id	sid	tid	token	lemma	pos
ajst-19200	1	1	academic	academic	ADJ
ajst-19200	1	2	journal	journal	NOUN
ajst-19200	1	3	of	of	ADP
ajst-19200	1	4	science	science	NOUN
ajst-19200	1	5	and	and	CCONJ
ajst-19200	1	6	technology	technology	NOUN
ajst-19200	1	7	issn	issn	NOUN
ajst-19200	1	8	:	:	PUNCT
ajst-19200	1	9	2771	2771	NUM
ajst-19200	1	10	-	-	SYM
ajst-19200	1	11	3032	3032	NUM
ajst-19200	1	12	|	|	NOUN
ajst-19200	1	13	vol	vol	NOUN
ajst-19200	1	14	.	.	PROPN
ajst-19200	2	1	10	10	NUM
ajst-19200	2	2	,	,	PUNCT
ajst-19200	2	3	no	no	INTJ
ajst-19200	2	4	.	.	NOUN
ajst-19200	2	5	1	1	NUM
ajst-19200	2	6	,	,	PUNCT
ajst-19200	2	7	2024	2024	NUM
ajst-19200	2	8	272	272	NUM
ajst-19200	2	9	detection	detection	NOUN
ajst-19200	2	10	of	of	ADP
ajst-19200	2	11	rice	rice	NOUN
ajst-19200	2	12	leaf	leaf	NOUN
ajst-19200	2	13	diseases	disease	NOUN
ajst-19200	2	14	based	base	VERB
ajst-19200	2	15	on	on	ADP
ajst-19200	2	16	improved	improved	ADJ
ajst-19200	2	17	yolov8n	yolov8n	PROPN
ajst-19200	2	18	xue	xue	PROPN
ajst-19200	2	19	liu1	liu1	PROPN
ajst-19200	2	20	,	,	PUNCT
ajst-19200	2	21	shunyong	shunyong	ADJ
ajst-19200	2	22	zhou1	zhou1	PROPN
ajst-19200	2	23	,	,	PUNCT
ajst-19200	2	24	*	*	PUNCT
ajst-19200	2	25	,	,	PUNCT
ajst-19200	2	26	ziyang	ziyang	PROPN
ajst-19200	2	27	peng1	peng1	PROPN
ajst-19200	2	28	,	,	PUNCT
ajst-19200	2	29	hangling	hangling	ADJ
ajst-19200	2	30	zhang1	zhang1	NOUN
ajst-19200	2	31	,	,	PUNCT
ajst-19200	2	32	qin	qin	PROPN
ajst-19200	3	1	hu1	hu1	NOUN
ajst-19200	3	2	1	1	NUM
ajst-19200	3	3	school	school	NOUN
ajst-19200	3	4	of	of	ADP
ajst-19200	3	5	automation	automation	NOUN
ajst-19200	3	6	and	and	CCONJ
ajst-19200	3	7	information	information	NOUN
ajst-19200	3	8	engineering	engineering	NOUN
ajst-19200	3	9	,	,	PUNCT
ajst-19200	3	10	sichuan	sichuan	PROPN
ajst-19200	3	11	university	university	PROPN
ajst-19200	3	12	of	of	ADP
ajst-19200	3	13	science	science	PROPN
ajst-19200	3	14	&	&	CCONJ
ajst-19200	3	15	engineering	engineering	PROPN
ajst-19200	3	16	,	,	PUNCT
ajst-19200	3	17	zigong	zigong	PROPN
ajst-19200	3	18	643000	643000	NUM
ajst-19200	3	19	,	,	PUNCT
ajst-19200	3	20	china	china	PROPN
ajst-19200	3	21	2	2	NUM
ajst-19200	3	22	artificial	artificial	ADJ
ajst-19200	3	23	intelligence	intelligence	NOUN
ajst-19200	3	24	key	key	NOUN
ajst-19200	3	25	laboratory	laboratory	NOUN
ajst-19200	3	26	of	of	ADP
ajst-19200	3	27	sichuan	sichuan	PROPN
ajst-19200	3	28	province	province	PROPN
ajst-19200	3	29	,	,	PUNCT
ajst-19200	3	30	sichuan	sichuan	PROPN
ajst-19200	3	31	university	university	PROPN
ajst-19200	3	32	of	of	ADP
ajst-19200	3	33	science	science	PROPN
ajst-19200	3	34	&	&	CCONJ
ajst-19200	3	35	engineering	engineering	PROPN
ajst-19200	3	36	,	,	PUNCT
ajst-19200	3	37	zigong	zigong	PROPN
ajst-19200	3	38	643000	643000	NUM
ajst-19200	3	39	,	,	PUNCT
ajst-19200	3	40	china	china	PROPN
ajst-19200	3	41	.	.	PUNCT
ajst-19200	4	1	*	*	PUNCT
ajst-19200	4	2	corresponding	correspond	VERB
ajst-19200	4	3	author	author	NOUN
ajst-19200	4	4	:	:	PUNCT
ajst-19200	4	5	shunyong	shunyong	PROPN
ajst-19200	4	6	zhou	zhou	PROPN
ajst-19200	4	7	(	(	PUNCT
ajst-19200	4	8	email	email	NOUN
ajst-19200	4	9	:	:	PUNCT
ajst-19200	4	10	lx1352839149@163.com	lx1352839149@163.com	X
ajst-19200	4	11	)	)	PUNCT
ajst-19200	4	12	abstract	abstract	NOUN
ajst-19200	4	13	:	:	PUNCT
ajst-19200	4	14	rice	rice	NOUN
ajst-19200	4	15	plays	play	VERB
ajst-19200	4	16	an	an	DET
ajst-19200	4	17	important	important	ADJ
ajst-19200	4	18	role	role	NOUN
ajst-19200	4	19	in	in	ADP
ajst-19200	4	20	human	human	ADJ
ajst-19200	4	21	food	food	NOUN
ajst-19200	4	22	chain	chain	NOUN
ajst-19200	4	23	,	,	PUNCT
ajst-19200	4	24	but	but	CCONJ
ajst-19200	4	25	it	it	PRON
ajst-19200	4	26	is	be	AUX
ajst-19200	4	27	easily	easily	ADV
ajst-19200	4	28	affected	affect	VERB
ajst-19200	4	29	by	by	ADP
ajst-19200	4	30	related	related	ADJ
ajst-19200	4	31	diseases	disease	NOUN
ajst-19200	4	32	in	in	ADP
ajst-19200	4	33	its	its	PRON
ajst-19200	4	34	growth	growth	NOUN
ajst-19200	4	35	,	,	PUNCT
ajst-19200	4	36	which	which	PRON
ajst-19200	4	37	seriously	seriously	ADV
ajst-19200	4	38	affects	affect	VERB
ajst-19200	4	39	rice	rice	NOUN
ajst-19200	4	40	yield	yield	NOUN
ajst-19200	4	41	.	.	PUNCT
ajst-19200	5	1	at	at	ADP
ajst-19200	5	2	present	present	ADJ
ajst-19200	5	3	,	,	PUNCT
ajst-19200	5	4	there	there	PRON
ajst-19200	5	5	are	be	VERB
ajst-19200	5	6	many	many	ADJ
ajst-19200	5	7	methods	method	NOUN
ajst-19200	5	8	to	to	PART
ajst-19200	5	9	detect	detect	VERB
ajst-19200	5	10	rice	rice	NOUN
ajst-19200	5	11	leaf	leaf	NOUN
ajst-19200	5	12	diseases	disease	NOUN
ajst-19200	5	13	,	,	PUNCT
ajst-19200	5	14	but	but	CCONJ
ajst-19200	5	15	there	there	PRON
ajst-19200	5	16	are	be	VERB
ajst-19200	5	17	still	still	ADV
ajst-19200	5	18	problems	problem	NOUN
ajst-19200	5	19	such	such	ADJ
ajst-19200	5	20	as	as	ADP
ajst-19200	5	21	large	large	ADJ
ajst-19200	5	22	model	model	NOUN
ajst-19200	5	23	and	and	CCONJ
ajst-19200	5	24	poor	poor	ADJ
ajst-19200	5	25	detection	detection	NOUN
ajst-19200	5	26	effect	effect	NOUN
ajst-19200	5	27	.	.	PUNCT
ajst-19200	6	1	in	in	ADP
ajst-19200	6	2	order	order	NOUN
ajst-19200	6	3	to	to	PART
ajst-19200	6	4	solve	solve	VERB
ajst-19200	6	5	the	the	DET
ajst-19200	6	6	limitations	limitation	NOUN
ajst-19200	6	7	of	of	ADP
ajst-19200	6	8	traditional	traditional	ADJ
ajst-19200	6	9	manual	manual	NOUN
ajst-19200	6	10	and	and	CCONJ
ajst-19200	6	11	deep	deep	ADJ
ajst-19200	6	12	learning	learning	NOUN
ajst-19200	6	13	-	-	PUNCT
ajst-19200	6	14	based	base	VERB
ajst-19200	6	15	models	model	NOUN
ajst-19200	6	16	,	,	PUNCT
ajst-19200	6	17	a	a	DET
ajst-19200	6	18	lightweight	lightweight	ADJ
ajst-19200	6	19	model	model	NOUN
ajst-19200	6	20	based	base	VERB
ajst-19200	6	21	on	on	ADP
ajst-19200	6	22	improved	improved	ADJ
ajst-19200	6	23	yolov8n	yolov8n	NOUN
ajst-19200	6	24	is	be	AUX
ajst-19200	6	25	proposed	propose	VERB
ajst-19200	6	26	.	.	PUNCT
ajst-19200	7	1	firstly	firstly	ADV
ajst-19200	7	2	,	,	PUNCT
ajst-19200	7	3	sppd	sppd	PROPN
ajst-19200	7	4	(	(	PUNCT
ajst-19200	7	5	spatial	spatial	ADJ
ajst-19200	7	6	pyramid	pyramid	NOUN
ajst-19200	7	7	pooling	pool	VERB
ajst-19200	7	8	and	and	CCONJ
ajst-19200	7	9	dilated	dilated	ADJ
ajst-19200	7	10	)	)	PUNCT
ajst-19200	7	11	structure	structure	NOUN
ajst-19200	7	12	with	with	ADP
ajst-19200	7	13	different	different	ADJ
ajst-19200	7	14	void	void	ADJ
ajst-19200	7	15	ratios	ratio	NOUN
ajst-19200	7	16	composed	compose	VERB
ajst-19200	7	17	of	of	ADP
ajst-19200	7	18	gelu	gelu	ADJ
ajst-19200	7	19	activation	activation	NOUN
ajst-19200	7	20	function	function	NOUN
ajst-19200	7	21	was	be	AUX
ajst-19200	7	22	added	add	VERB
ajst-19200	7	23	to	to	ADP
ajst-19200	7	24	the	the	DET
ajst-19200	7	25	backbone	backbone	NOUN
ajst-19200	7	26	network	network	NOUN
ajst-19200	7	27	to	to	PART
ajst-19200	7	28	increase	increase	VERB
ajst-19200	7	29	the	the	DET
ajst-19200	7	30	receptive	receptive	ADJ
ajst-19200	7	31	field	field	NOUN
ajst-19200	7	32	of	of	ADP
ajst-19200	7	33	the	the	DET
ajst-19200	7	34	network	network	NOUN
ajst-19200	7	35	,	,	PUNCT
ajst-19200	7	36	and	and	CCONJ
ajst-19200	7	37	coordinate	coordinate	VERB
ajst-19200	7	38	attention	attention	NOUN
ajst-19200	7	39	(	(	PUNCT
ajst-19200	7	40	ca	ca	NOUN
ajst-19200	7	41	)	)	PUNCT
ajst-19200	7	42	was	be	AUX
ajst-19200	7	43	combined	combine	VERB
ajst-19200	7	44	to	to	PART
ajst-19200	7	45	help	help	VERB
ajst-19200	7	46	the	the	DET
ajst-19200	7	47	model	model	NOUN
ajst-19200	7	48	pay	pay	VERB
ajst-19200	7	49	attention	attention	NOUN
ajst-19200	7	50	to	to	ADP
ajst-19200	7	51	the	the	DET
ajst-19200	7	52	characteristics	characteristic	NOUN
ajst-19200	7	53	of	of	ADP
ajst-19200	7	54	rice	rice	NOUN
ajst-19200	7	55	diseases	disease	NOUN
ajst-19200	7	56	and	and	CCONJ
ajst-19200	7	57	improve	improve	VERB
ajst-19200	7	58	the	the	DET
ajst-19200	7	59	detection	detection	NOUN
ajst-19200	7	60	accuracy	accuracy	NOUN
ajst-19200	7	61	.	.	PUNCT
ajst-19200	8	1	finally	finally	ADV
ajst-19200	8	2	,	,	PUNCT
ajst-19200	8	3	xsepconv	xsepconv	PROPN
ajst-19200	8	4	(	(	PUNCT
ajst-19200	8	5	extremely	extremely	ADV
ajst-19200	8	6	separated	separated	ADJ
ajst-19200	8	7	convolution	convolution	NOUN
ajst-19200	8	8	)	)	PUNCT
ajst-19200	8	9	is	be	AUX
ajst-19200	8	10	used	use	VERB
ajst-19200	8	11	to	to	PART
ajst-19200	8	12	reduce	reduce	VERB
ajst-19200	8	13	the	the	DET
ajst-19200	8	14	parameters	parameter	NOUN
ajst-19200	8	15	and	and	CCONJ
ajst-19200	8	16	improve	improve	VERB
ajst-19200	8	17	the	the	DET
ajst-19200	8	18	efficiency	efficiency	NOUN
ajst-19200	8	19	of	of	ADP
ajst-19200	8	20	the	the	DET
ajst-19200	8	21	model	model	NOUN
ajst-19200	8	22	.	.	PUNCT
ajst-19200	9	1	the	the	DET
ajst-19200	9	2	model	model	NOUN
ajst-19200	9	3	was	be	AUX
ajst-19200	9	4	trained	train	VERB
ajst-19200	9	5	and	and	CCONJ
ajst-19200	9	6	tested	test	VERB
ajst-19200	9	7	on	on	ADP
ajst-19200	9	8	the	the	DET
ajst-19200	9	9	self	self	NOUN
ajst-19200	9	10	-	-	PUNCT
ajst-19200	9	11	built	build	VERB
ajst-19200	9	12	rice	rice	NOUN
ajst-19200	9	13	leaf	leaf	NOUN
ajst-19200	9	14	disease	disease	NOUN
ajst-19200	9	15	image	image	NOUN
ajst-19200	9	16	data	datum	NOUN
ajst-19200	9	17	set	set	VERB
ajst-19200	9	18	,	,	PUNCT
ajst-19200	9	19	and	and	CCONJ
ajst-19200	9	20	its	its	PRON
ajst-19200	9	21	map	map	NOUN
ajst-19200	9	22	@0.5	@0.5	PROPN
ajst-19200	9	23	reached	reach	VERB
ajst-19200	9	24	89.3	89.3	NUM
ajst-19200	9	25	%	%	NOUN
ajst-19200	9	26	and	and	CCONJ
ajst-19200	9	27	fps	fps	PROPN
ajst-19200	9	28	reached	reach	VERB
ajst-19200	9	29	217	217	NUM
ajst-19200	9	30	.	.	PUNCT
ajst-19200	10	1	the	the	DET
ajst-19200	10	2	proposed	propose	VERB
ajst-19200	10	3	scx	scx	PROPN
ajst-19200	10	4	-	-	PUNCT
ajst-19200	10	5	yolov8n	yolov8n	NOUN
ajst-19200	10	6	model	model	NOUN
ajst-19200	10	7	is	be	AUX
ajst-19200	10	8	a	a	DET
ajst-19200	10	9	lightweight	lightweight	ADJ
ajst-19200	10	10	,	,	PUNCT
ajst-19200	10	11	efficient	efficient	ADJ
ajst-19200	10	12	and	and	CCONJ
ajst-19200	10	13	high	high	ADJ
ajst-19200	10	14	-	-	PUNCT
ajst-19200	10	15	performance	performance	NOUN
ajst-19200	10	16	rice	rice	NOUN
ajst-19200	10	17	leaf	leaf	NOUN
ajst-19200	10	18	disease	disease	NOUN
ajst-19200	10	19	detection	detection	NOUN
ajst-19200	10	20	model	model	NOUN
ajst-19200	10	21	,	,	PUNCT
ajst-19200	10	22	and	and	CCONJ
ajst-19200	10	23	compared	compare	VERB
ajst-19200	10	24	with	with	ADP
ajst-19200	10	25	other	other	ADJ
ajst-19200	10	26	mainstream	mainstream	NOUN
ajst-19200	10	27	models	model	NOUN
ajst-19200	10	28	,	,	PUNCT
ajst-19200	10	29	it	it	PRON
ajst-19200	10	30	also	also	ADV
ajst-19200	10	31	has	have	VERB
ajst-19200	10	32	certain	certain	ADJ
ajst-19200	10	33	advantages	advantage	NOUN
ajst-19200	10	34	in	in	ADP
ajst-19200	10	35	accuracy	accuracy	NOUN
ajst-19200	10	36	and	and	CCONJ
ajst-19200	10	37	recall	recall	NOUN
ajst-19200	10	38	rate	rate	NOUN
ajst-19200	10	39	,	,	PUNCT
ajst-19200	10	40	which	which	PRON
ajst-19200	10	41	can	can	AUX
ajst-19200	10	42	provide	provide	VERB
ajst-19200	10	43	an	an	DET
ajst-19200	10	44	accurate	accurate	ADJ
ajst-19200	10	45	and	and	CCONJ
ajst-19200	10	46	accurate	accurate	ADJ
ajst-19200	10	47	rice	rice	NOUN
ajst-19200	10	48	leaf	leaf	NOUN
ajst-19200	10	49	disease	disease	NOUN
ajst-19200	10	50	detection	detection	NOUN
ajst-19200	10	51	and	and	CCONJ
ajst-19200	10	52	other	other	ADJ
ajst-19200	10	53	related	related	ADJ
ajst-19200	10	54	fields	field	NOUN
ajst-19200	10	55	.	.	PUNCT
ajst-19200	11	1	keywords	keyword	NOUN
ajst-19200	11	2	:	:	PUNCT
ajst-19200	11	3	rice	rice	NOUN
ajst-19200	11	4	leaf	leaf	NOUN
ajst-19200	11	5	disease	disease	NOUN
ajst-19200	11	6	;	;	PUNCT
ajst-19200	11	7	gelu	gelu	ADJ
ajst-19200	11	8	;	;	PUNCT
ajst-19200	11	9	sppg	sppg	ADJ
ajst-19200	11	10	;	;	PUNCT
ajst-19200	11	11	coordinate	coordinate	VERB
ajst-19200	11	12	attention	attention	NOUN
ajst-19200	11	13	mechanism	mechanism	NOUN
ajst-19200	11	14	;	;	PUNCT
ajst-19200	11	15	xsepconv	xsepconv	PROPN
ajst-19200	11	16	.	.	PROPN
ajst-19200	12	1	1	1	X
ajst-19200	12	2	.	.	X
ajst-19200	12	3	introduction	introduction	NOUN
ajst-19200	12	4	rice	rice	NOUN
ajst-19200	12	5	is	be	AUX
ajst-19200	12	6	the	the	DET
ajst-19200	12	7	food	food	NOUN
ajst-19200	12	8	resource	resource	NOUN
ajst-19200	12	9	that	that	PRON
ajst-19200	12	10	human	human	ADJ
ajst-19200	12	11	beings	being	NOUN
ajst-19200	12	12	depend	depend	VERB
ajst-19200	12	13	on	on	ADP
ajst-19200	12	14	,	,	PUNCT
ajst-19200	12	15	and	and	CCONJ
ajst-19200	12	16	it	it	PRON
ajst-19200	12	17	is	be	AUX
ajst-19200	12	18	the	the	DET
ajst-19200	12	19	most	most	ADV
ajst-19200	12	20	extensive	extensive	ADJ
ajst-19200	12	21	cereal	cereal	NOUN
ajst-19200	12	22	plant	plant	NOUN
ajst-19200	12	23	in	in	ADP
ajst-19200	12	24	the	the	DET
ajst-19200	12	25	world	world	NOUN
ajst-19200	12	26	.	.	PUNCT
ajst-19200	13	1	however	however	ADV
ajst-19200	13	2	,	,	PUNCT
ajst-19200	13	3	in	in	ADP
ajst-19200	13	4	the	the	DET
ajst-19200	13	5	process	process	NOUN
ajst-19200	13	6	of	of	ADP
ajst-19200	13	7	rice	rice	NOUN
ajst-19200	13	8	growth	growth	NOUN
ajst-19200	13	9	,	,	PUNCT
ajst-19200	13	10	rice	rice	NOUN
ajst-19200	13	11	production	production	NOUN
ajst-19200	13	12	is	be	AUX
ajst-19200	13	13	often	often	ADV
ajst-19200	13	14	reduced	reduce	VERB
ajst-19200	13	15	due	due	ADP
ajst-19200	13	16	to	to	ADP
ajst-19200	13	17	the	the	DET
ajst-19200	13	18	influence	influence	NOUN
ajst-19200	13	19	of	of	ADP
ajst-19200	13	20	climate	climate	NOUN
ajst-19200	13	21	,	,	PUNCT
ajst-19200	13	22	temperature	temperature	NOUN
ajst-19200	13	23	,	,	PUNCT
ajst-19200	13	24	diseases	disease	NOUN
ajst-19200	13	25	,	,	PUNCT
ajst-19200	13	26	pests	pest	NOUN
ajst-19200	13	27	and	and	CCONJ
ajst-19200	13	28	viruses	virus	NOUN
ajst-19200	13	29	,	,	PUNCT
ajst-19200	13	30	which	which	PRON
ajst-19200	13	31	may	may	AUX
ajst-19200	13	32	directly	directly	ADV
ajst-19200	13	33	lead	lead	VERB
ajst-19200	13	34	to	to	ADP
ajst-19200	13	35	rice	rice	NOUN
ajst-19200	13	36	death	death	NOUN
ajst-19200	13	37	and	and	CCONJ
ajst-19200	13	38	seriously	seriously	ADV
ajst-19200	13	39	affect	affect	VERB
ajst-19200	13	40	the	the	DET
ajst-19200	13	41	agricultural	agricultural	ADJ
ajst-19200	13	42	economy	economy	NOUN
ajst-19200	13	43	[	[	X
ajst-19200	13	44	1	1	NUM
ajst-19200	13	45	]	]	PUNCT
ajst-19200	13	46	.	.	PUNCT
ajst-19200	14	1	this	this	PRON
ajst-19200	14	2	means	mean	VERB
ajst-19200	14	3	that	that	SCONJ
ajst-19200	14	4	rice	rice	NOUN
ajst-19200	14	5	must	must	AUX
ajst-19200	14	6	be	be	AUX
ajst-19200	14	7	protected	protect	VERB
ajst-19200	14	8	from	from	ADP
ajst-19200	14	9	these	these	DET
ajst-19200	14	10	factors	factor	NOUN
ajst-19200	14	11	,	,	PUNCT
ajst-19200	14	12	and	and	CCONJ
ajst-19200	14	13	at	at	ADP
ajst-19200	14	14	the	the	DET
ajst-19200	14	15	same	same	ADJ
ajst-19200	14	16	time	time	NOUN
ajst-19200	14	17	,	,	PUNCT
ajst-19200	14	18	specific	specific	ADJ
ajst-19200	14	19	disease	disease	NOUN
ajst-19200	14	20	types	type	NOUN
ajst-19200	14	21	can	can	AUX
ajst-19200	14	22	be	be	AUX
ajst-19200	14	23	determined	determine	VERB
ajst-19200	14	24	through	through	ADP
ajst-19200	14	25	disease	disease	NOUN
ajst-19200	14	26	detection	detection	NOUN
ajst-19200	14	27	,	,	PUNCT
ajst-19200	14	28	so	so	SCONJ
ajst-19200	14	29	as	as	SCONJ
ajst-19200	14	30	to	to	PART
ajst-19200	14	31	guide	guide	VERB
ajst-19200	14	32	the	the	DET
ajst-19200	14	33	rational	rational	ADJ
ajst-19200	14	34	selection	selection	NOUN
ajst-19200	14	35	of	of	ADP
ajst-19200	14	36	control	control	NOUN
ajst-19200	14	37	methods	method	NOUN
ajst-19200	14	38	and	and	CCONJ
ajst-19200	14	39	pesticides	pesticide	NOUN
ajst-19200	14	40	,	,	PUNCT
ajst-19200	14	41	which	which	PRON
ajst-19200	14	42	will	will	AUX
ajst-19200	14	43	help	help	VERB
ajst-19200	14	44	to	to	PART
ajst-19200	14	45	avoid	avoid	VERB
ajst-19200	14	46	excessive	excessive	ADJ
ajst-19200	14	47	use	use	NOUN
ajst-19200	14	48	of	of	ADP
ajst-19200	14	49	pesticides	pesticide	NOUN
ajst-19200	14	50	and	and	CCONJ
ajst-19200	14	51	reduce	reduce	VERB
ajst-19200	14	52	.	.	PUNCT
ajst-19200	15	1	in	in	ADP
ajst-19200	15	2	order	order	NOUN
ajst-19200	15	3	to	to	PART
ajst-19200	15	4	detect	detect	VERB
ajst-19200	15	5	the	the	DET
ajst-19200	15	6	diseases	disease	NOUN
ajst-19200	15	7	of	of	ADP
ajst-19200	15	8	rice	rice	NOUN
ajst-19200	15	9	plants	plant	NOUN
ajst-19200	15	10	to	to	ADP
ajst-19200	15	11	the	the	DET
ajst-19200	15	12	maximum	maximum	ADJ
ajst-19200	15	13	extent	extent	NOUN
ajst-19200	15	14	,	,	PUNCT
ajst-19200	15	15	the	the	DET
ajst-19200	15	16	disease	disease	NOUN
ajst-19200	15	17	degree	degree	NOUN
ajst-19200	15	18	of	of	ADP
ajst-19200	15	19	rice	rice	NOUN
ajst-19200	15	20	leaves	leave	NOUN
ajst-19200	15	21	is	be	AUX
ajst-19200	15	22	generally	generally	ADV
ajst-19200	15	23	detected	detect	VERB
ajst-19200	15	24	.	.	PUNCT
ajst-19200	16	1	the	the	DET
ajst-19200	16	2	traditional	traditional	ADJ
ajst-19200	16	3	rice	rice	NOUN
ajst-19200	16	4	disease	disease	NOUN
ajst-19200	16	5	detection	detection	NOUN
ajst-19200	16	6	method	method	NOUN
ajst-19200	16	7	relies	rely	VERB
ajst-19200	16	8	on	on	ADP
ajst-19200	16	9	visual	visual	ADJ
ajst-19200	16	10	detection	detection	NOUN
ajst-19200	16	11	by	by	ADP
ajst-19200	16	12	experts	expert	NOUN
ajst-19200	16	13	or	or	CCONJ
ajst-19200	16	14	experienced	experienced	ADJ
ajst-19200	16	15	farmers	farmer	NOUN
ajst-19200	16	16	,	,	PUNCT
ajst-19200	16	17	but	but	CCONJ
ajst-19200	16	18	this	this	DET
ajst-19200	16	19	method	method	NOUN
ajst-19200	16	20	is	be	AUX
ajst-19200	16	21	not	not	PART
ajst-19200	16	22	suitable	suitable	ADJ
ajst-19200	16	23	for	for	ADP
ajst-19200	16	24	largescale	largescale	NOUN
ajst-19200	16	25	cultivated	cultivate	VERB
ajst-19200	16	26	farmland	farmland	NOUN
ajst-19200	16	27	,	,	PUNCT
ajst-19200	16	28	and	and	CCONJ
ajst-19200	16	29	it	it	PRON
ajst-19200	16	30	takes	take	VERB
ajst-19200	16	31	a	a	DET
ajst-19200	16	32	long	long	ADJ
ajst-19200	16	33	time	time	NOUN
ajst-19200	16	34	and	and	CCONJ
ajst-19200	16	35	can	can	AUX
ajst-19200	16	36	not	not	PART
ajst-19200	16	37	feed	feed	VERB
ajst-19200	16	38	back	back	ADV
ajst-19200	16	39	the	the	DET
ajst-19200	16	40	changes	change	NOUN
ajst-19200	16	41	of	of	ADP
ajst-19200	16	42	rice	rice	NOUN
ajst-19200	16	43	diseases	disease	NOUN
ajst-19200	16	44	in	in	ADP
ajst-19200	16	45	time	time	NOUN
ajst-19200	16	46	.	.	PUNCT
ajst-19200	17	1	with	with	ADP
ajst-19200	17	2	the	the	DET
ajst-19200	17	3	development	development	NOUN
ajst-19200	17	4	of	of	ADP
ajst-19200	17	5	deep	deep	ADJ
ajst-19200	17	6	learning	learning	NOUN
ajst-19200	17	7	technology	technology	NOUN
ajst-19200	17	8	,	,	PUNCT
ajst-19200	17	9	the	the	DET
ajst-19200	17	10	agricultural	agricultural	ADJ
ajst-19200	17	11	field	field	NOUN
ajst-19200	17	12	has	have	AUX
ajst-19200	17	13	become	become	VERB
ajst-19200	17	14	more	more	ADV
ajst-19200	17	15	intelligent	intelligent	ADJ
ajst-19200	17	16	and	and	CCONJ
ajst-19200	17	17	accurate	accurate	ADJ
ajst-19200	17	18	,	,	PUNCT
ajst-19200	17	19	which	which	PRON
ajst-19200	17	20	can	can	AUX
ajst-19200	17	21	detect	detect	VERB
ajst-19200	17	22	the	the	DET
ajst-19200	17	23	growth	growth	NOUN
ajst-19200	17	24	of	of	ADP
ajst-19200	17	25	rice	rice	NOUN
ajst-19200	17	26	in	in	ADP
ajst-19200	17	27	real	real	ADJ
ajst-19200	17	28	time	time	NOUN
ajst-19200	17	29	and	and	CCONJ
ajst-19200	17	30	provide	provide	VERB
ajst-19200	17	31	a	a	DET
ajst-19200	17	32	reasonable	reasonable	ADJ
ajst-19200	17	33	solution	solution	NOUN
ajst-19200	17	34	for	for	ADP
ajst-19200	17	35	the	the	DET
ajst-19200	17	36	agricultural	agricultural	ADJ
ajst-19200	17	37	sector1	sector1	NOUN
ajst-19200	18	1	[	[	X
ajst-19200	18	2	2	2	NUM
ajst-19200	18	3	]	]	PUNCT
ajst-19200	18	4	.	.	PUNCT
ajst-19200	19	1	for	for	ADP
ajst-19200	19	2	example	example	NOUN
ajst-19200	19	3	,	,	PUNCT
ajst-19200	19	4	matin	matin	PROPN
ajst-19200	19	5	used	use	VERB
ajst-19200	19	6	alexnet	alexnet	ADJ
ajst-19200	19	7	neural	neural	ADJ
ajst-19200	19	8	network	network	NOUN
ajst-19200	19	9	to	to	PART
ajst-19200	19	10	detect	detect	VERB
ajst-19200	19	11	three	three	NUM
ajst-19200	19	12	kinds	kind	NOUN
ajst-19200	19	13	of	of	ADP
ajst-19200	19	14	diseases	disease	NOUN
ajst-19200	19	15	,	,	PUNCT
ajst-19200	19	16	but	but	CCONJ
ajst-19200	19	17	in	in	ADP
ajst-19200	19	18	the	the	DET
ajst-19200	19	19	experimental	experimental	ADJ
ajst-19200	19	20	data	datum	NOUN
ajst-19200	19	21	set	set	VERB
ajst-19200	19	22	,	,	PUNCT
ajst-19200	19	23	the	the	DET
ajst-19200	19	24	number	number	NOUN
ajst-19200	19	25	of	of	ADP
ajst-19200	19	26	each	each	DET
ajst-19200	19	27	image	image	NOUN
ajst-19200	19	28	is	be	AUX
ajst-19200	19	29	only	only	ADV
ajst-19200	19	30	40	40	NUM
ajst-19200	20	1	[	[	SYM
ajst-19200	20	2	3	3	NUM
ajst-19200	20	3	]	]	PUNCT
ajst-19200	20	4	.	.	PUNCT
ajst-19200	21	1	zhou	zhou	PROPN
ajst-19200	21	2	et	et	PROPN
ajst-19200	21	3	al	al	PROPN
ajst-19200	21	4	.	.	PROPN
ajst-19200	21	5	combined	combine	VERB
ajst-19200	21	6	fcm	fcm	PROPN
ajst-19200	21	7	-	-	NOUN
ajst-19200	21	8	km	km	NOUN
ajst-19200	21	9	and	and	CCONJ
ajst-19200	21	10	faster	fast	ADJ
ajst-19200	21	11	rcnn	rcnn	NOUN
ajst-19200	21	12	to	to	PART
ajst-19200	21	13	detect	detect	VERB
ajst-19200	21	14	rice	rice	NOUN
ajst-19200	21	15	diseases	disease	NOUN
ajst-19200	21	16	,	,	PUNCT
ajst-19200	21	17	which	which	PRON
ajst-19200	21	18	has	have	VERB
ajst-19200	21	19	high	high	ADJ
ajst-19200	21	20	accuracy	accuracy	NOUN
ajst-19200	21	21	,	,	PUNCT
ajst-19200	21	22	but	but	CCONJ
ajst-19200	21	23	the	the	DET
ajst-19200	21	24	model	model	NOUN
ajst-19200	21	25	is	be	AUX
ajst-19200	21	26	too	too	ADV
ajst-19200	21	27	large	large	ADJ
ajst-19200	21	28	to	to	PART
ajst-19200	21	29	meet	meet	VERB
ajst-19200	21	30	the	the	DET
ajst-19200	21	31	actual	actual	ADJ
ajst-19200	21	32	needs	need	NOUN
ajst-19200	21	33	[	[	X
ajst-19200	21	34	4	4	NUM
ajst-19200	21	35	]	]	PUNCT
ajst-19200	21	36	.	.	PUNCT
ajst-19200	22	1	chen	chen	PROPN
ajst-19200	22	2	et	et	PROPN
ajst-19200	22	3	al	al	PROPN
ajst-19200	22	4	.	.	PROPN
ajst-19200	22	5	used	use	VERB
ajst-19200	22	6	enhanced	enhance	VERB
ajst-19200	22	7	inception	inception	NOUN
ajst-19200	22	8	module	module	NOUN
ajst-19200	22	9	to	to	PART
ajst-19200	22	10	extract	extract	VERB
ajst-19200	22	11	image	image	NOUN
ajst-19200	22	12	features	feature	NOUN
ajst-19200	22	13	for	for	ADP
ajst-19200	22	14	ssd	ssd	NOUN
ajst-19200	22	15	algorithm	algorithm	NOUN
ajst-19200	22	16	,	,	PUNCT
ajst-19200	22	17	and	and	CCONJ
ajst-19200	22	18	used	use	VERB
ajst-19200	22	19	transfer	transfer	NOUN
ajst-19200	22	20	learning	learn	VERB
ajst-19200	22	21	to	to	PART
ajst-19200	22	22	optimize	optimize	VERB
ajst-19200	22	23	the	the	DET
ajst-19200	22	24	model	model	NOUN
ajst-19200	22	25	.	.	PUNCT
ajst-19200	23	1	this	this	DET
ajst-19200	23	2	method	method	NOUN
ajst-19200	23	3	can	can	AUX
ajst-19200	23	4	achieve	achieve	VERB
ajst-19200	23	5	the	the	DET
ajst-19200	23	6	expected	expect	VERB
ajst-19200	23	7	performance	performance	NOUN
ajst-19200	23	8	[	[	X
ajst-19200	23	9	5	5	NUM
ajst-19200	23	10	]	]	PUNCT
ajst-19200	23	11	.	.	PUNCT
ajst-19200	24	1	yumang	yumang	PROPN
ajst-19200	24	2	used	use	VERB
ajst-19200	24	3	tiny	tiny	ADJ
ajst-19200	24	4	yolov3	yolov3	PROPN
ajst-19200	24	5	algorithm	algorithm	PROPN
ajst-19200	24	6	to	to	PART
ajst-19200	24	7	identify	identify	VERB
ajst-19200	24	8	bacterial	bacterial	ADJ
ajst-19200	24	9	leaf	leaf	NOUN
ajst-19200	24	10	blight	blight	NOUN
ajst-19200	24	11	.	.	PUNCT
ajst-19200	25	1	among	among	ADP
ajst-19200	25	2	20	20	NUM
ajst-19200	25	3	test	test	NOUN
ajst-19200	25	4	pictures	picture	NOUN
ajst-19200	25	5	,	,	PUNCT
ajst-19200	25	6	there	there	PRON
ajst-19200	25	7	was	be	VERB
ajst-19200	25	8	only	only	ADV
ajst-19200	25	9	one	one	NUM
ajst-19200	25	10	wrong	wrong	ADJ
ajst-19200	25	11	prediction	prediction	NOUN
ajst-19200	25	12	,	,	PUNCT
ajst-19200	25	13	with	with	ADP
ajst-19200	25	14	high	high	ADJ
ajst-19200	25	15	accuracy	accuracy	NOUN
ajst-19200	25	16	[	[	X
ajst-19200	25	17	6	6	NUM
ajst-19200	25	18	]	]	PUNCT
ajst-19200	25	19	.	.	PUNCT
ajst-19200	26	1	masykur	masykur	PROPN
ajst-19200	26	2	f	f	PROPN
ajst-19200	26	3	uses	use	VERB
ajst-19200	26	4	drones	drone	NOUN
ajst-19200	26	5	to	to	PART
ajst-19200	26	6	collect	collect	VERB
ajst-19200	26	7	images	image	NOUN
ajst-19200	26	8	at	at	ADP
ajst-19200	26	9	different	different	ADJ
ajst-19200	26	10	distances	distance	NOUN
ajst-19200	26	11	,	,	PUNCT
ajst-19200	26	12	and	and	CCONJ
ajst-19200	26	13	uses	use	VERB
ajst-19200	26	14	yolov4	yolov4	PROPN
ajst-19200	26	15	algorithm	algorithm	PROPN
ajst-19200	26	16	to	to	PART
ajst-19200	26	17	carry	carry	VERB
ajst-19200	26	18	out	out	ADP
ajst-19200	26	19	experiments	experiment	NOUN
ajst-19200	26	20	,	,	PUNCT
ajst-19200	26	21	which	which	PRON
ajst-19200	26	22	can	can	AUX
ajst-19200	26	23	detect	detect	VERB
ajst-19200	26	24	the	the	DET
ajst-19200	26	25	existence	existence	NOUN
ajst-19200	26	26	of	of	ADP
ajst-19200	26	27	pests	pest	NOUN
ajst-19200	26	28	on	on	ADP
ajst-19200	26	29	rice	rice	NOUN
ajst-19200	27	1	[	[	X
ajst-19200	27	2	7	7	NUM
ajst-19200	27	3	]	]	PUNCT
ajst-19200	27	4	.	.	PUNCT
ajst-19200	28	1	jhatial	jhatial	ADJ
ajst-19200	28	2	used	use	VERB
ajst-19200	28	3	yolov5	yolov5	NOUN
ajst-19200	28	4	algorithm	algorithm	NOUN
ajst-19200	28	5	to	to	PART
ajst-19200	28	6	detect	detect	VERB
ajst-19200	28	7	four	four	NUM
ajst-19200	28	8	kinds	kind	NOUN
ajst-19200	28	9	of	of	ADP
ajst-19200	28	10	rice	rice	NOUN
ajst-19200	28	11	diseases	disease	NOUN
ajst-19200	28	12	,	,	PUNCT
ajst-19200	28	13	but	but	CCONJ
ajst-19200	28	14	only	only	ADV
ajst-19200	28	15	the	the	DET
ajst-19200	28	16	original	original	ADJ
ajst-19200	28	17	algorithm	algorithm	NOUN
ajst-19200	28	18	was	be	AUX
ajst-19200	28	19	used	use	VERB
ajst-19200	28	20	,	,	PUNCT
ajst-19200	28	21	with	with	ADP
ajst-19200	28	22	fewer	few	ADJ
ajst-19200	28	23	training	training	NOUN
ajst-19200	28	24	rounds	round	NOUN
ajst-19200	28	25	,	,	PUNCT
ajst-19200	28	26	and	and	CCONJ
ajst-19200	28	27	the	the	DET
ajst-19200	28	28	model	model	NOUN
ajst-19200	28	29	did	do	AUX
ajst-19200	28	30	not	not	PART
ajst-19200	28	31	reach	reach	VERB
ajst-19200	28	32	the	the	DET
ajst-19200	28	33	ideal	ideal	ADJ
ajst-19200	28	34	state	state	NOUN
ajst-19200	29	1	[	[	X
ajst-19200	29	2	8	8	NUM
ajst-19200	29	3	]	]	PUNCT
ajst-19200	29	4	.	.	PUNCT
ajst-19200	30	1	the	the	DET
ajst-19200	30	2	above	above	ADV
ajst-19200	30	3	-	-	PUNCT
ajst-19200	30	4	mentioned	mention	VERB
ajst-19200	30	5	researchers	researcher	NOUN
ajst-19200	30	6	put	put	VERB
ajst-19200	30	7	forward	forward	ADV
ajst-19200	30	8	that	that	SCONJ
ajst-19200	30	9	some	some	DET
ajst-19200	30	10	rice	rice	NOUN
ajst-19200	30	11	disease	disease	NOUN
ajst-19200	30	12	detection	detection	NOUN
ajst-19200	30	13	models	model	NOUN
ajst-19200	30	14	have	have	VERB
ajst-19200	30	15	some	some	DET
ajst-19200	30	16	limitations	limitation	NOUN
ajst-19200	30	17	,	,	PUNCT
ajst-19200	30	18	but	but	CCONJ
ajst-19200	30	19	they	they	PRON
ajst-19200	30	20	have	have	AUX
ajst-19200	30	21	proved	prove	VERB
ajst-19200	30	22	the	the	DET
ajst-19200	30	23	potential	potential	NOUN
ajst-19200	30	24	of	of	ADP
ajst-19200	30	25	deep	deep	ADJ
ajst-19200	30	26	learning	learning	NOUN
ajst-19200	30	27	-	-	PUNCT
ajst-19200	30	28	based	base	VERB
ajst-19200	30	29	models	model	NOUN
ajst-19200	30	30	in	in	ADP
ajst-19200	30	31	rice	rice	NOUN
ajst-19200	30	32	disease	disease	NOUN
ajst-19200	30	33	detection	detection	NOUN
ajst-19200	30	34	.	.	PUNCT
ajst-19200	31	1	aiming	aim	VERB
ajst-19200	31	2	at	at	ADP
ajst-19200	31	3	the	the	DET
ajst-19200	31	4	diversity	diversity	NOUN
ajst-19200	31	5	and	and	CCONJ
ajst-19200	31	6	complexity	complexity	NOUN
ajst-19200	31	7	of	of	ADP
ajst-19200	31	8	rice	rice	NOUN
ajst-19200	31	9	leaf	leaf	NOUN
ajst-19200	31	10	diseases	disease	NOUN
ajst-19200	31	11	,	,	PUNCT
ajst-19200	31	12	this	this	DET
ajst-19200	31	13	paper	paper	NOUN
ajst-19200	31	14	realizes	realize	VERB
ajst-19200	31	15	the	the	DET
ajst-19200	31	16	efficient	efficient	ADJ
ajst-19200	31	17	detection	detection	NOUN
ajst-19200	31	18	and	and	CCONJ
ajst-19200	31	19	identification	identification	NOUN
ajst-19200	31	20	of	of	ADP
ajst-19200	31	21	rice	rice	NOUN
ajst-19200	31	22	leaf	leaf	NOUN
ajst-19200	31	23	diseases	disease	NOUN
ajst-19200	31	24	by	by	ADP
ajst-19200	31	25	applying	apply	VERB
ajst-19200	31	26	yolov8	yolov8	NOUN
ajst-19200	31	27	algorithm	algorithm	NOUN
ajst-19200	31	28	,	,	PUNCT
ajst-19200	31	29	mainly	mainly	ADV
ajst-19200	31	30	using	use	VERB
ajst-19200	31	31	the	the	DET
ajst-19200	31	32	spatial	spatial	ADJ
ajst-19200	31	33	pyramid	pyramid	NOUN
ajst-19200	31	34	pooling	pool	VERB
ajst-19200	31	35	(	(	PUNCT
ajst-19200	31	36	sppg	sppg	ADJ
ajst-19200	31	37	)	)	PUNCT
ajst-19200	31	38	structure	structure	NOUN
ajst-19200	31	39	with	with	ADP
ajst-19200	31	40	different	different	ADJ
ajst-19200	31	41	expansion	expansion	NOUN
ajst-19200	31	42	rates	rate	NOUN
ajst-19200	31	43	[	[	X
ajst-19200	31	44	9	9	NUM
ajst-19200	31	45	]	]	PUNCT
ajst-19200	31	46	to	to	PART
ajst-19200	31	47	increase	increase	VERB
ajst-19200	31	48	the	the	DET
ajst-19200	31	49	receptive	receptive	ADJ
ajst-19200	31	50	field	field	NOUN
ajst-19200	31	51	of	of	ADP
ajst-19200	31	52	the	the	DET
ajst-19200	31	53	network	network	NOUN
ajst-19200	31	54	;	;	PUNCT
ajst-19200	31	55	secondly	secondly	ADV
ajst-19200	31	56	,	,	PUNCT
ajst-19200	31	57	the	the	DET
ajst-19200	31	58	ca	ca	NOUN
ajst-19200	31	59	attention	attention	NOUN
ajst-19200	31	60	mechanism	mechanism	NOUN
ajst-19200	31	61	[	[	X
ajst-19200	31	62	10	10	NUM
ajst-19200	31	63	]	]	PUNCT
ajst-19200	31	64	is	be	AUX
ajst-19200	31	65	used	use	VERB
ajst-19200	31	66	to	to	PART
ajst-19200	31	67	help	help	VERB
ajst-19200	31	68	the	the	DET
ajst-19200	31	69	model	model	NOUN
ajst-19200	31	70	better	well	ADV
ajst-19200	31	71	capture	capture	VERB
ajst-19200	31	72	the	the	DET
ajst-19200	31	73	important	important	ADJ
ajst-19200	31	74	information	information	NOUN
ajst-19200	31	75	in	in	ADP
ajst-19200	31	76	the	the	DET
ajst-19200	31	77	image	image	NOUN
ajst-19200	31	78	and	and	CCONJ
ajst-19200	31	79	improve	improve	VERB
ajst-19200	31	80	the	the	DET
ajst-19200	31	81	robustness	robustness	NOUN
ajst-19200	31	82	of	of	ADP
ajst-19200	31	83	the	the	DET
ajst-19200	31	84	model	model	NOUN
ajst-19200	31	85	.	.	PUNCT
ajst-19200	32	1	at	at	ADP
ajst-19200	32	2	the	the	DET
ajst-19200	32	3	same	same	ADJ
ajst-19200	32	4	time	time	NOUN
ajst-19200	32	5	,	,	PUNCT
ajst-19200	32	6	considering	consider	VERB
ajst-19200	32	7	the	the	DET
ajst-19200	32	8	complexity	complexity	NOUN
ajst-19200	32	9	and	and	CCONJ
ajst-19200	32	10	parameters	parameter	NOUN
ajst-19200	32	11	of	of	ADP
ajst-19200	32	12	the	the	DET
ajst-19200	32	13	model	model	NOUN
ajst-19200	32	14	,	,	PUNCT
ajst-19200	32	15	xsepconv	xsepconv	PROPN
ajst-19200	32	16	structure	structure	NOUN
ajst-19200	32	17	[	[	X
ajst-19200	32	18	11	11	NUM
ajst-19200	32	19	]	]	PUNCT
ajst-19200	32	20	is	be	AUX
ajst-19200	32	21	used	use	VERB
ajst-19200	32	22	to	to	PART
ajst-19200	32	23	replace	replace	VERB
ajst-19200	32	24	the	the	DET
ajst-19200	32	25	down	down	ADV
ajst-19200	32	26	-	-	PUNCT
ajst-19200	32	27	sampling	sample	VERB
ajst-19200	32	28	structure	structure	NOUN
ajst-19200	32	29	of	of	ADP
ajst-19200	32	30	the	the	DET
ajst-19200	32	31	network	network	NOUN
ajst-19200	32	32	,	,	PUNCT
ajst-19200	32	33	which	which	PRON
ajst-19200	32	34	reduces	reduce	VERB
ajst-19200	32	35	the	the	DET
ajst-19200	32	36	demand	demand	NOUN
ajst-19200	32	37	for	for	ADP
ajst-19200	32	38	computing	compute	VERB
ajst-19200	32	39	resources	resource	NOUN
ajst-19200	32	40	.	.	PUNCT
ajst-19200	33	1	2	2	X
ajst-19200	33	2	.	.	X
ajst-19200	33	3	the	the	DET
ajst-19200	33	4	principle	principle	NOUN
ajst-19200	33	5	and	and	CCONJ
ajst-19200	33	6	improvement	improvement	NOUN
ajst-19200	33	7	of	of	ADP
ajst-19200	33	8	yolov8n	yolov8n	PROPN
ajst-19200	33	9	model	model	NOUN
ajst-19200	33	10	2.1	2.1	NUM
ajst-19200	33	11	.	.	PUNCT
ajst-19200	34	1	the	the	DET
ajst-19200	34	2	principle	principle	NOUN
ajst-19200	34	3	of	of	ADP
ajst-19200	34	4	yolov8	yolov8	PROPN
ajst-19200	34	5	model	model	PROPN
ajst-19200	34	6	yolov8	yolov8	PROPN
ajst-19200	34	7	is	be	AUX
ajst-19200	34	8	a	a	DET
ajst-19200	34	9	target	target	NOUN
ajst-19200	34	10	detection	detection	NOUN
ajst-19200	34	11	algorithm	algorithm	NOUN
ajst-19200	34	12	based	base	VERB
ajst-19200	34	13	on	on	ADP
ajst-19200	34	14	deep	deep	ADJ
ajst-19200	34	15	learning	learning	NOUN
ajst-19200	34	16	,	,	PUNCT
ajst-19200	34	17	which	which	PRON
ajst-19200	34	18	combines	combine	VERB
ajst-19200	34	19	the	the	DET
ajst-19200	34	20	advantages	advantage	NOUN
ajst-19200	34	21	of	of	ADP
ajst-19200	34	22	high	high	ADJ
ajst-19200	34	23	accuracy	accuracy	NOUN
ajst-19200	34	24	and	and	CCONJ
ajst-19200	34	25	real	real	ADJ
ajst-19200	34	26	-	-	PUNCT
ajst-19200	34	27	time	time	NOUN
ajst-19200	34	28	performance	performance	NOUN
ajst-19200	34	29	.	.	PUNCT
ajst-19200	35	1	it	it	PRON
ajst-19200	35	2	is	be	AUX
ajst-19200	35	3	a	a	DET
ajst-19200	35	4	new	new	ADJ
ajst-19200	35	5	yolo	yolo	ADJ
ajst-19200	35	6	series	series	PROPN
ajst-19200	35	7	algorithm	algorithm	PROPN
ajst-19200	35	8	proposed	propose	VERB
ajst-19200	35	9	by	by	ADP
ajst-19200	35	10	ultralytics	ultralytic	NOUN
ajst-19200	35	11	,	,	PUNCT
ajst-19200	35	12	which	which	PRON
ajst-19200	35	13	mainly	mainly	ADV
ajst-19200	35	14	includes	include	VERB
ajst-19200	35	15	five	five	NUM
ajst-19200	35	16	models	model	NOUN
ajst-19200	35	17	,	,	PUNCT
ajst-19200	35	18	such	such	ADJ
ajst-19200	35	19	as	as	ADP
ajst-19200	35	20	yolov8n	yolov8n	NOUN
ajst-19200	35	21	,	,	PUNCT
ajst-19200	35	22	yolov8s	yolov8s	PROPN
ajst-19200	35	23	,	,	PUNCT
ajst-19200	35	24	yolov8	yolov8	PROPN
ajst-19200	35	25	m	m	PROPN
ajst-19200	35	26	,	,	PUNCT
ajst-19200	35	27	yolov8l	yolov8l	PROPN
ajst-19200	35	28	and	and	CCONJ
ajst-19200	35	29	yolov8x	yolov8x	NOUN
ajst-19200	35	30	.	.	PUNCT
ajst-19200	36	1	it	it	PRON
ajst-19200	36	2	can	can	AUX
ajst-19200	36	3	quickly	quickly	ADV
ajst-19200	36	4	and	and	CCONJ
ajst-19200	36	5	accurately	accurately	ADV
ajst-19200	36	6	realize	realize	VERB
ajst-19200	36	7	tasks	task	NOUN
ajst-19200	36	8	such	such	ADJ
ajst-19200	36	9	as	as	ADP
ajst-19200	36	10	detection	detection	NOUN
ajst-19200	36	11	,	,	PUNCT
ajst-19200	36	12	tracking	tracking	NOUN
ajst-19200	36	13	,	,	PUNCT
ajst-19200	36	14	classification	classification	NOUN
ajst-19200	36	15	,	,	PUNCT
ajst-19200	36	16	case	case	NOUN
ajst-19200	36	17	segmentation	segmentation	NOUN
ajst-19200	36	18	and	and	CCONJ
ajst-19200	36	19	posture	posture	NOUN
ajst-19200	36	20	estimation	estimation	NOUN
ajst-19200	36	21	,	,	PUNCT
ajst-19200	36	22	and	and	CCONJ
ajst-19200	36	23	can	can	AUX
ajst-19200	36	24	effectively	effectively	ADV
ajst-19200	36	25	deal	deal	VERB
ajst-19200	36	26	with	with	ADP
ajst-19200	36	27	rice	rice	NOUN
ajst-19200	36	28	leaf	leaf	NOUN
ajst-19200	36	29	diseases	disease	NOUN
ajst-19200	36	30	.	.	PUNCT
ajst-19200	37	1	yolov8n	yolov8n	NOUN
ajst-19200	37	2	is	be	AUX
ajst-19200	37	3	relatively	relatively	ADV
ajst-19200	37	4	simple	simple	ADJ
ajst-19200	37	5	,	,	PUNCT
ajst-19200	37	6	contains	contain	VERB
ajst-19200	37	7	fewer	few	ADJ
ajst-19200	37	8	network	network	NOUN
ajst-19200	37	9	273	273	NUM
ajst-19200	37	10	layers	layer	NOUN
ajst-19200	37	11	,	,	PUNCT
ajst-19200	37	12	and	and	CCONJ
ajst-19200	37	13	is	be	AUX
ajst-19200	37	14	easier	easy	ADJ
ajst-19200	37	15	to	to	PART
ajst-19200	37	16	train	train	VERB
ajst-19200	37	17	and	and	CCONJ
ajst-19200	37	18	adjust	adjust	VERB
ajst-19200	37	19	.	.	PUNCT
ajst-19200	38	1	in	in	ADP
ajst-19200	38	2	order	order	NOUN
ajst-19200	38	3	to	to	PART
ajst-19200	38	4	maintain	maintain	VERB
ajst-19200	38	5	high	high	ADJ
ajst-19200	38	6	accuracy	accuracy	NOUN
ajst-19200	38	7	and	and	CCONJ
ajst-19200	38	8	faster	fast	ADJ
ajst-19200	38	9	reasoning	reasoning	NOUN
ajst-19200	38	10	speed	speed	NOUN
ajst-19200	38	11	,	,	PUNCT
ajst-19200	38	12	this	this	DET
ajst-19200	38	13	paper	paper	NOUN
ajst-19200	38	14	chooses	choose	VERB
ajst-19200	38	15	yolov8n	yolov8n	PROPN
ajst-19200	38	16	as	as	ADP
ajst-19200	38	17	the	the	DET
ajst-19200	38	18	basic	basic	ADJ
ajst-19200	38	19	model	model	NOUN
ajst-19200	38	20	and	and	CCONJ
ajst-19200	38	21	improves	improve	VERB
ajst-19200	38	22	it	it	PRON
ajst-19200	38	23	.	.	PUNCT
ajst-19200	39	1	yolov8n	yolov8n	NOUN
ajst-19200	39	2	is	be	AUX
ajst-19200	39	3	mainly	mainly	ADV
ajst-19200	39	4	composed	compose	VERB
ajst-19200	39	5	of	of	ADP
ajst-19200	39	6	input	input	NOUN
ajst-19200	39	7	layer	layer	NOUN
ajst-19200	39	8	,	,	PUNCT
ajst-19200	39	9	backbone	backbone	NOUN
ajst-19200	39	10	,	,	PUNCT
ajst-19200	39	11	neck	neck	NOUN
ajst-19200	39	12	and	and	CCONJ
ajst-19200	39	13	output	output	NOUN
ajst-19200	39	14	layer	layer	NOUN
ajst-19200	39	15	,	,	PUNCT
ajst-19200	39	16	as	as	SCONJ
ajst-19200	39	17	shown	show	VERB
ajst-19200	39	18	in	in	ADP
ajst-19200	39	19	figure	figure	NOUN
ajst-19200	39	20	1	1	NUM
ajst-19200	39	21	.	.	PUNCT
ajst-19200	40	1	among	among	ADP
ajst-19200	40	2	them	they	PRON
ajst-19200	40	3	,	,	PUNCT
ajst-19200	40	4	the	the	DET
ajst-19200	40	5	input	input	NOUN
ajst-19200	40	6	layer	layer	NOUN
ajst-19200	40	7	mainly	mainly	ADV
ajst-19200	40	8	preprocesses	preprocesse	VERB
ajst-19200	40	9	the	the	DET
ajst-19200	40	10	image	image	NOUN
ajst-19200	40	11	and	and	CCONJ
ajst-19200	40	12	enhances	enhance	VERB
ajst-19200	40	13	the	the	DET
ajst-19200	40	14	data	datum	NOUN
ajst-19200	40	15	.	.	PUNCT
ajst-19200	41	1	backbone	backbone	NOUN
ajst-19200	41	2	mainly	mainly	ADV
ajst-19200	41	3	extracts	extract	VERB
ajst-19200	41	4	the	the	DET
ajst-19200	41	5	characteristics	characteristic	NOUN
ajst-19200	41	6	of	of	ADP
ajst-19200	41	7	rice	rice	NOUN
ajst-19200	41	8	diseases	disease	NOUN
ajst-19200	41	9	through	through	ADP
ajst-19200	41	10	cbs	cbs	PROPN
ajst-19200	41	11	,	,	PUNCT
ajst-19200	41	12	c2f	c2f	NOUN
ajst-19200	41	13	and	and	CCONJ
ajst-19200	41	14	sppf	sppf	ADJ
ajst-19200	41	15	structure	structure	NOUN
ajst-19200	41	16	[	[	X
ajst-19200	41	17	12	12	NUM
ajst-19200	41	18	]	]	PUNCT
ajst-19200	41	19	.	.	PUNCT
ajst-19200	42	1	cbs	cbs	PROPN
ajst-19200	42	2	structure	structure	NOUN
ajst-19200	42	3	is	be	AUX
ajst-19200	42	4	responsible	responsible	ADJ
ajst-19200	42	5	for	for	ADP
ajst-19200	42	6	the	the	DET
ajst-19200	42	7	down	down	ADV
ajst-19200	42	8	-	-	PUNCT
ajst-19200	42	9	sampling	sample	VERB
ajst-19200	42	10	process	process	NOUN
ajst-19200	42	11	of	of	ADP
ajst-19200	42	12	the	the	DET
ajst-19200	42	13	feature	feature	NOUN
ajst-19200	42	14	map	map	NOUN
ajst-19200	42	15	,	,	PUNCT
ajst-19200	42	16	which	which	PRON
ajst-19200	42	17	is	be	AUX
ajst-19200	42	18	composed	compose	VERB
ajst-19200	42	19	of	of	ADP
ajst-19200	42	20	convolutional	convolutional	ADJ
ajst-19200	42	21	layer	layer	NOUN
ajst-19200	42	22	,	,	PUNCT
ajst-19200	42	23	batch	batch	VERB
ajst-19200	42	24	normalization	normalization	NOUN
ajst-19200	42	25	layer	layer	NOUN
ajst-19200	42	26	and	and	CCONJ
ajst-19200	42	27	silu	silu	ADJ
ajst-19200	42	28	activation	activation	NOUN
ajst-19200	42	29	function	function	NOUN
ajst-19200	42	30	.	.	PUNCT
ajst-19200	43	1	it	it	PRON
ajst-19200	43	2	is	be	AUX
ajst-19200	43	3	repeatedly	repeatedly	ADV
ajst-19200	43	4	stacked	stack	VERB
ajst-19200	43	5	in	in	ADP
ajst-19200	43	6	the	the	DET
ajst-19200	43	7	backbone	backbone	NOUN
ajst-19200	43	8	network	network	NOUN
ajst-19200	43	9	to	to	PART
ajst-19200	43	10	gradually	gradually	ADV
ajst-19200	43	11	extract	extract	VERB
ajst-19200	43	12	the	the	DET
ajst-19200	43	13	advanced	advanced	ADJ
ajst-19200	43	14	features	feature	NOUN
ajst-19200	43	15	of	of	ADP
ajst-19200	43	16	the	the	DET
ajst-19200	43	17	image	image	NOUN
ajst-19200	43	18	.	.	PUNCT
ajst-19200	44	1	c2f	c2f	PROPN
ajst-19200	44	2	first	first	ADV
ajst-19200	44	3	adjusts	adjust	VERB
ajst-19200	44	4	the	the	DET
ajst-19200	44	5	number	number	NOUN
ajst-19200	44	6	of	of	ADP
ajst-19200	44	7	channels	channel	NOUN
ajst-19200	44	8	through	through	ADP
ajst-19200	44	9	cbs	cbs	PROPN
ajst-19200	44	10	structure	structure	NOUN
ajst-19200	44	11	for	for	ADP
ajst-19200	44	12	subsequent	subsequent	ADJ
ajst-19200	44	13	feature	feature	NOUN
ajst-19200	44	14	fusion	fusion	NOUN
ajst-19200	44	15	.	.	PUNCT
ajst-19200	45	1	after	after	ADP
ajst-19200	45	2	processing	process	VERB
ajst-19200	45	3	the	the	DET
ajst-19200	45	4	input	input	NOUN
ajst-19200	45	5	feature	feature	NOUN
ajst-19200	45	6	map	map	NOUN
ajst-19200	45	7	,	,	PUNCT
ajst-19200	45	8	it	it	PRON
ajst-19200	45	9	divides	divide	VERB
ajst-19200	45	10	the	the	DET
ajst-19200	45	11	results	result	NOUN
ajst-19200	45	12	into	into	ADP
ajst-19200	45	13	two	two	NUM
ajst-19200	45	14	blocks	block	NOUN
ajst-19200	45	15	according	accord	VERB
ajst-19200	45	16	to	to	ADP
ajst-19200	45	17	the	the	DET
ajst-19200	45	18	channel	channel	NOUN
ajst-19200	45	19	dimension	dimension	NOUN
ajst-19200	45	20	,	,	PUNCT
ajst-19200	45	21	and	and	CCONJ
ajst-19200	45	22	converts	convert	VERB
ajst-19200	45	23	the	the	DET
ajst-19200	45	24	blocked	block	VERB
ajst-19200	45	25	results	result	NOUN
ajst-19200	45	26	into	into	ADP
ajst-19200	45	27	a	a	DET
ajst-19200	45	28	list	list	NOUN
ajst-19200	45	29	.	.	PUNCT
ajst-19200	46	1	then	then	ADV
ajst-19200	46	2	,	,	PUNCT
ajst-19200	46	3	the	the	DET
ajst-19200	46	4	last	last	ADJ
ajst-19200	46	5	block	block	NOUN
ajst-19200	46	6	tensor	tensor	NOUN
ajst-19200	46	7	in	in	ADP
ajst-19200	46	8	the	the	DET
ajst-19200	46	9	list	list	NOUN
ajst-19200	46	10	is	be	AUX
ajst-19200	46	11	extracted	extract	VERB
ajst-19200	46	12	by	by	ADP
ajst-19200	46	13	the	the	DET
ajst-19200	46	14	bottleneck	bottleneck	NOUN
ajst-19200	46	15	module	module	NOUN
ajst-19200	46	16	,	,	PUNCT
ajst-19200	46	17	which	which	PRON
ajst-19200	46	18	uses	use	VERB
ajst-19200	46	19	residual	residual	ADJ
ajst-19200	46	20	connection	connection	NOUN
ajst-19200	46	21	to	to	PART
ajst-19200	46	22	enhance	enhance	VERB
ajst-19200	46	23	the	the	DET
ajst-19200	46	24	feature	feature	NOUN
ajst-19200	46	25	representation	representation	NOUN
ajst-19200	46	26	ability	ability	NOUN
ajst-19200	46	27	of	of	ADP
ajst-19200	46	28	the	the	DET
ajst-19200	46	29	model	model	NOUN
ajst-19200	46	30	.	.	PUNCT
ajst-19200	47	1	the	the	DET
ajst-19200	47	2	low	low	ADJ
ajst-19200	47	3	-	-	PUNCT
ajst-19200	47	4	level	level	NOUN
ajst-19200	47	5	features	feature	NOUN
ajst-19200	47	6	and	and	CCONJ
ajst-19200	47	7	high	high	ADJ
ajst-19200	47	8	-	-	PUNCT
ajst-19200	47	9	level	level	NOUN
ajst-19200	47	10	features	feature	NOUN
ajst-19200	47	11	can	can	AUX
ajst-19200	47	12	be	be	AUX
ajst-19200	47	13	fused	fuse	VERB
ajst-19200	47	14	by	by	ADP
ajst-19200	47	15	adding	add	VERB
ajst-19200	47	16	the	the	DET
ajst-19200	47	17	input	input	NOUN
ajst-19200	47	18	features	feature	NOUN
ajst-19200	47	19	and	and	CCONJ
ajst-19200	47	20	the	the	DET
ajst-19200	47	21	convolved	convolved	ADJ
ajst-19200	47	22	output	output	NOUN
ajst-19200	47	23	features	feature	NOUN
ajst-19200	47	24	.	.	PUNCT
ajst-19200	48	1	at	at	ADP
ajst-19200	48	2	the	the	DET
ajst-19200	48	3	same	same	ADJ
ajst-19200	48	4	time	time	NOUN
ajst-19200	48	5	,	,	PUNCT
ajst-19200	48	6	feature	feature	NOUN
ajst-19200	48	7	information	information	NOUN
ajst-19200	48	8	can	can	AUX
ajst-19200	48	9	be	be	AUX
ajst-19200	48	10	further	far	ADV
ajst-19200	48	11	extracted	extract	VERB
ajst-19200	48	12	and	and	CCONJ
ajst-19200	48	13	enriched	enrich	VERB
ajst-19200	48	14	through	through	ADP
ajst-19200	48	15	multiple	multiple	ADJ
ajst-19200	48	16	bottleneck	bottleneck	NOUN
ajst-19200	48	17	modules	module	NOUN
ajst-19200	48	18	,	,	PUNCT
ajst-19200	48	19	thus	thus	ADV
ajst-19200	48	20	enhancing	enhance	VERB
ajst-19200	48	21	the	the	DET
ajst-19200	48	22	expressive	expressive	ADJ
ajst-19200	48	23	ability	ability	NOUN
ajst-19200	48	24	of	of	ADP
ajst-19200	48	25	the	the	DET
ajst-19200	48	26	network	network	NOUN
ajst-19200	48	27	.	.	PUNCT
ajst-19200	49	1	the	the	DET
ajst-19200	49	2	sppf	sppf	ADJ
ajst-19200	49	3	module	module	NOUN
ajst-19200	49	4	captures	capture	VERB
ajst-19200	49	5	the	the	DET
ajst-19200	49	6	features	feature	NOUN
ajst-19200	49	7	of	of	ADP
ajst-19200	49	8	different	different	ADJ
ajst-19200	49	9	receptive	receptive	ADJ
ajst-19200	49	10	field	field	NOUN
ajst-19200	49	11	sizes	size	NOUN
ajst-19200	49	12	by	by	ADP
ajst-19200	49	13	sequentially	sequentially	ADV
ajst-19200	49	14	pooling	pool	VERB
ajst-19200	49	15	the	the	DET
ajst-19200	49	16	maximum	maximum	ADJ
ajst-19200	49	17	pool	pool	NOUN
ajst-19200	49	18	with	with	ADP
ajst-19200	49	19	a	a	DET
ajst-19200	49	20	kernel	kernel	NOUN
ajst-19200	49	21	size	size	NOUN
ajst-19200	49	22	of	of	ADP
ajst-19200	49	23	5	5	NUM
ajst-19200	49	24	,	,	PUNCT
ajst-19200	49	25	and	and	CCONJ
ajst-19200	49	26	provides	provide	VERB
ajst-19200	49	27	wider	wide	ADJ
ajst-19200	49	28	context	context	NOUN
ajst-19200	49	29	information	information	NOUN
ajst-19200	49	30	to	to	PART
ajst-19200	49	31	enhance	enhance	VERB
ajst-19200	49	32	the	the	DET
ajst-19200	49	33	accuracy	accuracy	NOUN
ajst-19200	49	34	of	of	ADP
ajst-19200	49	35	detection	detection	NOUN
ajst-19200	49	36	.	.	PUNCT
ajst-19200	50	1	the	the	DET
ajst-19200	50	2	neck	neck	NOUN
ajst-19200	50	3	module	module	NOUN
ajst-19200	50	4	of	of	ADP
ajst-19200	50	5	yolov8n	yolov8n	PROPN
ajst-19200	50	6	is	be	AUX
ajst-19200	50	7	composed	compose	VERB
ajst-19200	50	8	of	of	ADP
ajst-19200	50	9	fpn[13	fpn[13	PROPN
ajst-19200	50	10	]	]	PUNCT
ajst-19200	50	11	and	and	CCONJ
ajst-19200	50	12	panet[14	panet[14	PROPN
ajst-19200	50	13	]	]	PUNCT
ajst-19200	50	14	structures	structure	NOUN
ajst-19200	50	15	,	,	PUNCT
ajst-19200	50	16	which	which	PRON
ajst-19200	50	17	eliminates	eliminate	VERB
ajst-19200	50	18	the	the	DET
ajst-19200	50	19	convolution	convolution	NOUN
ajst-19200	50	20	operation	operation	NOUN
ajst-19200	50	21	before	before	ADP
ajst-19200	50	22	upsampling	upsample	VERB
ajst-19200	50	23	in	in	ADP
ajst-19200	50	24	yolov5	yolov5	NOUN
ajst-19200	50	25	,	,	PUNCT
ajst-19200	50	26	and	and	CCONJ
ajst-19200	50	27	realizes	realize	VERB
ajst-19200	50	28	the	the	DET
ajst-19200	50	29	lightweight	lightweight	NOUN
ajst-19200	50	30	of	of	ADP
ajst-19200	50	31	the	the	DET
ajst-19200	50	32	model	model	NOUN
ajst-19200	50	33	while	while	SCONJ
ajst-19200	50	34	maintaining	maintain	VERB
ajst-19200	50	35	the	the	DET
ajst-19200	50	36	original	original	ADJ
ajst-19200	50	37	performance	performance	NOUN
ajst-19200	50	38	.	.	PUNCT
ajst-19200	51	1	fpn	fpn	PROPN
ajst-19200	51	2	constructs	construct	VERB
ajst-19200	51	3	a	a	DET
ajst-19200	51	4	pyramid	pyramid	NOUN
ajst-19200	51	5	by	by	ADP
ajst-19200	51	6	bottom	bottom	ADJ
ajst-19200	51	7	-	-	PUNCT
ajst-19200	51	8	up	up	NOUN
ajst-19200	51	9	and	and	CCONJ
ajst-19200	51	10	horizontal	horizontal	ADJ
ajst-19200	51	11	connection	connection	NOUN
ajst-19200	51	12	,	,	PUNCT
ajst-19200	51	13	and	and	CCONJ
ajst-19200	51	14	panet	panet	NOUN
ajst-19200	51	15	fuses	fuse	VERB
ajst-19200	51	16	the	the	DET
ajst-19200	51	17	bottom	bottom	ADJ
ajst-19200	51	18	-	-	PUNCT
ajst-19200	51	19	up	up	ADP
ajst-19200	51	20	feature	feature	NOUN
ajst-19200	51	21	map	map	NOUN
ajst-19200	51	22	with	with	ADP
ajst-19200	51	23	the	the	DET
ajst-19200	51	24	top	top	ADJ
ajst-19200	51	25	-	-	PUNCT
ajst-19200	51	26	down	down	ADP
ajst-19200	51	27	feature	feature	NOUN
ajst-19200	51	28	map	map	NOUN
ajst-19200	51	29	layer	layer	NOUN
ajst-19200	51	30	by	by	ADP
ajst-19200	51	31	layer	layer	NOUN
ajst-19200	51	32	to	to	PART
ajst-19200	51	33	obtain	obtain	VERB
ajst-19200	51	34	a	a	DET
ajst-19200	51	35	feature	feature	NOUN
ajst-19200	51	36	pyramid	pyramid	NOUN
ajst-19200	51	37	with	with	ADP
ajst-19200	51	38	rich	rich	ADJ
ajst-19200	51	39	semantic	semantic	ADJ
ajst-19200	51	40	information	information	NOUN
ajst-19200	51	41	and	and	CCONJ
ajst-19200	51	42	high	high	ADJ
ajst-19200	51	43	resolution	resolution	NOUN
ajst-19200	51	44	,	,	PUNCT
ajst-19200	51	45	which	which	PRON
ajst-19200	51	46	can	can	AUX
ajst-19200	51	47	effectively	effectively	ADV
ajst-19200	51	48	extract	extract	VERB
ajst-19200	51	49	and	and	CCONJ
ajst-19200	51	50	utilize	utilize	VERB
ajst-19200	51	51	multi	multi	ADJ
ajst-19200	51	52	-	-	ADJ
ajst-19200	51	53	scale	scale	ADJ
ajst-19200	51	54	features	feature	NOUN
ajst-19200	51	55	.	.	PUNCT
ajst-19200	52	1	the	the	DET
ajst-19200	52	2	output	output	NOUN
ajst-19200	52	3	layer	layer	NOUN
ajst-19200	52	4	of	of	ADP
ajst-19200	52	5	yolov8n	yolov8n	NOUN
ajst-19200	52	6	adopts	adopt	VERB
ajst-19200	52	7	the	the	DET
ajst-19200	52	8	idea	idea	NOUN
ajst-19200	52	9	of	of	ADP
ajst-19200	52	10	"	"	PUNCT
ajst-19200	52	11	double	double	ADJ
ajst-19200	52	12	decoupling	decoupling	NOUN
ajst-19200	52	13	heads	head	NOUN
ajst-19200	52	14	"	"	PUNCT
ajst-19200	52	15	,	,	PUNCT
ajst-19200	52	16	and	and	CCONJ
ajst-19200	52	17	two	two	NUM
ajst-19200	52	18	independent	independent	ADJ
ajst-19200	52	19	sub	sub	NOUN
ajst-19200	52	20	-	-	NOUN
ajst-19200	52	21	networks	network	NOUN
ajst-19200	52	22	are	be	AUX
ajst-19200	52	23	used	use	VERB
ajst-19200	52	24	to	to	PART
ajst-19200	52	25	process	process	VERB
ajst-19200	52	26	the	the	DET
ajst-19200	52	27	target	target	NOUN
ajst-19200	52	28	classification	classification	NOUN
ajst-19200	52	29	and	and	CCONJ
ajst-19200	52	30	bounding	bound	VERB
ajst-19200	52	31	box	box	NOUN
ajst-19200	52	32	regression	regression	NOUN
ajst-19200	52	33	,	,	PUNCT
ajst-19200	52	34	thus	thus	ADV
ajst-19200	52	35	improving	improve	VERB
ajst-19200	52	36	the	the	DET
ajst-19200	52	37	effect	effect	NOUN
ajst-19200	52	38	and	and	CCONJ
ajst-19200	52	39	performance	performance	NOUN
ajst-19200	52	40	of	of	ADP
ajst-19200	52	41	the	the	DET
ajst-19200	52	42	model	model	NOUN
ajst-19200	52	43	.	.	PUNCT
ajst-19200	53	1	figure	figure	NOUN
ajst-19200	53	2	1	1	NUM
ajst-19200	53	3	.	.	PUNCT
ajst-19200	54	1	yolov8n	yolov8n	NOUN
ajst-19200	54	2	model	model	NOUN
ajst-19200	54	3	structure	structure	NOUN
ajst-19200	54	4	diagram	diagram	PROPN
ajst-19200	54	5	2.2	2.2	NUM
ajst-19200	54	6	.	.	PUNCT
ajst-19200	55	1	improvement	improvement	NOUN
ajst-19200	55	2	of	of	ADP
ajst-19200	55	3	yolov8n	yolov8n	NOUN
ajst-19200	55	4	model	model	NOUN
ajst-19200	55	5	the	the	DET
ajst-19200	55	6	improvement	improvement	NOUN
ajst-19200	55	7	of	of	ADP
ajst-19200	55	8	this	this	DET
ajst-19200	55	9	model	model	NOUN
ajst-19200	55	10	mainly	mainly	ADV
ajst-19200	55	11	consists	consist	VERB
ajst-19200	55	12	of	of	ADP
ajst-19200	55	13	three	three	NUM
ajst-19200	55	14	parts	part	NOUN
ajst-19200	55	15	:	:	PUNCT
ajst-19200	55	16	sppg	sppg	ADJ
ajst-19200	55	17	structure	structure	NOUN
ajst-19200	55	18	,	,	PUNCT
ajst-19200	55	19	ca	can	AUX
ajst-19200	55	20	attention	attention	NOUN
ajst-19200	55	21	mechanism	mechanism	NOUN
ajst-19200	55	22	and	and	CCONJ
ajst-19200	55	23	xsepconv	xsepconv	PROPN
ajst-19200	55	24	lightweight	lightweight	PROPN
ajst-19200	55	25	structure	structure	NOUN
ajst-19200	55	26	,	,	PUNCT
ajst-19200	55	27	and	and	CCONJ
ajst-19200	55	28	the	the	DET
ajst-19200	55	29	model	model	NOUN
ajst-19200	55	30	is	be	AUX
ajst-19200	55	31	named	name	VERB
ajst-19200	55	32	scx	scx	NOUN
ajst-19200	55	33	-	-	PUNCT
ajst-19200	55	34	yolov8n	yolov8n	PROPN
ajst-19200	55	35	.	.	PUNCT
ajst-19200	56	1	the	the	DET
ajst-19200	56	2	structure	structure	NOUN
ajst-19200	56	3	is	be	AUX
ajst-19200	56	4	shown	show	VERB
ajst-19200	56	5	in	in	ADP
ajst-19200	56	6	figure	figure	NOUN
ajst-19200	56	7	2	2	NUM
ajst-19200	56	8	.	.	PUNCT
ajst-19200	56	9	figure	figure	NOUN
ajst-19200	56	10	2	2	NUM
ajst-19200	56	11	.	.	PUNCT
ajst-19200	56	12	structural	structural	ADJ
ajst-19200	56	13	diagram	diagram	NOUN
ajst-19200	56	14	of	of	ADP
ajst-19200	56	15	scx	scx	PROPN
ajst-19200	56	16	-	-	PUNCT
ajst-19200	56	17	yolov8n	yolov8n	NOUN
ajst-19200	56	18	model	model	NOUN
ajst-19200	56	19	2.2.1	2.2.1	NUM
ajst-19200	56	20	.	.	PUNCT
ajst-19200	57	1	improve	improve	VERB
ajst-19200	57	2	the	the	DET
ajst-19200	57	3	sppf	sppf	ADJ
ajst-19200	57	4	structure	structure	NOUN
ajst-19200	57	5	the	the	DET
ajst-19200	57	6	size	size	NOUN
ajst-19200	57	7	of	of	ADP
ajst-19200	57	8	the	the	DET
ajst-19200	57	9	receptive	receptive	ADJ
ajst-19200	57	10	field	field	NOUN
ajst-19200	57	11	of	of	ADP
ajst-19200	57	12	the	the	DET
ajst-19200	57	13	feature	feature	NOUN
ajst-19200	57	14	map	map	NOUN
ajst-19200	57	15	is	be	AUX
ajst-19200	57	16	related	relate	VERB
ajst-19200	57	17	to	to	ADP
ajst-19200	57	18	whether	whether	SCONJ
ajst-19200	57	19	the	the	DET
ajst-19200	57	20	network	network	NOUN
ajst-19200	57	21	can	can	AUX
ajst-19200	57	22	find	find	VERB
ajst-19200	57	23	more	more	ADV
ajst-19200	57	24	global	global	ADJ
ajst-19200	57	25	or	or	CCONJ
ajst-19200	57	26	detailed	detailed	ADJ
ajst-19200	57	27	information	information	NOUN
ajst-19200	57	28	in	in	ADP
ajst-19200	57	29	the	the	DET
ajst-19200	57	30	image	image	NOUN
ajst-19200	57	31	.	.	PUNCT
ajst-19200	58	1	considering	consider	VERB
ajst-19200	58	2	that	that	SCONJ
ajst-19200	58	3	there	there	PRON
ajst-19200	58	4	are	be	VERB
ajst-19200	58	5	many	many	ADJ
ajst-19200	58	6	small	small	ADJ
ajst-19200	58	7	targets	target	NOUN
ajst-19200	58	8	in	in	ADP
ajst-19200	58	9	the	the	DET
ajst-19200	58	10	rice	rice	NOUN
ajst-19200	58	11	disease	disease	NOUN
ajst-19200	58	12	image	image	NOUN
ajst-19200	58	13	,	,	PUNCT
ajst-19200	58	14	and	and	CCONJ
ajst-19200	58	15	the	the	DET
ajst-19200	58	16	contextual	contextual	ADJ
ajst-19200	58	17	information	information	NOUN
ajst-19200	58	18	of	of	ADP
ajst-19200	58	19	the	the	DET
ajst-19200	58	20	receptive	receptive	ADJ
ajst-19200	58	21	field	field	NOUN
ajst-19200	58	22	can	can	AUX
ajst-19200	58	23	effectively	effectively	ADV
ajst-19200	58	24	help	help	VERB
ajst-19200	58	25	to	to	PART
ajst-19200	58	26	detect	detect	VERB
ajst-19200	58	27	small	small	ADJ
ajst-19200	58	28	-	-	PUNCT
ajst-19200	58	29	scale	scale	NOUN
ajst-19200	58	30	targets	target	NOUN
ajst-19200	58	31	,	,	PUNCT
ajst-19200	58	32	a	a	DET
ajst-19200	58	33	geconv	geconv	NOUN
ajst-19200	58	34	convolution	convolution	NOUN
ajst-19200	58	35	structure	structure	NOUN
ajst-19200	58	36	with	with	ADP
ajst-19200	58	37	different	different	ADJ
ajst-19200	58	38	dilated	dilated	ADJ
ajst-19200	58	39	convolution	convolution	NOUN
ajst-19200	58	40	is	be	AUX
ajst-19200	58	41	added	add	VERB
ajst-19200	58	42	to	to	ADP
ajst-19200	58	43	the	the	DET
ajst-19200	58	44	sppf	sppf	ADJ
ajst-19200	58	45	structure	structure	NOUN
ajst-19200	58	46	,	,	PUNCT
ajst-19200	58	47	which	which	PRON
ajst-19200	58	48	can	can	AUX
ajst-19200	58	49	expand	expand	VERB
ajst-19200	58	50	the	the	DET
ajst-19200	58	51	receptive	receptive	ADJ
ajst-19200	58	52	field	field	NOUN
ajst-19200	58	53	,	,	PUNCT
ajst-19200	58	54	capture	capture	VERB
ajst-19200	58	55	more	more	ADV
ajst-19200	58	56	characteristic	characteristic	ADJ
ajst-19200	58	57	information	information	NOUN
ajst-19200	58	58	and	and	CCONJ
ajst-19200	58	59	improve	improve	VERB
ajst-19200	58	60	the	the	DET
ajst-19200	58	61	detection	detection	NOUN
ajst-19200	58	62	accuracy	accuracy	NOUN
ajst-19200	58	63	without	without	ADP
ajst-19200	58	64	reducing	reduce	VERB
ajst-19200	58	65	the	the	DET
ajst-19200	58	66	resolution	resolution	NOUN
ajst-19200	58	67	of	of	ADP
ajst-19200	58	68	the	the	DET
ajst-19200	58	69	feature	feature	NOUN
ajst-19200	58	70	map	map	NOUN
ajst-19200	58	71	and	and	CCONJ
ajst-19200	58	72	increasing	increase	VERB
ajst-19200	58	73	the	the	DET
ajst-19200	58	74	calculation	calculation	NOUN
ajst-19200	58	75	amount	amount	NOUN
ajst-19200	58	76	,	,	PUNCT
ajst-19200	58	77	as	as	SCONJ
ajst-19200	58	78	shown	show	VERB
ajst-19200	58	79	in	in	ADP
ajst-19200	58	80	figure	figure	NOUN
ajst-19200	58	81	3	3	NUM
ajst-19200	58	82	.	.	PUNCT
ajst-19200	59	1	firstly	firstly	ADV
ajst-19200	59	2	,	,	PUNCT
ajst-19200	59	3	the	the	DET
ajst-19200	59	4	feature	feature	NOUN
ajst-19200	59	5	maps	map	NOUN
ajst-19200	59	6	generated	generate	VERB
ajst-19200	59	7	by	by	ADP
ajst-19200	59	8	the	the	DET
ajst-19200	59	9	backbone	backbone	NOUN
ajst-19200	59	10	network	network	NOUN
ajst-19200	59	11	are	be	AUX
ajst-19200	59	12	transmitted	transmit	VERB
ajst-19200	59	13	to	to	ADP
ajst-19200	59	14	the	the	DET
ajst-19200	59	15	cbs	cbs	PROPN
ajst-19200	59	16	module	module	NOUN
ajst-19200	59	17	to	to	PART
ajst-19200	59	18	realize	realize	VERB
ajst-19200	59	19	the	the	DET
ajst-19200	59	20	crosschannel	crosschannel	NOUN
ajst-19200	59	21	interaction	interaction	NOUN
ajst-19200	59	22	of	of	ADP
ajst-19200	59	23	information	information	NOUN
ajst-19200	59	24	.	.	PUNCT
ajst-19200	60	1	then	then	ADV
ajst-19200	60	2	,	,	PUNCT
ajst-19200	60	3	the	the	DET
ajst-19200	60	4	maximum	maximum	ADJ
ajst-19200	60	5	pooling	pooling	NOUN
ajst-19200	60	6	with	with	ADP
ajst-19200	60	7	the	the	DET
ajst-19200	60	8	kernel	kernel	NOUN
ajst-19200	60	9	size	size	NOUN
ajst-19200	60	10	of	of	ADP
ajst-19200	60	11	3	3	NUM
ajst-19200	60	12	is	be	AUX
ajst-19200	60	13	carried	carry	VERB
ajst-19200	60	14	out	out	ADP
ajst-19200	60	15	three	three	NUM
ajst-19200	60	16	times	time	NOUN
ajst-19200	60	17	in	in	ADP
ajst-19200	60	18	turn	turn	NOUN
ajst-19200	60	19	.	.	PUNCT
ajst-19200	61	1	the	the	DET
ajst-19200	61	2	generated	generate	VERB
ajst-19200	61	3	three	three	NUM
ajst-19200	61	4	receptive	receptive	ADJ
ajst-19200	61	5	field	field	NOUN
ajst-19200	61	6	feature	feature	NOUN
ajst-19200	61	7	maps	map	NOUN
ajst-19200	61	8	are	be	AUX
ajst-19200	61	9	sent	send	VERB
ajst-19200	61	10	to	to	ADP
ajst-19200	61	11	the	the	DET
ajst-19200	61	12	geconv	geconv	NOUN
ajst-19200	61	13	structure	structure	NOUN
ajst-19200	61	14	with	with	ADP
ajst-19200	61	15	different	different	ADJ
ajst-19200	61	16	hollowing	hollowing	NOUN
ajst-19200	61	17	rates	rate	NOUN
ajst-19200	61	18	,	,	PUNCT
ajst-19200	61	19	and	and	CCONJ
ajst-19200	61	20	the	the	DET
ajst-19200	61	21	cbs	cbs	PROPN
ajst-19200	61	22	module	module	NOUN
ajst-19200	61	23	passes	pass	VERB
ajst-19200	61	24	through	through	ADP
ajst-19200	61	25	the	the	DET
ajst-19200	61	26	geconv	geconv	NOUN
ajst-19200	61	27	structure	structure	NOUN
ajst-19200	61	28	with	with	ADP
ajst-19200	61	29	a	a	DET
ajst-19200	61	30	hollowing	hollow	VERB
ajst-19200	61	31	rate	rate	NOUN
ajst-19200	61	32	of	of	ADP
ajst-19200	61	33	1	1	NUM
ajst-19200	61	34	,	,	PUNCT
ajst-19200	61	35	and	and	CCONJ
ajst-19200	61	36	then	then	ADV
ajst-19200	61	37	the	the	DET
ajst-19200	61	38	features	feature	NOUN
ajst-19200	61	39	of	of	ADP
ajst-19200	61	40	all	all	DET
ajst-19200	61	41	branches	branch	NOUN
ajst-19200	61	42	are	be	AUX
ajst-19200	61	43	connected	connect	VERB
ajst-19200	61	44	.	.	PUNCT
ajst-19200	62	1	finally	finally	ADV
ajst-19200	62	2	,	,	PUNCT
ajst-19200	62	3	the	the	DET
ajst-19200	62	4	feature	feature	NOUN
ajst-19200	62	5	layer	layer	NOUN
ajst-19200	62	6	is	be	AUX
ajst-19200	62	7	output	output	VERB
ajst-19200	62	8	through	through	ADP
ajst-19200	62	9	cbs	cbs	PROPN
ajst-19200	62	10	convolution	convolution	NOUN
ajst-19200	62	11	.	.	PUNCT
ajst-19200	63	1	geconv	geconv	NOUN
ajst-19200	63	2	consists	consist	VERB
ajst-19200	63	3	of	of	ADP
ajst-19200	63	4	ordinary	ordinary	ADJ
ajst-19200	63	5	convolution	convolution	NOUN
ajst-19200	63	6	,	,	PUNCT
ajst-19200	63	7	bn	bn	NOUN
ajst-19200	63	8	layer	layer	NOUN
ajst-19200	63	9	and	and	CCONJ
ajst-19200	63	10	gelu	gelu	ADJ
ajst-19200	63	11	activation	activation	NOUN
ajst-19200	63	12	function	function	NOUN
ajst-19200	63	13	[	[	X
ajst-19200	63	14	15	15	NUM
ajst-19200	63	15	]	]	PUNCT
ajst-19200	63	16	.	.	PUNCT
ajst-19200	64	1	as	as	SCONJ
ajst-19200	64	2	shown	show	VERB
ajst-19200	64	3	in	in	ADP
ajst-19200	64	4	formula	formula	NOUN
ajst-19200	64	5	(	(	PUNCT
ajst-19200	64	6	1	1	NUM
ajst-19200	64	7	)	)	PUNCT
ajst-19200	64	8	,	,	PUNCT
ajst-19200	64	9	the	the	DET
ajst-19200	64	10	gelu	gelu	ADJ
ajst-19200	64	11	activation	activation	NOUN
ajst-19200	64	12	function	function	NOUN
ajst-19200	64	13	is	be	AUX
ajst-19200	64	14	nonlinear	nonlinear	ADJ
ajst-19200	64	15	in	in	ADP
ajst-19200	64	16	the	the	DET
ajst-19200	64	17	whole	whole	ADJ
ajst-19200	64	18	real	real	ADJ
ajst-19200	64	19	number	number	NOUN
ajst-19200	64	20	range	range	NOUN
ajst-19200	64	21	and	and	CCONJ
ajst-19200	64	22	smooth	smooth	ADJ
ajst-19200	64	23	in	in	ADP
ajst-19200	64	24	the	the	DET
ajst-19200	64	25	negative	negative	ADJ
ajst-19200	64	26	number	number	NOUN
ajst-19200	64	27	range	range	NOUN
ajst-19200	64	28	,	,	PUNCT
ajst-19200	64	29	which	which	PRON
ajst-19200	64	30	makes	make	VERB
ajst-19200	64	31	it	it	PRON
ajst-19200	64	32	more	more	ADV
ajst-19200	64	33	suitable	suitable	ADJ
ajst-19200	64	34	for	for	ADP
ajst-19200	64	35	optimization	optimization	NOUN
ajst-19200	64	36	methods	method	NOUN
ajst-19200	64	37	such	such	ADJ
ajst-19200	64	38	as	as	ADP
ajst-19200	64	39	gradient	gradient	ADJ
ajst-19200	64	40	descent	descent	NOUN
ajst-19200	64	41	,	,	PUNCT
ajst-19200	64	42	and	and	CCONJ
ajst-19200	64	43	easier	easy	ADJ
ajst-19200	64	44	to	to	PART
ajst-19200	64	45	deal	deal	VERB
ajst-19200	64	46	with	with	ADP
ajst-19200	64	47	when	when	SCONJ
ajst-19200	64	48	propagating	propagate	VERB
ajst-19200	64	49	backward	backward	ADV
ajst-19200	64	50	,	,	PUNCT
ajst-19200	64	51	which	which	PRON
ajst-19200	64	52	helps	help	VERB
ajst-19200	64	53	to	to	PART
ajst-19200	64	54	reduce	reduce	VERB
ajst-19200	64	55	the	the	DET
ajst-19200	64	56	problem	problem	NOUN
ajst-19200	64	57	of	of	ADP
ajst-19200	64	58	gradient	gradient	ADJ
ajst-19200	64	59	disappearance	disappearance	NOUN
ajst-19200	64	60	,	,	PUNCT
ajst-19200	64	61	improve	improve	VERB
ajst-19200	64	62	the	the	DET
ajst-19200	64	63	representation	representation	NOUN
ajst-19200	64	64	ability	ability	NOUN
ajst-19200	64	65	of	of	ADP
ajst-19200	64	66	the	the	DET
ajst-19200	64	67	model	model	NOUN
ajst-19200	64	68	,	,	PUNCT
ajst-19200	64	69	and	and	CCONJ
ajst-19200	64	70	preserve	preserve	VERB
ajst-19200	64	71	the	the	DET
ajst-19200	64	72	linear	linear	ADJ
ajst-19200	64	73	characteristics	characteristic	NOUN
ajst-19200	64	74	in	in	ADP
ajst-19200	64	75	more	more	ADJ
ajst-19200	64	76	input	input	NOUN
ajst-19200	64	77	ranges	range	NOUN
ajst-19200	64	78	,	,	PUNCT
ajst-19200	64	79	thus	thus	ADV
ajst-19200	64	80	better	well	ADV
ajst-19200	64	81	processing	process	VERB
ajst-19200	64	82	the	the	DET
ajst-19200	64	83	input	input	NOUN
ajst-19200	64	84	feature	feature	NOUN
ajst-19200	64	85	information	information	NOUN
ajst-19200	64	86	.	.	PUNCT
ajst-19200	65	1	1	1	NUM
ajst-19200	65	2	1	1	NUM
ajst-19200	65	3	2	2	NUM
ajst-19200	65	4	2	2	NUM
ajst-19200	65	5	xgelu	xgelu	NOUN
ajst-19200	65	6	x	x	SYM
ajst-19200	65	7	xp	xp	ADJ
ajst-19200	65	8	x	x	SYM
ajst-19200	65	9	x	x	SYM
ajst-19200	65	10	x	x	X
ajst-19200	65	11	er	er	INTJ
ajst-19200	65	12	f	f	X
ajst-19200	65	13	(	(	PUNCT
ajst-19200	65	14	1	1	NUM
ajst-19200	65	15	)	)	PUNCT
ajst-19200	65	16	274	274	NUM
ajst-19200	65	17	figure	figure	NOUN
ajst-19200	65	18	3	3	NUM
ajst-19200	65	19	.	.	PUNCT
ajst-19200	65	20	structure	structure	NOUN
ajst-19200	65	21	diagram	diagram	NOUN
ajst-19200	65	22	of	of	ADP
ajst-19200	65	23	sppg	sppg	ADJ
ajst-19200	65	24	model	model	NOUN
ajst-19200	65	25	2.2.2	2.2.2	NUM
ajst-19200	65	26	.	.	PUNCT
ajst-19200	65	27	ca	can	AUX
ajst-19200	65	28	attention	attention	NOUN
ajst-19200	65	29	mechanism	mechanism	NOUN
ajst-19200	65	30	in	in	ADP
ajst-19200	65	31	order	order	NOUN
ajst-19200	65	32	to	to	PART
ajst-19200	65	33	effectively	effectively	ADV
ajst-19200	65	34	learn	learn	VERB
ajst-19200	65	35	the	the	DET
ajst-19200	65	36	target	target	NOUN
ajst-19200	65	37	characteristics	characteristic	NOUN
ajst-19200	65	38	and	and	CCONJ
ajst-19200	65	39	location	location	NOUN
ajst-19200	65	40	information	information	NOUN
ajst-19200	65	41	of	of	ADP
ajst-19200	65	42	rice	rice	NOUN
ajst-19200	65	43	diseases	disease	NOUN
ajst-19200	65	44	,	,	PUNCT
ajst-19200	65	45	ca	can	AUX
ajst-19200	65	46	attention	attention	NOUN
ajst-19200	65	47	mechanism	mechanism	NOUN
ajst-19200	65	48	was	be	AUX
ajst-19200	65	49	added	add	VERB
ajst-19200	65	50	to	to	ADP
ajst-19200	65	51	the	the	DET
ajst-19200	65	52	backbone	backbone	NOUN
ajst-19200	65	53	feature	feature	NOUN
ajst-19200	65	54	extraction	extraction	NOUN
ajst-19200	65	55	network	network	NOUN
ajst-19200	65	56	to	to	PART
ajst-19200	65	57	automatically	automatically	ADV
ajst-19200	65	58	learn	learn	VERB
ajst-19200	65	59	the	the	DET
ajst-19200	65	60	correlation	correlation	NOUN
ajst-19200	65	61	and	and	CCONJ
ajst-19200	65	62	feature	feature	NOUN
ajst-19200	65	63	representation	representation	NOUN
ajst-19200	65	64	between	between	ADP
ajst-19200	65	65	different	different	ADJ
ajst-19200	65	66	channel	channel	NOUN
ajst-19200	65	67	locations	location	NOUN
ajst-19200	65	68	.	.	PUNCT
ajst-19200	66	1	as	as	SCONJ
ajst-19200	66	2	shown	show	VERB
ajst-19200	66	3	in	in	ADP
ajst-19200	66	4	figure	figure	NOUN
ajst-19200	66	5	4	4	NUM
ajst-19200	66	6	,	,	PUNCT
ajst-19200	66	7	ca	can	AUX
ajst-19200	66	8	attention	attention	NOUN
ajst-19200	66	9	mechanism	mechanism	NOUN
ajst-19200	66	10	can	can	AUX
ajst-19200	66	11	capture	capture	VERB
ajst-19200	66	12	the	the	DET
ajst-19200	66	13	features	feature	NOUN
ajst-19200	66	14	on	on	ADP
ajst-19200	66	15	two	two	NUM
ajst-19200	66	16	channels	channel	NOUN
ajst-19200	66	17	at	at	ADP
ajst-19200	66	18	the	the	DET
ajst-19200	66	19	same	same	ADJ
ajst-19200	66	20	time	time	NOUN
ajst-19200	66	21	,	,	PUNCT
ajst-19200	66	22	which	which	PRON
ajst-19200	66	23	is	be	AUX
ajst-19200	66	24	helpful	helpful	ADJ
ajst-19200	66	25	to	to	PART
ajst-19200	66	26	extract	extract	VERB
ajst-19200	66	27	important	important	ADJ
ajst-19200	66	28	feature	feature	NOUN
ajst-19200	66	29	information	information	NOUN
ajst-19200	66	30	without	without	ADP
ajst-19200	66	31	increasing	increase	VERB
ajst-19200	66	32	network	network	NOUN
ajst-19200	66	33	parameters	parameter	NOUN
ajst-19200	66	34	and	and	CCONJ
ajst-19200	66	35	model	model	NOUN
ajst-19200	66	36	calculation	calculation	NOUN
ajst-19200	66	37	.	.	PUNCT
ajst-19200	67	1	figure	figure	NOUN
ajst-19200	67	2	4	4	NUM
ajst-19200	67	3	.	.	PUNCT
ajst-19200	67	4	structure	structure	NOUN
ajst-19200	67	5	diagram	diagram	NOUN
ajst-19200	67	6	of	of	ADP
ajst-19200	67	7	ca	ca	NOUN
ajst-19200	67	8	attention	attention	NOUN
ajst-19200	67	9	mechanism	mechanism	NOUN
ajst-19200	67	10	first	first	ADV
ajst-19200	67	11	of	of	ADP
ajst-19200	67	12	all	all	PRON
ajst-19200	67	13	,	,	PUNCT
ajst-19200	67	14	in	in	ADP
ajst-19200	67	15	order	order	NOUN
ajst-19200	67	16	to	to	PART
ajst-19200	67	17	reduce	reduce	VERB
ajst-19200	67	18	the	the	DET
ajst-19200	67	19	computational	computational	ADJ
ajst-19200	67	20	complexity	complexity	NOUN
ajst-19200	67	21	,	,	PUNCT
ajst-19200	67	22	ca	can	AUX
ajst-19200	67	23	attention	attention	NOUN
ajst-19200	67	24	mechanism	mechanism	NOUN
ajst-19200	67	25	will	will	AUX
ajst-19200	67	26	pool	pool	VERB
ajst-19200	67	27	each	each	DET
ajst-19200	67	28	channel	channel	NOUN
ajst-19200	67	29	in	in	ADP
ajst-19200	67	30	the	the	DET
ajst-19200	67	31	input	input	NOUN
ajst-19200	67	32	feature	feature	NOUN
ajst-19200	67	33	map	map	NOUN
ajst-19200	67	34	through	through	ADP
ajst-19200	67	35	the	the	DET
ajst-19200	67	36	global	global	ADJ
ajst-19200	67	37	average	average	ADJ
ajst-19200	67	38	operation	operation	NOUN
ajst-19200	67	39	based	base	VERB
ajst-19200	67	40	on	on	ADP
ajst-19200	67	41	width	width	NOUN
ajst-19200	67	42	and	and	CCONJ
ajst-19200	67	43	height	height	NOUN
ajst-19200	67	44	to	to	PART
ajst-19200	67	45	obtain	obtain	VERB
ajst-19200	67	46	an	an	DET
ajst-19200	67	47	information	information	NOUN
ajst-19200	67	48	feature	feature	NOUN
ajst-19200	67	49	map	map	NOUN
ajst-19200	67	50	containing	contain	VERB
ajst-19200	67	51	each	each	DET
ajst-19200	67	52	channel	channel	NOUN
ajst-19200	67	53	,	,	PUNCT
ajst-19200	67	54	as	as	SCONJ
ajst-19200	67	55	shown	show	VERB
ajst-19200	67	56	in	in	ADP
ajst-19200	67	57	formula	formula	NOUN
ajst-19200	67	58	(	(	PUNCT
ajst-19200	67	59	2	2	NUM
ajst-19200	67	60	)	)	PUNCT
ajst-19200	67	61	and	and	CCONJ
ajst-19200	67	62	(	(	PUNCT
ajst-19200	67	63	3	3	NUM
ajst-19200	67	64	)	)	PUNCT
ajst-19200	67	65	;	;	PUNCT
ajst-19200	67	66	then	then	ADV
ajst-19200	67	67	,	,	PUNCT
ajst-19200	67	68	the	the	DET
ajst-19200	67	69	feature	feature	NOUN
ajst-19200	67	70	map	map	NOUN
ajst-19200	67	71	connected	connect	VERB
ajst-19200	67	72	in	in	ADP
ajst-19200	67	73	series	series	NOUN
ajst-19200	67	74	along	along	ADP
ajst-19200	67	75	the	the	DET
ajst-19200	67	76	spatial	spatial	ADJ
ajst-19200	67	77	dimension	dimension	NOUN
ajst-19200	67	78	is	be	AUX
ajst-19200	67	79	transferred	transfer	VERB
ajst-19200	67	80	to	to	ADP
ajst-19200	67	81	the	the	DET
ajst-19200	67	82	convolution	convolution	NOUN
ajst-19200	67	83	layer	layer	NOUN
ajst-19200	67	84	,	,	PUNCT
ajst-19200	67	85	bn	bn	NOUN
ajst-19200	67	86	layer	layer	NOUN
ajst-19200	67	87	and	and	CCONJ
ajst-19200	67	88	activation	activation	NOUN
ajst-19200	67	89	function	function	NOUN
ajst-19200	67	90	layer	layer	NOUN
ajst-19200	67	91	with	with	ADP
ajst-19200	67	92	the	the	DET
ajst-19200	67	93	convolution	convolution	NOUN
ajst-19200	67	94	kernel	kernel	NOUN
ajst-19200	67	95	size	size	NOUN
ajst-19200	67	96	of	of	ADP
ajst-19200	67	97	1×1	1×1	NUM
ajst-19200	67	98	,	,	PUNCT
ajst-19200	67	99	as	as	SCONJ
ajst-19200	67	100	shown	show	VERB
ajst-19200	67	101	in	in	ADP
ajst-19200	67	102	formula	formula	NOUN
ajst-19200	67	103	(	(	PUNCT
ajst-19200	67	104	4	4	NUM
ajst-19200	67	105	)	)	PUNCT
ajst-19200	67	106	;	;	PUNCT
ajst-19200	67	107	then	then	ADV
ajst-19200	67	108	,	,	PUNCT
ajst-19200	67	109	the	the	DET
ajst-19200	67	110	generated	generate	VERB
ajst-19200	67	111	feature	feature	NOUN
ajst-19200	67	112	map	map	NOUN
ajst-19200	67	113	is	be	AUX
ajst-19200	67	114	sliced	slice	VERB
ajst-19200	67	115	along	along	ADP
ajst-19200	67	116	the	the	DET
ajst-19200	67	117	width	width	ADJ
ajst-19200	67	118	-	-	PUNCT
ajst-19200	67	119	height	height	NOUN
ajst-19200	67	120	dimension	dimension	NOUN
ajst-19200	67	121	to	to	PART
ajst-19200	67	122	obtain	obtain	VERB
ajst-19200	67	123	two	two	NUM
ajst-19200	67	124	separate	separate	ADJ
ajst-19200	67	125	feature	feature	NOUN
ajst-19200	67	126	maps	map	NOUN
ajst-19200	67	127	,	,	PUNCT
ajst-19200	67	128	and	and	CCONJ
ajst-19200	67	129	after	after	ADP
ajst-19200	67	130	passing	pass	VERB
ajst-19200	67	131	through	through	ADP
ajst-19200	67	132	the	the	DET
ajst-19200	67	133	convolution	convolution	NOUN
ajst-19200	67	134	layer	layer	NOUN
ajst-19200	67	135	with	with	ADP
ajst-19200	67	136	tanh	tanh	NOUN
ajst-19200	67	137	activation	activation	NOUN
ajst-19200	67	138	function	function	NOUN
ajst-19200	67	139	,	,	PUNCT
ajst-19200	67	140	the	the	DET
ajst-19200	67	141	attention	attention	NOUN
ajst-19200	67	142	weight	weight	NOUN
ajst-19200	67	143	in	in	ADP
ajst-19200	67	144	the	the	DET
ajst-19200	67	145	width	width	ADJ
ajst-19200	67	146	-	-	PUNCT
ajst-19200	67	147	height	height	NOUN
ajst-19200	67	148	direction	direction	NOUN
ajst-19200	67	149	is	be	AUX
ajst-19200	67	150	generated	generate	VERB
ajst-19200	67	151	,	,	PUNCT
ajst-19200	67	152	as	as	SCONJ
ajst-19200	67	153	shown	show	VERB
ajst-19200	67	154	in	in	ADP
ajst-19200	67	155	formula	formula	NOUN
ajst-19200	67	156	(	(	PUNCT
ajst-19200	67	157	5	5	NUM
ajst-19200	67	158	)	)	PUNCT
ajst-19200	67	159	and	and	CCONJ
ajst-19200	67	160	(	(	PUNCT
ajst-19200	67	161	6	6	NUM
ajst-19200	67	162	)	)	PUNCT
ajst-19200	67	163	;	;	PUNCT
ajst-19200	67	164	finally	finally	ADV
ajst-19200	67	165	,	,	PUNCT
ajst-19200	67	166	with	with	ADP
ajst-19200	67	167	the	the	DET
ajst-19200	67	168	input	input	NOUN
ajst-19200	67	169	feature	feature	NOUN
ajst-19200	67	170	map	map	NOUN
ajst-19200	67	171	,	,	PUNCT
ajst-19200	67	172	the	the	DET
ajst-19200	67	173	feature	feature	NOUN
ajst-19200	67	174	value	value	NOUN
ajst-19200	67	175	of	of	ADP
ajst-19200	67	176	each	each	DET
ajst-19200	67	177	channel	channel	NOUN
ajst-19200	67	178	is	be	AUX
ajst-19200	67	179	multiplied	multiply	VERB
ajst-19200	67	180	by	by	ADP
ajst-19200	67	181	the	the	DET
ajst-19200	67	182	corresponding	correspond	VERB
ajst-19200	67	183	attention	attention	NOUN
ajst-19200	67	184	weight	weight	NOUN
ajst-19200	67	185	through	through	ADP
ajst-19200	67	186	element	element	NOUN
ajst-19200	67	187	-	-	PUNCT
ajst-19200	67	188	by	by	ADP
ajst-19200	67	189	-	-	PUNCT
ajst-19200	67	190	element	element	NOUN
ajst-19200	67	191	multiplication	multiplication	NOUN
ajst-19200	67	192	to	to	PART
ajst-19200	67	193	obtain	obtain	VERB
ajst-19200	67	194	the	the	DET
ajst-19200	67	195	output	output	NOUN
ajst-19200	67	196	feature	feature	NOUN
ajst-19200	67	197	map	map	NOUN
ajst-19200	67	198	of	of	ADP
ajst-19200	67	199	ca	ca	NOUN
ajst-19200	67	200	attention	attention	NOUN
ajst-19200	67	201	mechanism	mechanism	NOUN
ajst-19200	67	202	,	,	PUNCT
ajst-19200	67	203	as	as	SCONJ
ajst-19200	67	204	shown	show	VERB
ajst-19200	67	205	in	in	ADP
ajst-19200	67	206	formula	formula	NOUN
ajst-19200	67	207	(	(	PUNCT
ajst-19200	67	208	7	7	NUM
ajst-19200	67	209	)	)	PUNCT
ajst-19200	67	210	.	.	PUNCT
ajst-19200	68	1	compared	compare	VERB
ajst-19200	68	2	with	with	ADP
ajst-19200	68	3	sigmoid	sigmoid	NOUN
ajst-19200	68	4	activation	activation	NOUN
ajst-19200	68	5	function	function	NOUN
ajst-19200	68	6	,	,	PUNCT
ajst-19200	68	7	tanh	tanh	PROPN
ajst-19200	68	8	has	have	VERB
ajst-19200	68	9	better	well	ADJ
ajst-19200	68	10	output	output	NOUN
ajst-19200	68	11	range	range	NOUN
ajst-19200	68	12	,	,	PUNCT
ajst-19200	68	13	larger	large	ADJ
ajst-19200	68	14	gradient	gradient	NOUN
ajst-19200	68	15	(	(	PUNCT
ajst-19200	68	16	near	near	ADP
ajst-19200	68	17	zero	zero	NUM
ajst-19200	68	18	)	)	PUNCT
ajst-19200	68	19	and	and	CCONJ
ajst-19200	68	20	zero	zero	NUM
ajst-19200	68	21	centrality	centrality	NOUN
ajst-19200	68	22	,	,	PUNCT
ajst-19200	68	23	which	which	PRON
ajst-19200	68	24	can	can	AUX
ajst-19200	68	25	alleviate	alleviate	VERB
ajst-19200	68	26	the	the	DET
ajst-19200	68	27	problem	problem	NOUN
ajst-19200	68	28	of	of	ADP
ajst-19200	68	29	gradient	gradient	ADJ
ajst-19200	68	30	disappearance	disappearance	NOUN
ajst-19200	68	31	.	.	PUNCT
ajst-19200	69	1	ca	can	AUX
ajst-19200	69	2	attention	attention	NOUN
ajst-19200	69	3	mechanism	mechanism	NOUN
ajst-19200	69	4	not	not	PART
ajst-19200	69	5	only	only	ADV
ajst-19200	69	6	considers	consider	VERB
ajst-19200	69	7	the	the	DET
ajst-19200	69	8	importance	importance	NOUN
ajst-19200	69	9	of	of	ADP
ajst-19200	69	10	information	information	NOUN
ajst-19200	69	11	between	between	ADP
ajst-19200	69	12	different	different	ADJ
ajst-19200	69	13	channels	channel	NOUN
ajst-19200	69	14	,	,	PUNCT
ajst-19200	69	15	but	but	CCONJ
ajst-19200	69	16	also	also	ADV
ajst-19200	69	17	considers	consider	VERB
ajst-19200	69	18	the	the	DET
ajst-19200	69	19	spatial	spatial	ADJ
ajst-19200	69	20	location	location	NOUN
ajst-19200	69	21	information	information	NOUN
ajst-19200	69	22	.	.	PUNCT
ajst-19200	70	1	it	it	PRON
ajst-19200	70	2	connects	connect	VERB
ajst-19200	70	3	the	the	DET
ajst-19200	70	4	horizontal	horizontal	ADJ
ajst-19200	70	5	and	and	CCONJ
ajst-19200	70	6	vertical	vertical	ADJ
ajst-19200	70	7	features	feature	NOUN
ajst-19200	70	8	to	to	PART
ajst-19200	70	9	form	form	VERB
ajst-19200	70	10	the	the	DET
ajst-19200	70	11	whole	whole	ADJ
ajst-19200	70	12	global	global	ADJ
ajst-19200	70	13	feature	feature	NOUN
ajst-19200	70	14	,	,	PUNCT
ajst-19200	70	15	which	which	PRON
ajst-19200	70	16	can	can	AUX
ajst-19200	70	17	better	well	ADV
ajst-19200	70	18	help	help	VERB
ajst-19200	70	19	the	the	DET
ajst-19200	70	20	model	model	NOUN
ajst-19200	70	21	pay	pay	VERB
ajst-19200	70	22	attention	attention	NOUN
ajst-19200	70	23	to	to	ADP
ajst-19200	70	24	the	the	DET
ajst-19200	70	25	characteristics	characteristic	NOUN
ajst-19200	70	26	of	of	ADP
ajst-19200	70	27	rice	rice	NOUN
ajst-19200	70	28	diseases	disease	NOUN
ajst-19200	70	29	.	.	PUNCT
ajst-19200	71	1	0	0	NUM
ajst-19200	71	2	1	1	NUM
ajst-19200	71	3	,	,	PUNCT
ajst-19200	71	4	h	h	NOUN
ajst-19200	72	1	c	c	NOUN
ajst-19200	72	2	c	c	NOUN
ajst-19200	73	1	i	i	PRON
ajst-19200	73	2	w	w	PROPN
ajst-19200	73	3	z	z	NOUN
ajst-19200	73	4	h	h	NOUN
ajst-19200	74	1	x	x	PUNCT
ajst-19200	74	2	h	h	NOUN
ajst-19200	75	1	i	i	PRON
ajst-19200	75	2	w	w	VERB
ajst-19200	75	3	(	(	PUNCT
ajst-19200	75	4	2	2	NUM
ajst-19200	75	5	)	)	PUNCT
ajst-19200	75	6	0	0	NUM
ajst-19200	75	7	1	1	NUM
ajst-19200	75	8	,	,	PUNCT
ajst-19200	75	9	w	w	NOUN
ajst-19200	75	10	c	c	NOUN
ajst-19200	75	11	c	c	PROPN
ajst-19200	75	12	j	j	PROPN
ajst-19200	75	13	w	w	PROPN
ajst-19200	75	14	z	z	PROPN
ajst-19200	75	15	w	w	PROPN
ajst-19200	75	16	x	x	X
ajst-19200	75	17	j	j	PROPN
ajst-19200	75	18	w	w	PROPN
ajst-19200	75	19	h	h	PROPN
ajst-19200	75	20	(	(	PUNCT
ajst-19200	75	21	3	3	NUM
ajst-19200	75	22	)	)	PUNCT
ajst-19200	75	23	1	1	NUM
ajst-19200	75	24	,	,	PUNCT
ajst-19200	75	25	h	h	NOUN
ajst-19200	76	1	wf	wf	PROPN
ajst-19200	76	2	f	f	PROPN
ajst-19200	76	3	z	z	PROPN
ajst-19200	76	4	z	z	PROPN
ajst-19200	76	5	(	(	PUNCT
ajst-19200	76	6	4	4	NUM
ajst-19200	76	7	)	)	PUNCT
ajst-19200	77	1	h	h	NOUN
ajst-19200	77	2	h	h	NOUN
ajst-19200	77	3	hg	hg	PROPN
ajst-19200	77	4	f	f	PROPN
ajst-19200	77	5	f	f	PROPN
ajst-19200	77	6	(	(	PUNCT
ajst-19200	77	7	5	5	NUM
ajst-19200	77	8	)	)	PUNCT
ajst-19200	77	9	w	w	NOUN
ajst-19200	78	1	w	w	PROPN
ajst-19200	78	2	wg	wg	PROPN
ajst-19200	78	3	f	f	PROPN
ajst-19200	78	4	f	f	X
ajst-19200	78	5	(	(	PUNCT
ajst-19200	78	6	6	6	NUM
ajst-19200	78	7	)	)	PUNCT
ajst-19200	78	8	,	,	PUNCT
ajst-19200	78	9	,	,	PUNCT
ajst-19200	78	10	h	h	NOUN
ajst-19200	79	1	w	w	NOUN
ajst-19200	79	2	c	c	NOUN
ajst-19200	79	3	c	c	NOUN
ajst-19200	80	1	c	c	NOUN
ajst-19200	80	2	cy	cy	INTJ
ajst-19200	80	3	i	i	PRON
ajst-19200	80	4	j	j	NOUN
ajst-19200	80	5	x	x	VERB
ajst-19200	81	1	i	i	PRON
ajst-19200	81	2	j	j	NOUN
ajst-19200	82	1	g	g	NOUN
ajst-19200	82	2	i	i	PRON
ajst-19200	82	3	g	g	PROPN
ajst-19200	82	4	j	j	PROPN
ajst-19200	82	5	(	(	PUNCT
ajst-19200	82	6	7	7	NUM
ajst-19200	82	7	)	)	PUNCT
ajst-19200	82	8	2.2.3	2.2.3	NUM
ajst-19200	82	9	.	.	PUNCT
ajst-19200	83	1	lightweight	lightweight	ADJ
ajst-19200	83	2	design	design	NOUN
ajst-19200	83	3	in	in	ADP
ajst-19200	83	4	order	order	NOUN
ajst-19200	83	5	to	to	PART
ajst-19200	83	6	reduce	reduce	VERB
ajst-19200	83	7	the	the	DET
ajst-19200	83	8	amount	amount	NOUN
ajst-19200	83	9	of	of	ADP
ajst-19200	83	10	calculation	calculation	NOUN
ajst-19200	83	11	caused	cause	VERB
ajst-19200	83	12	by	by	ADP
ajst-19200	83	13	the	the	DET
ajst-19200	83	14	attention	attention	NOUN
ajst-19200	83	15	mechanism	mechanism	NOUN
ajst-19200	83	16	of	of	ADP
ajst-19200	83	17	sppg	sppg	NOUN
ajst-19200	83	18	and	and	CCONJ
ajst-19200	83	19	ca	ca	NOUN
ajst-19200	83	20	,	,	PUNCT
ajst-19200	83	21	and	and	CCONJ
ajst-19200	83	22	at	at	ADP
ajst-19200	83	23	the	the	DET
ajst-19200	83	24	same	same	ADJ
ajst-19200	83	25	time	time	NOUN
ajst-19200	83	26	speed	speed	VERB
ajst-19200	83	27	up	up	ADP
ajst-19200	83	28	the	the	DET
ajst-19200	83	29	reasoning	reasoning	NOUN
ajst-19200	83	30	to	to	PART
ajst-19200	83	31	enhance	enhance	VERB
ajst-19200	83	32	the	the	DET
ajst-19200	83	33	flexibility	flexibility	NOUN
ajst-19200	83	34	of	of	ADP
ajst-19200	83	35	model	model	NOUN
ajst-19200	83	36	deployment	deployment	NOUN
ajst-19200	83	37	,	,	PUNCT
ajst-19200	83	38	xsepconv	xsepconv	PROPN
ajst-19200	83	39	structure	structure	NOUN
ajst-19200	83	40	is	be	AUX
ajst-19200	83	41	used	use	VERB
ajst-19200	83	42	to	to	PART
ajst-19200	83	43	reduce	reduce	VERB
ajst-19200	83	44	the	the	DET
ajst-19200	83	45	number	number	NOUN
ajst-19200	83	46	of	of	ADP
ajst-19200	83	47	parameters	parameter	NOUN
ajst-19200	83	48	and	and	CCONJ
ajst-19200	83	49	improve	improve	VERB
ajst-19200	83	50	the	the	DET
ajst-19200	83	51	efficiency	efficiency	NOUN
ajst-19200	83	52	of	of	ADP
ajst-19200	83	53	the	the	DET
ajst-19200	83	54	model	model	NOUN
ajst-19200	83	55	.	.	PUNCT
ajst-19200	84	1	xsepconv	xsepconv	PROPN
ajst-19200	84	2	structure	structure	PROPN
ajst-19200	84	3	is	be	AUX
ajst-19200	84	4	a	a	DET
ajst-19200	84	5	combination	combination	NOUN
ajst-19200	84	6	of	of	ADP
ajst-19200	84	7	depth	depth	NOUN
ajst-19200	84	8	separable	separable	ADJ
ajst-19200	84	9	convolution	convolution	NOUN
ajst-19200	84	10	[	[	X
ajst-19200	84	11	16	16	NUM
ajst-19200	84	12	]	]	PUNCT
ajst-19200	84	13	and	and	CCONJ
ajst-19200	84	14	se	se	X
ajst-19200	84	15	attention	attention	NOUN
ajst-19200	84	16	mechanism	mechanism	NOUN
ajst-19200	84	17	[	[	X
ajst-19200	84	18	17	17	NUM
ajst-19200	84	19	]	]	PUNCT
ajst-19200	84	20	,	,	PUNCT
ajst-19200	84	21	which	which	PRON
ajst-19200	84	22	extends	extend	VERB
ajst-19200	84	23	and	and	CCONJ
ajst-19200	84	24	improves	improve	VERB
ajst-19200	84	25	the	the	DET
ajst-19200	84	26	traditional	traditional	ADJ
ajst-19200	84	27	convolution	convolution	NOUN
ajst-19200	84	28	structure	structure	NOUN
ajst-19200	84	29	.	.	PUNCT
ajst-19200	85	1	as	as	SCONJ
ajst-19200	85	2	shown	show	VERB
ajst-19200	85	3	in	in	ADP
ajst-19200	85	4	figure	figure	NOUN
ajst-19200	85	5	5	5	NUM
ajst-19200	85	6	,	,	PUNCT
ajst-19200	85	7	it	it	PRON
ajst-19200	85	8	can	can	AUX
ajst-19200	85	9	not	not	PART
ajst-19200	85	10	only	only	ADV
ajst-19200	85	11	capture	capture	VERB
ajst-19200	85	12	the	the	DET
ajst-19200	85	13	detailed	detailed	ADJ
ajst-19200	85	14	features	feature	NOUN
ajst-19200	85	15	of	of	ADP
ajst-19200	85	16	the	the	DET
ajst-19200	85	17	feature	feature	NOUN
ajst-19200	85	18	map	map	NOUN
ajst-19200	85	19	,	,	PUNCT
ajst-19200	85	20	improve	improve	VERB
ajst-19200	85	21	the	the	DET
ajst-19200	85	22	perceptual	perceptual	ADJ
ajst-19200	85	23	ability	ability	NOUN
ajst-19200	85	24	of	of	ADP
ajst-19200	85	25	the	the	DET
ajst-19200	85	26	model	model	NOUN
ajst-19200	85	27	,	,	PUNCT
ajst-19200	85	28	but	but	CCONJ
ajst-19200	85	29	also	also	ADV
ajst-19200	85	30	reduce	reduce	VERB
ajst-19200	85	31	the	the	DET
ajst-19200	85	32	calculation	calculation	NOUN
ajst-19200	85	33	cost	cost	NOUN
ajst-19200	85	34	and	and	CCONJ
ajst-19200	85	35	parameter	parameter	NOUN
ajst-19200	85	36	size	size	NOUN
ajst-19200	85	37	.	.	PUNCT
ajst-19200	86	1	firstly	firstly	ADV
ajst-19200	86	2	,	,	PUNCT
ajst-19200	86	3	the	the	DET
ajst-19200	86	4	depth	depth	NOUN
ajst-19200	86	5	separable	separable	ADJ
ajst-19200	86	6	convolution	convolution	NOUN
ajst-19200	86	7	with	with	ADP
ajst-19200	86	8	the	the	DET
ajst-19200	86	9	convolution	convolution	NOUN
ajst-19200	86	10	kernel	kernel	NOUN
ajst-19200	86	11	size	size	NOUN
ajst-19200	86	12	of	of	ADP
ajst-19200	86	13	2×2	2×2	NUM
ajst-19200	86	14	is	be	AUX
ajst-19200	86	15	used	use	VERB
ajst-19200	86	16	to	to	PART
ajst-19200	86	17	reduce	reduce	VERB
ajst-19200	86	18	the	the	DET
ajst-19200	86	19	computational	computational	ADJ
ajst-19200	86	20	complexity	complexity	NOUN
ajst-19200	86	21	.	.	PUNCT
ajst-19200	87	1	then	then	ADV
ajst-19200	87	2	,	,	PUNCT
ajst-19200	87	3	an	an	DET
ajst-19200	87	4	improved	improved	ADJ
ajst-19200	87	5	symmetric	symmetric	ADJ
ajst-19200	87	6	filling	filling	NOUN
ajst-19200	87	7	strategy	strategy	NOUN
ajst-19200	87	8	is	be	AUX
ajst-19200	87	9	used	use	VERB
ajst-19200	87	10	to	to	PART
ajst-19200	87	11	compensate	compensate	VERB
ajst-19200	87	12	for	for	ADP
ajst-19200	87	13	the	the	DET
ajst-19200	87	14	negative	negative	ADJ
ajst-19200	87	15	effects	effect	NOUN
ajst-19200	87	16	caused	cause	VERB
ajst-19200	87	17	by	by	ADP
ajst-19200	87	18	convolution	convolution	NOUN
ajst-19200	87	19	,	,	PUNCT
ajst-19200	87	20	that	that	ADV
ajst-19200	87	21	is	is	ADV
ajst-19200	87	22	,	,	PUNCT
ajst-19200	87	23	convolution	convolution	NOUN
ajst-19200	87	24	with	with	ADP
ajst-19200	87	25	a	a	DET
ajst-19200	87	26	convolution	convolution	NOUN
ajst-19200	87	27	kernel	kernel	NOUN
ajst-19200	87	28	size	size	NOUN
ajst-19200	87	29	of	of	ADP
ajst-19200	87	30	1x3	1x3	NUM
ajst-19200	87	31	in	in	ADP
ajst-19200	87	32	the	the	DET
ajst-19200	87	33	width	width	NOUN
ajst-19200	87	34	of	of	ADP
ajst-19200	87	35	the	the	DET
ajst-19200	87	36	feature	feature	NOUN
ajst-19200	87	37	map	map	NOUN
ajst-19200	87	38	and	and	CCONJ
ajst-19200	87	39	a	a	DET
ajst-19200	87	40	convolution	convolution	NOUN
ajst-19200	87	41	kernel	kernel	NOUN
ajst-19200	87	42	size	size	NOUN
ajst-19200	87	43	of	of	ADP
ajst-19200	87	44	3x1	3x1	NUM
ajst-19200	87	45	in	in	ADP
ajst-19200	87	46	the	the	DET
ajst-19200	87	47	height	height	NOUN
ajst-19200	87	48	can	can	AUX
ajst-19200	87	49	significantly	significantly	ADV
ajst-19200	87	50	reduce	reduce	VERB
ajst-19200	87	51	the	the	DET
ajst-19200	87	52	demand	demand	NOUN
ajst-19200	87	53	for	for	ADP
ajst-19200	87	54	computing	compute	VERB
ajst-19200	87	55	resources	resource	NOUN
ajst-19200	87	56	and	and	CCONJ
ajst-19200	87	57	improve	improve	VERB
ajst-19200	87	58	the	the	DET
ajst-19200	87	59	operation	operation	NOUN
ajst-19200	87	60	efficiency	efficiency	NOUN
ajst-19200	87	61	,	,	PUNCT
ajst-19200	87	62	and	and	CCONJ
ajst-19200	87	63	on	on	ADP
ajst-19200	87	64	the	the	DET
ajst-19200	87	65	other	other	ADJ
ajst-19200	87	66	hand	hand	NOUN
ajst-19200	87	67	,	,	PUNCT
ajst-19200	87	68	it	it	PRON
ajst-19200	87	69	can	can	AUX
ajst-19200	87	70	better	well	ADV
ajst-19200	87	71	capture	capture	VERB
ajst-19200	87	72	the	the	DET
ajst-19200	87	73	context	context	NOUN
ajst-19200	87	74	information	information	NOUN
ajst-19200	87	75	of	of	ADP
ajst-19200	87	76	the	the	DET
ajst-19200	87	77	input	input	NOUN
ajst-19200	87	78	image	image	NOUN
ajst-19200	87	79	,	,	PUNCT
ajst-19200	87	80	which	which	PRON
ajst-19200	87	81	is	be	AUX
ajst-19200	87	82	conducive	conducive	ADJ
ajst-19200	87	83	to	to	ADP
ajst-19200	87	84	extracting	extract	VERB
ajst-19200	87	85	more	more	ADJ
ajst-19200	87	86	global	global	ADJ
ajst-19200	87	87	features	feature	NOUN
ajst-19200	87	88	.	.	PUNCT
ajst-19200	88	1	figure	figure	VERB
ajst-19200	88	2	5	5	NUM
ajst-19200	88	3	.	.	PUNCT
ajst-19200	89	1	xsepconv	xsepconv	PROPN
ajst-19200	89	2	convolution	convolution	PROPN
ajst-19200	89	3	diagram	diagram	PROPN
ajst-19200	89	4	275	275	NUM
ajst-19200	90	1	the	the	DET
ajst-19200	90	2	xsepconv	xsepconv	PROPN
ajst-19200	90	3	structure	structure	NOUN
ajst-19200	90	4	also	also	ADV
ajst-19200	90	5	introduces	introduce	VERB
ajst-19200	90	6	the	the	DET
ajst-19200	90	7	se	se	PROPN
ajst-19200	90	8	attention	attention	NOUN
ajst-19200	90	9	mechanism	mechanism	NOUN
ajst-19200	90	10	,	,	PUNCT
ajst-19200	90	11	which	which	PRON
ajst-19200	90	12	allows	allow	VERB
ajst-19200	90	13	the	the	DET
ajst-19200	90	14	model	model	NOUN
ajst-19200	90	15	to	to	PART
ajst-19200	90	16	pay	pay	VERB
ajst-19200	90	17	more	more	ADJ
ajst-19200	90	18	attention	attention	NOUN
ajst-19200	90	19	to	to	ADP
ajst-19200	90	20	the	the	DET
ajst-19200	90	21	predetermined	predetermine	VERB
ajst-19200	90	22	target	target	NOUN
ajst-19200	90	23	of	of	ADP
ajst-19200	90	24	the	the	DET
ajst-19200	90	25	image	image	NOUN
ajst-19200	90	26	.	.	PUNCT
ajst-19200	91	1	the	the	DET
ajst-19200	91	2	se	se	PROPN
ajst-19200	91	3	module	module	NOUN
ajst-19200	91	4	is	be	AUX
ajst-19200	91	5	to	to	PART
ajst-19200	91	6	gain	gain	VERB
ajst-19200	91	7	the	the	DET
ajst-19200	91	8	attention	attention	NOUN
ajst-19200	91	9	in	in	ADP
ajst-19200	91	10	the	the	DET
ajst-19200	91	11	channel	channel	NOUN
ajst-19200	91	12	dimension	dimension	NOUN
ajst-19200	91	13	.	.	PUNCT
ajst-19200	92	1	as	as	SCONJ
ajst-19200	92	2	shown	show	VERB
ajst-19200	92	3	in	in	ADP
ajst-19200	92	4	figure	figure	NOUN
ajst-19200	92	5	6	6	NUM
ajst-19200	92	6	,	,	PUNCT
ajst-19200	92	7	firstly	firstly	ADV
ajst-19200	92	8	,	,	PUNCT
ajst-19200	92	9	squeeze	squeeze	VERB
ajst-19200	92	10	the	the	DET
ajst-19200	92	11	feature	feature	NOUN
ajst-19200	92	12	map	map	NOUN
ajst-19200	92	13	obtained	obtain	VERB
ajst-19200	92	14	by	by	ADP
ajst-19200	92	15	convolution	convolution	NOUN
ajst-19200	92	16	to	to	PART
ajst-19200	92	17	take	take	VERB
ajst-19200	92	18	the	the	DET
ajst-19200	92	19	global	global	ADJ
ajst-19200	92	20	spatial	spatial	ADJ
ajst-19200	92	21	characteristics	characteristic	NOUN
ajst-19200	92	22	of	of	ADP
ajst-19200	92	23	each	each	DET
ajst-19200	92	24	channel	channel	NOUN
ajst-19200	92	25	as	as	ADP
ajst-19200	92	26	the	the	DET
ajst-19200	92	27	representation	representation	NOUN
ajst-19200	92	28	of	of	ADP
ajst-19200	92	29	the	the	DET
ajst-19200	92	30	channel	channel	NOUN
ajst-19200	92	31	,	,	PUNCT
ajst-19200	92	32	then	then	ADV
ajst-19200	92	33	carry	carry	VERB
ajst-19200	92	34	out	out	ADP
ajst-19200	92	35	nonlinear	nonlinear	ADJ
ajst-19200	92	36	transformation	transformation	NOUN
ajst-19200	92	37	excitation	excitation	NOUN
ajst-19200	92	38	to	to	PART
ajst-19200	92	39	learn	learn	VERB
ajst-19200	92	40	the	the	DET
ajst-19200	92	41	dependence	dependence	NOUN
ajst-19200	92	42	degree	degree	NOUN
ajst-19200	92	43	of	of	ADP
ajst-19200	92	44	each	each	DET
ajst-19200	92	45	channel	channel	NOUN
ajst-19200	92	46	,	,	PUNCT
ajst-19200	92	47	and	and	CCONJ
ajst-19200	92	48	finally	finally	ADV
ajst-19200	92	49	adjust	adjust	VERB
ajst-19200	92	50	the	the	DET
ajst-19200	92	51	feature	feature	NOUN
ajst-19200	92	52	map	map	NOUN
ajst-19200	92	53	by	by	ADP
ajst-19200	92	54	multiplying	multiply	VERB
ajst-19200	92	55	it	it	PRON
ajst-19200	92	56	with	with	ADP
ajst-19200	92	57	the	the	DET
ajst-19200	92	58	number	number	NOUN
ajst-19200	92	59	of	of	ADP
ajst-19200	92	60	channels	channel	NOUN
ajst-19200	92	61	on	on	ADP
ajst-19200	92	62	the	the	DET
ajst-19200	92	63	previously	previously	ADV
ajst-19200	92	64	unplaced	unplace	VERB
ajst-19200	92	65	feature	feature	NOUN
ajst-19200	92	66	map	map	NOUN
ajst-19200	92	67	,	,	PUNCT
ajst-19200	92	68	as	as	SCONJ
ajst-19200	92	69	shown	show	VERB
ajst-19200	92	70	in	in	ADP
ajst-19200	92	71	the	the	DET
ajst-19200	92	72	figure	figure	NOUN
ajst-19200	92	73	.	.	PUNCT
ajst-19200	93	1	depth	depth	NOUN
ajst-19200	93	2	separable	separable	ADJ
ajst-19200	93	3	convolution	convolution	NOUN
ajst-19200	93	4	can	can	AUX
ajst-19200	93	5	be	be	AUX
ajst-19200	93	6	divided	divide	VERB
ajst-19200	93	7	into	into	ADP
ajst-19200	93	8	depth	depth	NOUN
ajst-19200	93	9	convolution	convolution	NOUN
ajst-19200	93	10	and	and	CCONJ
ajst-19200	93	11	pointby	pointby	NOUN
ajst-19200	93	12	-	-	PUNCT
ajst-19200	93	13	point	point	NOUN
ajst-19200	93	14	convolution	convolution	NOUN
ajst-19200	93	15	.	.	PUNCT
ajst-19200	94	1	an	an	DET
ajst-19200	94	2	effective	effective	ADJ
ajst-19200	94	3	alternative	alternative	NOUN
ajst-19200	94	4	to	to	ADP
ajst-19200	94	5	ordinary	ordinary	ADJ
ajst-19200	94	6	depth	depth	NOUN
ajst-19200	94	7	convolution	convolution	NOUN
ajst-19200	94	8	.	.	PUNCT
ajst-19200	95	1	figure	figure	NOUN
ajst-19200	95	2	6	6	NUM
ajst-19200	95	3	.	.	PUNCT
ajst-19200	95	4	structural	structural	ADJ
ajst-19200	95	5	diagram	diagram	NOUN
ajst-19200	95	6	of	of	ADP
ajst-19200	95	7	se	se	X
ajst-19200	95	8	attention	attention	NOUN
ajst-19200	95	9	mechanism	mechanism	NOUN
ajst-19200	95	10	3	3	NUM
ajst-19200	95	11	.	.	PUNCT
ajst-19200	95	12	model	model	NOUN
ajst-19200	95	13	performance	performance	NOUN
ajst-19200	95	14	analysis	analysis	NOUN
ajst-19200	95	15	3.1	3.1	NUM
ajst-19200	95	16	.	.	PUNCT
ajst-19200	95	17	experimental	experimental	ADJ
ajst-19200	95	18	environment	environment	NOUN
ajst-19200	95	19	and	and	CCONJ
ajst-19200	95	20	parameter	parameter	NOUN
ajst-19200	95	21	setting	set	VERB
ajst-19200	95	22	the	the	DET
ajst-19200	95	23	model	model	NOUN
ajst-19200	95	24	training	training	NOUN
ajst-19200	95	25	is	be	AUX
ajst-19200	95	26	conducted	conduct	VERB
ajst-19200	95	27	on	on	ADP
ajst-19200	95	28	the	the	DET
ajst-19200	95	29	windows	window	NOUN
ajst-19200	95	30	operating	operating	NOUN
ajst-19200	95	31	system	system	NOUN
ajst-19200	95	32	using	use	VERB
ajst-19200	95	33	the	the	DET
ajst-19200	95	34	pytorch	pytorch	NOUN
ajst-19200	95	35	framework	framework	NOUN
ajst-19200	95	36	for	for	ADP
ajst-19200	95	37	training	training	NOUN
ajst-19200	95	38	and	and	CCONJ
ajst-19200	95	39	testing	testing	NOUN
ajst-19200	95	40	,	,	PUNCT
ajst-19200	95	41	and	and	CCONJ
ajst-19200	95	42	the	the	DET
ajst-19200	95	43	environment	environment	NOUN
ajst-19200	95	44	configuration	configuration	NOUN
ajst-19200	95	45	is	be	AUX
ajst-19200	95	46	shown	show	VERB
ajst-19200	95	47	in	in	ADP
ajst-19200	95	48	table	table	NOUN
ajst-19200	95	49	1	1	NUM
ajst-19200	95	50	.	.	PUNCT
ajst-19200	96	1	the	the	DET
ajst-19200	96	2	input	input	NOUN
ajst-19200	96	3	image	image	NOUN
ajst-19200	96	4	size	size	NOUN
ajst-19200	96	5	is	be	AUX
ajst-19200	96	6	set	set	VERB
ajst-19200	96	7	to	to	ADP
ajst-19200	96	8	320	320	NUM
ajst-19200	96	9	pixels×	pixels×	NOUN
ajst-19200	96	10	320	320	NUM
ajst-19200	96	11	pixels	pixel	NOUN
ajst-19200	96	12	,	,	PUNCT
ajst-19200	96	13	the	the	DET
ajst-19200	96	14	batch	batch	NOUN
ajst-19200	96	15	size	size	NOUN
ajst-19200	96	16	is	be	AUX
ajst-19200	96	17	set	set	VERB
ajst-19200	96	18	to	to	ADP
ajst-19200	96	19	16	16	NUM
ajst-19200	96	20	,	,	PUNCT
ajst-19200	96	21	the	the	DET
ajst-19200	96	22	number	number	NOUN
ajst-19200	96	23	of	of	ADP
ajst-19200	96	24	training	training	NOUN
ajst-19200	96	25	steps	step	NOUN
ajst-19200	96	26	is	be	AUX
ajst-19200	96	27	set	set	VERB
ajst-19200	96	28	to	to	ADP
ajst-19200	96	29	200	200	NUM
ajst-19200	96	30	,	,	PUNCT
ajst-19200	96	31	the	the	DET
ajst-19200	96	32	learning	learning	NOUN
ajst-19200	96	33	rate	rate	NOUN
ajst-19200	96	34	is	be	AUX
ajst-19200	96	35	set	set	VERB
ajst-19200	96	36	to	to	ADP
ajst-19200	96	37	0.01	0.01	NUM
ajst-19200	96	38	,	,	PUNCT
ajst-19200	96	39	the	the	DET
ajst-19200	96	40	momentum	momentum	NOUN
ajst-19200	96	41	is	be	AUX
ajst-19200	96	42	set	set	VERB
ajst-19200	96	43	to	to	ADP
ajst-19200	96	44	0.937	0.937	NUM
ajst-19200	96	45	,	,	PUNCT
ajst-19200	96	46	the	the	DET
ajst-19200	96	47	random	random	ADJ
ajst-19200	96	48	gradient	gradient	NOUN
ajst-19200	96	49	descent	descent	NOUN
ajst-19200	96	50	is	be	AUX
ajst-19200	96	51	optimized	optimize	VERB
ajst-19200	96	52	with	with	ADP
ajst-19200	96	53	the	the	DET
ajst-19200	96	54	weight	weight	NOUN
ajst-19200	96	55	attenuation	attenuation	NOUN
ajst-19200	96	56	of	of	ADP
ajst-19200	96	57	0.005	0.005	NUM
ajst-19200	96	58	,	,	PUNCT
ajst-19200	96	59	and	and	CCONJ
ajst-19200	96	60	the	the	DET
ajst-19200	96	61	number	number	NOUN
ajst-19200	96	62	of	of	ADP
ajst-19200	96	63	work	work	NOUN
ajst-19200	96	64	processes	process	NOUN
ajst-19200	96	65	is	be	AUX
ajst-19200	96	66	2	2	NUM
ajst-19200	96	67	.	.	PUNCT
ajst-19200	96	68	table	table	NOUN
ajst-19200	96	69	1	1	NUM
ajst-19200	96	70	.	.	PUNCT
ajst-19200	96	71	experimental	experimental	ADJ
ajst-19200	96	72	configuration	configuration	NOUN
ajst-19200	96	73	operating	operating	NOUN
ajst-19200	96	74	system	system	NOUN
ajst-19200	96	75	microsoft	microsoft	PROPN
ajst-19200	96	76	windows	window	VERB
ajst-19200	96	77	10	10	NUM
ajst-19200	96	78	(	(	PUNCT
ajst-19200	96	79	64	64	NUM
ajst-19200	96	80	)	)	PUNCT
ajst-19200	96	81	cpu	cpu	NOUN
ajst-19200	96	82	12th	12th	NOUN
ajst-19200	97	1	gen	gen	PROPN
ajst-19200	97	2	intel(r	intel(r	PROPN
ajst-19200	97	3	)	)	PUNCT
ajst-19200	97	4	core(tm	core(tm	NOUN
ajst-19200	97	5	)	)	PUNCT
ajst-19200	97	6	i512400(2500	i512400(2500	NOUN
ajst-19200	97	7	mhz	mhz	NOUN
ajst-19200	97	8	)	)	PUNCT
ajst-19200	97	9	internal	internal	ADJ
ajst-19200	97	10	storage	storage	NOUN
ajst-19200	97	11	16.00	16.00	NUM
ajst-19200	97	12	gb	gb	ADP
ajst-19200	97	13	(	(	PUNCT
ajst-19200	97	14	3200	3200	NUM
ajst-19200	97	15	mhz	mhz	NOUN
ajst-19200	97	16	)	)	PUNCT
ajst-19200	97	17	display	display	NOUN
ajst-19200	97	18	card	card	NOUN
ajst-19200	97	19	nvidia	nvidia	PROPN
ajst-19200	97	20	geforce	geforce	NOUN
ajst-19200	97	21	rtx	rtx	PROPN
ajst-19200	97	22	3060	3060	NUM
ajst-19200	97	23	(	(	PUNCT
ajst-19200	97	24	12288	12288	NUM
ajst-19200	97	25	mb	mb	NOUN
ajst-19200	97	26	)	)	PUNCT
ajst-19200	97	27	memory	memory	NOUN
ajst-19200	97	28	12	12	NUM
ajst-19200	97	29	g	g	PROPN
ajst-19200	97	30	3.2	3.2	NUM
ajst-19200	97	31	.	.	PUNCT
ajst-19200	98	1	experimental	experimental	ADJ
ajst-19200	98	2	data	datum	NOUN
ajst-19200	98	3	set	set	VERB
ajst-19200	98	4	the	the	DET
ajst-19200	98	5	detection	detection	NOUN
ajst-19200	98	6	target	target	NOUN
ajst-19200	98	7	of	of	ADP
ajst-19200	98	8	this	this	DET
ajst-19200	98	9	paper	paper	NOUN
ajst-19200	98	10	is	be	AUX
ajst-19200	98	11	rice	rice	NOUN
ajst-19200	98	12	diseases	disease	NOUN
ajst-19200	98	13	.	.	PUNCT
ajst-19200	99	1	in	in	ADP
ajst-19200	99	2	the	the	DET
ajst-19200	99	3	process	process	NOUN
ajst-19200	99	4	of	of	ADP
ajst-19200	99	5	rice	rice	NOUN
ajst-19200	99	6	growth	growth	NOUN
ajst-19200	99	7	,	,	PUNCT
ajst-19200	99	8	it	it	PRON
ajst-19200	99	9	will	will	AUX
ajst-19200	99	10	be	be	AUX
ajst-19200	99	11	caused	cause	VERB
ajst-19200	99	12	by	by	ADP
ajst-19200	99	13	unsuitable	unsuitable	ADJ
ajst-19200	99	14	growth	growth	NOUN
ajst-19200	99	15	environment	environment	NOUN
ajst-19200	99	16	or	or	CCONJ
ajst-19200	99	17	harmful	harmful	ADJ
ajst-19200	99	18	substances	substance	NOUN
ajst-19200	99	19	and	and	CCONJ
ajst-19200	99	20	infectious	infectious	ADJ
ajst-19200	99	21	diseases	disease	NOUN
ajst-19200	99	22	in	in	ADP
ajst-19200	99	23	the	the	DET
ajst-19200	99	24	environment	environment	NOUN
ajst-19200	99	25	.	.	PUNCT
ajst-19200	100	1	according	accord	VERB
ajst-19200	100	2	to	to	ADP
ajst-19200	100	3	this	this	DET
ajst-19200	100	4	study	study	NOUN
ajst-19200	100	5	,	,	PUNCT
ajst-19200	100	6	four	four	NUM
ajst-19200	100	7	diseases	disease	NOUN
ajst-19200	100	8	of	of	ADP
ajst-19200	100	9	rice	rice	NOUN
ajst-19200	100	10	,	,	PUNCT
ajst-19200	100	11	namely	namely	ADV
ajst-19200	100	12	brown	brown	ADJ
ajst-19200	100	13	spot	spot	NOUN
ajst-19200	100	14	,	,	PUNCT
ajst-19200	100	15	rice	rice	NOUN
ajst-19200	100	16	blast	blast	NOUN
ajst-19200	100	17	,	,	PUNCT
ajst-19200	100	18	sheath	sheath	NOUN
ajst-19200	100	19	blight	blight	NOUN
ajst-19200	100	20	and	and	CCONJ
ajst-19200	100	21	bacterial	bacterial	ADJ
ajst-19200	100	22	blight	blight	NOUN
ajst-19200	100	23	,	,	PUNCT
ajst-19200	100	24	were	be	AUX
ajst-19200	100	25	studied	study	VERB
ajst-19200	100	26	,	,	PUNCT
ajst-19200	100	27	among	among	ADP
ajst-19200	100	28	which	which	PRON
ajst-19200	100	29	rice	rice	NOUN
ajst-19200	100	30	sheath	sheath	NOUN
ajst-19200	100	31	blight	blight	NOUN
ajst-19200	100	32	was	be	AUX
ajst-19200	100	33	very	very	ADV
ajst-19200	100	34	similar	similar	ADJ
ajst-19200	100	35	to	to	ADP
ajst-19200	100	36	rice	rice	NOUN
ajst-19200	100	37	blast	blast	NOUN
ajst-19200	100	38	.	.	PUNCT
ajst-19200	101	1	the	the	DET
ajst-19200	101	2	data	datum	NOUN
ajst-19200	101	3	set	set	VERB
ajst-19200	101	4	needed	need	VERB
ajst-19200	101	5	for	for	ADP
ajst-19200	101	6	the	the	DET
ajst-19200	101	7	research	research	NOUN
ajst-19200	101	8	comes	come	VERB
ajst-19200	101	9	from	from	ADP
ajst-19200	101	10	the	the	DET
ajst-19200	101	11	public	public	ADJ
ajst-19200	101	12	data	datum	NOUN
ajst-19200	101	13	set	set	VERB
ajst-19200	101	14	3	3	NUM
ajst-19200	101	15	-	-	PUNCT
ajst-19200	101	16	class	class	NOUN
ajst-19200	101	17	-	-	PUNCT
ajst-19200	101	18	riceleafdisease	riceleafdisease	NOUN
ajst-19200	101	19	,	,	PUNCT
ajst-19200	101	20	rice	rice	NOUN
ajst-19200	101	21	leaf	leaf	NOUN
ajst-19200	101	22	disease	disease	NOUN
ajst-19200	101	23	and	and	CCONJ
ajst-19200	101	24	other	other	ADJ
ajst-19200	101	25	public	public	ADJ
ajst-19200	101	26	images	image	NOUN
ajst-19200	101	27	on	on	ADP
ajst-19200	101	28	the	the	DET
ajst-19200	101	29	network	network	NOUN
ajst-19200	101	30	platform	platform	NOUN
ajst-19200	101	31	.	.	PUNCT
ajst-19200	102	1	a	a	DET
ajst-19200	102	2	large	large	ADJ
ajst-19200	102	3	number	number	NOUN
ajst-19200	102	4	of	of	ADP
ajst-19200	102	5	pictures	picture	NOUN
ajst-19200	102	6	of	of	ADP
ajst-19200	102	7	real	real	ADJ
ajst-19200	102	8	scenes	scene	NOUN
ajst-19200	102	9	are	be	AUX
ajst-19200	102	10	added	add	VERB
ajst-19200	102	11	to	to	PART
ajst-19200	102	12	solve	solve	VERB
ajst-19200	102	13	the	the	DET
ajst-19200	102	14	problem	problem	NOUN
ajst-19200	102	15	of	of	ADP
ajst-19200	102	16	over	over	ADV
ajst-19200	102	17	-	-	PUNCT
ajst-19200	102	18	fitting	fitting	NOUN
ajst-19200	102	19	of	of	ADP
ajst-19200	102	20	high	high	ADJ
ajst-19200	102	21	-	-	PUNCT
ajst-19200	102	22	precision	precision	NOUN
ajst-19200	102	23	images	image	NOUN
ajst-19200	102	24	and	and	CCONJ
ajst-19200	102	25	increase	increase	VERB
ajst-19200	102	26	the	the	DET
ajst-19200	102	27	generalization	generalization	NOUN
ajst-19200	102	28	ability	ability	NOUN
ajst-19200	102	29	of	of	ADP
ajst-19200	102	30	the	the	DET
ajst-19200	102	31	model	model	NOUN
ajst-19200	102	32	.	.	PUNCT
ajst-19200	103	1	firstly	firstly	ADV
ajst-19200	103	2	,	,	PUNCT
ajst-19200	103	3	all	all	DET
ajst-19200	103	4	the	the	DET
ajst-19200	103	5	data	datum	NOUN
ajst-19200	103	6	were	be	AUX
ajst-19200	103	7	manually	manually	ADV
ajst-19200	103	8	eliminated	eliminate	VERB
ajst-19200	103	9	,	,	PUNCT
ajst-19200	103	10	and	and	CCONJ
ajst-19200	103	11	labeled	label	VERB
ajst-19200	103	12	with	with	ADP
ajst-19200	103	13	labelimg	labelimg	ADJ
ajst-19200	103	14	software	software	NOUN
ajst-19200	103	15	according	accord	VERB
ajst-19200	103	16	to	to	ADP
ajst-19200	103	17	the	the	DET
ajst-19200	103	18	rich	rich	ADJ
ajst-19200	103	19	experience	experience	NOUN
ajst-19200	103	20	of	of	ADP
ajst-19200	103	21	rice	rice	NOUN
ajst-19200	103	22	professionals	professional	NOUN
ajst-19200	103	23	and	and	CCONJ
ajst-19200	103	24	growers	grower	NOUN
ajst-19200	103	25	.	.	PUNCT
ajst-19200	104	1	examples	example	NOUN
ajst-19200	104	2	of	of	ADP
ajst-19200	104	3	disease	disease	NOUN
ajst-19200	104	4	types	type	NOUN
ajst-19200	104	5	and	and	CCONJ
ajst-19200	104	6	labels	label	NOUN
ajst-19200	104	7	of	of	ADP
ajst-19200	104	8	rice	rice	NOUN
ajst-19200	104	9	are	be	AUX
ajst-19200	104	10	shown	show	VERB
ajst-19200	104	11	in	in	ADP
ajst-19200	104	12	figure	figure	NOUN
ajst-19200	104	13	7	7	NUM
ajst-19200	104	14	.	.	PUNCT
ajst-19200	104	15	figure	figure	VERB
ajst-19200	104	16	7	7	NUM
ajst-19200	104	17	.	.	NOUN
ajst-19200	104	18	types	type	NOUN
ajst-19200	104	19	of	of	ADP
ajst-19200	104	20	rice	rice	NOUN
ajst-19200	104	21	diseases	disease	NOUN
ajst-19200	104	22	in	in	ADP
ajst-19200	104	23	deep	deep	ADJ
ajst-19200	104	24	learning	learning	NOUN
ajst-19200	104	25	,	,	PUNCT
ajst-19200	104	26	data	datum	NOUN
ajst-19200	104	27	set	set	VERB
ajst-19200	104	28	preprocessing	preprocessing	NOUN
ajst-19200	104	29	and	and	CCONJ
ajst-19200	104	30	data	datum	NOUN
ajst-19200	104	31	enhancement	enhancement	NOUN
ajst-19200	104	32	is	be	AUX
ajst-19200	104	33	a	a	DET
ajst-19200	104	34	key	key	ADJ
ajst-19200	104	35	step	step	NOUN
ajst-19200	104	36	,	,	PUNCT
ajst-19200	104	37	which	which	PRON
ajst-19200	104	38	can	can	AUX
ajst-19200	104	39	help	help	VERB
ajst-19200	104	40	improve	improve	VERB
ajst-19200	104	41	the	the	DET
ajst-19200	104	42	performance	performance	NOUN
ajst-19200	104	43	and	and	CCONJ
ajst-19200	104	44	robustness	robustness	NOUN
ajst-19200	104	45	of	of	ADP
ajst-19200	104	46	the	the	DET
ajst-19200	104	47	model	model	NOUN
ajst-19200	104	48	.	.	PUNCT
ajst-19200	105	1	firstly	firstly	ADV
ajst-19200	105	2	,	,	PUNCT
ajst-19200	105	3	in	in	ADP
ajst-19200	105	4	order	order	NOUN
ajst-19200	105	5	to	to	PART
ajst-19200	105	6	ensure	ensure	VERB
ajst-19200	105	7	the	the	DET
ajst-19200	105	8	quality	quality	NOUN
ajst-19200	105	9	of	of	ADP
ajst-19200	105	10	data	datum	NOUN
ajst-19200	105	11	,	,	PUNCT
ajst-19200	105	12	manual	manual	ADJ
ajst-19200	105	13	cleaning	cleaning	NOUN
ajst-19200	105	14	and	and	CCONJ
ajst-19200	105	15	screening	screening	NOUN
ajst-19200	105	16	are	be	AUX
ajst-19200	105	17	carried	carry	VERB
ajst-19200	105	18	out	out	ADP
ajst-19200	105	19	,	,	PUNCT
ajst-19200	105	20	and	and	CCONJ
ajst-19200	105	21	then	then	ADV
ajst-19200	105	22	the	the	DET
ajst-19200	105	23	data	datum	NOUN
ajst-19200	105	24	set	set	VERB
ajst-19200	105	25	is	be	AUX
ajst-19200	105	26	enhanced	enhance	VERB
ajst-19200	105	27	,	,	PUNCT
ajst-19200	105	28	such	such	ADJ
ajst-19200	105	29	as	as	ADP
ajst-19200	105	30	image	image	NOUN
ajst-19200	105	31	flipping	flipping	NOUN
ajst-19200	105	32	,	,	PUNCT
ajst-19200	105	33	image	image	NOUN
ajst-19200	105	34	mirroring	mirroring	NOUN
ajst-19200	105	35	,	,	PUNCT
ajst-19200	105	36	brightness	brightness	NOUN
ajst-19200	105	37	and	and	CCONJ
ajst-19200	105	38	contrast	contrast	VERB
ajst-19200	105	39	adjustment	adjustment	NOUN
ajst-19200	105	40	.	.	PUNCT
ajst-19200	106	1	in	in	ADP
ajst-19200	106	2	the	the	DET
ajst-19200	106	3	experiment	experiment	NOUN
ajst-19200	106	4	,	,	PUNCT
ajst-19200	106	5	there	there	PRON
ajst-19200	106	6	are	be	VERB
ajst-19200	106	7	3692	3692	NUM
ajst-19200	106	8	enlarged	enlarged	ADJ
ajst-19200	106	9	data	data	NOUN
ajst-19200	106	10	sets	set	NOUN
ajst-19200	106	11	,	,	PUNCT
ajst-19200	106	12	and	and	CCONJ
ajst-19200	106	13	the	the	DET
ajst-19200	106	14	training	training	NOUN
ajst-19200	106	15	set	set	NOUN
ajst-19200	106	16	and	and	CCONJ
ajst-19200	106	17	verification	verification	NOUN
ajst-19200	106	18	set	set	NOUN
ajst-19200	106	19	are	be	AUX
ajst-19200	106	20	divided	divide	VERB
ajst-19200	106	21	according	accord	VERB
ajst-19200	106	22	to	to	ADP
ajst-19200	106	23	the	the	DET
ajst-19200	106	24	ratio	ratio	NOUN
ajst-19200	106	25	of	of	ADP
ajst-19200	106	26	8	8	NUM
ajst-19200	106	27	:	:	SYM
ajst-19200	106	28	2	2	NUM
ajst-19200	106	29	for	for	ADP
ajst-19200	106	30	training	training	NOUN
ajst-19200	106	31	,	,	PUNCT
ajst-19200	106	32	tuning	tuning	NOUN
ajst-19200	106	33	and	and	CCONJ
ajst-19200	106	34	evaluation	evaluation	NOUN
ajst-19200	106	35	of	of	ADP
ajst-19200	106	36	the	the	DET
ajst-19200	106	37	model	model	NOUN
ajst-19200	106	38	.	.	PUNCT
ajst-19200	107	1	3.3	3.3	NUM
ajst-19200	107	2	.	.	PUNCT
ajst-19200	108	1	evaluation	evaluation	NOUN
ajst-19200	108	2	indicators	indicator	NOUN
ajst-19200	108	3	in	in	ADP
ajst-19200	108	4	order	order	NOUN
ajst-19200	108	5	to	to	PART
ajst-19200	108	6	evaluate	evaluate	VERB
ajst-19200	108	7	the	the	DET
ajst-19200	108	8	effectiveness	effectiveness	NOUN
ajst-19200	108	9	of	of	ADP
ajst-19200	108	10	scx	scx	PROPN
ajst-19200	108	11	-	-	PUNCT
ajst-19200	108	12	yolov8n	yolov8n	NOUN
ajst-19200	108	13	network	network	NOUN
ajst-19200	108	14	model	model	NOUN
ajst-19200	108	15	in	in	ADP
ajst-19200	108	16	rice	rice	NOUN
ajst-19200	108	17	pest	pest	NOUN
ajst-19200	108	18	detection	detection	NOUN
ajst-19200	108	19	,	,	PUNCT
ajst-19200	108	20	this	this	DET
ajst-19200	108	21	study	study	NOUN
ajst-19200	108	22	selected	select	VERB
ajst-19200	108	23	precision	precision	NOUN
ajst-19200	108	24	,	,	PUNCT
ajst-19200	108	25	recall	recall	NOUN
ajst-19200	108	26	,	,	PUNCT
ajst-19200	108	27	average	average	ADJ
ajst-19200	108	28	precision	precision	NOUN
ajst-19200	108	29	(	(	PUNCT
ajst-19200	108	30	map	map	NOUN
ajst-19200	108	31	)	)	PUNCT
ajst-19200	108	32	,	,	PUNCT
ajst-19200	108	33	parameters	parameter	NOUN
ajst-19200	108	34	,	,	PUNCT
ajst-19200	108	35	model	model	NOUN
ajst-19200	108	36	size	size	NOUN
ajst-19200	108	37	(	(	PUNCT
ajst-19200	108	38	weight	weight	NOUN
ajst-19200	108	39	)	)	PUNCT
ajst-19200	108	40	and	and	CCONJ
ajst-19200	108	41	fps	fps	VERB
ajst-19200	108	42	as	as	ADP
ajst-19200	108	43	evaluation	evaluation	NOUN
ajst-19200	108	44	indicators	indicator	NOUN
ajst-19200	108	45	,	,	PUNCT
ajst-19200	108	46	and	and	CCONJ
ajst-19200	108	47	used	use	VERB
ajst-19200	108	48	map@0.5	map@0.5	VERB
ajst-19200	108	49	with	with	ADP
ajst-19200	108	50	iou	iou	NOUN
ajst-19200	108	51	threshold	threshold	NOUN
ajst-19200	108	52	of	of	ADP
ajst-19200	108	53	0.5	0.5	NUM
ajst-19200	108	54	as	as	ADP
ajst-19200	108	55	evaluation	evaluation	NOUN
ajst-19200	108	56	indicators	indicator	NOUN
ajst-19200	108	57	.	.	PUNCT
ajst-19200	109	1	the	the	DET
ajst-19200	109	2	formula	formula	NOUN
ajst-19200	109	3	for	for	ADP
ajst-19200	109	4	calculating	calculate	VERB
ajst-19200	109	5	the	the	DET
ajst-19200	109	6	accuracy	accuracy	NOUN
ajst-19200	109	7	rate	rate	NOUN
ajst-19200	109	8	is	be	AUX
ajst-19200	109	9	shown	show	VERB
ajst-19200	109	10	in	in	ADP
ajst-19200	109	11	formula	formula	NOUN
ajst-19200	109	12	(	(	PUNCT
ajst-19200	109	13	8)	8)	NUM
ajst-19200	109	14	,	,	PUNCT
ajst-19200	109	15	the	the	DET
ajst-19200	109	16	formula	formula	NOUN
ajst-19200	109	17	for	for	ADP
ajst-19200	109	18	calculating	calculate	VERB
ajst-19200	109	19	the	the	DET
ajst-19200	109	20	recall	recall	NOUN
ajst-19200	109	21	rate	rate	NOUN
ajst-19200	109	22	is	be	AUX
ajst-19200	109	23	shown	show	VERB
ajst-19200	109	24	in	in	ADP
ajst-19200	109	25	formula	formula	NOUN
ajst-19200	109	26	(	(	PUNCT
ajst-19200	109	27	9	9	NUM
ajst-19200	109	28	)	)	PUNCT
ajst-19200	109	29	and	and	CCONJ
ajst-19200	109	30	the	the	DET
ajst-19200	109	31	formula	formula	NOUN
ajst-19200	109	32	for	for	ADP
ajst-19200	109	33	calculating	calculate	VERB
ajst-19200	109	34	the	the	DET
ajst-19200	109	35	average	average	ADJ
ajst-19200	109	36	accuracy	accuracy	NOUN
ajst-19200	109	37	score	score	NOUN
ajst-19200	109	38	is	be	AUX
ajst-19200	109	39	shown	show	VERB
ajst-19200	109	40	in	in	ADP
ajst-19200	109	41	formula	formula	NOUN
ajst-19200	109	42	(	(	PUNCT
ajst-19200	109	43	10	10	NUM
ajst-19200	109	44	)	)	PUNCT
ajst-19200	109	45	.	.	PUNCT
ajst-19200	110	1	100%tpprecision	100%tpprecision	NUM
ajst-19200	110	2	tp	tp	X
ajst-19200	110	3	fp	fp	X
ajst-19200	110	4	(	(	PUNCT
ajst-19200	110	5	8)	8)	NUM
ajst-19200	110	6	100%tprecall	100%tprecall	NUM
ajst-19200	110	7	tp	tp	ADP
ajst-19200	110	8	fn	fn	PROPN
ajst-19200	110	9	(	(	PUNCT
ajst-19200	110	10	9	9	NUM
ajst-19200	110	11	)	)	SYM
ajst-19200	110	12	1	1	NUM
ajst-19200	110	13	0	0	NUM
ajst-19200	110	14	p	p	NOUN
ajst-19200	110	15	r	r	NOUN
ajst-19200	110	16	drap	drap	NOUN
ajst-19200	110	17	map	map	NOUN
ajst-19200	110	18	n	n	PRON
ajst-19200	110	19	class	class	NOUN
ajst-19200	110	20	n	n	CCONJ
ajst-19200	110	21	class	class	NOUN
ajst-19200	110	22	(	(	PUNCT
ajst-19200	110	23	10	10	NUM
ajst-19200	110	24	)	)	PUNCT
ajst-19200	110	25	among	among	ADP
ajst-19200	110	26	them	they	PRON
ajst-19200	110	27	,	,	PUNCT
ajst-19200	110	28	,	,	PUNCT
ajst-19200	110	29	,	,	PUNCT
ajst-19200	110	30	represents	represent	VERB
ajst-19200	110	31	the	the	DET
ajst-19200	110	32	number	number	NOUN
ajst-19200	110	33	of	of	ADP
ajst-19200	110	34	rice	rice	NOUN
ajst-19200	110	35	diseases	disease	NOUN
ajst-19200	110	36	correctly	correctly	ADV
ajst-19200	110	37	detected	detect	VERB
ajst-19200	110	38	,	,	PUNCT
ajst-19200	110	39	the	the	DET
ajst-19200	110	40	number	number	NOUN
ajst-19200	110	41	of	of	ADP
ajst-19200	110	42	rice	rice	NOUN
ajst-19200	110	43	diseases	disease	NOUN
ajst-19200	110	44	and	and	CCONJ
ajst-19200	110	45	insect	insect	NOUN
ajst-19200	110	46	pests	pest	NOUN
ajst-19200	110	47	incorrectly	incorrectly	ADV
ajst-19200	110	48	detected	detect	VERB
ajst-19200	110	49	and	and	CCONJ
ajst-19200	110	50	the	the	DET
ajst-19200	110	51	number	number	NOUN
ajst-19200	110	52	of	of	ADP
ajst-19200	110	53	rice	rice	NOUN
ajst-19200	110	54	diseases	disease	NOUN
ajst-19200	110	55	and	and	CCONJ
ajst-19200	110	56	insect	insect	NOUN
ajst-19200	110	57	pests	pest	NOUN
ajst-19200	110	58	incorrectly	incorrectly	ADV
ajst-19200	110	59	detected	detect	VERB
ajst-19200	110	60	respectively	respectively	ADV
ajst-19200	110	61	,	,	PUNCT
ajst-19200	110	62	and	and	CCONJ
ajst-19200	110	63	represents	represent	VERB
ajst-19200	110	64	the	the	DET
ajst-19200	110	65	number	number	NOUN
ajst-19200	110	66	of	of	ADP
ajst-19200	110	67	categories	category	NOUN
ajst-19200	110	68	;	;	PUNCT
ajst-19200	110	69	is	be	AUX
ajst-19200	110	70	the	the	DET
ajst-19200	110	71	correct	correct	ADJ
ajst-19200	110	72	proportion	proportion	NOUN
ajst-19200	110	73	of	of	ADP
ajst-19200	110	74	all	all	DET
ajst-19200	110	75	prediction	prediction	NOUN
ajst-19200	110	76	targets	target	NOUN
ajst-19200	110	77	;	;	PUNCT
ajst-19200	110	78	276	276	NUM
ajst-19200	110	79	indicates	indicate	VERB
ajst-19200	110	80	the	the	DET
ajst-19200	110	81	correct	correct	ADJ
ajst-19200	110	82	proportion	proportion	NOUN
ajst-19200	110	83	of	of	ADP
ajst-19200	110	84	all	all	DET
ajst-19200	110	85	real	real	ADJ
ajst-19200	110	86	targets	target	NOUN
ajst-19200	110	87	.	.	PUNCT
ajst-19200	111	1	is	be	AUX
ajst-19200	111	2	the	the	DET
ajst-19200	111	3	area	area	NOUN
ajst-19200	111	4	under	under	ADP
ajst-19200	111	5	the	the	DET
ajst-19200	111	6	pr	pr	NOUN
ajst-19200	111	7	curve	curve	NOUN
ajst-19200	111	8	(	(	PUNCT
ajst-19200	111	9	recall	recall	NOUN
ajst-19200	111	10	is	be	AUX
ajst-19200	111	11	the	the	DET
ajst-19200	111	12	horizontal	horizontal	ADJ
ajst-19200	111	13	axis	axis	NOUN
ajst-19200	111	14	and	and	CCONJ
ajst-19200	111	15	accuracy	accuracy	NOUN
ajst-19200	111	16	is	be	AUX
ajst-19200	111	17	the	the	DET
ajst-19200	111	18	vertical	vertical	ADJ
ajst-19200	111	19	axis	axis	NOUN
ajst-19200	111	20	)	)	PUNCT
ajst-19200	111	21	,	,	PUNCT
ajst-19200	111	22	which	which	PRON
ajst-19200	111	23	is	be	AUX
ajst-19200	111	24	the	the	DET
ajst-19200	111	25	average	average	ADJ
ajst-19200	111	26	accuracy	accuracy	NOUN
ajst-19200	111	27	of	of	ADP
ajst-19200	111	28	a	a	DET
ajst-19200	111	29	single	single	ADJ
ajst-19200	111	30	target	target	NOUN
ajst-19200	111	31	.	.	PUNCT
ajst-19200	112	1	in	in	ADP
ajst-19200	112	2	order	order	NOUN
ajst-19200	112	3	to	to	PART
ajst-19200	112	4	compare	compare	VERB
ajst-19200	112	5	the	the	DET
ajst-19200	112	6	performance	performance	NOUN
ajst-19200	112	7	of	of	ADP
ajst-19200	112	8	all	all	DET
ajst-19200	112	9	target	target	NOUN
ajst-19200	112	10	categories	category	NOUN
ajst-19200	112	11	,	,	PUNCT
ajst-19200	112	12	the	the	DET
ajst-19200	112	13	average	average	ADJ
ajst-19200	112	14	ap	ap	PROPN
ajst-19200	112	15	(	(	PUNCT
ajst-19200	112	16	)	)	PUNCT
ajst-19200	112	17	is	be	AUX
ajst-19200	112	18	used	use	VERB
ajst-19200	112	19	as	as	ADP
ajst-19200	112	20	the	the	DET
ajst-19200	112	21	evaluation	evaluation	NOUN
ajst-19200	112	22	index	index	NOUN
ajst-19200	112	23	of	of	ADP
ajst-19200	112	24	accuracy	accuracy	NOUN
ajst-19200	112	25	.	.	PUNCT
ajst-19200	113	1	fps	fps	PROPN
ajst-19200	113	2	is	be	AUX
ajst-19200	113	3	the	the	DET
ajst-19200	113	4	speed	speed	NOUN
ajst-19200	113	5	at	at	ADP
ajst-19200	113	6	which	which	PRON
ajst-19200	113	7	the	the	DET
ajst-19200	113	8	evaluation	evaluation	NOUN
ajst-19200	113	9	model	model	NOUN
ajst-19200	113	10	detects	detect	VERB
ajst-19200	113	11	rice	rice	NOUN
ajst-19200	113	12	diseases	disease	NOUN
ajst-19200	113	13	,	,	PUNCT
ajst-19200	113	14	that	that	ADV
ajst-19200	113	15	is	is	ADV
ajst-19200	113	16	,	,	PUNCT
ajst-19200	113	17	the	the	DET
ajst-19200	113	18	number	number	NOUN
ajst-19200	113	19	of	of	ADP
ajst-19200	113	20	pictures	picture	NOUN
ajst-19200	113	21	that	that	PRON
ajst-19200	113	22	can	can	AUX
ajst-19200	113	23	be	be	AUX
ajst-19200	113	24	processed	process	VERB
ajst-19200	113	25	per	per	ADP
ajst-19200	113	26	second	second	NOUN
ajst-19200	113	27	.	.	PUNCT
ajst-19200	114	1	3.4	3.4	NUM
ajst-19200	114	2	.	.	PUNCT
ajst-19200	114	3	results	result	NOUN
ajst-19200	114	4	and	and	CCONJ
ajst-19200	114	5	discussion	discussion	NOUN
ajst-19200	114	6	in	in	ADP
ajst-19200	114	7	order	order	NOUN
ajst-19200	114	8	to	to	PART
ajst-19200	114	9	improve	improve	VERB
ajst-19200	114	10	the	the	DET
ajst-19200	114	11	accuracy	accuracy	NOUN
ajst-19200	114	12	of	of	ADP
ajst-19200	114	13	rice	rice	NOUN
ajst-19200	114	14	disease	disease	NOUN
ajst-19200	114	15	detection	detection	NOUN
ajst-19200	114	16	,	,	PUNCT
ajst-19200	114	17	a	a	DET
ajst-19200	114	18	detection	detection	NOUN
ajst-19200	114	19	model	model	NOUN
ajst-19200	114	20	based	base	VERB
ajst-19200	114	21	on	on	ADP
ajst-19200	114	22	yolov8n	yolov8n	PROPN
ajst-19200	114	23	was	be	AUX
ajst-19200	114	24	proposed	propose	VERB
ajst-19200	114	25	in	in	ADP
ajst-19200	114	26	this	this	DET
ajst-19200	114	27	study	study	NOUN
ajst-19200	114	28	.	.	PUNCT
ajst-19200	115	1	table	table	NOUN
ajst-19200	115	2	2	2	NUM
ajst-19200	115	3	shows	show	VERB
ajst-19200	115	4	the	the	DET
ajst-19200	115	5	performance	performance	NOUN
ajst-19200	115	6	of	of	ADP
ajst-19200	115	7	scx	scx	NOUN
ajst-19200	115	8	-	-	PUNCT
ajst-19200	115	9	yolov8n	yolov8n	NOUN
ajst-19200	115	10	and	and	CCONJ
ajst-19200	115	11	yolov8n	yolov8n	PROPN
ajst-19200	115	12	in	in	ADP
ajst-19200	115	13	various	various	ADJ
ajst-19200	115	14	indicators	indicator	NOUN
ajst-19200	115	15	.	.	PUNCT
ajst-19200	116	1	according	accord	VERB
ajst-19200	116	2	to	to	ADP
ajst-19200	116	3	the	the	DET
ajst-19200	116	4	results	result	NOUN
ajst-19200	116	5	in	in	ADP
ajst-19200	116	6	table	table	NOUN
ajst-19200	116	7	2	2	NUM
ajst-19200	116	8	,	,	PUNCT
ajst-19200	116	9	scx	scx	NOUN
ajst-19200	116	10	-	-	PUNCT
ajst-19200	116	11	yolov8n	yolov8n	NOUN
ajst-19200	116	12	is	be	AUX
ajst-19200	116	13	superior	superior	ADJ
ajst-19200	116	14	to	to	ADP
ajst-19200	116	15	the	the	DET
ajst-19200	116	16	original	original	ADJ
ajst-19200	116	17	model	model	NOUN
ajst-19200	116	18	in	in	ADP
ajst-19200	116	19	precision	precision	NOUN
ajst-19200	116	20	,	,	PUNCT
ajst-19200	116	21	the	the	DET
ajst-19200	116	22	map	map	NOUN
ajst-19200	116	23	is	be	AUX
ajst-19200	116	24	increased	increase	VERB
ajst-19200	116	25	by	by	ADP
ajst-19200	116	26	3.0	3.0	NUM
ajst-19200	116	27	%	%	NOUN
ajst-19200	116	28	.	.	PUNCT
ajst-19200	117	1	the	the	DET
ajst-19200	117	2	weight	weight	NOUN
ajst-19200	117	3	file	file	NOUN
ajst-19200	117	4	of	of	ADP
ajst-19200	117	5	sxc	sxc	PROPN
ajst-19200	117	6	-	-	PUNCT
ajst-19200	117	7	yolov8n	yolov8n	PROPN
ajst-19200	117	8	model	model	NOUN
ajst-19200	117	9	is	be	AUX
ajst-19200	117	10	6.13	6.13	NUM
ajst-19200	117	11	mb	mb	NOUN
ajst-19200	117	12	,	,	PUNCT
ajst-19200	117	13	which	which	PRON
ajst-19200	117	14	is	be	AUX
ajst-19200	117	15	3.7	3.7	NUM
ajst-19200	117	16	percentage	percentage	NOUN
ajst-19200	117	17	points	point	NOUN
ajst-19200	117	18	larger	large	ADJ
ajst-19200	117	19	than	than	ADP
ajst-19200	117	20	that	that	PRON
ajst-19200	117	21	of	of	ADP
ajst-19200	117	22	yolov8n	yolov8n	PROPN
ajst-19200	117	23	model	model	NOUN
ajst-19200	117	24	,	,	PUNCT
ajst-19200	117	25	and	and	CCONJ
ajst-19200	117	26	the	the	DET
ajst-19200	117	27	parameter	parameter	NOUN
ajst-19200	117	28	quantity	quantity	NOUN
ajst-19200	117	29	is	be	AUX
ajst-19200	117	30	increased	increase	VERB
ajst-19200	117	31	by	by	ADP
ajst-19200	117	32	3.1	3.1	NUM
ajst-19200	117	33	percentage	percentage	NOUN
ajst-19200	117	34	points	point	NOUN
ajst-19200	117	35	.	.	PUNCT
ajst-19200	118	1	although	although	SCONJ
ajst-19200	118	2	the	the	DET
ajst-19200	118	3	improved	improved	ADJ
ajst-19200	118	4	structure	structure	NOUN
ajst-19200	118	5	has	have	AUX
ajst-19200	118	6	increased	increase	VERB
ajst-19200	118	7	the	the	DET
ajst-19200	118	8	calculation	calculation	NOUN
ajst-19200	118	9	amount	amount	NOUN
ajst-19200	118	10	,	,	PUNCT
ajst-19200	118	11	the	the	DET
ajst-19200	118	12	detection	detection	NOUN
ajst-19200	118	13	accuracy	accuracy	NOUN
ajst-19200	118	14	of	of	ADP
ajst-19200	118	15	rice	rice	NOUN
ajst-19200	118	16	leaf	leaf	NOUN
ajst-19200	118	17	diseases	disease	NOUN
ajst-19200	118	18	has	have	AUX
ajst-19200	118	19	been	be	AUX
ajst-19200	118	20	obviously	obviously	ADV
ajst-19200	118	21	improved	improve	VERB
ajst-19200	118	22	.	.	PUNCT
ajst-19200	119	1	although	although	SCONJ
ajst-19200	119	2	the	the	DET
ajst-19200	119	3	detection	detection	NOUN
ajst-19200	119	4	speed	speed	NOUN
ajst-19200	119	5	of	of	ADP
ajst-19200	119	6	sxc	sxc	PROPN
ajst-19200	119	7	-	-	PUNCT
ajst-19200	119	8	yolov8n	yolov8n	PROPN
ajst-19200	119	9	is	be	AUX
ajst-19200	119	10	6	6	NUM
ajst-19200	119	11	frames	frame	NOUN
ajst-19200	119	12	per	per	ADP
ajst-19200	119	13	second	second	NOUN
ajst-19200	119	14	less	less	ADJ
ajst-19200	119	15	than	than	ADP
ajst-19200	119	16	that	that	PRON
ajst-19200	119	17	of	of	ADP
ajst-19200	119	18	yolov8n	yolov8n	PROPN
ajst-19200	119	19	,	,	PUNCT
ajst-19200	119	20	the	the	DET
ajst-19200	119	21	detection	detection	NOUN
ajst-19200	119	22	speed	speed	NOUN
ajst-19200	119	23	is	be	AUX
ajst-19200	119	24	still	still	ADV
ajst-19200	119	25	200	200	NUM
ajst-19200	119	26	frames	frame	NOUN
ajst-19200	119	27	per	per	ADP
ajst-19200	119	28	second	second	NOUN
ajst-19200	119	29	,	,	PUNCT
ajst-19200	119	30	which	which	PRON
ajst-19200	119	31	meets	meet	VERB
ajst-19200	119	32	the	the	DET
ajst-19200	119	33	requirements	requirement	NOUN
ajst-19200	119	34	of	of	ADP
ajst-19200	119	35	rapid	rapid	ADJ
ajst-19200	119	36	and	and	CCONJ
ajst-19200	119	37	efficient	efficient	ADJ
ajst-19200	119	38	detection	detection	NOUN
ajst-19200	119	39	of	of	ADP
ajst-19200	119	40	rice	rice	NOUN
ajst-19200	119	41	diseases	disease	NOUN
ajst-19200	119	42	.	.	PUNCT
ajst-19200	120	1	table	table	NOUN
ajst-19200	120	2	2	2	NUM
ajst-19200	120	3	.	.	PUNCT
ajst-19200	120	4	comparison	comparison	NOUN
ajst-19200	120	5	of	of	ADP
ajst-19200	120	6	results	result	NOUN
ajst-19200	120	7	before	before	ADP
ajst-19200	120	8	and	and	CCONJ
ajst-19200	120	9	after	after	ADP
ajst-19200	120	10	yolo	yolo	ADJ
ajst-19200	120	11	v8	v8	PROPN
ajst-19200	120	12	n	n	CCONJ
ajst-19200	120	13	improvement	improvement	NOUN
ajst-19200	120	14	model	model	NOUN
ajst-19200	120	15	map@0.5/%	map@0.5/%	PROPN
ajst-19200	120	16	weight	weight	NOUN
ajst-19200	120	17	/	/	SYM
ajst-19200	120	18	mb	mb	PROPN
ajst-19200	120	19	fps	fps	PROPN
ajst-19200	120	20	yolov8n	yolov8n	PROPN
ajst-19200	120	21	86.3	86.3	NUM
ajst-19200	120	22	5.91	5.91	NUM
ajst-19200	120	23	223	223	NUM
ajst-19200	120	24	scx	scx	NOUN
ajst-19200	120	25	-	-	PUNCT
ajst-19200	120	26	yolov8n	yolov8n	NOUN
ajst-19200	120	27	89.3	89.3	NUM
ajst-19200	120	28	6.13	6.13	NUM
ajst-19200	120	29	217	217	NUM
ajst-19200	120	30	in	in	ADP
ajst-19200	120	31	the	the	DET
ajst-19200	120	32	training	training	NOUN
ajst-19200	120	33	process	process	NOUN
ajst-19200	120	34	,	,	PUNCT
ajst-19200	120	35	the	the	DET
ajst-19200	120	36	convergence	convergence	NOUN
ajst-19200	120	37	process	process	NOUN
ajst-19200	120	38	of	of	ADP
ajst-19200	120	39	each	each	DET
ajst-19200	120	40	evaluation	evaluation	NOUN
ajst-19200	120	41	index	index	NOUN
ajst-19200	120	42	of	of	ADP
ajst-19200	120	43	yolov8n	yolov8n	PROPN
ajst-19200	120	44	and	and	CCONJ
ajst-19200	120	45	scx	scx	PROPN
ajst-19200	120	46	-	-	PUNCT
ajst-19200	120	47	yolov8n	yolov8n	NOUN
ajst-19200	120	48	models	model	NOUN
ajst-19200	120	49	is	be	AUX
ajst-19200	120	50	shown	show	VERB
ajst-19200	120	51	in	in	ADP
ajst-19200	120	52	figures	figure	NOUN
ajst-19200	120	53	a	a	PRON
ajst-19200	120	54	and	and	CCONJ
ajst-19200	120	55	b	b	NOUN
ajst-19200	120	56	in	in	ADP
ajst-19200	120	57	figure	figure	NOUN
ajst-19200	120	58	8	8	NUM
ajst-19200	120	59	.	.	PUNCT
ajst-19200	121	1	by	by	ADP
ajst-19200	121	2	comparing	compare	VERB
ajst-19200	121	3	figures	figure	NOUN
ajst-19200	121	4	a	a	PRON
ajst-19200	121	5	and	and	CCONJ
ajst-19200	121	6	b	b	NOUN
ajst-19200	121	7	,	,	PUNCT
ajst-19200	121	8	we	we	PRON
ajst-19200	121	9	can	can	AUX
ajst-19200	121	10	see	see	VERB
ajst-19200	121	11	that	that	SCONJ
ajst-19200	121	12	scx	scx	NOUN
ajst-19200	121	13	-	-	PUNCT
ajst-19200	121	14	yolov8n	yolov8n	NOUN
ajst-19200	121	15	model	model	NOUN
ajst-19200	121	16	is	be	AUX
ajst-19200	121	17	stronger	strong	ADJ
ajst-19200	121	18	than	than	ADP
ajst-19200	121	19	scx	scx	NOUN
ajst-19200	121	20	-	-	PUNCT
ajst-19200	121	21	yolov8n	yolov8n	NOUN
ajst-19200	121	22	in	in	ADP
ajst-19200	121	23	both	both	DET
ajst-19200	121	24	convergence	convergence	NOUN
ajst-19200	121	25	speed	speed	NOUN
ajst-19200	121	26	and	and	CCONJ
ajst-19200	121	27	convergence	convergence	NOUN
ajst-19200	121	28	ability	ability	NOUN
ajst-19200	121	29	.	.	PUNCT
ajst-19200	122	1	among	among	ADP
ajst-19200	122	2	them	they	PRON
ajst-19200	122	3	,	,	PUNCT
ajst-19200	122	4	scx	scx	NOUN
ajst-19200	122	5	-	-	PUNCT
ajst-19200	122	6	yolov8n	yolov8n	PROPN
ajst-19200	122	7	showed	show	VERB
ajst-19200	122	8	a	a	DET
ajst-19200	122	9	fast	fast	ADJ
ajst-19200	122	10	convergence	convergence	NOUN
ajst-19200	122	11	speed	speed	NOUN
ajst-19200	122	12	at	at	ADP
ajst-19200	122	13	the	the	DET
ajst-19200	122	14	initial	initial	ADJ
ajst-19200	122	15	stage	stage	NOUN
ajst-19200	122	16	of	of	ADP
ajst-19200	122	17	training	training	NOUN
ajst-19200	122	18	,	,	PUNCT
ajst-19200	122	19	which	which	PRON
ajst-19200	122	20	means	mean	VERB
ajst-19200	122	21	that	that	SCONJ
ajst-19200	122	22	the	the	DET
ajst-19200	122	23	model	model	NOUN
ajst-19200	122	24	has	have	AUX
ajst-19200	122	25	made	make	VERB
ajst-19200	122	26	rapid	rapid	ADJ
ajst-19200	122	27	progress	progress	NOUN
ajst-19200	122	28	in	in	ADP
ajst-19200	122	29	learning	learn	VERB
ajst-19200	122	30	tasks	task	NOUN
ajst-19200	122	31	.	.	PUNCT
ajst-19200	123	1	in	in	ADP
ajst-19200	123	2	the	the	DET
ajst-19200	123	3	15th	15th	ADJ
ajst-19200	123	4	epoch	epoch	NOUN
ajst-19200	123	5	,	,	PUNCT
ajst-19200	123	6	the	the	DET
ajst-19200	123	7	model	model	NOUN
ajst-19200	123	8	has	have	AUX
ajst-19200	123	9	achieved	achieve	VERB
ajst-19200	123	10	ideal	ideal	ADJ
ajst-19200	123	11	results	result	NOUN
ajst-19200	123	12	,	,	PUNCT
ajst-19200	123	13	which	which	PRON
ajst-19200	123	14	shows	show	VERB
ajst-19200	123	15	that	that	SCONJ
ajst-19200	123	16	the	the	DET
ajst-19200	123	17	model	model	NOUN
ajst-19200	123	18	can	can	AUX
ajst-19200	123	19	effectively	effectively	ADV
ajst-19200	123	20	learn	learn	VERB
ajst-19200	123	21	the	the	DET
ajst-19200	123	22	characteristics	characteristic	NOUN
ajst-19200	123	23	and	and	CCONJ
ajst-19200	123	24	patterns	pattern	NOUN
ajst-19200	123	25	of	of	ADP
ajst-19200	123	26	data	datum	NOUN
ajst-19200	123	27	in	in	ADP
ajst-19200	123	28	a	a	DET
ajst-19200	123	29	short	short	ADJ
ajst-19200	123	30	time	time	NOUN
ajst-19200	123	31	.	.	PUNCT
ajst-19200	124	1	in	in	ADP
ajst-19200	124	2	the	the	DET
ajst-19200	124	3	subsequent	subsequent	ADJ
ajst-19200	124	4	training	training	NOUN
ajst-19200	124	5	process	process	NOUN
ajst-19200	124	6	,	,	PUNCT
ajst-19200	124	7	the	the	DET
ajst-19200	124	8	scx	scx	PROPN
ajst-19200	124	9	-	-	PUNCT
ajst-19200	124	10	yolov8n	yolov8n	NOUN
ajst-19200	124	11	model	model	NOUN
ajst-19200	124	12	continued	continue	VERB
ajst-19200	124	13	to	to	PART
ajst-19200	124	14	improve	improve	VERB
ajst-19200	124	15	,	,	PUNCT
ajst-19200	124	16	and	and	CCONJ
ajst-19200	124	17	finally	finally	ADV
ajst-19200	124	18	reached	reach	VERB
ajst-19200	124	19	the	the	DET
ajst-19200	124	20	optimal	optimal	ADJ
ajst-19200	124	21	value	value	NOUN
ajst-19200	124	22	of	of	ADP
ajst-19200	124	23	89.3	89.3	NUM
ajst-19200	124	24	in	in	ADP
ajst-19200	124	25	the	the	DET
ajst-19200	124	26	232nd	232nd	NOUN
ajst-19200	124	27	epoch	epoch	NOUN
ajst-19200	124	28	.	.	PUNCT
ajst-19200	125	1	this	this	PRON
ajst-19200	125	2	shows	show	VERB
ajst-19200	125	3	that	that	SCONJ
ajst-19200	125	4	the	the	DET
ajst-19200	125	5	model	model	NOUN
ajst-19200	125	6	has	have	AUX
ajst-19200	125	7	achieved	achieve	VERB
ajst-19200	125	8	a	a	DET
ajst-19200	125	9	higher	high	ADJ
ajst-19200	125	10	performance	performance	NOUN
ajst-19200	125	11	level	level	NOUN
ajst-19200	125	12	after	after	ADP
ajst-19200	125	13	continuous	continuous	ADJ
ajst-19200	125	14	training	training	NOUN
ajst-19200	125	15	and	and	CCONJ
ajst-19200	125	16	optimization	optimization	NOUN
ajst-19200	125	17	,	,	PUNCT
ajst-19200	125	18	and	and	CCONJ
ajst-19200	125	19	further	far	ADV
ajst-19200	125	20	improved	improve	VERB
ajst-19200	125	21	the	the	DET
ajst-19200	125	22	accuracy	accuracy	NOUN
ajst-19200	125	23	and	and	CCONJ
ajst-19200	125	24	efficiency	efficiency	NOUN
ajst-19200	125	25	in	in	ADP
ajst-19200	125	26	the	the	DET
ajst-19200	125	27	target	target	NOUN
ajst-19200	125	28	detection	detection	NOUN
ajst-19200	125	29	task	task	NOUN
ajst-19200	125	30	.	.	PUNCT
ajst-19200	126	1	in	in	ADP
ajst-19200	126	2	addition	addition	NOUN
ajst-19200	126	3	to	to	ADP
ajst-19200	126	4	the	the	DET
ajst-19200	126	5	loss	loss	NOUN
ajst-19200	126	6	function	function	NOUN
ajst-19200	126	7	diagram	diagram	NOUN
ajst-19200	126	8	,	,	PUNCT
ajst-19200	126	9	the	the	DET
ajst-19200	126	10	comparison	comparison	NOUN
ajst-19200	126	11	diagram	diagram	NOUN
ajst-19200	126	12	of	of	ADP
ajst-19200	126	13	p	p	NOUN
ajst-19200	126	14	-	-	PUNCT
ajst-19200	126	15	r	r	NOUN
ajst-19200	126	16	curves	curve	NOUN
ajst-19200	126	17	detected	detect	VERB
ajst-19200	126	18	by	by	ADP
ajst-19200	126	19	scx	scx	NOUN
ajst-19200	126	20	-	-	PUNCT
ajst-19200	126	21	yolov8n	yolov8n	NOUN
ajst-19200	126	22	and	and	CCONJ
ajst-19200	126	23	yolov8n	yolov8n	NOUN
ajst-19200	126	24	models	model	NOUN
ajst-19200	126	25	on	on	ADP
ajst-19200	126	26	the	the	DET
ajst-19200	126	27	rice	rice	NOUN
ajst-19200	126	28	leaf	leaf	NOUN
ajst-19200	126	29	disease	disease	NOUN
ajst-19200	126	30	data	datum	NOUN
ajst-19200	126	31	set	set	VERB
ajst-19200	126	32	is	be	AUX
ajst-19200	126	33	shown	show	VERB
ajst-19200	126	34	in	in	ADP
ajst-19200	126	35	figure	figure	NOUN
ajst-19200	126	36	9	9	NUM
ajst-19200	126	37	:	:	PUNCT
ajst-19200	126	38	(	(	PUNCT
ajst-19200	126	39	a)yolov8n	a)yolov8n	X
ajst-19200	126	40	(	(	PUNCT
ajst-19200	126	41	b)scx	b)scx	PROPN
ajst-19200	126	42	-	-	PUNCT
ajst-19200	126	43	yolov8n	yolov8n	NOUN
ajst-19200	126	44	figure	figure	NOUN
ajst-19200	126	45	9	9	NUM
ajst-19200	126	46	.	.	PUNCT
ajst-19200	127	1	p	p	X
ajst-19200	127	2	-	-	PUNCT
ajst-19200	127	3	r	r	NOUN
ajst-19200	127	4	curve	curve	NOUN
ajst-19200	127	5	as	as	SCONJ
ajst-19200	127	6	can	can	AUX
ajst-19200	127	7	be	be	AUX
ajst-19200	127	8	seen	see	VERB
ajst-19200	127	9	from	from	ADP
ajst-19200	127	10	figure	figure	NOUN
ajst-19200	127	11	9	9	NUM
ajst-19200	127	12	,	,	PUNCT
ajst-19200	127	13	scx	scx	NOUN
ajst-19200	127	14	-	-	PUNCT
ajst-19200	127	15	yolov8n	yolov8n	NOUN
ajst-19200	127	16	shows	show	VERB
ajst-19200	127	17	a	a	DET
ajst-19200	127	18	significant	significant	ADJ
ajst-19200	127	19	improvement	improvement	NOUN
ajst-19200	127	20	in	in	ADP
ajst-19200	127	21	the	the	DET
ajst-19200	127	22	detection	detection	NOUN
ajst-19200	127	23	of	of	ADP
ajst-19200	127	24	each	each	DET
ajst-19200	127	25	category	category	NOUN
ajst-19200	127	26	compared	compare	VERB
ajst-19200	127	27	with	with	ADP
ajst-19200	127	28	yolov8n	yolov8n	NOUN
ajst-19200	127	29	,	,	PUNCT
ajst-19200	127	30	and	and	CCONJ
ajst-19200	127	31	the	the	DET
ajst-19200	127	32	area	area	NOUN
ajst-19200	127	33	enclosed	enclose	VERB
ajst-19200	127	34	by	by	ADP
ajst-19200	127	35	the	the	DET
ajst-19200	127	36	curve	curve	NOUN
ajst-19200	127	37	is	be	AUX
ajst-19200	127	38	larger	large	ADJ
ajst-19200	127	39	,	,	PUNCT
ajst-19200	127	40	which	which	PRON
ajst-19200	127	41	means	mean	VERB
ajst-19200	127	42	that	that	SCONJ
ajst-19200	127	43	scx	scx	NOUN
ajst-19200	127	44	-	-	PUNCT
ajst-19200	127	45	yolov8n	yolov8n	NOUN
ajst-19200	127	46	model	model	NOUN
ajst-19200	127	47	is	be	AUX
ajst-19200	127	48	more	more	ADV
ajst-19200	127	49	accurate	accurate	ADJ
ajst-19200	127	50	and	and	CCONJ
ajst-19200	127	51	accurate	accurate	ADJ
ajst-19200	127	52	in	in	ADP
ajst-19200	127	53	the	the	DET
ajst-19200	127	54	task	task	NOUN
ajst-19200	127	55	of	of	ADP
ajst-19200	127	56	rice	rice	NOUN
ajst-19200	127	57	disease	disease	NOUN
ajst-19200	127	58	detection	detection	NOUN
ajst-19200	127	59	,	,	PUNCT
ajst-19200	127	60	and	and	CCONJ
ajst-19200	127	61	can	can	AUX
ajst-19200	127	62	better	well	ADV
ajst-19200	127	63	identify	identify	VERB
ajst-19200	127	64	disease	disease	NOUN
ajst-19200	127	65	types	type	NOUN
ajst-19200	127	66	and	and	CCONJ
ajst-19200	127	67	better	well	ADJ
ajst-19200	127	68	locate	locate	ADJ
ajst-19200	127	69	rice	rice	NOUN
ajst-19200	127	70	diseases	disease	NOUN
ajst-19200	127	71	,	,	PUNCT
ajst-19200	127	72	thus	thus	ADV
ajst-19200	127	73	improving	improve	VERB
ajst-19200	127	74	the	the	DET
ajst-19200	127	75	yield	yield	NOUN
ajst-19200	127	76	and	and	CCONJ
ajst-19200	127	77	reducing	reduce	VERB
ajst-19200	127	78	losses	loss	NOUN
ajst-19200	127	79	.	.	PUNCT
ajst-19200	128	1	in	in	ADP
ajst-19200	128	2	order	order	NOUN
ajst-19200	128	3	to	to	PART
ajst-19200	128	4	compare	compare	VERB
ajst-19200	128	5	the	the	DET
ajst-19200	128	6	detection	detection	NOUN
ajst-19200	128	7	effects	effect	NOUN
ajst-19200	128	8	of	of	ADP
ajst-19200	128	9	the	the	DET
ajst-19200	128	10	improved	improved	ADJ
ajst-19200	128	11	algorithm	algorithm	NOUN
ajst-19200	128	12	and	and	CCONJ
ajst-19200	128	13	the	the	DET
ajst-19200	128	14	improved	improved	ADJ
ajst-19200	128	15	algorithm	algorithm	NOUN
ajst-19200	128	16	more	more	ADV
ajst-19200	128	17	intuitively	intuitively	ADV
ajst-19200	128	18	,	,	PUNCT
ajst-19200	128	19	the	the	DET
ajst-19200	128	20	comparison	comparison	NOUN
ajst-19200	128	21	and	and	CCONJ
ajst-19200	128	22	visualization	visualization	NOUN
ajst-19200	128	23	of	of	ADP
ajst-19200	128	24	the	the	DET
ajst-19200	128	25	detection	detection	NOUN
ajst-19200	128	26	images	image	NOUN
ajst-19200	128	27	before	before	ADV
ajst-19200	128	28	and	and	CCONJ
ajst-19200	128	29	after	after	SCONJ
ajst-19200	128	30	the	the	DET
ajst-19200	128	31	improvement	improvement	NOUN
ajst-19200	128	32	will	will	AUX
ajst-19200	128	33	be	be	AUX
ajst-19200	128	34	made	make	VERB
ajst-19200	128	35	,	,	PUNCT
ajst-19200	128	36	as	as	SCONJ
ajst-19200	128	37	shown	show	VERB
ajst-19200	128	38	in	in	ADP
ajst-19200	128	39	figure	figure	NOUN
ajst-19200	128	40	10	10	NUM
ajst-19200	128	41	.	.	PUNCT
ajst-19200	129	1	(	(	PUNCT
ajst-19200	129	2	a)yolov8n	a)yolov8n	X
ajst-19200	129	3	(	(	PUNCT
ajst-19200	129	4	b)scx	b)scx	PROPN
ajst-19200	129	5	-	-	PUNCT
ajst-19200	129	6	yolov8n	yolov8n	NOUN
ajst-19200	129	7	figure	figure	NOUN
ajst-19200	129	8	8	8	NUM
ajst-19200	129	9	.	.	PUNCT
ajst-19200	129	10	types	type	NOUN
ajst-19200	129	11	of	of	ADP
ajst-19200	129	12	rice	rice	NOUN
ajst-19200	129	13	diseases	disease	NOUN
ajst-19200	129	14	bacterial	bacterial	ADJ
ajst-19200	129	15	blight	blight	NOUN
ajst-19200	129	16	0.93	0.93	NUM
ajst-19200	129	17	blast	blast	NOUN
ajst-19200	129	18	0.88	0.88	NUM
ajst-19200	129	19	blast	blast	NOUN
ajst-19200	129	20	0.82	0.82	NUM
ajst-19200	129	21	brown	brown	ADJ
ajst-19200	129	22	spot	spot	NOUN
ajst-19200	129	23	0.70	0.70	NUM
ajst-19200	129	24	brown	brown	ADJ
ajst-19200	129	25	spot	spot	NOUN
ajst-19200	129	26	0.70	0.70	NUM
ajst-19200	129	27	sheath	sheath	NOUN
ajst-19200	129	28	blight	blight	NOUN
ajst-19200	129	29	0.69	0.69	NUM
ajst-19200	129	30	bacterial	bacterial	ADJ
ajst-19200	129	31	blight	blight	NOUN
ajst-19200	129	32	0.93	0.93	NUM
ajst-19200	129	33	blast	blast	NOUN
ajst-19200	129	34	0.90	0.90	NUM
ajst-19200	129	35	blast	blast	NOUN
ajst-19200	129	36	0.83	0.83	NUM
ajst-19200	129	37	brown	brown	ADJ
ajst-19200	129	38	spot	spot	NOUN
ajst-19200	129	39	0.75	0.75	NUM
ajst-19200	129	40	brown	brown	ADJ
ajst-19200	129	41	spot	spot	NOUN
ajst-19200	129	42	0.70	0.70	NUM
ajst-19200	129	43	sheath	sheath	NOUN
ajst-19200	129	44	blight	blight	NOUN
ajst-19200	129	45	0.86	0.86	NUM
ajst-19200	129	46	bacterial	bacterial	ADJ
ajst-19200	129	47	blight	blight	NOUN
ajst-19200	129	48	0.72	0.72	NUM
ajst-19200	129	49	brown	brown	ADJ
ajst-19200	129	50	spot	spot	NOUN
ajst-19200	129	51	0.72	0.72	NUM
ajst-19200	129	52	blast	blast	NOUN
ajst-19200	129	53	0.64	0.64	NUM
ajst-19200	129	54	blast	blast	NOUN
ajst-19200	129	55	0.75	0.75	NUM
ajst-19200	129	56	a	a	DET
ajst-19200	129	57	b	b	NOUN
ajst-19200	129	58	c	c	PROPN
ajst-19200	129	59	d	d	PROPN
ajst-19200	129	60	a	a	DET
ajst-19200	129	61	´	´	NOUN
ajst-19200	130	1	b	b	NUM
ajst-19200	130	2	´	´	NOUN
ajst-19200	130	3	c	c	NOUN
ajst-19200	130	4	´	´	NOUN
ajst-19200	130	5	d	d	NOUN
ajst-19200	130	6	´	´	NOUN
ajst-19200	130	7	figure	figure	NOUN
ajst-19200	130	8	10	10	NUM
ajst-19200	130	9	.	.	PUNCT
ajst-19200	131	1	detection	detection	NOUN
ajst-19200	131	2	contrast	contrast	NOUN
ajst-19200	131	3	diagram	diagram	NOUN
ajst-19200	131	4	as	as	SCONJ
ajst-19200	131	5	shown	show	VERB
ajst-19200	131	6	in	in	ADP
ajst-19200	131	7	figure	figure	NOUN
ajst-19200	131	8	10	10	NUM
ajst-19200	131	9	,	,	PUNCT
ajst-19200	131	10	in	in	ADP
ajst-19200	131	11	which	which	PRON
ajst-19200	131	12	a	a	DET
ajst-19200	131	13	,	,	PUNCT
ajst-19200	131	14	b	b	NOUN
ajst-19200	131	15	,	,	PUNCT
ajst-19200	131	16	c	c	PROPN
ajst-19200	131	17	and	and	CCONJ
ajst-19200	131	18	d	d	PROPN
ajst-19200	131	19	are	be	AUX
ajst-19200	131	20	the	the	DET
ajst-19200	131	21	model	model	NOUN
ajst-19200	131	22	detection	detection	NOUN
ajst-19200	131	23	charts	chart	NOUN
ajst-19200	131	24	before	before	ADP
ajst-19200	131	25	improvement	improvement	NOUN
ajst-19200	131	26	,	,	PUNCT
ajst-19200	131	27	and	and	CCONJ
ajst-19200	131	28	a	a	DET
ajst-19200	131	29	'	'	PUNCT
ajst-19200	131	30	,	,	PUNCT
ajst-19200	131	31	b	b	NOUN
ajst-19200	131	32	'	'	X
ajst-19200	131	33	,	,	PUNCT
ajst-19200	131	34	c	c	X
ajst-19200	131	35	'	'	PUNCT
ajst-19200	131	36	and	and	CCONJ
ajst-19200	131	37	d	d	X
ajst-19200	131	38	'	'	PUNCT
ajst-19200	131	39	are	be	AUX
ajst-19200	131	40	the	the	DET
ajst-19200	131	41	improved	improved	ADJ
ajst-19200	131	42	model	model	NOUN
ajst-19200	131	43	detection	detection	NOUN
ajst-19200	131	44	charts	chart	NOUN
ajst-19200	131	45	.	.	PUNCT
ajst-19200	132	1	from	from	ADP
ajst-19200	132	2	figures	figure	NOUN
ajst-19200	132	3	a	a	DET
ajst-19200	132	4	,	,	PUNCT
ajst-19200	132	5	b	b	NOUN
ajst-19200	132	6	,	,	PUNCT
ajst-19200	132	7	c	c	PROPN
ajst-19200	132	8	and	and	CCONJ
ajst-19200	132	9	d(a	d(a	PROPN
ajst-19200	132	10	'	'	PART
ajst-19200	132	11	,	,	PUNCT
ajst-19200	132	12	b	b	NOUN
ajst-19200	132	13	'	'	PUNCT
ajst-19200	132	14	,	,	PUNCT
ajst-19200	132	15	c	c	X
ajst-19200	132	16	'	'	PUNCT
ajst-19200	132	17	,	,	PUNCT
ajst-19200	132	18	d	d	NOUN
ajst-19200	132	19	'	'	PUNCT
ajst-19200	132	20	)	)	PUNCT
ajst-19200	132	21	,	,	PUNCT
ajst-19200	132	22	it	it	PRON
ajst-19200	132	23	can	can	AUX
ajst-19200	132	24	be	be	AUX
ajst-19200	132	25	seen	see	VERB
ajst-19200	132	26	that	that	SCONJ
ajst-19200	132	27	the	the	DET
ajst-19200	132	28	overall	overall	ADJ
ajst-19200	132	29	confidence	confidence	NOUN
ajst-19200	132	30	of	of	ADP
ajst-19200	132	31	the	the	DET
ajst-19200	132	32	improved	improved	ADJ
ajst-19200	132	33	model	model	NOUN
ajst-19200	132	34	in	in	ADP
ajst-19200	132	35	detection	detection	NOUN
ajst-19200	132	36	is	be	AUX
ajst-19200	132	37	improved	improve	VERB
ajst-19200	132	38	,	,	PUNCT
ajst-19200	132	39	and	and	CCONJ
ajst-19200	132	40	the	the	DET
ajst-19200	132	41	small	small	ADJ
ajst-19200	132	42	target	target	NOUN
ajst-19200	132	43	is	be	AUX
ajst-19200	132	44	improved	improve	VERB
ajst-19200	132	45	.	.	PUNCT
ajst-19200	133	1	map	map	VERB
ajst-19200	133	2	277	277	NUM
ajst-19200	133	3	4	4	NUM
ajst-19200	133	4	.	.	PUNCT
ajst-19200	134	1	conclusion	conclusion	NOUN
ajst-19200	134	2	in	in	ADP
ajst-19200	134	3	this	this	DET
ajst-19200	134	4	paper	paper	NOUN
ajst-19200	134	5	,	,	PUNCT
ajst-19200	134	6	a	a	DET
ajst-19200	134	7	rice	rice	NOUN
ajst-19200	134	8	leaf	leaf	NOUN
ajst-19200	134	9	disease	disease	NOUN
ajst-19200	134	10	detection	detection	NOUN
ajst-19200	134	11	model	model	NOUN
ajst-19200	134	12	combining	combine	VERB
ajst-19200	134	13	sppg	sppg	ADJ
ajst-19200	134	14	structure	structure	NOUN
ajst-19200	134	15	,	,	PUNCT
ajst-19200	134	16	ca	can	AUX
ajst-19200	134	17	attention	attention	NOUN
ajst-19200	134	18	mechanism	mechanism	NOUN
ajst-19200	134	19	and	and	CCONJ
ajst-19200	134	20	xsepconv	xsepconv	NOUN
ajst-19200	134	21	structure	structure	NOUN
ajst-19200	134	22	with	with	ADP
ajst-19200	134	23	different	different	ADJ
ajst-19200	134	24	expansion	expansion	NOUN
ajst-19200	134	25	rates	rate	NOUN
ajst-19200	134	26	is	be	AUX
ajst-19200	134	27	proposed	propose	VERB
ajst-19200	134	28	.	.	PUNCT
ajst-19200	135	1	through	through	ADP
ajst-19200	135	2	training	training	NOUN
ajst-19200	135	3	and	and	CCONJ
ajst-19200	135	4	optimization	optimization	NOUN
ajst-19200	135	5	on	on	ADP
ajst-19200	135	6	a	a	DET
ajst-19200	135	7	large	large	ADJ
ajst-19200	135	8	-	-	PUNCT
ajst-19200	135	9	scale	scale	NOUN
ajst-19200	135	10	rice	rice	NOUN
ajst-19200	135	11	leaf	leaf	NOUN
ajst-19200	135	12	disease	disease	NOUN
ajst-19200	135	13	data	datum	NOUN
ajst-19200	135	14	set	set	VERB
ajst-19200	135	15	,	,	PUNCT
ajst-19200	135	16	the	the	DET
ajst-19200	135	17	excellent	excellent	ADJ
ajst-19200	135	18	performance	performance	NOUN
ajst-19200	135	19	of	of	ADP
ajst-19200	135	20	scx	scx	NOUN
ajst-19200	135	21	-	-	PUNCT
ajst-19200	135	22	yolov8n	yolov8n	NOUN
ajst-19200	135	23	in	in	ADP
ajst-19200	135	24	rice	rice	NOUN
ajst-19200	135	25	leaf	leaf	NOUN
ajst-19200	135	26	disease	disease	NOUN
ajst-19200	135	27	detection	detection	NOUN
ajst-19200	135	28	task	task	NOUN
ajst-19200	135	29	is	be	AUX
ajst-19200	135	30	demonstrated	demonstrate	VERB
ajst-19200	135	31	.	.	PUNCT
ajst-19200	136	1	the	the	DET
ajst-19200	136	2	experimental	experimental	ADJ
ajst-19200	136	3	results	result	NOUN
ajst-19200	136	4	show	show	VERB
ajst-19200	136	5	that	that	SCONJ
ajst-19200	136	6	the	the	DET
ajst-19200	136	7	map	map	NOUN
ajst-19200	136	8	of	of	ADP
ajst-19200	136	9	the	the	DET
ajst-19200	136	10	model	model	NOUN
ajst-19200	136	11	reaches	reach	VERB
ajst-19200	136	12	89.3	89.3	NUM
ajst-19200	136	13	%	%	NOUN
ajst-19200	136	14	,	,	PUNCT
ajst-19200	136	15	which	which	PRON
ajst-19200	136	16	can	can	AUX
ajst-19200	136	17	meet	meet	VERB
ajst-19200	136	18	the	the	DET
ajst-19200	136	19	requirements	requirement	NOUN
ajst-19200	136	20	of	of	ADP
ajst-19200	136	21	detecting	detect	VERB
ajst-19200	136	22	leaf	leaf	NOUN
ajst-19200	136	23	diseases	disease	NOUN
ajst-19200	136	24	of	of	ADP
ajst-19200	136	25	rice	rice	NOUN
ajst-19200	136	26	to	to	ADP
ajst-19200	136	27	a	a	DET
ajst-19200	136	28	certain	certain	ADJ
ajst-19200	136	29	extent	extent	NOUN
ajst-19200	136	30	,	,	PUNCT
ajst-19200	136	31	and	and	CCONJ
ajst-19200	136	32	also	also	ADV
ajst-19200	136	33	has	have	VERB
ajst-19200	136	34	the	the	DET
ajst-19200	136	35	characteristics	characteristic	NOUN
ajst-19200	136	36	of	of	ADP
ajst-19200	136	37	light	light	ADJ
ajst-19200	136	38	weight	weight	NOUN
ajst-19200	136	39	.	.	PUNCT
ajst-19200	137	1	the	the	DET
ajst-19200	137	2	model	model	NOUN
ajst-19200	137	3	is	be	AUX
ajst-19200	137	4	only	only	ADV
ajst-19200	137	5	6.5	6.5	NUM
ajst-19200	137	6	mb	mb	NOUN
ajst-19200	137	7	and	and	CCONJ
ajst-19200	137	8	can	can	AUX
ajst-19200	137	9	be	be	AUX
ajst-19200	137	10	easily	easily	ADV
ajst-19200	137	11	integrated	integrate	VERB
ajst-19200	137	12	into	into	ADP
ajst-19200	137	13	embedded	embed	VERB
ajst-19200	137	14	devices	device	NOUN
ajst-19200	137	15	.	.	PUNCT
ajst-19200	138	1	the	the	DET
ajst-19200	138	2	future	future	ADJ
ajst-19200	138	3	work	work	NOUN
ajst-19200	138	4	of	of	ADP
ajst-19200	138	5	this	this	DET
ajst-19200	138	6	research	research	NOUN
ajst-19200	138	7	will	will	AUX
ajst-19200	138	8	focus	focus	VERB
ajst-19200	138	9	on	on	ADP
ajst-19200	138	10	integrating	integrate	VERB
ajst-19200	138	11	the	the	DET
ajst-19200	138	12	proposed	propose	VERB
ajst-19200	138	13	model	model	NOUN
ajst-19200	138	14	into	into	ADP
ajst-19200	138	15	mobile	mobile	ADJ
ajst-19200	138	16	devices	device	NOUN
ajst-19200	138	17	or	or	CCONJ
ajst-19200	138	18	drones	drone	NOUN
ajst-19200	138	19	,	,	PUNCT
ajst-19200	138	20	so	so	SCONJ
ajst-19200	138	21	that	that	SCONJ
ajst-19200	138	22	marginal	marginal	ADJ
ajst-19200	138	23	farmers	farmer	NOUN
ajst-19200	138	24	can	can	AUX
ajst-19200	138	25	use	use	VERB
ajst-19200	138	26	smart	smart	ADJ
ajst-19200	138	27	phones	phone	NOUN
ajst-19200	138	28	to	to	PART
ajst-19200	138	29	detect	detect	VERB
ajst-19200	138	30	leaf	leaf	NOUN
ajst-19200	138	31	diseases	disease	NOUN
ajst-19200	138	32	in	in	ADP
ajst-19200	138	33	real	real	ADJ
ajst-19200	138	34	time	time	NOUN
ajst-19200	138	35	,	,	PUNCT
ajst-19200	138	36	or	or	CCONJ
ajst-19200	138	37	observe	observe	VERB
ajst-19200	138	38	large	large	ADJ
ajst-19200	138	39	-	-	PUNCT
ajst-19200	138	40	scale	scale	NOUN
ajst-19200	138	41	rice	rice	NOUN
ajst-19200	138	42	fields	field	NOUN
ajst-19200	138	43	on	on	ADP
ajst-19200	138	44	drones	drone	NOUN
ajst-19200	138	45	.	.	PUNCT
ajst-19200	139	1	in	in	ADP
ajst-19200	139	2	addition	addition	NOUN
ajst-19200	139	3	,	,	PUNCT
ajst-19200	139	4	the	the	DET
ajst-19200	139	5	study	study	NOUN
ajst-19200	139	6	will	will	AUX
ajst-19200	139	7	explore	explore	VERB
ajst-19200	139	8	a	a	DET
ajst-19200	139	9	higher	high	ADJ
ajst-19200	139	10	map	map	NOUN
ajst-19200	139	11	model	model	NOUN
ajst-19200	139	12	to	to	PART
ajst-19200	139	13	further	far	ADV
ajst-19200	139	14	improve	improve	VERB
ajst-19200	139	15	the	the	DET
ajst-19200	139	16	accuracy	accuracy	NOUN
ajst-19200	139	17	of	of	ADP
ajst-19200	139	18	the	the	DET
ajst-19200	139	19	detection	detection	NOUN
ajst-19200	139	20	system	system	NOUN
ajst-19200	139	21	and	and	CCONJ
ajst-19200	139	22	provide	provide	VERB
ajst-19200	139	23	strong	strong	ADJ
ajst-19200	139	24	support	support	NOUN
ajst-19200	139	25	for	for	ADP
ajst-19200	139	26	disease	disease	NOUN
ajst-19200	139	27	diagnosis	diagnosis	NOUN
ajst-19200	139	28	and	and	CCONJ
ajst-19200	139	29	prevention	prevention	NOUN
ajst-19200	139	30	in	in	ADP
ajst-19200	139	31	the	the	DET
ajst-19200	139	32	agricultural	agricultural	ADJ
ajst-19200	139	33	field	field	NOUN
ajst-19200	139	34	.	.	PUNCT
ajst-19200	140	1	references	reference	NOUN
ajst-19200	140	2	[	[	X
ajst-19200	140	3	1	1	NUM
ajst-19200	140	4	]	]	X
ajst-19200	140	5	mishra	mishra	PROPN
ajst-19200	140	6	r	r	PROPN
ajst-19200	140	7	,	,	PUNCT
ajst-19200	140	8	joshi	joshi	PROPN
ajst-19200	140	9	r	r	PROPN
ajst-19200	140	10	k	k	PROPN
ajst-19200	140	11	,	,	PUNCT
ajst-19200	140	12	zhao	zhao	PROPN
ajst-19200	140	13	k.	k.	PROPN
ajst-19200	140	14	genome	genome	NOUN
ajst-19200	140	15	editing	editing	NOUN
ajst-19200	140	16	in	in	ADP
ajst-19200	140	17	rice	rice	NOUN
ajst-19200	140	18	:	:	PUNCT
ajst-19200	140	19	recent	recent	ADJ
ajst-19200	140	20	advances	advance	NOUN
ajst-19200	140	21	,	,	PUNCT
ajst-19200	140	22	challenges	challenge	NOUN
ajst-19200	140	23	,	,	PUNCT
ajst-19200	140	24	and	and	CCONJ
ajst-19200	140	25	future	future	ADJ
ajst-19200	140	26	implications[j	implications[j	NOUN
ajst-19200	140	27	]	]	PUNCT
ajst-19200	140	28	.	.	PUNCT
ajst-19200	141	1	frontiers	frontier	NOUN
ajst-19200	141	2	in	in	ADP
ajst-19200	141	3	plant	plant	NOUN
ajst-19200	141	4	science	science	NOUN
ajst-19200	141	5	,	,	PUNCT
ajst-19200	141	6	2018,9	2018,9	NUM
ajst-19200	141	7	:	:	PUNCT
ajst-19200	141	8	1361	1361	NUM
ajst-19200	141	9	.	.	PUNCT
ajst-19200	142	1	[	[	X
ajst-19200	142	2	2	2	NUM
ajst-19200	142	3	]	]	X
ajst-19200	142	4	jia	jia	PROPN
ajst-19200	142	5	l	l	PROPN
ajst-19200	142	6	,	,	PUNCT
ajst-19200	142	7	wang	wang	PROPN
ajst-19200	142	8	t	t	PROPN
ajst-19200	142	9	,	,	PUNCT
ajst-19200	142	10	chen	chen	PROPN
ajst-19200	142	11	y	y	PROPN
ajst-19200	142	12	,	,	PUNCT
ajst-19200	142	13	et	et	PROPN
ajst-19200	142	14	al	al	PROPN
ajst-19200	142	15	.	.	PUNCT
ajst-19200	142	16	mobilenet	mobilenet	PROPN
ajst-19200	142	17	-	-	PUNCT
ajst-19200	142	18	ca	ca	NOUN
ajst-19200	142	19	-	-	PUNCT
ajst-19200	142	20	yolo	yolo	NOUN
ajst-19200	142	21	:	:	PUNCT
ajst-19200	142	22	an	an	DET
ajst-19200	142	23	improved	improved	ADJ
ajst-19200	142	24	yolov7	yolov7	NOUN
ajst-19200	142	25	based	base	VERB
ajst-19200	142	26	on	on	ADP
ajst-19200	142	27	the	the	DET
ajst-19200	142	28	mobilenetv3	mobilenetv3	NOUN
ajst-19200	142	29	and	and	CCONJ
ajst-19200	142	30	attention	attention	NOUN
ajst-19200	142	31	mechanism	mechanism	NOUN
ajst-19200	142	32	for	for	ADP
ajst-19200	142	33	rice	rice	NOUN
ajst-19200	142	34	pests	pest	NOUN
ajst-19200	142	35	and	and	CCONJ
ajst-19200	142	36	diseases	disease	NOUN
ajst-19200	142	37	detection[j	detection[j	PROPN
ajst-19200	142	38	]	]	PUNCT
ajst-19200	142	39	.	.	PUNCT
ajst-19200	143	1	agriculture	agriculture	NOUN
ajst-19200	143	2	,	,	PUNCT
ajst-19200	143	3	2023,13(7	2023,13(7	NOUN
ajst-19200	143	4	):	):	PUNCT
ajst-19200	143	5	1285	1285	NUM
ajst-19200	143	6	.	.	PUNCT
ajst-19200	144	1	[	[	X
ajst-19200	144	2	3	3	NUM
ajst-19200	144	3	]	]	X
ajst-19200	144	4	matin	matin	PROPN
ajst-19200	144	5	m	m	PROPN
ajst-19200	144	6	m	m	PROPN
ajst-19200	144	7	h	h	NOUN
ajst-19200	144	8	,	,	PUNCT
ajst-19200	144	9	khatun	khatun	PROPN
ajst-19200	144	10	a	a	PRON
ajst-19200	144	11	,	,	PUNCT
ajst-19200	144	12	moazzam	moazzam	VERB
ajst-19200	144	13	m	m	NOUN
ajst-19200	144	14	g	g	NOUN
ajst-19200	144	15	,	,	PUNCT
ajst-19200	144	16	et	et	PROPN
ajst-19200	144	17	al	al	PROPN
ajst-19200	144	18	.	.	PUNCT
ajst-19200	145	1	an	an	DET
ajst-19200	145	2	efficient	efficient	ADJ
ajst-19200	145	3	disease	disease	NOUN
ajst-19200	145	4	detection	detection	NOUN
ajst-19200	145	5	technique	technique	NOUN
ajst-19200	145	6	of	of	ADP
ajst-19200	145	7	rice	rice	NOUN
ajst-19200	145	8	leaf	leaf	NOUN
ajst-19200	145	9	using	use	VERB
ajst-19200	145	10	alexnet[j	alexnet[j	PRON
ajst-19200	145	11	]	]	PUNCT
ajst-19200	145	12	.	.	PUNCT
ajst-19200	146	1	journal	journal	PROPN
ajst-19200	146	2	of	of	ADP
ajst-19200	146	3	computer	computer	NOUN
ajst-19200	146	4	and	and	CCONJ
ajst-19200	146	5	communications	communication	NOUN
ajst-19200	146	6	,	,	PUNCT
ajst-19200	146	7	2020,8(12	2020,8(12	NUM
ajst-19200	146	8	):	):	PUNCT
ajst-19200	146	9	49	49	NUM
ajst-19200	146	10	-	-	SYM
ajst-19200	146	11	57	57	NUM
ajst-19200	146	12	.	.	PUNCT
ajst-19200	147	1	[	[	X
ajst-19200	147	2	4	4	X
ajst-19200	147	3	]	]	X
ajst-19200	147	4	zhou	zhou	NOUN
ajst-19200	147	5	g	g	PROPN
ajst-19200	147	6	,	,	PUNCT
ajst-19200	147	7	zhang	zhang	PROPN
ajst-19200	147	8	w	w	PROPN
ajst-19200	147	9	,	,	PUNCT
ajst-19200	147	10	chen	chen	PROPN
ajst-19200	147	11	a	a	PROPN
ajst-19200	147	12	,	,	PUNCT
ajst-19200	147	13	et	et	PROPN
ajst-19200	147	14	al	al	PROPN
ajst-19200	147	15	.	.	PROPN
ajst-19200	147	16	rapid	rapid	ADJ
ajst-19200	147	17	detection	detection	NOUN
ajst-19200	147	18	of	of	ADP
ajst-19200	147	19	rice	rice	NOUN
ajst-19200	147	20	disease	disease	NOUN
ajst-19200	147	21	based	base	VERB
ajst-19200	147	22	on	on	ADP
ajst-19200	147	23	fcm	fcm	NOUN
ajst-19200	147	24	-	-	ADJ
ajst-19200	147	25	km	km	NOUN
ajst-19200	147	26	and	and	CCONJ
ajst-19200	147	27	faster	fast	ADJ
ajst-19200	147	28	r	r	NOUN
ajst-19200	147	29	-	-	PUNCT
ajst-19200	147	30	cnn	cnn	NOUN
ajst-19200	147	31	fusion[j	fusion[j	PROPN
ajst-19200	147	32	]	]	PUNCT
ajst-19200	147	33	.	.	PUNCT
ajst-19200	148	1	ieee	ieee	NOUN
ajst-19200	148	2	access	access	NOUN
ajst-19200	148	3	,	,	PUNCT
ajst-19200	148	4	2019,7	2019,7	NUM
ajst-19200	148	5	:	:	PUNCT
ajst-19200	148	6	143190	143190	NUM
ajst-19200	148	7	-	-	SYM
ajst-19200	148	8	143206	143206	NUM
ajst-19200	148	9	.	.	PUNCT
ajst-19200	149	1	[	[	X
ajst-19200	149	2	5	5	X
ajst-19200	149	3	]	]	X
ajst-19200	149	4	chen	chen	PROPN
ajst-19200	149	5	j	j	PROPN
ajst-19200	149	6	,	,	PUNCT
ajst-19200	149	7	chen	chen	PROPN
ajst-19200	149	8	w	w	PROPN
ajst-19200	149	9	,	,	PUNCT
ajst-19200	149	10	zeb	zeb	PROPN
ajst-19200	149	11	a	a	PROPN
ajst-19200	149	12	,	,	PUNCT
ajst-19200	149	13	et	et	PROPN
ajst-19200	149	14	al	al	PROPN
ajst-19200	149	15	.	.	PUNCT
ajst-19200	149	16	lightweight	lightweight	PROPN
ajst-19200	149	17	inception	inception	NOUN
ajst-19200	149	18	networks	network	NOUN
ajst-19200	149	19	for	for	ADP
ajst-19200	149	20	the	the	DET
ajst-19200	149	21	recognition	recognition	NOUN
ajst-19200	149	22	and	and	CCONJ
ajst-19200	149	23	detection	detection	NOUN
ajst-19200	149	24	of	of	ADP
ajst-19200	149	25	rice	rice	NOUN
ajst-19200	149	26	plant	plant	NOUN
ajst-19200	149	27	diseases[j	diseases[j	PROPN
ajst-19200	149	28	]	]	PUNCT
ajst-19200	149	29	.	.	PUNCT
ajst-19200	150	1	ieee	ieee	PROPN
ajst-19200	150	2	sensors	sensor	NOUN
ajst-19200	150	3	journal	journal	PROPN
ajst-19200	150	4	,	,	PUNCT
ajst-19200	150	5	2022,22(14	2022,22(14	NUM
ajst-19200	150	6	):	):	PUNCT
ajst-19200	150	7	14628	14628	NUM
ajst-19200	150	8	-	-	SYM
ajst-19200	150	9	14638	14638	NUM
ajst-19200	150	10	.	.	PUNCT
ajst-19200	151	1	[	[	X
ajst-19200	151	2	6	6	NUM
ajst-19200	151	3	]	]	X
ajst-19200	151	4	yumang	yumang	NOUN
ajst-19200	151	5	a	a	DET
ajst-19200	151	6	n	n	CCONJ
ajst-19200	151	7	,	,	PUNCT
ajst-19200	151	8	villaverde	villaverde	ADJ
ajst-19200	151	9	j	j	PROPN
ajst-19200	152	1	f	f	X
ajst-19200	152	2	,	,	PUNCT
ajst-19200	152	3	mc	mc	PROPN
ajst-19200	152	4	henry	henry	PROPN
ajst-19200	152	5	c	c	PROPN
ajst-19200	152	6	t	t	PROPN
ajst-19200	152	7	,	,	PUNCT
ajst-19200	152	8	et	et	PROPN
ajst-19200	152	9	al	al	PROPN
ajst-19200	152	10	.	.	PUNCT
ajst-19200	153	1	bacterial	bacterial	ADJ
ajst-19200	153	2	leaf	leaf	NOUN
ajst-19200	153	3	blight	blight	NOUN
ajst-19200	153	4	identification	identification	NOUN
ajst-19200	153	5	of	of	ADP
ajst-19200	153	6	rice	rice	NOUN
ajst-19200	153	7	fields	field	NOUN
ajst-19200	153	8	using	use	VERB
ajst-19200	153	9	tiny	tiny	ADJ
ajst-19200	153	10	yolov3	yolov3	PROPN
ajst-19200	153	11	:	:	PUNCT
ajst-19200	153	12	2022	2022	NUM
ajst-19200	153	13	ieee	ieee	PROPN
ajst-19200	153	14	international	international	ADJ
ajst-19200	153	15	conference	conference	NOUN
ajst-19200	153	16	on	on	ADP
ajst-19200	153	17	artificial	artificial	ADJ
ajst-19200	153	18	intelligence	intelligence	NOUN
ajst-19200	153	19	in	in	ADP
ajst-19200	153	20	engineering	engineering	NOUN
ajst-19200	153	21	and	and	CCONJ
ajst-19200	153	22	technology	technology	NOUN
ajst-19200	153	23	(	(	PUNCT
ajst-19200	153	24	iicaiet)[c	iicaiet)[c	PROPN
ajst-19200	153	25	]	]	X
ajst-19200	153	26	:	:	PUNCT
ajst-19200	153	27	ieee	ieee	NOUN
ajst-19200	153	28	,	,	PUNCT
ajst-19200	153	29	2022	2022	NUM
ajst-19200	153	30	.	.	PUNCT
ajst-19200	154	1	[	[	X
ajst-19200	154	2	7	7	X
ajst-19200	154	3	]	]	X
ajst-19200	154	4	masykur	masykur	X
ajst-19200	154	5	f	f	PROPN
ajst-19200	154	6	,	,	PUNCT
ajst-19200	154	7	adi	adi	PROPN
ajst-19200	154	8	k	k	PROPN
ajst-19200	154	9	,	,	PUNCT
ajst-19200	154	10	nurhayati	nurhayati	PROPN
ajst-19200	154	11	o	o	PROPN
ajst-19200	154	12	d.	d.	PROPN
ajst-19200	154	13	approach	approach	NOUN
ajst-19200	154	14	and	and	CCONJ
ajst-19200	154	15	analysis	analysis	NOUN
ajst-19200	154	16	of	of	ADP
ajst-19200	154	17	yolov4	yolov4	PROPN
ajst-19200	154	18	algorithm	algorithm	NOUN
ajst-19200	154	19	for	for	ADP
ajst-19200	154	20	rice	rice	NOUN
ajst-19200	154	21	diseases	disease	NOUN
ajst-19200	154	22	detection	detection	NOUN
ajst-19200	154	23	at	at	ADP
ajst-19200	154	24	different	different	ADJ
ajst-19200	154	25	drone	drone	NOUN
ajst-19200	154	26	image	image	NOUN
ajst-19200	154	27	acquisition	acquisition	NOUN
ajst-19200	154	28	distances[j	distances[j	PROPN
ajst-19200	154	29	]	]	PUNCT
ajst-19200	154	30	.	.	PUNCT
ajst-19200	155	1	2023	2023	NUM
ajst-19200	155	2	.	.	PUNCT
ajst-19200	156	1	[	[	X
ajst-19200	156	2	8	8	NUM
ajst-19200	156	3	]	]	X
ajst-19200	156	4	jhatial	jhatial	ADJ
ajst-19200	156	5	m	m	PROPN
ajst-19200	156	6	j	j	PROPN
ajst-19200	156	7	,	,	PUNCT
ajst-19200	156	8	shaikh	shaikh	PROPN
ajst-19200	156	9	r	r	PROPN
ajst-19200	156	10	a	a	NOUN
ajst-19200	156	11	,	,	PUNCT
ajst-19200	156	12	shaikh	shaikh	PROPN
ajst-19200	156	13	n	n	CCONJ
ajst-19200	156	14	a	a	PROPN
ajst-19200	156	15	,	,	PUNCT
ajst-19200	156	16	et	et	PROPN
ajst-19200	156	17	al	al	PROPN
ajst-19200	156	18	.	.	PUNCT
ajst-19200	157	1	deep	deep	ADJ
ajst-19200	157	2	learning	learning	NOUN
ajst-19200	157	3	-	-	PUNCT
ajst-19200	157	4	based	base	VERB
ajst-19200	157	5	rice	rice	NOUN
ajst-19200	157	6	leaf	leaf	NOUN
ajst-19200	157	7	diseases	disease	NOUN
ajst-19200	157	8	detection	detection	NOUN
ajst-19200	157	9	using	use	VERB
ajst-19200	157	10	yolov5[j	yolov5[j	PROPN
ajst-19200	157	11	]	]	PUNCT
ajst-19200	157	12	.	.	PUNCT
ajst-19200	158	1	sukkur	sukkur	PROPN
ajst-19200	158	2	iba	iba	PROPN
ajst-19200	158	3	journal	journal	PROPN
ajst-19200	158	4	of	of	ADP
ajst-19200	158	5	computing	computing	NOUN
ajst-19200	158	6	and	and	CCONJ
ajst-19200	158	7	mathematical	mathematical	ADJ
ajst-19200	158	8	sciences	sciences	PROPN
ajst-19200	158	9	,	,	PUNCT
ajst-19200	158	10	2022,6(1	2022,6(1	NUM
ajst-19200	158	11	):	):	PUNCT
ajst-19200	158	12	49	49	NUM
ajst-19200	158	13	-	-	SYM
ajst-19200	158	14	61	61	NUM
ajst-19200	158	15	.	.	PUNCT
ajst-19200	159	1	[	[	X
ajst-19200	159	2	9	9	NUM
ajst-19200	159	3	]	]	X
ajst-19200	159	4	wu	wu	PROPN
ajst-19200	159	5	z	z	PROPN
ajst-19200	159	6	,	,	PUNCT
ajst-19200	159	7	xue	xue	PROPN
ajst-19200	159	8	r	r	PROPN
ajst-19200	159	9	,	,	PUNCT
ajst-19200	159	10	li	li	PROPN
ajst-19200	159	11	h.	h.	PROPN
ajst-19200	159	12	real	real	ADJ
ajst-19200	159	13	-	-	PUNCT
ajst-19200	159	14	time	time	NOUN
ajst-19200	159	15	video	video	NOUN
ajst-19200	159	16	fire	fire	NOUN
ajst-19200	159	17	detection	detection	NOUN
ajst-19200	159	18	via	via	ADP
ajst-19200	159	19	modified	modified	ADJ
ajst-19200	159	20	yolov5	yolov5	NOUN
ajst-19200	159	21	network	network	NOUN
ajst-19200	159	22	model[j	model[j	PROPN
ajst-19200	159	23	]	]	PUNCT
ajst-19200	159	24	.	.	PUNCT
ajst-19200	160	1	fire	fire	NOUN
ajst-19200	160	2	technology	technology	NOUN
ajst-19200	160	3	,	,	PUNCT
ajst-19200	160	4	2022,58(4	2022,58(4	NOUN
ajst-19200	160	5	):	):	PUNCT
ajst-19200	160	6	2377	2377	NUM
ajst-19200	160	7	-	-	SYM
ajst-19200	160	8	2403	2403	NUM
ajst-19200	160	9	.	.	PUNCT
ajst-19200	161	1	[	[	X
ajst-19200	161	2	10	10	NUM
ajst-19200	161	3	]	]	X
ajst-19200	161	4	hou	hou	PROPN
ajst-19200	162	1	q	q	NOUN
ajst-19200	162	2	,	,	PUNCT
ajst-19200	162	3	zhou	zhou	PROPN
ajst-19200	162	4	d	d	PROPN
ajst-19200	162	5	,	,	PUNCT
ajst-19200	162	6	feng	feng	PROPN
ajst-19200	162	7	j.	j.	PROPN
ajst-19200	162	8	coordinate	coordinate	VERB
ajst-19200	162	9	attention	attention	NOUN
ajst-19200	162	10	for	for	ADP
ajst-19200	162	11	efficient	efficient	ADJ
ajst-19200	162	12	mobile	mobile	ADJ
ajst-19200	162	13	network	network	NOUN
ajst-19200	162	14	design	design	NOUN
ajst-19200	162	15	:	:	PUNCT
ajst-19200	162	16	proceedings	proceeding	NOUN
ajst-19200	162	17	of	of	ADP
ajst-19200	162	18	the	the	DET
ajst-19200	162	19	ieee	ieee	NOUN
ajst-19200	162	20	/	/	SYM
ajst-19200	162	21	cvf	cvf	NOUN
ajst-19200	162	22	conference	conference	NOUN
ajst-19200	162	23	on	on	ADP
ajst-19200	162	24	computer	computer	NOUN
ajst-19200	162	25	vision	vision	NOUN
ajst-19200	162	26	and	and	CCONJ
ajst-19200	162	27	pattern	pattern	NOUN
ajst-19200	162	28	recognition[c	recognition[c	PROPN
ajst-19200	162	29	]	]	PUNCT
ajst-19200	162	30	,	,	PUNCT
ajst-19200	162	31	2021	2021	NUM
ajst-19200	162	32	.	.	PUNCT
ajst-19200	163	1	[	[	X
ajst-19200	163	2	11	11	NUM
ajst-19200	163	3	]	]	X
ajst-19200	163	4	chen	chen	PROPN
ajst-19200	163	5	j	j	PROPN
ajst-19200	163	6	,	,	PUNCT
ajst-19200	163	7	lu	lu	PROPN
ajst-19200	163	8	z	z	PROPN
ajst-19200	163	9	,	,	PUNCT
ajst-19200	163	10	xue	xue	PROPN
ajst-19200	163	11	j	j	PROPN
ajst-19200	163	12	,	,	PUNCT
ajst-19200	163	13	et	et	PROPN
ajst-19200	163	14	al	al	PROPN
ajst-19200	163	15	.	.	PROPN
ajst-19200	164	1	xsepconv	xsepconv	PROPN
ajst-19200	164	2	:	:	PUNCT
ajst-19200	164	3	extremely	extremely	ADV
ajst-19200	164	4	separated	separate	VERB
ajst-19200	164	5	convolution[j	convolution[j	NOUN
ajst-19200	164	6	]	]	PUNCT
ajst-19200	164	7	.	.	PUNCT
ajst-19200	165	1	arxiv	arxiv	PROPN
ajst-19200	165	2	preprint	preprint	VERB
ajst-19200	165	3	arxiv:2002.12046	arxiv:2002.12046	PROPN
ajst-19200	165	4	,	,	PUNCT
ajst-19200	165	5	2020	2020	NUM
ajst-19200	165	6	.	.	PUNCT
ajst-19200	166	1	[	[	X
ajst-19200	166	2	12	12	NUM
ajst-19200	166	3	]	]	PUNCT
ajst-19200	166	4	he	he	PRON
ajst-19200	166	5	k	k	PROPN
ajst-19200	166	6	,	,	PUNCT
ajst-19200	166	7	zhang	zhang	PROPN
ajst-19200	166	8	x	x	PROPN
ajst-19200	166	9	,	,	PUNCT
ajst-19200	166	10	ren	ren	PROPN
ajst-19200	166	11	s	s	PROPN
ajst-19200	166	12	,	,	PUNCT
ajst-19200	166	13	et	et	PROPN
ajst-19200	166	14	al	al	PROPN
ajst-19200	166	15	.	.	PUNCT
ajst-19200	167	1	spatial	spatial	ADJ
ajst-19200	167	2	pyramid	pyramid	NOUN
ajst-19200	167	3	pooling	pool	VERB
ajst-19200	167	4	in	in	ADP
ajst-19200	167	5	deep	deep	ADJ
ajst-19200	167	6	convolutional	convolutional	ADJ
ajst-19200	167	7	networks	network	NOUN
ajst-19200	167	8	for	for	ADP
ajst-19200	167	9	visual	visual	ADJ
ajst-19200	167	10	recognition[j	recognition[j	NOUN
ajst-19200	167	11	]	]	PUNCT
ajst-19200	167	12	.	.	PUNCT
ajst-19200	168	1	ieee	ieee	NOUN
ajst-19200	168	2	transactions	transaction	NOUN
ajst-19200	168	3	on	on	ADP
ajst-19200	168	4	pattern	pattern	NOUN
ajst-19200	168	5	analysis	analysis	NOUN
ajst-19200	168	6	and	and	CCONJ
ajst-19200	168	7	machine	machine	NOUN
ajst-19200	168	8	intelligence	intelligence	NOUN
ajst-19200	168	9	,	,	PUNCT
ajst-19200	168	10	2015,37(9	2015,37(9	NOUN
ajst-19200	168	11	):	):	PUNCT
ajst-19200	168	12	1904	1904	NUM
ajst-19200	168	13	-	-	SYM
ajst-19200	168	14	1916	1916	NUM
ajst-19200	168	15	.	.	PUNCT
ajst-19200	169	1	[	[	X
ajst-19200	169	2	13	13	NUM
ajst-19200	169	3	]	]	X
ajst-19200	169	4	lin	lin	PROPN
ajst-19200	169	5	t	t	PROPN
ajst-19200	169	6	,	,	PUNCT
ajst-19200	169	7	dollár	dollár	NOUN
ajst-19200	169	8	p	p	NOUN
ajst-19200	169	9	,	,	PUNCT
ajst-19200	169	10	girshick	girshick	ADJ
ajst-19200	169	11	r	r	NOUN
ajst-19200	169	12	,	,	PUNCT
ajst-19200	169	13	et	et	PROPN
ajst-19200	169	14	al	al	PROPN
ajst-19200	169	15	.	.	PROPN
ajst-19200	170	1	feature	feature	PROPN
ajst-19200	170	2	pyramid	pyramid	NOUN
ajst-19200	170	3	networks	network	NOUN
ajst-19200	170	4	for	for	ADP
ajst-19200	170	5	object	object	NOUN
ajst-19200	170	6	detection	detection	NOUN
ajst-19200	170	7	:	:	PUNCT
ajst-19200	170	8	proceedings	proceeding	NOUN
ajst-19200	170	9	of	of	ADP
ajst-19200	170	10	the	the	DET
ajst-19200	170	11	ieee	ieee	NOUN
ajst-19200	170	12	conference	conference	NOUN
ajst-19200	170	13	on	on	ADP
ajst-19200	170	14	computer	computer	NOUN
ajst-19200	170	15	vision	vision	NOUN
ajst-19200	170	16	and	and	CCONJ
ajst-19200	170	17	pattern	pattern	NOUN
ajst-19200	170	18	recognition[c	recognition[c	PROPN
ajst-19200	170	19	]	]	PUNCT
ajst-19200	170	20	,	,	PUNCT
ajst-19200	170	21	2017	2017	NUM
ajst-19200	170	22	.	.	PUNCT
ajst-19200	171	1	[	[	X
ajst-19200	171	2	14	14	NUM
ajst-19200	171	3	]	]	X
ajst-19200	171	4	liu	liu	PROPN
ajst-19200	171	5	s	s	PROPN
ajst-19200	171	6	,	,	PUNCT
ajst-19200	171	7	qi	qi	PROPN
ajst-19200	171	8	l	l	NOUN
ajst-19200	171	9	,	,	PUNCT
ajst-19200	171	10	qin	qin	PROPN
ajst-19200	171	11	h	h	PROPN
ajst-19200	171	12	,	,	PUNCT
ajst-19200	171	13	et	et	PROPN
ajst-19200	171	14	al	al	PROPN
ajst-19200	171	15	.	.	PROPN
ajst-19200	171	16	path	path	PROPN
ajst-19200	171	17	aggregation	aggregation	NOUN
ajst-19200	171	18	network	network	NOUN
ajst-19200	171	19	for	for	ADP
ajst-19200	171	20	instance	instance	NOUN
ajst-19200	171	21	segmentation	segmentation	NOUN
ajst-19200	171	22	:	:	PUNCT
ajst-19200	171	23	proceedings	proceeding	NOUN
ajst-19200	171	24	of	of	ADP
ajst-19200	171	25	the	the	DET
ajst-19200	171	26	ieee	ieee	NOUN
ajst-19200	171	27	conference	conference	NOUN
ajst-19200	171	28	on	on	ADP
ajst-19200	171	29	computer	computer	NOUN
ajst-19200	171	30	vision	vision	NOUN
ajst-19200	171	31	and	and	CCONJ
ajst-19200	171	32	pattern	pattern	NOUN
ajst-19200	171	33	recognition[c	recognition[c	PROPN
ajst-19200	171	34	]	]	PUNCT
ajst-19200	171	35	,	,	PUNCT
ajst-19200	171	36	2018	2018	NUM
ajst-19200	171	37	.	.	PUNCT
ajst-19200	172	1	[	[	X
ajst-19200	172	2	15	15	NUM
ajst-19200	172	3	]	]	X
ajst-19200	172	4	hendrycks	hendryck	NOUN
ajst-19200	172	5	d	d	PROPN
ajst-19200	172	6	,	,	PUNCT
ajst-19200	172	7	gimpel	gimpel	PROPN
ajst-19200	172	8	k.	k.	PROPN
ajst-19200	172	9	gaussian	gaussian	PROPN
ajst-19200	172	10	error	error	NOUN
ajst-19200	172	11	linear	linear	NOUN
ajst-19200	172	12	units	unit	NOUN
ajst-19200	172	13	(	(	PUNCT
ajst-19200	172	14	gelus)[j	gelus)[j	NOUN
ajst-19200	172	15	]	]	PUNCT
ajst-19200	172	16	.	.	PUNCT
ajst-19200	173	1	arxiv	arxiv	PROPN
ajst-19200	173	2	preprint	preprint	PROPN
ajst-19200	173	3	arxiv:1606.08415	arxiv:1606.08415	NOUN
ajst-19200	173	4	,	,	PUNCT
ajst-19200	173	5	2016	2016	NUM
ajst-19200	173	6	.	.	PUNCT
ajst-19200	174	1	[	[	X
ajst-19200	174	2	16	16	NUM
ajst-19200	174	3	]	]	X
ajst-19200	174	4	hu	hu	PROPN
ajst-19200	174	5	j	j	PROPN
ajst-19200	174	6	,	,	PUNCT
ajst-19200	174	7	shen	shen	PROPN
ajst-19200	174	8	l	l	PROPN
ajst-19200	174	9	,	,	PUNCT
ajst-19200	174	10	sun	sun	PROPN
ajst-19200	174	11	g.	g.	PROPN
ajst-19200	174	12	squeeze	squeeze	PROPN
ajst-19200	174	13	-	-	PUNCT
ajst-19200	174	14	and	and	CCONJ
ajst-19200	174	15	-	-	PUNCT
ajst-19200	174	16	excitation	excitation	NOUN
ajst-19200	174	17	networks	network	NOUN
ajst-19200	174	18	:	:	PUNCT
ajst-19200	174	19	proceedings	proceeding	NOUN
ajst-19200	174	20	of	of	ADP
ajst-19200	174	21	the	the	DET
ajst-19200	174	22	ieee	ieee	NOUN
ajst-19200	174	23	conference	conference	NOUN
ajst-19200	174	24	on	on	ADP
ajst-19200	174	25	computer	computer	NOUN
ajst-19200	174	26	vision	vision	NOUN
ajst-19200	174	27	and	and	CCONJ
ajst-19200	174	28	pattern	pattern	NOUN
ajst-19200	174	29	recognition[c	recognition[c	PROPN
ajst-19200	174	30	]	]	PUNCT
ajst-19200	174	31	,	,	PUNCT
ajst-19200	174	32	2018	2018	NUM
ajst-19200	174	33	.	.	PUNCT
ajst-19200	175	1	[	[	X
ajst-19200	175	2	17	17	NUM
ajst-19200	175	3	]	]	X
ajst-19200	175	4	chollet	chollet	PROPN
ajst-19200	175	5	f.	f.	PROPN
ajst-19200	175	6	xception	xception	PROPN
ajst-19200	175	7	:	:	PUNCT
ajst-19200	175	8	deep	deep	ADJ
ajst-19200	175	9	learning	learn	VERB
ajst-19200	175	10	with	with	ADP
ajst-19200	175	11	depthwise	depthwise	NOUN
ajst-19200	175	12	separable	separable	ADJ
ajst-19200	175	13	convolutions	convolution	NOUN
ajst-19200	175	14	:	:	PUNCT
ajst-19200	175	15	proceedings	proceeding	NOUN
ajst-19200	175	16	of	of	ADP
ajst-19200	175	17	the	the	DET
ajst-19200	175	18	ieee	ieee	NOUN
ajst-19200	175	19	conference	conference	NOUN
ajst-19200	175	20	on	on	ADP
ajst-19200	175	21	computer	computer	NOUN
ajst-19200	175	22	vision	vision	NOUN
ajst-19200	175	23	and	and	CCONJ
ajst-19200	175	24	pattern	pattern	NOUN
ajst-19200	175	25	recognition[c	recognition[c	PROPN
ajst-19200	175	26	]	]	PUNCT
ajst-19200	175	27	,	,	PUNCT
ajst-19200	175	28	2017	2017	NUM
ajst-19200	175	29	.	.	PUNCT