id	sid	tid	token	lemma	pos
fcis-29392	1	1	frontiers	frontier	NOUN
fcis-29392	1	2	in	in	ADP
fcis-29392	1	3	computing	computing	NOUN
fcis-29392	1	4	and	and	CCONJ
fcis-29392	1	5	intelligent	intelligent	ADJ
fcis-29392	1	6	systems	system	NOUN
fcis-29392	1	7	issn	issn	VERB
fcis-29392	1	8	:	:	PUNCT
fcis-29392	1	9	2832	2832	NUM
fcis-29392	1	10	-	-	SYM
fcis-29392	1	11	6024	6024	NUM
fcis-29392	1	12	|	|	NOUN
fcis-29392	1	13	vol	vol	NOUN
fcis-29392	1	14	.	.	PROPN
fcis-29392	2	1	11	11	NUM
fcis-29392	2	2	,	,	PUNCT
fcis-29392	2	3	no	no	INTJ
fcis-29392	2	4	.	.	NOUN
fcis-29392	2	5	1	1	NUM
fcis-29392	2	6	,	,	PUNCT
fcis-29392	2	7	2025	2025	NUM
fcis-29392	2	8	97	97	NUM
fcis-29392	2	9	research	research	NOUN
fcis-29392	2	10	on	on	ADP
fcis-29392	2	11	detr‐based	detr‐based	ADJ
fcis-29392	2	12	weed	weed	NOUN
fcis-29392	2	13	detection	detection	NOUN
fcis-29392	2	14	algorithm	algorithm	NOUN
fcis-29392	2	15	wenbing	wenbe	VERB
fcis-29392	2	16	liao	liao	PROPN
fcis-29392	2	17	1	1	PROPN
fcis-29392	2	18	and	and	CCONJ
fcis-29392	2	19	wenwen	wenwen	ADJ
fcis-29392	2	20	li	li	PROPN
fcis-29392	2	21	2	2	NUM
fcis-29392	2	22	1	1	NUM
fcis-29392	2	23	school	school	NOUN
fcis-29392	2	24	of	of	ADP
fcis-29392	2	25	information	information	NOUN
fcis-29392	2	26	and	and	CCONJ
fcis-29392	2	27	control	control	PROPN
fcis-29392	2	28	engineering	engineering	PROPN
fcis-29392	2	29	,	,	PUNCT
fcis-29392	2	30	jilin	jilin	PROPN
fcis-29392	2	31	institute	institute	PROPN
fcis-29392	2	32	of	of	ADP
fcis-29392	2	33	chemical	chemical	PROPN
fcis-29392	2	34	technology	technology	PROPN
fcis-29392	2	35	,	,	PUNCT
fcis-29392	2	36	jilin	jilin	PROPN
fcis-29392	2	37	jilin	jilin	PROPN
fcis-29392	2	38	132022	132022	PROPN
fcis-29392	2	39	,	,	PUNCT
fcis-29392	2	40	china	china	PROPN
fcis-29392	2	41	2	2	NUM
fcis-29392	2	42	school	school	NOUN
fcis-29392	2	43	of	of	ADP
fcis-29392	2	44	mechanical	mechanical	ADJ
fcis-29392	2	45	and	and	CCONJ
fcis-29392	2	46	control	control	PROPN
fcis-29392	2	47	engineering	engineering	PROPN
fcis-29392	2	48	,	,	PUNCT
fcis-29392	2	49	baicheng	baicheng	PROPN
fcis-29392	2	50	normal	normal	ADJ
fcis-29392	2	51	college	college	PROPN
fcis-29392	2	52	,	,	PUNCT
fcis-29392	2	53	baicheng	baicheng	PROPN
fcis-29392	2	54	,	,	PUNCT
fcis-29392	2	55	jilin	jilin	PROPN
fcis-29392	2	56	137000	137000	NUM
fcis-29392	2	57	,	,	PUNCT
fcis-29392	2	58	china	china	PROPN
fcis-29392	2	59	abstract	abstract	NOUN
fcis-29392	2	60	:	:	PUNCT
fcis-29392	2	61	to	to	PART
fcis-29392	2	62	address	address	VERB
fcis-29392	2	63	the	the	DET
fcis-29392	2	64	problem	problem	NOUN
fcis-29392	2	65	of	of	ADP
fcis-29392	2	66	complex	complex	ADJ
fcis-29392	2	67	field	field	NOUN
fcis-29392	2	68	conditions	condition	NOUN
fcis-29392	2	69	and	and	CCONJ
fcis-29392	2	70	high	high	ADJ
fcis-29392	2	71	similarity	similarity	NOUN
fcis-29392	2	72	between	between	ADP
fcis-29392	2	73	corn	corn	NOUN
fcis-29392	2	74	seedlings	seedling	NOUN
fcis-29392	2	75	and	and	CCONJ
fcis-29392	2	76	weeds	weed	NOUN
fcis-29392	2	77	,	,	PUNCT
fcis-29392	2	78	this	this	DET
fcis-29392	2	79	study	study	NOUN
fcis-29392	2	80	proposes	propose	VERB
fcis-29392	2	81	an	an	DET
fcis-29392	2	82	improved	improved	ADJ
fcis-29392	2	83	detr	detr	NOUN
fcis-29392	2	84	(	(	PUNCT
fcis-29392	2	85	detection	detection	NOUN
fcis-29392	2	86	transformer	transformer	NOUN
fcis-29392	2	87	)	)	PUNCT
fcis-29392	2	88	model	model	NOUN
fcis-29392	2	89	for	for	ADP
fcis-29392	2	90	weed	weed	NOUN
fcis-29392	2	91	detection	detection	NOUN
fcis-29392	2	92	in	in	ADP
fcis-29392	2	93	corn	corn	NOUN
fcis-29392	2	94	fields	field	NOUN
fcis-29392	2	95	,	,	PUNCT
fcis-29392	2	96	which	which	PRON
fcis-29392	2	97	uses	use	VERB
fcis-29392	2	98	the	the	DET
fcis-29392	2	99	cbam	cbam	NOUN
fcis-29392	2	100	convolutional	convolutional	ADJ
fcis-29392	2	101	attention	attention	NOUN
fcis-29392	2	102	mechanism	mechanism	NOUN
fcis-29392	2	103	in	in	ADP
fcis-29392	2	104	the	the	DET
fcis-29392	2	105	detr	detr	NOUN
fcis-29392	2	106	model	model	NOUN
fcis-29392	2	107	,	,	PUNCT
fcis-29392	2	108	and	and	CCONJ
fcis-29392	2	109	uses	use	VERB
fcis-29392	2	110	a	a	DET
fcis-29392	2	111	focal	focal	ADJ
fcis-29392	2	112	loss	loss	NOUN
fcis-29392	2	113	function	function	NOUN
fcis-29392	2	114	instead	instead	ADV
fcis-29392	2	115	of	of	ADP
fcis-29392	2	116	the	the	DET
fcis-29392	2	117	traditional	traditional	ADJ
fcis-29392	2	118	cross	cross	ADJ
fcis-29392	2	119	-	-	ADJ
fcis-29392	2	120	entropy	entropy	ADJ
fcis-29392	2	121	loss	loss	NOUN
fcis-29392	2	122	function	function	NOUN
fcis-29392	2	123	to	to	PART
fcis-29392	2	124	balance	balance	VERB
fcis-29392	2	125	the	the	DET
fcis-29392	2	126	number	number	NOUN
fcis-29392	2	127	of	of	ADP
fcis-29392	2	128	positive	positive	ADJ
fcis-29392	2	129	and	and	CCONJ
fcis-29392	2	130	negative	negative	ADJ
fcis-29392	2	131	class	class	NOUN
fcis-29392	2	132	samples	sample	NOUN
fcis-29392	2	133	of	of	ADP
fcis-29392	2	134	the	the	DET
fcis-29392	2	135	data	datum	NOUN
fcis-29392	2	136	.	.	PUNCT
fcis-29392	3	1	compared	compare	VERB
fcis-29392	3	2	with	with	ADP
fcis-29392	3	3	the	the	DET
fcis-29392	3	4	original	original	ADJ
fcis-29392	3	5	model	model	NOUN
fcis-29392	3	6	,	,	PUNCT
fcis-29392	3	7	the	the	DET
fcis-29392	3	8	map	map	NOUN
fcis-29392	3	9	(	(	PUNCT
fcis-29392	3	10	mean	mean	VERB
fcis-29392	3	11	average	average	ADJ
fcis-29392	3	12	precision	precision	NOUN
fcis-29392	3	13	)	)	PUNCT
fcis-29392	3	14	of	of	ADP
fcis-29392	3	15	the	the	DET
fcis-29392	3	16	improved	improved	ADJ
fcis-29392	3	17	model	model	NOUN
fcis-29392	3	18	was	be	AUX
fcis-29392	3	19	increased	increase	VERB
fcis-29392	3	20	by	by	ADP
fcis-29392	3	21	1.12	1.12	NUM
fcis-29392	3	22	%	%	NOUN
fcis-29392	3	23	to	to	ADP
fcis-29392	3	24	91.56	91.56	NUM
fcis-29392	3	25	%	%	NOUN
fcis-29392	3	26	.	.	PUNCT
fcis-29392	4	1	keywords	keyword	NOUN
fcis-29392	4	2	:	:	PUNCT
fcis-29392	4	3	transformer	transformer	NOUN
fcis-29392	4	4	;	;	PUNCT
fcis-29392	4	5	cbam	cbam	NOUN
fcis-29392	4	6	;	;	PUNCT
fcis-29392	4	7	focal	focal	ADJ
fcis-29392	4	8	point	point	NOUN
fcis-29392	4	9	loss	loss	NOUN
fcis-29392	4	10	;	;	PUNCT
fcis-29392	4	11	weed	weed	VERB
fcis-29392	4	12	detection	detection	NOUN
fcis-29392	4	13	.	.	PUNCT
fcis-29392	5	1	1	1	X
fcis-29392	5	2	.	.	X
fcis-29392	5	3	introduction	introduction	NOUN
fcis-29392	5	4	weed	weed	NOUN
fcis-29392	5	5	infestation	infestation	NOUN
fcis-29392	5	6	is	be	AUX
fcis-29392	5	7	one	one	NUM
fcis-29392	5	8	of	of	ADP
fcis-29392	5	9	the	the	DET
fcis-29392	5	10	three	three	NUM
fcis-29392	5	11	major	major	ADJ
fcis-29392	5	12	biological	biological	ADJ
fcis-29392	5	13	disasters	disaster	NOUN
fcis-29392	5	14	in	in	ADP
fcis-29392	5	15	agricultural	agricultural	ADJ
fcis-29392	5	16	production	production	NOUN
fcis-29392	5	17	,	,	PUNCT
fcis-29392	5	18	which	which	PRON
fcis-29392	5	19	leads	lead	VERB
fcis-29392	5	20	to	to	ADP
fcis-29392	5	21	the	the	DET
fcis-29392	5	22	loss	loss	NOUN
fcis-29392	5	23	of	of	ADP
fcis-29392	5	24	world	world	NOUN
fcis-29392	5	25	food	food	NOUN
fcis-29392	5	26	production	production	NOUN
fcis-29392	5	27	equivalent	equivalent	ADJ
fcis-29392	5	28	to	to	ADP
fcis-29392	5	29	about	about	ADV
fcis-29392	5	30	1	1	NUM
fcis-29392	5	31	billion	billion	NUM
fcis-29392	5	32	people	people	NOUN
fcis-29392	5	33	's	's	PART
fcis-29392	5	34	rations	ration	NOUN
fcis-29392	5	35	each	each	DET
fcis-29392	5	36	year	year	NOUN
fcis-29392	5	37	and	and	CCONJ
fcis-29392	5	38	causes	cause	VERB
fcis-29392	5	39	direct	direct	ADJ
fcis-29392	5	40	economic	economic	ADJ
fcis-29392	5	41	losses	loss	NOUN
fcis-29392	5	42	of	of	ADP
fcis-29392	5	43	about	about	ADV
fcis-29392	5	44	120	120	NUM
fcis-29392	5	45	billion	billion	NUM
fcis-29392	5	46	dollars	dollar	NOUN
fcis-29392	5	47	[	[	X
fcis-29392	5	48	1	1	NUM
fcis-29392	5	49	]	]	PUNCT
fcis-29392	5	50	.	.	PUNCT
fcis-29392	6	1	china	china	PROPN
fcis-29392	6	2	is	be	AUX
fcis-29392	6	3	also	also	ADV
fcis-29392	6	4	one	one	NUM
fcis-29392	6	5	of	of	ADP
fcis-29392	6	6	the	the	DET
fcis-29392	6	7	country	country	NOUN
fcis-29392	6	8	’s	’s	PART
fcis-29392	6	9	most	most	ADV
fcis-29392	6	10	seriously	seriously	ADV
fcis-29392	6	11	afflicted	afflict	VERB
fcis-29392	6	12	by	by	ADP
fcis-29392	6	13	the	the	DET
fcis-29392	6	14	weed	weed	NOUN
fcis-29392	6	15	problem	problem	NOUN
fcis-29392	6	16	,	,	PUNCT
fcis-29392	6	17	and	and	CCONJ
fcis-29392	6	18	the	the	DET
fcis-29392	6	19	invasion	invasion	NOUN
fcis-29392	6	20	of	of	ADP
fcis-29392	6	21	weeds	weed	NOUN
fcis-29392	6	22	will	will	AUX
fcis-29392	6	23	make	make	VERB
fcis-29392	6	24	the	the	DET
fcis-29392	6	25	crop	crop	NOUN
fcis-29392	6	26	yield	yield	NOUN
fcis-29392	6	27	decline	decline	NOUN
fcis-29392	6	28	,	,	PUNCT
fcis-29392	6	29	while	while	SCONJ
fcis-29392	6	30	the	the	DET
fcis-29392	6	31	traditional	traditional	ADJ
fcis-29392	6	32	weed	weed	NOUN
fcis-29392	6	33	control	control	NOUN
fcis-29392	6	34	methods	method	NOUN
fcis-29392	6	35	are	be	AUX
fcis-29392	6	36	no	no	ADV
fcis-29392	6	37	longer	long	ADV
fcis-29392	6	38	suitable	suitable	ADJ
fcis-29392	6	39	for	for	ADP
fcis-29392	6	40	the	the	DET
fcis-29392	6	41	current	current	ADJ
fcis-29392	6	42	environment	environment	NOUN
fcis-29392	7	1	[	[	X
fcis-29392	7	2	2	2	NUM
fcis-29392	7	3	]	]	PUNCT
fcis-29392	7	4	.	.	PUNCT
fcis-29392	8	1	with	with	ADP
fcis-29392	8	2	the	the	DET
fcis-29392	8	3	rapid	rapid	ADJ
fcis-29392	8	4	development	development	NOUN
fcis-29392	8	5	of	of	ADP
fcis-29392	8	6	computer	computer	NOUN
fcis-29392	8	7	vision	vision	NOUN
fcis-29392	8	8	and	and	CCONJ
fcis-29392	8	9	artificial	artificial	ADJ
fcis-29392	8	10	intelligence	intelligence	NOUN
fcis-29392	8	11	technology	technology	NOUN
fcis-29392	8	12	,	,	PUNCT
fcis-29392	8	13	weed	weed	VERB
fcis-29392	8	14	detection	detection	NOUN
fcis-29392	8	15	methods	method	NOUN
fcis-29392	8	16	based	base	VERB
fcis-29392	8	17	on	on	ADP
fcis-29392	8	18	image	image	NOUN
fcis-29392	8	19	processing	processing	NOUN
fcis-29392	8	20	and	and	CCONJ
fcis-29392	8	21	deep	deep	ADJ
fcis-29392	8	22	learning	learning	NOUN
fcis-29392	8	23	have	have	AUX
fcis-29392	8	24	gradually	gradually	ADV
fcis-29392	8	25	become	become	VERB
fcis-29392	8	26	a	a	DET
fcis-29392	8	27	research	research	NOUN
fcis-29392	8	28	hotspot	hotspot	NOUN
fcis-29392	8	29	.	.	PUNCT
fcis-29392	9	1	by	by	ADP
fcis-29392	9	2	using	use	VERB
fcis-29392	9	3	advanced	advanced	ADJ
fcis-29392	9	4	image	image	NOUN
fcis-29392	9	5	processing	processing	NOUN
fcis-29392	9	6	algorithms	algorithm	NOUN
fcis-29392	9	7	and	and	CCONJ
fcis-29392	9	8	deep	deep	ADJ
fcis-29392	9	9	learning	learning	NOUN
fcis-29392	9	10	models	model	NOUN
fcis-29392	9	11	,	,	PUNCT
fcis-29392	9	12	weeds	weed	NOUN
fcis-29392	9	13	in	in	ADP
fcis-29392	9	14	agricultural	agricultural	ADJ
fcis-29392	9	15	fields	field	NOUN
fcis-29392	9	16	can	can	AUX
fcis-29392	9	17	be	be	AUX
fcis-29392	9	18	identified	identify	VERB
fcis-29392	9	19	and	and	CCONJ
fcis-29392	9	20	classified	classify	VERB
fcis-29392	9	21	,	,	PUNCT
fcis-29392	9	22	laying	lay	VERB
fcis-29392	9	23	the	the	DET
fcis-29392	9	24	algorithmic	algorithmic	ADJ
fcis-29392	9	25	foundation	foundation	NOUN
fcis-29392	9	26	for	for	ADP
fcis-29392	9	27	agricultural	agricultural	ADJ
fcis-29392	9	28	weeding	weed	VERB
fcis-29392	9	29	equipment	equipment	NOUN
fcis-29392	9	30	to	to	PART
fcis-29392	9	31	realize	realize	VERB
fcis-29392	9	32	intelligent	intelligent	ADJ
fcis-29392	9	33	and	and	CCONJ
fcis-29392	9	34	automated	automate	VERB
fcis-29392	9	35	,	,	PUNCT
fcis-29392	9	36	and	and	CCONJ
fcis-29392	9	37	realizing	realize	VERB
fcis-29392	9	38	intelligent	intelligent	ADJ
fcis-29392	9	39	agricultural	agricultural	ADJ
fcis-29392	9	40	management	management	NOUN
fcis-29392	9	41	[	[	X
fcis-29392	9	42	3,4	3,4	NUM
fcis-29392	9	43	]	]	PUNCT
fcis-29392	9	44	.	.	PUNCT
fcis-29392	10	1	in	in	ADP
fcis-29392	10	2	the	the	DET
fcis-29392	10	3	early	early	ADJ
fcis-29392	10	4	days	day	NOUN
fcis-29392	10	5	,	,	PUNCT
fcis-29392	10	6	due	due	ADP
fcis-29392	10	7	to	to	ADP
fcis-29392	10	8	the	the	DET
fcis-29392	10	9	influence	influence	NOUN
fcis-29392	10	10	of	of	ADP
fcis-29392	10	11	computer	computer	NOUN
fcis-29392	10	12	arithmetic	arithmetic	ADJ
fcis-29392	10	13	power	power	NOUN
fcis-29392	10	14	,	,	PUNCT
fcis-29392	10	15	deep	deep	ADJ
fcis-29392	10	16	learning	learning	NOUN
fcis-29392	10	17	methods	method	NOUN
fcis-29392	10	18	were	be	AUX
fcis-29392	10	19	not	not	PART
fcis-29392	10	20	popularized	popularize	VERB
fcis-29392	10	21	,	,	PUNCT
fcis-29392	10	22	and	and	CCONJ
fcis-29392	10	23	machine	machine	NOUN
fcis-29392	10	24	vision	vision	NOUN
fcis-29392	10	25	-	-	PUNCT
fcis-29392	10	26	based	base	VERB
fcis-29392	10	27	recognition	recognition	NOUN
fcis-29392	10	28	methods	method	NOUN
fcis-29392	10	29	were	be	AUX
fcis-29392	10	30	widely	widely	ADV
fcis-29392	10	31	used	use	VERB
fcis-29392	10	32	in	in	ADP
fcis-29392	10	33	crop	crop	NOUN
fcis-29392	10	34	and	and	CCONJ
fcis-29392	10	35	weed	weed	NOUN
fcis-29392	10	36	recognition	recognition	NOUN
fcis-29392	10	37	.	.	PUNCT
fcis-29392	11	1	mathanker	mathanker	NOUN
fcis-29392	11	2	et	et	NOUN
fcis-29392	11	3	al[5	al[5	ADV
fcis-29392	11	4	]	]	PUNCT
fcis-29392	11	5	extracted	extract	VERB
fcis-29392	11	6	multiple	multiple	ADJ
fcis-29392	11	7	features	feature	NOUN
fcis-29392	11	8	including	include	VERB
fcis-29392	11	9	color	color	NOUN
fcis-29392	11	10	and	and	CCONJ
fcis-29392	11	11	texture	texture	NOUN
fcis-29392	11	12	in	in	ADP
fcis-29392	11	13	oilseed	oilseed	NOUN
fcis-29392	11	14	rape	rape	NOUN
fcis-29392	11	15	and	and	CCONJ
fcis-29392	11	16	wheat	wheat	NOUN
fcis-29392	11	17	crops	crop	NOUN
fcis-29392	11	18	and	and	CCONJ
fcis-29392	11	19	used	use	VERB
fcis-29392	11	20	adaboost	adaboost	ADV
fcis-29392	11	21	and	and	CCONJ
fcis-29392	11	22	support	support	VERB
fcis-29392	11	23	vector	vector	NOUN
fcis-29392	11	24	machines	machine	NOUN
fcis-29392	11	25	to	to	PART
fcis-29392	11	26	perform	perform	VERB
fcis-29392	11	27	automatic	automatic	ADJ
fcis-29392	11	28	weed	weed	NOUN
fcis-29392	11	29	recognition	recognition	NOUN
fcis-29392	11	30	.	.	PUNCT
fcis-29392	12	1	tian	tian	PROPN
fcis-29392	12	2	ronghui	ronghui	PROPN
fcis-29392	12	3	et	et	PROPN
fcis-29392	12	4	al	al	PROPN
fcis-29392	13	1	[	[	X
fcis-29392	13	2	6	6	NUM
fcis-29392	13	3	]	]	PUNCT
fcis-29392	13	4	achieved	achieve	VERB
fcis-29392	13	5	accurate	accurate	ADJ
fcis-29392	13	6	recognition	recognition	NOUN
fcis-29392	13	7	of	of	ADP
fcis-29392	13	8	overlapping	overlap	VERB
fcis-29392	13	9	leaves	leave	NOUN
fcis-29392	13	10	and	and	CCONJ
fcis-29392	13	11	weeds	weed	NOUN
fcis-29392	13	12	based	base	VERB
fcis-29392	13	13	on	on	ADP
fcis-29392	13	14	image	image	NOUN
fcis-29392	13	15	chunking	chunk	VERB
fcis-29392	13	16	and	and	CCONJ
fcis-29392	13	17	reconstruction	reconstruction	NOUN
fcis-29392	13	18	combined	combine	VERB
fcis-29392	13	19	with	with	ADP
fcis-29392	13	20	support	support	NOUN
fcis-29392	13	21	vector	vector	NOUN
fcis-29392	13	22	machine	machine	NOUN
fcis-29392	13	23	.	.	PUNCT
fcis-29392	14	1	since	since	SCONJ
fcis-29392	14	2	traditional	traditional	ADJ
fcis-29392	14	3	image	image	NOUN
fcis-29392	14	4	algorithms	algorithm	NOUN
fcis-29392	14	5	mainly	mainly	ADV
fcis-29392	14	6	rely	rely	VERB
fcis-29392	14	7	on	on	ADP
fcis-29392	14	8	manually	manually	ADV
fcis-29392	14	9	designed	design	VERB
fcis-29392	14	10	feature	feature	NOUN
fcis-29392	14	11	extractors	extractor	NOUN
fcis-29392	14	12	and	and	CCONJ
fcis-29392	14	13	lack	lack	VERB
fcis-29392	14	14	adaptive	adaptive	ADJ
fcis-29392	14	15	learning	learning	NOUN
fcis-29392	14	16	ability	ability	NOUN
fcis-29392	14	17	,	,	PUNCT
fcis-29392	14	18	the	the	DET
fcis-29392	14	19	generalization	generalization	NOUN
fcis-29392	14	20	ability	ability	NOUN
fcis-29392	14	21	and	and	CCONJ
fcis-29392	14	22	robustness	robustness	NOUN
fcis-29392	14	23	are	be	AUX
fcis-29392	14	24	relatively	relatively	ADV
fcis-29392	14	25	poor	poor	ADJ
fcis-29392	14	26	,	,	PUNCT
fcis-29392	14	27	while	while	SCONJ
fcis-29392	14	28	with	with	ADP
fcis-29392	14	29	the	the	DET
fcis-29392	14	30	improvement	improvement	NOUN
fcis-29392	14	31	of	of	ADP
fcis-29392	14	32	computational	computational	ADJ
fcis-29392	14	33	resources	resource	NOUN
fcis-29392	14	34	and	and	CCONJ
fcis-29392	14	35	the	the	DET
fcis-29392	14	36	availability	availability	NOUN
fcis-29392	14	37	of	of	ADP
fcis-29392	14	38	large	large	ADJ
fcis-29392	14	39	amounts	amount	NOUN
fcis-29392	14	40	of	of	ADP
fcis-29392	14	41	data	datum	NOUN
fcis-29392	14	42	,	,	PUNCT
fcis-29392	14	43	deep	deep	ADJ
fcis-29392	14	44	learning	learning	NOUN
fcis-29392	14	45	has	have	AUX
fcis-29392	14	46	attracted	attract	VERB
fcis-29392	14	47	extensive	extensive	ADJ
fcis-29392	14	48	attention	attention	NOUN
fcis-29392	14	49	from	from	ADP
fcis-29392	14	50	researchers	researcher	NOUN
fcis-29392	14	51	,	,	PUNCT
fcis-29392	14	52	and	and	CCONJ
fcis-29392	14	53	detection	detection	NOUN
fcis-29392	14	54	methods	method	NOUN
fcis-29392	14	55	based	base	VERB
fcis-29392	14	56	on	on	ADP
fcis-29392	14	57	convolutional	convolutional	ADJ
fcis-29392	14	58	neural	neural	ADJ
fcis-29392	14	59	networks	network	NOUN
fcis-29392	14	60	have	have	AUX
fcis-29392	14	61	made	make	VERB
fcis-29392	14	62	significant	significant	ADJ
fcis-29392	14	63	progress	progress	NOUN
fcis-29392	14	64	.	.	PUNCT
fcis-29392	15	1	zhong	zhong	PROPN
fcis-29392	15	2	bin	bin	PROPN
fcis-29392	15	3	et	et	PROPN
fcis-29392	15	4	al	al	PROPN
fcis-29392	16	1	[	[	X
fcis-29392	16	2	7	7	NUM
fcis-29392	16	3	]	]	PUNCT
fcis-29392	16	4	proposed	propose	VERB
fcis-29392	16	5	a	a	DET
fcis-29392	16	6	pasture	pasture	NOUN
fcis-29392	16	7	weed	weed	NOUN
fcis-29392	16	8	detection	detection	NOUN
fcis-29392	16	9	based	base	VERB
fcis-29392	16	10	on	on	ADP
fcis-29392	16	11	an	an	DET
fcis-29392	16	12	improved	improved	ADJ
fcis-29392	16	13	dino	dino	NOUN
fcis-29392	16	14	detection	detection	NOUN
fcis-29392	16	15	network	network	NOUN
fcis-29392	16	16	,	,	PUNCT
fcis-29392	16	17	which	which	PRON
fcis-29392	16	18	enhanced	enhance	VERB
fcis-29392	16	19	the	the	DET
fcis-29392	16	20	extraction	extraction	NOUN
fcis-29392	16	21	of	of	ADP
fcis-29392	16	22	features	feature	NOUN
fcis-29392	16	23	by	by	ADP
fcis-29392	16	24	introducing	introduce	VERB
fcis-29392	16	25	an	an	DET
fcis-29392	16	26	attention	attention	NOUN
fcis-29392	16	27	mechanism	mechanism	NOUN
fcis-29392	16	28	to	to	PART
fcis-29392	16	29	achieve	achieve	VERB
fcis-29392	16	30	better	well	ADJ
fcis-29392	16	31	recognition	recognition	NOUN
fcis-29392	16	32	accuracy	accuracy	NOUN
fcis-29392	16	33	.	.	PUNCT
fcis-29392	17	1	jin	jin	NOUN
fcis-29392	17	2	x	x	PUNCT
fcis-29392	17	3	et	et	PROPN
fcis-29392	17	4	al	al	PROPN
fcis-29392	18	1	[	[	X
fcis-29392	18	2	8	8	NUM
fcis-29392	18	3	]	]	PUNCT
fcis-29392	18	4	used	use	VERB
fcis-29392	18	5	three	three	NUM
fcis-29392	18	6	convolutional	convolutional	ADJ
fcis-29392	18	7	neural	neural	ADJ
fcis-29392	18	8	networks	network	NOUN
fcis-29392	18	9	(	(	PUNCT
fcis-29392	18	10	densenet	densenet	NOUN
fcis-29392	18	11	,	,	PUNCT
fcis-29392	18	12	efficientnet	efficientnet	NOUN
fcis-29392	18	13	,	,	PUNCT
fcis-29392	18	14	resnet	resnet	NOUN
fcis-29392	18	15	)	)	PUNCT
fcis-29392	18	16	to	to	PART
fcis-29392	18	17	detect	detect	VERB
fcis-29392	18	18	weeds	weed	NOUN
fcis-29392	18	19	in	in	ADP
fcis-29392	18	20	individuals	individual	NOUN
fcis-29392	18	21	growing	grow	VERB
fcis-29392	18	22	in	in	ADP
fcis-29392	18	23	bermudagrass	bermudagrass	NOUN
fcis-29392	18	24	stratum	stratum	NOUN
fcis-29392	18	25	weed	weed	VERB
fcis-29392	18	26	species	specie	NOUN
fcis-29392	18	27	as	as	ADV
fcis-29392	18	28	well	well	ADV
fcis-29392	18	29	as	as	ADP
fcis-29392	18	30	herbicide	herbicide	NOUN
fcis-29392	18	31	susceptible	susceptible	ADJ
fcis-29392	18	32	weeds	weed	NOUN
fcis-29392	18	33	.	.	PUNCT
fcis-29392	19	1	moazzam	moazzam	NOUN
fcis-29392	19	2	s	s	VERB
fcis-29392	19	3	i	i	INTJ
fcis-29392	19	4	et	et	NOUN
fcis-29392	19	5	al	al	PROPN
fcis-29392	20	1	[	[	X
fcis-29392	20	2	9	9	NUM
fcis-29392	20	3	]	]	PUNCT
fcis-29392	20	4	used	use	VERB
fcis-29392	20	5	a	a	DET
fcis-29392	20	6	new	new	ADJ
fcis-29392	20	7	two	two	NUM
fcis-29392	20	8	-	-	PUNCT
fcis-29392	20	9	stage	stage	NOUN
fcis-29392	20	10	approach	approach	NOUN
fcis-29392	20	11	to	to	PART
fcis-29392	20	12	improve	improve	VERB
fcis-29392	20	13	the	the	DET
fcis-29392	20	14	classification	classification	NOUN
fcis-29392	20	15	accuracy	accuracy	NOUN
fcis-29392	20	16	of	of	ADP
fcis-29392	20	17	crop	crop	NOUN
fcis-29392	20	18	weeds	weed	NOUN
fcis-29392	20	19	.	.	PUNCT
fcis-29392	21	1	in	in	ADP
fcis-29392	21	2	the	the	DET
fcis-29392	21	3	first	first	ADJ
fcis-29392	21	4	stage	stage	NOUN
fcis-29392	21	5	,	,	PUNCT
fcis-29392	21	6	a	a	DET
fcis-29392	21	7	binary	binary	ADJ
fcis-29392	21	8	pixel	pixel	ADJ
fcis-29392	21	9	-	-	PUNCT
fcis-29392	21	10	level	level	NOUN
fcis-29392	21	11	classifier	classifier	NOUN
fcis-29392	21	12	was	be	AUX
fcis-29392	21	13	developed	develop	VERB
fcis-29392	21	14	to	to	PART
fcis-29392	21	15	segment	segment	VERB
fcis-29392	21	16	the	the	DET
fcis-29392	21	17	background	background	NOUN
fcis-29392	21	18	and	and	CCONJ
fcis-29392	21	19	vegetation	vegetation	NOUN
fcis-29392	21	20	;	;	PUNCT
fcis-29392	21	21	in	in	ADP
fcis-29392	21	22	the	the	DET
fcis-29392	21	23	second	second	ADJ
fcis-29392	21	24	stage	stage	NOUN
fcis-29392	21	25	,	,	PUNCT
fcis-29392	21	26	a	a	DET
fcis-29392	21	27	three	three	NUM
fcis-29392	21	28	-	-	PUNCT
fcis-29392	21	29	class	class	NOUN
fcis-29392	21	30	pixel	pixel	ADJ
fcis-29392	21	31	-	-	PUNCT
fcis-29392	21	32	level	level	NOUN
fcis-29392	21	33	classifier	classifier	NOUN
fcis-29392	21	34	was	be	AUX
fcis-29392	21	35	devised	devise	VERB
fcis-29392	21	36	to	to	PART
fcis-29392	21	37	classify	classify	VERB
fcis-29392	21	38	the	the	DET
fcis-29392	21	39	background	background	NOUN
fcis-29392	21	40	,	,	PUNCT
fcis-29392	21	41	weeds	weed	NOUN
fcis-29392	21	42	,	,	PUNCT
fcis-29392	21	43	and	and	CCONJ
fcis-29392	21	44	tobacco	tobacco	NOUN
fcis-29392	21	45	.	.	PUNCT
fcis-29392	22	1	jinyang	jinyang	PROPN
fcis-29392	22	2	le	le	X
fcis-29392	22	3	et	et	PROPN
fcis-29392	22	4	al	al	PROPN
fcis-29392	23	1	[	[	X
fcis-29392	23	2	10	10	NUM
fcis-29392	23	3	]	]	PUNCT
fcis-29392	23	4	proposed	propose	VERB
fcis-29392	23	5	a	a	DET
fcis-29392	23	6	weed	weed	NOUN
fcis-29392	23	7	detection	detection	NOUN
fcis-29392	23	8	model	model	NOUN
fcis-29392	23	9	yolov7	yolov7	NOUN
fcis-29392	23	10	-	-	PUNCT
fcis-29392	23	11	fweed	fweed	NOUN
fcis-29392	23	12	based	base	VERB
fcis-29392	23	13	on	on	ADP
fcis-29392	23	14	the	the	DET
fcis-29392	23	15	improved	improved	ADJ
fcis-29392	23	16	yolov7	yolov7	NOUN
fcis-29392	23	17	,	,	PUNCT
fcis-29392	23	18	which	which	PRON
fcis-29392	23	19	used	use	VERB
fcis-29392	23	20	f	f	X
fcis-29392	23	21	-	-	PUNCT
fcis-29392	23	22	relu	relu	NOUN
fcis-29392	23	23	as	as	ADP
fcis-29392	23	24	the	the	DET
fcis-29392	23	25	activation	activation	NOUN
fcis-29392	23	26	function	function	NOUN
fcis-29392	23	27	of	of	ADP
fcis-29392	23	28	the	the	DET
fcis-29392	23	29	convolutional	convolutional	ADJ
fcis-29392	23	30	module	module	NOUN
fcis-29392	23	31	and	and	CCONJ
fcis-29392	23	32	added	add	VERB
fcis-29392	23	33	the	the	DET
fcis-29392	23	34	maxpool	maxpool	ADJ
fcis-29392	23	35	multihead	multihead	NOUN
fcis-29392	23	36	self	self	NOUN
fcis-29392	23	37	-	-	PUNCT
fcis-29392	23	38	attention	attention	NOUN
fcis-29392	23	39	(	(	PUNCT
fcis-29392	23	40	m	m	NOUN
fcis-29392	23	41	-	-	PUNCT
fcis-29392	23	42	mhsa	mhsa	VERB
fcis-29392	23	43	)	)	PUNCT
fcis-29392	23	44	module	module	NOUN
fcis-29392	23	45	in	in	ADP
fcis-29392	23	46	order	order	NOUN
fcis-29392	23	47	to	to	PART
fcis-29392	23	48	improve	improve	VERB
fcis-29392	23	49	the	the	DET
fcis-29392	23	50	accuracy	accuracy	NOUN
fcis-29392	23	51	of	of	ADP
fcis-29392	23	52	weed	weed	NOUN
fcis-29392	23	53	recognition	recognition	NOUN
fcis-29392	23	54	.	.	PUNCT
fcis-29392	24	1	zhang	zhang	PROPN
fcis-29392	24	2	packing	pack	VERB
fcis-29392	24	3	[	[	X
fcis-29392	24	4	11	11	NUM
fcis-29392	24	5	]	]	PUNCT
fcis-29392	24	6	implemented	implement	VERB
fcis-29392	24	7	weed	weed	NOUN
fcis-29392	24	8	detection	detection	NOUN
fcis-29392	24	9	using	use	VERB
fcis-29392	24	10	yolov5s.ong	yolov5s.ong	PROPN
fcis-29392	24	11	p	p	PROPN
fcis-29392	24	12	et	et	PROPN
fcis-29392	24	13	al	al	PROPN
fcis-29392	25	1	[	[	X
fcis-29392	25	2	12	12	NUM
fcis-29392	25	3	]	]	PUNCT
fcis-29392	25	4	used	use	VERB
fcis-29392	25	5	convolutional	convolutional	ADJ
fcis-29392	25	6	neural	neural	ADJ
fcis-29392	25	7	network	network	NOUN
fcis-29392	25	8	(	(	PUNCT
fcis-29392	25	9	cnn	cnn	PROPN
fcis-29392	25	10	)	)	PUNCT
fcis-29392	25	11	to	to	PART
fcis-29392	25	12	detect	detect	VERB
fcis-29392	25	13	weeds	weed	NOUN
fcis-29392	25	14	in	in	ADP
fcis-29392	25	15	cabbage	cabbage	NOUN
fcis-29392	25	16	fields	field	NOUN
fcis-29392	25	17	using	use	VERB
fcis-29392	25	18	images	image	NOUN
fcis-29392	25	19	acquired	acquire	VERB
fcis-29392	25	20	by	by	ADP
fcis-29392	25	21	uavs	uavs	NOUN
fcis-29392	25	22	and	and	CCONJ
fcis-29392	25	23	compared	compare	VERB
fcis-29392	25	24	the	the	DET
fcis-29392	25	25	performance	performance	NOUN
fcis-29392	25	26	of	of	ADP
fcis-29392	25	27	random	random	ADJ
fcis-29392	25	28	forest	forest	NOUN
fcis-29392	25	29	(	(	PUNCT
fcis-29392	25	30	rf	rf	NOUN
fcis-29392	25	31	)	)	PUNCT
fcis-29392	25	32	and	and	CCONJ
fcis-29392	25	33	cnn	cnn	PROPN
fcis-29392	25	34	and	and	CCONJ
fcis-29392	25	35	concluded	conclude	VERB
fcis-29392	25	36	that	that	SCONJ
fcis-29392	25	37	the	the	DET
fcis-29392	25	38	overall	overall	ADJ
fcis-29392	25	39	accuracy	accuracy	NOUN
fcis-29392	25	40	of	of	ADP
fcis-29392	25	41	cnn	cnn	PROPN
fcis-29392	25	42	is	be	AUX
fcis-29392	25	43	higher	high	ADJ
fcis-29392	25	44	than	than	ADP
fcis-29392	25	45	that	that	PRON
fcis-29392	25	46	of	of	ADP
fcis-29392	25	47	random	random	ADJ
fcis-29392	25	48	forest	forest	NOUN
fcis-29392	25	49	.	.	PUNCT
fcis-29392	26	1	khan	khan	PROPN
fcis-29392	26	2	s	s	PROPN
fcis-29392	26	3	d	d	X
fcis-29392	26	4	et	et	NOUN
fcis-29392	26	5	al	al	PROPN
fcis-29392	27	1	[	[	X
fcis-29392	27	2	13	13	NUM
fcis-29392	27	3	]	]	PUNCT
fcis-29392	27	4	based	base	VERB
fcis-29392	27	5	on	on	ADP
fcis-29392	27	6	encoderdecoder	encoderdecoder	ADJ
fcis-29392	27	7	architecture	architecture	NOUN
fcis-29392	27	8	designed	design	VERB
fcis-29392	27	9	a	a	DET
fcis-29392	27	10	new	new	ADJ
fcis-29392	27	11	deep	deep	ADJ
fcis-29392	27	12	learning	learning	NOUN
fcis-29392	27	13	architecture	architecture	NOUN
fcis-29392	27	14	was	be	AUX
fcis-29392	27	15	designed	design	VERB
fcis-29392	27	16	,	,	PUNCT
fcis-29392	27	17	where	where	SCONJ
fcis-29392	27	18	the	the	DET
fcis-29392	27	19	encoder	encoder	NOUN
fcis-29392	27	20	part	part	NOUN
fcis-29392	27	21	effectively	effectively	ADV
fcis-29392	27	22	combines	combine	VERB
fcis-29392	27	23	a	a	DET
fcis-29392	27	24	dense	dense	ADJ
fcis-29392	27	25	absorbing	absorb	VERB
fcis-29392	27	26	network	network	NOUN
fcis-29392	27	27	and	and	CCONJ
fcis-29392	27	28	a	a	DET
fcis-29392	27	29	spatial	spatial	ADJ
fcis-29392	27	30	pyramid	pyramid	NOUN
fcis-29392	27	31	pooling	pool	VERB
fcis-29392	27	32	module	module	NOUN
fcis-29392	27	33	for	for	ADP
fcis-29392	27	34	multi	multi	ADJ
fcis-29392	27	35	-	-	ADJ
fcis-29392	27	36	scale	scale	ADJ
fcis-29392	27	37	feature	feature	NOUN
fcis-29392	27	38	extraction	extraction	NOUN
fcis-29392	27	39	;	;	PUNCT
fcis-29392	27	40	the	the	DET
fcis-29392	27	41	decoder	decoder	NOUN
fcis-29392	27	42	part	part	NOUN
fcis-29392	27	43	contains	contain	VERB
fcis-29392	27	44	a	a	DET
fcis-29392	27	45	deconvolutional	deconvolutional	ADJ
fcis-29392	27	46	layer	layer	NOUN
fcis-29392	27	47	and	and	CCONJ
fcis-29392	27	48	an	an	DET
fcis-29392	27	49	attention	attention	NOUN
fcis-29392	27	50	unit	unit	NOUN
fcis-29392	27	51	,	,	PUNCT
fcis-29392	27	52	which	which	PRON
fcis-29392	27	53	helps	help	VERB
fcis-29392	27	54	to	to	PART
fcis-29392	27	55	recover	recover	VERB
fcis-29392	27	56	the	the	DET
fcis-29392	27	57	spatial	spatial	ADJ
fcis-29392	27	58	information	information	NOUN
fcis-29392	27	59	and	and	CCONJ
fcis-29392	27	60	improves	improve	VERB
fcis-29392	27	61	the	the	DET
fcis-29392	27	62	ability	ability	NOUN
fcis-29392	27	63	to	to	PART
fcis-29392	27	64	accurately	accurately	ADV
fcis-29392	27	65	locate	locate	VERB
fcis-29392	27	66	weeds	weed	NOUN
fcis-29392	27	67	and	and	CCONJ
fcis-29392	27	68	crops	crop	NOUN
fcis-29392	27	69	in	in	ADP
fcis-29392	27	70	the	the	DET
fcis-29392	27	71	image	image	NOUN
fcis-29392	27	72	.	.	PUNCT
fcis-29392	28	1	the	the	DET
fcis-29392	28	2	above	above	ADJ
fcis-29392	28	3	detection	detection	NOUN
fcis-29392	28	4	algorithms	algorithm	NOUN
fcis-29392	28	5	have	have	AUX
fcis-29392	28	6	achieved	achieve	VERB
fcis-29392	28	7	better	well	ADJ
fcis-29392	28	8	results	result	NOUN
fcis-29392	28	9	in	in	ADP
fcis-29392	28	10	weed	weed	NOUN
fcis-29392	28	11	detection	detection	NOUN
fcis-29392	28	12	,	,	PUNCT
fcis-29392	28	13	but	but	CCONJ
fcis-29392	28	14	there	there	PRON
fcis-29392	28	15	are	be	VERB
fcis-29392	28	16	still	still	ADV
fcis-29392	28	17	some	some	DET
fcis-29392	28	18	limitations	limitation	NOUN
fcis-29392	28	19	,	,	PUNCT
fcis-29392	28	20	the	the	DET
fcis-29392	28	21	weeds	weed	NOUN
fcis-29392	28	22	in	in	ADP
fcis-29392	28	23	the	the	DET
fcis-29392	28	24	field	field	NOUN
fcis-29392	28	25	are	be	AUX
fcis-29392	28	26	complex	complex	ADJ
fcis-29392	28	27	,	,	PUNCT
fcis-29392	28	28	there	there	PRON
fcis-29392	28	29	is	be	VERB
fcis-29392	28	30	occlusion	occlusion	NOUN
fcis-29392	28	31	,	,	PUNCT
fcis-29392	28	32	blurring	blurring	NOUN
fcis-29392	28	33	and	and	CCONJ
fcis-29392	28	34	other	other	ADJ
fcis-29392	28	35	conditions	condition	NOUN
fcis-29392	28	36	,	,	PUNCT
fcis-29392	28	37	transformer	transformer	NOUN
fcis-29392	28	38	is	be	AUX
fcis-29392	28	39	better	well	ADJ
fcis-29392	28	40	at	at	ADP
fcis-29392	28	41	dealing	deal	VERB
fcis-29392	28	42	with	with	ADP
fcis-29392	28	43	global	global	ADJ
fcis-29392	28	44	information	information	NOUN
fcis-29392	28	45	compared	compare	VERB
fcis-29392	28	46	to	to	ADP
fcis-29392	28	47	convolutional	convolutional	ADJ
fcis-29392	28	48	networks	network	NOUN
fcis-29392	28	49	,	,	PUNCT
fcis-29392	28	50	so	so	SCONJ
fcis-29392	28	51	this	this	DET
fcis-29392	28	52	study	study	NOUN
fcis-29392	28	53	uses	use	VERB
fcis-29392	28	54	the	the	DET
fcis-29392	28	55	transformer	transformer	NOUN
fcis-29392	28	56	-	-	PUNCT
fcis-29392	28	57	based	base	VERB
fcis-29392	28	58	model	model	NOUN
fcis-29392	28	59	for	for	ADP
fcis-29392	28	60	the	the	DET
fcis-29392	28	61	weed	weed	NOUN
fcis-29392	28	62	detection	detection	NOUN
fcis-29392	28	63	task	task	NOUN
fcis-29392	28	64	in	in	ADP
fcis-29392	28	65	order	order	NOUN
fcis-29392	28	66	to	to	PART
fcis-29392	28	67	achieve	achieve	VERB
fcis-29392	28	68	better	well	ADJ
fcis-29392	28	69	results	result	NOUN
fcis-29392	28	70	,	,	PUNCT
fcis-29392	28	71	and	and	CCONJ
fcis-29392	28	72	to	to	PART
fcis-29392	28	73	provide	provide	VERB
fcis-29392	28	74	a	a	DET
fcis-29392	28	75	smart	smart	ADJ
fcis-29392	28	76	weed	weed	NOUN
fcis-29392	28	77	control	control	NOUN
fcis-29392	28	78	equipment	equipment	NOUN
fcis-29392	28	79	with	with	ADP
fcis-29392	28	80	a	a	DET
fcis-29392	28	81	theoretical	theoretical	ADJ
fcis-29392	28	82	basis	basis	NOUN
fcis-29392	28	83	.	.	PUNCT
fcis-29392	29	1	2	2	X
fcis-29392	29	2	.	.	X
fcis-29392	29	3	detr	detr	PROPN
fcis-29392	29	4	network	network	PROPN
fcis-29392	29	5	model	model	PROPN
fcis-29392	29	6	detr	detr	PROPN
fcis-29392	29	7	(	(	PUNCT
fcis-29392	29	8	detection	detection	NOUN
fcis-29392	29	9	transformer	transformer	NOUN
fcis-29392	29	10	)	)	PUNCT
fcis-29392	30	1	[	[	X
fcis-29392	30	2	14	14	NUM
fcis-29392	30	3	]	]	PUNCT
fcis-29392	30	4	is	be	AUX
fcis-29392	30	5	an	an	DET
fcis-29392	30	6	end	end	NOUN
fcis-29392	30	7	-	-	PUNCT
fcis-29392	30	8	to	to	ADP
fcis-29392	30	9	-	-	PUNCT
fcis-29392	30	10	end	end	NOUN
fcis-29392	30	11	target	target	NOUN
fcis-29392	30	12	detection	detection	NOUN
fcis-29392	30	13	network	network	NOUN
fcis-29392	30	14	based	base	VERB
fcis-29392	30	15	on	on	ADP
fcis-29392	30	16	transformer	transformer	NOUN
fcis-29392	30	17	[	[	X
fcis-29392	30	18	15	15	NUM
fcis-29392	30	19	]	]	PUNCT
fcis-29392	30	20	proposed	propose	VERB
fcis-29392	30	21	by	by	ADP
fcis-29392	30	22	facebook	facebook	PROPN
fcis-29392	30	23	team	team	NOUN
fcis-29392	30	24	.	.	PUNCT
fcis-29392	31	1	traditional	traditional	ADJ
fcis-29392	31	2	detection	detection	NOUN
fcis-29392	31	3	methods	method	NOUN
fcis-29392	31	4	typically	typically	ADV
fcis-29392	31	5	use	use	VERB
fcis-29392	31	6	a	a	DET
fcis-29392	31	7	two	two	NUM
fcis-29392	31	8	-	-	PUNCT
fcis-29392	31	9	stage	stage	NOUN
fcis-29392	31	10	process	process	NOUN
fcis-29392	31	11	,	,	PUNCT
fcis-29392	31	12	where	where	SCONJ
fcis-29392	31	13	candidate	candidate	NOUN
fcis-29392	31	14	frames	frame	NOUN
fcis-29392	31	15	are	be	AUX
fcis-29392	31	16	first	first	ADV
fcis-29392	31	17	generated	generate	VERB
fcis-29392	31	18	,	,	PUNCT
fcis-29392	31	19	and	and	CCONJ
fcis-29392	31	20	then	then	ADV
fcis-29392	31	21	classification	classification	NOUN
fcis-29392	31	22	and	and	CCONJ
fcis-29392	31	23	bounding	bounding	NOUN
fcis-29392	31	24	box	box	NOUN
fcis-29392	31	25	regression	regression	NOUN
fcis-29392	31	26	is	be	AUX
fcis-29392	31	27	performed	perform	VERB
fcis-29392	31	28	on	on	ADP
fcis-29392	31	29	these	these	DET
fcis-29392	31	30	candidate	candidate	NOUN
fcis-29392	31	31	frames	frame	NOUN
fcis-29392	31	32	.	.	PUNCT
fcis-29392	32	1	compared	compare	VERB
fcis-29392	32	2	to	to	ADP
fcis-29392	32	3	convolution	convolution	NOUN
fcis-29392	32	4	-	-	PUNCT
fcis-29392	32	5	based	base	VERB
fcis-29392	32	6	detection	detection	NOUN
fcis-29392	32	7	networks	network	NOUN
fcis-29392	32	8	,	,	PUNCT
fcis-29392	32	9	detr	detr	NOUN
fcis-29392	32	10	eliminates	eliminate	NOUN
fcis-29392	32	11	processes	process	NOUN
fcis-29392	32	12	such	such	ADJ
fcis-29392	32	13	as	as	ADP
fcis-29392	32	14	candidate	candidate	NOUN
fcis-29392	32	15	frame	frame	NOUN
fcis-29392	32	16	generation	generation	NOUN
fcis-29392	32	17	and	and	CCONJ
fcis-29392	32	18	nonmaximal	nonmaximal	ADJ
fcis-29392	32	19	suppression	suppression	NOUN
fcis-29392	32	20	(	(	PUNCT
fcis-29392	32	21	nms	nms	NOUN
fcis-29392	32	22	)	)	PUNCT
fcis-29392	32	23	,	,	PUNCT
fcis-29392	32	24	transforming	transform	VERB
fcis-29392	32	25	the	the	DET
fcis-29392	32	26	target	target	NOUN
fcis-29392	32	27	detection	detection	NOUN
fcis-29392	32	28	task	task	NOUN
fcis-29392	32	29	into	into	ADP
fcis-29392	32	30	an	an	DET
fcis-29392	32	31	ensemble	ensemble	ADJ
fcis-29392	32	32	prediction	prediction	NOUN
fcis-29392	32	33	problem	problem	NOUN
fcis-29392	32	34	and	and	CCONJ
fcis-29392	32	35	98	98	NUM
fcis-29392	32	36	greatly	greatly	ADV
fcis-29392	32	37	simplifying	simplify	VERB
fcis-29392	32	38	the	the	DET
fcis-29392	32	39	target	target	NOUN
fcis-29392	32	40	detection	detection	NOUN
fcis-29392	32	41	process	process	NOUN
fcis-29392	32	42	.	.	PUNCT
fcis-29392	33	1	the	the	DET
fcis-29392	33	2	model	model	NOUN
fcis-29392	33	3	structure	structure	NOUN
fcis-29392	33	4	of	of	ADP
fcis-29392	33	5	detr	detr	NOUN
fcis-29392	33	6	is	be	AUX
fcis-29392	33	7	shown	show	VERB
fcis-29392	33	8	in	in	ADP
fcis-29392	33	9	fig	fig	NOUN
fcis-29392	33	10	.	.	PUNCT
fcis-29392	34	1	1	1	NUM
fcis-29392	34	2	,	,	PUNCT
fcis-29392	34	3	which	which	PRON
fcis-29392	34	4	can	can	AUX
fcis-29392	34	5	be	be	AUX
fcis-29392	34	6	divided	divide	VERB
fcis-29392	34	7	into	into	ADP
fcis-29392	34	8	the	the	DET
fcis-29392	34	9	following	follow	VERB
fcis-29392	34	10	three	three	NUM
fcis-29392	34	11	parts	part	NOUN
fcis-29392	34	12	:	:	PUNCT
fcis-29392	34	13	first	first	ADV
fcis-29392	34	14	,	,	PUNCT
fcis-29392	34	15	the	the	DET
fcis-29392	34	16	cnn	cnn	PROPN
fcis-29392	34	17	backbone	backbone	NOUN
fcis-29392	34	18	network	network	NOUN
fcis-29392	34	19	for	for	ADP
fcis-29392	34	20	image	image	NOUN
fcis-29392	34	21	feature	feature	NOUN
fcis-29392	34	22	extraction	extraction	NOUN
fcis-29392	34	23	using	use	VERB
fcis-29392	34	24	resnet	resnet	ADJ
fcis-29392	34	25	network	network	NOUN
fcis-29392	34	26	;	;	PUNCT
fcis-29392	34	27	second	second	X
fcis-29392	34	28	,	,	PUNCT
fcis-29392	34	29	the	the	DET
fcis-29392	34	30	encoder	encoder	NOUN
fcis-29392	34	31	and	and	CCONJ
fcis-29392	34	32	decoder	decoder	NOUN
fcis-29392	34	33	based	base	VERB
fcis-29392	34	34	on	on	ADP
fcis-29392	34	35	selfattention	selfattention	PROPN
fcis-29392	34	36	transformer	transformer	NOUN
fcis-29392	34	37	;	;	PUNCT
fcis-29392	34	38	and	and	CCONJ
fcis-29392	34	39	third	third	ADV
fcis-29392	34	40	,	,	PUNCT
fcis-29392	34	41	the	the	DET
fcis-29392	34	42	feed	feed	NOUN
fcis-29392	34	43	-	-	PUNCT
fcis-29392	34	44	forward	forward	NOUN
fcis-29392	34	45	network	network	NOUN
fcis-29392	34	46	,	,	PUNCT
fcis-29392	34	47	ffn	ffn	PROPN
fcis-29392	34	48	,	,	PUNCT
fcis-29392	34	49	which	which	PRON
fcis-29392	34	50	carries	carry	VERB
fcis-29392	34	51	out	out	ADP
fcis-29392	34	52	the	the	DET
fcis-29392	34	53	final	final	ADJ
fcis-29392	34	54	detection	detection	NOUN
fcis-29392	34	55	.	.	PUNCT
fcis-29392	35	1	the	the	DET
fcis-29392	35	2	original	original	ADJ
fcis-29392	35	3	image	image	NOUN
fcis-29392	35	4	is	be	AUX
fcis-29392	35	5	fed	feed	VERB
fcis-29392	35	6	into	into	ADP
fcis-29392	35	7	the	the	DET
fcis-29392	35	8	resnet	resnet	NOUN
fcis-29392	35	9	network	network	NOUN
fcis-29392	35	10	to	to	PART
fcis-29392	35	11	generate	generate	VERB
fcis-29392	35	12	a	a	DET
fcis-29392	35	13	feature	feature	NOUN
fcis-29392	35	14	map	map	NOUN
fcis-29392	35	15	,	,	PUNCT
fcis-29392	35	16	and	and	CCONJ
fcis-29392	35	17	then	then	ADV
fcis-29392	35	18	undergoes	undergo	VERB
fcis-29392	35	19	a	a	DET
fcis-29392	35	20	1×1	1×1	ADJ
fcis-29392	35	21	convolution	convolution	NOUN
fcis-29392	35	22	to	to	PART
fcis-29392	35	23	convert	convert	VERB
fcis-29392	35	24	the	the	DET
fcis-29392	35	25	channel	channel	NOUN
fcis-29392	35	26	dimension	dimension	NOUN
fcis-29392	35	27	of	of	ADP
fcis-29392	35	28	the	the	DET
fcis-29392	35	29	resnet	resnet	ADJ
fcis-29392	35	30	output	output	NOUN
fcis-29392	35	31	into	into	ADP
fcis-29392	35	32	a	a	DET
fcis-29392	35	33	smaller	small	ADJ
fcis-29392	35	34	dimension	dimension	NOUN
fcis-29392	35	35	d	d	NOUN
fcis-29392	35	36	to	to	PART
fcis-29392	35	37	obtain	obtain	VERB
fcis-29392	35	38	a	a	DET
fcis-29392	35	39	new	new	ADJ
fcis-29392	35	40	feature	feature	NOUN
fcis-29392	35	41	map	map	NOUN
fcis-29392	35	42	d×h×w	d×h×w	PROPN
fcis-29392	36	1	.	.	PUNCT
fcis-29392	36	2	transformer	transformer	NOUN
fcis-29392	36	3	expects	expect	VERB
fcis-29392	36	4	a	a	DET
fcis-29392	36	5	sequence	sequence	NOUN
fcis-29392	36	6	as	as	ADP
fcis-29392	36	7	input	input	NOUN
fcis-29392	36	8	,	,	PUNCT
fcis-29392	36	9	so	so	ADV
fcis-29392	36	10	we	we	PRON
fcis-29392	36	11	collapse	collapse	VERB
fcis-29392	36	12	the	the	DET
fcis-29392	36	13	spatial	spatial	ADJ
fcis-29392	36	14	dimension	dimension	NOUN
fcis-29392	36	15	of	of	ADP
fcis-29392	36	16	the	the	DET
fcis-29392	36	17	new	new	ADJ
fcis-29392	36	18	feature	feature	NOUN
fcis-29392	36	19	map	map	NOUN
fcis-29392	36	20	into	into	ADP
fcis-29392	36	21	a	a	DET
fcis-29392	36	22	single	single	ADJ
fcis-29392	36	23	dimension	dimension	NOUN
fcis-29392	36	24	to	to	PART
fcis-29392	36	25	obtain	obtain	VERB
fcis-29392	36	26	d×hw	d×hw	PROPN
fcis-29392	36	27	,	,	PUNCT
fcis-29392	36	28	which	which	PRON
fcis-29392	36	29	is	be	AUX
fcis-29392	36	30	then	then	ADV
fcis-29392	36	31	passed	pass	VERB
fcis-29392	36	32	as	as	ADP
fcis-29392	36	33	an	an	DET
fcis-29392	36	34	input	input	NOUN
fcis-29392	36	35	with	with	ADP
fcis-29392	36	36	the	the	DET
fcis-29392	36	37	addition	addition	NOUN
fcis-29392	36	38	of	of	ADP
fcis-29392	36	39	positional	positional	ADJ
fcis-29392	36	40	encoding	encoding	NOUN
fcis-29392	36	41	to	to	ADP
fcis-29392	36	42	the	the	DET
fcis-29392	36	43	transformer	transformer	NOUN
fcis-29392	36	44	.	.	PUNCT
fcis-29392	37	1	the	the	DET
fcis-29392	37	2	detr	detr	NOUN
fcis-29392	37	3	decoder	decoder	NOUN
fcis-29392	37	4	decodes	decode	VERB
fcis-29392	37	5	n	n	PRON
fcis-29392	37	6	objects	object	NOUN
fcis-29392	37	7	in	in	ADP
fcis-29392	37	8	parallel	parallel	NOUN
fcis-29392	37	9	,	,	PUNCT
fcis-29392	37	10	and	and	CCONJ
fcis-29392	37	11	the	the	DET
fcis-29392	37	12	n	n	NUM
fcis-29392	37	13	object	object	NOUN
fcis-29392	37	14	queries	query	NOUN
fcis-29392	37	15	are	be	AUX
fcis-29392	37	16	converted	convert	VERB
fcis-29392	37	17	into	into	ADP
fcis-29392	37	18	one	one	NUM
fcis-29392	37	19	output	output	NOUN
fcis-29392	37	20	embedding	embed	VERB
fcis-29392	37	21	by	by	ADP
fcis-29392	37	22	the	the	DET
fcis-29392	37	23	decoder	decoder	NOUN
fcis-29392	37	24	.	.	PUNCT
fcis-29392	38	1	the	the	DET
fcis-29392	38	2	feed	feed	NOUN
fcis-29392	38	3	-	-	PUNCT
fcis-29392	38	4	forward	forward	NOUN
fcis-29392	38	5	network	network	NOUN
fcis-29392	38	6	decodes	decode	VERB
fcis-29392	38	7	them	they	PRON
fcis-29392	38	8	independently	independently	ADV
fcis-29392	38	9	as	as	ADP
fcis-29392	38	10	bounding	bound	VERB
fcis-29392	38	11	box	box	NOUN
fcis-29392	38	12	coordinates	coordinate	NOUN
fcis-29392	38	13	,	,	PUNCT
fcis-29392	38	14	predicting	predict	VERB
fcis-29392	38	15	the	the	DET
fcis-29392	38	16	normalized	normalize	VERB
fcis-29392	38	17	center	center	NOUN
fcis-29392	38	18	coordinates	coordinate	NOUN
fcis-29392	38	19	,	,	PUNCT
fcis-29392	38	20	height	height	NOUN
fcis-29392	38	21	and	and	CCONJ
fcis-29392	38	22	width	width	NOUN
fcis-29392	38	23	of	of	ADP
fcis-29392	38	24	the	the	DET
fcis-29392	38	25	bounding	bounding	NOUN
fcis-29392	38	26	box	box	NOUN
fcis-29392	38	27	,	,	PUNCT
fcis-29392	38	28	while	while	SCONJ
fcis-29392	38	29	the	the	DET
fcis-29392	38	30	linear	linear	ADJ
fcis-29392	38	31	layer	layer	NOUN
fcis-29392	38	32	predicts	predict	VERB
fcis-29392	38	33	the	the	DET
fcis-29392	38	34	category	category	NOUN
fcis-29392	38	35	labels	label	VERB
fcis-29392	38	36	using	use	VERB
fcis-29392	38	37	a	a	DET
fcis-29392	38	38	softmax	softmax	NOUN
fcis-29392	38	39	function	function	NOUN
fcis-29392	38	40	.	.	PUNCT
fcis-29392	39	1	the	the	DET
fcis-29392	39	2	detr	detr	NOUN
fcis-29392	39	3	model	model	NOUN
fcis-29392	39	4	exploits	exploit	VERB
fcis-29392	39	5	the	the	DET
fcis-29392	39	6	self	self	NOUN
fcis-29392	39	7	-	-	PUNCT
fcis-29392	39	8	attention	attention	NOUN
fcis-29392	39	9	of	of	ADP
fcis-29392	39	10	these	these	DET
fcis-29392	39	11	embeddings	embedding	NOUN
fcis-29392	39	12	and	and	CCONJ
fcis-29392	39	13	the	the	DET
fcis-29392	39	14	encoder	encoder	NOUN
fcis-29392	39	15	-	-	PUNCT
fcis-29392	39	16	decoder	decoder	NOUN
fcis-29392	39	17	attention	attention	NOUN
fcis-29392	39	18	to	to	ADP
fcis-29392	39	19	reason	reason	NOUN
fcis-29392	39	20	globally	globally	ADV
fcis-29392	39	21	over	over	ADP
fcis-29392	39	22	all	all	DET
fcis-29392	39	23	the	the	DET
fcis-29392	39	24	objects	object	NOUN
fcis-29392	39	25	,	,	PUNCT
fcis-29392	39	26	being	be	AUX
fcis-29392	39	27	able	able	ADJ
fcis-29392	39	28	to	to	PART
fcis-29392	39	29	use	use	VERB
fcis-29392	39	30	the	the	DET
fcis-29392	39	31	whole	whole	ADJ
fcis-29392	39	32	image	image	NOUN
fcis-29392	39	33	as	as	ADP
fcis-29392	39	34	a	a	DET
fcis-29392	39	35	context	context	NOUN
fcis-29392	39	36	.	.	PUNCT
fcis-29392	40	1	fig	fig	NOUN
fcis-29392	40	2	1	1	NUM
fcis-29392	40	3	.	.	PUNCT
fcis-29392	40	4	detr	detr	NOUN
fcis-29392	40	5	model	model	NOUN
fcis-29392	40	6	architecture	architecture	NOUN
fcis-29392	40	7	the	the	DET
fcis-29392	40	8	detr	detr	NOUN
fcis-29392	40	9	model	model	NOUN
fcis-29392	40	10	uses	use	VERB
fcis-29392	40	11	an	an	DET
fcis-29392	40	12	ensemble	ensemble	ADJ
fcis-29392	40	13	-	-	PUNCT
fcis-29392	40	14	based	base	VERB
fcis-29392	40	15	loss	loss	NOUN
fcis-29392	40	16	function	function	NOUN
fcis-29392	40	17	that	that	PRON
fcis-29392	40	18	predicts	predict	VERB
fcis-29392	40	19	a	a	DET
fcis-29392	40	20	fixed	fix	VERB
fcis-29392	40	21	-	-	PUNCT
fcis-29392	40	22	size	size	NOUN
fcis-29392	40	23	ensemble	ensemble	NOUN
fcis-29392	40	24	of	of	ADP
fcis-29392	40	25	n	n	NOUN
fcis-29392	40	26	bounding	bound	VERB
fcis-29392	40	27	boxes	box	NOUN
fcis-29392	40	28	that	that	PRON
fcis-29392	40	29	can	can	AUX
fcis-29392	40	30	be	be	AUX
fcis-29392	40	31	predicted	predict	VERB
fcis-29392	40	32	for	for	ADP
fcis-29392	40	33	all	all	DET
fcis-29392	40	34	objects	object	NOUN
fcis-29392	40	35	simultaneously	simultaneously	ADV
fcis-29392	40	36	.	.	PUNCT
fcis-29392	41	1	n	n	PRON
fcis-29392	41	2	is	be	AUX
fcis-29392	41	3	usually	usually	ADV
fcis-29392	41	4	set	set	VERB
fcis-29392	41	5	to	to	PART
fcis-29392	41	6	be	be	AUX
fcis-29392	41	7	much	much	ADV
fcis-29392	41	8	larger	large	ADJ
fcis-29392	41	9	than	than	ADP
fcis-29392	41	10	the	the	DET
fcis-29392	41	11	actual	actual	ADJ
fcis-29392	41	12	number	number	NOUN
fcis-29392	41	13	of	of	ADP
fcis-29392	41	14	objects	object	NOUN
fcis-29392	41	15	of	of	ADP
fcis-29392	41	16	interest	interest	NOUN
fcis-29392	41	17	in	in	ADP
fcis-29392	41	18	the	the	DET
fcis-29392	41	19	image	image	NOUN
fcis-29392	41	20	,	,	PUNCT
fcis-29392	41	21	and	and	CCONJ
fcis-29392	41	22	requires	require	VERB
fcis-29392	41	23	an	an	DET
fcis-29392	41	24	additional	additional	ADJ
fcis-29392	41	25	special	special	ADJ
fcis-29392	41	26	class	class	NOUN
fcis-29392	41	27	labeled	label	VERB
fcis-29392	41	28	“	"	PUNCT
fcis-29392	41	29	∅	∅	NOUN
fcis-29392	41	30	”	"	PUNCT
fcis-29392	41	31	to	to	PART
fcis-29392	41	32	indicate	indicate	VERB
fcis-29392	41	33	that	that	SCONJ
fcis-29392	41	34	no	no	DET
fcis-29392	41	35	objects	object	NOUN
fcis-29392	41	36	are	be	AUX
fcis-29392	41	37	detected	detect	VERB
fcis-29392	41	38	within	within	ADP
fcis-29392	41	39	a	a	DET
fcis-29392	41	40	slot	slot	NOUN
fcis-29392	41	41	.	.	PUNCT
fcis-29392	42	1	no	no	DET
fcis-29392	42	2	objects	object	NOUN
fcis-29392	42	3	are	be	AUX
fcis-29392	42	4	detected	detect	VERB
fcis-29392	42	5	.	.	PUNCT
fcis-29392	43	1	this	this	DET
fcis-29392	43	2	class	class	NOUN
fcis-29392	43	3	acts	act	VERB
fcis-29392	43	4	similarly	similarly	ADV
fcis-29392	43	5	to	to	ADP
fcis-29392	43	6	the	the	DET
fcis-29392	43	7	background	background	NOUN
fcis-29392	43	8	class	class	NOUN
fcis-29392	43	9	in	in	ADP
fcis-29392	43	10	standard	standard	ADJ
fcis-29392	43	11	object	object	NOUN
fcis-29392	43	12	detection	detection	NOUN
fcis-29392	43	13	methods	method	NOUN
fcis-29392	43	14	.	.	PUNCT
fcis-29392	44	1	3	3	X
fcis-29392	44	2	.	.	X
fcis-29392	44	3	model	model	NOUN
fcis-29392	44	4	algorithm	algorithm	PROPN
fcis-29392	44	5	improvement	improvement	NOUN
fcis-29392	44	6	3.1	3.1	NUM
fcis-29392	44	7	.	.	PUNCT
fcis-29392	44	8	focal	focal	ADJ
fcis-29392	44	9	loss	loss	NOUN
fcis-29392	44	10	function	function	NOUN
fcis-29392	44	11	in	in	ADP
fcis-29392	44	12	most	most	ADJ
fcis-29392	44	13	cases	case	NOUN
fcis-29392	44	14	the	the	DET
fcis-29392	44	15	foreground	foreground	NOUN
fcis-29392	44	16	region	region	NOUN
fcis-29392	44	17	is	be	AUX
fcis-29392	44	18	smaller	small	ADJ
fcis-29392	44	19	than	than	ADP
fcis-29392	44	20	the	the	DET
fcis-29392	44	21	background	background	NOUN
fcis-29392	44	22	region	region	NOUN
fcis-29392	44	23	,	,	PUNCT
fcis-29392	44	24	so	so	CCONJ
fcis-29392	44	25	the	the	DET
fcis-29392	44	26	number	number	NOUN
fcis-29392	44	27	of	of	ADP
fcis-29392	44	28	anchors	anchor	NOUN
fcis-29392	44	29	corresponding	correspond	VERB
fcis-29392	44	30	to	to	ADP
fcis-29392	44	31	the	the	DET
fcis-29392	44	32	foreground	foreground	NOUN
fcis-29392	44	33	target	target	NOUN
fcis-29392	44	34	tends	tend	VERB
fcis-29392	44	35	to	to	PART
fcis-29392	44	36	be	be	AUX
fcis-29392	44	37	smaller	small	ADJ
fcis-29392	44	38	than	than	ADP
fcis-29392	44	39	the	the	DET
fcis-29392	44	40	number	number	NOUN
fcis-29392	44	41	of	of	ADP
fcis-29392	44	42	anchors	anchor	NOUN
fcis-29392	44	43	corresponding	correspond	VERB
fcis-29392	44	44	to	to	ADP
fcis-29392	44	45	the	the	DET
fcis-29392	44	46	background	background	NOUN
fcis-29392	44	47	target	target	NOUN
fcis-29392	44	48	,	,	PUNCT
fcis-29392	44	49	and	and	CCONJ
fcis-29392	44	50	there	there	PRON
fcis-29392	44	51	is	be	VERB
fcis-29392	44	52	a	a	DET
fcis-29392	44	53	serious	serious	ADJ
fcis-29392	44	54	classification	classification	NOUN
fcis-29392	44	55	imbalance	imbalance	NOUN
fcis-29392	44	56	problem	problem	NOUN
fcis-29392	44	57	in	in	ADP
fcis-29392	44	58	the	the	DET
fcis-29392	44	59	foreground	foreground	NOUN
fcis-29392	44	60	and	and	CCONJ
fcis-29392	44	61	background	background	NOUN
fcis-29392	44	62	,	,	PUNCT
fcis-29392	44	63	and	and	CCONJ
fcis-29392	44	64	this	this	DET
fcis-29392	44	65	imbalance	imbalance	NOUN
fcis-29392	44	66	problem	problem	NOUN
fcis-29392	44	67	affects	affect	VERB
fcis-29392	44	68	the	the	DET
fcis-29392	44	69	training	training	NOUN
fcis-29392	44	70	process	process	NOUN
fcis-29392	44	71	of	of	ADP
fcis-29392	44	72	the	the	DET
fcis-29392	44	73	model	model	NOUN
fcis-29392	44	74	.	.	PUNCT
fcis-29392	45	1	it	it	PRON
fcis-29392	45	2	leads	lead	VERB
fcis-29392	45	3	to	to	ADP
fcis-29392	45	4	two	two	NUM
fcis-29392	45	5	problems	problem	NOUN
fcis-29392	45	6	:	:	PUNCT
fcis-29392	45	7	(	(	PUNCT
fcis-29392	45	8	1	1	X
fcis-29392	45	9	)	)	PUNCT
fcis-29392	45	10	training	training	NOUN
fcis-29392	45	11	is	be	AUX
fcis-29392	45	12	inefficient	inefficient	ADJ
fcis-29392	45	13	because	because	SCONJ
fcis-29392	45	14	most	most	ADJ
fcis-29392	45	15	places	place	NOUN
fcis-29392	45	16	are	be	AUX
fcis-29392	45	17	simple	simple	ADJ
fcis-29392	45	18	negative	negative	ADJ
fcis-29392	45	19	examples	example	NOUN
fcis-29392	45	20	,	,	PUNCT
fcis-29392	45	21	which	which	PRON
fcis-29392	45	22	do	do	AUX
fcis-29392	45	23	not	not	PART
fcis-29392	45	24	help	help	VERB
fcis-29392	45	25	the	the	DET
fcis-29392	45	26	model	model	NOUN
fcis-29392	45	27	learning	learning	NOUN
fcis-29392	45	28	;	;	PUNCT
fcis-29392	45	29	(	(	PUNCT
fcis-29392	45	30	2	2	X
fcis-29392	45	31	)	)	PUNCT
fcis-29392	45	32	too	too	ADV
fcis-29392	45	33	many	many	ADJ
fcis-29392	45	34	negative	negative	ADJ
fcis-29392	45	35	samples	sample	NOUN
fcis-29392	45	36	will	will	AUX
fcis-29392	45	37	dominate	dominate	VERB
fcis-29392	45	38	the	the	DET
fcis-29392	45	39	model	model	NOUN
fcis-29392	45	40	training	training	NOUN
fcis-29392	45	41	and	and	CCONJ
fcis-29392	45	42	lead	lead	VERB
fcis-29392	45	43	to	to	ADP
fcis-29392	45	44	lower	low	ADJ
fcis-29392	45	45	model	model	NOUN
fcis-29392	45	46	accuracy	accuracy	NOUN
fcis-29392	45	47	.	.	PUNCT
fcis-29392	46	1	detr	detr	NOUN
fcis-29392	46	2	infers	infer	NOUN
fcis-29392	46	3	a	a	DET
fcis-29392	46	4	fixed	fix	VERB
fcis-29392	46	5	-	-	PUNCT
fcis-29392	46	6	size	size	NOUN
fcis-29392	46	7	set	set	NOUN
fcis-29392	46	8	of	of	ADP
fcis-29392	46	9	n	n	NOUN
fcis-29392	46	10	predictions	prediction	NOUN
fcis-29392	46	11	in	in	ADP
fcis-29392	46	12	a	a	DET
fcis-29392	46	13	single	single	ADJ
fcis-29392	46	14	pass	pass	NOUN
fcis-29392	46	15	through	through	ADP
fcis-29392	46	16	the	the	DET
fcis-29392	46	17	decoder	decoder	NOUN
fcis-29392	46	18	,	,	PUNCT
fcis-29392	46	19	and	and	CCONJ
fcis-29392	46	20	detr	detr	NOUN
fcis-29392	46	21	produces	produce	VERB
fcis-29392	46	22	an	an	DET
fcis-29392	46	23	optimal	optimal	ADJ
fcis-29392	46	24	dichotomous	dichotomous	ADJ
fcis-29392	46	25	match	match	NOUN
fcis-29392	46	26	between	between	ADP
fcis-29392	46	27	predicted	predict	VERB
fcis-29392	46	28	and	and	CCONJ
fcis-29392	46	29	real	real	ADJ
fcis-29392	46	30	objects	object	NOUN
fcis-29392	46	31	,	,	PUNCT
fcis-29392	46	32	optimizing	optimize	VERB
fcis-29392	46	33	object	object	NOUN
fcis-29392	46	34	-	-	PUNCT
fcis-29392	46	35	specific	specific	ADJ
fcis-29392	46	36	losses	loss	NOUN
fcis-29392	46	37	.	.	PUNCT
fcis-29392	47	1	first	first	ADV
fcis-29392	47	2	,	,	PUNCT
fcis-29392	47	3	detr	detr	NOUN
fcis-29392	47	4	performs	perform	VERB
fcis-29392	47	5	a	a	DET
fcis-29392	47	6	bipartite	bipartite	NOUN
fcis-29392	47	7	graph	graph	NOUN
fcis-29392	47	8	matching	match	VERB
fcis-29392	47	9	using	use	VERB
fcis-29392	47	10	an	an	DET
fcis-29392	47	11	improved	improved	ADJ
fcis-29392	47	12	hungarian	hungarian	ADJ
fcis-29392	47	13	algorithm	algorithm	NOUN
fcis-29392	47	14	,	,	PUNCT
fcis-29392	47	15	which	which	PRON
fcis-29392	47	16	matches	match	VERB
fcis-29392	47	17	the	the	DET
fcis-29392	47	18	predicted	predict	VERB
fcis-29392	47	19	set	set	VERB
fcis-29392	47	20	with	with	ADP
fcis-29392	47	21	the	the	DET
fcis-29392	47	22	true	true	ADJ
fcis-29392	47	23	set	set	NOUN
fcis-29392	47	24	one	one	NUM
fcis-29392	47	25	by	by	ADP
fcis-29392	47	26	one	one	NUM
fcis-29392	47	27	,	,	PUNCT
fcis-29392	47	28	so	so	SCONJ
fcis-29392	47	29	that	that	SCONJ
fcis-29392	47	30	the	the	DET
fcis-29392	47	31	matching	match	VERB
fcis-29392	47	32	loss	loss	NOUN
fcis-29392	47	33	is	be	AUX
fcis-29392	47	34	minimized	minimize	VERB
fcis-29392	47	35	,	,	PUNCT
fcis-29392	47	36	and	and	CCONJ
fcis-29392	47	37	a	a	DET
fcis-29392	47	38	prediction	prediction	NOUN
fcis-29392	47	39	result	result	NOUN
fcis-29392	47	40	that	that	PRON
fcis-29392	47	41	minimizes	minimize	VERB
fcis-29392	47	42	the	the	DET
fcis-29392	47	43	loss	loss	NOUN
fcis-29392	47	44	with	with	ADP
fcis-29392	47	45	the	the	DET
fcis-29392	47	46	current	current	ADJ
fcis-29392	47	47	true	true	ADJ
fcis-29392	47	48	value	value	NOUN
fcis-29392	47	49	is	be	AUX
fcis-29392	47	50	obtained	obtain	VERB
fcis-29392	47	51	by	by	ADP
fcis-29392	47	52	the	the	DET
fcis-29392	47	53	hungarian	hungarian	ADJ
fcis-29392	47	54	algorithm	algorithm	NOUN
fcis-29392	47	55	.	.	PUNCT
fcis-29392	48	1	after	after	ADP
fcis-29392	48	2	that	that	PRON
fcis-29392	48	3	,	,	PUNCT
fcis-29392	48	4	the	the	DET
fcis-29392	48	5	loss	loss	NOUN
fcis-29392	48	6	function	function	NOUN
fcis-29392	48	7	is	be	AUX
fcis-29392	48	8	calculated	calculate	VERB
fcis-29392	48	9	,	,	PUNCT
fcis-29392	48	10	which	which	PRON
fcis-29392	48	11	is	be	AUX
fcis-29392	48	12	a	a	DET
fcis-29392	48	13	linear	linear	ADJ
fcis-29392	48	14	combination	combination	NOUN
fcis-29392	48	15	of	of	ADP
fcis-29392	48	16	classification	classification	NOUN
fcis-29392	48	17	loss	loss	NOUN
fcis-29392	48	18	and	and	CCONJ
fcis-29392	48	19	bounding	bound	VERB
fcis-29392	48	20	box	box	NOUN
fcis-29392	48	21	loss	loss	NOUN
fcis-29392	48	22	.	.	PUNCT
fcis-29392	49	1	the	the	DET
fcis-29392	49	2	categorization	categorization	NOUN
fcis-29392	49	3	loss	loss	NOUN
fcis-29392	49	4	is	be	AUX
fcis-29392	49	5	calculated	calculate	VERB
fcis-29392	49	6	from	from	ADP
fcis-29392	49	7	the	the	DET
fcis-29392	49	8	cross	cross	NOUN
fcis-29392	49	9	-	-	NOUN
fcis-29392	49	10	entropy	entropy	NOUN
fcis-29392	49	11	of	of	ADP
fcis-29392	49	12	the	the	DET
fcis-29392	49	13	categorized	categorize	VERB
fcis-29392	49	14	predicted	predict	VERB
fcis-29392	49	15	value	value	NOUN
fcis-29392	49	16	and	and	CCONJ
fcis-29392	49	17	the	the	DET
fcis-29392	49	18	true	true	ADJ
fcis-29392	49	19	value	value	NOUN
fcis-29392	49	20	,	,	PUNCT
fcis-29392	49	21	and	and	CCONJ
fcis-29392	49	22	the	the	DET
fcis-29392	49	23	bounding	bounding	NOUN
fcis-29392	49	24	box	box	NOUN
fcis-29392	49	25	loss	loss	NOUN
fcis-29392	49	26	is	be	AUX
fcis-29392	49	27	a	a	DET
fcis-29392	49	28	linear	linear	ADJ
fcis-29392	49	29	combination	combination	NOUN
fcis-29392	49	30	of	of	ADP
fcis-29392	49	31	the	the	DET
fcis-29392	49	32	l1	l1	PROPN
fcis-29392	49	33	loss	loss	NOUN
fcis-29392	49	34	and	and	CCONJ
fcis-29392	49	35	the	the	DET
fcis-29392	49	36	giou	giou	NOUN
fcis-29392	49	37	loss	loss	NOUN
fcis-29392	49	38	.	.	PUNCT
fcis-29392	50	1	the	the	DET
fcis-29392	50	2	standard	standard	ADJ
fcis-29392	50	3	cross	cross	ADJ
fcis-29392	50	4	-	-	ADJ
fcis-29392	50	5	entropy	entropy	ADJ
fcis-29392	50	6	loss	loss	NOUN
fcis-29392	50	7	function	function	NOUN
fcis-29392	50	8	has	have	VERB
fcis-29392	50	9	the	the	DET
fcis-29392	50	10	same	same	ADJ
fcis-29392	50	11	contribution	contribution	NOUN
fcis-29392	50	12	weight	weight	NOUN
fcis-29392	50	13	for	for	ADP
fcis-29392	50	14	each	each	DET
fcis-29392	50	15	sample	sample	NOUN
fcis-29392	50	16	,	,	PUNCT
fcis-29392	50	17	and	and	CCONJ
fcis-29392	50	18	when	when	SCONJ
fcis-29392	50	19	there	there	PRON
fcis-29392	50	20	is	be	VERB
fcis-29392	50	21	an	an	DET
fcis-29392	50	22	imbalance	imbalance	NOUN
fcis-29392	50	23	between	between	ADP
fcis-29392	50	24	positive	positive	ADJ
fcis-29392	50	25	and	and	CCONJ
fcis-29392	50	26	negative	negative	ADJ
fcis-29392	50	27	samples	sample	NOUN
fcis-29392	50	28	,	,	PUNCT
fcis-29392	50	29	the	the	DET
fcis-29392	50	30	model	model	NOUN
fcis-29392	50	31	training	training	NOUN
fcis-29392	50	32	process	process	NOUN
fcis-29392	50	33	may	may	AUX
fcis-29392	50	34	have	have	VERB
fcis-29392	50	35	a	a	DET
fcis-29392	50	36	dominant	dominant	ADJ
fcis-29392	50	37	effect	effect	NOUN
fcis-29392	50	38	,	,	PUNCT
fcis-29392	50	39	resulting	result	VERB
fcis-29392	50	40	in	in	ADP
fcis-29392	50	41	a	a	DET
fcis-29392	50	42	weaker	weak	ADJ
fcis-29392	50	43	model	model	NOUN
fcis-29392	50	44	for	for	ADP
fcis-29392	50	45	positive	positive	ADJ
fcis-29392	50	46	sample	sample	NOUN
fcis-29392	50	47	discrimination	discrimination	NOUN
fcis-29392	50	48	.	.	PUNCT
fcis-29392	51	1	the	the	DET
fcis-29392	51	2	standard	standard	PROPN
fcis-29392	51	3	cross	cross	PROPN
fcis-29392	51	4	entropy	entropy	PROPN
fcis-29392	51	5	is	be	AUX
fcis-29392	51	6	shown	show	VERB
fcis-29392	51	7	in	in	ADP
fcis-29392	51	8	equation	equation	NOUN
fcis-29392	51	9	(	(	PUNCT
fcis-29392	51	10	3	3	NUM
fcis-29392	51	11	):	):	PUNCT
fcis-29392	51	12	,	,	PUNCT
fcis-29392	51	13	1	1	NUM
fcis-29392	51	14	1	1	NUM
fcis-29392	51	15	,	,	PUNCT
fcis-29392	51	16	otherwise	otherwise	ADV
fcis-29392	51	17	(	(	PUNCT
fcis-29392	51	18	1	1	X
fcis-29392	51	19	)	)	PUNCT
fcis-29392	51	20	where	where	SCONJ
fcis-29392	51	21	y	y	PROPN
fcis-29392	51	22	∈	∈	PROPN
fcis-29392	51	23	1,1	1,1	NUM
fcis-29392	51	24	,	,	PUNCT
fcis-29392	51	25	representing	represent	VERB
fcis-29392	51	26	positive	positive	ADJ
fcis-29392	51	27	and	and	CCONJ
fcis-29392	51	28	negative	negative	ADJ
fcis-29392	51	29	samples	sample	NOUN
fcis-29392	51	30	,	,	PUNCT
fcis-29392	51	31	is	be	AUX
fcis-29392	51	32	the	the	DET
fcis-29392	51	33	labeling	labeling	NOUN
fcis-29392	51	34	probability	probability	NOUN
fcis-29392	51	35	predicted	predict	VERB
fcis-29392	51	36	by	by	ADP
fcis-29392	51	37	the	the	DET
fcis-29392	51	38	model	model	NOUN
fcis-29392	51	39	,	,	PUNCT
fcis-29392	51	40	and	and	CCONJ
fcis-29392	51	41	if	if	SCONJ
fcis-29392	51	42	p	p	X
fcis-29392	51	43	>	>	X
fcis-29392	51	44	0.5	0.5	NUM
fcis-29392	51	45	,	,	PUNCT
fcis-29392	51	46	it	it	PRON
fcis-29392	51	47	represents	represent	VERB
fcis-29392	51	48	a	a	DET
fcis-29392	51	49	positive	positive	ADJ
fcis-29392	51	50	sample	sample	NOUN
fcis-29392	51	51	,	,	PUNCT
fcis-29392	51	52	otherwise	otherwise	ADV
fcis-29392	51	53	it	it	PRON
fcis-29392	51	54	is	be	AUX
fcis-29392	51	55	a	a	DET
fcis-29392	51	56	negative	negative	ADJ
fcis-29392	51	57	sample	sample	NOUN
fcis-29392	51	58	.	.	PUNCT
fcis-29392	52	1	define	define	VERB
fcis-29392	52	2	by	by	ADP
fcis-29392	52	3	equation	equation	NOUN
fcis-29392	52	4	(	(	PUNCT
fcis-29392	52	5	2	2	NUM
fcis-29392	52	6	)	)	PUNCT
fcis-29392	52	7	and	and	CCONJ
fcis-29392	52	8	rewrite	rewrite	VERB
fcis-29392	52	9	the	the	DET
fcis-29392	52	10	loss	loss	NOUN
fcis-29392	52	11	function	function	NOUN
fcis-29392	52	12	as	as	ADP
fcis-29392	52	13	ce	ce	PROPN
fcis-29392	52	14	log	log	NOUN
fcis-29392	52	15	.	.	PUNCT
fcis-29392	53	1	,	,	PUNCT
fcis-29392	53	2	1	1	NUM
fcis-29392	53	3	1	1	NUM
fcis-29392	53	4	,	,	PUNCT
fcis-29392	53	5	(	(	PUNCT
fcis-29392	53	6	2	2	NUM
fcis-29392	53	7	)	)	PUNCT
fcis-29392	53	8	in	in	ADP
fcis-29392	53	9	order	order	NOUN
fcis-29392	53	10	to	to	PART
fcis-29392	53	11	improve	improve	VERB
fcis-29392	53	12	the	the	DET
fcis-29392	53	13	effect	effect	NOUN
fcis-29392	53	14	of	of	ADP
fcis-29392	53	15	target	target	NOUN
fcis-29392	53	16	detection	detection	NOUN
fcis-29392	53	17	,	,	PUNCT
fcis-29392	53	18	this	this	DET
fcis-29392	53	19	paper	paper	NOUN
fcis-29392	53	20	replaces	replace	VERB
fcis-29392	53	21	the	the	DET
fcis-29392	53	22	cross	cross	ADJ
fcis-29392	53	23	-	-	ADJ
fcis-29392	53	24	entropy	entropy	ADJ
fcis-29392	53	25	loss	loss	NOUN
fcis-29392	53	26	function	function	NOUN
fcis-29392	53	27	in	in	ADP
fcis-29392	53	28	the	the	DET
fcis-29392	53	29	classification	classification	NOUN
fcis-29392	53	30	loss	loss	NOUN
fcis-29392	53	31	with	with	ADP
fcis-29392	53	32	the	the	DET
fcis-29392	53	33	focus	focus	NOUN
fcis-29392	53	34	loss	loss	NOUN
fcis-29392	53	35	function	function	NOUN
fcis-29392	53	36	[	[	X
fcis-29392	53	37	16	16	NUM
fcis-29392	53	38	]	]	PUNCT
fcis-29392	53	39	for	for	ADP
fcis-29392	53	40	calculation	calculation	NOUN
fcis-29392	53	41	.	.	PUNCT
fcis-29392	54	1	focus	focus	NOUN
fcis-29392	54	2	loss	loss	NOUN
fcis-29392	54	3	solves	solve	VERB
fcis-29392	54	4	the	the	DET
fcis-29392	54	5	problems	problem	NOUN
fcis-29392	54	6	of	of	ADP
fcis-29392	54	7	positive	positive	ADJ
fcis-29392	54	8	and	and	CCONJ
fcis-29392	54	9	negative	negative	ADJ
fcis-29392	54	10	sample	sample	NOUN
fcis-29392	54	11	extreme	extreme	ADJ
fcis-29392	54	12	imbalance	imbalance	NOUN
fcis-29392	54	13	and	and	CCONJ
fcis-29392	54	14	difficult	difficult	ADJ
fcis-29392	54	15	to	to	PART
fcis-29392	54	16	classify	classify	VERB
fcis-29392	54	17	sample	sample	NOUN
fcis-29392	54	18	learning	learning	NOUN
fcis-29392	54	19	by	by	ADP
fcis-29392	54	20	adjusting	adjust	VERB
fcis-29392	54	21	the	the	DET
fcis-29392	54	22	weight	weight	NOUN
fcis-29392	54	23	of	of	ADP
fcis-29392	54	24	easy	easy	ADJ
fcis-29392	54	25	to	to	PART
fcis-29392	54	26	classify	classify	VERB
fcis-29392	54	27	samples	sample	NOUN
fcis-29392	54	28	,	,	PUNCT
fcis-29392	54	29	which	which	PRON
fcis-29392	54	30	makes	make	VERB
fcis-29392	54	31	the	the	DET
fcis-29392	54	32	model	model	NOUN
fcis-29392	54	33	pay	pay	VERB
fcis-29392	54	34	more	more	ADJ
fcis-29392	54	35	attention	attention	NOUN
fcis-29392	54	36	to	to	ADP
fcis-29392	54	37	difficult	difficult	ADJ
fcis-29392	54	38	to	to	PART
fcis-29392	54	39	classify	classify	VERB
fcis-29392	54	40	samples	sample	NOUN
fcis-29392	54	41	.	.	PUNCT
fcis-29392	55	1	the	the	DET
fcis-29392	55	2	focus	focus	NOUN
fcis-29392	55	3	loss	loss	NOUN
fcis-29392	55	4	formula	formula	NOUN
fcis-29392	55	5	is	be	AUX
fcis-29392	55	6	shown	show	VERB
fcis-29392	55	7	in	in	ADP
fcis-29392	55	8	(	(	PUNCT
fcis-29392	55	9	3	3	NUM
fcis-29392	55	10	):	):	SYM
fcis-29392	55	11	1	1	NUM
fcis-29392	55	12	(	(	PUNCT
fcis-29392	55	13	3	3	NUM
fcis-29392	55	14	)	)	PUNCT
fcis-29392	55	15	the	the	DET
fcis-29392	55	16	definition	definition	NOUN
fcis-29392	55	17	of	of	ADP
fcis-29392	55	18	is	be	AUX
fcis-29392	55	19	similar	similar	ADJ
fcis-29392	55	20	to	to	ADP
fcis-29392	55	21	that	that	PRON
fcis-29392	55	22	of	of	ADP
fcis-29392	55	23	.	.	PUNCT
fcis-29392	56	1	in	in	ADP
fcis-29392	56	2	the	the	DET
fcis-29392	56	3	formula	formula	NOUN
fcis-29392	56	4	for	for	ADP
fcis-29392	56	5	focus	focus	NOUN
fcis-29392	56	6	loss	loss	NOUN
fcis-29392	56	7	,	,	PUNCT
fcis-29392	56	8	weights	weight	NOUN
fcis-29392	56	9	are	be	AUX
fcis-29392	56	10	introduced	introduce	VERB
fcis-29392	56	11	to	to	PART
fcis-29392	56	12	improve	improve	VERB
fcis-29392	56	13	the	the	DET
fcis-29392	56	14	imbalance	imbalance	NOUN
fcis-29392	56	15	of	of	ADP
fcis-29392	56	16	positive	positive	ADJ
fcis-29392	56	17	and	and	CCONJ
fcis-29392	56	18	negative	negative	ADJ
fcis-29392	56	19	samples	sample	NOUN
fcis-29392	56	20	,	,	PUNCT
fcis-29392	56	21	and	and	CCONJ
fcis-29392	56	22	a	a	DET
fcis-29392	56	23	modulation	modulation	NOUN
fcis-29392	56	24	factor	factor	NOUN
fcis-29392	56	25	1	1	NUM
fcis-29392	56	26	is	be	AUX
fcis-29392	56	27	added	add	VERB
fcis-29392	56	28	to	to	PART
fcis-29392	56	29	regulate	regulate	VERB
fcis-29392	56	30	the	the	DET
fcis-29392	56	31	weights	weight	NOUN
fcis-29392	56	32	of	of	ADP
fcis-29392	56	33	the	the	DET
fcis-29392	56	34	difficult	difficult	ADJ
fcis-29392	56	35	and	and	CCONJ
fcis-29392	56	36	easy	easy	ADJ
fcis-29392	56	37	samples	sample	NOUN
fcis-29392	56	38	.	.	PUNCT
fcis-29392	57	1	when	when	SCONJ
fcis-29392	57	2	a	a	DET
fcis-29392	57	3	border	border	NOUN
fcis-29392	57	4	is	be	AUX
fcis-29392	57	5	misclassified	misclassifie	VERB
fcis-29392	57	6	,	,	PUNCT
fcis-29392	57	7	1	1	NUM
fcis-29392	57	8	is	be	AUX
fcis-29392	57	9	close	close	ADJ
fcis-29392	57	10	to	to	ADP
fcis-29392	57	11	1	1	NUM
fcis-29392	57	12	,	,	PUNCT
fcis-29392	57	13	and	and	CCONJ
fcis-29392	57	14	its	its	PRON
fcis-29392	57	15	loss	loss	NOUN
fcis-29392	57	16	is	be	AUX
fcis-29392	57	17	almost	almost	ADV
fcis-29392	57	18	unaffected	unaffected	ADJ
fcis-29392	57	19	,	,	PUNCT
fcis-29392	57	20	and	and	CCONJ
fcis-29392	57	21	when	when	SCONJ
fcis-29392	57	22	is	be	AUX
fcis-29392	57	23	close	close	ADJ
fcis-29392	57	24	to	to	ADP
fcis-29392	57	25	1	1	NUM
fcis-29392	57	26	,	,	PUNCT
fcis-29392	57	27	which	which	PRON
fcis-29392	57	28	indicates	indicate	VERB
fcis-29392	57	29	that	that	SCONJ
fcis-29392	57	30	it	it	PRON
fcis-29392	57	31	has	have	VERB
fcis-29392	57	32	better	well	ADJ
fcis-29392	57	33	classification	classification	NOUN
fcis-29392	57	34	prediction	prediction	NOUN
fcis-29392	57	35	and	and	CCONJ
fcis-29392	57	36	is	be	AUX
fcis-29392	57	37	a	a	DET
fcis-29392	57	38	simple	simple	ADJ
fcis-29392	57	39	sample	sample	NOUN
fcis-29392	57	40	,	,	PUNCT
fcis-29392	57	41	1	1	NUM
fcis-29392	57	42	is	be	AUX
fcis-29392	57	43	close	close	ADJ
fcis-29392	57	44	to	to	ADP
fcis-29392	57	45	0	0	NUM
fcis-29392	57	46	,	,	PUNCT
fcis-29392	57	47	so	so	ADV
fcis-29392	57	48	its	its	PRON
fcis-29392	57	49	loss	loss	NOUN
fcis-29392	57	50	is	be	AUX
fcis-29392	57	51	moderated	moderate	VERB
fcis-29392	57	52	down	down	ADP
fcis-29392	57	53	.	.	PUNCT
fcis-29392	58	1	is	be	AUX
fcis-29392	58	2	a	a	DET
fcis-29392	58	3	moderating	moderate	VERB
fcis-29392	58	4	factor	factor	NOUN
fcis-29392	58	5	,	,	PUNCT
fcis-29392	58	6	and	and	CCONJ
fcis-29392	58	7	the	the	DET
fcis-29392	58	8	larger	large	ADJ
fcis-29392	58	9	is	be	AUX
fcis-29392	58	10	,	,	PUNCT
fcis-29392	58	11	the	the	PRON
fcis-29392	58	12	lower	low	ADJ
fcis-29392	58	13	the	the	DET
fcis-29392	58	14	contribution	contribution	NOUN
fcis-29392	58	15	of	of	ADP
fcis-29392	58	16	the	the	DET
fcis-29392	58	17	simple	simple	ADJ
fcis-29392	58	18	sample	sample	NOUN
fcis-29392	58	19	loss	loss	NOUN
fcis-29392	58	20	will	will	AUX
fcis-29392	58	21	be	be	AUX
fcis-29392	58	22	.	.	PUNCT
fcis-29392	59	1	3.2	3.2	NUM
fcis-29392	59	2	.	.	PUNCT
fcis-29392	60	1	cbam	cbam	NOUN
fcis-29392	60	2	attention	attention	NOUN
fcis-29392	60	3	module	module	NOUN
fcis-29392	60	4	cbam	cbam	NOUN
fcis-29392	60	5	[	[	X
fcis-29392	60	6	17	17	NUM
fcis-29392	60	7	]	]	PUNCT
fcis-29392	60	8	,	,	PUNCT
fcis-29392	60	9	in	in	ADP
fcis-29392	60	10	order	order	NOUN
fcis-29392	60	11	to	to	PART
fcis-29392	60	12	emphasize	emphasize	VERB
fcis-29392	60	13	features	feature	NOUN
fcis-29392	60	14	that	that	PRON
fcis-29392	60	15	are	be	AUX
fcis-29392	60	16	99	99	NUM
fcis-29392	60	17	meaningful	meaningful	ADJ
fcis-29392	60	18	along	along	ADP
fcis-29392	60	19	the	the	DET
fcis-29392	60	20	two	two	NUM
fcis-29392	60	21	main	main	ADJ
fcis-29392	60	22	dimensions	dimension	NOUN
fcis-29392	60	23	,	,	PUNCT
fcis-29392	60	24	channel	channel	NOUN
fcis-29392	60	25	and	and	CCONJ
fcis-29392	60	26	space	space	NOUN
fcis-29392	60	27	,	,	PUNCT
fcis-29392	60	28	applies	apply	VERB
fcis-29392	60	29	channel	channel	NOUN
fcis-29392	60	30	and	and	CCONJ
fcis-29392	60	31	spatial	spatial	ADJ
fcis-29392	60	32	attention	attention	NOUN
fcis-29392	60	33	modules	module	NOUN
fcis-29392	60	34	sequentially	sequentially	ADV
fcis-29392	60	35	,	,	PUNCT
fcis-29392	60	36	allowing	allow	VERB
fcis-29392	60	37	each	each	DET
fcis-29392	60	38	branch	branch	NOUN
fcis-29392	60	39	to	to	PART
fcis-29392	60	40	learn	learn	VERB
fcis-29392	60	41	what	what	PRON
fcis-29392	60	42	is	be	AUX
fcis-29392	60	43	important	important	ADJ
fcis-29392	60	44	on	on	ADP
fcis-29392	60	45	the	the	DET
fcis-29392	60	46	channel	channel	NOUN
fcis-29392	60	47	and	and	CCONJ
fcis-29392	60	48	spatial	spatial	ADJ
fcis-29392	60	49	axes	axis	NOUN
fcis-29392	60	50	,	,	PUNCT
fcis-29392	60	51	respectively	respectively	ADV
fcis-29392	60	52	.	.	PUNCT
fcis-29392	61	1	the	the	DET
fcis-29392	61	2	modular	modular	ADJ
fcis-29392	61	3	structure	structure	NOUN
fcis-29392	61	4	of	of	ADP
fcis-29392	61	5	cbam	cbam	NOUN
fcis-29392	61	6	is	be	AUX
fcis-29392	61	7	shown	show	VERB
fcis-29392	61	8	in	in	ADP
fcis-29392	61	9	fig	fig	NOUN
fcis-29392	61	10	.	.	PUNCT
fcis-29392	62	1	2.given	2.given	NUM
fcis-29392	62	2	an	an	DET
fcis-29392	62	3	intermediate	intermediate	ADJ
fcis-29392	62	4	feature	feature	NOUN
fcis-29392	62	5	map	map	NOUN
fcis-29392	62	6	,	,	PUNCT
fcis-29392	62	7	the	the	DET
fcis-29392	62	8	cbam	cbam	NOUN
fcis-29392	62	9	module	module	NOUN
fcis-29392	62	10	sequentially	sequentially	ADV
fcis-29392	62	11	infers	infer	VERB
fcis-29392	62	12	the	the	DET
fcis-29392	62	13	attention	attention	NOUN
fcis-29392	62	14	map	map	NOUN
fcis-29392	62	15	along	along	ADP
fcis-29392	62	16	the	the	DET
fcis-29392	62	17	two	two	NUM
fcis-29392	62	18	separate	separate	ADJ
fcis-29392	62	19	dimensions	dimension	NOUN
fcis-29392	62	20	(	(	PUNCT
fcis-29392	62	21	channel	channel	NOUN
fcis-29392	62	22	and	and	CCONJ
fcis-29392	62	23	spatial	spatial	ADJ
fcis-29392	62	24	)	)	PUNCT
fcis-29392	62	25	,	,	PUNCT
fcis-29392	62	26	the	the	DET
fcis-29392	62	27	graph	graph	NOUN
fcis-29392	62	28	,	,	PUNCT
fcis-29392	62	29	and	and	CCONJ
fcis-29392	62	30	then	then	ADV
fcis-29392	62	31	multiplies	multiply	VERB
fcis-29392	62	32	the	the	DET
fcis-29392	62	33	attention	attention	NOUN
fcis-29392	62	34	graph	graph	NOUN
fcis-29392	62	35	by	by	ADP
fcis-29392	62	36	the	the	DET
fcis-29392	62	37	input	input	NOUN
fcis-29392	62	38	feature	feature	NOUN
fcis-29392	62	39	graph	graph	NOUN
fcis-29392	62	40	for	for	ADP
fcis-29392	62	41	adaptive	adaptive	ADJ
fcis-29392	62	42	feature	feature	NOUN
fcis-29392	62	43	refinement	refinement	NOUN
fcis-29392	62	44	.	.	PUNCT
fcis-29392	63	1	the	the	DET
fcis-29392	63	2	module	module	NOUN
fcis-29392	63	3	can	can	AUX
fcis-29392	63	4	optimize	optimize	VERB
fcis-29392	63	5	the	the	DET
fcis-29392	63	6	information	information	NOUN
fcis-29392	63	7	flow	flow	NOUN
fcis-29392	63	8	process	process	NOUN
fcis-29392	63	9	within	within	ADP
fcis-29392	63	10	the	the	DET
fcis-29392	63	11	network	network	NOUN
fcis-29392	63	12	by	by	ADP
fcis-29392	63	13	learning	learn	VERB
fcis-29392	63	14	which	which	DET
fcis-29392	63	15	information	information	NOUN
fcis-29392	63	16	in	in	ADP
fcis-29392	63	17	the	the	DET
fcis-29392	63	18	features	feature	NOUN
fcis-29392	63	19	needs	need	VERB
fcis-29392	63	20	to	to	PART
fcis-29392	63	21	be	be	AUX
fcis-29392	63	22	emphasized	emphasize	VERB
fcis-29392	63	23	or	or	CCONJ
fcis-29392	63	24	suppressed	suppress	VERB
fcis-29392	63	25	.	.	PUNCT
fcis-29392	64	1	fig	fig	NOUN
fcis-29392	64	2	2	2	NUM
fcis-29392	64	3	.	.	PUNCT
fcis-29392	65	1	cbam	cbam	NOUN
fcis-29392	65	2	structure	structure	NOUN
fcis-29392	65	3	the	the	DET
fcis-29392	65	4	overall	overall	ADJ
fcis-29392	65	5	attention	attention	NOUN
fcis-29392	65	6	generation	generation	NOUN
fcis-29392	65	7	process	process	NOUN
fcis-29392	65	8	can	can	AUX
fcis-29392	65	9	be	be	AUX
fcis-29392	65	10	summarized	summarize	VERB
fcis-29392	65	11	as	as	SCONJ
fcis-29392	65	12	shown	show	VERB
fcis-29392	65	13	in	in	ADP
fcis-29392	65	14	equations	equation	NOUN
fcis-29392	65	15	(	(	PUNCT
fcis-29392	65	16	4	4	NUM
fcis-29392	65	17	)	)	PUNCT
fcis-29392	65	18	,	,	PUNCT
fcis-29392	65	19	(	(	PUNCT
fcis-29392	65	20	5	5	NUM
fcis-29392	65	21	):	):	PUNCT
fcis-29392	65	22	⨂	⨂	X
fcis-29392	65	23	(	(	PUNCT
fcis-29392	65	24	4	4	X
fcis-29392	65	25	)	)	PUNCT
fcis-29392	65	26	⨂	⨂	NOUN
fcis-29392	65	27	(	(	PUNCT
fcis-29392	65	28	5	5	X
fcis-29392	65	29	)	)	PUNCT
fcis-29392	65	30	f	f	PROPN
fcis-29392	65	31	denotes	denote	VERB
fcis-29392	65	32	the	the	DET
fcis-29392	65	33	features	feature	NOUN
fcis-29392	65	34	input	input	NOUN
fcis-29392	65	35	to	to	ADP
fcis-29392	65	36	the	the	DET
fcis-29392	65	37	cbam	cbam	NOUN
fcis-29392	65	38	module	module	NOUN
fcis-29392	65	39	,	,	PUNCT
fcis-29392	65	40	and	and	CCONJ
fcis-29392	65	41	and	and	CCONJ
fcis-29392	65	42	are	be	AUX
fcis-29392	65	43	the	the	DET
fcis-29392	65	44	cbam	cbam	NOUN
fcis-29392	65	45	-	-	PUNCT
fcis-29392	65	46	derived	derive	VERB
fcis-29392	65	47	1d	1d	NUM
fcis-29392	65	48	channel	channel	NOUN
fcis-29392	65	49	attention	attention	NOUN
fcis-29392	65	50	and	and	CCONJ
fcis-29392	65	51	2d	2d	NOUN
fcis-29392	65	52	spatial	spatial	ADJ
fcis-29392	65	53	attention	attention	NOUN
fcis-29392	65	54	,	,	PUNCT
fcis-29392	65	55	respectively	respectively	ADV
fcis-29392	65	56	,	,	PUNCT
fcis-29392	65	57	where	where	SCONJ
fcis-29392	65	58	⊗	⊗	PROPN
fcis-29392	65	59	denotes	denote	NOUN
fcis-29392	65	60	multiplication	multiplication	NOUN
fcis-29392	65	61	by	by	ADP
fcis-29392	65	62	elements	element	NOUN
fcis-29392	65	63	each	each	DET
fcis-29392	65	64	channel	channel	NOUN
fcis-29392	65	65	of	of	ADP
fcis-29392	65	66	the	the	DET
fcis-29392	65	67	feature	feature	NOUN
fcis-29392	65	68	map	map	NOUN
fcis-29392	65	69	is	be	AUX
fcis-29392	65	70	considered	consider	VERB
fcis-29392	65	71	as	as	ADP
fcis-29392	65	72	a	a	DET
fcis-29392	65	73	feature	feature	NOUN
fcis-29392	65	74	detector	detector	NOUN
fcis-29392	65	75	and	and	CCONJ
fcis-29392	65	76	the	the	DET
fcis-29392	65	77	channel	channel	NOUN
fcis-29392	65	78	attention	attention	NOUN
fcis-29392	65	79	is	be	AUX
fcis-29392	65	80	focused	focus	VERB
fcis-29392	65	81	on	on	ADP
fcis-29392	65	82	the	the	DET
fcis-29392	65	83	meaningful	meaningful	ADJ
fcis-29392	65	84	features	feature	NOUN
fcis-29392	65	85	of	of	ADP
fcis-29392	65	86	the	the	DET
fcis-29392	65	87	given	give	VERB
fcis-29392	65	88	input	input	NOUN
fcis-29392	65	89	image	image	NOUN
fcis-29392	65	90	.	.	PUNCT
fcis-29392	66	1	to	to	PART
fcis-29392	66	2	compute	compute	VERB
fcis-29392	66	3	the	the	DET
fcis-29392	66	4	channel	channel	NOUN
fcis-29392	66	5	attention	attention	NOUN
fcis-29392	66	6	efficiently	efficiently	ADV
fcis-29392	66	7	,	,	PUNCT
fcis-29392	66	8	the	the	DET
fcis-29392	66	9	spatial	spatial	ADJ
fcis-29392	66	10	dimension	dimension	NOUN
fcis-29392	66	11	of	of	ADP
fcis-29392	66	12	the	the	DET
fcis-29392	66	13	input	input	NOUN
fcis-29392	66	14	feature	feature	NOUN
fcis-29392	66	15	map	map	NOUN
fcis-29392	66	16	is	be	AUX
fcis-29392	66	17	squeezed	squeeze	VERB
fcis-29392	66	18	.	.	PUNCT
fcis-29392	67	1	the	the	DET
fcis-29392	67	2	spatial	spatial	ADJ
fcis-29392	67	3	attention	attention	NOUN
fcis-29392	67	4	map	map	NOUN
fcis-29392	67	5	is	be	AUX
fcis-29392	67	6	generated	generate	VERB
fcis-29392	67	7	by	by	ADP
fcis-29392	67	8	exploiting	exploit	VERB
fcis-29392	67	9	the	the	DET
fcis-29392	67	10	spatial	spatial	ADJ
fcis-29392	67	11	relationships	relationship	NOUN
fcis-29392	67	12	of	of	ADP
fcis-29392	67	13	the	the	DET
fcis-29392	67	14	features	feature	NOUN
fcis-29392	67	15	.	.	PUNCT
fcis-29392	68	1	unlike	unlike	ADP
fcis-29392	68	2	channel	channel	NOUN
fcis-29392	68	3	attention	attention	NOUN
fcis-29392	68	4	,	,	PUNCT
fcis-29392	68	5	spatial	spatial	ADJ
fcis-29392	68	6	attention	attention	NOUN
fcis-29392	68	7	concentrates	concentrate	VERB
fcis-29392	68	8	on	on	ADP
fcis-29392	68	9	the	the	DET
fcis-29392	68	10	effective	effective	ADJ
fcis-29392	68	11	information	information	NOUN
fcis-29392	68	12	locations	location	NOUN
fcis-29392	68	13	on	on	ADP
fcis-29392	68	14	the	the	DET
fcis-29392	68	15	feature	feature	NOUN
fcis-29392	68	16	map	map	NOUN
fcis-29392	68	17	and	and	CCONJ
fcis-29392	68	18	complements	complement	VERB
fcis-29392	68	19	channel	channel	NOUN
fcis-29392	68	20	attention	attention	NOUN
fcis-29392	68	21	.	.	PUNCT
fcis-29392	69	1	to	to	PART
fcis-29392	69	2	compute	compute	VERB
fcis-29392	69	3	spatial	spatial	ADJ
fcis-29392	69	4	attention	attention	NOUN
fcis-29392	69	5	,	,	PUNCT
fcis-29392	69	6	average	average	ADJ
fcis-29392	69	7	pooling	pooling	NOUN
fcis-29392	69	8	and	and	CCONJ
fcis-29392	69	9	maximum	maximum	ADJ
fcis-29392	69	10	pooling	pool	VERB
fcis-29392	69	11	operations	operation	NOUN
fcis-29392	69	12	are	be	AUX
fcis-29392	69	13	first	first	ADV
fcis-29392	69	14	applied	apply	VERB
fcis-29392	69	15	along	along	ADP
fcis-29392	69	16	the	the	DET
fcis-29392	69	17	channel	channel	NOUN
fcis-29392	69	18	axis	axis	NOUN
fcis-29392	69	19	and	and	CCONJ
fcis-29392	69	20	connected	connect	VERB
fcis-29392	69	21	to	to	PART
fcis-29392	69	22	generate	generate	VERB
fcis-29392	69	23	a	a	DET
fcis-29392	69	24	valid	valid	ADJ
fcis-29392	69	25	feature	feature	NOUN
fcis-29392	69	26	descriptor	descriptor	NOUN
fcis-29392	69	27	.	.	PUNCT
fcis-29392	70	1	fig	fig	NOUN
fcis-29392	70	2	3	3	NUM
fcis-29392	70	3	.	.	PUNCT
fcis-29392	70	4	model	model	NOUN
fcis-29392	70	5	structure	structure	NOUN
fcis-29392	70	6	the	the	DET
fcis-29392	70	7	structure	structure	NOUN
fcis-29392	70	8	of	of	ADP
fcis-29392	70	9	the	the	DET
fcis-29392	70	10	model	model	NOUN
fcis-29392	70	11	with	with	ADP
fcis-29392	70	12	the	the	DET
fcis-29392	70	13	addition	addition	NOUN
fcis-29392	70	14	of	of	ADP
fcis-29392	70	15	the	the	DET
fcis-29392	70	16	cbam	cbam	NOUN
fcis-29392	70	17	module	module	NOUN
fcis-29392	70	18	is	be	AUX
fcis-29392	70	19	shown	show	VERB
fcis-29392	70	20	in	in	ADP
fcis-29392	70	21	fig	fig	NOUN
fcis-29392	70	22	.	.	PUNCT
fcis-29392	71	1	3	3	X
fcis-29392	71	2	.	.	X
fcis-29392	71	3	after	after	SCONJ
fcis-29392	71	4	the	the	DET
fcis-29392	71	5	original	original	ADJ
fcis-29392	71	6	image	image	NOUN
fcis-29392	71	7	is	be	AUX
fcis-29392	71	8	processed	process	VERB
fcis-29392	71	9	by	by	ADP
fcis-29392	71	10	the	the	DET
fcis-29392	71	11	resnet	resnet	NOUN
fcis-29392	71	12	network	network	NOUN
fcis-29392	71	13	,	,	PUNCT
fcis-29392	71	14	the	the	DET
fcis-29392	71	15	features	feature	NOUN
fcis-29392	71	16	are	be	AUX
fcis-29392	71	17	refined	refine	VERB
fcis-29392	71	18	using	use	VERB
fcis-29392	71	19	the	the	DET
fcis-29392	71	20	cbam	cbam	NOUN
fcis-29392	71	21	attention	attention	NOUN
fcis-29392	71	22	module	module	NOUN
fcis-29392	71	23	,	,	PUNCT
fcis-29392	71	24	which	which	PRON
fcis-29392	71	25	helps	help	VERB
fcis-29392	71	26	the	the	DET
fcis-29392	71	27	network	network	NOUN
fcis-29392	71	28	to	to	PART
fcis-29392	71	29	focus	focus	VERB
fcis-29392	71	30	on	on	ADP
fcis-29392	71	31	the	the	DET
fcis-29392	71	32	regions	region	NOUN
fcis-29392	71	33	and	and	CCONJ
fcis-29392	71	34	feature	feature	NOUN
fcis-29392	71	35	channels	channel	NOUN
fcis-29392	71	36	that	that	PRON
fcis-29392	71	37	are	be	AUX
fcis-29392	71	38	more	more	ADV
fcis-29392	71	39	important	important	ADJ
fcis-29392	71	40	to	to	ADP
fcis-29392	71	41	the	the	DET
fcis-29392	71	42	current	current	ADJ
fcis-29392	71	43	task	task	NOUN
fcis-29392	71	44	,	,	PUNCT
fcis-29392	71	45	thus	thus	ADV
fcis-29392	71	46	improving	improve	VERB
fcis-29392	71	47	the	the	DET
fcis-29392	71	48	feature	feature	NOUN
fcis-29392	71	49	extraction	extraction	NOUN
fcis-29392	71	50	ability	ability	NOUN
fcis-29392	71	51	of	of	ADP
fcis-29392	71	52	the	the	DET
fcis-29392	71	53	network	network	NOUN
fcis-29392	71	54	and	and	CCONJ
fcis-29392	71	55	the	the	DET
fcis-29392	71	56	final	final	ADJ
fcis-29392	71	57	recognition	recognition	NOUN
fcis-29392	71	58	effect	effect	NOUN
fcis-29392	71	59	.	.	PUNCT
fcis-29392	72	1	at	at	ADP
fcis-29392	72	2	the	the	DET
fcis-29392	72	3	same	same	ADJ
fcis-29392	72	4	time	time	NOUN
fcis-29392	72	5	,	,	PUNCT
fcis-29392	72	6	jump	jump	NOUN
fcis-29392	72	7	connections	connection	NOUN
fcis-29392	72	8	are	be	AUX
fcis-29392	72	9	added	add	VERB
fcis-29392	72	10	after	after	ADP
fcis-29392	72	11	cbam	cbam	NOUN
fcis-29392	72	12	to	to	PART
fcis-29392	72	13	preserve	preserve	VERB
fcis-29392	72	14	the	the	DET
fcis-29392	72	15	output	output	NOUN
fcis-29392	72	16	features	feature	NOUN
fcis-29392	72	17	in	in	ADP
fcis-29392	72	18	the	the	DET
fcis-29392	72	19	original	original	ADJ
fcis-29392	72	20	network	network	NOUN
fcis-29392	72	21	,	,	PUNCT
fcis-29392	72	22	and	and	CCONJ
fcis-29392	72	23	the	the	DET
fcis-29392	72	24	information	information	NOUN
fcis-29392	72	25	is	be	AUX
fcis-29392	72	26	more	more	ADV
fcis-29392	72	27	easily	easily	ADV
fcis-29392	72	28	propagated	propagate	VERB
fcis-29392	72	29	to	to	ADP
fcis-29392	72	30	the	the	DET
fcis-29392	72	31	later	later	ADJ
fcis-29392	72	32	networks	network	NOUN
fcis-29392	72	33	to	to	PART
fcis-29392	72	34	avoid	avoid	VERB
fcis-29392	72	35	information	information	NOUN
fcis-29392	72	36	loss	loss	NOUN
fcis-29392	72	37	.	.	PUNCT
fcis-29392	73	1	4	4	X
fcis-29392	73	2	.	.	X
fcis-29392	73	3	experimental	experimental	ADJ
fcis-29392	73	4	results	result	NOUN
fcis-29392	73	5	and	and	CCONJ
fcis-29392	73	6	analysis	analysis	NOUN
fcis-29392	73	7	4.1	4.1	NUM
fcis-29392	73	8	.	.	PUNCT
fcis-29392	74	1	introduction	introduction	NOUN
fcis-29392	74	2	to	to	ADP
fcis-29392	74	3	the	the	DET
fcis-29392	74	4	dataset	dataset	NOUN
fcis-29392	74	5	in	in	ADP
fcis-29392	74	6	this	this	DET
fcis-29392	74	7	study	study	NOUN
fcis-29392	74	8	,	,	PUNCT
fcis-29392	74	9	we	we	PRON
fcis-29392	74	10	used	use	VERB
fcis-29392	74	11	a	a	DET
fcis-29392	74	12	dataset	dataset	NOUN
fcis-29392	74	13	from	from	ADP
fcis-29392	74	14	the	the	DET
fcis-29392	74	15	corn	corn	NOUN
fcis-29392	74	16	weed	weed	NOUN
fcis-29392	74	17	dataset	dataset	NOUN
fcis-29392	74	18	that	that	PRON
fcis-29392	74	19	is	be	AUX
fcis-29392	74	20	publicly	publicly	ADV
fcis-29392	74	21	available	available	ADJ
fcis-29392	74	22	online	online	ADV
fcis-29392	75	1	[	[	X
fcis-29392	75	2	18	18	NUM
fcis-29392	75	3	]	]	PUNCT
fcis-29392	75	4	,	,	PUNCT
fcis-29392	75	5	and	and	CCONJ
fcis-29392	75	6	changed	change	VERB
fcis-29392	75	7	the	the	DET
fcis-29392	75	8	dataset	dataset	NOUN
fcis-29392	75	9	to	to	PART
fcis-29392	75	10	have	have	VERB
fcis-29392	75	11	five	five	NUM
fcis-29392	75	12	categories	category	NOUN
fcis-29392	75	13	,	,	PUNCT
fcis-29392	75	14	which	which	PRON
fcis-29392	75	15	were	be	AUX
fcis-29392	75	16	taken	take	VERB
fcis-29392	75	17	from	from	ADP
fcis-29392	75	18	the	the	DET
fcis-29392	75	19	natural	natural	ADJ
fcis-29392	75	20	environment	environment	NOUN
fcis-29392	75	21	of	of	ADP
fcis-29392	75	22	corn	corn	NOUN
fcis-29392	75	23	seedling	seedling	NOUN
fcis-29392	75	24	field	field	NOUN
fcis-29392	75	25	,	,	PUNCT
fcis-29392	75	26	and	and	CCONJ
fcis-29392	75	27	images	image	NOUN
fcis-29392	75	28	were	be	AUX
fcis-29392	75	29	collected	collect	VERB
fcis-29392	75	30	under	under	ADP
fcis-29392	75	31	different	different	ADJ
fcis-29392	75	32	soil	soil	NOUN
fcis-29392	75	33	background	background	NOUN
fcis-29392	75	34	and	and	CCONJ
fcis-29392	75	35	sunlight	sunlight	NOUN
fcis-29392	75	36	conditions	condition	NOUN
fcis-29392	75	37	.	.	PUNCT
fcis-29392	76	1	the	the	DET
fcis-29392	76	2	dataset	dataset	NOUN
fcis-29392	76	3	contains	contain	VERB
fcis-29392	76	4	maize	maize	NOUN
fcis-29392	76	5	seedlings	seedling	NOUN
fcis-29392	76	6	with	with	ADP
fcis-29392	76	7	four	four	NUM
fcis-29392	76	8	common	common	ADJ
fcis-29392	76	9	weeds	weed	NOUN
fcis-29392	76	10	such	such	ADJ
fcis-29392	76	11	as	as	ADP
fcis-29392	76	12	prickly	prickly	ADJ
fcis-29392	76	13	adelgid	adelgid	ADJ
fcis-29392	76	14	,	,	PUNCT
fcis-29392	76	15	sedge	sedge	NOUN
fcis-29392	76	16	,	,	PUNCT
fcis-29392	76	17	quinoa	quinoa	NOUN
fcis-29392	76	18	and	and	CCONJ
fcis-29392	76	19	early	early	ADJ
fcis-29392	76	20	morning	morning	NOUN
fcis-29392	76	21	glory	glory	NOUN
fcis-29392	76	22	,	,	PUNCT
fcis-29392	76	23	a	a	DET
fcis-29392	76	24	total	total	NOUN
fcis-29392	76	25	of	of	ADP
fcis-29392	76	26	5	5	NUM
fcis-29392	76	27	medium	medium	ADJ
fcis-29392	76	28	field	field	NOUN
fcis-29392	76	29	plants	plant	NOUN
fcis-29392	76	30	,	,	PUNCT
fcis-29392	76	31	and	and	CCONJ
fcis-29392	76	32	the	the	DET
fcis-29392	76	33	image	image	NOUN
fcis-29392	76	34	size	size	NOUN
fcis-29392	76	35	is	be	AUX
fcis-29392	76	36	800	800	NUM
fcis-29392	76	37	×	×	NOUN
fcis-29392	76	38	600.meanwhile	600.meanwhile	NOUN
fcis-29392	76	39	,	,	PUNCT
fcis-29392	76	40	in	in	ADP
fcis-29392	76	41	order	order	NOUN
fcis-29392	76	42	to	to	PART
fcis-29392	76	43	make	make	VERB
fcis-29392	76	44	the	the	DET
fcis-29392	76	45	model	model	NOUN
fcis-29392	76	46	learn	learn	VERB
fcis-29392	76	47	a	a	DET
fcis-29392	76	48	good	good	ADJ
fcis-29392	76	49	characterization	characterization	NOUN
fcis-29392	76	50	,	,	PUNCT
fcis-29392	76	51	the	the	DET
fcis-29392	76	52	dataset	dataset	NOUN
fcis-29392	76	53	is	be	AUX
fcis-29392	76	54	subjected	subject	VERB
fcis-29392	76	55	to	to	ADP
fcis-29392	76	56	data	datum	NOUN
fcis-29392	76	57	enhancement	enhancement	NOUN
fcis-29392	76	58	.	.	PUNCT
fcis-29392	77	1	the	the	DET
fcis-29392	77	2	diversity	diversity	NOUN
fcis-29392	77	3	of	of	ADP
fcis-29392	77	4	data	datum	NOUN
fcis-29392	77	5	samples	sample	NOUN
fcis-29392	77	6	is	be	AUX
fcis-29392	77	7	improved	improve	VERB
fcis-29392	77	8	by	by	ADP
fcis-29392	77	9	flipping	flip	VERB
fcis-29392	77	10	,	,	PUNCT
fcis-29392	77	11	rotating	rotate	VERB
fcis-29392	77	12	,	,	PUNCT
fcis-29392	77	13	changing	change	VERB
fcis-29392	77	14	contrast	contrast	NOUN
fcis-29392	77	15	,	,	PUNCT
fcis-29392	77	16	adding	add	VERB
fcis-29392	77	17	noise	noise	NOUN
fcis-29392	77	18	and	and	CCONJ
fcis-29392	77	19	other	other	ADJ
fcis-29392	77	20	operations	operation	NOUN
fcis-29392	77	21	on	on	ADP
fcis-29392	77	22	the	the	DET
fcis-29392	77	23	graphs	graph	NOUN
fcis-29392	77	24	to	to	PART
fcis-29392	77	25	reduce	reduce	VERB
fcis-29392	77	26	the	the	DET
fcis-29392	77	27	network	network	NOUN
fcis-29392	77	28	overfitting	overfitte	VERB
fcis-29392	77	29	phenomenon	phenomenon	NOUN
fcis-29392	77	30	.	.	PUNCT
fcis-29392	78	1	the	the	DET
fcis-29392	78	2	image	image	NOUN
fcis-29392	78	3	enhancement	enhancement	NOUN
fcis-29392	78	4	result	result	NOUN
fcis-29392	78	5	is	be	AUX
fcis-29392	78	6	shown	show	VERB
fcis-29392	78	7	in	in	ADP
fcis-29392	78	8	fig	fig	NOUN
fcis-29392	78	9	.	.	PUNCT
fcis-29392	79	1	4	4	NUM
fcis-29392	79	2	:	:	SYM
fcis-29392	79	3	4.2	4.2	NUM
fcis-29392	79	4	.	.	PUNCT
fcis-29392	79	5	assessment	assessment	NOUN
fcis-29392	79	6	of	of	ADP
fcis-29392	79	7	indicators	indicator	NOUN
fcis-29392	79	8	in	in	ADP
fcis-29392	79	9	this	this	DET
fcis-29392	79	10	paper	paper	NOUN
fcis-29392	79	11	,	,	PUNCT
fcis-29392	79	12	we	we	PRON
fcis-29392	79	13	use	use	VERB
fcis-29392	79	14	map	map	NOUN
fcis-29392	79	15	(	(	PUNCT
fcis-29392	79	16	mean	mean	ADJ
fcis-29392	79	17	average	average	ADJ
fcis-29392	79	18	precison	precison	NOUN
fcis-29392	79	19	)	)	PUNCT
fcis-29392	79	20	as	as	ADP
fcis-29392	79	21	the	the	DET
fcis-29392	79	22	evaluation	evaluation	NOUN
fcis-29392	79	23	metrics	metric	NOUN
fcis-29392	79	24	of	of	ADP
fcis-29392	79	25	algorithm	algorithm	NOUN
fcis-29392	79	26	accuracy	accuracy	NOUN
fcis-29392	79	27	.	.	PUNCT
fcis-29392	80	1	map	map	NOUN
fcis-29392	80	2	(	(	PUNCT
fcis-29392	80	3	mean	mean	VERB
fcis-29392	80	4	average	average	ADJ
fcis-29392	80	5	precision	precision	NOUN
fcis-29392	80	6	)	)	PUNCT
fcis-29392	80	7	is	be	AUX
fcis-29392	80	8	one	one	NUM
fcis-29392	80	9	of	of	ADP
fcis-29392	80	10	the	the	DET
fcis-29392	80	11	most	most	ADV
fcis-29392	80	12	common	common	ADJ
fcis-29392	80	13	evaluation	evaluation	NOUN
fcis-29392	80	14	metrics	metric	NOUN
fcis-29392	80	15	in	in	ADP
fcis-29392	80	16	the	the	DET
fcis-29392	80	17	task	task	NOUN
fcis-29392	80	18	of	of	ADP
fcis-29392	80	19	target	target	NOUN
fcis-29392	80	20	detection	detection	NOUN
fcis-29392	80	21	,	,	PUNCT
fcis-29392	80	22	which	which	PRON
fcis-29392	80	23	indicates	indicate	VERB
fcis-29392	80	24	the	the	DET
fcis-29392	80	25	average	average	NOUN
fcis-29392	80	26	of	of	ADP
fcis-29392	80	27	the	the	DET
fcis-29392	80	28	detection	detection	NOUN
fcis-29392	80	29	precision	precision	NOUN
fcis-29392	80	30	(	(	PUNCT
fcis-29392	80	31	ap	ap	PROPN
fcis-29392	80	32	)	)	PUNCT
fcis-29392	80	33	of	of	ADP
fcis-29392	80	34	each	each	DET
fcis-29392	80	35	category	category	NOUN
fcis-29392	80	36	in	in	ADP
fcis-29392	80	37	the	the	DET
fcis-29392	80	38	dataset	dataset	NOUN
fcis-29392	80	39	,	,	PUNCT
fcis-29392	80	40	which	which	PRON
fcis-29392	80	41	can	can	AUX
fcis-29392	80	42	reflect	reflect	VERB
fcis-29392	80	43	the	the	DET
fcis-29392	80	44	average	average	ADJ
fcis-29392	80	45	accuracy	accuracy	NOUN
fcis-29392	80	46	performance	performance	NOUN
fcis-29392	80	47	of	of	ADP
fcis-29392	80	48	the	the	DET
fcis-29392	80	49	model	model	NOUN
fcis-29392	80	50	on	on	ADP
fcis-29392	80	51	all	all	DET
fcis-29392	80	52	categories	category	NOUN
fcis-29392	80	53	and	and	CCONJ
fcis-29392	80	54	measure	measure	VERB
fcis-29392	80	55	the	the	DET
fcis-29392	80	56	comprehensive	comprehensive	ADJ
fcis-29392	80	57	performance	performance	NOUN
fcis-29392	80	58	of	of	ADP
fcis-29392	80	59	the	the	DET
fcis-29392	80	60	model	model	NOUN
fcis-29392	80	61	.	.	PUNCT
fcis-29392	81	1	the	the	DET
fcis-29392	81	2	above	above	ADJ
fcis-29392	81	3	evaluation	evaluation	NOUN
fcis-29392	81	4	metrics	metric	NOUN
fcis-29392	81	5	have	have	AUX
fcis-29392	81	6	formulas	formula	NOUN
fcis-29392	81	7	calculated	calculate	VERB
fcis-29392	81	8	as	as	SCONJ
fcis-29392	81	9	shown	show	VERB
fcis-29392	81	10	in	in	ADP
fcis-29392	81	11	(	(	PUNCT
fcis-29392	81	12	6)(9	6)(9	NUM
fcis-29392	81	13	):	):	PUNCT
fcis-29392	81	14	p	p	X
fcis-29392	81	15	(	(	PUNCT
fcis-29392	81	16	6	6	NUM
fcis-29392	81	17	)	)	PUNCT
fcis-29392	81	18	r	r	NOUN
fcis-29392	81	19	(	(	PUNCT
fcis-29392	81	20	7	7	NUM
fcis-29392	81	21	)	)	PUNCT
fcis-29392	81	22	ap	ap	NOUN
fcis-29392	81	23	(	(	PUNCT
fcis-29392	81	24	8)	8)	NUM
fcis-29392	81	25	map	map	NOUN
fcis-29392	81	26	∑	∑	INTJ
fcis-29392	81	27	(	(	PUNCT
fcis-29392	81	28	9	9	NUM
fcis-29392	81	29	)	)	SYM
fcis-29392	81	30	100	100	NUM
fcis-29392	81	31	(	(	PUNCT
fcis-29392	81	32	a	a	X
fcis-29392	81	33	)	)	PUNCT
fcis-29392	81	34	image	image	NOUN
fcis-29392	81	35	rotation	rotation	NOUN
fcis-29392	81	36	(	(	PUNCT
fcis-29392	81	37	b	b	NOUN
fcis-29392	81	38	)	)	PUNCT
fcis-29392	81	39	image	image	NOUN
fcis-29392	81	40	contrast	contrast	NOUN
fcis-29392	81	41	enhancement	enhancement	NOUN
fcis-29392	81	42	(	(	PUNCT
fcis-29392	81	43	c	c	X
fcis-29392	81	44	)	)	PUNCT
fcis-29392	81	45	add	add	VERB
fcis-29392	81	46	noise	noise	NOUN
fcis-29392	81	47	(	(	PUNCT
fcis-29392	81	48	d	d	NOUN
fcis-29392	81	49	)	)	PUNCT
fcis-29392	81	50	image	image	NOUN
fcis-29392	81	51	stitching	stitching	NOUN
fcis-29392	81	52	fig	fig	NOUN
fcis-29392	81	53	4	4	NUM
fcis-29392	81	54	.	.	PUNCT
fcis-29392	81	55	data	datum	NOUN
fcis-29392	81	56	enhancement	enhancement	NOUN
fcis-29392	81	57	in	in	ADP
fcis-29392	81	58	the	the	DET
fcis-29392	81	59	above	above	ADJ
fcis-29392	81	60	equation	equation	NOUN
fcis-29392	81	61	:	:	PUNCT
fcis-29392	81	62	the	the	DET
fcis-29392	81	63	number	number	NOUN
fcis-29392	81	64	of	of	ADP
fcis-29392	81	65	positive	positive	ADJ
fcis-29392	81	66	samples	sample	NOUN
fcis-29392	81	67	predicted	predict	VERB
fcis-29392	81	68	to	to	PART
fcis-29392	81	69	be	be	AUX
fcis-29392	81	70	in	in	ADP
fcis-29392	81	71	the	the	DET
fcis-29392	81	72	positive	positive	ADJ
fcis-29392	81	73	category	category	NOUN
fcis-29392	81	74	,	,	PUNCT
fcis-29392	81	75	the	the	DET
fcis-29392	81	76	number	number	NOUN
fcis-29392	81	77	of	of	ADP
fcis-29392	81	78	negative	negative	ADJ
fcis-29392	81	79	samples	sample	NOUN
fcis-29392	81	80	predicted	predict	VERB
fcis-29392	81	81	to	to	PART
fcis-29392	81	82	be	be	AUX
fcis-29392	81	83	in	in	ADP
fcis-29392	81	84	the	the	DET
fcis-29392	81	85	positive	positive	ADJ
fcis-29392	81	86	category	category	NOUN
fcis-29392	81	87	,	,	PUNCT
fcis-29392	81	88	and	and	CCONJ
fcis-29392	81	89	the	the	DET
fcis-29392	81	90	number	number	NOUN
fcis-29392	81	91	of	of	ADP
fcis-29392	81	92	positive	positive	ADJ
fcis-29392	81	93	samples	sample	NOUN
fcis-29392	81	94	predicted	predict	VERB
fcis-29392	81	95	to	to	PART
fcis-29392	81	96	be	be	AUX
fcis-29392	81	97	in	in	ADP
fcis-29392	81	98	the	the	DET
fcis-29392	81	99	negative	negative	ADJ
fcis-29392	81	100	category	category	NOUN
fcis-29392	81	101	for	for	ADP
fcis-29392	81	102	tp	tp	NOUN
fcis-29392	81	103	,	,	PUNCT
fcis-29392	81	104	fp	fp	X
fcis-29392	81	105	,	,	PUNCT
fcis-29392	81	106	and	and	CCONJ
fcis-29392	81	107	fn	fn	NOUN
fcis-29392	81	108	,	,	PUNCT
fcis-29392	81	109	respectively	respectively	ADV
fcis-29392	81	110	,	,	PUNCT
fcis-29392	81	111	p	p	NOUN
fcis-29392	81	112	denotes	denote	VERB
fcis-29392	81	113	the	the	DET
fcis-29392	81	114	precision	precision	NOUN
fcis-29392	81	115	rate	rate	NOUN
fcis-29392	81	116	,	,	PUNCT
fcis-29392	81	117	i.e.	i.e.	X
fcis-29392	81	118	,	,	PUNCT
fcis-29392	81	119	the	the	DET
fcis-29392	81	120	proportion	proportion	NOUN
fcis-29392	81	121	of	of	ADP
fcis-29392	81	122	actual	actual	ADJ
fcis-29392	81	123	positive	positive	ADJ
fcis-29392	81	124	samples	sample	NOUN
fcis-29392	81	125	among	among	ADP
fcis-29392	81	126	the	the	DET
fcis-29392	81	127	results	result	NOUN
fcis-29392	81	128	predicted	predict	VERB
fcis-29392	81	129	to	to	PART
fcis-29392	81	130	be	be	AUX
fcis-29392	81	131	positive	positive	ADJ
fcis-29392	81	132	samples	sample	NOUN
fcis-29392	81	133	,	,	PUNCT
fcis-29392	81	134	and	and	CCONJ
fcis-29392	81	135	r	r	NOUN
fcis-29392	81	136	stands	stand	VERB
fcis-29392	81	137	for	for	ADP
fcis-29392	81	138	the	the	DET
fcis-29392	81	139	recall	recall	NOUN
fcis-29392	81	140	rate	rate	NOUN
fcis-29392	81	141	,	,	PUNCT
fcis-29392	81	142	which	which	PRON
fcis-29392	81	143	denotes	denote	VERB
fcis-29392	81	144	the	the	DET
fcis-29392	81	145	proportion	proportion	NOUN
fcis-29392	81	146	of	of	ADP
fcis-29392	81	147	positive	positive	ADJ
fcis-29392	81	148	samples	sample	NOUN
fcis-29392	81	149	correctly	correctly	ADV
fcis-29392	81	150	detected	detect	VERB
fcis-29392	81	151	by	by	ADP
fcis-29392	81	152	the	the	DET
fcis-29392	81	153	model	model	NOUN
fcis-29392	81	154	as	as	ADP
fcis-29392	81	155	positive	positive	ADJ
fcis-29392	81	156	samples	sample	NOUN
fcis-29392	81	157	out	out	ADP
fcis-29392	81	158	of	of	ADP
fcis-29392	81	159	the	the	DET
fcis-29392	81	160	positive	positive	ADJ
fcis-29392	81	161	samples	sample	NOUN
fcis-29392	81	162	used	use	VERB
fcis-29392	81	163	in	in	ADP
fcis-29392	81	164	the	the	DET
fcis-29392	81	165	test	test	NOUN
fcis-29392	81	166	set	set	NOUN
fcis-29392	81	167	.	.	PUNCT
fcis-29392	82	1	4.3	4.3	NUM
fcis-29392	82	2	.	.	PUNCT
fcis-29392	82	3	results	result	VERB
fcis-29392	82	4	the	the	DET
fcis-29392	82	5	gpu	gpu	NOUN
fcis-29392	82	6	used	use	VERB
fcis-29392	82	7	in	in	ADP
fcis-29392	82	8	this	this	DET
fcis-29392	82	9	experiment	experiment	NOUN
fcis-29392	82	10	is	be	AUX
fcis-29392	82	11	rtx3090	rtx3090	NOUN
fcis-29392	82	12	,	,	PUNCT
fcis-29392	82	13	the	the	DET
fcis-29392	82	14	python	python	NOUN
fcis-29392	82	15	version	version	NOUN
fcis-29392	82	16	is	be	AUX
fcis-29392	82	17	3.8	3.8	NUM
fcis-29392	82	18	,	,	PUNCT
fcis-29392	82	19	and	and	CCONJ
fcis-29392	82	20	the	the	DET
fcis-29392	82	21	deep	deep	ADJ
fcis-29392	82	22	learning	learning	NOUN
fcis-29392	82	23	framework	framework	NOUN
fcis-29392	82	24	is	be	AUX
fcis-29392	82	25	pytorch	pytorch	NOUN
fcis-29392	82	26	,	,	PUNCT
fcis-29392	82	27	version	version	NOUN
fcis-29392	82	28	1.11	1.11	NUM
fcis-29392	82	29	.	.	PUNCT
fcis-29392	83	1	during	during	ADP
fcis-29392	83	2	the	the	DET
fcis-29392	83	3	training	training	NOUN
fcis-29392	83	4	process	process	NOUN
fcis-29392	83	5	,	,	PUNCT
fcis-29392	83	6	in	in	ADP
fcis-29392	83	7	order	order	NOUN
fcis-29392	83	8	to	to	PART
fcis-29392	83	9	evaluate	evaluate	VERB
fcis-29392	83	10	the	the	DET
fcis-29392	83	11	performance	performance	NOUN
fcis-29392	83	12	of	of	ADP
fcis-29392	83	13	the	the	DET
fcis-29392	83	14	models	model	NOUN
fcis-29392	83	15	more	more	ADV
fcis-29392	83	16	comprehensively	comprehensively	ADV
fcis-29392	83	17	,	,	PUNCT
fcis-29392	83	18	we	we	PRON
fcis-29392	83	19	performed	perform	VERB
fcis-29392	83	20	a	a	DET
fcis-29392	83	21	validation	validation	NOUN
fcis-29392	83	22	evaluation	evaluation	NOUN
fcis-29392	83	23	of	of	ADP
fcis-29392	83	24	the	the	DET
fcis-29392	83	25	models	model	NOUN
fcis-29392	83	26	after	after	ADP
fcis-29392	83	27	every	every	DET
fcis-29392	83	28	10	10	NUM
fcis-29392	83	29	epochs	epoch	NOUN
fcis-29392	83	30	and	and	CCONJ
fcis-29392	83	31	recorded	record	VERB
fcis-29392	83	32	the	the	DET
fcis-29392	83	33	map	map	NOUN
fcis-29392	83	34	change	change	VERB
fcis-29392	83	35	curves	curve	NOUN
fcis-29392	83	36	of	of	ADP
fcis-29392	83	37	each	each	DET
fcis-29392	83	38	model	model	NOUN
fcis-29392	83	39	in	in	ADP
fcis-29392	83	40	figure	figure	NOUN
fcis-29392	83	41	5	5	NUM
fcis-29392	83	42	.	.	PUNCT
fcis-29392	83	43	according	accord	VERB
fcis-29392	83	44	to	to	ADP
fcis-29392	83	45	the	the	DET
fcis-29392	83	46	map	map	NOUN
fcis-29392	83	47	change	change	VERB
fcis-29392	83	48	curves	curve	NOUN
fcis-29392	83	49	of	of	ADP
fcis-29392	83	50	the	the	DET
fcis-29392	83	51	models	model	NOUN
fcis-29392	83	52	plotted	plot	VERB
fcis-29392	83	53	in	in	ADP
fcis-29392	83	54	fig	fig	NOUN
fcis-29392	83	55	.	.	PUNCT
fcis-29392	84	1	5	5	NUM
fcis-29392	84	2	,	,	PUNCT
fcis-29392	84	3	we	we	PRON
fcis-29392	84	4	can	can	AUX
fcis-29392	84	5	see	see	VERB
fcis-29392	84	6	the	the	DET
fcis-29392	84	7	impact	impact	NOUN
fcis-29392	84	8	of	of	ADP
fcis-29392	84	9	different	different	ADJ
fcis-29392	84	10	algorithms	algorithm	NOUN
fcis-29392	84	11	on	on	ADP
fcis-29392	84	12	the	the	DET
fcis-29392	84	13	model	model	NOUN
fcis-29392	84	14	performance	performance	NOUN
fcis-29392	84	15	.	.	PUNCT
fcis-29392	85	1	by	by	ADP
fcis-29392	85	2	introducing	introduce	VERB
fcis-29392	85	3	the	the	DET
fcis-29392	85	4	convolutional	convolutional	ADJ
fcis-29392	85	5	block	block	NOUN
fcis-29392	85	6	attention	attention	NOUN
fcis-29392	85	7	mechanism	mechanism	NOUN
fcis-29392	85	8	(	(	PUNCT
fcis-29392	85	9	cbam	cbam	NOUN
fcis-29392	85	10	)	)	PUNCT
fcis-29392	85	11	and	and	CCONJ
fcis-29392	85	12	focal	focal	ADJ
fcis-29392	85	13	loss	loss	NOUN
fcis-29392	85	14	,	,	PUNCT
fcis-29392	85	15	the	the	DET
fcis-29392	85	16	map	map	NOUN
fcis-29392	85	17	of	of	ADP
fcis-29392	85	18	the	the	DET
fcis-29392	85	19	models	model	NOUN
fcis-29392	85	20	both	both	CCONJ
fcis-29392	85	21	achieved	achieve	VERB
fcis-29392	85	22	better	well	ADJ
fcis-29392	85	23	results	result	NOUN
fcis-29392	85	24	compared	compare	VERB
fcis-29392	85	25	to	to	ADP
fcis-29392	85	26	the	the	DET
fcis-29392	85	27	original	original	ADJ
fcis-29392	85	28	model	model	NOUN
fcis-29392	85	29	at	at	ADP
fcis-29392	85	30	the	the	DET
fcis-29392	85	31	final	final	ADJ
fcis-29392	85	32	convergence	convergence	NOUN
fcis-29392	85	33	stage	stage	NOUN
fcis-29392	85	34	.	.	PUNCT
fcis-29392	86	1	in	in	ADP
fcis-29392	86	2	order	order	NOUN
fcis-29392	86	3	to	to	PART
fcis-29392	86	4	show	show	VERB
fcis-29392	86	5	the	the	DET
fcis-29392	86	6	effect	effect	NOUN
fcis-29392	86	7	of	of	ADP
fcis-29392	86	8	the	the	DET
fcis-29392	86	9	models	model	NOUN
fcis-29392	86	10	in	in	ADP
fcis-29392	86	11	the	the	DET
fcis-29392	86	12	training	training	NOUN
fcis-29392	86	13	process	process	NOUN
fcis-29392	86	14	more	more	ADV
fcis-29392	86	15	clearly	clearly	ADV
fcis-29392	86	16	,	,	PUNCT
fcis-29392	86	17	table	table	NOUN
fcis-29392	86	18	1	1	NUM
fcis-29392	86	19	lists	list	VERB
fcis-29392	86	20	the	the	DET
fcis-29392	86	21	best	good	ADJ
fcis-29392	86	22	map	map	NOUN
fcis-29392	86	23	values	value	NOUN
fcis-29392	86	24	achieved	achieve	VERB
fcis-29392	86	25	by	by	ADP
fcis-29392	86	26	each	each	DET
fcis-29392	86	27	model	model	NOUN
fcis-29392	86	28	in	in	ADP
fcis-29392	86	29	the	the	DET
fcis-29392	86	30	evaluation	evaluation	NOUN
fcis-29392	86	31	process	process	NOUN
fcis-29392	86	32	.	.	PUNCT
fcis-29392	87	1	based	base	VERB
fcis-29392	87	2	on	on	ADP
fcis-29392	87	3	the	the	DET
fcis-29392	87	4	contents	content	NOUN
fcis-29392	87	5	of	of	ADP
fcis-29392	87	6	table	table	NOUN
fcis-29392	87	7	1	1	NUM
fcis-29392	87	8	,	,	PUNCT
fcis-29392	87	9	it	it	PRON
fcis-29392	87	10	can	can	AUX
fcis-29392	87	11	be	be	AUX
fcis-29392	87	12	known	know	VERB
fcis-29392	87	13	that	that	SCONJ
fcis-29392	87	14	the	the	DET
fcis-29392	87	15	incorporation	incorporation	NOUN
fcis-29392	87	16	of	of	ADP
fcis-29392	87	17	the	the	DET
fcis-29392	87	18	cbam	cbam	NOUN
fcis-29392	87	19	attention	attention	NOUN
fcis-29392	87	20	mechanism	mechanism	NOUN
fcis-29392	87	21	and	and	CCONJ
fcis-29392	87	22	the	the	DET
fcis-29392	87	23	focus	focus	NOUN
fcis-29392	87	24	loss	loss	NOUN
fcis-29392	87	25	function	function	NOUN
fcis-29392	87	26	achieved	achieve	VERB
fcis-29392	87	27	the	the	DET
fcis-29392	87	28	best	good	ADJ
fcis-29392	87	29	test	test	NOUN
fcis-29392	87	30	results	result	NOUN
fcis-29392	87	31	in	in	ADP
fcis-29392	87	32	the	the	DET
fcis-29392	87	33	dataset	dataset	NOUN
fcis-29392	87	34	,	,	PUNCT
fcis-29392	87	35	with	with	ADP
fcis-29392	87	36	an	an	DET
fcis-29392	87	37	improvement	improvement	NOUN
fcis-29392	87	38	of	of	ADP
fcis-29392	87	39	1.12	1.12	NUM
fcis-29392	87	40	%	%	NOUN
fcis-29392	87	41	compared	compare	VERB
fcis-29392	87	42	to	to	ADP
fcis-29392	87	43	the	the	DET
fcis-29392	87	44	original	original	ADJ
fcis-29392	87	45	model	model	NOUN
fcis-29392	87	46	of	of	ADP
fcis-29392	87	47	detr	detr	NOUN
fcis-29392	87	48	,	,	PUNCT
fcis-29392	87	49	and	and	CCONJ
fcis-29392	87	50	this	this	DET
fcis-29392	87	51	enhancement	enhancement	NOUN
fcis-29392	87	52	suggests	suggest	VERB
fcis-29392	87	53	that	that	SCONJ
fcis-29392	87	54	the	the	DET
fcis-29392	87	55	cbam	cbam	NOUN
fcis-29392	87	56	attention	attention	NOUN
fcis-29392	87	57	mechanism	mechanism	NOUN
fcis-29392	87	58	and	and	CCONJ
fcis-29392	87	59	the	the	DET
fcis-29392	87	60	focus	focus	NOUN
fcis-29392	87	61	loss	loss	NOUN
fcis-29392	87	62	function	function	NOUN
fcis-29392	87	63	play	play	VERB
fcis-29392	87	64	an	an	DET
fcis-29392	87	65	obvious	obvious	ADJ
fcis-29392	87	66	role	role	NOUN
fcis-29392	87	67	in	in	ADP
fcis-29392	87	68	improving	improve	VERB
fcis-29392	87	69	the	the	DET
fcis-29392	87	70	model	model	NOUN
fcis-29392	87	71	performance	performance	NOUN
fcis-29392	87	72	.	.	PUNCT
fcis-29392	88	1	fig	fig	NOUN
fcis-29392	88	2	5	5	NUM
fcis-29392	88	3	.	.	X
fcis-29392	88	4	map	map	VERB
fcis-29392	88	5	change	change	NOUN
fcis-29392	88	6	curve	curve	NOUN
fcis-29392	88	7	table	table	NOUN
fcis-29392	88	8	1	1	NUM
fcis-29392	88	9	.	.	PUNCT
fcis-29392	88	10	results	result	NOUN
fcis-29392	88	11	of	of	ADP
fcis-29392	88	12	detr	detr	NOUN
fcis-29392	88	13	experiments	experiment	NOUN
fcis-29392	88	14	focal	focal	ADJ
fcis-29392	88	15	loss	loss	NOUN
fcis-29392	88	16	cbam	cbam	NOUN
fcis-29392	88	17	map	map	NOUN
fcis-29392	88	18	detr	detr	PROPN
fcis-29392	88	19	90.44	90.44	NUM
fcis-29392	88	20	√	√	NUM
fcis-29392	88	21	90.96	90.96	NUM
fcis-29392	88	22	√	√	PROPN
fcis-29392	88	23	√	√	ADP
fcis-29392	88	24	91.56	91.56	NUM
fcis-29392	88	25	(	(	PUNCT
fcis-29392	88	26	a	a	NOUN
fcis-29392	88	27	)	)	PUNCT
fcis-29392	88	28	(	(	PUNCT
fcis-29392	88	29	b	b	X
fcis-29392	88	30	)	)	PUNCT
fcis-29392	88	31	fig	fig	NOUN
fcis-29392	88	32	6	6	NUM
fcis-29392	88	33	.	.	PUNCT
fcis-29392	88	34	model	model	NOUN
fcis-29392	88	35	detection	detection	NOUN
fcis-29392	88	36	results	result	VERB
fcis-29392	88	37	fig	fig	NOUN
fcis-29392	88	38	.	.	PUNCT
fcis-29392	89	1	6	6	NUM
fcis-29392	89	2	shows	show	VERB
fcis-29392	89	3	the	the	DET
fcis-29392	89	4	test	test	NOUN
fcis-29392	89	5	results	result	NOUN
fcis-29392	89	6	of	of	ADP
fcis-29392	89	7	the	the	DET
fcis-29392	89	8	original	original	ADJ
fcis-29392	89	9	detr	detr	NOUN
fcis-29392	89	10	model	model	NOUN
fcis-29392	89	11	and	and	CCONJ
fcis-29392	89	12	the	the	DET
fcis-29392	89	13	improved	improved	ADJ
fcis-29392	89	14	model	model	NOUN
fcis-29392	89	15	on	on	ADP
fcis-29392	89	16	the	the	DET
fcis-29392	89	17	test	test	NOUN
fcis-29392	89	18	set	set	NOUN
fcis-29392	89	19	,	,	PUNCT
fcis-29392	89	20	and	and	CCONJ
fcis-29392	89	21	four	four	NUM
fcis-29392	89	22	images	image	NOUN
fcis-29392	89	23	are	be	AUX
fcis-29392	89	24	selected	select	VERB
fcis-29392	89	25	to	to	PART
fcis-29392	89	26	compare	compare	VERB
fcis-29392	89	27	the	the	DET
fcis-29392	89	28	performance	performance	NOUN
fcis-29392	89	29	of	of	ADP
fcis-29392	89	30	the	the	DET
fcis-29392	89	31	models	model	NOUN
fcis-29392	89	32	.	.	PUNCT
fcis-29392	90	1	fig	fig	NOUN
fcis-29392	90	2	.	.	PUNCT
fcis-29392	91	1	6(a	6(a	NUM
fcis-29392	91	2	)	)	PUNCT
fcis-29392	91	3	0	0	NUM
fcis-29392	91	4	50	50	NUM
fcis-29392	91	5	100	100	NUM
fcis-29392	91	6	150	150	NUM
fcis-29392	91	7	200	200	NUM
fcis-29392	91	8	250	250	NUM
fcis-29392	91	9	300	300	NUM
fcis-29392	91	10	0.0	0.0	NUM
fcis-29392	91	11	0.2	0.2	NUM
fcis-29392	91	12	0.4	0.4	NUM
fcis-29392	91	13	0.6	0.6	NUM
fcis-29392	91	14	0.8	0.8	NUM
fcis-29392	91	15	1.0	1.0	NUM
fcis-29392	91	16	m	m	NOUN
fcis-29392	91	17	ap	ap	PROPN
fcis-29392	91	18	epoch	epoch	PROPN
fcis-29392	91	19	detr+fl+cbam	detr+fl+cbam	PROPN
fcis-29392	91	20	detr+fl	detr+fl	X
fcis-29392	91	21	detr	detr	PROPN
fcis-29392	91	22	101	101	NUM
fcis-29392	91	23	shows	show	VERB
fcis-29392	91	24	the	the	DET
fcis-29392	91	25	test	test	NOUN
fcis-29392	91	26	results	result	NOUN
fcis-29392	91	27	of	of	ADP
fcis-29392	91	28	the	the	DET
fcis-29392	91	29	detr	detr	NOUN
fcis-29392	91	30	model	model	NOUN
fcis-29392	91	31	and	and	CCONJ
fcis-29392	91	32	fig	fig	NOUN
fcis-29392	91	33	.	.	PUNCT
fcis-29392	92	1	6(b	6(b	NUM
fcis-29392	92	2	)	)	PUNCT
fcis-29392	92	3	shows	show	VERB
fcis-29392	92	4	the	the	DET
fcis-29392	92	5	test	test	NOUN
fcis-29392	92	6	results	result	NOUN
fcis-29392	92	7	of	of	ADP
fcis-29392	92	8	the	the	DET
fcis-29392	92	9	improved	improved	ADJ
fcis-29392	92	10	model	model	NOUN
fcis-29392	92	11	.	.	PUNCT
fcis-29392	93	1	from	from	ADP
fcis-29392	93	2	fig	fig	NOUN
fcis-29392	93	3	.	.	PUNCT
fcis-29392	94	1	6(a	6(a	NUM
fcis-29392	94	2	)	)	PUNCT
fcis-29392	94	3	,	,	PUNCT
fcis-29392	94	4	it	it	PRON
fcis-29392	94	5	can	can	AUX
fcis-29392	94	6	be	be	AUX
fcis-29392	94	7	seen	see	VERB
fcis-29392	94	8	that	that	SCONJ
fcis-29392	94	9	the	the	DET
fcis-29392	94	10	original	original	ADJ
fcis-29392	94	11	model	model	NOUN
fcis-29392	94	12	will	will	AUX
fcis-29392	94	13	have	have	AUX
fcis-29392	94	14	missed	miss	VERB
fcis-29392	94	15	detection	detection	NOUN
fcis-29392	94	16	as	as	ADV
fcis-29392	94	17	well	well	ADV
fcis-29392	94	18	as	as	ADP
fcis-29392	94	19	detection	detection	NOUN
fcis-29392	94	20	errors	error	NOUN
fcis-29392	94	21	when	when	SCONJ
fcis-29392	94	22	there	there	PRON
fcis-29392	94	23	are	be	VERB
fcis-29392	94	24	more	more	ADJ
fcis-29392	94	25	targets	target	NOUN
fcis-29392	94	26	.	.	PUNCT
fcis-29392	95	1	the	the	DET
fcis-29392	95	2	addition	addition	NOUN
fcis-29392	95	3	of	of	ADP
fcis-29392	95	4	cbam	cbam	NOUN
fcis-29392	95	5	attention	attention	NOUN
fcis-29392	95	6	and	and	CCONJ
fcis-29392	95	7	focus	focus	VERB
fcis-29392	95	8	loss	loss	NOUN
fcis-29392	95	9	effectively	effectively	ADV
fcis-29392	95	10	improves	improve	VERB
fcis-29392	95	11	the	the	DET
fcis-29392	95	12	model	model	NOUN
fcis-29392	95	13	's	's	PART
fcis-29392	95	14	missed	miss	VERB
fcis-29392	95	15	detection	detection	NOUN
fcis-29392	95	16	as	as	ADV
fcis-29392	95	17	well	well	ADV
fcis-29392	95	18	as	as	ADP
fcis-29392	95	19	the	the	DET
fcis-29392	95	20	occurrence	occurrence	NOUN
fcis-29392	95	21	of	of	ADP
fcis-29392	95	22	detecting	detect	VERB
fcis-29392	95	23	wrong	wrong	ADJ
fcis-29392	95	24	targets	target	NOUN
fcis-29392	95	25	,	,	PUNCT
fcis-29392	95	26	which	which	PRON
fcis-29392	95	27	proves	prove	VERB
fcis-29392	95	28	the	the	DET
fcis-29392	95	29	effectiveness	effectiveness	NOUN
fcis-29392	95	30	of	of	ADP
fcis-29392	95	31	the	the	DET
fcis-29392	95	32	improved	improved	ADJ
fcis-29392	95	33	model	model	NOUN
fcis-29392	95	34	.	.	PUNCT
fcis-29392	96	1	5	5	X
fcis-29392	96	2	.	.	X
fcis-29392	96	3	summarize	summarize	VERB
fcis-29392	96	4	in	in	ADP
fcis-29392	96	5	this	this	DET
fcis-29392	96	6	paper	paper	NOUN
fcis-29392	96	7	,	,	PUNCT
fcis-29392	96	8	the	the	DET
fcis-29392	96	9	transformer	transformer	NOUN
fcis-29392	96	10	model	model	NOUN
fcis-29392	96	11	is	be	AUX
fcis-29392	96	12	applied	apply	VERB
fcis-29392	96	13	to	to	ADP
fcis-29392	96	14	the	the	DET
fcis-29392	96	15	weed	weed	NOUN
fcis-29392	96	16	detection	detection	NOUN
fcis-29392	96	17	task	task	NOUN
fcis-29392	96	18	,	,	PUNCT
fcis-29392	96	19	based	base	VERB
fcis-29392	96	20	on	on	ADP
fcis-29392	96	21	the	the	DET
fcis-29392	96	22	detr	detr	NOUN
fcis-29392	96	23	model	model	NOUN
fcis-29392	96	24	,	,	PUNCT
fcis-29392	96	25	channel	channel	NOUN
fcis-29392	96	26	attention	attention	NOUN
fcis-29392	96	27	and	and	CCONJ
fcis-29392	96	28	spatial	spatial	ADJ
fcis-29392	96	29	attention	attention	NOUN
fcis-29392	96	30	are	be	AUX
fcis-29392	96	31	added	add	VERB
fcis-29392	96	32	to	to	ADP
fcis-29392	96	33	the	the	DET
fcis-29392	96	34	detr	detr	NOUN
fcis-29392	96	35	feature	feature	NOUN
fcis-29392	96	36	extraction	extraction	NOUN
fcis-29392	96	37	network	network	NOUN
fcis-29392	96	38	to	to	PART
fcis-29392	96	39	improve	improve	VERB
fcis-29392	96	40	the	the	DET
fcis-29392	96	41	feature	feature	NOUN
fcis-29392	96	42	extraction	extraction	NOUN
fcis-29392	96	43	ability	ability	NOUN
fcis-29392	96	44	of	of	ADP
fcis-29392	96	45	the	the	DET
fcis-29392	96	46	model	model	NOUN
fcis-29392	96	47	,	,	PUNCT
fcis-29392	96	48	and	and	CCONJ
fcis-29392	96	49	the	the	DET
fcis-29392	96	50	focus	focus	NOUN
fcis-29392	96	51	loss	loss	NOUN
fcis-29392	96	52	function	function	NOUN
fcis-29392	96	53	is	be	AUX
fcis-29392	96	54	used	use	VERB
fcis-29392	96	55	to	to	PART
fcis-29392	96	56	improve	improve	VERB
fcis-29392	96	57	the	the	DET
fcis-29392	96	58	small	small	ADJ
fcis-29392	96	59	target	target	NOUN
fcis-29392	96	60	detection	detection	NOUN
fcis-29392	96	61	effect	effect	NOUN
fcis-29392	96	62	of	of	ADP
fcis-29392	96	63	the	the	DET
fcis-29392	96	64	model	model	NOUN
fcis-29392	96	65	.	.	PUNCT
fcis-29392	97	1	the	the	DET
fcis-29392	97	2	final	final	ADJ
fcis-29392	97	3	detection	detection	NOUN
fcis-29392	97	4	effect	effect	NOUN
fcis-29392	97	5	is	be	AUX
fcis-29392	97	6	improved	improve	VERB
fcis-29392	97	7	by	by	ADP
fcis-29392	97	8	1.12	1.12	NUM
fcis-29392	97	9	%	%	NOUN
fcis-29392	97	10	based	base	VERB
fcis-29392	97	11	on	on	ADP
fcis-29392	97	12	the	the	DET
fcis-29392	97	13	original	original	ADJ
fcis-29392	97	14	detr	detr	NOUN
fcis-29392	97	15	model	model	NOUN
fcis-29392	97	16	.	.	PUNCT
fcis-29392	98	1	comparing	compare	VERB
fcis-29392	98	2	the	the	DET
fcis-29392	98	3	before	before	ADV
fcis-29392	98	4	and	and	CCONJ
fcis-29392	98	5	after	after	ADP
fcis-29392	98	6	effects	effect	NOUN
fcis-29392	98	7	,	,	PUNCT
fcis-29392	98	8	our	our	PRON
fcis-29392	98	9	model	model	NOUN
fcis-29392	98	10	improves	improve	VERB
fcis-29392	98	11	the	the	DET
fcis-29392	98	12	leakage	leakage	NOUN
fcis-29392	98	13	detection	detection	NOUN
fcis-29392	98	14	of	of	ADP
fcis-29392	98	15	the	the	DET
fcis-29392	98	16	detr	detr	NOUN
fcis-29392	98	17	model	model	NOUN
fcis-29392	98	18	and	and	CCONJ
fcis-29392	98	19	improves	improve	VERB
fcis-29392	98	20	the	the	DET
fcis-29392	98	21	ability	ability	NOUN
fcis-29392	98	22	of	of	ADP
fcis-29392	98	23	the	the	DET
fcis-29392	98	24	model	model	NOUN
fcis-29392	98	25	for	for	ADP
fcis-29392	98	26	small	small	ADJ
fcis-29392	98	27	target	target	NOUN
fcis-29392	98	28	detection	detection	NOUN
fcis-29392	98	29	.	.	PUNCT
fcis-29392	99	1	references	reference	NOUN
fcis-29392	99	2	[	[	X
fcis-29392	99	3	1	1	NUM
fcis-29392	99	4	]	]	PUNCT
fcis-29392	99	5	chen	chen	PROPN
fcis-29392	99	6	k	k	PROPN
fcis-29392	99	7	,	,	PUNCT
fcis-29392	99	8	yang	yang	PROPN
fcis-29392	99	9	h	h	PROPN
fcis-29392	99	10	,	,	PUNCT
fcis-29392	99	11	wu	wu	PROPN
fcis-29392	99	12	d	d	PROPN
fcis-29392	99	13	,	,	PUNCT
fcis-29392	99	14	et	et	PROPN
fcis-29392	99	15	al	al	PROPN
fcis-29392	99	16	.	.	PROPN
fcis-29392	99	17	weed	weed	VERB
fcis-29392	99	18	biology	biology	NOUN
fcis-29392	99	19	and	and	CCONJ
fcis-29392	99	20	management	management	NOUN
fcis-29392	99	21	in	in	ADP
fcis-29392	99	22	the	the	DET
fcis-29392	99	23	multi	multi	ADJ
fcis-29392	99	24	-	-	ADJ
fcis-29392	99	25	omics	omics	ADJ
fcis-29392	99	26	era	era	NOUN
fcis-29392	99	27	:	:	PUNCT
fcis-29392	99	28	progress	progress	NOUN
fcis-29392	99	29	and	and	CCONJ
fcis-29392	99	30	perspectives[j	perspectives[j	PROPN
fcis-29392	99	31	]	]	PUNCT
fcis-29392	99	32	.	.	PUNCT
fcis-29392	100	1	plant	plant	NOUN
fcis-29392	100	2	communications	communication	NOUN
fcis-29392	100	3	,	,	PUNCT
fcis-29392	100	4	2024	2024	NUM
fcis-29392	100	5	.	.	PUNCT
fcis-29392	101	1	[	[	X
fcis-29392	101	2	2	2	NUM
fcis-29392	101	3	]	]	X
fcis-29392	101	4	zhang	zhang	PROPN
fcis-29392	101	5	z	z	PROPN
fcis-29392	101	6	,	,	PUNCT
fcis-29392	101	7	li	li	PROPN
fcis-29392	101	8	r	r	PROPN
fcis-29392	101	9	,	,	PUNCT
fcis-29392	101	10	zhao	zhao	PROPN
fcis-29392	101	11	c	c	PROPN
fcis-29392	101	12	,	,	PUNCT
fcis-29392	101	13	et	et	PROPN
fcis-29392	101	14	al	al	PROPN
fcis-29392	101	15	.	.	PROPN
fcis-29392	101	16	reduction	reduction	NOUN
fcis-29392	101	17	in	in	ADP
fcis-29392	101	18	weed	weed	NOUN
fcis-29392	101	19	infestation	infestation	NOUN
fcis-29392	101	20	through	through	ADP
fcis-29392	101	21	integrated	integrate	VERB
fcis-29392	101	22	depletion	depletion	NOUN
fcis-29392	101	23	of	of	ADP
fcis-29392	101	24	the	the	DET
fcis-29392	101	25	weed	weed	NOUN
fcis-29392	101	26	seed	seed	NOUN
fcis-29392	101	27	bank	bank	NOUN
fcis-29392	101	28	in	in	ADP
fcis-29392	101	29	a	a	DET
fcis-29392	101	30	ricewheat	ricewheat	NOUN
fcis-29392	101	31	cropping	crop	VERB
fcis-29392	101	32	system[j	system[j	NOUN
fcis-29392	101	33	]	]	PUNCT
fcis-29392	101	34	.	.	PUNCT
fcis-29392	102	1	agronomy	agronomy	NOUN
fcis-29392	102	2	for	for	ADP
fcis-29392	102	3	sustainable	sustainable	ADJ
fcis-29392	102	4	development	development	NOUN
fcis-29392	102	5	,	,	PUNCT
fcis-29392	102	6	2021	2021	NUM
fcis-29392	102	7	,	,	PUNCT
fcis-29392	102	8	41(1	41(1	NUM
fcis-29392	102	9	):	):	PUNCT
fcis-29392	102	10	10	10	NUM
fcis-29392	102	11	.	.	PUNCT
fcis-29392	103	1	[	[	X
fcis-29392	103	2	3	3	X
fcis-29392	103	3	]	]	X
fcis-29392	103	4	chen	chen	PROPN
fcis-29392	103	5	l	l	PROPN
fcis-29392	103	6	,	,	PUNCT
fcis-29392	103	7	jin	jin	PROPN
fcis-29392	103	8	m	m	PROPN
fcis-29392	103	9	,	,	PUNCT
fcis-29392	103	10	zhang	zhang	PROPN
fcis-29392	103	11	w	w	PROPN
fcis-29392	103	12	l	l	PROPN
fcis-29392	103	13	,	,	PUNCT
fcis-29392	103	14	et	et	PROPN
fcis-29392	103	15	al	al	PROPN
fcis-29392	103	16	.	.	PUNCT
fcis-29392	103	17	research	research	NOUN
fcis-29392	103	18	advances	advance	NOUN
fcis-29392	103	19	on	on	ADP
fcis-29392	103	20	characteristics	characteristic	NOUN
fcis-29392	103	21	,	,	PUNCT
fcis-29392	103	22	damage	damage	NOUN
fcis-29392	103	23	and	and	CCONJ
fcis-29392	103	24	control	control	NOUN
fcis-29392	103	25	measures	measure	NOUN
fcis-29392	103	26	of	of	ADP
fcis-29392	103	27	weedy	weedy	ADJ
fcis-29392	103	28	rice[j	rice[j	NOUN
fcis-29392	103	29	]	]	PUNCT
fcis-29392	103	30	.	.	PUNCT
fcis-29392	104	1	2020	2020	NUM
fcis-29392	104	2	.	.	PUNCT
fcis-29392	105	1	[	[	X
fcis-29392	105	2	4	4	NUM
fcis-29392	105	3	]	]	X
fcis-29392	105	4	yuan	yuan	NOUN
fcis-29392	105	5	hongbo	hongbo	NOUN
fcis-29392	105	6	,	,	PUNCT
fcis-29392	105	7	zhao	zhao	PROPN
fcis-29392	105	8	nudong	nudong	PROPN
fcis-29392	105	9	,	,	PUNCT
fcis-29392	105	10	cheng	cheng	PROPN
fcis-29392	105	11	man	man	PROPN
fcis-29392	105	12	.	.	PUNCT
fcis-29392	106	1	research	research	NOUN
fcis-29392	106	2	progress	progress	NOUN
fcis-29392	106	3	and	and	CCONJ
fcis-29392	106	4	prospect	prospect	NOUN
fcis-29392	106	5	of	of	ADP
fcis-29392	106	6	field	field	NOUN
fcis-29392	106	7	weed	weed	NOUN
fcis-29392	106	8	recognition	recognition	NOUN
fcis-29392	106	9	based	base	VERB
fcis-29392	106	10	on	on	ADP
fcis-29392	106	11	image	image	NOUN
fcis-29392	106	12	processing[j	processing[j	NOUN
fcis-29392	106	13	]	]	PUNCT
fcis-29392	106	14	.	.	PUNCT
fcis-29392	107	1	journal	journal	PROPN
fcis-29392	107	2	of	of	ADP
fcis-29392	107	3	agricultural	agricultural	ADJ
fcis-29392	107	4	machinery	machinery	NOUN
fcis-29392	107	5	,	,	PUNCT
fcis-29392	107	6	2020	2020	NUM
fcis-29392	107	7	,	,	PUNCT
fcis-29392	107	8	51(s2	51(s2	NUM
fcis-29392	107	9	):	):	PUNCT
fcis-29392	107	10	323	323	NUM
fcis-29392	107	11	-	-	SYM
fcis-29392	107	12	334	334	NUM
fcis-29392	107	13	.	.	PUNCT
fcis-29392	108	1	[	[	X
fcis-29392	108	2	5	5	NUM
fcis-29392	108	3	]	]	SYM
fcis-29392	108	4	mathanker	mathanker	NOUN
fcis-29392	108	5	s	s	PART
fcis-29392	108	6	k	k	NOUN
fcis-29392	108	7	,	,	PUNCT
fcis-29392	108	8	weckler	weckler	NOUN
fcis-29392	108	9	p	p	PROPN
fcis-29392	108	10	r	r	PROPN
fcis-29392	108	11	,	,	PUNCT
fcis-29392	108	12	taylor	taylor	PROPN
fcis-29392	108	13	r	r	PROPN
fcis-29392	108	14	k	k	PROPN
fcis-29392	108	15	,	,	PUNCT
fcis-29392	108	16	et	et	PROPN
fcis-29392	108	17	al	al	PROPN
fcis-29392	108	18	.	.	PROPN
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fcis-29392	109	4	vector	vector	NOUN
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fcis-29392	109	9	weed	weed	NOUN
fcis-29392	109	10	control	control	NOUN
fcis-29392	109	11	:	:	PUNCT
fcis-29392	109	12	canola	canola	PROPN
fcis-29392	109	13	and	and	CCONJ
fcis-29392	109	14	wheat[c]//2010	wheat[c]//2010	PROPN
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fcis-29392	109	16	,	,	PUNCT
fcis-29392	109	17	pennsylvania	pennsylvania	PROPN
fcis-29392	109	18	,	,	PUNCT
fcis-29392	109	19	june	june	PROPN
fcis-29392	109	20	20	20	NUM
fcis-29392	109	21	-	-	SYM
fcis-29392	109	22	june	june	PROPN
fcis-29392	109	23	23	23	NUM
fcis-29392	109	24	,	,	PUNCT
fcis-29392	109	25	2010	2010	NUM
fcis-29392	109	26	.	.	PUNCT
fcis-29392	110	1	american	american	ADJ
fcis-29392	110	2	society	society	NOUN
fcis-29392	110	3	of	of	ADP
fcis-29392	110	4	agricultural	agricultural	ADJ
fcis-29392	110	5	and	and	CCONJ
fcis-29392	110	6	biological	biological	ADJ
fcis-29392	110	7	engineers	engineer	NOUN
fcis-29392	110	8	,	,	PUNCT
fcis-29392	110	9	2010	2010	NUM
fcis-29392	110	10	:	:	PUNCT
fcis-29392	111	1	1	1	X
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fcis-29392	112	3	]	]	X
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fcis-29392	112	6	,	,	PUNCT
fcis-29392	112	7	yang	yang	PROPN
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fcis-29392	112	9	,	,	PUNCT
fcis-29392	112	10	wu	wu	PROPN
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fcis-29392	112	13	et	et	PROPN
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fcis-29392	112	17	of	of	ADP
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fcis-29392	112	19	leaves	leave	NOUN
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fcis-29392	112	21	weeds	weed	NOUN
fcis-29392	112	22	in	in	ADP
fcis-29392	112	23	spinach	spinach	NOUN
fcis-29392	112	24	based	base	VERB
fcis-29392	112	25	on	on	ADP
fcis-29392	112	26	image	image	NOUN
fcis-29392	112	27	chunking	chunking	NOUN
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fcis-29392	112	29	reconstruction[j	reconstruction[j	PROPN
fcis-29392	112	30	]	]	PUNCT
fcis-29392	112	31	.	.	PUNCT
fcis-29392	113	1	transactions	transaction	NOUN
fcis-29392	113	2	of	of	ADP
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fcis-29392	113	4	chinese	chinese	ADJ
fcis-29392	113	5	society	society	NOUN
fcis-29392	113	6	of	of	ADP
fcis-29392	113	7	agricultural	agricultural	ADJ
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fcis-29392	113	9	,	,	PUNCT
fcis-29392	113	10	2020	2020	NUM
fcis-29392	113	11	,	,	PUNCT
fcis-29392	113	12	36(4	36(4	NUM
fcis-29392	113	13	)	)	PUNCT
fcis-29392	113	14	.	.	PUNCT
fcis-29392	114	1	[	[	X
fcis-29392	114	2	7	7	X
fcis-29392	114	3	]	]	X
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fcis-29392	114	19	pasture	pasture	NOUN
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fcis-29392	114	21	on	on	ADP
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fcis-29392	116	4	,	,	PUNCT
fcis-29392	116	5	2023	2023	NUM
fcis-29392	116	6	,	,	PUNCT
fcis-29392	116	7	52(9	52(9	NUM
fcis-29392	116	8	):	):	PUNCT
fcis-29392	116	9	156	156	NUM
fcis-29392	116	10	-	-	SYM
fcis-29392	116	11	163	163	NUM
fcis-29392	116	12	.	.	PUNCT
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fcis-29392	117	2	8	8	NUM
fcis-29392	117	3	]	]	X
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fcis-29392	117	5	x	x	X
fcis-29392	117	6	,	,	PUNCT
fcis-29392	117	7	liu	liu	PROPN
fcis-29392	117	8	t	t	PROPN
fcis-29392	117	9	,	,	PUNCT
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fcis-29392	117	24	susceptibilitybased	susceptibilitybase	VERB
fcis-29392	117	25	weed	weed	NOUN
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fcis-29392	117	28	turf[j	turf[j	NOUN
fcis-29392	117	29	]	]	PUNCT
fcis-29392	117	30	.	.	PUNCT
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fcis-29392	118	2	in	in	ADP
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fcis-29392	118	5	,	,	PUNCT
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fcis-29392	118	7	,	,	PUNCT
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fcis-29392	118	9	:	:	SYM
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fcis-29392	119	3	]	]	PUNCT
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fcis-29392	119	7	,	,	PUNCT
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fcis-29392	119	32	weed	weed	VERB
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fcis-29392	119	38	.	.	PUNCT
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fcis-29392	120	2	agricultural	agricultural	ADJ
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fcis-29392	120	4	,	,	PUNCT
fcis-29392	120	5	2023	2023	NUM
fcis-29392	120	6	,	,	PUNCT
fcis-29392	120	7	4	4	NUM
fcis-29392	120	8	:	:	SYM
fcis-29392	120	9	100142	100142	NUM
fcis-29392	120	10	.	.	PUNCT
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fcis-29392	121	30	.	.	PUNCT
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fcis-29392	122	5	,	,	PUNCT
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fcis-29392	122	7	,	,	PUNCT
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fcis-29392	122	9	:	:	SYM
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fcis-29392	122	11	.	.	PUNCT
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fcis-29392	123	25	]	]	PUNCT
fcis-29392	123	26	.	.	PUNCT
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fcis-29392	124	8	:	:	SYM
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fcis-29392	126	7	):	):	PUNCT
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fcis-29392	128	8	:	:	PUNCT
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fcis-29392	128	10	-	-	SYM
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fcis-29392	129	17	is	be	AUX
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fcis-29392	129	22	.	.	PUNCT
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fcis-29392	131	27	conference	conference	NOUN
fcis-29392	131	28	on	on	ADP
fcis-29392	131	29	computer	computer	NOUN
fcis-29392	131	30	vision	vision	NOUN
fcis-29392	131	31	.	.	PUNCT
fcis-29392	132	1	2017	2017	NUM
fcis-29392	132	2	:	:	PUNCT
fcis-29392	132	3	2980	2980	NUM
fcis-29392	132	4	-	-	SYM
fcis-29392	132	5	2988	2988	NUM
fcis-29392	132	6	.	.	PUNCT
fcis-29392	133	1	[	[	X
fcis-29392	133	2	16	16	NUM
fcis-29392	133	3	]	]	X
fcis-29392	133	4	woo	woo	PROPN
fcis-29392	133	5	s	s	PROPN
fcis-29392	133	6	,	,	PUNCT
fcis-29392	133	7	park	park	PROPN
fcis-29392	133	8	j	j	PROPN
fcis-29392	133	9	,	,	PUNCT
fcis-29392	133	10	lee	lee	PROPN
fcis-29392	133	11	j	j	PROPN
fcis-29392	133	12	y	y	PROPN
fcis-29392	133	13	,	,	PUNCT
fcis-29392	133	14	et	et	PROPN
fcis-29392	133	15	al	al	PROPN
fcis-29392	133	16	.	.	PUNCT
fcis-29392	133	17	cbam	cbam	NOUN
fcis-29392	133	18	:	:	PUNCT
fcis-29392	133	19	convolutional	convolutional	ADJ
fcis-29392	133	20	block	block	NOUN
fcis-29392	133	21	attention	attention	NOUN
fcis-29392	133	22	module[c]//proceedings	module[c]//proceeding	NOUN
fcis-29392	133	23	of	of	ADP
fcis-29392	133	24	the	the	DET
fcis-29392	133	25	european	european	PROPN
fcis-29392	133	26	conference	conference	PROPN
fcis-29392	133	27	on	on	ADP
fcis-29392	133	28	computer	computer	NOUN
fcis-29392	133	29	vision	vision	NOUN
fcis-29392	133	30	(	(	PUNCT
fcis-29392	133	31	eccv	eccv	ADV
fcis-29392	133	32	)	)	PUNCT
fcis-29392	133	33	.	.	PUNCT
fcis-29392	134	1	2018	2018	NUM
fcis-29392	134	2	:	:	PUNCT
fcis-29392	134	3	3	3	NUM
fcis-29392	134	4	-	-	SYM
fcis-29392	134	5	19	19	NUM
fcis-29392	134	6	.	.	PUNCT
fcis-29392	135	1	[	[	X
fcis-29392	135	2	17	17	NUM
fcis-29392	135	3	]	]	X
fcis-29392	135	4	jiang	jiang	PROPN
fcis-29392	135	5	h	h	PROPN
fcis-29392	135	6	,	,	PUNCT
fcis-29392	135	7	zhang	zhang	PROPN
fcis-29392	135	8	c	c	PROPN
fcis-29392	135	9	,	,	PUNCT
fcis-29392	135	10	qiao	qiao	PROPN
fcis-29392	135	11	y	y	PROPN
fcis-29392	135	12	,	,	PUNCT
fcis-29392	135	13	et	et	PROPN
fcis-29392	135	14	al	al	PROPN
fcis-29392	135	15	.	.	PROPN
fcis-29392	136	1	cnn	cnn	PROPN
fcis-29392	136	2	feature	feature	VERB
fcis-29392	136	3	based	base	VERB
fcis-29392	136	4	graph	graph	NOUN
fcis-29392	136	5	convolutional	convolutional	ADJ
fcis-29392	136	6	network	network	NOUN
fcis-29392	136	7	for	for	ADP
fcis-29392	136	8	weed	weed	NOUN
fcis-29392	136	9	and	and	CCONJ
fcis-29392	136	10	crop	crop	NOUN
fcis-29392	136	11	recognition	recognition	NOUN
fcis-29392	136	12	in	in	ADP
fcis-29392	136	13	smart	smart	ADJ
fcis-29392	136	14	farming[j	farming[j	PROPN
fcis-29392	136	15	]	]	PUNCT
fcis-29392	136	16	.	.	PUNCT
fcis-29392	137	1	computers	computer	NOUN
fcis-29392	137	2	and	and	CCONJ
fcis-29392	137	3	electronics	electronic	NOUN
fcis-29392	137	4	in	in	ADP
fcis-29392	137	5	agriculture	agriculture	NOUN
fcis-29392	137	6	,	,	PUNCT
fcis-29392	137	7	2020	2020	NUM
fcis-29392	137	8	,	,	PUNCT
fcis-29392	137	9	174	174	NUM
fcis-29392	137	10	:	:	PUNCT
fcis-29392	137	11	105450	105450	NUM
fcis-29392	137	12	.	.	PUNCT