id	sid	tid	token	lemma	pos
ajst-31210	1	1	academic	academic	ADJ
ajst-31210	1	2	journal	journal	NOUN
ajst-31210	1	3	of	of	ADP
ajst-31210	1	4	science	science	NOUN
ajst-31210	1	5	and	and	CCONJ
ajst-31210	1	6	technology	technology	NOUN
ajst-31210	1	7	issn	issn	NOUN
ajst-31210	1	8	:	:	PUNCT
ajst-31210	1	9	2771	2771	NUM
ajst-31210	1	10	-	-	SYM
ajst-31210	1	11	3032	3032	NUM
ajst-31210	1	12	|	|	NOUN
ajst-31210	1	13	vol	vol	NOUN
ajst-31210	1	14	.	.	PROPN
ajst-31210	1	15	15	15	NUM
ajst-31210	1	16	,	,	PUNCT
ajst-31210	1	17	no	no	INTJ
ajst-31210	1	18	.	.	NOUN
ajst-31210	1	19	3	3	NUM
ajst-31210	1	20	,	,	PUNCT
ajst-31210	1	21	2025	2025	NUM
ajst-31210	1	22	73	73	NUM
ajst-31210	1	23	research	research	NOUN
ajst-31210	1	24	on	on	ADP
ajst-31210	1	25	the	the	DET
ajst-31210	1	26	method	method	NOUN
ajst-31210	1	27	of	of	ADP
ajst-31210	1	28	rice	rice	NOUN
ajst-31210	1	29	seed	seed	NOUN
ajst-31210	1	30	density	density	NOUN
ajst-31210	1	31	detection	detection	NOUN
ajst-31210	1	32	in	in	ADP
ajst-31210	1	33	rice	rice	NOUN
ajst-31210	1	34	seedling	seedling	NOUN
ajst-31210	1	35	tray	tray	NOUN
ajst-31210	1	36	based	base	VERB
ajst-31210	1	37	on	on	ADP
ajst-31210	1	38	mcnn	mcnn	PROPN
ajst-31210	1	39	xiangwu	xiangwu	PROPN
ajst-31210	1	40	deng	deng	PROPN
ajst-31210	2	1	*	*	PROPN
ajst-31210	2	2	,	,	PUNCT
ajst-31210	2	3	dacheng	dacheng	PROPN
ajst-31210	2	4	liu	liu	PROPN
ajst-31210	2	5	,	,	PUNCT
ajst-31210	2	6	ruhui	ruhui	PROPN
ajst-31210	2	7	chen	chen	PROPN
ajst-31210	2	8	,	,	PUNCT
ajst-31210	2	9	sheng	sheng	PROPN
ajst-31210	2	10	xie	xie	PROPN
ajst-31210	2	11	,	,	PUNCT
ajst-31210	2	12	ziqin	ziqin	PROPN
ajst-31210	2	13	hong	hong	PROPN
ajst-31210	2	14	college	college	PROPN
ajst-31210	2	15	of	of	ADP
ajst-31210	2	16	electronic	electronic	ADJ
ajst-31210	2	17	information	information	NOUN
ajst-31210	2	18	engineering	engineering	NOUN
ajst-31210	2	19	,	,	PUNCT
ajst-31210	2	20	guangdong	guangdong	PROPN
ajst-31210	2	21	university	university	PROPN
ajst-31210	2	22	of	of	ADP
ajst-31210	2	23	petrochemical	petrochemical	NOUN
ajst-31210	2	24	technology	technology	NOUN
ajst-31210	2	25	,	,	PUNCT
ajst-31210	2	26	maoming	maoming	NOUN
ajst-31210	2	27	,	,	PUNCT
ajst-31210	2	28	525000	525000	NUM
ajst-31210	2	29	,	,	PUNCT
ajst-31210	2	30	china	china	PROPN
ajst-31210	2	31	*	*	PUNCT
ajst-31210	2	32	corresponding	correspond	VERB
ajst-31210	2	33	author	author	NOUN
ajst-31210	2	34	:	:	PUNCT
ajst-31210	2	35	xiangwu	xiangwu	PROPN
ajst-31210	2	36	deng	deng	PROPN
ajst-31210	2	37	abstract	abstract	PROPN
ajst-31210	2	38	:	:	PUNCT
ajst-31210	2	39	due	due	ADP
ajst-31210	2	40	to	to	ADP
ajst-31210	2	41	the	the	DET
ajst-31210	2	42	small	small	ADJ
ajst-31210	2	43	size	size	NOUN
ajst-31210	2	44	of	of	ADP
ajst-31210	2	45	the	the	DET
ajst-31210	2	46	rice	rice	NOUN
ajst-31210	2	47	seed	seed	NOUN
ajst-31210	2	48	images	image	NOUN
ajst-31210	2	49	in	in	ADP
ajst-31210	2	50	the	the	DET
ajst-31210	2	51	rice	rice	NOUN
ajst-31210	2	52	seedling	seedling	NOUN
ajst-31210	2	53	tray	tray	NOUN
ajst-31210	2	54	and	and	CCONJ
ajst-31210	2	55	hole	hole	NOUN
ajst-31210	2	56	tray	tray	NOUN
ajst-31210	2	57	,	,	PUNCT
ajst-31210	2	58	perspective	perspective	ADJ
ajst-31210	2	59	distortion	distortion	NOUN
ajst-31210	2	60	occurs	occur	VERB
ajst-31210	2	61	,	,	PUNCT
ajst-31210	2	62	and	and	CCONJ
ajst-31210	2	63	the	the	DET
ajst-31210	2	64	size	size	NOUN
ajst-31210	2	65	of	of	ADP
ajst-31210	2	66	each	each	DET
ajst-31210	2	67	target	target	NOUN
ajst-31210	2	68	in	in	ADP
ajst-31210	2	69	the	the	DET
ajst-31210	2	70	image	image	NOUN
ajst-31210	2	71	varies	vary	VERB
ajst-31210	2	72	.	.	PUNCT
ajst-31210	3	1	traditional	traditional	ADJ
ajst-31210	3	2	convolutional	convolutional	ADJ
ajst-31210	3	3	neural	neural	ADJ
ajst-31210	3	4	networks	network	NOUN
ajst-31210	3	5	using	use	VERB
ajst-31210	3	6	receptive	receptive	ADJ
ajst-31210	3	7	field	field	NOUN
ajst-31210	3	8	convolution	convolution	NOUN
ajst-31210	3	9	kernels	kernel	NOUN
ajst-31210	3	10	of	of	ADP
ajst-31210	3	11	the	the	DET
ajst-31210	3	12	same	same	ADJ
ajst-31210	3	13	size	size	NOUN
ajst-31210	3	14	can	can	AUX
ajst-31210	3	15	not	not	PART
ajst-31210	3	16	accurately	accurately	ADV
ajst-31210	3	17	capture	capture	VERB
ajst-31210	3	18	target	target	NOUN
ajst-31210	3	19	features	feature	NOUN
ajst-31210	3	20	.	.	PUNCT
ajst-31210	4	1	although	although	SCONJ
ajst-31210	4	2	some	some	DET
ajst-31210	4	3	scholars	scholar	NOUN
ajst-31210	4	4	have	have	AUX
ajst-31210	4	5	addressed	address	VERB
ajst-31210	4	6	this	this	DET
ajst-31210	4	7	issue	issue	NOUN
ajst-31210	4	8	by	by	ADP
ajst-31210	4	9	combining	combine	VERB
ajst-31210	4	10	density	density	NOUN
ajst-31210	4	11	maps	map	NOUN
ajst-31210	4	12	extracted	extract	VERB
ajst-31210	4	13	from	from	ADP
ajst-31210	4	14	image	image	NOUN
ajst-31210	4	15	blocks	block	NOUN
ajst-31210	4	16	of	of	ADP
ajst-31210	4	17	different	different	ADJ
ajst-31210	4	18	resolutions	resolution	NOUN
ajst-31210	4	19	or	or	CCONJ
ajst-31210	4	20	feature	feature	NOUN
ajst-31210	4	21	maps	map	NOUN
ajst-31210	4	22	obtained	obtain	VERB
ajst-31210	4	23	through	through	ADP
ajst-31210	4	24	convolutional	convolutional	ADJ
ajst-31210	4	25	filters	filter	NOUN
ajst-31210	4	26	of	of	ADP
ajst-31210	4	27	different	different	ADJ
ajst-31210	4	28	sizes	size	NOUN
ajst-31210	4	29	.	.	PUNCT
ajst-31210	5	1	by	by	ADP
ajst-31210	5	2	indiscriminately	indiscriminately	ADV
ajst-31210	5	3	fusing	fuse	VERB
ajst-31210	5	4	information	information	NOUN
ajst-31210	5	5	from	from	ADP
ajst-31210	5	6	all	all	DET
ajst-31210	5	7	scales	scale	NOUN
ajst-31210	5	8	,	,	PUNCT
ajst-31210	5	9	these	these	DET
ajst-31210	5	10	methods	method	NOUN
ajst-31210	5	11	ignore	ignore	VERB
ajst-31210	5	12	the	the	DET
ajst-31210	5	13	fact	fact	NOUN
ajst-31210	5	14	that	that	SCONJ
ajst-31210	5	15	the	the	DET
ajst-31210	5	16	scales	scale	NOUN
ajst-31210	5	17	in	in	ADP
ajst-31210	5	18	the	the	DET
ajst-31210	5	19	image	image	NOUN
ajst-31210	5	20	are	be	AUX
ajst-31210	5	21	continuously	continuously	ADV
ajst-31210	5	22	changing	change	VERB
ajst-31210	5	23	.	.	PUNCT
ajst-31210	6	1	training	train	VERB
ajst-31210	6	2	a	a	DET
ajst-31210	6	3	classifier	classifier	NOUN
ajst-31210	6	4	to	to	PART
ajst-31210	6	5	predict	predict	VERB
ajst-31210	6	6	the	the	DET
ajst-31210	6	7	receptive	receptive	ADJ
ajst-31210	6	8	field	field	NOUN
ajst-31210	6	9	size	size	NOUN
ajst-31210	6	10	used	use	VERB
ajst-31210	6	11	locally	locally	ADV
ajst-31210	6	12	can	can	AUX
ajst-31210	6	13	solve	solve	VERB
ajst-31210	6	14	this	this	DET
ajst-31210	6	15	problem	problem	NOUN
ajst-31210	6	16	,	,	PUNCT
ajst-31210	6	17	but	but	CCONJ
ajst-31210	6	18	it	it	PRON
ajst-31210	6	19	is	be	AUX
ajst-31210	6	20	not	not	PART
ajst-31210	6	21	an	an	DET
ajst-31210	6	22	end	end	NOUN
ajst-31210	6	23	-	-	PUNCT
ajst-31210	6	24	to	to	ADP
ajst-31210	6	25	-	-	PUNCT
ajst-31210	6	26	end	end	NOUN
ajst-31210	6	27	training	training	NOUN
ajst-31210	6	28	approach	approach	NOUN
ajst-31210	6	29	and	and	CCONJ
ajst-31210	6	30	can	can	AUX
ajst-31210	6	31	not	not	PART
ajst-31210	6	32	effectively	effectively	ADV
ajst-31210	6	33	address	address	VERB
ajst-31210	6	34	rapid	rapid	ADJ
ajst-31210	6	35	scale	scale	NOUN
ajst-31210	6	36	changes	change	NOUN
ajst-31210	6	37	.	.	PUNCT
ajst-31210	7	1	this	this	DET
ajst-31210	7	2	article	article	NOUN
ajst-31210	7	3	introduces	introduce	VERB
ajst-31210	7	4	multi	multi	ADJ
ajst-31210	7	5	-	-	ADJ
ajst-31210	7	6	scale	scale	ADJ
ajst-31210	7	7	convolutional	convolutional	ADJ
ajst-31210	7	8	neural	neural	ADJ
ajst-31210	7	9	networks	network	NOUN
ajst-31210	7	10	(	(	PUNCT
ajst-31210	7	11	mcnn	mcnn	NOUN
ajst-31210	7	12	)	)	PUNCT
ajst-31210	7	13	,	,	PUNCT
ajst-31210	7	14	which	which	PRON
ajst-31210	7	15	explicitly	explicitly	ADV
ajst-31210	7	16	extract	extract	VERB
ajst-31210	7	17	features	feature	NOUN
ajst-31210	7	18	on	on	ADP
ajst-31210	7	19	multiple	multiple	ADJ
ajst-31210	7	20	receptive	receptive	ADJ
ajst-31210	7	21	field	field	NOUN
ajst-31210	7	22	sizes	size	NOUN
ajst-31210	7	23	and	and	CCONJ
ajst-31210	7	24	learn	learn	VERB
ajst-31210	7	25	the	the	DET
ajst-31210	7	26	importance	importance	NOUN
ajst-31210	7	27	of	of	ADP
ajst-31210	7	28	each	each	DET
ajst-31210	7	29	such	such	ADJ
ajst-31210	7	30	feature	feature	NOUN
ajst-31210	7	31	at	at	ADP
ajst-31210	7	32	each	each	DET
ajst-31210	7	33	image	image	NOUN
ajst-31210	7	34	position	position	NOUN
ajst-31210	7	35	.	.	PUNCT
ajst-31210	8	1	this	this	DET
ajst-31210	8	2	method	method	NOUN
ajst-31210	8	3	adaptively	adaptively	ADV
ajst-31210	8	4	encodes	encode	VERB
ajst-31210	8	5	the	the	DET
ajst-31210	8	6	scale	scale	NOUN
ajst-31210	8	7	of	of	ADP
ajst-31210	8	8	contextual	contextual	ADJ
ajst-31210	8	9	information	information	NOUN
ajst-31210	8	10	required	require	VERB
ajst-31210	8	11	to	to	PART
ajst-31210	8	12	predict	predict	VERB
ajst-31210	8	13	target	target	NOUN
ajst-31210	8	14	density	density	NOUN
ajst-31210	8	15	,	,	PUNCT
ajst-31210	8	16	thereby	thereby	ADV
ajst-31210	8	17	explaining	explain	VERB
ajst-31210	8	18	potential	potential	ADJ
ajst-31210	8	19	rapid	rapid	ADJ
ajst-31210	8	20	scale	scale	NOUN
ajst-31210	8	21	changes	change	NOUN
ajst-31210	8	22	.	.	PUNCT
ajst-31210	9	1	keywords	keyword	NOUN
ajst-31210	9	2	:	:	PUNCT
ajst-31210	9	3	rice	rice	NOUN
ajst-31210	9	4	seedling	seedling	NOUN
ajst-31210	9	5	tray	tray	NOUN
ajst-31210	9	6	;	;	PUNCT
ajst-31210	9	7	rice	rice	NOUN
ajst-31210	9	8	seed	seed	NOUN
ajst-31210	9	9	counting	counting	NOUN
ajst-31210	9	10	;	;	PUNCT
ajst-31210	9	11	features	feature	NOUN
ajst-31210	9	12	;	;	PUNCT
ajst-31210	9	13	multi	multi	ADJ
ajst-31210	9	14	-	-	ADJ
ajst-31210	9	15	scale	scale	ADJ
ajst-31210	9	16	convolutional	convolutional	ADJ
ajst-31210	9	17	neural	neural	ADJ
ajst-31210	9	18	networks	network	NOUN
ajst-31210	9	19	.	.	PUNCT
ajst-31210	10	1	1	1	X
ajst-31210	10	2	.	.	X
ajst-31210	10	3	introduction	introduction	NOUN
ajst-31210	10	4	the	the	DET
ajst-31210	10	5	main	main	ADJ
ajst-31210	10	6	methods	method	NOUN
ajst-31210	10	7	of	of	ADP
ajst-31210	10	8	transplanting	transplant	VERB
ajst-31210	10	9	rice	rice	NOUN
ajst-31210	10	10	seedlings	seedling	NOUN
ajst-31210	10	11	include	include	VERB
ajst-31210	10	12	seedling	seedling	NOUN
ajst-31210	10	13	throwing	throwing	NOUN
ajst-31210	10	14	and	and	CCONJ
ajst-31210	10	15	transplanting	transplanting	NOUN
ajst-31210	10	16	.	.	PUNCT
ajst-31210	11	1	to	to	PART
ajst-31210	11	2	achieve	achieve	VERB
ajst-31210	11	3	stable	stable	ADJ
ajst-31210	11	4	yield	yield	NOUN
ajst-31210	11	5	,	,	PUNCT
ajst-31210	11	6	the	the	DET
ajst-31210	11	7	prerequisite	prerequisite	NOUN
ajst-31210	11	8	is	be	AUX
ajst-31210	11	9	the	the	DET
ajst-31210	11	10	seedling	seedling	NOUN
ajst-31210	11	11	raising	raising	NOUN
ajst-31210	11	12	process	process	NOUN
ajst-31210	11	13	.	.	PUNCT
ajst-31210	12	1	especially	especially	ADV
ajst-31210	12	2	in	in	ADP
ajst-31210	12	3	the	the	DET
ajst-31210	12	4	machine	machine	NOUN
ajst-31210	12	5	transplanting	transplanting	NOUN
ajst-31210	12	6	method	method	NOUN
ajst-31210	12	7	,	,	PUNCT
ajst-31210	12	8	the	the	DET
ajst-31210	12	9	uniformity	uniformity	NOUN
ajst-31210	12	10	of	of	ADP
ajst-31210	12	11	seedling	seedling	NOUN
ajst-31210	12	12	tray	tray	NOUN
ajst-31210	12	13	sowing	sowing	NOUN
ajst-31210	12	14	is	be	AUX
ajst-31210	12	15	a	a	DET
ajst-31210	12	16	prerequisite	prerequisite	NOUN
ajst-31210	12	17	guarantee	guarantee	NOUN
ajst-31210	12	18	for	for	ADP
ajst-31210	12	19	the	the	DET
ajst-31210	12	20	quality	quality	NOUN
ajst-31210	12	21	of	of	ADP
ajst-31210	12	22	seedling	seedle	VERB
ajst-31210	12	23	cultivation	cultivation	NOUN
ajst-31210	12	24	,	,	PUNCT
ajst-31210	12	25	indicating	indicate	VERB
ajst-31210	12	26	that	that	SCONJ
ajst-31210	12	27	seedling	seedling	NOUN
ajst-31210	12	28	cultivation	cultivation	NOUN
ajst-31210	12	29	is	be	AUX
ajst-31210	12	30	the	the	DET
ajst-31210	12	31	key	key	ADJ
ajst-31210	12	32	factor	factor	NOUN
ajst-31210	12	33	restricting	restrict	VERB
ajst-31210	12	34	mechanical	mechanical	ADJ
ajst-31210	12	35	transplanting	transplanting	NOUN
ajst-31210	12	36	.	.	PUNCT
ajst-31210	13	1	for	for	ADP
ajst-31210	13	2	conventional	conventional	ADJ
ajst-31210	13	3	rice	rice	NOUN
ajst-31210	13	4	seedling	seedling	NOUN
ajst-31210	13	5	cultivation	cultivation	NOUN
ajst-31210	13	6	and	and	CCONJ
ajst-31210	13	7	transplanting	transplanting	NOUN
ajst-31210	13	8	,	,	PUNCT
ajst-31210	13	9	if	if	SCONJ
ajst-31210	13	10	the	the	DET
ajst-31210	13	11	uniformity	uniformity	NOUN
ajst-31210	13	12	of	of	ADP
ajst-31210	13	13	seed	seed	NOUN
ajst-31210	13	14	distribution	distribution	NOUN
ajst-31210	13	15	in	in	ADP
ajst-31210	13	16	the	the	DET
ajst-31210	13	17	seedling	seedling	NOUN
ajst-31210	13	18	tray	tray	NOUN
ajst-31210	13	19	is	be	AUX
ajst-31210	13	20	poor	poor	ADJ
ajst-31210	13	21	during	during	ADP
ajst-31210	13	22	rice	rice	NOUN
ajst-31210	13	23	seedling	seedling	NOUN
ajst-31210	13	24	cultivation	cultivation	NOUN
ajst-31210	13	25	,	,	PUNCT
ajst-31210	13	26	it	it	PRON
ajst-31210	13	27	will	will	AUX
ajst-31210	13	28	lead	lead	VERB
ajst-31210	13	29	to	to	ADP
ajst-31210	13	30	uneven	uneven	ADJ
ajst-31210	13	31	seedling	seedling	NOUN
ajst-31210	13	32	picking	picking	NOUN
ajst-31210	13	33	by	by	ADP
ajst-31210	13	34	the	the	DET
ajst-31210	13	35	transplanter	transplanter	NOUN
ajst-31210	13	36	during	during	ADP
ajst-31210	13	37	the	the	DET
ajst-31210	13	38	transplanting	transplant	VERB
ajst-31210	13	39	process	process	NOUN
ajst-31210	13	40	;	;	PUNCT
ajst-31210	13	41	if	if	SCONJ
ajst-31210	13	42	there	there	PRON
ajst-31210	13	43	is	be	VERB
ajst-31210	13	44	a	a	DET
ajst-31210	13	45	missed	miss	VERB
ajst-31210	13	46	sowing	sowing	NOUN
ajst-31210	13	47	in	in	ADP
ajst-31210	13	48	the	the	DET
ajst-31210	13	49	seedling	seedling	NOUN
ajst-31210	13	50	tray	tray	NOUN
ajst-31210	13	51	,	,	PUNCT
ajst-31210	13	52	it	it	PRON
ajst-31210	13	53	will	will	AUX
ajst-31210	13	54	cause	cause	VERB
ajst-31210	13	55	a	a	DET
ajst-31210	13	56	missed	miss	VERB
ajst-31210	13	57	insertion	insertion	NOUN
ajst-31210	13	58	phenomenon	phenomenon	NOUN
ajst-31210	13	59	;	;	PUNCT
ajst-31210	13	60	if	if	SCONJ
ajst-31210	13	61	the	the	DET
ajst-31210	13	62	proportion	proportion	NOUN
ajst-31210	13	63	of	of	ADP
ajst-31210	13	64	voids	voids	NOUN
ajst-31210	13	65	is	be	AUX
ajst-31210	13	66	high	high	ADJ
ajst-31210	13	67	,	,	PUNCT
ajst-31210	13	68	it	it	PRON
ajst-31210	13	69	will	will	AUX
ajst-31210	13	70	ultimately	ultimately	ADV
ajst-31210	13	71	lead	lead	VERB
ajst-31210	13	72	to	to	ADP
ajst-31210	13	73	a	a	DET
ajst-31210	13	74	decrease	decrease	NOUN
ajst-31210	13	75	in	in	ADP
ajst-31210	13	76	rice	rice	NOUN
ajst-31210	13	77	yield	yield	NOUN
ajst-31210	13	78	.	.	PUNCT
ajst-31210	14	1	for	for	ADP
ajst-31210	14	2	super	super	ADJ
ajst-31210	14	3	rice	rice	NOUN
ajst-31210	14	4	,	,	PUNCT
ajst-31210	14	5	the	the	DET
ajst-31210	14	6	number	number	NOUN
ajst-31210	14	7	of	of	ADP
ajst-31210	14	8	seedlings	seedling	NOUN
ajst-31210	14	9	used	use	VERB
ajst-31210	14	10	per	per	ADP
ajst-31210	14	11	hole	hole	NOUN
ajst-31210	14	12	is	be	AUX
ajst-31210	14	13	small	small	ADJ
ajst-31210	14	14	,	,	PUNCT
ajst-31210	14	15	and	and	CCONJ
ajst-31210	14	16	the	the	DET
ajst-31210	14	17	number	number	NOUN
ajst-31210	14	18	of	of	ADP
ajst-31210	14	19	seeds	seed	NOUN
ajst-31210	14	20	sown	sow	VERB
ajst-31210	14	21	is	be	AUX
ajst-31210	14	22	also	also	ADV
ajst-31210	14	23	small	small	ADJ
ajst-31210	14	24	.	.	PUNCT
ajst-31210	15	1	therefore	therefore	ADV
ajst-31210	15	2	,	,	PUNCT
ajst-31210	15	3	high	high	ADJ
ajst-31210	15	4	sowing	sowing	NOUN
ajst-31210	15	5	accuracy	accuracy	NOUN
ajst-31210	15	6	and	and	CCONJ
ajst-31210	15	7	low	low	ADJ
ajst-31210	15	8	hole	hole	NOUN
ajst-31210	15	9	rate	rate	NOUN
ajst-31210	15	10	are	be	AUX
ajst-31210	15	11	required	require	VERB
ajst-31210	15	12	for	for	ADP
ajst-31210	15	13	mechanized	mechanized	ADJ
ajst-31210	15	14	seedling	seedling	NOUN
ajst-31210	15	15	cultivation	cultivation	NOUN
ajst-31210	15	16	and	and	CCONJ
ajst-31210	15	17	sowing	sowing	NOUN
ajst-31210	15	18	.	.	PUNCT
ajst-31210	16	1	therefore	therefore	ADV
ajst-31210	16	2	,	,	PUNCT
ajst-31210	16	3	to	to	PART
ajst-31210	16	4	ensure	ensure	VERB
ajst-31210	16	5	the	the	DET
ajst-31210	16	6	quality	quality	NOUN
ajst-31210	16	7	of	of	ADP
ajst-31210	16	8	seedling	seedle	VERB
ajst-31210	16	9	cultivation	cultivation	NOUN
ajst-31210	16	10	,	,	PUNCT
ajst-31210	16	11	the	the	DET
ajst-31210	16	12	first	first	ADJ
ajst-31210	16	13	step	step	NOUN
ajst-31210	16	14	is	be	AUX
ajst-31210	16	15	to	to	PART
ajst-31210	16	16	test	test	VERB
ajst-31210	16	17	the	the	DET
ajst-31210	16	18	density	density	NOUN
ajst-31210	16	19	and	and	CCONJ
ajst-31210	16	20	quantity	quantity	NOUN
ajst-31210	16	21	of	of	ADP
ajst-31210	16	22	rice	rice	NOUN
ajst-31210	16	23	seeds	seed	NOUN
ajst-31210	16	24	in	in	ADP
ajst-31210	16	25	the	the	DET
ajst-31210	16	26	seedling	seedling	NOUN
ajst-31210	16	27	tray	tray	NOUN
ajst-31210	16	28	.	.	PUNCT
ajst-31210	17	1	rice	rice	NOUN
ajst-31210	17	2	seed	seed	NOUN
ajst-31210	17	3	counting	counting	NOUN
ajst-31210	17	4	is	be	AUX
ajst-31210	17	5	an	an	DET
ajst-31210	17	6	important	important	ADJ
ajst-31210	17	7	research	research	NOUN
ajst-31210	17	8	direction	direction	NOUN
ajst-31210	17	9	in	in	ADP
ajst-31210	17	10	the	the	DET
ajst-31210	17	11	field	field	NOUN
ajst-31210	17	12	of	of	ADP
ajst-31210	17	13	agricultural	agricultural	ADJ
ajst-31210	17	14	technology	technology	NOUN
ajst-31210	17	15	,	,	PUNCT
ajst-31210	17	16	aimed	aim	VERB
ajst-31210	17	17	at	at	ADP
ajst-31210	17	18	improving	improve	VERB
ajst-31210	17	19	harvesting	harvesting	NOUN
ajst-31210	17	20	efficiency	efficiency	NOUN
ajst-31210	17	21	and	and	CCONJ
ajst-31210	17	22	grain	grain	NOUN
ajst-31210	17	23	yield	yield	NOUN
ajst-31210	17	24	by	by	ADP
ajst-31210	17	25	accurately	accurately	ADV
ajst-31210	17	26	measuring	measure	VERB
ajst-31210	17	27	the	the	DET
ajst-31210	17	28	quantity	quantity	NOUN
ajst-31210	17	29	of	of	ADP
ajst-31210	17	30	rice	rice	NOUN
ajst-31210	17	31	grains	grain	NOUN
ajst-31210	17	32	.	.	PUNCT
ajst-31210	18	1	at	at	ADP
ajst-31210	18	2	present	present	ADJ
ajst-31210	18	3	,	,	PUNCT
ajst-31210	18	4	there	there	PRON
ajst-31210	18	5	are	be	VERB
ajst-31210	18	6	some	some	DET
ajst-31210	18	7	research	research	NOUN
ajst-31210	18	8	results	result	NOUN
ajst-31210	18	9	on	on	ADP
ajst-31210	18	10	rice	rice	NOUN
ajst-31210	18	11	seed	seed	NOUN
ajst-31210	18	12	counting	counting	NOUN
ajst-31210	18	13	abroad	abroad	ADV
ajst-31210	18	14	.	.	PUNCT
ajst-31210	19	1	with	with	ADP
ajst-31210	19	2	the	the	DET
ajst-31210	19	3	gradual	gradual	ADJ
ajst-31210	19	4	maturity	maturity	NOUN
ajst-31210	19	5	of	of	ADP
ajst-31210	19	6	computer	computer	NOUN
ajst-31210	19	7	vision	vision	NOUN
ajst-31210	19	8	and	and	CCONJ
ajst-31210	19	9	image	image	NOUN
ajst-31210	19	10	processing	processing	NOUN
ajst-31210	19	11	technology	technology	NOUN
ajst-31210	19	12	,	,	PUNCT
ajst-31210	19	13	image	image	NOUN
ajst-31210	19	14	recognition	recognition	NOUN
ajst-31210	19	15	,	,	PUNCT
ajst-31210	19	16	morphological	morphological	ADJ
ajst-31210	19	17	parameter	parameter	NOUN
ajst-31210	19	18	measurement	measurement	NOUN
ajst-31210	19	19	,	,	PUNCT
ajst-31210	19	20	particle	particle	NOUN
ajst-31210	19	21	counting	counting	NOUN
ajst-31210	19	22	,	,	PUNCT
ajst-31210	19	23	and	and	CCONJ
ajst-31210	19	24	other	other	ADJ
ajst-31210	19	25	applications	application	NOUN
ajst-31210	19	26	have	have	AUX
ajst-31210	19	27	been	be	AUX
ajst-31210	19	28	applied	apply	VERB
ajst-31210	19	29	in	in	ADP
ajst-31210	19	30	crop	crop	NOUN
ajst-31210	19	31	breeding	breeding	NOUN
ajst-31210	19	32	,	,	PUNCT
ajst-31210	19	33	quality	quality	NOUN
ajst-31210	19	34	identification	identification	NOUN
ajst-31210	19	35	,	,	PUNCT
ajst-31210	19	36	and	and	CCONJ
ajst-31210	19	37	other	other	ADJ
ajst-31210	19	38	fields	field	NOUN
ajst-31210	19	39	.	.	PUNCT
ajst-31210	20	1	at	at	ADP
ajst-31210	20	2	the	the	DET
ajst-31210	20	3	same	same	ADJ
ajst-31210	20	4	time	time	NOUN
ajst-31210	20	5	,	,	PUNCT
ajst-31210	20	6	utilizing	utilize	VERB
ajst-31210	20	7	the	the	DET
ajst-31210	20	8	powerful	powerful	ADJ
ajst-31210	20	9	computing	computing	NOUN
ajst-31210	20	10	software	software	NOUN
ajst-31210	20	11	matlab	matlab	PROPN
ajst-31210	20	12	matrix	matrix	NOUN
ajst-31210	20	13	lab	lab	NOUN
ajst-31210	20	14	,	,	PUNCT
ajst-31210	20	15	image	image	NOUN
ajst-31210	20	16	processing	processing	NOUN
ajst-31210	20	17	such	such	ADJ
ajst-31210	20	18	as	as	ADP
ajst-31210	20	19	image	image	NOUN
ajst-31210	20	20	display	display	NOUN
ajst-31210	20	21	and	and	CCONJ
ajst-31210	20	22	color	color	NOUN
ajst-31210	20	23	space	space	NOUN
ajst-31210	20	24	transformation	transformation	NOUN
ajst-31210	20	25	can	can	AUX
ajst-31210	20	26	be	be	AUX
ajst-31210	20	27	achieved	achieve	VERB
ajst-31210	20	28	.	.	PUNCT
ajst-31210	21	1	in	in	ADP
ajst-31210	21	2	terms	term	NOUN
ajst-31210	21	3	of	of	ADP
ajst-31210	21	4	grain	grain	NOUN
ajst-31210	21	5	counting	counting	NOUN
ajst-31210	21	6	,	,	PUNCT
ajst-31210	21	7	jia	jia	PROPN
ajst-31210	21	8	peng	peng	PROPN
ajst-31210	21	9	,	,	PUNCT
ajst-31210	21	10	li	li	PROPN
ajst-31210	21	11	yongkui	yongkui	PROPN
ajst-31210	21	12	,	,	PUNCT
ajst-31210	21	13	and	and	CCONJ
ajst-31210	21	14	others	other	NOUN
ajst-31210	21	15	used	use	VERB
ajst-31210	21	16	matlab	matlab	PROPN
ajst-31210	21	17	grayscale	grayscale	NOUN
ajst-31210	21	18	processing	processing	NOUN
ajst-31210	21	19	,	,	PUNCT
ajst-31210	21	20	noise	noise	NOUN
ajst-31210	21	21	filtering	filtering	NOUN
ajst-31210	21	22	,	,	PUNCT
ajst-31210	21	23	and	and	CCONJ
ajst-31210	21	24	binarization	binarization	NOUN
ajst-31210	21	25	processing	processing	NOUN
ajst-31210	21	26	to	to	PART
ajst-31210	21	27	achieve	achieve	VERB
ajst-31210	21	28	counting	counting	NOUN
ajst-31210	21	29	during	during	ADP
ajst-31210	21	30	the	the	DET
ajst-31210	21	31	seed	seed	NOUN
ajst-31210	21	32	inspection	inspection	NOUN
ajst-31210	21	33	process	process	NOUN
ajst-31210	21	34	.	.	PUNCT
ajst-31210	22	1	their	their	PRON
ajst-31210	22	2	results	result	NOUN
ajst-31210	22	3	showed	show	VERB
ajst-31210	22	4	that	that	SCONJ
ajst-31210	22	5	the	the	DET
ajst-31210	22	6	technical	technical	ADJ
ajst-31210	22	7	accuracy	accuracy	NOUN
ajst-31210	22	8	of	of	ADP
ajst-31210	22	9	grains	grain	NOUN
ajst-31210	22	10	in	in	ADP
ajst-31210	22	11	the	the	DET
ajst-31210	22	12	unpressed	unpressed	ADJ
ajst-31210	22	13	state	state	NOUN
ajst-31210	22	14	could	could	AUX
ajst-31210	22	15	reach	reach	VERB
ajst-31210	22	16	100	100	NUM
ajst-31210	22	17	%	%	NOUN
ajst-31210	23	1	[	[	X
ajst-31210	23	2	3	3	NUM
ajst-31210	23	3	]	]	PUNCT
ajst-31210	23	4	.	.	PUNCT
ajst-31210	24	1	tian	tian	PROPN
ajst-31210	24	2	mengxiang	mengxiang	PROPN
ajst-31210	24	3	and	and	CCONJ
ajst-31210	24	4	others	other	NOUN
ajst-31210	24	5	also	also	ADV
ajst-31210	24	6	used	use	VERB
ajst-31210	24	7	matlab	matlab	PROPN
ajst-31210	24	8	to	to	PART
ajst-31210	24	9	perform	perform	VERB
ajst-31210	24	10	grayscale	grayscale	NOUN
ajst-31210	24	11	processing	processing	NOUN
ajst-31210	24	12	,	,	PUNCT
ajst-31210	24	13	image	image	NOUN
ajst-31210	24	14	denoising	denoising	NOUN
ajst-31210	24	15	,	,	PUNCT
ajst-31210	24	16	image	image	NOUN
ajst-31210	24	17	segmentation	segmentation	NOUN
ajst-31210	24	18	,	,	PUNCT
ajst-31210	24	19	and	and	CCONJ
ajst-31210	24	20	other	other	ADJ
ajst-31210	24	21	operations	operation	NOUN
ajst-31210	24	22	on	on	ADP
ajst-31210	24	23	rice	rice	NOUN
ajst-31210	24	24	grain	grain	NOUN
ajst-31210	24	25	images	image	NOUN
ajst-31210	24	26	.	.	PUNCT
ajst-31210	25	1	in	in	ADP
ajst-31210	25	2	addition	addition	NOUN
ajst-31210	25	3	,	,	PUNCT
ajst-31210	25	4	distance	distance	NOUN
ajst-31210	25	5	transformation	transformation	NOUN
ajst-31210	25	6	was	be	AUX
ajst-31210	25	7	performed	perform	VERB
ajst-31210	25	8	to	to	PART
ajst-31210	25	9	reduce	reduce	VERB
ajst-31210	25	10	the	the	DET
ajst-31210	25	11	size	size	NOUN
ajst-31210	25	12	of	of	ADP
ajst-31210	25	13	each	each	DET
ajst-31210	25	14	grain	grain	NOUN
ajst-31210	25	15	using	use	VERB
ajst-31210	25	16	local	local	ADJ
ajst-31210	25	17	minima	minima	NOUN
ajst-31210	25	18	,	,	PUNCT
ajst-31210	25	19	so	so	SCONJ
ajst-31210	25	20	as	as	SCONJ
ajst-31210	25	21	to	to	PART
ajst-31210	25	22	separate	separate	VERB
ajst-31210	25	23	the	the	DET
ajst-31210	25	24	adhered	adhere	VERB
ajst-31210	25	25	grains	grain	NOUN
ajst-31210	25	26	and	and	CCONJ
ajst-31210	25	27	ensure	ensure	VERB
ajst-31210	25	28	the	the	DET
ajst-31210	25	29	accuracy	accuracy	NOUN
ajst-31210	25	30	of	of	ADP
ajst-31210	25	31	grain	grain	NOUN
ajst-31210	25	32	counting	counting	NOUN
ajst-31210	25	33	.	.	PUNCT
ajst-31210	26	1	the	the	DET
ajst-31210	26	2	final	final	ADJ
ajst-31210	26	3	count	count	NOUN
ajst-31210	26	4	of	of	ADP
ajst-31210	26	5	connected	connect	VERB
ajst-31210	26	6	domains	domain	NOUN
ajst-31210	26	7	is	be	AUX
ajst-31210	26	8	the	the	DET
ajst-31210	26	9	number	number	NOUN
ajst-31210	26	10	of	of	ADP
ajst-31210	26	11	grains	grain	NOUN
ajst-31210	26	12	.	.	PUNCT
ajst-31210	27	1	both	both	DET
ajst-31210	27	2	single	single	ADJ
ajst-31210	27	3	and	and	CCONJ
ajst-31210	27	4	sticky	sticky	ADJ
ajst-31210	27	5	rice	rice	NOUN
ajst-31210	27	6	grains	grain	NOUN
ajst-31210	27	7	can	can	AUX
ajst-31210	27	8	be	be	AUX
ajst-31210	27	9	accurately	accurately	ADV
ajst-31210	27	10	and	and	CCONJ
ajst-31210	27	11	automatically	automatically	ADV
ajst-31210	27	12	counted	count	VERB
ajst-31210	27	13	,	,	PUNCT
ajst-31210	27	14	with	with	ADP
ajst-31210	27	15	an	an	DET
ajst-31210	27	16	accuracy	accuracy	NOUN
ajst-31210	27	17	rate	rate	NOUN
ajst-31210	27	18	of	of	ADP
ajst-31210	27	19	up	up	ADP
ajst-31210	27	20	to	to	PART
ajst-31210	27	21	100	100	NUM
ajst-31210	27	22	%	%	NOUN
ajst-31210	27	23	[	[	X
ajst-31210	27	24	4	4	NUM
ajst-31210	27	25	]	]	PUNCT
ajst-31210	27	26	.	.	PUNCT
ajst-31210	28	1	ma	ma	PROPN
ajst-31210	28	2	xu	xu	PROPN
ajst-31210	28	3	et	et	PROPN
ajst-31210	28	4	al	al	PROPN
ajst-31210	28	5	.	.	PUNCT
ajst-31210	29	1	[	[	X
ajst-31210	29	2	5	5	NUM
ajst-31210	29	3	]	]	PUNCT
ajst-31210	29	4	used	use	VERB
ajst-31210	29	5	convolutional	convolutional	ADJ
ajst-31210	29	6	neural	neural	ADJ
ajst-31210	29	7	networks	network	NOUN
ajst-31210	29	8	(	(	PUNCT
ajst-31210	29	9	cnn	cnn	PROPN
ajst-31210	29	10	)	)	PUNCT
ajst-31210	29	11	to	to	PART
ajst-31210	29	12	detect	detect	VERB
ajst-31210	29	13	the	the	DET
ajst-31210	29	14	seeding	seeding	NOUN
ajst-31210	29	15	amount	amount	NOUN
ajst-31210	29	16	of	of	ADP
ajst-31210	29	17	rice	rice	NOUN
ajst-31210	29	18	bowl	bowl	NOUN
ajst-31210	29	19	floppy	floppy	ADJ
ajst-31210	29	20	disks	disk	NOUN
ajst-31210	29	21	.	.	PUNCT
ajst-31210	30	1	they	they	PRON
ajst-31210	30	2	divided	divide	VERB
ajst-31210	30	3	the	the	DET
ajst-31210	30	4	bowl	bowl	NOUN
ajst-31210	30	5	floppy	floppy	ADJ
ajst-31210	30	6	disks	disk	NOUN
ajst-31210	30	7	into	into	ADP
ajst-31210	30	8	single	single	ADJ
ajst-31210	30	9	hole	hole	NOUN
ajst-31210	30	10	images	image	NOUN
ajst-31210	30	11	using	use	VERB
ajst-31210	30	12	grids	grid	NOUN
ajst-31210	30	13	,	,	PUNCT
ajst-31210	30	14	and	and	CCONJ
ajst-31210	30	15	then	then	ADV
ajst-31210	30	16	classified	classify	VERB
ajst-31210	30	17	the	the	DET
ajst-31210	30	18	number	number	NOUN
ajst-31210	30	19	of	of	ADP
ajst-31210	30	20	rice	rice	NOUN
ajst-31210	30	21	seeds	seed	NOUN
ajst-31210	30	22	,	,	PUNCT
ajst-31210	30	23	simplifying	simplify	VERB
ajst-31210	30	24	the	the	DET
ajst-31210	30	25	problem	problem	NOUN
ajst-31210	30	26	of	of	ADP
ajst-31210	30	27	rice	rice	NOUN
ajst-31210	30	28	seed	seed	NOUN
ajst-31210	30	29	quantity	quantity	NOUN
ajst-31210	30	30	into	into	ADP
ajst-31210	30	31	a	a	DET
ajst-31210	30	32	classification	classification	NOUN
ajst-31210	30	33	problem	problem	NOUN
ajst-31210	30	34	.	.	PUNCT
ajst-31210	31	1	steven	steven	PROPN
ajst-31210	31	2	w.	w.	PROPN
ajst-31210	31	3	chen	chen	PROPN
ajst-31210	31	4	et	et	PROPN
ajst-31210	31	5	al	al	PROPN
ajst-31210	31	6	.	.	PUNCT
ajst-31210	32	1	[	[	X
ajst-31210	32	2	6	6	NUM
ajst-31210	32	3	]	]	PUNCT
ajst-31210	32	4	(	(	PUNCT
ajst-31210	32	5	2017	2017	NUM
ajst-31210	32	6	)	)	PUNCT
ajst-31210	32	7	used	use	VERB
ajst-31210	32	8	deep	deep	ADJ
ajst-31210	32	9	learning	learning	NOUN
ajst-31210	32	10	to	to	PART
ajst-31210	32	11	extract	extract	VERB
ajst-31210	32	12	candidate	candidate	NOUN
ajst-31210	32	13	regions	region	NOUN
ajst-31210	32	14	from	from	ADP
ajst-31210	32	15	the	the	DET
ajst-31210	32	16	image	image	NOUN
ajst-31210	32	17	of	of	ADP
ajst-31210	32	18	fruits	fruit	NOUN
ajst-31210	32	19	using	use	VERB
ajst-31210	32	20	a	a	DET
ajst-31210	32	21	half	half	ADJ
ajst-31210	32	22	point	point	NOUN
ajst-31210	32	23	detector	detector	NOUN
ajst-31210	32	24	with	with	ADP
ajst-31210	32	25	a	a	DET
ajst-31210	32	26	fully	fully	ADV
ajst-31210	32	27	convolutional	convolutional	ADJ
ajst-31210	32	28	network	network	NOUN
ajst-31210	32	29	.	.	PUNCT
ajst-31210	33	1	they	they	PRON
ajst-31210	33	2	then	then	ADV
ajst-31210	33	3	estimated	estimate	VERB
ajst-31210	33	4	the	the	DET
ajst-31210	33	5	number	number	NOUN
ajst-31210	33	6	of	of	ADP
ajst-31210	33	7	fruits	fruit	NOUN
ajst-31210	33	8	in	in	ADP
ajst-31210	33	9	each	each	DET
ajst-31210	33	10	region	region	NOUN
ajst-31210	33	11	using	use	VERB
ajst-31210	33	12	the	the	DET
ajst-31210	33	13	algorithm	algorithm	NOUN
ajst-31210	33	14	of	of	ADP
ajst-31210	33	15	a	a	DET
ajst-31210	33	16	second	second	ADJ
ajst-31210	33	17	convolutional	convolutional	ADJ
ajst-31210	33	18	network	network	NOUN
ajst-31210	33	19	.	.	PUNCT
ajst-31210	34	1	finally	finally	ADV
ajst-31210	34	2	,	,	PUNCT
ajst-31210	34	3	a	a	DET
ajst-31210	34	4	linear	linear	ADJ
ajst-31210	34	5	regression	regression	NOUN
ajst-31210	34	6	model	model	NOUN
ajst-31210	34	7	was	be	AUX
ajst-31210	34	8	used	use	VERB
ajst-31210	34	9	to	to	PART
ajst-31210	34	10	count	count	VERB
ajst-31210	34	11	the	the	DET
ajst-31210	34	12	total	total	ADJ
ajst-31210	34	13	number	number	NOUN
ajst-31210	34	14	of	of	ADP
ajst-31210	34	15	fruits	fruit	NOUN
ajst-31210	34	16	,	,	PUNCT
ajst-31210	34	17	achieving	achieve	VERB
ajst-31210	34	18	the	the	DET
ajst-31210	34	19	ability	ability	NOUN
ajst-31210	34	20	to	to	PART
ajst-31210	34	21	count	count	VERB
ajst-31210	34	22	different	different	ADJ
ajst-31210	34	23	types	type	NOUN
ajst-31210	34	24	of	of	ADP
ajst-31210	34	25	fruits	fruit	NOUN
ajst-31210	34	26	under	under	ADP
ajst-31210	34	27	uncontrollable	uncontrollable	ADJ
ajst-31210	34	28	light	light	ADJ
ajst-31210	34	29	exposure	exposure	NOUN
ajst-31210	34	30	and	and	CCONJ
ajst-31210	34	31	high	high	ADJ
ajst-31210	34	32	occlusion	occlusion	NOUN
ajst-31210	34	33	.	.	PUNCT
ajst-31210	35	1	this	this	DET
ajst-31210	35	2	design	design	NOUN
ajst-31210	35	3	uses	use	VERB
ajst-31210	35	4	the	the	DET
ajst-31210	35	5	classic	classic	ADJ
ajst-31210	35	6	network	network	NOUN
ajst-31210	35	7	model	model	NOUN
ajst-31210	35	8	of	of	ADP
ajst-31210	35	9	deep	deep	ADJ
ajst-31210	35	10	learning	learning	NOUN
ajst-31210	35	11	for	for	ADP
ajst-31210	35	12	crowd	crowd	NOUN
ajst-31210	35	13	counting	counting	NOUN
ajst-31210	35	14	tasks	task	NOUN
ajst-31210	35	15	,	,	PUNCT
ajst-31210	35	16	multi	multi	ADJ
ajst-31210	35	17	scale	scale	NOUN
ajst-31210	35	18	convolutional	convolutional	ADJ
ajst-31210	35	19	neural	neural	ADJ
ajst-31210	35	20	networks	network	NOUN
ajst-31210	35	21	(	(	PUNCT
ajst-31210	35	22	mcnn	mcnn	NOUN
ajst-31210	35	23	)	)	PUNCT
ajst-31210	35	24	,	,	PUNCT
ajst-31210	35	25	to	to	PART
ajst-31210	35	26	estimate	estimate	VERB
ajst-31210	35	27	the	the	DET
ajst-31210	35	28	density	density	NOUN
ajst-31210	35	29	of	of	ADP
ajst-31210	35	30	targets	target	NOUN
ajst-31210	35	31	in	in	ADP
ajst-31210	35	32	input	input	NOUN
ajst-31210	35	33	images	image	NOUN
ajst-31210	35	34	,	,	PUNCT
ajst-31210	35	35	and	and	CCONJ
ajst-31210	35	36	the	the	DET
ajst-31210	35	37	quantity	quantity	NOUN
ajst-31210	35	38	can	can	AUX
ajst-31210	35	39	be	be	AUX
ajst-31210	35	40	obtained	obtain	VERB
ajst-31210	35	41	through	through	ADP
ajst-31210	35	42	integration	integration	NOUN
ajst-31210	35	43	.	.	PUNCT
ajst-31210	36	1	this	this	DET
ajst-31210	36	2	method	method	NOUN
ajst-31210	36	3	can	can	AUX
ajst-31210	36	4	better	well	ADV
ajst-31210	36	5	adapt	adapt	VERB
ajst-31210	36	6	to	to	ADP
ajst-31210	36	7	different	different	ADJ
ajst-31210	36	8	objectives	objective	NOUN
ajst-31210	36	9	,	,	PUNCT
ajst-31210	36	10	enhance	enhance	VERB
ajst-31210	36	11	the	the	DET
ajst-31210	36	12	applicability	applicability	NOUN
ajst-31210	36	13	of	of	ADP
ajst-31210	36	14	the	the	DET
ajst-31210	36	15	model	model	NOUN
ajst-31210	36	16	,	,	PUNCT
ajst-31210	36	17	and	and	CCONJ
ajst-31210	36	18	at	at	ADP
ajst-31210	36	19	the	the	DET
ajst-31210	36	20	same	same	ADJ
ajst-31210	36	21	time	time	NOUN
ajst-31210	36	22	,	,	PUNCT
ajst-31210	36	23	the	the	DET
ajst-31210	36	24	density	density	NOUN
ajst-31210	36	25	map	map	NOUN
ajst-31210	36	26	can	can	AUX
ajst-31210	36	27	provide	provide	VERB
ajst-31210	36	28	more	more	ADJ
ajst-31210	36	29	information	information	NOUN
ajst-31210	36	30	for	for	ADP
ajst-31210	36	31	operators	operator	NOUN
ajst-31210	36	32	.	.	PUNCT
ajst-31210	37	1	however	however	ADV
ajst-31210	37	2	,	,	PUNCT
ajst-31210	37	3	mcnn	mcnn	PROPN
ajst-31210	37	4	estimates	estimate	VERB
ajst-31210	37	5	the	the	DET
ajst-31210	37	6	target	target	NOUN
ajst-31210	37	7	density	density	NOUN
ajst-31210	37	8	of	of	ADP
ajst-31210	37	9	each	each	DET
ajst-31210	37	10	small	small	ADJ
ajst-31210	37	11	unit	unit	NOUN
ajst-31210	37	12	in	in	ADP
ajst-31210	37	13	the	the	DET
ajst-31210	37	14	image	image	NOUN
ajst-31210	37	15	based	base	VERB
ajst-31210	37	16	on	on	ADP
ajst-31210	37	17	regression	regression	NOUN
ajst-31210	37	18	training	training	NOUN
ajst-31210	37	19	to	to	PART
ajst-31210	37	20	obtain	obtain	VERB
ajst-31210	37	21	the	the	DET
ajst-31210	37	22	number	number	NOUN
ajst-31210	37	23	of	of	ADP
ajst-31210	37	24	targets	target	NOUN
ajst-31210	37	25	in	in	ADP
ajst-31210	37	26	the	the	DET
ajst-31210	37	27	entire	entire	ADJ
ajst-31210	37	28	image	image	NOUN
ajst-31210	37	29	,	,	PUNCT
ajst-31210	37	30	without	without	ADP
ajst-31210	37	31	directly	directly	ADV
ajst-31210	37	32	detecting	detect	VERB
ajst-31210	37	33	the	the	DET
ajst-31210	37	34	number	number	NOUN
ajst-31210	37	35	of	of	ADP
ajst-31210	37	36	targets	target	NOUN
ajst-31210	37	37	in	in	ADP
ajst-31210	37	38	the	the	DET
ajst-31210	37	39	entire	entire	ADJ
ajst-31210	37	40	image	image	NOUN
ajst-31210	37	41	.	.	PUNCT
ajst-31210	38	1	for	for	ADP
ajst-31210	38	2	the	the	DET
ajst-31210	38	3	scenario	scenario	NOUN
ajst-31210	38	4	of	of	ADP
ajst-31210	38	5	using	use	VERB
ajst-31210	38	6	seedling	seedling	NOUN
ajst-31210	38	7	trays	tray	NOUN
ajst-31210	38	8	,	,	PUNCT
ajst-31210	38	9	the	the	DET
ajst-31210	38	10	density	density	NOUN
ajst-31210	38	11	map	map	NOUN
ajst-31210	38	12	can	can	AUX
ajst-31210	38	13	be	be	AUX
ajst-31210	38	14	used	use	VERB
ajst-31210	38	15	to	to	PART
ajst-31210	38	16	discover	discover	VERB
ajst-31210	38	17	whether	whether	SCONJ
ajst-31210	38	18	the	the	DET
ajst-31210	38	19	distribution	distribution	NOUN
ajst-31210	38	20	of	of	ADP
ajst-31210	38	21	rice	rice	NOUN
ajst-31210	38	22	seeds	seed	NOUN
ajst-31210	38	23	is	be	AUX
ajst-31210	38	24	reasonable	reasonable	ADJ
ajst-31210	38	25	,	,	PUNCT
ajst-31210	38	26	which	which	PRON
ajst-31210	38	27	facilitates	facilitate	VERB
ajst-31210	38	28	the	the	DET
ajst-31210	38	29	full	full	ADJ
ajst-31210	38	30	utilization	utilization	NOUN
ajst-31210	38	31	of	of	ADP
ajst-31210	38	32	each	each	DET
ajst-31210	38	33	74	74	NUM
ajst-31210	38	34	seedling	seedling	NOUN
ajst-31210	38	35	tray	tray	NOUN
ajst-31210	38	36	while	while	SCONJ
ajst-31210	38	37	ensuring	ensure	VERB
ajst-31210	38	38	the	the	DET
ajst-31210	38	39	normal	normal	ADJ
ajst-31210	38	40	development	development	NOUN
ajst-31210	38	41	space	space	NOUN
ajst-31210	38	42	of	of	ADP
ajst-31210	38	43	rice	rice	NOUN
ajst-31210	38	44	seeds	seed	NOUN
ajst-31210	38	45	.	.	PUNCT
ajst-31210	39	1	2	2	X
ajst-31210	39	2	.	.	X
ajst-31210	39	3	materials	material	NOUN
ajst-31210	39	4	and	and	CCONJ
ajst-31210	39	5	methods	method	NOUN
ajst-31210	39	6	2.1	2.1	NUM
ajst-31210	39	7	.	.	PUNCT
ajst-31210	40	1	image	image	NOUN
ajst-31210	40	2	acquisition	acquisition	NOUN
ajst-31210	40	3	and	and	CCONJ
ajst-31210	40	4	annotation	annotation	NOUN
ajst-31210	40	5	2.1.1	2.1.1	NUM
ajst-31210	40	6	.	.	PUNCT
ajst-31210	41	1	dataset	dataset	VERB
ajst-31210	41	2	due	due	ADP
ajst-31210	41	3	to	to	ADP
ajst-31210	41	4	the	the	DET
ajst-31210	41	5	original	original	ADJ
ajst-31210	41	6	image	image	NOUN
ajst-31210	41	7	resolution	resolution	NOUN
ajst-31210	41	8	of	of	ADP
ajst-31210	41	9	3648	3648	NUM
ajst-31210	41	10	pixels	pixel	NOUN
ajst-31210	41	11	to	to	ADP
ajst-31210	41	12	2736	2736	NUM
ajst-31210	41	13	pixels	pixel	NOUN
ajst-31210	41	14	in	in	ADP
ajst-31210	41	15	the	the	DET
ajst-31210	41	16	dataset	dataset	NOUN
ajst-31210	41	17	,	,	PUNCT
ajst-31210	41	18	even	even	ADV
ajst-31210	41	19	if	if	SCONJ
ajst-31210	41	20	the	the	DET
ajst-31210	41	21	original	original	ADJ
ajst-31210	41	22	image	image	NOUN
ajst-31210	41	23	is	be	AUX
ajst-31210	41	24	cut	cut	VERB
ajst-31210	41	25	to	to	ADP
ajst-31210	41	26	a	a	DET
ajst-31210	41	27	size	size	NOUN
ajst-31210	41	28	suitable	suitable	ADJ
ajst-31210	41	29	for	for	ADP
ajst-31210	41	30	annotation	annotation	NOUN
ajst-31210	41	31	data	datum	NOUN
ajst-31210	41	32	,	,	PUNCT
ajst-31210	41	33	the	the	DET
ajst-31210	41	34	resolution	resolution	NOUN
ajst-31210	41	35	is	be	AUX
ajst-31210	41	36	still	still	ADV
ajst-31210	41	37	608	608	NUM
ajst-31210	41	38	pixels	pixel	NOUN
ajst-31210	41	39	to	to	ADP
ajst-31210	41	40	684	684	NUM
ajst-31210	41	41	pixels	pixel	NOUN
ajst-31210	41	42	.	.	PUNCT
ajst-31210	42	1	the	the	DET
ajst-31210	42	2	size	size	NOUN
ajst-31210	42	3	of	of	ADP
ajst-31210	42	4	the	the	DET
ajst-31210	42	5	ground_truth	ground_truth	PROPN
ajst-31210	42	6	and	and	CCONJ
ajst-31210	42	7	h5	h5	PROPN
ajst-31210	42	8	files	file	NOUN
ajst-31210	42	9	generated	generate	VERB
ajst-31210	42	10	during	during	ADP
ajst-31210	42	11	training	training	NOUN
ajst-31210	42	12	is	be	AUX
ajst-31210	42	13	tied	tie	VERB
ajst-31210	42	14	to	to	ADP
ajst-31210	42	15	the	the	DET
ajst-31210	42	16	resolution	resolution	NOUN
ajst-31210	42	17	,	,	PUNCT
ajst-31210	42	18	and	and	CCONJ
ajst-31210	42	19	the	the	DET
ajst-31210	42	20	image	image	NOUN
ajst-31210	42	21	resolution	resolution	NOUN
ajst-31210	42	22	needs	need	VERB
ajst-31210	42	23	to	to	PART
ajst-31210	42	24	be	be	AUX
ajst-31210	42	25	reduced	reduce	VERB
ajst-31210	42	26	again	again	ADV
ajst-31210	42	27	.	.	PUNCT
ajst-31210	43	1	due	due	ADP
ajst-31210	43	2	to	to	ADP
ajst-31210	43	3	the	the	DET
ajst-31210	43	4	original	original	ADJ
ajst-31210	43	5	image	image	NOUN
ajst-31210	43	6	resolution	resolution	NOUN
ajst-31210	43	7	of	of	ADP
ajst-31210	43	8	the	the	DET
ajst-31210	43	9	entire	entire	ADJ
ajst-31210	43	10	seedling	seedling	NOUN
ajst-31210	43	11	tray	tray	NOUN
ajst-31210	43	12	being	be	AUX
ajst-31210	43	13	3648	3648	NUM
ajst-31210	43	14	pixels	pixel	NOUN
ajst-31210	43	15	*	*	PUNCT
ajst-31210	43	16	2736	2736	NUM
ajst-31210	43	17	pixels	pixel	NOUN
ajst-31210	43	18	,	,	PUNCT
ajst-31210	43	19	the	the	DET
ajst-31210	43	20	original	original	ADJ
ajst-31210	43	21	image	image	NOUN
ajst-31210	43	22	was	be	AUX
ajst-31210	43	23	cut	cut	VERB
ajst-31210	43	24	into	into	ADP
ajst-31210	43	25	a	a	DET
ajst-31210	43	26	size	size	NOUN
ajst-31210	43	27	suitable	suitable	ADJ
ajst-31210	43	28	for	for	ADP
ajst-31210	43	29	annotation	annotation	NOUN
ajst-31210	43	30	data	datum	NOUN
ajst-31210	43	31	,	,	PUNCT
ajst-31210	43	32	with	with	ADP
ajst-31210	43	33	a	a	DET
ajst-31210	43	34	resolution	resolution	NOUN
ajst-31210	43	35	of	of	ADP
ajst-31210	43	36	608	608	NUM
ajst-31210	43	37	pixels	pixel	NOUN
ajst-31210	43	38	*	*	PUNCT
ajst-31210	43	39	684	684	NUM
ajst-31210	43	40	pixels	pixel	NOUN
ajst-31210	43	41	.	.	PUNCT
ajst-31210	44	1	the	the	DET
ajst-31210	44	2	size	size	NOUN
ajst-31210	44	3	of	of	ADP
ajst-31210	44	4	the	the	DET
ajst-31210	44	5	ground_truth	ground_truth	PROPN
ajst-31210	44	6	and	and	CCONJ
ajst-31210	44	7	h5	h5	PROPN
ajst-31210	44	8	files	file	NOUN
ajst-31210	44	9	generated	generate	VERB
ajst-31210	44	10	during	during	ADP
ajst-31210	44	11	training	training	NOUN
ajst-31210	44	12	is	be	AUX
ajst-31210	44	13	tied	tie	VERB
ajst-31210	44	14	to	to	ADP
ajst-31210	44	15	the	the	DET
ajst-31210	44	16	resolution	resolution	NOUN
ajst-31210	44	17	,	,	PUNCT
ajst-31210	44	18	and	and	CCONJ
ajst-31210	44	19	the	the	DET
ajst-31210	44	20	image	image	NOUN
ajst-31210	44	21	resolution	resolution	NOUN
ajst-31210	44	22	needs	need	VERB
ajst-31210	44	23	to	to	PART
ajst-31210	44	24	be	be	AUX
ajst-31210	44	25	reduced	reduce	VERB
ajst-31210	44	26	again	again	ADV
ajst-31210	44	27	.	.	PUNCT
ajst-31210	45	1	the	the	DET
ajst-31210	45	2	application	application	NOUN
ajst-31210	45	3	scenario	scenario	NOUN
ajst-31210	45	4	of	of	ADP
ajst-31210	45	5	this	this	DET
ajst-31210	45	6	article	article	NOUN
ajst-31210	45	7	is	be	AUX
ajst-31210	45	8	a	a	DET
ajst-31210	45	9	rice	rice	NOUN
ajst-31210	45	10	seedling	seedling	NOUN
ajst-31210	45	11	tray	tray	NOUN
ajst-31210	45	12	,	,	PUNCT
ajst-31210	45	13	which	which	PRON
ajst-31210	45	14	requires	require	VERB
ajst-31210	45	15	a	a	DET
ajst-31210	45	16	self	self	NOUN
ajst-31210	45	17	-	-	PUNCT
ajst-31210	45	18	made	make	VERB
ajst-31210	45	19	seedling	seedling	NOUN
ajst-31210	45	20	tray	tray	NOUN
ajst-31210	45	21	dataset	dataset	NOUN
ajst-31210	45	22	of	of	ADP
ajst-31210	45	23	432	432	NUM
ajst-31210	45	24	rice	rice	NOUN
ajst-31210	45	25	seeds	seed	NOUN
ajst-31210	45	26	(	(	PUNCT
ajst-31210	45	27	324	324	NUM
ajst-31210	45	28	in	in	ADP
ajst-31210	45	29	the	the	DET
ajst-31210	45	30	training	training	NOUN
ajst-31210	45	31	set	set	NOUN
ajst-31210	45	32	and	and	CCONJ
ajst-31210	45	33	108	108	NUM
ajst-31210	45	34	in	in	ADP
ajst-31210	45	35	the	the	DET
ajst-31210	45	36	testing	testing	NOUN
ajst-31210	45	37	set	set	NOUN
ajst-31210	45	38	)	)	PUNCT
ajst-31210	45	39	,	,	PUNCT
ajst-31210	45	40	with	with	ADP
ajst-31210	45	41	an	an	DET
ajst-31210	45	42	average	average	ADJ
ajst-31210	45	43	resolution	resolution	NOUN
ajst-31210	45	44	of	of	ADP
ajst-31210	45	45	228	228	NUM
ajst-31210	45	46	pixels	pixel	NOUN
ajst-31210	45	47	*	*	PUNCT
ajst-31210	45	48	256	256	NUM
ajst-31210	45	49	pixels	pixel	NOUN
ajst-31210	45	50	.	.	PUNCT
ajst-31210	46	1	use	use	VERB
ajst-31210	46	2	the	the	DET
ajst-31210	46	3	tool	tool	NOUN
ajst-31210	46	4	cclabeler	cclabeler	NOUN
ajst-31210	46	5	to	to	PART
ajst-31210	46	6	label	label	VERB
ajst-31210	46	7	the	the	DET
ajst-31210	46	8	data	datum	NOUN
ajst-31210	46	9	and	and	CCONJ
ajst-31210	46	10	integrate	integrate	VERB
ajst-31210	46	11	it	it	PRON
ajst-31210	46	12	into	into	ADP
ajst-31210	46	13	a	a	DET
ajst-31210	46	14	complete	complete	ADJ
ajst-31210	46	15	dataset	dataset	NOUN
ajst-31210	46	16	.	.	PUNCT
ajst-31210	47	1	the	the	DET
ajst-31210	47	2	overall	overall	ADJ
ajst-31210	47	3	size	size	NOUN
ajst-31210	47	4	of	of	ADP
ajst-31210	47	5	the	the	DET
ajst-31210	47	6	dataset	dataset	NOUN
ajst-31210	47	7	is	be	AUX
ajst-31210	47	8	198	198	NUM
ajst-31210	47	9	mb	mb	NOUN
ajst-31210	47	10	,	,	PUNCT
ajst-31210	47	11	and	and	CCONJ
ajst-31210	47	12	the	the	DET
ajst-31210	47	13	file	file	NOUN
ajst-31210	47	14	structure	structure	NOUN
ajst-31210	47	15	diagram	diagram	NOUN
ajst-31210	47	16	is	be	AUX
ajst-31210	47	17	shown	show	VERB
ajst-31210	47	18	below	below	ADP
ajst-31210	47	19	.	.	PUNCT
ajst-31210	48	1	among	among	ADP
ajst-31210	48	2	them	they	PRON
ajst-31210	48	3	,	,	PUNCT
ajst-31210	48	4	train_data	train_data	PROPN
ajst-31210	48	5	and	and	CCONJ
ajst-31210	48	6	test_data	test_data	NOUN
ajst-31210	48	7	are	be	AUX
ajst-31210	48	8	the	the	DET
ajst-31210	48	9	training	training	NOUN
ajst-31210	48	10	set	set	NOUN
ajst-31210	48	11	and	and	CCONJ
ajst-31210	48	12	the	the	DET
ajst-31210	48	13	testing	testing	NOUN
ajst-31210	48	14	set	set	NOUN
ajst-31210	48	15	,	,	PUNCT
ajst-31210	48	16	respectively	respectively	ADV
ajst-31210	48	17	.	.	PUNCT
ajst-31210	49	1	the	the	DET
ajst-31210	49	2	two	two	NUM
ajst-31210	49	3	folders	folder	NOUN
ajst-31210	49	4	store	store	VERB
ajst-31210	49	5	the	the	DET
ajst-31210	49	6	rice	rice	NOUN
ajst-31210	49	7	seed	seed	NOUN
ajst-31210	49	8	images	image	NOUN
ajst-31210	49	9	of	of	ADP
ajst-31210	49	10	the	the	DET
ajst-31210	49	11	seedling	seedling	NOUN
ajst-31210	49	12	tray	tray	NOUN
ajst-31210	49	13	in	in	ADP
ajst-31210	49	14	the	the	DET
ajst-31210	49	15	format	format	NOUN
ajst-31210	49	16	of	of	ADP
ajst-31210	49	17	.	.	PUNCT
ajst-31210	50	1	jpg	jpg	NOUN
ajst-31210	50	2	and	and	CCONJ
ajst-31210	50	3	the	the	PRON
ajst-31210	50	4	.	.	PUNCT
ajst-31210	51	1	json	json	NOUN
ajst-31210	51	2	file	file	NOUN
ajst-31210	51	3	generated	generate	VERB
ajst-31210	51	4	after	after	ADP
ajst-31210	51	5	marking	mark	VERB
ajst-31210	51	6	the	the	DET
ajst-31210	51	7	rice	rice	NOUN
ajst-31210	51	8	seeds	seed	NOUN
ajst-31210	51	9	.	.	PUNCT
ajst-31210	52	1	as	as	SCONJ
ajst-31210	52	2	shown	show	VERB
ajst-31210	52	3	in	in	ADP
ajst-31210	52	4	figure	figure	NOUN
ajst-31210	52	5	1	1	NUM
ajst-31210	52	6	.	.	PUNCT
ajst-31210	52	7	figure	figure	NOUN
ajst-31210	52	8	1	1	NUM
ajst-31210	52	9	.	.	PUNCT
ajst-31210	52	10	file	file	NOUN
ajst-31210	52	11	structure	structure	NOUN
ajst-31210	52	12	diagram	diagram	NOUN
ajst-31210	52	13	of	of	ADP
ajst-31210	52	14	the	the	DET
ajst-31210	52	15	corndataset	corndataset	NOUN
ajst-31210	52	16	dataset	dataset	VERB
ajst-31210	52	17	2.1.2	2.1.2	NUM
ajst-31210	52	18	.	.	PUNCT
ajst-31210	52	19	image	image	NOUN
ajst-31210	52	20	annotation	annotation	NOUN
ajst-31210	52	21	the	the	DET
ajst-31210	52	22	tool	tool	NOUN
ajst-31210	52	23	used	use	VERB
ajst-31210	52	24	for	for	ADP
ajst-31210	52	25	annotating	annotate	VERB
ajst-31210	52	26	rice	rice	NOUN
ajst-31210	52	27	seed	seed	NOUN
ajst-31210	52	28	data	datum	NOUN
ajst-31210	52	29	is	be	AUX
ajst-31210	52	30	cclabeler	cclabeler	NOUN
ajst-31210	52	31	,	,	PUNCT
ajst-31210	52	32	which	which	PRON
ajst-31210	52	33	is	be	AUX
ajst-31210	52	34	a	a	DET
ajst-31210	52	35	chinese	chinese	ADJ
ajst-31210	52	36	text	text	NOUN
ajst-31210	52	37	annotation	annotation	NOUN
ajst-31210	52	38	tool	tool	NOUN
ajst-31210	52	39	designed	design	VERB
ajst-31210	52	40	to	to	PART
ajst-31210	52	41	assist	assist	VERB
ajst-31210	52	42	researchers	researcher	NOUN
ajst-31210	52	43	and	and	CCONJ
ajst-31210	52	44	developers	developer	NOUN
ajst-31210	52	45	in	in	ADP
ajst-31210	52	46	annotating	annotate	VERB
ajst-31210	52	47	chinese	chinese	ADJ
ajst-31210	52	48	text	text	NOUN
ajst-31210	52	49	.	.	PUNCT
ajst-31210	53	1	this	this	DET
ajst-31210	53	2	tool	tool	NOUN
ajst-31210	53	3	is	be	AUX
ajst-31210	53	4	based	base	VERB
ajst-31210	53	5	on	on	ADP
ajst-31210	53	6	the	the	DET
ajst-31210	53	7	python	python	NOUN
ajst-31210	53	8	language	language	NOUN
ajst-31210	53	9	and	and	CCONJ
ajst-31210	53	10	utilizes	utilize	VERB
ajst-31210	53	11	various	various	ADJ
ajst-31210	53	12	open	open	ADJ
ajst-31210	53	13	-	-	PUNCT
ajst-31210	53	14	source	source	NOUN
ajst-31210	53	15	toolkits	toolkit	NOUN
ajst-31210	53	16	and	and	CCONJ
ajst-31210	53	17	libraries	library	NOUN
ajst-31210	53	18	,	,	PUNCT
ajst-31210	53	19	such	such	ADJ
ajst-31210	53	20	as	as	ADP
ajst-31210	53	21	nltk	nltk	PROPN
ajst-31210	53	22	,	,	PUNCT
ajst-31210	53	23	jieba	jieba	NOUN
ajst-31210	53	24	,	,	PUNCT
ajst-31210	53	25	and	and	CCONJ
ajst-31210	53	26	pandas	panda	NOUN
ajst-31210	53	27	.	.	PUNCT
ajst-31210	54	1	cclabeler	cclabeler	PROPN
ajst-31210	54	2	supports	support	VERB
ajst-31210	54	3	various	various	ADJ
ajst-31210	54	4	types	type	NOUN
ajst-31210	54	5	of	of	ADP
ajst-31210	54	6	annotation	annotation	NOUN
ajst-31210	54	7	tasks	task	NOUN
ajst-31210	54	8	,	,	PUNCT
ajst-31210	54	9	such	such	ADJ
ajst-31210	54	10	as	as	ADP
ajst-31210	54	11	part	part	NOUN
ajst-31210	54	12	of	of	ADP
ajst-31210	54	13	speech	speech	NOUN
ajst-31210	54	14	tagging	tagging	NOUN
ajst-31210	54	15	,	,	PUNCT
ajst-31210	54	16	named	name	VERB
ajst-31210	54	17	entity	entity	NOUN
ajst-31210	54	18	recognition	recognition	NOUN
ajst-31210	54	19	,	,	PUNCT
ajst-31210	54	20	sentiment	sentiment	NOUN
ajst-31210	54	21	analysis	analysis	NOUN
ajst-31210	54	22	,	,	PUNCT
ajst-31210	54	23	etc	etc	X
ajst-31210	54	24	.	.	X
ajst-31210	55	1	this	this	DET
ajst-31210	55	2	tool	tool	NOUN
ajst-31210	55	3	aims	aim	VERB
ajst-31210	55	4	to	to	PART
ajst-31210	55	5	provide	provide	VERB
ajst-31210	55	6	users	user	NOUN
ajst-31210	55	7	with	with	ADP
ajst-31210	55	8	an	an	DET
ajst-31210	55	9	efficient	efficient	ADJ
ajst-31210	55	10	text	text	NOUN
ajst-31210	55	11	annotation	annotation	NOUN
ajst-31210	55	12	experience	experience	NOUN
ajst-31210	55	13	and	and	CCONJ
ajst-31210	55	14	has	have	VERB
ajst-31210	55	15	a	a	DET
ajst-31210	55	16	certain	certain	ADJ
ajst-31210	55	17	degree	degree	NOUN
ajst-31210	55	18	of	of	ADP
ajst-31210	55	19	flexibility	flexibility	NOUN
ajst-31210	55	20	and	and	CCONJ
ajst-31210	55	21	scalability	scalability	NOUN
ajst-31210	55	22	to	to	PART
ajst-31210	55	23	meet	meet	VERB
ajst-31210	55	24	various	various	ADJ
ajst-31210	55	25	needs	need	NOUN
ajst-31210	55	26	.	.	PUNCT
ajst-31210	56	1	cclabeler	cclabeler	PROPN
ajst-31210	56	2	is	be	AUX
ajst-31210	56	3	particularly	particularly	ADV
ajst-31210	56	4	suitable	suitable	ADJ
ajst-31210	56	5	for	for	ADP
ajst-31210	56	6	research	research	NOUN
ajst-31210	56	7	and	and	CCONJ
ajst-31210	56	8	development	development	NOUN
ajst-31210	56	9	work	work	NOUN
ajst-31210	56	10	on	on	ADP
ajst-31210	56	11	annotating	annotate	VERB
ajst-31210	56	12	chinese	chinese	ADJ
ajst-31210	56	13	text	text	NOUN
ajst-31210	56	14	.	.	PUNCT
ajst-31210	57	1	navigate	navigate	VERB
ajst-31210	57	2	to	to	ADP
ajst-31210	57	3	the	the	DET
ajst-31210	57	4	cclabeler	cclabeler	PROPN
ajst-31210	57	5	directory	directory	PROPN
ajst-31210	57	6	in	in	ADP
ajst-31210	57	7	the	the	DET
ajst-31210	57	8	cmd	cmd	NOUN
ajst-31210	57	9	window	window	NOUN
ajst-31210	57	10	,	,	PUNCT
ajst-31210	57	11	execute	execute	VERB
ajst-31210	57	12	python	python	NOUN
ajst-31210	57	13	manageability	manageability	NOUN
ajst-31210	57	14	.	.	PUNCT
ajst-31210	58	1	py	py	PROPN
ajst-31210	58	2	runserver	runserver	PROPN
ajst-31210	58	3	8000	8000	NUM
ajst-31210	58	4	,	,	PUNCT
ajst-31210	58	5	enter	enter	VERB
ajst-31210	58	6	localhost	localhost	NOUN
ajst-31210	58	7	:	:	PUNCT
ajst-31210	58	8	8000	8000	NUM
ajst-31210	58	9	in	in	ADP
ajst-31210	58	10	the	the	DET
ajst-31210	58	11	browser	browser	NOUN
ajst-31210	58	12	address	address	NOUN
ajst-31210	58	13	bar	bar	NOUN
ajst-31210	58	14	to	to	PART
ajst-31210	58	15	enter	enter	VERB
ajst-31210	58	16	the	the	DET
ajst-31210	58	17	login	login	NOUN
ajst-31210	58	18	interface	interface	NOUN
ajst-31210	58	19	,	,	PUNCT
ajst-31210	58	20	and	and	CCONJ
ajst-31210	58	21	enter	enter	VERB
ajst-31210	58	22	the	the	DET
ajst-31210	58	23	account	account	NOUN
ajst-31210	58	24	information	information	NOUN
ajst-31210	58	25	configured	configure	VERB
ajst-31210	58	26	in	in	ADP
ajst-31210	58	27	the	the	DET
ajst-31210	58	28	json	json	NOUN
ajst-31210	58	29	folder	folder	NOUN
ajst-31210	58	30	to	to	PART
ajst-31210	58	31	annotate	annotate	VERB
ajst-31210	58	32	the	the	DET
ajst-31210	58	33	image	image	NOUN
ajst-31210	58	34	.	.	PUNCT
ajst-31210	59	1	figure	figure	NOUN
ajst-31210	59	2	2	2	NUM
ajst-31210	59	3	.	.	PUNCT
ajst-31210	59	4	image	image	NOUN
ajst-31210	59	5	annotation	annotation	NOUN
ajst-31210	59	6	operation	operation	NOUN
ajst-31210	59	7	interface	interface	NOUN
ajst-31210	59	8	2.2	2.2	NUM
ajst-31210	59	9	.	.	PUNCT
ajst-31210	60	1	mcnn	mcnn	PROPN
ajst-31210	60	2	structural	structural	ADJ
ajst-31210	60	3	model	model	NOUN
ajst-31210	60	4	mcnn	mcnn	PROPN
ajst-31210	60	5	is	be	AUX
ajst-31210	60	6	a	a	DET
ajst-31210	60	7	deep	deep	ADJ
ajst-31210	60	8	learning	learning	NOUN
ajst-31210	60	9	model	model	NOUN
ajst-31210	60	10	based	base	VERB
ajst-31210	60	11	on	on	ADP
ajst-31210	60	12	multi	multi	ADJ
ajst-31210	60	13	-	-	ADJ
ajst-31210	60	14	channel	channel	ADJ
ajst-31210	60	15	convolutional	convolutional	ADJ
ajst-31210	60	16	neural	neural	ADJ
ajst-31210	60	17	networks	network	NOUN
ajst-31210	60	18	,	,	PUNCT
ajst-31210	60	19	specifically	specifically	ADV
ajst-31210	60	20	designed	design	VERB
ajst-31210	60	21	for	for	ADP
ajst-31210	60	22	object	object	NOUN
ajst-31210	60	23	detection	detection	NOUN
ajst-31210	60	24	.	.	PUNCT
ajst-31210	61	1	its	its	PRON
ajst-31210	61	2	main	main	ADJ
ajst-31210	61	3	feature	feature	NOUN
ajst-31210	61	4	is	be	AUX
ajst-31210	61	5	the	the	DET
ajst-31210	61	6	ability	ability	NOUN
ajst-31210	61	7	to	to	PART
ajst-31210	61	8	extract	extract	VERB
ajst-31210	61	9	various	various	ADJ
ajst-31210	61	10	features	feature	NOUN
ajst-31210	61	11	such	such	ADJ
ajst-31210	61	12	as	as	ADP
ajst-31210	61	13	the	the	DET
ajst-31210	61	14	shape	shape	NOUN
ajst-31210	61	15	,	,	PUNCT
ajst-31210	61	16	texture	texture	NOUN
ajst-31210	61	17	,	,	PUNCT
ajst-31210	61	18	and	and	CCONJ
ajst-31210	61	19	color	color	NOUN
ajst-31210	61	20	of	of	ADP
ajst-31210	61	21	the	the	DET
ajst-31210	61	22	target	target	NOUN
ajst-31210	61	23	,	,	PUNCT
ajst-31210	61	24	and	and	CCONJ
ajst-31210	61	25	effectively	effectively	ADV
ajst-31210	61	26	fuse	fuse	VERB
ajst-31210	61	27	these	these	DET
ajst-31210	61	28	features	feature	NOUN
ajst-31210	61	29	.	.	PUNCT
ajst-31210	62	1	it	it	PRON
ajst-31210	62	2	improves	improve	VERB
ajst-31210	62	3	the	the	DET
ajst-31210	62	4	accuracy	accuracy	NOUN
ajst-31210	62	5	and	and	CCONJ
ajst-31210	62	6	efficiency	efficiency	NOUN
ajst-31210	62	7	of	of	ADP
ajst-31210	62	8	the	the	DET
ajst-31210	62	9	model	model	NOUN
ajst-31210	62	10	through	through	ADP
ajst-31210	62	11	parallel	parallel	ADJ
ajst-31210	62	12	computing	computing	NOUN
ajst-31210	62	13	of	of	ADP
ajst-31210	62	14	multiple	multiple	ADJ
ajst-31210	62	15	convolutional	convolutional	ADJ
ajst-31210	62	16	layers	layer	NOUN
ajst-31210	62	17	.	.	PUNCT
ajst-31210	63	1	at	at	ADP
ajst-31210	63	2	the	the	DET
ajst-31210	63	3	same	same	ADJ
ajst-31210	63	4	time	time	NOUN
ajst-31210	63	5	,	,	PUNCT
ajst-31210	63	6	it	it	PRON
ajst-31210	63	7	can	can	AUX
ajst-31210	63	8	perform	perform	VERB
ajst-31210	63	9	multi	multi	ADJ
ajst-31210	63	10	-	-	ADJ
ajst-31210	63	11	scale	scale	ADJ
ajst-31210	63	12	object	object	NOUN
ajst-31210	63	13	detection	detection	NOUN
ajst-31210	63	14	at	at	ADP
ajst-31210	63	15	different	different	ADJ
ajst-31210	63	16	resolutions	resolution	NOUN
ajst-31210	63	17	,	,	PUNCT
ajst-31210	63	18	thereby	thereby	ADV
ajst-31210	63	19	identifying	identify	VERB
ajst-31210	63	20	targets	target	NOUN
ajst-31210	63	21	of	of	ADP
ajst-31210	63	22	different	different	ADJ
ajst-31210	63	23	sizes	size	NOUN
ajst-31210	63	24	and	and	CCONJ
ajst-31210	63	25	shapes	shape	NOUN
ajst-31210	63	26	.	.	PUNCT
ajst-31210	64	1	compared	compare	VERB
ajst-31210	64	2	to	to	ADP
ajst-31210	64	3	traditional	traditional	ADJ
ajst-31210	64	4	convolutional	convolutional	ADJ
ajst-31210	64	5	neural	neural	ADJ
ajst-31210	64	6	networks	network	NOUN
ajst-31210	64	7	,	,	PUNCT
ajst-31210	64	8	mcnn	mcnn	NOUN
ajst-31210	64	9	adds	add	VERB
ajst-31210	64	10	multiple	multiple	ADJ
ajst-31210	64	11	independent	independent	ADJ
ajst-31210	64	12	convolutional	convolutional	ADJ
ajst-31210	64	13	layers	layer	NOUN
ajst-31210	64	14	to	to	ADP
ajst-31210	64	15	the	the	DET
ajst-31210	64	16	75	75	NUM
ajst-31210	64	17	network	network	NOUN
ajst-31210	64	18	structure	structure	NOUN
ajst-31210	64	19	and	and	CCONJ
ajst-31210	64	20	combines	combine	VERB
ajst-31210	64	21	them	they	PRON
ajst-31210	64	22	into	into	ADP
ajst-31210	64	23	a	a	DET
ajst-31210	64	24	whole	whole	NOUN
ajst-31210	64	25	.	.	PUNCT
ajst-31210	65	1	mcnn	mcnn	NOUN
ajst-31210	65	2	typically	typically	ADV
ajst-31210	65	3	consists	consist	VERB
ajst-31210	65	4	of	of	ADP
ajst-31210	65	5	three	three	NUM
ajst-31210	65	6	main	main	ADJ
ajst-31210	65	7	parts	part	NOUN
ajst-31210	65	8	:	:	PUNCT
ajst-31210	65	9	input	input	NOUN
ajst-31210	65	10	layer	layer	NOUN
ajst-31210	65	11	,	,	PUNCT
ajst-31210	65	12	multi	multi	ADJ
ajst-31210	65	13	column	column	NOUN
ajst-31210	65	14	convolutional	convolutional	ADJ
ajst-31210	65	15	layer	layer	NOUN
ajst-31210	65	16	,	,	PUNCT
ajst-31210	65	17	and	and	CCONJ
ajst-31210	65	18	output	output	NOUN
ajst-31210	65	19	layer	layer	NOUN
ajst-31210	65	20	.	.	PUNCT
ajst-31210	66	1	the	the	DET
ajst-31210	66	2	input	input	NOUN
ajst-31210	66	3	layer	layer	NOUN
ajst-31210	66	4	receives	receive	VERB
ajst-31210	66	5	the	the	DET
ajst-31210	66	6	image	image	NOUN
ajst-31210	66	7	data	datum	NOUN
ajst-31210	66	8	to	to	PART
ajst-31210	66	9	be	be	AUX
ajst-31210	66	10	processed	process	VERB
ajst-31210	66	11	,	,	PUNCT
ajst-31210	66	12	while	while	SCONJ
ajst-31210	66	13	the	the	DET
ajst-31210	66	14	multi	multi	ADJ
ajst-31210	66	15	column	column	NOUN
ajst-31210	66	16	convolutional	convolutional	ADJ
ajst-31210	66	17	layer	layer	NOUN
ajst-31210	66	18	is	be	AUX
ajst-31210	66	19	composed	compose	VERB
ajst-31210	66	20	of	of	ADP
ajst-31210	66	21	multiple	multiple	ADJ
ajst-31210	66	22	independent	independent	ADJ
ajst-31210	66	23	convolutional	convolutional	ADJ
ajst-31210	66	24	neural	neural	ADJ
ajst-31210	66	25	networks	network	NOUN
ajst-31210	66	26	,	,	PUNCT
ajst-31210	66	27	each	each	PRON
ajst-31210	66	28	of	of	ADP
ajst-31210	66	29	which	which	PRON
ajst-31210	66	30	extracts	extract	NOUN
ajst-31210	66	31	features	feature	VERB
ajst-31210	66	32	through	through	ADP
ajst-31210	66	33	different	different	ADJ
ajst-31210	66	34	filters	filter	NOUN
ajst-31210	66	35	.	.	PUNCT
ajst-31210	67	1	these	these	DET
ajst-31210	67	2	independent	independent	ADJ
ajst-31210	67	3	convolutional	convolutional	ADJ
ajst-31210	67	4	neural	neural	ADJ
ajst-31210	67	5	networks	network	NOUN
ajst-31210	67	6	can	can	AUX
ajst-31210	67	7	simultaneously	simultaneously	ADV
ajst-31210	67	8	process	process	VERB
ajst-31210	67	9	different	different	ADJ
ajst-31210	67	10	features	feature	NOUN
ajst-31210	67	11	,	,	PUNCT
ajst-31210	67	12	reducing	reduce	VERB
ajst-31210	67	13	the	the	DET
ajst-31210	67	14	model	model	NOUN
ajst-31210	67	15	's	's	PART
ajst-31210	67	16	dependence	dependence	NOUN
ajst-31210	67	17	on	on	ADP
ajst-31210	67	18	pooling	pool	VERB
ajst-31210	67	19	layers	layer	NOUN
ajst-31210	67	20	while	while	SCONJ
ajst-31210	67	21	also	also	ADV
ajst-31210	67	22	increasing	increase	VERB
ajst-31210	67	23	the	the	DET
ajst-31210	67	24	model	model	NOUN
ajst-31210	67	25	's	's	PART
ajst-31210	67	26	robustness	robustness	NOUN
ajst-31210	67	27	and	and	CCONJ
ajst-31210	67	28	generalization	generalization	NOUN
ajst-31210	67	29	ability	ability	NOUN
ajst-31210	67	30	.	.	PUNCT
ajst-31210	68	1	in	in	ADP
ajst-31210	68	2	figure	figure	NOUN
ajst-31210	68	3	3	3	NUM
ajst-31210	68	4	,	,	PUNCT
ajst-31210	68	5	it	it	PRON
ajst-31210	68	6	can	can	AUX
ajst-31210	68	7	be	be	AUX
ajst-31210	68	8	seen	see	VERB
ajst-31210	68	9	that	that	SCONJ
ajst-31210	68	10	mcnn	mcnn	NOUN
ajst-31210	68	11	consists	consist	VERB
ajst-31210	68	12	of	of	ADP
ajst-31210	68	13	three	three	NUM
ajst-31210	68	14	parallel	parallel	ADJ
ajst-31210	68	15	convolutional	convolutional	ADJ
ajst-31210	68	16	neural	neural	ADJ
ajst-31210	68	17	networks	network	NOUN
ajst-31210	68	18	,	,	PUNCT
ajst-31210	68	19	using	use	VERB
ajst-31210	68	20	receptive	receptive	ADJ
ajst-31210	68	21	fields	field	NOUN
ajst-31210	68	22	of	of	ADP
ajst-31210	68	23	9	9	NUM
ajst-31210	68	24			PROPN
ajst-31210	68	25	9	9	NUM
ajst-31210	68	26	,	,	PUNCT
ajst-31210	68	27	7	7	NUM
ajst-31210	68	28			PROPN
ajst-31210	68	29	7	7	NUM
ajst-31210	68	30	,	,	PUNCT
ajst-31210	68	31	and	and	CCONJ
ajst-31210	68	32	5	5	NUM
ajst-31210	68	33			PROPN
ajst-31210	68	34	5	5	NUM
ajst-31210	68	35	,	,	PUNCT
ajst-31210	68	36	and	and	CCONJ
ajst-31210	68	37	convolution	convolution	NOUN
ajst-31210	68	38	kernels	kernel	NOUN
ajst-31210	68	39	of	of	ADP
ajst-31210	68	40	16	16	NUM
ajst-31210	68	41	,	,	PUNCT
ajst-31210	68	42	20	20	NUM
ajst-31210	68	43	,	,	PUNCT
ajst-31210	68	44	and	and	CCONJ
ajst-31210	68	45	24	24	NUM
ajst-31210	68	46	,	,	PUNCT
ajst-31210	68	47	respectively	respectively	ADV
ajst-31210	68	48	,	,	PUNCT
ajst-31210	68	49	to	to	PART
ajst-31210	68	50	convolve	convolve	VERB
ajst-31210	68	51	the	the	DET
ajst-31210	68	52	rice	rice	NOUN
ajst-31210	68	53	seed	seed	NOUN
ajst-31210	68	54	images	image	NOUN
ajst-31210	68	55	in	in	ADP
ajst-31210	68	56	the	the	DET
ajst-31210	68	57	seedling	seedling	NOUN
ajst-31210	68	58	tray	tray	NOUN
ajst-31210	68	59	.	.	PUNCT
ajst-31210	69	1	at	at	ADP
ajst-31210	69	2	the	the	DET
ajst-31210	69	3	same	same	ADJ
ajst-31210	69	4	time	time	NOUN
ajst-31210	69	5	,	,	PUNCT
ajst-31210	69	6	the	the	DET
ajst-31210	69	7	step	step	NOUN
ajst-31210	69	8	size	size	NOUN
ajst-31210	69	9	of	of	ADP
ajst-31210	69	10	each	each	DET
ajst-31210	69	11	convolutional	convolutional	ADJ
ajst-31210	69	12	layer	layer	NOUN
ajst-31210	69	13	is	be	AUX
ajst-31210	69	14	one	one	NUM
ajst-31210	69	15	pixel	pixel	NOUN
ajst-31210	69	16	to	to	PART
ajst-31210	69	17	ensure	ensure	VERB
ajst-31210	69	18	that	that	SCONJ
ajst-31210	69	19	the	the	DET
ajst-31210	69	20	output	output	NOUN
ajst-31210	69	21	size	size	NOUN
ajst-31210	69	22	of	of	ADP
ajst-31210	69	23	each	each	DET
ajst-31210	69	24	convolutional	convolutional	ADJ
ajst-31210	69	25	layer	layer	NOUN
ajst-31210	69	26	remains	remain	VERB
ajst-31210	69	27	unchanged	unchanged	ADJ
ajst-31210	69	28	.	.	PUNCT
ajst-31210	70	1	maximum	maximum	ADJ
ajst-31210	70	2	pooling	pooling	NOUN
ajst-31210	70	3	is	be	AUX
ajst-31210	70	4	used	use	VERB
ajst-31210	70	5	for	for	ADP
ajst-31210	70	6	each	each	DET
ajst-31210	70	7	2	2	NUM
ajst-31210	70	8			PROPN
ajst-31210	70	9	2	2	NUM
ajst-31210	70	10	region	region	NOUN
ajst-31210	70	11	,	,	PUNCT
ajst-31210	70	12	and	and	CCONJ
ajst-31210	70	13	relu	relu	NOUN
ajst-31210	70	14	is	be	AUX
ajst-31210	70	15	used	use	VERB
ajst-31210	70	16	as	as	ADP
ajst-31210	70	17	the	the	DET
ajst-31210	70	18	activation	activation	NOUN
ajst-31210	70	19	function	function	NOUN
ajst-31210	70	20	.	.	PUNCT
ajst-31210	71	1	using	use	VERB
ajst-31210	71	2	smaller	small	ADJ
ajst-31210	71	3	convolution	convolution	NOUN
ajst-31210	71	4	kernels	kernel	NOUN
ajst-31210	71	5	for	for	ADP
ajst-31210	71	6	larger	large	ADJ
ajst-31210	71	7	convolutional	convolutional	ADJ
ajst-31210	71	8	neural	neural	ADJ
ajst-31210	71	9	networks	network	NOUN
ajst-31210	71	10	makes	make	VERB
ajst-31210	71	11	the	the	DET
ajst-31210	71	12	features	feature	NOUN
ajst-31210	71	13	learned	learn	VERB
ajst-31210	71	14	by	by	ADP
ajst-31210	71	15	the	the	DET
ajst-31210	71	16	network	network	NOUN
ajst-31210	71	17	adaptive	adaptive	ADJ
ajst-31210	71	18	.	.	PUNCT
ajst-31210	72	1	mcnn	mcnn	NOUN
ajst-31210	72	2	replaces	replace	VERB
ajst-31210	72	3	fully	fully	ADV
ajst-31210	72	4	connected	connected	ADJ
ajst-31210	72	5	layers	layer	NOUN
ajst-31210	72	6	with	with	ADP
ajst-31210	72	7	1	1	NUM
ajst-31210	72	8			ADJ
ajst-31210	72	9	1	1	NUM
ajst-31210	72	10	matrices	matrix	NOUN
ajst-31210	72	11	to	to	PART
ajst-31210	72	12	reduce	reduce	VERB
ajst-31210	72	13	model	model	NOUN
ajst-31210	72	14	parameters	parameter	NOUN
ajst-31210	72	15	:	:	PUNCT
ajst-31210	72	16	fully	fully	ADV
ajst-31210	72	17	connected	connected	ADJ
ajst-31210	72	18	layers	layer	NOUN
ajst-31210	72	19	typically	typically	ADV
ajst-31210	72	20	introduce	introduce	VERB
ajst-31210	72	21	a	a	DET
ajst-31210	72	22	large	large	ADJ
ajst-31210	72	23	number	number	NOUN
ajst-31210	72	24	of	of	ADP
ajst-31210	72	25	model	model	NOUN
ajst-31210	72	26	parameters	parameter	NOUN
ajst-31210	72	27	,	,	PUNCT
ajst-31210	72	28	increasing	increase	VERB
ajst-31210	72	29	the	the	DET
ajst-31210	72	30	complexity	complexity	NOUN
ajst-31210	72	31	of	of	ADP
ajst-31210	72	32	the	the	DET
ajst-31210	72	33	model	model	NOUN
ajst-31210	72	34	,	,	PUNCT
ajst-31210	72	35	while	while	SCONJ
ajst-31210	72	36	1	1	NUM
ajst-31210	72	37			PROPN
ajst-31210	72	38	1	1	NUM
ajst-31210	72	39	convolution	convolution	NOUN
ajst-31210	72	40	kernels	kernel	NOUN
ajst-31210	72	41	can	can	AUX
ajst-31210	72	42	reduce	reduce	VERB
ajst-31210	72	43	the	the	DET
ajst-31210	72	44	number	number	NOUN
ajst-31210	72	45	of	of	ADP
ajst-31210	72	46	channels	channel	NOUN
ajst-31210	72	47	without	without	ADP
ajst-31210	72	48	affecting	affect	VERB
ajst-31210	72	49	the	the	DET
ajst-31210	72	50	size	size	NOUN
ajst-31210	72	51	of	of	ADP
ajst-31210	72	52	the	the	DET
ajst-31210	72	53	feature	feature	NOUN
ajst-31210	72	54	map	map	NOUN
ajst-31210	72	55	,	,	PUNCT
ajst-31210	72	56	thereby	thereby	ADV
ajst-31210	72	57	reducing	reduce	VERB
ajst-31210	72	58	the	the	DET
ajst-31210	72	59	number	number	NOUN
ajst-31210	72	60	of	of	ADP
ajst-31210	72	61	model	model	NOUN
ajst-31210	72	62	parameters	parameter	NOUN
ajst-31210	72	63	.	.	PUNCT
ajst-31210	73	1	improving	improve	VERB
ajst-31210	73	2	model	model	NOUN
ajst-31210	73	3	efficiency	efficiency	NOUN
ajst-31210	73	4	:	:	PUNCT
ajst-31210	73	5	as	as	ADP
ajst-31210	73	6	a	a	DET
ajst-31210	73	7	1x1	1x1	NUM
ajst-31210	73	8	convolution	convolution	NOUN
ajst-31210	73	9	kernel	kernel	NOUN
ajst-31210	73	10	can	can	AUX
ajst-31210	73	11	reduce	reduce	VERB
ajst-31210	73	12	the	the	DET
ajst-31210	73	13	number	number	NOUN
ajst-31210	73	14	of	of	ADP
ajst-31210	73	15	channels	channel	NOUN
ajst-31210	73	16	,	,	PUNCT
ajst-31210	73	17	it	it	PRON
ajst-31210	73	18	can	can	AUX
ajst-31210	73	19	reduce	reduce	VERB
ajst-31210	73	20	computational	computational	ADJ
ajst-31210	73	21	complexity	complexity	NOUN
ajst-31210	73	22	and	and	CCONJ
ajst-31210	73	23	improve	improve	VERB
ajst-31210	73	24	model	model	NOUN
ajst-31210	73	25	efficiency	efficiency	NOUN
ajst-31210	73	26	,	,	PUNCT
ajst-31210	73	27	especially	especially	ADV
ajst-31210	73	28	in	in	ADP
ajst-31210	73	29	situations	situation	NOUN
ajst-31210	73	30	where	where	SCONJ
ajst-31210	73	31	hardware	hardware	NOUN
ajst-31210	73	32	resources	resource	NOUN
ajst-31210	73	33	such	such	ADJ
ajst-31210	73	34	as	as	ADP
ajst-31210	73	35	gpus	gpu	NOUN
ajst-31210	73	36	are	be	AUX
ajst-31210	73	37	limited	limited	ADJ
ajst-31210	73	38	.	.	PUNCT
ajst-31210	74	1	enhance	enhance	VERB
ajst-31210	74	2	feature	feature	NOUN
ajst-31210	74	3	expression	expression	NOUN
ajst-31210	74	4	ability	ability	NOUN
ajst-31210	74	5	:	:	PUNCT
ajst-31210	74	6	a	a	DET
ajst-31210	74	7	1x1	1x1	NUM
ajst-31210	74	8	convolution	convolution	NOUN
ajst-31210	74	9	kernel	kernel	NOUN
ajst-31210	74	10	can	can	AUX
ajst-31210	74	11	linearly	linearly	ADV
ajst-31210	74	12	combine	combine	VERB
ajst-31210	74	13	features	feature	NOUN
ajst-31210	74	14	from	from	ADP
ajst-31210	74	15	different	different	ADJ
ajst-31210	74	16	channels	channel	NOUN
ajst-31210	74	17	to	to	PART
ajst-31210	74	18	generate	generate	VERB
ajst-31210	74	19	new	new	ADJ
ajst-31210	74	20	feature	feature	NOUN
ajst-31210	74	21	representations	representation	NOUN
ajst-31210	74	22	,	,	PUNCT
ajst-31210	74	23	which	which	PRON
ajst-31210	74	24	can	can	AUX
ajst-31210	74	25	enhance	enhance	VERB
ajst-31210	74	26	the	the	DET
ajst-31210	74	27	feature	feature	NOUN
ajst-31210	74	28	expression	expression	NOUN
ajst-31210	74	29	ability	ability	NOUN
ajst-31210	74	30	of	of	ADP
ajst-31210	74	31	the	the	DET
ajst-31210	74	32	model	model	NOUN
ajst-31210	74	33	.	.	PUNCT
ajst-31210	75	1	avoiding	avoid	VERB
ajst-31210	75	2	overfitting	overfitte	VERB
ajst-31210	75	3	:	:	PUNCT
ajst-31210	75	4	using	use	VERB
ajst-31210	75	5	a	a	DET
ajst-31210	75	6	1x1	1x1	NUM
ajst-31210	75	7	convolution	convolution	NOUN
ajst-31210	75	8	kernel	kernel	NOUN
ajst-31210	75	9	can	can	AUX
ajst-31210	75	10	increase	increase	VERB
ajst-31210	75	11	the	the	DET
ajst-31210	75	12	nonlinearity	nonlinearity	NOUN
ajst-31210	75	13	of	of	ADP
ajst-31210	75	14	the	the	DET
ajst-31210	75	15	network	network	NOUN
ajst-31210	75	16	,	,	PUNCT
ajst-31210	75	17	thereby	thereby	ADV
ajst-31210	75	18	improving	improve	VERB
ajst-31210	75	19	the	the	DET
ajst-31210	75	20	model	model	NOUN
ajst-31210	75	21	's	's	PART
ajst-31210	75	22	generalization	generalization	NOUN
ajst-31210	75	23	ability	ability	NOUN
ajst-31210	75	24	and	and	CCONJ
ajst-31210	75	25	avoiding	avoid	VERB
ajst-31210	75	26	overfitting	overfitte	VERB
ajst-31210	75	27	.	.	PUNCT
ajst-31210	76	1	figure	figure	NOUN
ajst-31210	76	2	3	3	NUM
ajst-31210	76	3	.	.	PUNCT
ajst-31210	76	4	mcnn	mcnn	NOUN
ajst-31210	76	5	network	network	NOUN
ajst-31210	76	6	model	model	NOUN
ajst-31210	76	7	structure	structure	NOUN
ajst-31210	76	8	in	in	ADP
ajst-31210	76	9	the	the	DET
ajst-31210	76	10	mcnn	mcnn	NOUN
ajst-31210	76	11	model	model	NOUN
ajst-31210	76	12	,	,	PUNCT
ajst-31210	76	13	pooling	pool	VERB
ajst-31210	76	14	operations	operation	NOUN
ajst-31210	76	15	and	and	CCONJ
ajst-31210	76	16	spatial	spatial	ADJ
ajst-31210	76	17	pyramid	pyramid	NOUN
ajst-31210	76	18	pooling	pool	VERB
ajst-31210	76	19	strategies	strategy	NOUN
ajst-31210	76	20	are	be	AUX
ajst-31210	76	21	adopted	adopt	VERB
ajst-31210	76	22	.	.	PUNCT
ajst-31210	77	1	in	in	ADP
ajst-31210	77	2	pooling	pool	VERB
ajst-31210	77	3	operations	operation	NOUN
ajst-31210	77	4	,	,	PUNCT
ajst-31210	77	5	by	by	ADP
ajst-31210	77	6	reducing	reduce	VERB
ajst-31210	77	7	the	the	DET
ajst-31210	77	8	size	size	NOUN
ajst-31210	77	9	of	of	ADP
ajst-31210	77	10	feature	feature	NOUN
ajst-31210	77	11	maps	map	NOUN
ajst-31210	77	12	,	,	PUNCT
ajst-31210	77	13	the	the	DET
ajst-31210	77	14	parameters	parameter	NOUN
ajst-31210	77	15	and	and	CCONJ
ajst-31210	77	16	computational	computational	ADJ
ajst-31210	77	17	complexity	complexity	NOUN
ajst-31210	77	18	of	of	ADP
ajst-31210	77	19	the	the	DET
ajst-31210	77	20	model	model	NOUN
ajst-31210	77	21	can	can	AUX
ajst-31210	77	22	be	be	AUX
ajst-31210	77	23	reduced	reduce	VERB
ajst-31210	77	24	,	,	PUNCT
ajst-31210	77	25	while	while	SCONJ
ajst-31210	77	26	also	also	ADV
ajst-31210	77	27	preventing	prevent	VERB
ajst-31210	77	28	overfitting	overfitte	VERB
ajst-31210	77	29	to	to	ADP
ajst-31210	77	30	a	a	DET
ajst-31210	77	31	certain	certain	ADJ
ajst-31210	77	32	extent	extent	NOUN
ajst-31210	77	33	.	.	PUNCT
ajst-31210	78	1	in	in	ADP
ajst-31210	78	2	spatial	spatial	ADJ
ajst-31210	78	3	pyramid	pyramid	NOUN
ajst-31210	78	4	pooling	pooling	NOUN
ajst-31210	78	5	,	,	PUNCT
ajst-31210	78	6	the	the	DET
ajst-31210	78	7	feature	feature	NOUN
ajst-31210	78	8	map	map	NOUN
ajst-31210	78	9	size	size	NOUN
ajst-31210	78	10	can	can	AUX
ajst-31210	78	11	be	be	AUX
ajst-31210	78	12	unified	unified	ADJ
ajst-31210	78	13	,	,	PUNCT
ajst-31210	78	14	multiscale	multiscale	ADJ
ajst-31210	78	15	features	feature	NOUN
ajst-31210	78	16	can	can	AUX
ajst-31210	78	17	be	be	AUX
ajst-31210	78	18	extracted	extract	VERB
ajst-31210	78	19	,	,	PUNCT
ajst-31210	78	20	the	the	DET
ajst-31210	78	21	receptive	receptive	ADJ
ajst-31210	78	22	field	field	NOUN
ajst-31210	78	23	of	of	ADP
ajst-31210	78	24	the	the	DET
ajst-31210	78	25	network	network	NOUN
ajst-31210	78	26	can	can	AUX
ajst-31210	78	27	be	be	AUX
ajst-31210	78	28	increased	increase	VERB
ajst-31210	78	29	,	,	PUNCT
ajst-31210	78	30	and	and	CCONJ
ajst-31210	78	31	the	the	DET
ajst-31210	78	32	occurrence	occurrence	NOUN
ajst-31210	78	33	of	of	ADP
ajst-31210	78	34	overfitting	overfitting	NOUN
ajst-31210	78	35	can	can	AUX
ajst-31210	78	36	be	be	AUX
ajst-31210	78	37	reduced	reduce	VERB
ajst-31210	78	38	.	.	PUNCT
ajst-31210	79	1	the	the	DET
ajst-31210	79	2	structure	structure	NOUN
ajst-31210	79	3	of	of	ADP
ajst-31210	79	4	spatial	spatial	ADJ
ajst-31210	79	5	pyramid	pyramid	NOUN
ajst-31210	79	6	pooling	pool	VERB
ajst-31210	79	7	is	be	AUX
ajst-31210	79	8	as	as	SCONJ
ajst-31210	79	9	follows	follow	VERB
ajst-31210	79	10	:	:	PUNCT
ajst-31210	79	11	input	input	NOUN
ajst-31210	79	12	feature	feature	NOUN
ajst-31210	79	13	map	map	NOUN
ajst-31210	79	14	:	:	PUNCT
ajst-31210	79	15	the	the	DET
ajst-31210	79	16	input	input	NOUN
ajst-31210	79	17	of	of	ADP
ajst-31210	79	18	spp	spp	NOUN
ajst-31210	79	19	is	be	AUX
ajst-31210	79	20	a	a	DET
ajst-31210	79	21	feature	feature	NOUN
ajst-31210	79	22	map	map	NOUN
ajst-31210	79	23	,	,	PUNCT
ajst-31210	79	24	and	and	CCONJ
ajst-31210	79	25	the	the	DET
ajst-31210	79	26	size	size	NOUN
ajst-31210	79	27	of	of	ADP
ajst-31210	79	28	the	the	DET
ajst-31210	79	29	feature	feature	NOUN
ajst-31210	79	30	map	map	NOUN
ajst-31210	79	31	can	can	AUX
ajst-31210	79	32	be	be	AUX
ajst-31210	79	33	any	any	DET
ajst-31210	79	34	size	size	NOUN
ajst-31210	79	35	.	.	PUNCT
ajst-31210	80	1	block	block	NOUN
ajst-31210	80	2	:	:	PUNCT
ajst-31210	80	3	divide	divide	VERB
ajst-31210	80	4	the	the	DET
ajst-31210	80	5	input	input	NOUN
ajst-31210	80	6	feature	feature	NOUN
ajst-31210	80	7	map	map	NOUN
ajst-31210	80	8	into	into	ADP
ajst-31210	80	9	blocks	block	NOUN
ajst-31210	80	10	and	and	CCONJ
ajst-31210	80	11	perform	perform	VERB
ajst-31210	80	12	pooling	pool	VERB
ajst-31210	80	13	operations	operation	NOUN
ajst-31210	80	14	on	on	ADP
ajst-31210	80	15	each	each	DET
ajst-31210	80	16	block	block	NOUN
ajst-31210	80	17	separately	separately	ADV
ajst-31210	80	18	.	.	PUNCT
ajst-31210	81	1	the	the	DET
ajst-31210	81	2	size	size	NOUN
ajst-31210	81	3	and	and	CCONJ
ajst-31210	81	4	number	number	NOUN
ajst-31210	81	5	of	of	ADP
ajst-31210	81	6	blocks	block	NOUN
ajst-31210	81	7	are	be	AUX
ajst-31210	81	8	determined	determine	VERB
ajst-31210	81	9	based	base	VERB
ajst-31210	81	10	on	on	ADP
ajst-31210	81	11	the	the	DET
ajst-31210	81	12	design	design	NOUN
ajst-31210	81	13	parameters	parameter	NOUN
ajst-31210	81	14	of	of	ADP
ajst-31210	81	15	spp	spp	NOUN
ajst-31210	81	16	and	and	CCONJ
ajst-31210	81	17	can	can	AUX
ajst-31210	81	18	include	include	VERB
ajst-31210	81	19	pooling	pool	VERB
ajst-31210	81	20	layers	layer	NOUN
ajst-31210	81	21	of	of	ADP
ajst-31210	81	22	different	different	ADJ
ajst-31210	81	23	scales	scale	NOUN
ajst-31210	81	24	to	to	PART
ajst-31210	81	25	extract	extract	VERB
ajst-31210	81	26	multi	multi	ADJ
ajst-31210	81	27	-	-	ADJ
ajst-31210	81	28	scale	scale	ADJ
ajst-31210	81	29	features	feature	NOUN
ajst-31210	81	30	.	.	PUNCT
ajst-31210	82	1	pooling	pool	VERB
ajst-31210	82	2	:	:	PUNCT
ajst-31210	82	3	pooling	pool	VERB
ajst-31210	82	4	each	each	DET
ajst-31210	82	5	block	block	NOUN
ajst-31210	82	6	and	and	CCONJ
ajst-31210	82	7	compressing	compress	VERB
ajst-31210	82	8	it	it	PRON
ajst-31210	82	9	into	into	ADP
ajst-31210	82	10	a	a	DET
ajst-31210	82	11	fixed	fix	VERB
ajst-31210	82	12	size	size	NOUN
ajst-31210	82	13	vector	vector	NOUN
ajst-31210	82	14	.	.	PUNCT
ajst-31210	83	1	common	common	ADJ
ajst-31210	83	2	pooling	pooling	NOUN
ajst-31210	83	3	methods	method	NOUN
ajst-31210	83	4	include	include	VERB
ajst-31210	83	5	max	max	PROPN
ajst-31210	83	6	pooling	pooling	NOUN
ajst-31210	83	7	,	,	PUNCT
ajst-31210	83	8	average	average	ADJ
ajst-31210	83	9	pooling	pooling	NOUN
ajst-31210	83	10	,	,	PUNCT
ajst-31210	83	11	etc	etc	X
ajst-31210	83	12	.	.	X
ajst-31210	84	1	splicing	splice	VERB
ajst-31210	84	2	:	:	PUNCT
ajst-31210	84	3	splicing	splice	VERB
ajst-31210	84	4	all	all	PRON
ajst-31210	84	5	pooled	pool	VERB
ajst-31210	84	6	vectors	vector	NOUN
ajst-31210	84	7	together	together	ADV
ajst-31210	84	8	to	to	PART
ajst-31210	84	9	form	form	VERB
ajst-31210	84	10	a	a	DET
ajst-31210	84	11	feature	feature	NOUN
ajst-31210	84	12	vector	vector	NOUN
ajst-31210	84	13	of	of	ADP
ajst-31210	84	14	length	length	NOUN
ajst-31210	84	15	n	n	CCONJ
ajst-31210	84	16	,	,	PUNCT
ajst-31210	84	17	where	where	SCONJ
ajst-31210	84	18	n	n	X
ajst-31210	84	19	is	be	AUX
ajst-31210	84	20	the	the	DET
ajst-31210	84	21	total	total	ADJ
ajst-31210	84	22	dimension	dimension	NOUN
ajst-31210	84	23	of	of	ADP
ajst-31210	84	24	all	all	DET
ajst-31210	84	25	block	block	NOUN
ajst-31210	84	26	pooled	pool	VERB
ajst-31210	84	27	vectors	vector	NOUN
ajst-31210	84	28	.	.	PUNCT
ajst-31210	85	1	output	output	NOUN
ajst-31210	85	2	:	:	PUNCT
ajst-31210	85	3	input	input	VERB
ajst-31210	85	4	the	the	DET
ajst-31210	85	5	feature	feature	NOUN
ajst-31210	85	6	vectors	vector	NOUN
ajst-31210	85	7	into	into	ADP
ajst-31210	85	8	the	the	DET
ajst-31210	85	9	fully	fully	ADV
ajst-31210	85	10	connected	connect	VERB
ajst-31210	85	11	layer	layer	NOUN
ajst-31210	85	12	for	for	ADP
ajst-31210	85	13	subsequent	subsequent	ADJ
ajst-31210	85	14	tasks	task	NOUN
ajst-31210	85	15	such	such	ADJ
ajst-31210	85	16	as	as	ADP
ajst-31210	85	17	classification	classification	NOUN
ajst-31210	85	18	.	.	PUNCT
ajst-31210	86	1	different	different	ADJ
ajst-31210	86	2	sizes	size	NOUN
ajst-31210	86	3	of	of	ADP
ajst-31210	86	4	input	input	NOUN
ajst-31210	86	5	images	image	NOUN
ajst-31210	86	6	may	may	AUX
ajst-31210	86	7	result	result	VERB
ajst-31210	86	8	in	in	ADP
ajst-31210	86	9	feature	feature	NOUN
ajst-31210	86	10	maps	map	NOUN
ajst-31210	86	11	of	of	ADP
ajst-31210	86	12	different	different	ADJ
ajst-31210	86	13	sizes	size	NOUN
ajst-31210	86	14	,	,	PUNCT
ajst-31210	86	15	which	which	PRON
ajst-31210	86	16	can	can	AUX
ajst-31210	86	17	pose	pose	VERB
ajst-31210	86	18	difficulties	difficulty	NOUN
ajst-31210	86	19	for	for	ADP
ajst-31210	86	20	subsequent	subsequent	ADJ
ajst-31210	86	21	fully	fully	ADV
ajst-31210	86	22	connected	connected	ADJ
ajst-31210	86	23	layers	layer	NOUN
ajst-31210	86	24	.	.	PUNCT
ajst-31210	87	1	by	by	ADP
ajst-31210	87	2	using	use	VERB
ajst-31210	87	3	spp	spp	NOUN
ajst-31210	87	4	,	,	PUNCT
ajst-31210	87	5	the	the	DET
ajst-31210	87	6	size	size	NOUN
ajst-31210	87	7	of	of	ADP
ajst-31210	87	8	the	the	DET
ajst-31210	87	9	feature	feature	NOUN
ajst-31210	87	10	map	map	NOUN
ajst-31210	87	11	can	can	AUX
ajst-31210	87	12	be	be	AUX
ajst-31210	87	13	fixed	fix	VERB
ajst-31210	87	14	to	to	ADP
ajst-31210	87	15	a	a	DET
ajst-31210	87	16	fixed	fix	VERB
ajst-31210	87	17	tensor	tensor	NOUN
ajst-31210	87	18	,	,	PUNCT
ajst-31210	87	19	thereby	thereby	ADV
ajst-31210	87	20	unifying	unify	VERB
ajst-31210	87	21	the	the	DET
ajst-31210	87	22	size	size	NOUN
ajst-31210	87	23	of	of	ADP
ajst-31210	87	24	the	the	DET
ajst-31210	87	25	feature	feature	NOUN
ajst-31210	87	26	map	map	NOUN
ajst-31210	87	27	and	and	CCONJ
ajst-31210	87	28	reducing	reduce	VERB
ajst-31210	87	29	the	the	DET
ajst-31210	87	30	computational	computational	ADJ
ajst-31210	87	31	complexity	complexity	NOUN
ajst-31210	87	32	of	of	ADP
ajst-31210	87	33	the	the	DET
ajst-31210	87	34	fully	fully	ADV
ajst-31210	87	35	connected	connected	ADJ
ajst-31210	87	36	layer	layer	NOUN
ajst-31210	87	37	.	.	PUNCT
ajst-31210	88	1	spp	spp	NOUN
ajst-31210	88	2	can	can	AUX
ajst-31210	88	3	divide	divide	VERB
ajst-31210	88	4	the	the	DET
ajst-31210	88	5	input	input	NOUN
ajst-31210	88	6	image	image	NOUN
ajst-31210	88	7	into	into	ADP
ajst-31210	88	8	multiple	multiple	ADJ
ajst-31210	88	9	regions	region	NOUN
ajst-31210	88	10	,	,	PUNCT
ajst-31210	88	11	perform	perform	VERB
ajst-31210	88	12	pooling	pool	VERB
ajst-31210	88	13	operations	operation	NOUN
ajst-31210	88	14	on	on	ADP
ajst-31210	88	15	each	each	DET
ajst-31210	88	16	region	region	NOUN
ajst-31210	88	17	,	,	PUNCT
ajst-31210	88	18	and	and	CCONJ
ajst-31210	88	19	obtain	obtain	VERB
ajst-31210	88	20	feature	feature	NOUN
ajst-31210	88	21	representations	representation	NOUN
ajst-31210	88	22	within	within	ADP
ajst-31210	88	23	each	each	DET
ajst-31210	88	24	region	region	NOUN
ajst-31210	88	25	.	.	PUNCT
ajst-31210	89	1	by	by	ADP
ajst-31210	89	2	using	use	VERB
ajst-31210	89	3	pooling	pool	VERB
ajst-31210	89	4	layers	layer	NOUN
ajst-31210	89	5	of	of	ADP
ajst-31210	89	6	different	different	ADJ
ajst-31210	89	7	sizes	size	NOUN
ajst-31210	89	8	in	in	ADP
ajst-31210	89	9	spp	spp	NOUN
ajst-31210	89	10	,	,	PUNCT
ajst-31210	89	11	features	feature	NOUN
ajst-31210	89	12	of	of	ADP
ajst-31210	89	13	different	different	ADJ
ajst-31210	89	14	scales	scale	NOUN
ajst-31210	89	15	can	can	AUX
ajst-31210	89	16	be	be	AUX
ajst-31210	89	17	extracted	extract	VERB
ajst-31210	89	18	,	,	PUNCT
ajst-31210	89	19	thereby	thereby	ADV
ajst-31210	89	20	enhancing	enhance	VERB
ajst-31210	89	21	the	the	DET
ajst-31210	89	22	network	network	NOUN
ajst-31210	89	23	's	's	PART
ajst-31210	89	24	ability	ability	NOUN
ajst-31210	89	25	to	to	PART
ajst-31210	89	26	understand	understand	VERB
ajst-31210	89	27	images	image	NOUN
ajst-31210	89	28	.	.	PUNCT
ajst-31210	90	1	by	by	ADP
ajst-31210	90	2	using	use	VERB
ajst-31210	90	3	larger	large	ADJ
ajst-31210	90	4	pooling	pool	VERB
ajst-31210	90	5	layers	layer	NOUN
ajst-31210	90	6	in	in	ADP
ajst-31210	90	7	spp	spp	NOUN
ajst-31210	90	8	,	,	PUNCT
ajst-31210	90	9	the	the	DET
ajst-31210	90	10	receptive	receptive	ADJ
ajst-31210	90	11	field	field	NOUN
ajst-31210	90	12	of	of	ADP
ajst-31210	90	13	the	the	DET
ajst-31210	90	14	network	network	NOUN
ajst-31210	90	15	can	can	AUX
ajst-31210	90	16	be	be	AUX
ajst-31210	90	17	increased	increase	VERB
ajst-31210	90	18	,	,	PUNCT
ajst-31210	90	19	enabling	enable	VERB
ajst-31210	90	20	the	the	DET
ajst-31210	90	21	network	network	NOUN
ajst-31210	90	22	to	to	PART
ajst-31210	90	23	capture	capture	VERB
ajst-31210	90	24	broader	broad	ADJ
ajst-31210	90	25	contextual	contextual	ADJ
ajst-31210	90	26	information	information	NOUN
ajst-31210	90	27	and	and	CCONJ
ajst-31210	90	28	improve	improve	VERB
ajst-31210	90	29	its	its	PRON
ajst-31210	90	30	ability	ability	NOUN
ajst-31210	90	31	to	to	PART
ajst-31210	90	32	understand	understand	VERB
ajst-31210	90	33	images	image	NOUN
ajst-31210	90	34	.	.	PUNCT
ajst-31210	91	1	spp	spp	NOUN
ajst-31210	91	2	can	can	AUX
ajst-31210	91	3	reduce	reduce	VERB
ajst-31210	91	4	the	the	DET
ajst-31210	91	5	occurrence	occurrence	NOUN
ajst-31210	91	6	of	of	ADP
ajst-31210	91	7	overfitting	overfitte	VERB
ajst-31210	91	8	without	without	ADP
ajst-31210	91	9	increasing	increase	VERB
ajst-31210	91	10	network	network	NOUN
ajst-31210	91	11	parameters	parameter	NOUN
ajst-31210	91	12	.	.	PUNCT
ajst-31210	92	1	by	by	ADP
ajst-31210	92	2	pooling	pool	VERB
ajst-31210	92	3	each	each	DET
ajst-31210	92	4	region	region	NOUN
ajst-31210	92	5	,	,	PUNCT
ajst-31210	92	6	the	the	DET
ajst-31210	92	7	amount	amount	NOUN
ajst-31210	92	8	of	of	ADP
ajst-31210	92	9	data	datum	NOUN
ajst-31210	92	10	can	can	AUX
ajst-31210	92	11	be	be	AUX
ajst-31210	92	12	increased	increase	VERB
ajst-31210	92	13	,	,	PUNCT
ajst-31210	92	14	thereby	thereby	ADV
ajst-31210	92	15	reducing	reduce	VERB
ajst-31210	92	16	the	the	DET
ajst-31210	92	17	risk	risk	NOUN
ajst-31210	92	18	of	of	ADP
ajst-31210	92	19	overfitting	overfitte	VERB
ajst-31210	92	20	.	.	PUNCT
ajst-31210	93	1	3	3	X
ajst-31210	93	2	.	.	X
ajst-31210	93	3	experimental	experimental	ADJ
ajst-31210	93	4	results	result	NOUN
ajst-31210	93	5	and	and	CCONJ
ajst-31210	93	6	analysis	analysis	NOUN
ajst-31210	93	7	3.1	3.1	NUM
ajst-31210	93	8	.	.	PUNCT
ajst-31210	93	9	model	model	NOUN
ajst-31210	93	10	parameter	parameter	PROPN
ajst-31210	93	11	adjustment	adjustment	NOUN
ajst-31210	93	12	pp	pp	ADP
ajst-31210	93	13	paddlepaddle	paddlepaddle	ADJ
ajst-31210	93	14	visualdl	visualdl	NOUN
ajst-31210	93	15	is	be	AUX
ajst-31210	93	16	used	use	VERB
ajst-31210	93	17	for	for	ADP
ajst-31210	93	18	visual	visual	ADJ
ajst-31210	93	19	parameter	parameter	NOUN
ajst-31210	93	20	adjustment	adjustment	NOUN
ajst-31210	93	21	when	when	SCONJ
ajst-31210	93	22	training	training	NOUN
ajst-31210	93	23	models	model	NOUN
ajst-31210	93	24	.	.	PUNCT
ajst-31210	94	1	pp	pp	ADV
ajst-31210	94	2	paddlepaddle	paddlepaddle	NOUN
ajst-31210	94	3	visualdl	visualdl	NOUN
ajst-31210	94	4	is	be	AUX
ajst-31210	94	5	a	a	DET
ajst-31210	94	6	visual	visual	ADJ
ajst-31210	94	7	tool	tool	NOUN
ajst-31210	94	8	for	for	ADP
ajst-31210	94	9	in	in	ADP
ajst-31210	94	10	-	-	PUNCT
ajst-31210	94	11	depth	depth	NOUN
ajst-31210	94	12	learning	learning	NOUN
ajst-31210	94	13	development	development	NOUN
ajst-31210	94	14	,	,	PUNCT
ajst-31210	94	15	which	which	PRON
ajst-31210	94	16	aims	aim	VERB
ajst-31210	94	17	to	to	PART
ajst-31210	94	18	help	help	VERB
ajst-31210	94	19	developers	developer	NOUN
ajst-31210	94	20	better	well	ADV
ajst-31210	94	21	understand	understand	VERB
ajst-31210	94	22	,	,	PUNCT
ajst-31210	94	23	optimize	optimize	VERB
ajst-31210	94	24	and	and	CCONJ
ajst-31210	94	25	debug	debug	VERB
ajst-31210	94	26	their	their	PRON
ajst-31210	94	27	models	model	NOUN
ajst-31210	94	28	.	.	PUNCT
ajst-31210	95	1	this	this	DET
ajst-31210	95	2	tool	tool	NOUN
ajst-31210	95	3	provides	provide	VERB
ajst-31210	95	4	many	many	ADJ
ajst-31210	95	5	powerful	powerful	ADJ
ajst-31210	95	6	features	feature	NOUN
ajst-31210	95	7	in	in	ADP
ajst-31210	95	8	visualization	visualization	NOUN
ajst-31210	95	9	,	,	PUNCT
ajst-31210	95	10	including	include	VERB
ajst-31210	95	11	drawing	draw	VERB
ajst-31210	95	12	loss	loss	NOUN
ajst-31210	95	13	,	,	PUNCT
ajst-31210	95	14	accuracy	accuracy	NOUN
ajst-31210	95	15	,	,	PUNCT
ajst-31210	95	16	scalars	scalar	NOUN
ajst-31210	95	17	,	,	PUNCT
ajst-31210	95	18	and	and	CCONJ
ajst-31210	95	19	histograms	histogram	NOUN
ajst-31210	95	20	.	.	PUNCT
ajst-31210	96	1	in	in	ADP
ajst-31210	96	2	addition	addition	NOUN
ajst-31210	96	3	,	,	PUNCT
ajst-31210	96	4	pp	pp	ADP
ajst-31210	96	5	paddlepaddle	paddlepaddle	NOUN
ajst-31210	96	6	visualdl	visualdl	NOUN
ajst-31210	96	7	also	also	ADV
ajst-31210	96	8	76	76	NUM
ajst-31210	96	9	supports	support	VERB
ajst-31210	96	10	visual	visual	ADJ
ajst-31210	96	11	model	model	NOUN
ajst-31210	96	12	structure	structure	NOUN
ajst-31210	96	13	and	and	CCONJ
ajst-31210	96	14	gradient	gradient	NOUN
ajst-31210	96	15	flow	flow	NOUN
ajst-31210	96	16	graph	graph	NOUN
ajst-31210	96	17	to	to	PART
ajst-31210	96	18	monitor	monitor	VERB
ajst-31210	96	19	parameter	parameter	NOUN
ajst-31210	96	20	changes	change	NOUN
ajst-31210	96	21	and	and	CCONJ
ajst-31210	96	22	data	datum	NOUN
ajst-31210	96	23	flow	flow	NOUN
ajst-31210	96	24	during	during	ADP
ajst-31210	96	25	training	training	NOUN
ajst-31210	96	26	.	.	PUNCT
ajst-31210	97	1	this	this	DET
ajst-31210	97	2	tool	tool	NOUN
ajst-31210	97	3	not	not	PART
ajst-31210	97	4	only	only	ADV
ajst-31210	97	5	makes	make	VERB
ajst-31210	97	6	the	the	DET
ajst-31210	97	7	training	training	NOUN
ajst-31210	97	8	process	process	NOUN
ajst-31210	97	9	easier	easy	ADJ
ajst-31210	97	10	to	to	PART
ajst-31210	97	11	understand	understand	VERB
ajst-31210	97	12	,	,	PUNCT
ajst-31210	97	13	but	but	CCONJ
ajst-31210	97	14	also	also	ADV
ajst-31210	97	15	helps	help	VERB
ajst-31210	97	16	developers	developer	NOUN
ajst-31210	97	17	identify	identify	VERB
ajst-31210	97	18	problems	problem	NOUN
ajst-31210	97	19	and	and	CCONJ
ajst-31210	97	20	bottlenecks	bottleneck	NOUN
ajst-31210	97	21	in	in	ADP
ajst-31210	97	22	the	the	DET
ajst-31210	97	23	model	model	NOUN
ajst-31210	97	24	and	and	CCONJ
ajst-31210	97	25	optimize	optimize	VERB
ajst-31210	97	26	its	its	PRON
ajst-31210	97	27	performance	performance	NOUN
ajst-31210	97	28	.	.	PUNCT
ajst-31210	98	1	pp	pp	ADV
ajst-31210	98	2	paddlepaddle	paddlepaddle	ADJ
ajst-31210	98	3	visualdl	visualdl	NOUN
ajst-31210	98	4	is	be	AUX
ajst-31210	98	5	an	an	DET
ajst-31210	98	6	open	open	ADJ
ajst-31210	98	7	source	source	NOUN
ajst-31210	98	8	tool	tool	NOUN
ajst-31210	98	9	,	,	PUNCT
ajst-31210	98	10	which	which	PRON
ajst-31210	98	11	can	can	AUX
ajst-31210	98	12	be	be	AUX
ajst-31210	98	13	downloaded	download	VERB
ajst-31210	98	14	and	and	CCONJ
ajst-31210	98	15	used	use	VERB
ajst-31210	98	16	through	through	ADP
ajst-31210	98	17	github	github	PROPN
ajst-31210	98	18	and	and	CCONJ
ajst-31210	98	19	the	the	DET
ajst-31210	98	20	official	official	ADJ
ajst-31210	98	21	website	website	NOUN
ajst-31210	98	22	.	.	PUNCT
ajst-31210	99	1	observing	observe	VERB
ajst-31210	99	2	the	the	DET
ajst-31210	99	3	convergence	convergence	NOUN
ajst-31210	99	4	status	status	NOUN
ajst-31210	99	5	and	and	CCONJ
ajst-31210	99	6	minimum	minimum	NOUN
ajst-31210	99	7	mae	mae	PROPN
ajst-31210	99	8	of	of	ADP
ajst-31210	99	9	mae	mae	PROPN
ajst-31210	99	10	with	with	ADP
ajst-31210	99	11	learning	learn	VERB
ajst-31210	99	12	rates	rate	NOUN
ajst-31210	99	13	of	of	ADP
ajst-31210	99	14	1e-2	1e-2	PROPN
ajst-31210	99	15	,	,	PUNCT
ajst-31210	99	16	1e-3	1e-3	NUM
ajst-31210	99	17	,	,	PUNCT
ajst-31210	99	18	and	and	CCONJ
ajst-31210	99	19	1e-4	1e-4	NUM
ajst-31210	99	20	at	at	ADP
ajst-31210	99	21	epoch	epoch	PROPN
ajst-31210	99	22	20	20	NUM
ajst-31210	99	23	,	,	PUNCT
ajst-31210	99	24	mae	mae	PROPN
ajst-31210	99	25	refers	refer	VERB
ajst-31210	99	26	to	to	ADP
ajst-31210	99	27	the	the	DET
ajst-31210	99	28	mean	mean	ADJ
ajst-31210	99	29	absolute	absolute	ADJ
ajst-31210	99	30	error	error	NOUN
ajst-31210	99	31	,	,	PUNCT
ajst-31210	99	32	which	which	PRON
ajst-31210	99	33	is	be	AUX
ajst-31210	99	34	an	an	DET
ajst-31210	99	35	indicator	indicator	NOUN
ajst-31210	99	36	for	for	ADP
ajst-31210	99	37	measuring	measure	VERB
ajst-31210	99	38	the	the	DET
ajst-31210	99	39	error	error	NOUN
ajst-31210	99	40	of	of	ADP
ajst-31210	99	41	a	a	DET
ajst-31210	99	42	prediction	prediction	NOUN
ajst-31210	99	43	model	model	NOUN
ajst-31210	99	44	.	.	PUNCT
ajst-31210	100	1	in	in	ADP
ajst-31210	100	2	statistics	statistic	NOUN
ajst-31210	100	3	and	and	CCONJ
ajst-31210	100	4	machine	machine	NOUN
ajst-31210	100	5	learning	learning	NOUN
ajst-31210	100	6	,	,	PUNCT
ajst-31210	100	7	mae	mae	PROPN
ajst-31210	100	8	is	be	AUX
ajst-31210	100	9	commonly	commonly	ADV
ajst-31210	100	10	used	use	VERB
ajst-31210	100	11	to	to	PART
ajst-31210	100	12	evaluate	evaluate	VERB
ajst-31210	100	13	the	the	DET
ajst-31210	100	14	prediction	prediction	NOUN
ajst-31210	100	15	error	error	NOUN
ajst-31210	100	16	of	of	ADP
ajst-31210	100	17	a	a	DET
ajst-31210	100	18	model	model	NOUN
ajst-31210	100	19	on	on	ADP
ajst-31210	100	20	data	datum	NOUN
ajst-31210	100	21	points	point	NOUN
ajst-31210	100	22	.	.	PUNCT
ajst-31210	101	1	the	the	DET
ajst-31210	101	2	calculation	calculation	NOUN
ajst-31210	101	3	method	method	NOUN
ajst-31210	101	4	of	of	ADP
ajst-31210	101	5	mae	mae	PROPN
ajst-31210	101	6	is	be	AUX
ajst-31210	101	7	to	to	PART
ajst-31210	101	8	take	take	VERB
ajst-31210	101	9	the	the	DET
ajst-31210	101	10	absolute	absolute	ADJ
ajst-31210	101	11	difference	difference	NOUN
ajst-31210	101	12	between	between	ADP
ajst-31210	101	13	the	the	DET
ajst-31210	101	14	predicted	predict	VERB
ajst-31210	101	15	value	value	NOUN
ajst-31210	101	16	and	and	CCONJ
ajst-31210	101	17	the	the	DET
ajst-31210	101	18	actual	actual	ADJ
ajst-31210	101	19	value	value	NOUN
ajst-31210	101	20	of	of	ADP
ajst-31210	101	21	each	each	DET
ajst-31210	101	22	data	datum	NOUN
ajst-31210	101	23	point	point	NOUN
ajst-31210	101	24	,	,	PUNCT
ajst-31210	101	25	and	and	CCONJ
ajst-31210	101	26	then	then	ADV
ajst-31210	101	27	take	take	VERB
ajst-31210	101	28	the	the	DET
ajst-31210	101	29	average	average	NOUN
ajst-31210	101	30	of	of	ADP
ajst-31210	101	31	all	all	DET
ajst-31210	101	32	absolute	absolute	ADJ
ajst-31210	101	33	differences	difference	NOUN
ajst-31210	101	34	,	,	PUNCT
ajst-31210	101	35	which	which	PRON
ajst-31210	101	36	is	be	AUX
ajst-31210	101	37	mae	mae	PROPN
ajst-31210	101	38	.	.	PROPN
ajst-31210	101	39	compared	compare	VERB
ajst-31210	101	40	with	with	ADP
ajst-31210	101	41	other	other	ADJ
ajst-31210	101	42	error	error	NOUN
ajst-31210	101	43	indicators	indicator	NOUN
ajst-31210	101	44	,	,	PUNCT
ajst-31210	101	45	mae	mae	PROPN
ajst-31210	101	46	has	have	VERB
ajst-31210	101	47	good	good	ADJ
ajst-31210	101	48	interpretability	interpretability	NOUN
ajst-31210	101	49	and	and	CCONJ
ajst-31210	101	50	is	be	AUX
ajst-31210	101	51	easy	easy	ADJ
ajst-31210	101	52	to	to	PART
ajst-31210	101	53	understand	understand	VERB
ajst-31210	101	54	,	,	PUNCT
ajst-31210	101	55	and	and	CCONJ
ajst-31210	101	56	is	be	AUX
ajst-31210	101	57	insensitive	insensitive	ADJ
ajst-31210	101	58	to	to	ADP
ajst-31210	101	59	the	the	DET
ajst-31210	101	60	influence	influence	NOUN
ajst-31210	101	61	of	of	ADP
ajst-31210	101	62	outliers	outlier	NOUN
ajst-31210	101	63	.	.	PUNCT
ajst-31210	102	1	meanwhile	meanwhile	ADV
ajst-31210	102	2	,	,	PUNCT
ajst-31210	102	3	mae	mae	PROPN
ajst-31210	102	4	can	can	AUX
ajst-31210	102	5	also	also	ADV
ajst-31210	102	6	be	be	AUX
ajst-31210	102	7	used	use	VERB
ajst-31210	102	8	to	to	PART
ajst-31210	102	9	compare	compare	VERB
ajst-31210	102	10	the	the	DET
ajst-31210	102	11	predictive	predictive	ADJ
ajst-31210	102	12	performance	performance	NOUN
ajst-31210	102	13	of	of	ADP
ajst-31210	102	14	different	different	ADJ
ajst-31210	102	15	models	model	NOUN
ajst-31210	102	16	on	on	ADP
ajst-31210	102	17	the	the	DET
ajst-31210	102	18	same	same	ADJ
ajst-31210	102	19	dataset	dataset	NOUN
ajst-31210	102	20	.	.	PUNCT
ajst-31210	103	1	rmse	rmse	PROPN
ajst-31210	103	2	stands	stand	VERB
ajst-31210	103	3	for	for	ADP
ajst-31210	103	4	root	root	NOUN
ajst-31210	103	5	mean	mean	ADJ
ajst-31210	103	6	square	square	NOUN
ajst-31210	103	7	error	error	NOUN
ajst-31210	103	8	,	,	PUNCT
ajst-31210	103	9	which	which	PRON
ajst-31210	103	10	is	be	AUX
ajst-31210	103	11	a	a	DET
ajst-31210	103	12	common	common	ADJ
ajst-31210	103	13	metric	metric	NOUN
ajst-31210	103	14	used	use	VERB
ajst-31210	103	15	to	to	PART
ajst-31210	103	16	measure	measure	VERB
ajst-31210	103	17	the	the	DET
ajst-31210	103	18	error	error	NOUN
ajst-31210	103	19	of	of	ADP
ajst-31210	103	20	prediction	prediction	NOUN
ajst-31210	103	21	models	model	NOUN
ajst-31210	103	22	.	.	PUNCT
ajst-31210	104	1	in	in	ADP
ajst-31210	104	2	the	the	DET
ajst-31210	104	3	fields	field	NOUN
ajst-31210	104	4	of	of	ADP
ajst-31210	104	5	statistics	statistic	NOUN
ajst-31210	104	6	and	and	CCONJ
ajst-31210	104	7	machine	machine	NOUN
ajst-31210	104	8	learning	learning	NOUN
ajst-31210	104	9	,	,	PUNCT
ajst-31210	104	10	rmse	rmse	PROPN
ajst-31210	104	11	is	be	AUX
ajst-31210	104	12	commonly	commonly	ADV
ajst-31210	104	13	used	use	VERB
ajst-31210	104	14	to	to	PART
ajst-31210	104	15	measure	measure	VERB
ajst-31210	104	16	the	the	DET
ajst-31210	104	17	difference	difference	NOUN
ajst-31210	104	18	between	between	ADP
ajst-31210	104	19	model	model	NOUN
ajst-31210	104	20	predictions	prediction	NOUN
ajst-31210	104	21	and	and	CCONJ
ajst-31210	104	22	actual	actual	ADJ
ajst-31210	104	23	values	value	NOUN
ajst-31210	104	24	.	.	PUNCT
ajst-31210	105	1	the	the	DET
ajst-31210	105	2	calculation	calculation	NOUN
ajst-31210	105	3	method	method	NOUN
ajst-31210	105	4	of	of	ADP
ajst-31210	105	5	rmse	rmse	NOUN
ajst-31210	105	6	is	be	AUX
ajst-31210	105	7	to	to	PART
ajst-31210	105	8	square	square	VERB
ajst-31210	105	9	the	the	DET
ajst-31210	105	10	difference	difference	NOUN
ajst-31210	105	11	between	between	ADP
ajst-31210	105	12	the	the	DET
ajst-31210	105	13	predicted	predict	VERB
ajst-31210	105	14	value	value	NOUN
ajst-31210	105	15	and	and	CCONJ
ajst-31210	105	16	the	the	DET
ajst-31210	105	17	actual	actual	ADJ
ajst-31210	105	18	value	value	NOUN
ajst-31210	105	19	of	of	ADP
ajst-31210	105	20	each	each	DET
ajst-31210	105	21	data	datum	NOUN
ajst-31210	105	22	point	point	NOUN
ajst-31210	105	23	,	,	PUNCT
ajst-31210	105	24	then	then	ADV
ajst-31210	105	25	take	take	VERB
ajst-31210	105	26	the	the	DET
ajst-31210	105	27	average	average	NOUN
ajst-31210	105	28	of	of	ADP
ajst-31210	105	29	all	all	DET
ajst-31210	105	30	squared	squared	ADJ
ajst-31210	105	31	differences	difference	NOUN
ajst-31210	105	32	,	,	PUNCT
ajst-31210	105	33	and	and	CCONJ
ajst-31210	105	34	finally	finally	ADV
ajst-31210	105	35	square	square	VERB
ajst-31210	105	36	the	the	DET
ajst-31210	105	37	average	average	NOUN
ajst-31210	105	38	to	to	PART
ajst-31210	105	39	obtain	obtain	VERB
ajst-31210	105	40	rmse	rmse	NOUN
ajst-31210	105	41	.	.	PUNCT
ajst-31210	106	1	compared	compare	VERB
ajst-31210	106	2	with	with	ADP
ajst-31210	106	3	other	other	ADJ
ajst-31210	106	4	error	error	NOUN
ajst-31210	106	5	indicators	indicator	NOUN
ajst-31210	106	6	,	,	PUNCT
ajst-31210	106	7	rmse	rmse	PROPN
ajst-31210	106	8	has	have	VERB
ajst-31210	106	9	a	a	DET
ajst-31210	106	10	penalty	penalty	NOUN
ajst-31210	106	11	power	power	NOUN
ajst-31210	106	12	on	on	ADP
ajst-31210	106	13	the	the	DET
ajst-31210	106	14	square	square	NOUN
ajst-31210	106	15	of	of	ADP
ajst-31210	106	16	the	the	DET
ajst-31210	106	17	error	error	NOUN
ajst-31210	106	18	,	,	PUNCT
ajst-31210	106	19	which	which	PRON
ajst-31210	106	20	can	can	AUX
ajst-31210	106	21	better	well	ADV
ajst-31210	106	22	reflect	reflect	VERB
ajst-31210	106	23	the	the	DET
ajst-31210	106	24	size	size	NOUN
ajst-31210	106	25	and	and	CCONJ
ajst-31210	106	26	differences	difference	NOUN
ajst-31210	106	27	of	of	ADP
ajst-31210	106	28	prediction	prediction	NOUN
ajst-31210	106	29	errors	error	NOUN
ajst-31210	106	30	.	.	PUNCT
ajst-31210	107	1	rmse	rmse	PROPN
ajst-31210	107	2	can	can	AUX
ajst-31210	107	3	also	also	ADV
ajst-31210	107	4	be	be	AUX
ajst-31210	107	5	used	use	VERB
ajst-31210	107	6	to	to	PART
ajst-31210	107	7	compare	compare	VERB
ajst-31210	107	8	the	the	DET
ajst-31210	107	9	prediction	prediction	NOUN
ajst-31210	107	10	performance	performance	NOUN
ajst-31210	107	11	of	of	ADP
ajst-31210	107	12	different	different	ADJ
ajst-31210	107	13	models	model	NOUN
ajst-31210	107	14	on	on	ADP
ajst-31210	107	15	the	the	DET
ajst-31210	107	16	same	same	ADJ
ajst-31210	107	17	dataset	dataset	NOUN
ajst-31210	107	18	,	,	PUNCT
ajst-31210	107	19	in	in	ADP
ajst-31210	107	20	order	order	NOUN
ajst-31210	107	21	to	to	PART
ajst-31210	107	22	determine	determine	VERB
ajst-31210	107	23	the	the	DET
ajst-31210	107	24	optimal	optimal	ADJ
ajst-31210	107	25	prediction	prediction	NOUN
ajst-31210	107	26	model	model	NOUN
ajst-31210	107	27	.	.	PUNCT
ajst-31210	108	1	as	as	SCONJ
ajst-31210	108	2	shown	show	VERB
ajst-31210	108	3	in	in	ADP
ajst-31210	108	4	figure	figure	NOUN
ajst-31210	108	5	4	4	NUM
ajst-31210	108	6	(	(	PUNCT
ajst-31210	108	7	rmse	rmse	NOUN
ajst-31210	108	8	is	be	AUX
ajst-31210	108	9	dark	dark	ADJ
ajst-31210	108	10	blue	blue	ADJ
ajst-31210	108	11	,	,	PUNCT
ajst-31210	108	12	mae	mae	PROPN
ajst-31210	108	13	is	be	AUX
ajst-31210	108	14	light	light	ADJ
ajst-31210	108	15	blue	blue	ADJ
ajst-31210	108	16	)	)	PUNCT
ajst-31210	108	17	,	,	PUNCT
ajst-31210	108	18	it	it	PRON
ajst-31210	108	19	is	be	AUX
ajst-31210	108	20	observed	observe	VERB
ajst-31210	108	21	that	that	SCONJ
ajst-31210	108	22	the	the	DET
ajst-31210	108	23	lower	low	ADJ
ajst-31210	108	24	limit	limit	NOUN
ajst-31210	108	25	of	of	ADP
ajst-31210	108	26	mae	mae	PROPN
ajst-31210	108	27	is	be	AUX
ajst-31210	108	28	lower	low	ADJ
ajst-31210	108	29	when	when	SCONJ
ajst-31210	108	30	the	the	DET
ajst-31210	108	31	learning	learning	NOUN
ajst-31210	108	32	rate	rate	NOUN
ajst-31210	108	33	is	be	AUX
ajst-31210	108	34	1e-4	1e-4	NUM
ajst-31210	108	35	,	,	PUNCT
ajst-31210	108	36	and	and	CCONJ
ajst-31210	108	37	mae	mae	PROPN
ajst-31210	108	38	converges	converge	VERB
ajst-31210	108	39	to	to	ADP
ajst-31210	108	40	3.666	3.666	NUM
ajst-31210	108	41	when	when	SCONJ
ajst-31210	108	42	the	the	DET
ajst-31210	108	43	epoch	epoch	NOUN
ajst-31210	108	44	is	be	AUX
ajst-31210	108	45	200	200	NUM
ajst-31210	108	46	.	.	PUNCT
ajst-31210	109	1	therefore	therefore	ADV
ajst-31210	109	2	,	,	PUNCT
ajst-31210	109	3	the	the	DET
ajst-31210	109	4	best	good	ADJ
ajst-31210	109	5	model	model	NOUN
ajst-31210	109	6	for	for	ADP
ajst-31210	109	7	training	training	NOUN
ajst-31210	109	8	is	be	AUX
ajst-31210	109	9	selected	select	VERB
ajst-31210	109	10	with	with	ADP
ajst-31210	109	11	a	a	DET
ajst-31210	109	12	learning	learn	VERB
ajst-31210	109	13	rate	rate	NOUN
ajst-31210	109	14	of	of	ADP
ajst-31210	109	15	1e-4	1e-4	PROPN
ajst-31210	109	16	and	and	CCONJ
ajst-31210	109	17	an	an	DET
ajst-31210	109	18	epoch	epoch	NOUN
ajst-31210	109	19	of	of	ADP
ajst-31210	109	20	200	200	NUM
ajst-31210	109	21	.	.	PUNCT
ajst-31210	110	1	the	the	DET
ajst-31210	110	2	model	model	NOUN
ajst-31210	110	3	was	be	AUX
ajst-31210	110	4	tested	test	VERB
ajst-31210	110	5	and	and	CCONJ
ajst-31210	110	6	found	find	VERB
ajst-31210	110	7	to	to	PART
ajst-31210	110	8	have	have	AUX
ajst-31210	110	9	mae=3.879	mae=3.879	VERB
ajst-31210	110	10	and	and	CCONJ
ajst-31210	110	11	rmse=5.215	rmse=5.215	PROPN
ajst-31210	110	12	.	.	PROPN
ajst-31210	110	13	figure	figure	NOUN
ajst-31210	110	14	4	4	NUM
ajst-31210	110	15	.	.	PUNCT
ajst-31210	111	1	results	result	NOUN
ajst-31210	111	2	of	of	ADP
ajst-31210	111	3	mae	mae	PROPN
ajst-31210	111	4	and	and	CCONJ
ajst-31210	111	5	rmse	rmse	ADJ
ajst-31210	111	6	training	training	NOUN
ajst-31210	111	7	3.2	3.2	NUM
ajst-31210	111	8	.	.	PUNCT
ajst-31210	112	1	model	model	NOUN
ajst-31210	112	2	testing	testing	NOUN
ajst-31210	112	3	and	and	CCONJ
ajst-31210	112	4	analysis	analysis	NOUN
ajst-31210	112	5	randomly	randomly	ADV
ajst-31210	112	6	select	select	VERB
ajst-31210	112	7	20	20	NUM
ajst-31210	112	8	rice	rice	NOUN
ajst-31210	112	9	seed	seed	NOUN
ajst-31210	112	10	images	image	NOUN
ajst-31210	112	11	from	from	ADP
ajst-31210	112	12	the	the	DET
ajst-31210	112	13	seedling	seedling	NOUN
ajst-31210	112	14	tray	tray	NOUN
ajst-31210	112	15	for	for	ADP
ajst-31210	112	16	manual	manual	ADJ
ajst-31210	112	17	counting	counting	NOUN
ajst-31210	112	18	,	,	PUNCT
ajst-31210	112	19	and	and	CCONJ
ajst-31210	112	20	use	use	VERB
ajst-31210	112	21	the	the	DET
ajst-31210	112	22	model	model	NOUN
ajst-31210	112	23	trained	train	VERB
ajst-31210	112	24	in	in	ADP
ajst-31210	112	25	the	the	DET
ajst-31210	112	26	previous	previous	ADJ
ajst-31210	112	27	section	section	NOUN
ajst-31210	112	28	to	to	PART
ajst-31210	112	29	calculate	calculate	VERB
ajst-31210	112	30	the	the	DET
ajst-31210	112	31	number	number	NOUN
ajst-31210	112	32	of	of	ADP
ajst-31210	112	33	rice	rice	NOUN
ajst-31210	112	34	seeds	seed	NOUN
ajst-31210	112	35	.	.	PUNCT
ajst-31210	113	1	the	the	DET
ajst-31210	113	2	density	density	NOUN
ajst-31210	113	3	map	map	NOUN
ajst-31210	113	4	of	of	ADP
ajst-31210	113	5	rice	rice	NOUN
ajst-31210	113	6	seeds	seed	NOUN
ajst-31210	113	7	on	on	ADP
ajst-31210	113	8	a	a	DET
ajst-31210	113	9	bowl	bowl	NOUN
ajst-31210	113	10	shaped	shape	VERB
ajst-31210	113	11	floppy	floppy	ADJ
ajst-31210	113	12	disk	disk	NOUN
ajst-31210	113	13	based	base	VERB
ajst-31210	113	14	on	on	ADP
ajst-31210	113	15	mcnn	mcnn	NOUN
ajst-31210	113	16	is	be	AUX
ajst-31210	113	17	shown	show	VERB
ajst-31210	113	18	in	in	ADP
ajst-31210	113	19	figure	figure	NOUN
ajst-31210	113	20	5	5	NUM
ajst-31210	113	21	.	.	PUNCT
ajst-31210	114	1	(	(	PUNCT
ajst-31210	114	2	a	a	X
ajst-31210	114	3	)	)	PUNCT
ajst-31210	114	4	original	original	ADJ
ajst-31210	114	5	image	image	NOUN
ajst-31210	114	6	(	(	PUNCT
ajst-31210	114	7	b	b	NOUN
ajst-31210	114	8	)	)	PUNCT
ajst-31210	114	9	network	network	NOUN
ajst-31210	114	10	prediction	prediction	NOUN
ajst-31210	114	11	results	result	NOUN
ajst-31210	114	12	figure	figure	VERB
ajst-31210	114	13	5	5	NUM
ajst-31210	114	14	.	.	PUNCT
ajst-31210	114	15	density	density	NOUN
ajst-31210	114	16	map	map	NOUN
ajst-31210	114	17	of	of	ADP
ajst-31210	114	18	rice	rice	NOUN
ajst-31210	114	19	seeds	seed	NOUN
ajst-31210	114	20	on	on	ADP
ajst-31210	114	21	bowl	bowl	NOUN
ajst-31210	114	22	shaped	shape	VERB
ajst-31210	114	23	floppy	floppy	ADJ
ajst-31210	114	24	disks	disk	NOUN
ajst-31210	114	25	based	base	VERB
ajst-31210	114	26	on	on	ADP
ajst-31210	114	27	mcnn	mcnn	NOUN
ajst-31210	114	28	77	77	NUM
ajst-31210	114	29	after	after	ADP
ajst-31210	114	30	randomly	randomly	ADV
ajst-31210	114	31	selecting	select	VERB
ajst-31210	114	32	20	20	NUM
ajst-31210	114	33	images	image	NOUN
ajst-31210	114	34	for	for	ADP
ajst-31210	114	35	manual	manual	ADJ
ajst-31210	114	36	counting	counting	NOUN
ajst-31210	114	37	and	and	CCONJ
ajst-31210	114	38	network	network	NOUN
ajst-31210	114	39	modeling	modeling	NOUN
ajst-31210	114	40	,	,	PUNCT
ajst-31210	114	41	the	the	DET
ajst-31210	114	42	statistical	statistical	ADJ
ajst-31210	114	43	mae	mae	PROPN
ajst-31210	114	44	of	of	ADP
ajst-31210	114	45	rice	rice	NOUN
ajst-31210	114	46	seed	seed	NOUN
ajst-31210	114	47	counting	counting	NOUN
ajst-31210	114	48	was	be	AUX
ajst-31210	114	49	only	only	ADV
ajst-31210	114	50	0.065	0.065	NUM
ajst-31210	114	51	,	,	PUNCT
ajst-31210	114	52	which	which	PRON
ajst-31210	114	53	performed	perform	VERB
ajst-31210	114	54	well	well	ADV
ajst-31210	114	55	.	.	PUNCT
ajst-31210	115	1	however	however	ADV
ajst-31210	115	2	,	,	PUNCT
ajst-31210	115	3	the	the	DET
ajst-31210	115	4	vast	vast	ADJ
ajst-31210	115	5	majority	majority	NOUN
ajst-31210	115	6	of	of	ADP
ajst-31210	115	7	groups	group	NOUN
ajst-31210	115	8	could	could	AUX
ajst-31210	115	9	not	not	PART
ajst-31210	115	10	achieve	achieve	VERB
ajst-31210	115	11	100	100	NUM
ajst-31210	115	12	%	%	NOUN
ajst-31210	115	13	,	,	PUNCT
ajst-31210	115	14	and	and	CCONJ
ajst-31210	115	15	could	could	AUX
ajst-31210	115	16	basically	basically	ADV
ajst-31210	115	17	complete	complete	VERB
ajst-31210	115	18	the	the	DET
ajst-31210	115	19	low	low	ADJ
ajst-31210	115	20	requirement	requirement	NOUN
ajst-31210	115	21	scenario	scenario	NOUN
ajst-31210	115	22	of	of	ADP
ajst-31210	115	23	estimating	estimate	VERB
ajst-31210	115	24	and	and	CCONJ
ajst-31210	115	25	counting	count	VERB
ajst-31210	115	26	rice	rice	NOUN
ajst-31210	115	27	seed	seed	NOUN
ajst-31210	115	28	density	density	NOUN
ajst-31210	115	29	in	in	ADP
ajst-31210	115	30	seedling	seedling	NOUN
ajst-31210	115	31	trays	tray	NOUN
ajst-31210	115	32	.	.	PUNCT
ajst-31210	116	1	table	table	NOUN
ajst-31210	116	2	1	1	NUM
ajst-31210	116	3	.	.	PUNCT
ajst-31210	117	1	three	three	NUM
ajst-31210	117	2	scheme	scheme	NOUN
ajst-31210	117	3	comparing	compare	VERB
ajst-31210	117	4	number	number	NOUN
ajst-31210	117	5	manual	manual	ADJ
ajst-31210	117	6	counting	counting	NOUN
ajst-31210	117	7	network	network	NOUN
ajst-31210	117	8	prediction	prediction	NOUN
ajst-31210	117	9	absolute	absolute	ADJ
ajst-31210	117	10	error	error	NOUN
ajst-31210	117	11	1	1	NUM
ajst-31210	117	12	23	23	NUM
ajst-31210	117	13	24	24	NUM
ajst-31210	117	14	0.043	0.043	NUM
ajst-31210	117	15	2	2	NUM
ajst-31210	117	16	18	18	NUM
ajst-31210	117	17	17	17	NUM
ajst-31210	117	18	0.055	0.055	NUM
ajst-31210	117	19	3	3	NUM
ajst-31210	117	20	34	34	NUM
ajst-31210	117	21	32	32	NUM
ajst-31210	117	22	0.058	0.058	NUM
ajst-31210	117	23	4	4	NUM
ajst-31210	117	24	22	22	NUM
ajst-31210	117	25	19	19	NUM
ajst-31210	117	26	0.136	0.136	NUM
ajst-31210	117	27	5	5	NUM
ajst-31210	117	28	20	20	NUM
ajst-31210	117	29	19	19	NUM
ajst-31210	117	30	0.050	0.050	NUM
ajst-31210	117	31	6	6	NUM
ajst-31210	117	32	39	39	NUM
ajst-31210	117	33	41	41	NUM
ajst-31210	117	34	0.051	0.051	NUM
ajst-31210	117	35	7	7	NUM
ajst-31210	117	36	50	50	NUM
ajst-31210	117	37	46	46	NUM
ajst-31210	117	38	0.080	0.080	NUM
ajst-31210	117	39	8	8	NUM
ajst-31210	117	40	45	45	NUM
ajst-31210	117	41	47	47	NUM
ajst-31210	117	42	0.044	0.044	NUM
ajst-31210	117	43	9	9	NUM
ajst-31210	117	44	39	39	NUM
ajst-31210	117	45	38	38	NUM
ajst-31210	117	46	0.025	0.025	NUM
ajst-31210	117	47	10	10	NUM
ajst-31210	117	48	47	47	NUM
ajst-31210	117	49	48	48	NUM
ajst-31210	117	50	0.021	0.021	NUM
ajst-31210	117	51	11	11	NUM
ajst-31210	117	52	49	49	NUM
ajst-31210	117	53	45	45	NUM
ajst-31210	117	54	0.081	0.081	NUM
ajst-31210	117	55	12	12	NUM
ajst-31210	117	56	38	38	NUM
ajst-31210	117	57	37	37	NUM
ajst-31210	117	58	0.026	0.026	NUM
ajst-31210	117	59	13	13	NUM
ajst-31210	117	60	44	44	NUM
ajst-31210	117	61	46	46	NUM
ajst-31210	117	62	0.045	0.045	NUM
ajst-31210	117	63	14	14	NUM
ajst-31210	117	64	45	45	NUM
ajst-31210	117	65	46	46	NUM
ajst-31210	117	66	0.022	0.022	NUM
ajst-31210	117	67	15	15	NUM
ajst-31210	117	68	46	46	NUM
ajst-31210	117	69	46	46	NUM
ajst-31210	117	70	0	0	NUM
ajst-31210	117	71	16	16	NUM
ajst-31210	117	72	37	37	NUM
ajst-31210	117	73	43	43	NUM
ajst-31210	117	74	0.162	0.162	NUM
ajst-31210	117	75	17	17	NUM
ajst-31210	117	76	42	42	NUM
ajst-31210	117	77	42	42	NUM
ajst-31210	117	78	0	0	NUM
ajst-31210	117	79	18	18	NUM
ajst-31210	117	80	18	18	NUM
ajst-31210	117	81	16	16	NUM
ajst-31210	117	82	0.222	0.222	NUM
ajst-31210	117	83	19	19	NUM
ajst-31210	117	84	21	21	NUM
ajst-31210	117	85	16	16	NUM
ajst-31210	117	86	0.238	0.238	NUM
ajst-31210	117	87	20	20	NUM
ajst-31210	117	88	19	19	NUM
ajst-31210	117	89	20	20	NUM
ajst-31210	117	90	0.052	0.052	NUM
ajst-31210	117	91	mae	mae	PROPN
ajst-31210	117	92	0.065	0.065	NUM
ajst-31210	117	93	4	4	NUM
ajst-31210	117	94	.	.	PUNCT
ajst-31210	117	95	conclusion	conclusion	NOUN
ajst-31210	117	96	this	this	DET
ajst-31210	117	97	article	article	NOUN
ajst-31210	117	98	is	be	AUX
ajst-31210	117	99	based	base	VERB
ajst-31210	117	100	on	on	ADP
ajst-31210	117	101	mcnn	mcnn	NOUN
ajst-31210	117	102	to	to	PART
ajst-31210	117	103	detect	detect	VERB
ajst-31210	117	104	the	the	DET
ajst-31210	117	105	density	density	NOUN
ajst-31210	117	106	and	and	CCONJ
ajst-31210	117	107	quantity	quantity	NOUN
ajst-31210	117	108	of	of	ADP
ajst-31210	117	109	rice	rice	NOUN
ajst-31210	117	110	seeds	seed	NOUN
ajst-31210	117	111	in	in	ADP
ajst-31210	117	112	the	the	DET
ajst-31210	117	113	seedling	seedling	NOUN
ajst-31210	117	114	tray	tray	NOUN
ajst-31210	117	115	.	.	PUNCT
ajst-31210	118	1	the	the	DET
ajst-31210	118	2	accuracy	accuracy	NOUN
ajst-31210	118	3	and	and	CCONJ
ajst-31210	118	4	efficiency	efficiency	NOUN
ajst-31210	118	5	of	of	ADP
ajst-31210	118	6	the	the	DET
ajst-31210	118	7	model	model	NOUN
ajst-31210	118	8	are	be	AUX
ajst-31210	118	9	improved	improve	VERB
ajst-31210	118	10	through	through	ADP
ajst-31210	118	11	parallel	parallel	ADJ
ajst-31210	118	12	computing	computing	NOUN
ajst-31210	118	13	of	of	ADP
ajst-31210	118	14	three	three	NUM
ajst-31210	118	15	columns	column	NOUN
ajst-31210	118	16	of	of	ADP
ajst-31210	118	17	convolutional	convolutional	ADJ
ajst-31210	118	18	networks	network	NOUN
ajst-31210	118	19	.	.	PUNCT
ajst-31210	119	1	the	the	DET
ajst-31210	119	2	three	three	NUM
ajst-31210	119	3	networks	network	NOUN
ajst-31210	119	4	respectively	respectively	ADV
ajst-31210	119	5	sense	sense	VERB
ajst-31210	119	6	the	the	DET
ajst-31210	119	7	features	feature	NOUN
ajst-31210	119	8	of	of	ADP
ajst-31210	119	9	different	different	ADJ
ajst-31210	119	10	receptive	receptive	ADJ
ajst-31210	119	11	fields	field	NOUN
ajst-31210	119	12	,	,	PUNCT
ajst-31210	119	13	and	and	CCONJ
ajst-31210	119	14	even	even	ADV
ajst-31210	119	15	if	if	SCONJ
ajst-31210	119	16	the	the	DET
ajst-31210	119	17	image	image	NOUN
ajst-31210	119	18	resolution	resolution	NOUN
ajst-31210	119	19	or	or	CCONJ
ajst-31210	119	20	shooting	shooting	NOUN
ajst-31210	119	21	angle	angle	NOUN
ajst-31210	119	22	leads	lead	VERB
ajst-31210	119	23	to	to	ADP
ajst-31210	119	24	different	different	ADJ
ajst-31210	119	25	sizes	size	NOUN
ajst-31210	119	26	of	of	ADP
ajst-31210	119	27	rice	rice	NOUN
ajst-31210	119	28	seeds	seed	NOUN
ajst-31210	119	29	,	,	PUNCT
ajst-31210	119	30	each	each	DET
ajst-31210	119	31	column	column	NOUN
ajst-31210	119	32	of	of	ADP
ajst-31210	119	33	convolutional	convolutional	ADJ
ajst-31210	119	34	network	network	NOUN
ajst-31210	119	35	can	can	AUX
ajst-31210	119	36	still	still	ADV
ajst-31210	119	37	adapt	adapt	VERB
ajst-31210	119	38	.	.	PUNCT
ajst-31210	120	1	create	create	VERB
ajst-31210	120	2	a	a	DET
ajst-31210	120	3	dataset	dataset	NOUN
ajst-31210	120	4	of	of	ADP
ajst-31210	120	5	rice	rice	NOUN
ajst-31210	120	6	seedling	seedling	NOUN
ajst-31210	120	7	tray	tray	NOUN
ajst-31210	120	8	original	original	ADJ
ajst-31210	120	9	images	image	NOUN
ajst-31210	120	10	and	and	CCONJ
ajst-31210	120	11	design	design	VERB
ajst-31210	120	12	python	python	NOUN
ajst-31210	120	13	scripts	script	NOUN
ajst-31210	120	14	for	for	ADP
ajst-31210	120	15	automated	automate	VERB
ajst-31210	120	16	processing	processing	NOUN
ajst-31210	120	17	to	to	PART
ajst-31210	120	18	improve	improve	VERB
ajst-31210	120	19	the	the	DET
ajst-31210	120	20	efficiency	efficiency	NOUN
ajst-31210	120	21	of	of	ADP
ajst-31210	120	22	dataset	dataset	NOUN
ajst-31210	120	23	processing	processing	NOUN
ajst-31210	120	24	.	.	PUNCT
ajst-31210	121	1	mark	mark	VERB
ajst-31210	121	2	the	the	DET
ajst-31210	121	3	rice	rice	NOUN
ajst-31210	121	4	seeds	seed	NOUN
ajst-31210	121	5	in	in	ADP
ajst-31210	121	6	the	the	DET
ajst-31210	121	7	graph	graph	NOUN
ajst-31210	121	8	using	use	VERB
ajst-31210	121	9	cclabeler	cclabeler	NOUN
ajst-31210	121	10	,	,	PUNCT
ajst-31210	121	11	generate	generate	VERB
ajst-31210	121	12	an	an	DET
ajst-31210	121	13	h5	h5	NOUN
ajst-31210	121	14	file	file	NOUN
ajst-31210	121	15	,	,	PUNCT
ajst-31210	121	16	and	and	CCONJ
ajst-31210	121	17	organize	organize	VERB
ajst-31210	121	18	it	it	PRON
ajst-31210	121	19	into	into	ADP
ajst-31210	121	20	a	a	DET
ajst-31210	121	21	usable	usable	ADJ
ajst-31210	121	22	dataset	dataset	NOUN
ajst-31210	121	23	called	call	VERB
ajst-31210	121	24	corndataset	corndataset	NOUN
ajst-31210	121	25	.	.	PUNCT
ajst-31210	122	1	then	then	ADV
ajst-31210	122	2	start	start	VERB
ajst-31210	122	3	training	train	VERB
ajst-31210	122	4	the	the	DET
ajst-31210	122	5	model	model	NOUN
ajst-31210	122	6	.	.	PUNCT
ajst-31210	123	1	in	in	ADP
ajst-31210	123	2	the	the	DET
ajst-31210	123	3	process	process	NOUN
ajst-31210	123	4	of	of	ADP
ajst-31210	123	5	finding	find	VERB
ajst-31210	123	6	the	the	DET
ajst-31210	123	7	best	good	ADJ
ajst-31210	123	8	model	model	NOUN
ajst-31210	123	9	parameters	parameter	NOUN
ajst-31210	123	10	,	,	PUNCT
ajst-31210	123	11	use	use	VERB
ajst-31210	123	12	pp	pp	NOUN
ajst-31210	123	13	paddlepaddle	paddlepaddle	ADJ
ajst-31210	123	14	visualdl	visualdl	NOUN
ajst-31210	123	15	to	to	PART
ajst-31210	123	16	visually	visually	ADV
ajst-31210	123	17	adjust	adjust	VERB
ajst-31210	123	18	the	the	DET
ajst-31210	123	19	parameters	parameter	NOUN
ajst-31210	123	20	.	.	PUNCT
ajst-31210	124	1	when	when	SCONJ
ajst-31210	124	2	adjusting	adjust	VERB
ajst-31210	124	3	the	the	DET
ajst-31210	124	4	learning	learning	NOUN
ajst-31210	124	5	rate	rate	NOUN
ajst-31210	124	6	,	,	PUNCT
ajst-31210	124	7	it	it	PRON
ajst-31210	124	8	is	be	AUX
ajst-31210	124	9	found	find	VERB
ajst-31210	124	10	that	that	SCONJ
ajst-31210	124	11	the	the	DET
ajst-31210	124	12	learning	learning	NOUN
ajst-31210	124	13	rate	rate	NOUN
ajst-31210	124	14	is	be	AUX
ajst-31210	124	15	the	the	DET
ajst-31210	124	16	best	good	ADJ
ajst-31210	124	17	at	at	ADP
ajst-31210	124	18	1e-4	1e-4	NOUN
ajst-31210	124	19	.	.	PUNCT
ajst-31210	125	1	not	not	PART
ajst-31210	125	2	only	only	ADV
ajst-31210	125	3	does	do	AUX
ajst-31210	125	4	mae	mae	PROPN
ajst-31210	125	5	converge	converge	VERB
ajst-31210	125	6	,	,	PUNCT
ajst-31210	125	7	but	but	CCONJ
ajst-31210	125	8	also	also	ADV
ajst-31210	125	9	the	the	DET
ajst-31210	125	10	lower	low	ADJ
ajst-31210	125	11	limit	limit	NOUN
ajst-31210	125	12	of	of	ADP
ajst-31210	125	13	mae	mae	PROPN
ajst-31210	125	14	is	be	AUX
ajst-31210	125	15	the	the	DET
ajst-31210	125	16	lowest	low	ADJ
ajst-31210	125	17	.	.	PUNCT
ajst-31210	126	1	therefore	therefore	ADV
ajst-31210	126	2	,	,	PUNCT
ajst-31210	126	3	choose	choose	VERB
ajst-31210	126	4	epoch	epoch	NOUN
ajst-31210	126	5	and	and	CCONJ
ajst-31210	126	6	learning	learn	VERB
ajst-31210	126	7	rate	rate	NOUN
ajst-31210	126	8	parameters	parameter	NOUN
ajst-31210	126	9	to	to	PART
ajst-31210	126	10	train	train	VERB
ajst-31210	126	11	the	the	DET
ajst-31210	126	12	best	good	ADJ
ajst-31210	126	13	model	model	NOUN
ajst-31210	126	14	.	.	PUNCT
ajst-31210	127	1	by	by	ADP
ajst-31210	127	2	comparing	compare	VERB
ajst-31210	127	3	the	the	DET
ajst-31210	127	4	statistics	statistic	NOUN
ajst-31210	127	5	of	of	ADP
ajst-31210	127	6	network	network	NOUN
ajst-31210	127	7	input	input	NOUN
ajst-31210	127	8	images	image	NOUN
ajst-31210	127	9	with	with	ADP
ajst-31210	127	10	manual	manual	ADJ
ajst-31210	127	11	counting	counting	NOUN
ajst-31210	127	12	,	,	PUNCT
ajst-31210	127	13	the	the	DET
ajst-31210	127	14	accuracy	accuracy	NOUN
ajst-31210	127	15	of	of	ADP
ajst-31210	127	16	the	the	DET
ajst-31210	127	17	model	model	NOUN
ajst-31210	127	18	was	be	AUX
ajst-31210	127	19	analyzed	analyze	VERB
ajst-31210	127	20	.	.	PUNCT
ajst-31210	128	1	after	after	ADP
ajst-31210	128	2	comparing	compare	VERB
ajst-31210	128	3	the	the	DET
ajst-31210	128	4	results	result	NOUN
ajst-31210	128	5	with	with	ADP
ajst-31210	128	6	manual	manual	ADJ
ajst-31210	128	7	counting	counting	NOUN
ajst-31210	128	8	,	,	PUNCT
ajst-31210	128	9	the	the	DET
ajst-31210	128	10	average	average	ADJ
ajst-31210	128	11	absolute	absolute	ADJ
ajst-31210	128	12	error	error	NOUN
ajst-31210	128	13	was	be	AUX
ajst-31210	128	14	only	only	ADV
ajst-31210	128	15	0.065	0.065	NUM
ajst-31210	128	16	.	.	PUNCT
ajst-31210	129	1	this	this	DET
ajst-31210	129	2	model	model	NOUN
ajst-31210	129	3	can	can	AUX
ajst-31210	129	4	be	be	AUX
ajst-31210	129	5	applied	apply	VERB
ajst-31210	129	6	to	to	ADP
ajst-31210	129	7	application	application	NOUN
ajst-31210	129	8	scenarios	scenario	NOUN
ajst-31210	129	9	with	with	ADP
ajst-31210	129	10	lower	low	ADJ
ajst-31210	129	11	error	error	NOUN
ajst-31210	129	12	requirements	requirement	NOUN
ajst-31210	129	13	.	.	PUNCT
ajst-31210	130	1	the	the	DET
ajst-31210	130	2	model	model	NOUN
ajst-31210	130	3	still	still	ADV
ajst-31210	130	4	needs	need	VERB
ajst-31210	130	5	continuous	continuous	ADJ
ajst-31210	130	6	improvement	improvement	NOUN
ajst-31210	130	7	to	to	PART
ajst-31210	130	8	enhance	enhance	VERB
ajst-31210	130	9	its	its	PRON
ajst-31210	130	10	accuracy	accuracy	NOUN
ajst-31210	130	11	.	.	PUNCT
ajst-31210	131	1	acknowledgment	acknowledgment	NOUN
ajst-31210	131	2	college	college	NOUN
ajst-31210	131	3	student	student	NOUN
ajst-31210	131	4	innovation	innovation	NOUN
ajst-31210	131	5	and	and	CCONJ
ajst-31210	131	6	entrepreneurship	entrepreneurship	NOUN
ajst-31210	131	7	program	program	NOUN
ajst-31210	131	8	project	project	NOUN
ajst-31210	131	9	(	(	PUNCT
ajst-31210	131	10	24c159	24c159	NOUN
ajst-31210	131	11	)	)	PUNCT
ajst-31210	131	12	.	.	PUNCT
ajst-31210	132	1	references	reference	NOUN
ajst-31210	132	2	[	[	X
ajst-31210	132	3	1	1	NUM
ajst-31210	132	4	]	]	PUNCT
ajst-31210	132	5	yuan	yuan	NOUN
ajst-31210	132	6	peichao	peichao	NOUN
ajst-31210	132	7	,	,	PUNCT
ajst-31210	132	8	ji	ji	PROPN
ajst-31210	132	9	yao	yao	PROPN
ajst-31210	132	10	,	,	PUNCT
ajst-31210	132	11	zhang	zhang	PROPN
ajst-31210	132	12	wenyi	wenyi	PROPN
ajst-31210	132	13	,	,	PUNCT
ajst-31210	132	14	et	et	PROPN
ajst-31210	132	15	al	al	PROPN
ajst-31210	132	16	.	.	PUNCT
ajst-31210	132	17	research	research	NOUN
ajst-31210	132	18	status	status	NOUN
ajst-31210	132	19	and	and	CCONJ
ajst-31210	132	20	prospects	prospect	NOUN
ajst-31210	132	21	of	of	ADP
ajst-31210	132	22	mechanized	mechanized	ADJ
ajst-31210	132	23	transplanting	transplanting	NOUN
ajst-31210	132	24	of	of	ADP
ajst-31210	132	25	bowl	bowl	NOUN
ajst-31210	132	26	-	-	PUNCT
ajst-31210	132	27	seedlings	seedling	NOUN
ajst-31210	132	28	in	in	ADP
ajst-31210	132	29	rice	rice	NOUN
ajst-31210	133	1	[	[	X
ajst-31210	133	2	j	j	X
ajst-31210	133	3	]	]	X
ajst-31210	133	4	.	.	PUNCT
ajst-31210	134	1	journal	journal	PROPN
ajst-31210	134	2	of	of	ADP
ajst-31210	134	3	chinese	chinese	ADJ
ajst-31210	134	4	agricultural	agricultural	ADJ
ajst-31210	134	5	mechanization	mechanization	NOUN
ajst-31210	134	6	,	,	PUNCT
ajst-31210	134	7	2025	2025	NUM
ajst-31210	134	8	,	,	PUNCT
ajst-31210	134	9	46	46	NUM
ajst-31210	134	10	(	(	PUNCT
ajst-31210	134	11	04	04	NUM
ajst-31210	134	12	):	):	PUNCT
ajst-31210	134	13	29	29	NUM
ajst-31210	134	14	-	-	SYM
ajst-31210	134	15	34	34	NUM
ajst-31210	134	16	+	+	SYM
ajst-31210	134	17	57	57	NUM
ajst-31210	134	18	.	.	PUNCT
ajst-31210	135	1	[	[	X
ajst-31210	135	2	2	2	X
ajst-31210	135	3	]	]	PUNCT
ajst-31210	135	4	wang	wang	PROPN
ajst-31210	135	5	zhicheng	zhicheng	PROPN
ajst-31210	135	6	,	,	PUNCT
ajst-31210	135	7	zhan	zhan	PROPN
ajst-31210	135	8	xiaokang	xiaokang	PROPN
ajst-31210	135	9	,	,	PUNCT
ajst-31210	135	10	xue	xue	PROPN
ajst-31210	135	11	yang	yang	PROPN
ajst-31210	135	12	,	,	PUNCT
ajst-31210	135	13	et	et	PROPN
ajst-31210	135	14	al	al	PROPN
ajst-31210	135	15	.	.	PROPN
ajst-31210	135	16	effect	effect	NOUN
ajst-31210	135	17	of	of	ADP
ajst-31210	135	18	piriformospora	piriformospora	PROPN
ajst-31210	135	19	indica	indica	PROPN
ajst-31210	135	20	on	on	ADP
ajst-31210	135	21	seedling	seedle	VERB
ajst-31210	135	22	quality	quality	NOUN
ajst-31210	135	23	in	in	ADP
ajst-31210	135	24	rice	rice	NOUN
ajst-31210	135	25	machanical	machanical	ADJ
ajst-31210	135	26	transplanting	transplanting	NOUN
ajst-31210	135	27	[	[	X
ajst-31210	135	28	j	j	X
ajst-31210	135	29	]	]	X
ajst-31210	135	30	.	.	PUNCT
ajst-31210	136	1	journal	journal	PROPN
ajst-31210	136	2	of	of	ADP
ajst-31210	136	3	agricultural	agricultural	ADJ
ajst-31210	136	4	science	science	NOUN
ajst-31210	136	5	and	and	CCONJ
ajst-31210	136	6	technology	technology	NOUN
ajst-31210	136	7	,	,	PUNCT
ajst-31210	136	8	1	1	NUM
ajst-31210	136	9	-	-	SYM
ajst-31210	136	10	12	12	NUM
ajst-31210	136	11	.	.	PUNCT
ajst-31210	137	1	[	[	X
ajst-31210	137	2	3	3	X
ajst-31210	137	3	]	]	X
ajst-31210	137	4	jia	jia	PROPN
ajst-31210	137	5	peng	peng	PROPN
ajst-31210	137	6	,	,	PUNCT
ajst-31210	137	7	li	li	PROPN
ajst-31210	137	8	yongkui	yongkui	PROPN
ajst-31210	137	9	,	,	PUNCT
ajst-31210	137	10	zhao	zhao	PROPN
ajst-31210	137	11	ping	ping	PROPN
ajst-31210	137	12	.	.	PUNCT
ajst-31210	138	1	grain	grain	NOUN
ajst-31210	138	2	counting	counting	NOUN
ajst-31210	138	3	method	method	NOUN
ajst-31210	138	4	based	base	VERB
ajst-31210	138	5	on	on	ADP
ajst-31210	138	6	matlab	matlab	PROPN
ajst-31210	138	7	image	image	NOUN
ajst-31210	138	8	processing	processing	NOUN
ajst-31210	138	9	[	[	X
ajst-31210	138	10	j	j	X
ajst-31210	138	11	]	]	X
ajst-31210	138	12	.	.	PUNCT
ajst-31210	139	1	journal	journal	PROPN
ajst-31210	139	2	of	of	ADP
ajst-31210	139	3	agricultural	agricultural	ADJ
ajst-31210	139	4	mechanization	mechanization	NOUN
ajst-31210	139	5	research	research	NOUN
ajst-31210	139	6	,	,	PUNCT
ajst-31210	139	7	2009	2009	NUM
ajst-31210	139	8	,	,	PUNCT
ajst-31210	139	9	31	31	NUM
ajst-31210	139	10	(	(	PUNCT
ajst-31210	139	11	1	1	NUM
ajst-31210	139	12	):	):	PUNCT
ajst-31210	139	13	152	152	NUM
ajst-31210	139	14	-	-	SYM
ajst-31210	139	15	153	153	NUM
ajst-31210	139	16	,	,	PUNCT
ajst-31210	139	17	156	156	NUM
ajst-31210	139	18	.	.	PUNCT
ajst-31210	140	1	[	[	X
ajst-31210	140	2	4	4	NUM
ajst-31210	140	3	]	]	X
ajst-31210	140	4	tian	tian	PROPN
ajst-31210	140	5	mengxiang	mengxiang	PROPN
ajst-31210	140	6	,	,	PUNCT
ajst-31210	140	7	zhang	zhang	PROPN
ajst-31210	140	8	shilong	shilong	PROPN
ajst-31210	140	9	,	,	PUNCT
ajst-31210	140	10	he	he	PRON
ajst-31210	140	11	youxun	youxun	PROPN
ajst-31210	140	12	,	,	PUNCT
ajst-31210	140	13	et	et	PROPN
ajst-31210	140	14	al	al	PROPN
ajst-31210	140	15	.	.	PUNCT
ajst-31210	141	1	a	a	DET
ajst-31210	141	2	fast	fast	ADJ
ajst-31210	141	3	and	and	CCONJ
ajst-31210	141	4	efficient	efficient	ADJ
ajst-31210	141	5	automatic	automatic	ADJ
ajst-31210	141	6	counting	counting	NOUN
ajst-31210	141	7	method	method	NOUN
ajst-31210	141	8	for	for	ADP
ajst-31210	141	9	rice	rice	NOUN
ajst-31210	141	10	grains	grain	NOUN
ajst-31210	142	1	[	[	X
ajst-31210	142	2	j	j	X
ajst-31210	142	3	]	]	X
ajst-31210	142	4	.	.	PUNCT
ajst-31210	143	1	jiangsu	jiangsu	PROPN
ajst-31210	143	2	agricultural	agricultural	PROPN
ajst-31210	143	3	science	science	PROPN
ajst-31210	143	4	,	,	PUNCT
ajst-31210	143	5	2014	2014	NUM
ajst-31210	143	6	,	,	PUNCT
ajst-31210	143	7	42	42	NUM
ajst-31210	143	8	(	(	PUNCT
ajst-31210	143	9	2	2	NUM
ajst-31210	143	10	):	):	PUNCT
ajst-31210	143	11	64	64	NUM
ajst-31210	143	12	-	-	SYM
ajst-31210	143	13	66	66	NUM
ajst-31210	144	1	[	[	X
ajst-31210	144	2	5	5	NUM
ajst-31210	144	3	]	]	X
ajst-31210	144	4	deng	deng	PROPN
ajst-31210	144	5	xiangwu	xiangwu	PROPN
ajst-31210	144	6	,	,	PUNCT
ajst-31210	144	7	ma	ma	PROPN
ajst-31210	144	8	xu	xu	PROPN
ajst-31210	144	9	,	,	PUNCT
ajst-31210	144	10	qi	qi	PROPN
ajst-31210	144	11	long	long	ADV
ajst-31210	144	12	,	,	PUNCT
ajst-31210	144	13	et	et	PROPN
ajst-31210	144	14	al	al	PROPN
ajst-31210	144	15	.	.	PUNCT
ajst-31210	144	16	detection	detection	NOUN
ajst-31210	144	17	on	on	ADP
ajst-31210	144	18	rice	rice	NOUN
ajst-31210	144	19	seeds	seed	NOUN
ajst-31210	144	20	quantitiy	quantitiy	VERB
ajst-31210	144	21	per	per	ADP
ajst-31210	144	22	hole	hole	NOUN
ajst-31210	144	23	of	of	ADP
ajst-31210	144	24	the	the	DET
ajst-31210	144	25	pot	pot	NOUN
ajst-31210	144	26	body	body	NOUN
ajst-31210	144	27	seed	seed	NOUN
ajst-31210	144	28	tray	tray	NOUN
ajst-31210	144	29	based	base	VERB
ajst-31210	144	30	on	on	ADP
ajst-31210	144	31	convolutional	convolutional	ADJ
ajst-31210	144	32	network	network	NOUN
ajst-31210	144	33	[	[	X
ajst-31210	144	34	j	j	X
ajst-31210	144	35	]	]	X
ajst-31210	144	36	.	.	PUNCT
ajst-31210	145	1	journal	journal	PROPN
ajst-31210	145	2	of	of	ADP
ajst-31210	145	3	chinese	chinese	ADJ
ajst-31210	145	4	agricultural	agricultural	ADJ
ajst-31210	145	5	mechanization	mechanization	NOUN
ajst-31210	145	6	,	,	PUNCT
ajst-31210	145	7	2020	2020	NUM
ajst-31210	145	8	,	,	PUNCT
ajst-31210	145	9	41(7	41(7	NUM
ajst-31210	145	10	):	):	PUNCT
ajst-31210	145	11	130	130	NUM
ajst-31210	145	12	-	-	SYM
ajst-31210	145	13	136	136	NUM
ajst-31210	145	14	.	.	PUNCT
ajst-31210	146	1	[	[	X
ajst-31210	146	2	6	6	NUM
ajst-31210	146	3	]	]	PUNCT
ajst-31210	146	4	steven	steven	PROPN
ajst-31210	146	5	w.	w.	PROPN
ajst-31210	146	6	chen	chen	PROPN
ajst-31210	146	7	,	,	PUNCT
ajst-31210	146	8	shreyas	shreyas	PROPN
ajst-31210	146	9	s.	s.	PROPN
ajst-31210	146	10	shivakumar	shivakumar	PROPN
ajst-31210	146	11	,	,	PUNCT
ajst-31210	146	12	sandeep	sandeep	PROPN
ajst-31210	146	13	dcunha	dcunha	NOUN
ajst-31210	146	14	,	,	PUNCT
ajst-31210	146	15	et	et	PROPN
ajst-31210	146	16	al	al	PROPN
ajst-31210	146	17	.	.	PUNCT
ajst-31210	146	18	counting	count	VERB
ajst-31210	146	19	apples	apple	NOUN
ajst-31210	146	20	and	and	CCONJ
ajst-31210	146	21	orange	orange	NOUN
ajst-31210	146	22	with	with	ADP
ajst-31210	146	23	deep	deep	ADJ
ajst-31210	146	24	learning	learning	NOUN
ajst-31210	146	25	:	:	PUNCT
ajst-31210	146	26	a	a	DET
ajst-31210	146	27	datadriven	datadriven	ADJ
ajst-31210	146	28	approach[j	approach[j	NOUN
ajst-31210	146	29	]	]	X
ajst-31210	146	30	.	.	PUNCT
ajst-31210	147	1	ieee	ieee	NOUN
ajst-31210	147	2	robotics	robotic	NOUN
ajst-31210	147	3	and	and	CCONJ
ajst-31210	147	4	automation	automation	NOUN
ajst-31210	147	5	letters	letter	NOUN
ajst-31210	147	6	,	,	PUNCT
ajst-31210	147	7	2017	2017	NUM
ajst-31210	147	8	,	,	PUNCT
ajst-31210	147	9	02(02	02(02	NOUN
ajst-31210	147	10	):	):	PUNCT
ajst-31210	147	11	781	781	NUM
ajst-31210	147	12	.	.	PUNCT