brj-22232	337	14	forward	forward	ADJ
brj-22232	337	15	models	model	NOUN
brj-22232	337	16	and	and	CCONJ
brj-22232	337	17	site	site	NOUN
brj-22232	337	18	surveys	survey	NOUN
brj-22232	337	19	,	,	PUNCT
brj-22232	337	20	”	"	PUNCT
brj-22232	337	21	near	near	ADP
brj-22232	337	22	surface	surface	NOUN
brj-22232	337	23	geophysics	geophysic	NOUN
brj-22232	337	24	17(3	17(3	NUM
brj-22232	337	25	)	)	PUNCT
brj-22232	337	26	,	,	PUNCT
brj-22232	337	27	299	299	NUM
brj-22232	337	28	-	-	SYM
brj-22232	337	29	310	310	NUM
brj-22232	337	30	.	.	PUNCT
brj-22232	338	1	doi	doi	NOUN
brj-22232	338	2	:	:	PUNCT
brj-22232	338	3	10.1002	10.1002	NUM
brj-22232	338	4	/	/	SYM
brj-22232	338	5	nsg.12043	nsg.12043	NUM
brj-22232	338	6	pettinelli	pettinelli	NOUN
brj-22232	338	7	,	,	PUNCT
brj-22232	338	8	e.	e.	PROPN
brj-22232	338	9	,	,	PUNCT
brj-22232	338	10	di	di	PROPN
brj-22232	338	11	matteo	matteo	PROPN
brj-22232	338	12	,	,	PUNCT
brj-22232	338	13	a.	a.	PROPN
brj-22232	338	14	,	,	PUNCT
brj-22232	338	15	beaubien	beaubien	PROPN
brj-22232	338	16	,	,	PUNCT
brj-22232	338	17	s.	s.	PROPN
brj-22232	338	18	e.	e.	PROPN
brj-22232	338	19	,	,	PUNCT
brj-22232	338	20	mattei	mattei	PROPN
brj-22232	338	21	,	,	PUNCT
brj-22232	338	22	e.	e.	PROPN
brj-22232	338	23	,	,	PUNCT
brj-22232	338	24	lauro	lauro	PROPN
brj-22232	338	25	,	,	PUNCT
brj-22232	338	26	s.	s.	PROPN
brj-22232	338	27	e.	e.	PROPN
brj-22232	338	28	,	,	PUNCT
brj-22232	338	29	galli	galli	NOUN
brj-22232	338	30	,	,	PUNCT
brj-22232	338	31	a.	a.	NOUN
brj-22232	338	32	,	,	PUNCT
brj-22232	338	33	and	and	CCONJ
brj-22232	338	34	vannaroni	vannaroni	NOUN
brj-22232	338	35	,	,	PUNCT
brj-22232	338	36	g.	g.	PROPN
brj-22232	338	37	(	(	PUNCT
brj-22232	338	38	2014	2014	NUM
brj-22232	338	39	)	)	PUNCT
brj-22232	338	40	.	.	PUNCT
brj-22232	339	1	“	"	PUNCT
brj-22232	339	2	a	a	DET
brj-22232	339	3	controlled	control	VERB
brj-22232	339	4	experiment	experiment	NOUN
brj-22232	339	5	to	to	PART
brj-22232	339	6	investigate	investigate	VERB
brj-22232	339	7	the	the	DET
brj-22232	339	8	correlation	correlation	NOUN
brj-22232	339	9	between	between	ADP
brj-22232	339	10	early	early	ADJ
brj-22232	339	11	-	-	PUNCT
brj-22232	339	12	time	time	NOUN
brj-22232	339	13	signal	signal	NOUN
brj-22232	339	14	attributes	attribute	NOUN
brj-22232	339	15	of	of	ADP
brj-22232	339	16	ground	ground	NOUN
brj-22232	339	17	-	-	PUNCT
brj-22232	339	18	coupled	couple	VERB
brj-22232	339	19	radar	radar	NOUN
brj-22232	339	20	and	and	CCONJ
brj-22232	339	21	soil	soil	NOUN
brj-22232	339	22	dielectric	dielectric	ADJ
brj-22232	339	23	properties	property	NOUN
brj-22232	339	24	,	,	PUNCT
brj-22232	339	25	”	"	PUNCT
brj-22232	339	26	journal	journal	NOUN
brj-22232	339	27	of	of	ADP
brj-22232	339	28	applied	applied	ADJ
brj-22232	339	29	geophysics	geophysic	NOUN
brj-22232	339	30	101	101	NUM
brj-22232	339	31	,	,	PUNCT
brj-22232	339	32	68	68	NUM
brj-22232	339	33	-	-	SYM
brj-22232	339	34	76	76	NUM
brj-22232	339	35	.	.	PUNCT
brj-22232	340	1	doi	doi	NOUN
brj-22232	340	2	:	:	PUNCT
brj-22232	340	3	10.1016	10.1016	NUM
brj-22232	340	4	/	/	SYM
brj-22232	340	5	j.jappgeo.2013.11.012	j.jappgeo.2013.11.012	PROPN
brj-22232	340	6	ren	ren	PROPN
brj-22232	340	7	,	,	PUNCT
brj-22232	340	8	s.	s.	PROPN
brj-22232	340	9	,	,	PUNCT
brj-22232	340	10	he	he	PRON
brj-22232	340	11	,	,	PUNCT
brj-22232	340	12	k.	k.	PROPN
brj-22232	340	13	,	,	PUNCT
brj-22232	340	14	girshick	girshick	PROPN
brj-22232	340	15	,	,	PUNCT
brj-22232	340	16	r.	r.	PROPN
brj-22232	340	17	,	,	PUNCT
brj-22232	340	18	and	and	CCONJ
brj-22232	340	19	sun	sun	NOUN
brj-22232	340	20	,	,	PUNCT
brj-22232	340	21	j.	j.	PROPN
brj-22232	340	22	(	(	PUNCT
brj-22232	340	23	2017	2017	NUM
brj-22232	340	24	)	)	PUNCT
brj-22232	340	25	.	.	PUNCT
brj-22232	341	1	“	"	PUNCT
brj-22232	341	2	faster	fast	ADJ
brj-22232	341	3	r	r	NOUN
brj-22232	341	4	-	-	PUNCT
brj-22232	341	5	cnn	cnn	NOUN
brj-22232	341	6	:	:	PUNCT
brj-22232	341	7	towards	towards	ADP
brj-22232	341	8	real	real	ADJ
brj-22232	341	9	-	-	PUNCT
brj-22232	341	10	time	time	NOUN
brj-22232	341	11	object	object	NOUN
brj-22232	341	12	detection	detection	NOUN
brj-22232	341	13	with	with	ADP
brj-22232	341	14	region	region	NOUN
brj-22232	341	15	proposal	proposal	NOUN
brj-22232	341	16	networks	network	NOUN
brj-22232	341	17	,	,	PUNCT
brj-22232	341	18	”	"	PUNCT
brj-22232	341	19	ieee	ieee	NOUN
brj-22232	341	20	transactions	transaction	NOUN
brj-22232	341	21	on	on	ADP
brj-22232	341	22	pattern	pattern	NOUN
brj-22232	341	23	analysis	analysis	NOUN
brj-22232	341	24	and	and	CCONJ
brj-22232	341	25	machine	machine	NOUN
brj-22232	341	26	intelligence	intelligence	NOUN
brj-22232	341	27	39(6	39(6	NUM
brj-22232	341	28	)	)	PUNCT
brj-22232	341	29	,	,	PUNCT
brj-22232	341	30	1137	1137	NUM
brj-22232	341	31	-	-	SYM
brj-22232	341	32	1149	1149	NUM
brj-22232	341	33	.	.	PUNCT
brj-22232	342	1	doi	doi	NOUN
brj-22232	342	2	:	:	PUNCT
brj-22232	342	3	10.1109	10.1109	NUM
brj-22232	342	4	/	/	SYM
brj-22232	342	5	tpami.2016.2577031	tpami.2016.2577031	NUM
brj-22232	342	6	reubens	reuben	NOUN
brj-22232	342	7	,	,	PUNCT
brj-22232	342	8	b.	b.	PROPN
brj-22232	342	9	,	,	PUNCT
brj-22232	342	10	poesen	poesen	PROPN
brj-22232	342	11	,	,	PUNCT
brj-22232	342	12	j.	j.	PROPN
brj-22232	342	13	,	,	PUNCT
brj-22232	342	14	danjon	danjon	PROPN
brj-22232	342	15	,	,	PUNCT
brj-22232	342	16	f.	f.	PROPN
brj-22232	342	17	,	,	PUNCT
brj-22232	342	18	geudens	geudens	PROPN
brj-22232	342	19	,	,	PUNCT
brj-22232	342	20	g.	g.	PROPN
brj-22232	342	21	,	,	PUNCT
brj-22232	342	22	and	and	CCONJ
brj-22232	342	23	muys	muy	NOUN
brj-22232	342	24	,	,	PUNCT
brj-22232	342	25	b.	b.	PROPN
brj-22232	342	26	(	(	PUNCT
brj-22232	342	27	2007	2007	NUM
brj-22232	342	28	)	)	PUNCT
brj-22232	342	29	.	.	PUNCT
brj-22232	343	1	“	"	PUNCT
brj-22232	343	2	the	the	DET
brj-22232	343	3	role	role	NOUN
brj-22232	343	4	of	of	ADP
brj-22232	343	5	fine	fine	ADJ
brj-22232	343	6	and	and	CCONJ
brj-22232	343	7	coarse	coarse	ADJ
brj-22232	343	8	roots	root	NOUN
brj-22232	343	9	in	in	ADP
brj-22232	343	10	shallow	shallow	ADJ
brj-22232	343	11	slope	slope	NOUN
brj-22232	343	12	stability	stability	NOUN
brj-22232	343	13	and	and	CCONJ
brj-22232	343	14	soil	soil	NOUN
brj-22232	343	15	erosion	erosion	NOUN
brj-22232	343	16	control	control	NOUN
brj-22232	343	17	with	with	ADP
brj-22232	343	18	a	a	DET
brj-22232	343	19	focus	focus	NOUN
brj-22232	343	20	on	on	ADP
brj-22232	343	21	root	root	NOUN
brj-22232	343	22	system	system	NOUN
brj-22232	343	23	architecture	architecture	NOUN
brj-22232	343	24	:	:	PUNCT
brj-22232	343	25	a	a	DET
brj-22232	343	26	review	review	NOUN
brj-22232	343	27	,	,	PUNCT
brj-22232	343	28	”	"	PUNCT
brj-22232	343	29	trees	tree	NOUN
brj-22232	343	30	21(4	21(4	NUM
brj-22232	343	31	)	)	PUNCT
brj-22232	343	32	,	,	PUNCT
brj-22232	343	33	385	385	NUM
brj-22232	343	34	-	-	SYM
brj-22232	343	35	402	402	NUM
brj-22232	343	36	.	.	PUNCT
brj-22232	344	1	doi	doi	NOUN
brj-22232	344	2	:	:	PUNCT
brj-22232	344	3	10.1007	10.1007	NUM
brj-22232	344	4	/	/	SYM
brj-22232	344	5	s00468007	s00468007	NOUN
brj-22232	344	6	-	-	PUNCT
brj-22232	344	7	0132	0132	NUM
brj-22232	344	8	-	-	SYM
brj-22232	344	9	4	4	NUM
brj-22232	344	10	riedell	riedell	NOUN
brj-22232	344	11	,	,	PUNCT
brj-22232	344	12	w.	w.	PROPN
brj-22232	344	13	e.	e.	PROPN
brj-22232	344	14	,	,	PUNCT
brj-22232	344	15	and	and	CCONJ
brj-22232	344	16	osborne	osborne	PROPN
brj-22232	344	17	,	,	PUNCT
brj-22232	344	18	s.	s.	PROPN
brj-22232	344	19	l.	l.	PROPN
brj-22232	344	20	(	(	PUNCT
brj-22232	344	21	2017	2017	NUM
brj-22232	344	22	)	)	PUNCT
brj-22232	344	23	.	.	PUNCT
brj-22232	345	1	“	"	PUNCT
brj-22232	345	2	monolith	monolith	NOUN
brj-22232	345	3	root	root	NOUN
brj-22232	345	4	sampling	sampling	NOUN
brj-22232	345	5	elucidates	elucidate	VERB
brj-22232	345	6	western	western	ADJ
brj-22232	345	7	corn	corn	NOUN
brj-22232	345	8	rootworm	rootworm	NOUN
brj-22232	345	9	larval	larval	NOUN
brj-22232	345	10	feeding	feeding	NOUN
brj-22232	345	11	injury	injury	NOUN
brj-22232	345	12	in	in	ADP
brj-22232	345	13	maize	maize	NOUN
brj-22232	345	14	,	,	PUNCT
brj-22232	345	15	”	"	PUNCT
brj-22232	345	16	crop	crop	NOUN
brj-22232	345	17	science	science	NOUN
brj-22232	345	18	57(6	57(6	NUM
brj-22232	345	19	)	)	PUNCT
brj-22232	345	20	,	,	PUNCT
brj-22232	345	21	3170	3170	NUM
brj-22232	345	22	-	-	SYM
brj-22232	345	23	3178	3178	NUM
brj-22232	345	24	.	.	PUNCT
brj-22232	346	1	doi	doi	NOUN
brj-22232	346	2	:	:	PUNCT
brj-22232	346	3	10.2135	10.2135	NUM
brj-22232	346	4	/	/	SYM
brj-22232	346	5	cropsci2017.04.0218	cropsci2017.04.0218	PROPN
brj-22232	346	6	rosati	rosati	PROPN
brj-22232	346	7	,	,	PUNCT
brj-22232	346	8	r.	r.	PROPN
brj-22232	346	9	,	,	PUNCT
brj-22232	346	10	romeo	romeo	PROPN
brj-22232	346	11	,	,	PUNCT
brj-22232	346	12	l.	l.	PROPN
brj-22232	346	13	,	,	PUNCT
brj-22232	346	14	silvestri	silvestri	PROPN
brj-22232	346	15	,	,	PUNCT
brj-22232	346	16	s.	s.	PROPN
brj-22232	346	17	,	,	PUNCT
brj-22232	346	18	marcheggiani	marcheggiani	PROPN
brj-22232	346	19	,	,	PUNCT
brj-22232	346	20	f.	f.	PROPN
brj-22232	346	21	,	,	PUNCT
brj-22232	346	22	tiano	tiano	PROPN
brj-22232	346	23	,	,	PUNCT
brj-22232	346	24	l.	l.	PROPN
brj-22232	346	25	,	,	PUNCT
brj-22232	346	26	and	and	CCONJ
brj-22232	346	27	frontoni	frontoni	PROPN
brj-22232	346	28	,	,	PUNCT
brj-22232	346	29	e.	e.	PROPN
brj-22232	346	30	(	(	PUNCT
brj-22232	346	31	2020	2020	NUM
brj-22232	346	32	)	)	PUNCT
brj-22232	346	33	.	.	PUNCT
brj-22232	347	1	“	"	PUNCT
brj-22232	347	2	faster	fast	ADJ
brj-22232	347	3	r	r	NOUN
brj-22232	347	4	-	-	PUNCT
brj-22232	347	5	cnn	cnn	PROPN
brj-22232	347	6	approach	approach	NOUN
brj-22232	347	7	for	for	ADP
brj-22232	347	8	detection	detection	NOUN
brj-22232	347	9	and	and	CCONJ
brj-22232	347	10	quantification	quantification	NOUN
brj-22232	347	11	of	of	ADP
brj-22232	347	12	dna	dna	PROPN
brj-22232	347	13	damage	damage	NOUN
brj-22232	347	14	in	in	ADP
brj-22232	347	15	comet	comet	NOUN
brj-22232	347	16	assay	assay	NOUN
brj-22232	347	17	images	image	NOUN
brj-22232	347	18	,	,	PUNCT
brj-22232	347	19	”	"	PUNCT
brj-22232	347	20	computers	computer	NOUN
brj-22232	347	21	in	in	ADP
brj-22232	347	22	biology	biology	NOUN
brj-22232	347	23	and	and	CCONJ
brj-22232	347	24	medicine	medicine	NOUN
brj-22232	347	25	123	123	NUM
brj-22232	347	26	,	,	PUNCT
brj-22232	347	27	article	article	NOUN
brj-22232	347	28	i	i	PROPN
brj-22232	347	29	d	d	PROPN
brj-22232	347	30	103912	103912	NUM
brj-22232	347	31	.	.	PUNCT
brj-22232	348	1	doi	doi	NOUN
brj-22232	348	2	:	:	PUNCT
brj-22232	348	3	10.1016	10.1016	NUM
brj-22232	348	4	/	/	SYM
brj-22232	348	5	j.compbiomed.2020.103912	j.compbiomed.2020.103912	PROPN
brj-22232	348	6	sarro	sarro	PROPN
brj-22232	348	7	,	,	PUNCT
brj-22232	348	8	w.	w.	PROPN
brj-22232	348	9	s.	s.	PROPN
brj-22232	348	10	,	,	PUNCT
brj-22232	348	11	assis	assis	PROPN
brj-22232	348	12	,	,	PUNCT
brj-22232	348	13	g.	g.	PROPN
brj-22232	348	14	m.	m.	NOUN
brj-22232	348	15	,	,	PUNCT
brj-22232	348	16	and	and	CCONJ
brj-22232	348	17	ferreira	ferreira	PROPN
brj-22232	348	18	,	,	PUNCT
brj-22232	348	19	g.	g.	PROPN
brj-22232	348	20	c.	c.	PROPN
brj-22232	348	21	s.	s.	PROPN
brj-22232	348	22	(	(	PUNCT
brj-22232	348	23	2021	2021	NUM
brj-22232	348	24	)	)	PUNCT
brj-22232	348	25	.	.	PUNCT
brj-22232	349	1	“	"	PUNCT
brj-22232	349	2	experimental	experimental	ADJ
brj-22232	349	3	investigation	investigation	NOUN
brj-22232	349	4	of	of	ADP
brj-22232	349	5	the	the	DET
brj-22232	349	6	upv	upv	PROPN
brj-22232	349	7	wavelength	wavelength	NOUN
brj-22232	349	8	in	in	ADP
brj-22232	349	9	compacted	compact	VERB
brj-22232	349	10	soil	soil	NOUN
brj-22232	349	11	,	,	PUNCT
brj-22232	349	12	”	"	PUNCT
brj-22232	349	13	construction	construction	NOUN
brj-22232	349	14	and	and	CCONJ
brj-22232	349	15	building	building	NOUN
brj-22232	349	16	materials	material	NOUN
brj-22232	349	17	272	272	NUM
brj-22232	349	18	,	,	PUNCT
brj-22232	349	19	article	article	NOUN
brj-22232	349	20	i	i	PROPN
brj-22232	349	21	d	d	PROPN
brj-22232	349	22	121834	121834	NUM
brj-22232	349	23	.	.	PUNCT
brj-22232	350	1	doi	doi	NOUN
brj-22232	350	2	:	:	PUNCT
brj-22232	350	3	10.1016	10.1016	NUM
brj-22232	350	4	/	/	SYM
brj-22232	350	5	j.conbuildmat.2020.121834	j.conbuildmat.2020.121834	PROPN
brj-22232	350	6	seyfried	seyfried	PROPN
brj-22232	350	7	,	,	PUNCT
brj-22232	350	8	d.	d.	PROPN
brj-22232	350	9	,	,	PUNCT
brj-22232	350	10	and	and	CCONJ
brj-22232	350	11	schoebel	schoebel	NOUN
brj-22232	350	12	,	,	PUNCT
brj-22232	350	13	j.	j.	PROPN
brj-22232	350	14	(	(	PUNCT
brj-22232	350	15	2016	2016	NUM
brj-22232	350	16	)	)	PUNCT
brj-22232	350	17	.	.	PUNCT
brj-22232	351	1	“	"	PUNCT
brj-22232	351	2	ground	ground	NOUN
brj-22232	351	3	penetrating	penetrate	VERB
brj-22232	351	4	radar	radar	NOUN
brj-22232	351	5	for	for	ADP
brj-22232	351	6	asparagus	asparagus	ADJ
brj-22232	351	7	detection	detection	NOUN
brj-22232	351	8	,	,	PUNCT
brj-22232	351	9	”	"	PUNCT
brj-22232	351	10	journal	journal	NOUN
brj-22232	351	11	of	of	ADP
brj-22232	351	12	applied	apply	VERB
brj-22232	351	13	geophysics	geophysic	NOUN
brj-22232	351	14	,	,	PUNCT
brj-22232	351	15	126	126	NUM
brj-22232	351	16	,	,	PUNCT
brj-22232	351	17	191	191	NUM
brj-22232	351	18	-	-	SYM
brj-22232	351	19	197	197	NUM
brj-22232	351	20	.	.	PUNCT
brj-22232	352	1	doi	doi	NOUN
brj-22232	352	2	:	:	PUNCT
brj-22232	352	3	10.1016	10.1016	NUM
brj-22232	352	4	/	/	SYM
brj-22232	352	5	j.jappgeo.2016.01.022	j.jappgeo.2016.01.022	PROPN
brj-22232	352	6	tanoli	tanoli	PROPN
brj-22232	352	7	,	,	PUNCT
brj-22232	352	8	w.	w.	PROPN
brj-22232	352	9	a.	a.	PROPN
brj-22232	352	10	,	,	PUNCT
brj-22232	352	11	sharafat	sharafat	NOUN
brj-22232	352	12	,	,	PUNCT
brj-22232	352	13	a.	a.	NOUN
brj-22232	352	14	,	,	PUNCT
brj-22232	352	15	park	park	NOUN
brj-22232	352	16	,	,	PUNCT
brj-22232	352	17	j.	j.	PROPN
brj-22232	352	18	,	,	PUNCT
brj-22232	352	19	and	and	CCONJ
brj-22232	352	20	seo	seo	NOUN
brj-22232	352	21	,	,	PUNCT
brj-22232	352	22	j.	j.	PROPN
brj-22232	352	23	w.	w.	PROPN
brj-22232	352	24	(	(	PUNCT
brj-22232	352	25	2019	2019	NUM
brj-22232	352	26	)	)	PUNCT
brj-22232	352	27	.	.	PUNCT
brj-22232	353	1	“	"	PUNCT
brj-22232	353	2	damage	damage	NOUN
brj-22232	353	3	prevention	prevention	NOUN
brj-22232	353	4	for	for	ADP
brj-22232	353	5	underground	underground	ADJ
brj-22232	353	6	utilities	utility	NOUN
brj-22232	353	7	using	use	VERB
brj-22232	353	8	machine	machine	NOUN
brj-22232	353	9	guidance	guidance	NOUN
brj-22232	353	10	,	,	PUNCT
brj-22232	353	11	”	"	PUNCT
brj-22232	353	12	automation	automation	NOUN
brj-22232	353	13	in	in	ADP
brj-22232	353	14	construction	construction	NOUN
brj-22232	353	15	107	107	NUM
brj-22232	353	16	,	,	PUNCT
brj-22232	353	17	article	article	NOUN
brj-22232	353	18	i	i	PROPN
brj-22232	353	19	d	d	PROPN
brj-22232	353	20	102893	102893	NUM
brj-22232	353	21	.	.	PUNCT
brj-22232	354	1	doi	doi	NOUN
brj-22232	354	2	:	:	PUNCT
brj-22232	354	3	10.1016	10.1016	NUM
brj-22232	354	4	/	/	SYM
brj-22232	354	5	j.autcon.2019.102893	j.autcon.2019.102893	PROPN
brj-22232	354	6	thanh	thanh	X
brj-22232	354	7	le	le	X
brj-22232	354	8	,	,	PUNCT
brj-22232	354	9	v.	v.	ADP
brj-22232	354	10	n.	n.	PROPN
brj-22232	354	11	,	,	PUNCT
brj-22232	354	12	truong	truong	PROPN
brj-22232	354	13	,	,	PUNCT
brj-22232	354	14	g.	g.	PROPN
brj-22232	354	15	,	,	PUNCT
brj-22232	354	16	and	and	CCONJ
brj-22232	354	17	alameh	alameh	NOUN
brj-22232	354	18	,	,	PUNCT
brj-22232	354	19	k.	k.	PROPN
brj-22232	354	20	(	(	PUNCT
brj-22232	354	21	2021	2021	NUM
brj-22232	354	22	)	)	PUNCT
brj-22232	354	23	.	.	PUNCT
brj-22232	355	1	“	"	PUNCT
brj-22232	355	2	detecting	detect	VERB
brj-22232	355	3	weeds	weed	NOUN
brj-22232	355	4	from	from	ADP
brj-22232	355	5	crops	crop	NOUN
brj-22232	355	6	under	under	ADP
brj-22232	355	7	complex	complex	ADJ
brj-22232	355	8	field	field	NOUN
brj-22232	355	9	environments	environment	NOUN
brj-22232	355	10	based	base	VERB
brj-22232	355	11	on	on	ADP
brj-22232	355	12	faster	fast	ADJ
brj-22232	355	13	rcnn	rcnn	NOUN
brj-22232	355	14	,	,	PUNCT
brj-22232	355	15	”	"	PUNCT
brj-22232	355	16	in	in	ADP
brj-22232	355	17	:	:	PUNCT
brj-22232	355	18	2020	2020	NUM
brj-22232	355	19	ieee	ieee	PROPN
brj-22232	355	20	eighth	eighth	ADJ
brj-22232	355	21	international	international	ADJ
brj-22232	355	22	conference	conference	NOUN
brj-22232	355	23	on	on	ADP
brj-22232	355	24	communications	communication	NOUN
brj-22232	355	25	and	and	CCONJ
brj-22232	355	26	electronics	electronic	NOUN
brj-22232	355	27	(	(	PUNCT
brj-22232	355	28	icce	icce	NOUN
brj-22232	355	29	)	)	PUNCT
brj-22232	355	30	,	,	PUNCT
brj-22232	355	31	ieee	ieee	NOUN
brj-22232	355	32	,	,	PUNCT
brj-22232	355	33	phu	phu	PROPN
brj-22232	355	34	quoc	quoc	PROPN
brj-22232	355	35	island	island	NOUN
brj-22232	355	36	,	,	PUNCT
brj-22232	355	37	vietnam	vietnam	PROPN
brj-22232	355	38	,	,	PUNCT
brj-22232	355	39	pp	pp	ADJ
brj-22232	355	40	.	.	PUNCT
brj-22232	356	1	350	350	NUM
brj-22232	356	2	-	-	SYM
brj-22232	356	3	355	355	NUM
brj-22232	356	4	.	.	PUNCT
brj-22232	357	1	doi	doi	NOUN
brj-22232	357	2	:	:	PUNCT
brj-22232	357	3	10.1109	10.1109	NUM
brj-22232	357	4	/	/	SYM
brj-22232	357	5	icce48956.2021.9352073	icce48956.2021.9352073	NOUN
brj-22232	357	6	todkar	todkar	NOUN
brj-22232	357	7	,	,	PUNCT
brj-22232	357	8	s.	s.	PROPN
brj-22232	357	9	s.	s.	PROPN
brj-22232	357	10	,	,	PUNCT
brj-22232	357	11	baltazart	baltazart	PROPN
brj-22232	357	12	,	,	PUNCT
brj-22232	357	13	v.	v.	ADV
brj-22232	357	14	,	,	PUNCT
brj-22232	357	15	ihamouten	ihamouten	ADJ
brj-22232	357	16	,	,	PUNCT
brj-22232	357	17	a.	a.	NOUN
brj-22232	357	18	,	,	PUNCT
brj-22232	357	19	dérobert	dérobert	PROPN
brj-22232	357	20	,	,	PUNCT
brj-22232	357	21	x.	x.	NOUN
brj-22232	357	22	,	,	PUNCT
brj-22232	357	23	and	and	CCONJ
brj-22232	357	24	guilbert	guilbert	NOUN
brj-22232	357	25	,	,	PUNCT
brj-22232	357	26	d.	d.	PROPN
brj-22232	357	27	(	(	PUNCT
brj-22232	357	28	2021	2021	NUM
brj-22232	357	29	)	)	PUNCT
brj-22232	357	30	.	.	PUNCT
brj-22232	358	1	“	"	PUNCT
brj-22232	358	2	oneclass	oneclass	NOUN
brj-22232	358	3	svm	svm	NOUN
brj-22232	358	4	based	base	VERB
brj-22232	358	5	outlier	outlier	NOUN
brj-22232	358	6	detection	detection	NOUN
brj-22232	358	7	strategy	strategy	NOUN
brj-22232	358	8	to	to	PART
brj-22232	358	9	detect	detect	VERB
brj-22232	358	10	thin	thin	ADJ
brj-22232	358	11	interlayer	interlayer	NOUN
brj-22232	358	12	debondings	debonding	NOUN
brj-22232	358	13	within	within	ADP
brj-22232	358	14	pavement	pavement	NOUN
brj-22232	358	15	structures	structure	NOUN
brj-22232	358	16	using	use	VERB
brj-22232	358	17	ground	ground	NOUN
brj-22232	358	18	penetrating	penetrate	VERB
brj-22232	358	19	radar	radar	NOUN
brj-22232	358	20	data	datum	NOUN
brj-22232	358	21	,	,	PUNCT
brj-22232	358	22	”	"	PUNCT
brj-22232	358	23	journal	journal	NOUN
brj-22232	358	24	of	of	ADP
brj-22232	358	25	applied	apply	VERB
brj-22232	358	26	geophysics	geophysic	NOUN
brj-22232	358	27	192	192	NUM
brj-22232	358	28	,	,	PUNCT
brj-22232	358	29	article	article	NOUN
brj-22232	358	30	i	i	PROPN
brj-22232	358	31	d	d	PROPN
brj-22232	358	32	104392	104392	NUM
brj-22232	358	33	.	.	PUNCT
brj-22232	359	1	doi	doi	NOUN
brj-22232	359	2	:	:	PUNCT
brj-22232	359	3	10.1016	10.1016	NUM
brj-22232	359	4	/	/	SYM
brj-22232	359	5	j.jappgeo.2021.104392	j.jappgeo.2021.104392	PROPN
brj-22232	359	6	wang	wang	PROPN
brj-22232	359	7	,	,	PUNCT
brj-22232	359	8	y.	y.	PROPN
brj-22232	359	9	,	,	PUNCT
brj-22232	359	10	and	and	CCONJ
brj-22232	359	11	li	li	PROPN
brj-22232	359	12	,	,	PUNCT
brj-22232	359	13	x.	x.	NOUN
brj-22232	359	14	(	(	PUNCT
brj-22232	359	15	2015	2015	NUM
brj-22232	359	16	)	)	PUNCT
brj-22232	359	17	.	.	PUNCT
brj-22232	360	1	“	"	PUNCT
brj-22232	360	2	experimental	experimental	ADJ
brj-22232	360	3	study	study	NOUN
brj-22232	360	4	on	on	ADP
brj-22232	360	5	cracking	crack	VERB
brj-22232	360	6	damage	damage	NOUN
brj-22232	360	7	characteristics	characteristic	NOUN
brj-22232	360	8	of	of	ADP
brj-22232	360	9	a	a	DET
brj-22232	360	10	soil	soil	NOUN
brj-22232	360	11	and	and	CCONJ
brj-22232	360	12	rock	rock	NOUN
brj-22232	360	13	mixture	mixture	NOUN
brj-22232	360	14	by	by	ADP
brj-22232	360	15	upv	upv	NOUN
brj-22232	360	16	testing	testing	NOUN
brj-22232	360	17	,	,	PUNCT
brj-22232	360	18	”	"	PUNCT
brj-22232	360	19	bulletin	bulletin	NOUN
brj-22232	360	20	of	of	ADP
brj-22232	360	21	engineering	engineering	NOUN
brj-22232	360	22	geology	geology	NOUN
brj-22232	360	23	and	and	CCONJ
brj-22232	360	24	the	the	DET
brj-22232	360	25	environment	environment	NOUN
brj-22232	360	26	74(3	74(3	NOUN
brj-22232	360	27	)	)	PUNCT
brj-22232	360	28	,	,	PUNCT
brj-22232	360	29	775	775	NUM
brj-22232	360	30	-	-	SYM
brj-22232	360	31	788	788	NUM
brj-22232	360	32	.	.	PUNCT
brj-22232	361	1	doi	doi	NOUN
brj-22232	361	2	:	:	PUNCT
brj-22232	361	3	10.1007	10.1007	NUM
brj-22232	361	4	/	/	SYM
brj-22232	361	5	s10064	s10064	NOUN
brj-22232	361	6	-	-	PUNCT
brj-22232	361	7	014	014	NUM
brj-22232	361	8	-	-	PUNCT
brj-22232	361	9	0673	0673	NUM
brj-22232	361	10	-	-	PUNCT
brj-22232	361	11	x	x	SYM
brj-22232	361	12	wen	wen	PROPN
brj-22232	361	13	,	,	PUNCT
brj-22232	361	14	j.	j.	PROPN
brj-22232	361	15	,	,	PUNCT
brj-22232	361	16	li	li	PROPN
brj-22232	361	17	,	,	PUNCT
brj-22232	361	18	z.	z.	PROPN
brj-22232	361	19	,	,	PUNCT
brj-22232	361	20	and	and	CCONJ
brj-22232	361	21	xiao	xiao	PROPN
brj-22232	361	22	,	,	PUNCT
brj-22232	361	23	j.	j.	PROPN
brj-22232	361	24	(	(	PUNCT
brj-22232	361	25	2020	2020	NUM
brj-22232	361	26	)	)	PUNCT
brj-22232	361	27	.	.	PUNCT
brj-22232	362	1	“	"	PUNCT
brj-22232	362	2	noise	noise	NOUN
brj-22232	362	3	removal	removal	NOUN
brj-22232	362	4	in	in	ADP
brj-22232	362	5	tree	tree	NOUN
brj-22232	362	6	radar	radar	NOUN
brj-22232	362	7	b	b	X
brj-22232	362	8	-	-	PUNCT
brj-22232	362	9	scan	scan	ADJ
brj-22232	362	10	images	image	NOUN
brj-22232	362	11	based	base	VERB
brj-22232	362	12	on	on	ADP
brj-22232	362	13	shearlet	shearlet	NOUN
brj-22232	362	14	,	,	PUNCT
brj-22232	362	15	”	"	PUNCT
brj-22232	362	16	wood	wood	NOUN
brj-22232	362	17	research	research	NOUN
brj-22232	362	18	65(1	65(1	NOUN
brj-22232	362	19	)	)	PUNCT
brj-22232	362	20	,	,	PUNCT
brj-22232	362	21	1	1	NUM
brj-22232	362	22	-	-	SYM
brj-22232	362	23	12	12	NUM
brj-22232	362	24	.	.	PUNCT
brj-22232	363	1	doi	doi	NOUN
brj-22232	363	2	:	:	PUNCT
brj-22232	363	3	10.37763	10.37763	NUM
brj-22232	363	4	/	/	SYM
brj-22232	363	5	wr.1336	wr.1336	VERB
brj-22232	363	6	-	-	PROPN
brj-22232	363	7	4561/65.1.001012	4561/65.1.001012	PROPN
brj-22232	363	8	xiang	xiang	PROPN
brj-22232	363	9	,	,	PUNCT
brj-22232	363	10	z.	z.	PROPN
brj-22232	363	11	,	,	PUNCT
brj-22232	363	12	rashidi	rashidi	NOUN
brj-22232	363	13	,	,	PUNCT
brj-22232	363	14	a.	a.	NOUN
brj-22232	363	15	,	,	PUNCT
brj-22232	363	16	and	and	CCONJ
brj-22232	363	17	ou	ou	ADP
brj-22232	363	18	,	,	PUNCT
brj-22232	363	19	g.	g.	PROPN
brj-22232	363	20	(	(	PUNCT
brj-22232	363	21	2019	2019	NUM
brj-22232	363	22	)	)	PUNCT
brj-22232	363	23	.	.	PUNCT
brj-22232	364	1	“	"	PUNCT
brj-22232	364	2	an	an	DET
brj-22232	364	3	improved	improved	ADJ
brj-22232	364	4	convolutional	convolutional	ADJ
brj-22232	364	5	neural	neural	ADJ
brj-22232	364	6	network	network	NOUN
brj-22232	364	7	system	system	NOUN
brj-22232	364	8	for	for	ADP
brj-22232	364	9	automatically	automatically	ADV
brj-22232	364	10	detecting	detect	VERB
brj-22232	364	11	rebar	rebar	NOUN
brj-22232	364	12	in	in	ADP
brj-22232	364	13	gpr	gpr	PROPN
brj-22232	364	14	data	datum	NOUN
brj-22232	364	15	,	,	PUNCT
brj-22232	364	16	”	"	PUNCT
brj-22232	364	17	in	in	ADP
brj-22232	364	18	:	:	PUNCT
brj-22232	364	19	computing	compute	VERB
brj-22232	364	20	in	in	ADP
brj-22232	364	21	civil	civil	ADJ
brj-22232	364	22	engineering	engineering	NOUN
brj-22232	364	23	2019	2019	NUM
brj-22232	364	24	,	,	PUNCT
brj-22232	364	25	american	american	ADJ
brj-22232	364	26	society	society	NOUN
brj-22232	364	27	of	of	ADP
brj-22232	364	28	civil	civil	ADJ
brj-22232	364	29	engineers	engineer	NOUN
brj-22232	364	30	,	,	PUNCT
brj-22232	364	31	atlanta	atlanta	PROPN
brj-22232	364	32	,	,	PUNCT
brj-22232	364	33	ga	ga	PROPN
brj-22232	364	34	,	,	PUNCT
brj-22232	364	35	usa	usa	PROPN
brj-22232	364	36	,	,	PUNCT
brj-22232	364	37	pp	pp	PROPN
brj-22232	364	38	.	.	PUNCT
brj-22232	365	1	422	422	NUM
brj-22232	365	2	–	–	PUNCT
brj-22232	365	3	429	429	NUM
brj-22232	365	4	.	.	PUNCT
brj-22232	365	5	doi	doi	NOUN
brj-22232	365	6	:	:	PUNCT
brj-22232	365	7	10.1061/9780784482438.054	10.1061/9780784482438.054	NUM
brj-22232	365	8	peer	peer	NOUN
brj-22232	365	9	-	-	PUNCT
brj-22232	365	10	reviewed	review	VERB
brj-22232	365	11	article	article	NOUN
brj-22232	365	12	bioresources.com	bioresources.com	X
brj-22232	365	13	li	li	PROPN
brj-22232	365	14	et	et	PROPN
brj-22232	365	15	al	al	PROPN
brj-22232	365	16	.	.	PROPN
brj-22232	365	17	(	(	PUNCT
brj-22232	365	18	2023	2023	NUM
brj-22232	365	19	)	)	PUNCT
brj-22232	365	20	.	.	PUNCT
brj-22232	366	1	“	"	PUNCT
brj-22232	366	2	tree	tree	NOUN
brj-22232	366	3	root	root	NOUN
brj-22232	366	4	detection	detection	NOUN
brj-22232	366	5	training	training	NOUN
brj-22232	366	6	,	,	PUNCT
brj-22232	366	7	”	"	PUNCT
brj-22232	366	8	bioresources	bioresource	NOUN
brj-22232	366	9	18(1	18(1	NOUN
brj-22232	366	10	)	)	PUNCT
brj-22232	366	11	,	,	PUNCT
brj-22232	366	12	484	484	NUM
brj-22232	366	13	-	-	SYM
brj-22232	366	14	504	504	NUM
brj-22232	366	15	.	.	PUNCT
brj-22232	367	1	504	504	NUM
brj-22232	367	2	yao	yao	NOUN
brj-22232	367	3	,	,	PUNCT
brj-22232	367	4	s.	s.	PROPN
brj-22232	367	5	,	,	PUNCT
brj-22232	367	6	chen	chen	PROPN
brj-22232	367	7	,	,	PUNCT
brj-22232	367	8	y.	y.	PROPN
brj-22232	367	9	,	,	PUNCT
brj-22232	367	10	tian	tian	PROPN
brj-22232	367	11	,	,	PUNCT
brj-22232	367	12	x.	x.	PROPN
brj-22232	367	13	,	,	PUNCT
brj-22232	367	14	jiang	jiang	PROPN
brj-22232	367	15	,	,	PUNCT
brj-22232	367	16	r.	r.	PROPN
brj-22232	367	17	,	,	PUNCT
brj-22232	367	18	and	and	CCONJ
brj-22232	367	19	ma	ma	PROPN
brj-22232	367	20	,	,	PUNCT
brj-22232	367	21	s.	s.	PROPN
brj-22232	367	22	(	(	PUNCT
brj-22232	367	23	2020	2020	NUM
brj-22232	367	24	)	)	PUNCT
brj-22232	367	25	.	.	PUNCT
brj-22232	368	1	“	"	PUNCT
brj-22232	368	2	an	an	DET
brj-22232	368	3	improved	improved	ADJ
brj-22232	368	4	algorithm	algorithm	NOUN
brj-22232	368	5	for	for	ADP
brj-22232	368	6	detecting	detect	VERB
brj-22232	368	7	pneumonia	pneumonia	NOUN
brj-22232	368	8	based	base	VERB
brj-22232	368	9	on	on	ADP
brj-22232	368	10	yolov3	yolov3	PROPN
brj-22232	368	11	,	,	PUNCT
brj-22232	368	12	”	"	PUNCT
brj-22232	368	13	applied	apply	VERB
brj-22232	368	14	sciences	science	NOUN
brj-22232	368	15	10(5	10(5	NOUN
brj-22232	368	16	)	)	PUNCT
brj-22232	368	17	,	,	PUNCT
brj-22232	368	18	article	article	NOUN
brj-22232	368	19	no	no	NOUN
brj-22232	368	20	.	.	PROPN
brj-22232	368	21	1818	1818	NUM
brj-22232	368	22	.	.	PUNCT
brj-22232	369	1	doi	doi	NOUN
brj-22232	369	2	:	:	PUNCT
brj-22232	369	3	10.3390	10.3390	NUM
brj-22232	369	4	/	/	SYM
brj-22232	369	5	app10051818	app10051818	PROPN
brj-22232	369	6	yarak	yarak	PROPN
brj-22232	369	7	,	,	PUNCT
brj-22232	369	8	k.	k.	PROPN
brj-22232	369	9	,	,	PUNCT
brj-22232	369	10	witayangkurn	witayangkurn	PROPN
brj-22232	369	11	,	,	PUNCT
brj-22232	369	12	a.	a.	NOUN
brj-22232	369	13	,	,	PUNCT
brj-22232	369	14	kritiyutanont	kritiyutanont	NOUN
brj-22232	369	15	,	,	PUNCT
brj-22232	369	16	k.	k.	PROPN
brj-22232	369	17	,	,	PUNCT
brj-22232	369	18	arunplod	arunplod	PROPN
brj-22232	369	19	,	,	PUNCT
brj-22232	369	20	c.	c.	NOUN
brj-22232	369	21	,	,	PUNCT
brj-22232	369	22	and	and	CCONJ
brj-22232	369	23	shibasaki	shibasaki	NOUN
brj-22232	369	24	,	,	PUNCT
brj-22232	369	25	r.	r.	PROPN
brj-22232	369	26	(	(	PUNCT
brj-22232	369	27	2021	2021	NUM
brj-22232	369	28	)	)	PUNCT
brj-22232	369	29	.	.	PUNCT
brj-22232	370	1	“	"	PUNCT
brj-22232	370	2	oil	oil	NOUN
brj-22232	370	3	palm	palm	NOUN
brj-22232	370	4	tree	tree	NOUN
brj-22232	370	5	detection	detection	NOUN
brj-22232	370	6	and	and	CCONJ
brj-22232	370	7	health	health	NOUN
brj-22232	370	8	classification	classification	NOUN
brj-22232	370	9	on	on	ADP
brj-22232	370	10	high	high	ADJ
brj-22232	370	11	-	-	PUNCT
brj-22232	370	12	resolution	resolution	NOUN
brj-22232	370	13	imagery	imagery	NOUN
brj-22232	370	14	using	use	VERB
brj-22232	370	15	deep	deep	ADJ
brj-22232	370	16	learning	learning	NOUN
brj-22232	370	17	,	,	PUNCT
brj-22232	370	18	”	"	PUNCT
brj-22232	370	19	agriculture	agriculture	NOUN
brj-22232	370	20	11(2	11(2	NUM
brj-22232	370	21	)	)	PUNCT
brj-22232	370	22	,	,	PUNCT
brj-22232	370	23	article	article	NOUN
brj-22232	370	24	no	no	NOUN
brj-22232	370	25	.	.	PROPN
brj-22232	370	26	183	183	NUM
brj-22232	370	27	.	.	PUNCT
brj-22232	371	1	doi	doi	NOUN
brj-22232	371	2	:	:	PUNCT
brj-22232	371	3	10.3390	10.3390	NUM
brj-22232	371	4	/	/	SYM
brj-22232	371	5	agriculture11020183	agriculture11020183	PROPN
brj-22232	371	6	zhang	zhang	PROPN
brj-22232	371	7	,	,	PUNCT
brj-22232	371	8	x.	x.	PROPN
brj-22232	371	9	,	,	PUNCT
brj-22232	371	10	xue	xue	PROPN
brj-22232	371	11	,	,	PUNCT
brj-22232	371	12	f.	f.	PROPN
brj-22232	371	13	,	,	PUNCT
brj-22232	371	14	wang	wang	PROPN
brj-22232	371	15	,	,	PUNCT
brj-22232	371	16	z.	z.	PROPN
brj-22232	371	17	,	,	PUNCT
brj-22232	371	18	wen	wen	PROPN
brj-22232	371	19	,	,	PUNCT
brj-22232	371	20	j.	j.	PROPN
brj-22232	371	21	,	,	PUNCT
brj-22232	371	22	guan	guan	PROPN
brj-22232	371	23	,	,	PUNCT
brj-22232	371	24	c.	c.	PROPN
brj-22232	371	25	,	,	PUNCT
brj-22232	371	26	wang	wang	PROPN
brj-22232	371	27	,	,	PUNCT
brj-22232	371	28	f.	f.	PROPN
brj-22232	371	29	,	,	PUNCT
brj-22232	371	30	han	han	PROPN
brj-22232	371	31	,	,	PUNCT
brj-22232	371	32	l.	l.	PROPN
brj-22232	371	33	,	,	PUNCT
brj-22232	371	34	and	and	CCONJ
brj-22232	371	35	ying	ying	PROPN
brj-22232	371	36	,	,	PUNCT
brj-22232	371	37	n.	n.	NOUN
brj-22232	371	38	(	(	PUNCT
brj-22232	371	39	2021	2021	NUM
brj-22232	371	40	)	)	PUNCT
brj-22232	371	41	.	.	PUNCT
brj-22232	372	1	“	"	PUNCT
brj-22232	372	2	a	a	DET
brj-22232	372	3	novel	novel	ADJ
brj-22232	372	4	method	method	NOUN
brj-22232	372	5	of	of	ADP
brj-22232	372	6	hyperbola	hyperbola	PROPN
brj-22232	372	7	recognition	recognition	PROPN
brj-22232	372	8	in	in	ADP
brj-22232	372	9	ground	ground	NOUN
brj-22232	372	10	penetrating	penetrate	VERB
brj-22232	372	11	radar	radar	NOUN
brj-22232	372	12	(	(	PUNCT
brj-22232	372	13	gpr	gpr	PROPN
brj-22232	372	14	)	)	PUNCT
brj-22232	372	15	b	b	X
brj-22232	372	16	-	-	PUNCT
brj-22232	372	17	scan	scan	ADJ
brj-22232	372	18	image	image	NOUN
brj-22232	372	19	for	for	ADP
brj-22232	372	20	tree	tree	NOUN
brj-22232	372	21	roots	root	NOUN
brj-22232	372	22	detection	detection	NOUN
brj-22232	372	23	,	,	PUNCT
brj-22232	372	24	”	"	PUNCT
brj-22232	372	25	forests	forest	NOUN
brj-22232	372	26	12(8	12(8	NUM
brj-22232	372	27	)	)	PUNCT
brj-22232	372	28	,	,	PUNCT
brj-22232	372	29	article	article	NOUN
brj-22232	372	30	no	no	NOUN
brj-22232	372	31	.	.	PROPN
brj-22232	372	32	1019	1019	NUM
brj-22232	372	33	.	.	PUNCT
brj-22232	373	1	doi	doi	NOUN
brj-22232	373	2	:	:	PUNCT
brj-22232	373	3	10.3390	10.3390	NUM
brj-22232	373	4	/	/	SYM
brj-22232	373	5	f12081019	f12081019	NUM
brj-22232	373	6	zhou	zhou	PROPN
brj-22232	373	7	,	,	PUNCT
brj-22232	373	8	x.	x.	PROPN
brj-22232	373	9	,	,	PUNCT
brj-22232	373	10	chen	chen	PROPN
brj-22232	373	11	,	,	PUNCT
brj-22232	373	12	h.	h.	PROPN
brj-22232	373	13	,	,	PUNCT
brj-22232	373	14	and	and	CCONJ
brj-22232	373	15	hao	hao	PROPN
brj-22232	373	16	,	,	PUNCT
brj-22232	373	17	t.	t.	PROPN
brj-22232	373	18	(	(	PUNCT
brj-22232	373	19	2019	2019	NUM
brj-22232	373	20	)	)	PUNCT
brj-22232	373	21	.	.	PUNCT
brj-22232	374	1	“	"	PUNCT
brj-22232	374	2	efficient	efficient	ADJ
brj-22232	374	3	detection	detection	NOUN
brj-22232	374	4	of	of	ADP
brj-22232	374	5	buried	bury	VERB
brj-22232	374	6	plastic	plastic	NOUN
brj-22232	374	7	pipes	pipe	NOUN
brj-22232	374	8	by	by	ADP
brj-22232	374	9	combining	combine	VERB
brj-22232	374	10	gpr	gpr	PROPN
brj-22232	374	11	and	and	CCONJ
brj-22232	374	12	electric	electric	ADJ
brj-22232	374	13	field	field	NOUN
brj-22232	374	14	methods	method	NOUN
brj-22232	374	15	,	,	PUNCT
brj-22232	374	16	”	"	PUNCT
brj-22232	374	17	ieee	ieee	NOUN
brj-22232	374	18	transactions	transaction	NOUN
brj-22232	374	19	on	on	ADP
brj-22232	374	20	geoscience	geoscience	NOUN
brj-22232	374	21	and	and	CCONJ
brj-22232	374	22	remote	remote	ADJ
brj-22232	374	23	sensing	sense	VERB
brj-22232	374	24	57(6	57(6	NUM
brj-22232	374	25	)	)	PUNCT
brj-22232	374	26	,	,	PUNCT
brj-22232	374	27	3967	3967	NUM
brj-22232	374	28	-	-	SYM
brj-22232	374	29	3979	3979	NUM
brj-22232	374	30	.	.	PUNCT
brj-22232	375	1	doi	doi	NOUN
brj-22232	375	2	:	:	PUNCT
brj-22232	375	3	10.1109	10.1109	NUM
brj-22232	375	4	/	/	SYM
brj-22232	375	5	tgrs.2018.2889248	tgrs.2018.2889248	ADP
brj-22232	375	6	zheng	zheng	PROPN
brj-22232	375	7	,	,	PUNCT
brj-22232	375	8	j.	j.	PROPN
brj-22232	375	9	,	,	PUNCT
brj-22232	375	10	li	li	PROPN
brj-22232	375	11	,	,	PUNCT
brj-22232	375	12	w.	w.	PROPN
brj-22232	375	13	,	,	PUNCT
brj-22232	375	14	xia	xia	PROPN
brj-22232	375	15	,	,	PUNCT
brj-22232	375	16	m.	m.	NOUN
brj-22232	375	17	,	,	PUNCT
brj-22232	375	18	dong	dong	PROPN
brj-22232	375	19	,	,	PUNCT
brj-22232	375	20	r.	r.	PROPN
brj-22232	375	21	,	,	PUNCT
brj-22232	375	22	fu	fu	PROPN
brj-22232	375	23	,	,	PUNCT
brj-22232	375	24	h.	h.	PROPN
brj-22232	375	25	,	,	PUNCT
brj-22232	375	26	and	and	CCONJ
brj-22232	375	27	yuan	yuan	NOUN
brj-22232	375	28	,	,	PUNCT
brj-22232	375	29	s.	s.	PROPN
brj-22232	375	30	(	(	PUNCT
brj-22232	375	31	2019	2019	NUM
brj-22232	375	32	)	)	PUNCT
brj-22232	375	33	.	.	PUNCT
brj-22232	376	1	“	"	PUNCT
brj-22232	376	2	large	large	ADJ
brj-22232	376	3	-	-	PUNCT
brj-22232	376	4	scale	scale	NOUN
brj-22232	376	5	oil	oil	NOUN
brj-22232	376	6	palm	palm	NOUN
brj-22232	376	7	tree	tree	NOUN
brj-22232	376	8	detection	detection	NOUN
brj-22232	376	9	from	from	ADP
brj-22232	376	10	high	high	ADJ
brj-22232	376	11	-	-	PUNCT
brj-22232	376	12	resolution	resolution	NOUN
brj-22232	376	13	remote	remote	ADJ
brj-22232	376	14	sensing	sensing	NOUN
brj-22232	376	15	images	image	NOUN
brj-22232	376	16	using	use	VERB
brj-22232	376	17	faster	fast	ADJ
brj-22232	376	18	-	-	PUNCT
brj-22232	376	19	rcnn	rcnn	NOUN
brj-22232	376	20	,	,	PUNCT
brj-22232	376	21	”	"	PUNCT
brj-22232	376	22	in	in	ADP
brj-22232	376	23	:	:	PUNCT
brj-22232	376	24	igarss	igarss	NOUN
brj-22232	376	25	2019	2019	NUM
brj-22232	376	26	2019	2019	NUM
brj-22232	376	27	ieee	ieee	NOUN
brj-22232	376	28	international	international	ADJ
brj-22232	376	29	geoscience	geoscience	PROPN
brj-22232	376	30	and	and	CCONJ
brj-22232	376	31	remote	remote	ADJ
brj-22232	376	32	sensing	sense	VERB
brj-22232	376	33	symposium	symposium	NOUN
brj-22232	376	34	,	,	PUNCT
brj-22232	376	35	ieee	ieee	NOUN
brj-22232	376	36	,	,	PUNCT
brj-22232	376	37	yokohama	yokohama	PROPN
brj-22232	376	38	,	,	PUNCT
brj-22232	376	39	japan	japan	PROPN
brj-22232	376	40	,	,	PUNCT
brj-22232	376	41	pp	pp	ADP
brj-22232	376	42	.	.	PUNCT
brj-22232	376	43	1422	1422	NUM
brj-22232	376	44	-	-	SYM
brj-22232	376	45	1425	1425	NUM
brj-22232	376	46	.	.	PUNCT
brj-22232	377	1	doi	doi	NOUN
brj-22232	377	2	:	:	PUNCT
brj-22232	377	3	10.1109	10.1109	NUM
brj-22232	377	4	/	/	SYM
brj-22232	377	5	igarss.2019.8898360	igarss.2019.8898360	NOUN
brj-22232	377	6	zhou	zhou	NOUN
brj-22232	377	7	,	,	PUNCT
brj-22232	377	8	j.	j.	PROPN
brj-22232	377	9	,	,	PUNCT
brj-22232	377	10	tian	tian	PROPN
brj-22232	377	11	,	,	PUNCT
brj-22232	377	12	y.	y.	PROPN
brj-22232	377	13	,	,	PUNCT
brj-22232	377	14	yuan	yuan	PROPN
brj-22232	377	15	,	,	PUNCT
brj-22232	377	16	c.	c.	PROPN
brj-22232	377	17	,	,	PUNCT
brj-22232	377	18	yin	yin	PROPN
brj-22232	377	19	,	,	PUNCT
brj-22232	377	20	k.	k.	PROPN
brj-22232	377	21	,	,	PUNCT
brj-22232	377	22	yang	yang	PROPN
brj-22232	377	23	,	,	PUNCT
brj-22232	377	24	g.	g.	PROPN
brj-22232	377	25	,	,	PUNCT
brj-22232	377	26	and	and	CCONJ
brj-22232	377	27	wen	wen	PROPN
brj-22232	377	28	,	,	PUNCT
brj-22232	377	29	m.	m.	NOUN
brj-22232	377	30	(	(	PUNCT
brj-22232	377	31	2019	2019	NUM
brj-22232	377	32	)	)	PUNCT
brj-22232	377	33	.	.	PUNCT
brj-22232	378	1	“	"	PUNCT
brj-22232	378	2	improved	improve	VERB
brj-22232	378	3	uav	uav	PROPN
brj-22232	378	4	opium	opium	NOUN
brj-22232	378	5	poppy	poppy	ADJ
brj-22232	378	6	detection	detection	NOUN
brj-22232	378	7	using	use	VERB
brj-22232	378	8	an	an	DET
brj-22232	378	9	updated	update	VERB
brj-22232	378	10	yolov3	yolov3	PROPN
brj-22232	378	11	model	model	PROPN
brj-22232	378	12	,	,	PUNCT
brj-22232	378	13	”	"	PUNCT
brj-22232	378	14	sensors	sensor	NOUN
brj-22232	378	15	19(22	19(22	NUM
brj-22232	378	16	)	)	PUNCT
brj-22232	378	17	,	,	PUNCT
brj-22232	378	18	article	article	NOUN
brj-22232	378	19	no	no	NOUN
brj-22232	378	20	.	.	PUNCT
brj-22232	378	21	4851	4851	NUM
brj-22232	378	22	.	.	PUNCT
brj-22232	379	1	doi	doi	NOUN
brj-22232	379	2	:	:	PUNCT
brj-22232	379	3	10.3390	10.3390	NUM
brj-22232	379	4	/	/	SYM
brj-22232	379	5	s19224851	s19224851	PROPN
brj-22232	379	6	zhu	zhu	PROPN
brj-22232	379	7	,	,	PUNCT
brj-22232	379	8	j.-y	j.-y	PROPN
brj-22232	379	9	.	.	PUNCT
brj-22232	379	10	,	,	PUNCT
brj-22232	379	11	park	park	NOUN
brj-22232	379	12	,	,	PUNCT
brj-22232	379	13	t.	t.	PROPN
brj-22232	379	14	,	,	PUNCT
brj-22232	379	15	isola	isola	PROPN
brj-22232	379	16	,	,	PUNCT
brj-22232	379	17	p.	p.	NOUN
brj-22232	379	18	,	,	PUNCT
brj-22232	379	19	and	and	CCONJ
brj-22232	379	20	efros	efros	PROPN
brj-22232	379	21	,	,	PUNCT
brj-22232	379	22	a.	a.	NOUN
brj-22232	379	23	a.	a.	PROPN
brj-22232	379	24	(	(	PUNCT
brj-22232	379	25	2017	2017	NUM
brj-22232	379	26	)	)	PUNCT
brj-22232	379	27	.	.	PUNCT
brj-22232	380	1	“	"	PUNCT
brj-22232	380	2	unpaired	unpaired	ADJ
brj-22232	380	3	image	image	NOUN
brj-22232	380	4	-	-	PUNCT
brj-22232	380	5	to	to	ADP
brj-22232	380	6	-	-	PUNCT
brj-22232	380	7	image	image	NOUN
brj-22232	380	8	translation	translation	NOUN
brj-22232	380	9	using	use	VERB
brj-22232	380	10	cycle	cycle	NOUN
brj-22232	380	11	-	-	PUNCT
brj-22232	380	12	consistent	consistent	ADJ
brj-22232	380	13	adversarial	adversarial	ADJ
brj-22232	380	14	networks	network	NOUN
brj-22232	380	15	,	,	PUNCT
brj-22232	380	16	”	"	PUNCT
brj-22232	380	17	in	in	ADP
brj-22232	380	18	:	:	PUNCT
brj-22232	380	19	2017	2017	NUM
brj-22232	380	20	ieee	ieee	NOUN
brj-22232	380	21	international	international	ADJ
brj-22232	380	22	conference	conference	NOUN
brj-22232	380	23	on	on	ADP
brj-22232	380	24	computer	computer	NOUN
brj-22232	380	25	vision	vision	NOUN
brj-22232	380	26	(	(	PUNCT
brj-22232	380	27	iccv	iccv	PROPN
brj-22232	380	28	)	)	PUNCT
brj-22232	380	29	,	,	PUNCT
brj-22232	380	30	ieee	ieee	NOUN
brj-22232	380	31	,	,	PUNCT
brj-22232	380	32	venice	venice	PROPN
brj-22232	380	33	,	,	PUNCT
brj-22232	380	34	italy	italy	PROPN
brj-22232	380	35	,	,	PUNCT
brj-22232	380	36	pp	pp	X
brj-22232	380	37	.	.	PUNCT
brj-22232	381	1	2242	2242	NUM
brj-22232	381	2	-	-	SYM
brj-22232	381	3	2251	2251	NUM
brj-22232	381	4	.	.	PUNCT
brj-22232	382	1	doi	doi	NOUN
brj-22232	382	2	:	:	PUNCT
brj-22232	382	3	10.1109	10.1109	NUM
brj-22232	382	4	/	/	SYM
brj-22232	382	5	iccv.2017.244	iccv.2017.244	NOUN
brj-22232	382	6	article	article	NOUN
brj-22232	382	7	submitted	submit	VERB
brj-22232	382	8	:	:	PUNCT
brj-22232	382	9	august	august	PROPN
brj-22232	382	10	11	11	NUM
brj-22232	382	11	,	,	PUNCT
brj-22232	382	12	2022	2022	NUM
brj-22232	382	13	;	;	PUNCT
brj-22232	382	14	peer	peer	NOUN
brj-22232	382	15	review	review	NOUN
brj-22232	382	16	completed	complete	VERB
brj-22232	382	17	:	:	PUNCT
brj-22232	382	18	november	november	PROPN
brj-22232	382	19	5	5	NUM
brj-22232	382	20	,	,	PUNCT
brj-22232	382	21	2022	2022	NUM
brj-22232	382	22	;	;	PUNCT
brj-22232	382	23	revised	revise	VERB
brj-22232	382	24	version	version	NOUN
brj-22232	382	25	received	receive	VERB
brj-22232	382	26	and	and	CCONJ
brj-22232	382	27	accepted	accept	VERB
brj-22232	382	28	:	:	PUNCT
brj-22232	382	29	november	november	PROPN
brj-22232	382	30	8	8	NUM
brj-22232	382	31	,	,	PUNCT
brj-22232	382	32	2022	2022	NUM
brj-22232	382	33	;	;	PUNCT
brj-22232	382	34	published	publish	VERB
brj-22232	382	35	:	:	PUNCT
brj-22232	382	36	november	november	PROPN
brj-22232	382	37	16	16	NUM
brj-22232	382	38	,	,	PUNCT
brj-22232	382	39	2022	2022	NUM
brj-22232	382	40	.	.	PUNCT
brj-22232	383	1	doi	doi	NOUN
brj-22232	383	2	:	:	PUNCT
brj-22232	383	3	10.15376	10.15376	NUM
brj-22232	383	4	/	/	SYM
brj-22232	383	5	biores.18.1.484	biores.18.1.484	NOUN
brj-22232	383	6	-	-	PUNCT
brj-22232	383	7	504	504	NUM