id	sid	tid	token	lemma	pos
ajsts-5382	1	1	pa	pa	PROPN
ajsts-5382	1	2	ge	ge	PROPN
ajsts-5382	1	3	1	1	NUM
ajsts-5382	1	4	pa	pa	PROPN
ajsts-5382	1	5	ge	ge	PROPN
ajsts-5382	1	6	57	57	NUM
ajsts-5382	1	7	american	american	PROPN
ajsts-5382	1	8	journal	journal	NOUN
ajsts-5382	1	9	of	of	ADP
ajsts-5382	1	10	smart	smart	ADJ
ajsts-5382	1	11	technology	technology	NOUN
ajsts-5382	1	12	and	and	CCONJ
ajsts-5382	1	13	solutions	solution	NOUN
ajsts-5382	1	14	(	(	PUNCT
ajsts-5382	1	15	ajsts	ajst	NOUN
ajsts-5382	1	16	)	)	PUNCT
ajsts-5382	1	17	evaluating	evaluate	VERB
ajsts-5382	1	18	soybean	soybean	NOUN
ajsts-5382	1	19	root	root	NOUN
ajsts-5382	1	20	health	health	NOUN
ajsts-5382	1	21	using	use	VERB
ajsts-5382	1	22	residual	residual	ADJ
ajsts-5382	1	23	neural	neural	ADJ
ajsts-5382	1	24	network	network	NOUN
ajsts-5382	1	25	(	(	PUNCT
ajsts-5382	1	26	renn	renn	PROPN
ajsts-5382	1	27	)	)	PUNCT
ajsts-5382	1	28	based	base	VERB
ajsts-5382	1	29	image	image	NOUN
ajsts-5382	1	30	analysis	analysis	NOUN
ajsts-5382	1	31	vivek	vivek	ADJ
ajsts-5382	1	32	gupta1	gupta1	NOUN
ajsts-5382	1	33	*	*	PROPN
ajsts-5382	1	34	,	,	PUNCT
ajsts-5382	1	35	jhankar	jhankar	PROPN
ajsts-5382	1	36	moolchadani2	moolchadani2	PROPN
ajsts-5382	1	37	,	,	PUNCT
ajsts-5382	1	38	harsh	harsh	ADJ
ajsts-5382	1	39	singh	singh	PROPN
ajsts-5382	1	40	chouhan2	chouhan2	PROPN
ajsts-5382	1	41	volume	volume	NOUN
ajsts-5382	1	42	4	4	NUM
ajsts-5382	1	43	issue	issue	NOUN
ajsts-5382	1	44	2	2	NUM
ajsts-5382	1	45	,	,	PUNCT
ajsts-5382	1	46	year	year	NOUN
ajsts-5382	1	47	2025	2025	NUM
ajsts-5382	1	48	issn	issn	NOUN
ajsts-5382	1	49	:	:	PUNCT
ajsts-5382	1	50	2837	2837	NUM
ajsts-5382	1	51	-	-	SYM
ajsts-5382	1	52	0295	0295	NUM
ajsts-5382	1	53	(	(	PUNCT
ajsts-5382	1	54	online	online	ADJ
ajsts-5382	1	55	)	)	PUNCT
ajsts-5382	1	56	doi	doi	NOUN
ajsts-5382	1	57	:	:	PUNCT
ajsts-5382	1	58	https://doi.org/10.54536/ajsts.v4i2.5382	https://doi.org/10.54536/ajsts.v4i2.5382	PROPN
ajsts-5382	1	59	https://journals.e-palli.com/home/index.php/ajsts	https://journals.e-palli.com/home/index.php/ajst	NOUN
ajsts-5382	1	60	article	article	NOUN
ajsts-5382	1	61	information	information	NOUN
ajsts-5382	1	62	abstract	abstract	ADV
ajsts-5382	1	63	received	receive	VERB
ajsts-5382	1	64	:	:	PUNCT
ajsts-5382	1	65	june	june	PROPN
ajsts-5382	1	66	22	22	NUM
ajsts-5382	1	67	,	,	PUNCT
ajsts-5382	1	68	2025	2025	NUM
ajsts-5382	1	69	accepted	accept	VERB
ajsts-5382	1	70	:	:	PUNCT
ajsts-5382	1	71	july	july	PROPN
ajsts-5382	1	72	31	31	NUM
ajsts-5382	1	73	,	,	PUNCT
ajsts-5382	1	74	2025	2025	NUM
ajsts-5382	1	75	published	publish	VERB
ajsts-5382	1	76	:	:	PUNCT
ajsts-5382	1	77	september	september	PROPN
ajsts-5382	1	78	05	05	NUM
ajsts-5382	1	79	,	,	PUNCT
ajsts-5382	1	80	2025	2025	NUM
ajsts-5382	1	81	renn	renn	PROPN
ajsts-5382	1	82	’s	’s	PART
ajsts-5382	1	83	layer	layer	NOUN
ajsts-5382	1	84	-	-	PUNCT
ajsts-5382	1	85	wise	wise	ADJ
ajsts-5382	1	86	image	image	NOUN
ajsts-5382	1	87	segmentation	segmentation	NOUN
ajsts-5382	1	88	and	and	CCONJ
ajsts-5382	1	89	robust	robust	ADJ
ajsts-5382	1	90	data	datum	NOUN
ajsts-5382	1	91	processing	processing	NOUN
ajsts-5382	1	92	address	address	NOUN
ajsts-5382	1	93	the	the	DET
ajsts-5382	1	94	complexities	complexity	NOUN
ajsts-5382	1	95	of	of	ADP
ajsts-5382	1	96	soybean	soybean	NOUN
ajsts-5382	1	97	root	root	NOUN
ajsts-5382	1	98	analysis	analysis	NOUN
ajsts-5382	1	99	,	,	PUNCT
ajsts-5382	1	100	providing	provide	VERB
ajsts-5382	1	101	valuable	valuable	ADJ
ajsts-5382	1	102	insights	insight	NOUN
ajsts-5382	1	103	for	for	ADP
ajsts-5382	1	104	improved	improved	ADJ
ajsts-5382	1	105	crop	crop	NOUN
ajsts-5382	1	106	management	management	NOUN
ajsts-5382	1	107	.	.	PUNCT
ajsts-5382	2	1	accurate	accurate	ADJ
ajsts-5382	2	2	assessment	assessment	NOUN
ajsts-5382	2	3	of	of	ADP
ajsts-5382	2	4	soybean	soybean	NOUN
ajsts-5382	2	5	root	root	NOUN
ajsts-5382	2	6	health	health	NOUN
ajsts-5382	2	7	is	be	AUX
ajsts-5382	2	8	crucial	crucial	ADJ
ajsts-5382	2	9	for	for	ADP
ajsts-5382	2	10	optimal	optimal	ADJ
ajsts-5382	2	11	crop	crop	NOUN
ajsts-5382	2	12	production	production	NOUN
ajsts-5382	2	13	and	and	CCONJ
ajsts-5382	2	14	growth	growth	NOUN
ajsts-5382	2	15	.	.	PUNCT
ajsts-5382	3	1	this	this	DET
ajsts-5382	3	2	study	study	NOUN
ajsts-5382	3	3	utilizes	utilize	VERB
ajsts-5382	3	4	residual	residual	ADJ
ajsts-5382	3	5	neural	neural	ADJ
ajsts-5382	3	6	network	network	NOUN
ajsts-5382	3	7	(	(	PUNCT
ajsts-5382	3	8	renn	renn	PROPN
ajsts-5382	3	9	)	)	PUNCT
ajsts-5382	3	10	image	image	NOUN
ajsts-5382	3	11	evaluation	evaluation	NOUN
ajsts-5382	3	12	to	to	PART
ajsts-5382	3	13	analyze	analyze	VERB
ajsts-5382	3	14	soybean	soybean	NOUN
ajsts-5382	3	15	root	root	NOUN
ajsts-5382	3	16	development	development	NOUN
ajsts-5382	3	17	.	.	PUNCT
ajsts-5382	4	1	field	field	NOUN
ajsts-5382	4	2	data	datum	NOUN
ajsts-5382	4	3	is	be	AUX
ajsts-5382	4	4	collected	collect	VERB
ajsts-5382	4	5	and	and	CCONJ
ajsts-5382	4	6	integrated	integrate	VERB
ajsts-5382	4	7	by	by	ADP
ajsts-5382	4	8	deploying	deploy	VERB
ajsts-5382	4	9	sensorbased	sensorbase	VERB
ajsts-5382	4	10	devices	device	NOUN
ajsts-5382	4	11	(	(	PUNCT
ajsts-5382	4	12	iot	iot	NOUN
ajsts-5382	4	13	devices	device	NOUN
ajsts-5382	4	14	)	)	PUNCT
ajsts-5382	4	15	to	to	PART
ajsts-5382	4	16	evaluate	evaluate	VERB
ajsts-5382	4	17	soybean	soybean	NOUN
ajsts-5382	4	18	crop	crop	NOUN
ajsts-5382	4	19	stages	stage	NOUN
ajsts-5382	4	20	.	.	PUNCT
ajsts-5382	5	1	renn	renn	PROPN
ajsts-5382	5	2	facilitates	facilitate	VERB
ajsts-5382	5	3	data	datum	NOUN
ajsts-5382	5	4	preprocessing	preprocessing	NOUN
ajsts-5382	5	5	,	,	PUNCT
ajsts-5382	5	6	layer	layer	NOUN
ajsts-5382	5	7	-	-	PUNCT
ajsts-5382	5	8	wise	wise	ADJ
ajsts-5382	5	9	image	image	NOUN
ajsts-5382	5	10	segmentation	segmentation	NOUN
ajsts-5382	5	11	,	,	PUNCT
ajsts-5382	5	12	and	and	CCONJ
ajsts-5382	5	13	effective	effective	ADJ
ajsts-5382	5	14	data	datum	NOUN
ajsts-5382	5	15	processing	processing	NOUN
ajsts-5382	5	16	,	,	PUNCT
ajsts-5382	5	17	enabling	enable	VERB
ajsts-5382	5	18	accurate	accurate	ADJ
ajsts-5382	5	19	assessment	assessment	NOUN
ajsts-5382	5	20	of	of	ADP
ajsts-5382	5	21	root	root	NOUN
ajsts-5382	5	22	health	health	NOUN
ajsts-5382	5	23	,	,	PUNCT
ajsts-5382	5	24	plant	plant	NOUN
ajsts-5382	5	25	vigor	vigor	NOUN
ajsts-5382	5	26	,	,	PUNCT
ajsts-5382	5	27	flower	flower	NOUN
ajsts-5382	5	28	fragmentation	fragmentation	NOUN
ajsts-5382	5	29	,	,	PUNCT
ajsts-5382	5	30	and	and	CCONJ
ajsts-5382	5	31	fruit	fruit	NOUN
ajsts-5382	5	32	formation	formation	NOUN
ajsts-5382	5	33	.	.	PUNCT
ajsts-5382	6	1	this	this	DET
ajsts-5382	6	2	approach	approach	NOUN
ajsts-5382	6	3	predicts	predict	VERB
ajsts-5382	6	4	soybean	soybean	NOUN
ajsts-5382	6	5	crop	crop	NOUN
ajsts-5382	6	6	yield	yield	NOUN
ajsts-5382	6	7	and	and	CCONJ
ajsts-5382	6	8	provides	provide	VERB
ajsts-5382	6	9	valuable	valuable	ADJ
ajsts-5382	6	10	insights	insight	NOUN
ajsts-5382	6	11	into	into	ADP
ajsts-5382	6	12	degradation	degradation	NOUN
ajsts-5382	6	13	detection	detection	NOUN
ajsts-5382	6	14	and	and	CCONJ
ajsts-5382	6	15	decision	decision	NOUN
ajsts-5382	6	16	-	-	PUNCT
ajsts-5382	6	17	making	making	NOUN
ajsts-5382	6	18	for	for	ADP
ajsts-5382	6	19	optimal	optimal	ADJ
ajsts-5382	6	20	soybean	soybean	NOUN
ajsts-5382	6	21	cultivation	cultivation	NOUN
ajsts-5382	6	22	practices	practice	NOUN
ajsts-5382	6	23	.	.	PUNCT
ajsts-5382	7	1	renn	renn	PROPN
ajsts-5382	7	2	utilizes	utilize	VERB
ajsts-5382	7	3	layer	layer	NOUN
ajsts-5382	7	4	-	-	PUNCT
ajsts-5382	7	5	based	base	VERB
ajsts-5382	7	6	image	image	NOUN
ajsts-5382	7	7	formation	formation	NOUN
ajsts-5382	7	8	,	,	PUNCT
ajsts-5382	7	9	collecting	collect	VERB
ajsts-5382	7	10	data	datum	NOUN
ajsts-5382	7	11	from	from	ADP
ajsts-5382	7	12	farm	farm	NOUN
ajsts-5382	7	13	fields	field	NOUN
ajsts-5382	7	14	through	through	ADP
ajsts-5382	7	15	sensor	sensor	NOUN
ajsts-5382	7	16	-	-	PUNCT
ajsts-5382	7	17	based	base	VERB
ajsts-5382	7	18	devices	device	NOUN
ajsts-5382	7	19	.	.	PUNCT
ajsts-5382	8	1	the	the	DET
ajsts-5382	8	2	dataset	dataset	NOUN
ajsts-5382	8	3	encompasses	encompass	VERB
ajsts-5382	8	4	various	various	ADJ
ajsts-5382	8	5	environmental	environmental	ADJ
ajsts-5382	8	6	and	and	CCONJ
ajsts-5382	8	7	weather	weather	NOUN
ajsts-5382	8	8	conditions	condition	NOUN
ajsts-5382	8	9	,	,	PUNCT
ajsts-5382	8	10	ensuring	ensure	VERB
ajsts-5382	8	11	comprehensive	comprehensive	ADJ
ajsts-5382	8	12	coverage	coverage	NOUN
ajsts-5382	8	13	.	.	PUNCT
ajsts-5382	9	1	key	key	ADJ
ajsts-5382	9	2	considerations	consideration	NOUN
ajsts-5382	9	3	for	for	ADP
ajsts-5382	9	4	data	data	NOUN
ajsts-5382	9	5	preprocessing	preprocessing	NOUN
ajsts-5382	9	6	include	include	VERB
ajsts-5382	9	7	temperature	temperature	NOUN
ajsts-5382	9	8	,	,	PUNCT
ajsts-5382	9	9	humidity	humidity	NOUN
ajsts-5382	9	10	,	,	PUNCT
ajsts-5382	9	11	precipitation	precipitation	NOUN
ajsts-5382	9	12	as	as	ADP
ajsts-5382	9	13	the	the	DET
ajsts-5382	9	14	weather	weather	NOUN
ajsts-5382	9	15	conditions	condition	NOUN
ajsts-5382	9	16	,	,	PUNCT
ajsts-5382	9	17	soil	soil	NOUN
ajsts-5382	9	18	type	type	NOUN
ajsts-5382	9	19	,	,	PUNCT
ajsts-5382	9	20	moisture	moisture	NOUN
ajsts-5382	9	21	,	,	PUNCT
ajsts-5382	9	22	sunlight	sunlight	NOUN
ajsts-5382	9	23	as	as	ADP
ajsts-5382	9	24	environmental	environmental	ADJ
ajsts-5382	9	25	factors	factor	NOUN
ajsts-5382	9	26	,	,	PUNCT
ajsts-5382	9	27	field	field	NOUN
ajsts-5382	9	28	location	location	NOUN
ajsts-5382	9	29	,	,	PUNCT
ajsts-5382	9	30	soil	soil	NOUN
ajsts-5382	9	31	heterogeneity	heterogeneity	NOUN
ajsts-5382	9	32	as	as	ADP
ajsts-5382	9	33	spatial	spatial	ADJ
ajsts-5382	9	34	variability	variability	NOUN
ajsts-5382	9	35	,	,	PUNCT
ajsts-5382	9	36	and	and	CCONJ
ajsts-5382	9	37	growth	growth	NOUN
ajsts-5382	9	38	stage	stage	NOUN
ajsts-5382	9	39	,	,	PUNCT
ajsts-5382	9	40	seasonality	seasonality	NOUN
ajsts-5382	9	41	as	as	ADP
ajsts-5382	9	42	temporal	temporal	ADJ
ajsts-5382	9	43	variability	variability	NOUN
ajsts-5382	9	44	.	.	PUNCT
ajsts-5382	10	1	by	by	ADP
ajsts-5382	10	2	integrating	integrate	VERB
ajsts-5382	10	3	these	these	DET
ajsts-5382	10	4	factors	factor	NOUN
ajsts-5382	10	5	,	,	PUNCT
ajsts-5382	10	6	renn	renn	PROPN
ajsts-5382	10	7	enables	enable	VERB
ajsts-5382	10	8	accurate	accurate	ADJ
ajsts-5382	10	9	evaluation	evaluation	NOUN
ajsts-5382	10	10	of	of	ADP
ajsts-5382	10	11	soybean	soybean	NOUN
ajsts-5382	10	12	root	root	NOUN
ajsts-5382	10	13	conditions	condition	NOUN
ajsts-5382	10	14	,	,	PUNCT
ajsts-5382	10	15	facilitating	facilitate	VERB
ajsts-5382	10	16	root	root	NOUN
ajsts-5382	10	17	health	health	NOUN
ajsts-5382	10	18	assessment	assessment	NOUN
ajsts-5382	10	19	,	,	PUNCT
ajsts-5382	10	20	plant	plant	NOUN
ajsts-5382	10	21	growth	growth	NOUN
ajsts-5382	10	22	monitoring	monitoring	NOUN
ajsts-5382	10	23	,	,	PUNCT
ajsts-5382	10	24	yield	yield	NOUN
ajsts-5382	10	25	prediction	prediction	NOUN
ajsts-5382	10	26	,	,	PUNCT
ajsts-5382	10	27	and	and	CCONJ
ajsts-5382	10	28	optimized	optimize	VERB
ajsts-5382	10	29	cultivation	cultivation	NOUN
ajsts-5382	10	30	practices	practice	NOUN
ajsts-5382	10	31	.	.	PUNCT
ajsts-5382	11	1	keywords	keyword	NOUN
ajsts-5382	11	2	convolution	convolution	VERB
ajsts-5382	11	3	neural	neural	ADJ
ajsts-5382	11	4	network	network	NOUN
ajsts-5382	11	5	(	(	PUNCT
ajsts-5382	11	6	conn	conn	PROPN
ajsts-5382	11	7	)	)	PUNCT
ajsts-5382	11	8	,	,	PUNCT
ajsts-5382	11	9	data	datum	NOUN
ajsts-5382	11	10	preprocessing	preprocessing	NOUN
ajsts-5382	11	11	system	system	NOUN
ajsts-5382	11	12	(	(	PUNCT
ajsts-5382	11	13	dps	dps	NOUN
ajsts-5382	11	14	)	)	PUNCT
ajsts-5382	11	15	,	,	PUNCT
ajsts-5382	11	16	internet	internet	NOUN
ajsts-5382	11	17	of	of	ADP
ajsts-5382	11	18	things	thing	NOUN
ajsts-5382	11	19	(	(	PUNCT
ajsts-5382	11	20	iot	iot	NOUN
ajsts-5382	11	21	)	)	PUNCT
ajsts-5382	11	22	,	,	PUNCT
ajsts-5382	11	23	neural	neural	ADJ
ajsts-5382	11	24	network	network	NOUN
ajsts-5382	11	25	(	(	PUNCT
ajsts-5382	11	26	nn	nn	NOUN
ajsts-5382	11	27	)	)	PUNCT
ajsts-5382	11	28	,	,	PUNCT
ajsts-5382	11	29	residual	residual	ADJ
ajsts-5382	11	30	neural	neural	ADJ
ajsts-5382	11	31	networks	network	NOUN
ajsts-5382	11	32	(	(	PUNCT
ajsts-5382	11	33	resnn	resnn	X
ajsts-5382	11	34	)	)	PUNCT
ajsts-5382	11	35	1	1	NUM
ajsts-5382	11	36	department	department	NOUN
ajsts-5382	11	37	of	of	ADP
ajsts-5382	11	38	computer	computer	NOUN
ajsts-5382	11	39	science	science	NOUN
ajsts-5382	11	40	and	and	CCONJ
ajsts-5382	11	41	engineering	engineering	NOUN
ajsts-5382	11	42	,	,	PUNCT
ajsts-5382	11	43	aset	aset	NOUN
ajsts-5382	11	44	&	&	CCONJ
ajsts-5382	11	45	amity	amity	PROPN
ajsts-5382	11	46	university	university	PROPN
ajsts-5382	11	47	gwalior	gwalior	PROPN
ajsts-5382	11	48	,	,	PUNCT
ajsts-5382	11	49	mp	mp	PROPN
ajsts-5382	11	50	,	,	PUNCT
ajsts-5382	11	51	india	india	PROPN
ajsts-5382	11	52	2	2	NUM
ajsts-5382	11	53	department	department	NOUN
ajsts-5382	11	54	of	of	ADP
ajsts-5382	11	55	electronics	electronic	NOUN
ajsts-5382	11	56	and	and	CCONJ
ajsts-5382	11	57	communication	communication	NOUN
ajsts-5382	11	58	&	&	CCONJ
ajsts-5382	11	59	indore	indore	PROPN
ajsts-5382	11	60	institute	institute	PROPN
ajsts-5382	11	61	of	of	ADP
ajsts-5382	11	62	science	science	NOUN
ajsts-5382	11	63	and	and	CCONJ
ajsts-5382	11	64	technology	technology	NOUN
ajsts-5382	11	65	,	,	PUNCT
ajsts-5382	11	66	indore	indore	PROPN
ajsts-5382	11	67	,	,	PUNCT
ajsts-5382	11	68	mp	mp	PROPN
ajsts-5382	11	69	,	,	PUNCT
ajsts-5382	11	70	india	india	PROPN
ajsts-5382	11	71	*	*	PUNCT
ajsts-5382	11	72	corresponding	correspond	VERB
ajsts-5382	11	73	author	author	NOUN
ajsts-5382	11	74	’s	’s	PART
ajsts-5382	11	75	e	e	NOUN
ajsts-5382	11	76	-	-	NOUN
ajsts-5382	11	77	mail	mail	NOUN
ajsts-5382	11	78	:	:	PUNCT
ajsts-5382	11	79	vivek.gupta5@s.amity.edu	vivek.gupta5@s.amity.edu	NUM
ajsts-5382	11	80	introduction	introduction	NOUN
ajsts-5382	11	81	in	in	ADP
ajsts-5382	11	82	the	the	DET
ajsts-5382	11	83	realm	realm	NOUN
ajsts-5382	11	84	of	of	ADP
ajsts-5382	11	85	technological	technological	ADJ
ajsts-5382	11	86	approaches	approach	NOUN
ajsts-5382	11	87	,	,	PUNCT
ajsts-5382	11	88	the	the	DET
ajsts-5382	11	89	domain	domain	NOUN
ajsts-5382	11	90	of	of	ADP
ajsts-5382	11	91	agriculture	agriculture	NOUN
ajsts-5382	11	92	is	be	AUX
ajsts-5382	11	93	vast	vast	ADJ
ajsts-5382	11	94	and	and	CCONJ
ajsts-5382	11	95	plays	play	VERB
ajsts-5382	11	96	a	a	DET
ajsts-5382	11	97	significant	significant	ADJ
ajsts-5382	11	98	role	role	NOUN
ajsts-5382	11	99	in	in	ADP
ajsts-5382	11	100	the	the	DET
ajsts-5382	11	101	advancement	advancement	NOUN
ajsts-5382	11	102	of	of	ADP
ajsts-5382	11	103	agricultural	agricultural	ADJ
ajsts-5382	11	104	technology	technology	NOUN
ajsts-5382	11	105	.	.	PUNCT
ajsts-5382	12	1	the	the	DET
ajsts-5382	12	2	approaches	approach	NOUN
ajsts-5382	12	3	used	use	VERB
ajsts-5382	12	4	were	be	AUX
ajsts-5382	12	5	used	use	VERB
ajsts-5382	12	6	to	to	PART
ajsts-5382	12	7	evaluate	evaluate	VERB
ajsts-5382	12	8	the	the	DET
ajsts-5382	12	9	data	datum	NOUN
ajsts-5382	12	10	set	set	VERB
ajsts-5382	12	11	of	of	ADP
ajsts-5382	12	12	images	image	NOUN
ajsts-5382	12	13	.	.	PUNCT
ajsts-5382	13	1	the	the	DET
ajsts-5382	13	2	images	image	NOUN
ajsts-5382	13	3	are	be	AUX
ajsts-5382	13	4	clear	clear	ADJ
ajsts-5382	13	5	with	with	ADP
ajsts-5382	13	6	proper	proper	ADJ
ajsts-5382	13	7	originality	originality	NOUN
ajsts-5382	13	8	and	and	CCONJ
ajsts-5382	13	9	appropriate	appropriate	ADJ
ajsts-5382	13	10	for	for	ADP
ajsts-5382	13	11	evaluation	evaluation	NOUN
ajsts-5382	13	12	.	.	PUNCT
ajsts-5382	14	1	therefore	therefore	ADV
ajsts-5382	14	2	,	,	PUNCT
ajsts-5382	14	3	the	the	DET
ajsts-5382	14	4	technological	technological	ADJ
ajsts-5382	14	5	enhancement	enhancement	NOUN
ajsts-5382	14	6	toward	toward	ADP
ajsts-5382	14	7	the	the	DET
ajsts-5382	14	8	uses	use	NOUN
ajsts-5382	14	9	of	of	ADP
ajsts-5382	14	10	artificial	artificial	ADJ
ajsts-5382	14	11	intelligence	intelligence	NOUN
ajsts-5382	14	12	and	and	CCONJ
ajsts-5382	14	13	its	its	PRON
ajsts-5382	14	14	based	base	VERB
ajsts-5382	14	15	method	method	NOUN
ajsts-5382	14	16	for	for	ADP
ajsts-5382	14	17	the	the	DET
ajsts-5382	14	18	image	image	NOUN
ajsts-5382	14	19	evaluations	evaluation	NOUN
ajsts-5382	14	20	for	for	ADP
ajsts-5382	14	21	the	the	DET
ajsts-5382	14	22	soybean	soybean	NOUN
ajsts-5382	14	23	crop	crop	NOUN
ajsts-5382	14	24	farming	farming	NOUN
ajsts-5382	14	25	.	.	PUNCT
ajsts-5382	15	1	technologically	technologically	ADV
ajsts-5382	15	2	,	,	PUNCT
ajsts-5382	15	3	the	the	DET
ajsts-5382	15	4	devices	device	NOUN
ajsts-5382	15	5	deployed	deploy	VERB
ajsts-5382	15	6	for	for	ADP
ajsts-5382	15	7	the	the	DET
ajsts-5382	15	8	image	image	NOUN
ajsts-5382	15	9	extractions	extraction	NOUN
ajsts-5382	15	10	and	and	CCONJ
ajsts-5382	15	11	the	the	DET
ajsts-5382	15	12	images	image	NOUN
ajsts-5382	15	13	of	of	ADP
ajsts-5382	15	14	the	the	DET
ajsts-5382	15	15	plant	plant	NOUN
ajsts-5382	15	16	picked	pick	VERB
ajsts-5382	15	17	from	from	ADP
ajsts-5382	15	18	the	the	DET
ajsts-5382	15	19	field	field	NOUN
ajsts-5382	15	20	and	and	CCONJ
ajsts-5382	15	21	images	image	NOUN
ajsts-5382	15	22	are	be	AUX
ajsts-5382	15	23	further	far	ADV
ajsts-5382	15	24	forwarded	forward	VERB
ajsts-5382	15	25	for	for	ADP
ajsts-5382	15	26	the	the	DET
ajsts-5382	15	27	input	input	NOUN
ajsts-5382	15	28	values	value	NOUN
ajsts-5382	15	29	.	.	PUNCT
ajsts-5382	16	1	image	image	NOUN
ajsts-5382	16	2	recognition	recognition	NOUN
ajsts-5382	16	3	in	in	ADP
ajsts-5382	16	4	agriculture	agriculture	NOUN
ajsts-5382	16	5	has	have	AUX
ajsts-5382	16	6	promoted	promote	VERB
ajsts-5382	16	7	research	research	NOUN
ajsts-5382	16	8	for	for	ADP
ajsts-5382	16	9	the	the	DET
ajsts-5382	16	10	increase	increase	NOUN
ajsts-5382	16	11	in	in	ADP
ajsts-5382	16	12	the	the	DET
ajsts-5382	16	13	production	production	NOUN
ajsts-5382	16	14	of	of	ADP
ajsts-5382	16	15	the	the	DET
ajsts-5382	16	16	crop	crop	NOUN
ajsts-5382	16	17	.	.	PUNCT
ajsts-5382	17	1	additionally	additionally	ADV
ajsts-5382	17	2	,	,	PUNCT
ajsts-5382	17	3	crop	crop	NOUN
ajsts-5382	17	4	evaluation	evaluation	NOUN
ajsts-5382	17	5	research	research	NOUN
ajsts-5382	17	6	facilitates	facilitate	VERB
ajsts-5382	17	7	the	the	DET
ajsts-5382	17	8	identification	identification	NOUN
ajsts-5382	17	9	of	of	ADP
ajsts-5382	17	10	the	the	DET
ajsts-5382	17	11	health	health	NOUN
ajsts-5382	17	12	condition	condition	NOUN
ajsts-5382	17	13	of	of	ADP
ajsts-5382	17	14	the	the	DET
ajsts-5382	17	15	crop	crop	NOUN
ajsts-5382	17	16	plant	plant	NOUN
ajsts-5382	17	17	.	.	PUNCT
ajsts-5382	18	1	the	the	DET
ajsts-5382	18	2	system	system	NOUN
ajsts-5382	18	3	that	that	PRON
ajsts-5382	18	4	the	the	DET
ajsts-5382	18	5	paper	paper	NOUN
ajsts-5382	18	6	shows	show	VERB
ajsts-5382	18	7	focus	focus	VERB
ajsts-5382	18	8	on	on	ADP
ajsts-5382	18	9	the	the	DET
ajsts-5382	18	10	design	design	NOUN
ajsts-5382	18	11	of	of	ADP
ajsts-5382	18	12	the	the	DET
ajsts-5382	18	13	device	device	NOUN
ajsts-5382	18	14	and	and	CCONJ
ajsts-5382	18	15	the	the	DET
ajsts-5382	18	16	adoption	adoption	NOUN
ajsts-5382	18	17	of	of	ADP
ajsts-5382	18	18	the	the	DET
ajsts-5382	18	19	best	good	ADJ
ajsts-5382	18	20	method	method	NOUN
ajsts-5382	18	21	based	base	VERB
ajsts-5382	18	22	on	on	ADP
ajsts-5382	18	23	artificial	artificial	ADJ
ajsts-5382	18	24	intelligence	intelligence	NOUN
ajsts-5382	18	25	for	for	ADP
ajsts-5382	18	26	the	the	DET
ajsts-5382	18	27	validation	validation	NOUN
ajsts-5382	18	28	of	of	ADP
ajsts-5382	18	29	image	image	NOUN
ajsts-5382	18	30	-	-	PUNCT
ajsts-5382	18	31	based	base	VERB
ajsts-5382	18	32	data	data	NOUN
ajsts-5382	18	33	sets	set	NOUN
ajsts-5382	18	34	.	.	PUNCT
ajsts-5382	19	1	the	the	DET
ajsts-5382	19	2	approaches	approach	NOUN
ajsts-5382	19	3	of	of	ADP
ajsts-5382	19	4	residual	residual	ADJ
ajsts-5382	19	5	neural	neural	ADJ
ajsts-5382	19	6	network	network	NOUN
ajsts-5382	19	7	(	(	PUNCT
ajsts-5382	19	8	rnn	rnn	PROPN
ajsts-5382	19	9	)	)	PUNCT
ajsts-5382	19	10	are	be	AUX
ajsts-5382	19	11	suitable	suitable	ADJ
ajsts-5382	19	12	for	for	ADP
ajsts-5382	19	13	proper	proper	ADJ
ajsts-5382	19	14	validation	validation	NOUN
ajsts-5382	19	15	of	of	ADP
ajsts-5382	19	16	the	the	DET
ajsts-5382	19	17	image	image	NOUN
ajsts-5382	19	18	-	-	PUNCT
ajsts-5382	19	19	based	base	VERB
ajsts-5382	19	20	dataset	dataset	NOUN
ajsts-5382	19	21	.	.	PUNCT
ajsts-5382	20	1	here	here	ADV
ajsts-5382	20	2	,	,	PUNCT
ajsts-5382	20	3	the	the	DET
ajsts-5382	20	4	research	research	NOUN
ajsts-5382	20	5	engaged	engage	VERB
ajsts-5382	20	6	the	the	DET
ajsts-5382	20	7	iot	iot	NOUN
ajsts-5382	20	8	-	-	PUNCT
ajsts-5382	20	9	based	base	VERB
ajsts-5382	20	10	image	image	NOUN
ajsts-5382	20	11	cameras	camera	NOUN
ajsts-5382	20	12	that	that	PRON
ajsts-5382	20	13	study	study	VERB
ajsts-5382	20	14	and	and	CCONJ
ajsts-5382	20	15	evaluate	evaluate	VERB
ajsts-5382	20	16	data	data	NOUN
ajsts-5382	20	17	sets	set	NOUN
ajsts-5382	20	18	of	of	ADP
ajsts-5382	20	19	files	file	NOUN
ajsts-5382	20	20	and	and	CCONJ
ajsts-5382	20	21	input	input	VERB
ajsts-5382	20	22	the	the	DET
ajsts-5382	20	23	values	value	NOUN
ajsts-5382	20	24	of	of	ADP
ajsts-5382	20	25	the	the	DET
ajsts-5382	20	26	rnn	rnn	NOUN
ajsts-5382	20	27	method	method	NOUN
ajsts-5382	20	28	of	of	ADP
ajsts-5382	20	29	evaluation	evaluation	NOUN
ajsts-5382	20	30	of	of	ADP
ajsts-5382	20	31	the	the	DET
ajsts-5382	20	32	crop	crop	NOUN
ajsts-5382	20	33	conditions	condition	NOUN
ajsts-5382	20	34	.	.	PUNCT
ajsts-5382	21	1	as	as	SCONJ
ajsts-5382	21	2	research	research	NOUN
ajsts-5382	21	3	supports	support	NOUN
ajsts-5382	21	4	,	,	PUNCT
ajsts-5382	21	5	the	the	DET
ajsts-5382	21	6	ideology	ideology	NOUN
ajsts-5382	21	7	is	be	AUX
ajsts-5382	21	8	extracted	extract	VERB
ajsts-5382	21	9	based	base	VERB
ajsts-5382	21	10	on	on	ADP
ajsts-5382	21	11	technical	technical	ADJ
ajsts-5382	21	12	devices	device	NOUN
ajsts-5382	21	13	that	that	PRON
ajsts-5382	21	14	support	support	VERB
ajsts-5382	21	15	the	the	DET
ajsts-5382	21	16	states	state	NOUN
ajsts-5382	21	17	of	of	ADP
ajsts-5382	21	18	the	the	DET
ajsts-5382	21	19	root	root	NOUN
ajsts-5382	21	20	formation	formation	NOUN
ajsts-5382	21	21	and	and	CCONJ
ajsts-5382	21	22	condition	condition	NOUN
ajsts-5382	21	23	of	of	ADP
ajsts-5382	21	24	the	the	DET
ajsts-5382	21	25	soybean	soybean	NOUN
ajsts-5382	21	26	plant	plant	NOUN
ajsts-5382	21	27	in	in	ADP
ajsts-5382	21	28	the	the	DET
ajsts-5382	21	29	farming	farming	NOUN
ajsts-5382	21	30	of	of	ADP
ajsts-5382	21	31	soybeans	soybean	NOUN
ajsts-5382	21	32	(	(	PUNCT
ajsts-5382	21	33	he	he	PRON
ajsts-5382	21	34	,	,	PUNCT
ajsts-5382	21	35	2016	2016	NUM
ajsts-5382	21	36	)	)	PUNCT
ajsts-5382	21	37	.	.	PUNCT
ajsts-5382	22	1	figure	figure	VERB
ajsts-5382	22	2	1	1	NUM
ajsts-5382	22	3	:	:	PUNCT
ajsts-5382	22	4	model	model	NOUN
ajsts-5382	22	5	of	of	ADP
ajsts-5382	22	6	the	the	DET
ajsts-5382	22	7	evaluating	evaluate	VERB
ajsts-5382	22	8	the	the	DET
ajsts-5382	22	9	soybean	soybean	NOUN
ajsts-5382	22	10	plants	plant	NOUN
ajsts-5382	22	11	and	and	CCONJ
ajsts-5382	22	12	roots	root	NOUN
ajsts-5382	22	13	images	image	VERB
ajsts-5382	22	14	analysis	analysis	NOUN
ajsts-5382	22	15	literature	literature	NOUN
ajsts-5382	22	16	reviews	review	VERB
ajsts-5382	22	17	the	the	DET
ajsts-5382	22	18	literature	literature	NOUN
ajsts-5382	22	19	review	review	NOUN
ajsts-5382	22	20	considers	consider	VERB
ajsts-5382	22	21	the	the	DET
ajsts-5382	22	22	two	two	NUM
ajsts-5382	22	23	states	state	NOUN
ajsts-5382	22	24	of	of	ADP
ajsts-5382	22	25	image	image	NOUN
ajsts-5382	22	26	segmentation	segmentation	NOUN
ajsts-5382	22	27	,	,	PUNCT
ajsts-5382	22	28	the	the	DET
ajsts-5382	22	29	first	first	ADJ
ajsts-5382	22	30	is	be	AUX
ajsts-5382	22	31	considered	consider	VERB
ajsts-5382	22	32	which	which	PRON
ajsts-5382	22	33	is	be	AUX
ajsts-5382	22	34	based	base	VERB
ajsts-5382	22	35	on	on	ADP
ajsts-5382	22	36	computer	computer	NOUN
ajsts-5382	22	37	vision	vision	NOUN
ajsts-5382	22	38	and	and	CCONJ
ajsts-5382	22	39	the	the	DET
ajsts-5382	22	40	states	state	NOUN
ajsts-5382	22	41	of	of	ADP
ajsts-5382	22	42	images	image	NOUN
ajsts-5382	22	43	.	.	PUNCT
ajsts-5382	23	1	the	the	DET
ajsts-5382	23	2	second	second	NOUN
ajsts-5382	23	3	is	be	AUX
ajsts-5382	23	4	based	base	VERB
ajsts-5382	23	5	on	on	ADP
ajsts-5382	23	6	the	the	DET
ajsts-5382	23	7	model	model	NOUN
ajsts-5382	23	8	of	of	ADP
ajsts-5382	23	9	iot	iot	PROPN
ajsts-5382	23	10	controllers	controller	NOUN
ajsts-5382	23	11	that	that	PRON
ajsts-5382	23	12	illustrates	illustrate	VERB
ajsts-5382	23	13	the	the	DET
ajsts-5382	23	14	image	image	NOUN
ajsts-5382	23	15	processing	processing	NOUN
ajsts-5382	23	16	for	for	ADP
ajsts-5382	23	17	the	the	DET
ajsts-5382	23	18	segmentation	segmentation	NOUN
ajsts-5382	23	19	and	and	CCONJ
ajsts-5382	23	20	is	be	AUX
ajsts-5382	23	21	forwarded	forward	VERB
ajsts-5382	23	22	pa	pa	PROPN
ajsts-5382	23	23	ge	ge	PROPN
ajsts-5382	23	24	58	58	NUM
ajsts-5382	23	25	https://journals.e-palli.com/home/index.php/ajsts	https://journals.e-palli.com/home/index.php/ajst	NOUN
ajsts-5382	23	26	am	be	AUX
ajsts-5382	23	27	.	.	PUNCT
ajsts-5382	24	1	j.	j.	PROPN
ajsts-5382	24	2	smart	smart	PROPN
ajsts-5382	24	3	.	.	PUNCT
ajsts-5382	25	1	technol	technol	PROPN
ajsts-5382	25	2	.	.	PUNCT
ajsts-5382	25	3	solutions	solution	NOUN
ajsts-5382	25	4	4(2	4(2	NUM
ajsts-5382	25	5	)	)	PUNCT
ajsts-5382	25	6	57	57	NUM
ajsts-5382	25	7	-	-	SYM
ajsts-5382	25	8	62	62	NUM
ajsts-5382	25	9	,	,	PUNCT
ajsts-5382	25	10	2025	2025	NUM
ajsts-5382	25	11	to	to	ADP
ajsts-5382	25	12	the	the	DET
ajsts-5382	25	13	machine	machine	NOUN
ajsts-5382	25	14	learning	learning	NOUN
ajsts-5382	25	15	-	-	PUNCT
ajsts-5382	25	16	based	base	VERB
ajsts-5382	25	17	model	model	NOUN
ajsts-5382	25	18	of	of	ADP
ajsts-5382	25	19	the	the	DET
ajsts-5382	25	20	imaging	imaging	NOUN
ajsts-5382	25	21	system	system	NOUN
ajsts-5382	25	22	is	be	AUX
ajsts-5382	25	23	resnn	resnn	X
ajsts-5382	25	24	(	(	PUNCT
ajsts-5382	25	25	krizhevsky	krizhevsky	NOUN
ajsts-5382	25	26	,	,	PUNCT
ajsts-5382	25	27	2017	2017	NUM
ajsts-5382	25	28	)	)	PUNCT
ajsts-5382	25	29	.	.	PUNCT
ajsts-5382	26	1	based	base	VERB
ajsts-5382	26	2	on	on	ADP
ajsts-5382	26	3	computer	computer	NOUN
ajsts-5382	26	4	vision	vision	NOUN
ajsts-5382	26	5	techniques	technique	NOUN
ajsts-5382	26	6	:	:	PUNCT
ajsts-5382	26	7	computer	computer	NOUN
ajsts-5382	26	8	vision	vision	NOUN
ajsts-5382	26	9	technology	technology	NOUN
ajsts-5382	26	10	can	can	AUX
ajsts-5382	26	11	be	be	AUX
ajsts-5382	26	12	used	use	VERB
ajsts-5382	26	13	in	in	ADP
ajsts-5382	26	14	agriculture	agriculture	NOUN
ajsts-5382	26	15	to	to	PART
ajsts-5382	26	16	help	help	VERB
ajsts-5382	26	17	farmers	farmer	NOUN
ajsts-5382	26	18	monitor	monitor	VERB
ajsts-5382	26	19	crops	crop	NOUN
ajsts-5382	26	20	,	,	PUNCT
ajsts-5382	26	21	detect	detect	VERB
ajsts-5382	26	22	pests	pest	NOUN
ajsts-5382	26	23	and	and	CCONJ
ajsts-5382	26	24	diseases	disease	NOUN
ajsts-5382	26	25	,	,	PUNCT
ajsts-5382	26	26	and	and	CCONJ
ajsts-5382	26	27	improve	improve	VERB
ajsts-5382	26	28	yields	yield	NOUN
ajsts-5382	26	29	:	:	PUNCT
ajsts-5382	26	30	crop	crop	NOUN
ajsts-5382	26	31	monitoring	monitor	VERB
ajsts-5382	26	32	high	high	ADJ
ajsts-5382	26	33	-	-	PUNCT
ajsts-5382	26	34	resolution	resolution	NOUN
ajsts-5382	26	35	cameras	camera	NOUN
ajsts-5382	26	36	and	and	CCONJ
ajsts-5382	26	37	algorithms	algorithm	NOUN
ajsts-5382	26	38	can	can	AUX
ajsts-5382	26	39	analyze	analyze	VERB
ajsts-5382	26	40	images	image	NOUN
ajsts-5382	26	41	of	of	ADP
ajsts-5382	26	42	crops	crop	NOUN
ajsts-5382	26	43	to	to	PART
ajsts-5382	26	44	provide	provide	VERB
ajsts-5382	26	45	insights	insight	NOUN
ajsts-5382	26	46	into	into	ADP
ajsts-5382	26	47	plant	plant	NOUN
ajsts-5382	26	48	health	health	NOUN
ajsts-5382	26	49	,	,	PUNCT
ajsts-5382	26	50	growth	growth	NOUN
ajsts-5382	26	51	stages	stage	NOUN
ajsts-5382	26	52	,	,	PUNCT
ajsts-5382	26	53	and	and	CCONJ
ajsts-5382	26	54	potential	potential	ADJ
ajsts-5382	26	55	yield	yield	NOUN
ajsts-5382	26	56	.	.	PUNCT
ajsts-5382	27	1	pest	pest	NOUN
ajsts-5382	27	2	and	and	CCONJ
ajsts-5382	27	3	disease	disease	NOUN
ajsts-5382	27	4	detection	detection	NOUN
ajsts-5382	27	5	computer	computer	NOUN
ajsts-5382	27	6	vision	vision	NOUN
ajsts-5382	27	7	systems	system	NOUN
ajsts-5382	27	8	can	can	AUX
ajsts-5382	27	9	help	help	AUX
ajsts-5382	27	10	identify	identify	VERB
ajsts-5382	27	11	potential	potential	ADJ
ajsts-5382	27	12	pests	pest	NOUN
ajsts-5382	27	13	and	and	CCONJ
ajsts-5382	27	14	diseases	disease	NOUN
ajsts-5382	27	15	that	that	PRON
ajsts-5382	27	16	may	may	AUX
ajsts-5382	27	17	cause	cause	VERB
ajsts-5382	27	18	crop	crop	NOUN
ajsts-5382	27	19	losses	loss	NOUN
ajsts-5382	27	20	.	.	PUNCT
ajsts-5382	28	1	weed	weed	NOUN
ajsts-5382	28	2	identification	identification	NOUN
ajsts-5382	28	3	computer	computer	NOUN
ajsts-5382	28	4	vision	vision	NOUN
ajsts-5382	28	5	can	can	AUX
ajsts-5382	28	6	help	help	AUX
ajsts-5382	28	7	identify	identify	VERB
ajsts-5382	28	8	weeds	weed	NOUN
ajsts-5382	28	9	and	and	CCONJ
ajsts-5382	28	10	apply	apply	VERB
ajsts-5382	28	11	precision	precision	NOUN
ajsts-5382	28	12	herbicides	herbicide	NOUN
ajsts-5382	28	13	.	.	PUNCT
ajsts-5382	29	1	yield	yield	NOUN
ajsts-5382	29	2	prediction	prediction	NOUN
ajsts-5382	29	3	by	by	ADP
ajsts-5382	29	4	analysing	analyse	VERB
ajsts-5382	29	5	factors	factor	NOUN
ajsts-5382	29	6	like	like	ADP
ajsts-5382	29	7	plant	plant	NOUN
ajsts-5382	29	8	height	height	NOUN
ajsts-5382	29	9	,	,	PUNCT
ajsts-5382	29	10	leaf	leaf	NOUN
ajsts-5382	29	11	area	area	NOUN
ajsts-5382	29	12	,	,	PUNCT
ajsts-5382	29	13	and	and	CCONJ
ajsts-5382	29	14	fruit	fruit	NOUN
ajsts-5382	29	15	count	count	NOUN
ajsts-5382	30	1	,	,	PUNCT
ajsts-5382	30	2	computer	computer	NOUN
ajsts-5382	30	3	vision	vision	NOUN
ajsts-5382	30	4	can	can	AUX
ajsts-5382	30	5	help	help	VERB
ajsts-5382	30	6	predict	predict	VERB
ajsts-5382	30	7	crop	crop	NOUN
ajsts-5382	30	8	yield	yield	NOUN
ajsts-5382	30	9	.	.	PUNCT
ajsts-5382	31	1	automated	automate	VERB
ajsts-5382	31	2	harvesting	harvesting	NOUN
ajsts-5382	31	3	computer	computer	NOUN
ajsts-5382	31	4	vision	vision	NOUN
ajsts-5382	31	5	can	can	AUX
ajsts-5382	31	6	help	help	VERB
ajsts-5382	31	7	automate	automate	VERB
ajsts-5382	31	8	the	the	DET
ajsts-5382	31	9	process	process	NOUN
ajsts-5382	31	10	of	of	ADP
ajsts-5382	31	11	harvesting	harvest	VERB
ajsts-5382	31	12	crops	crop	NOUN
ajsts-5382	31	13	.	.	PUNCT
ajsts-5382	32	1	soil	soil	NOUN
ajsts-5382	32	2	analysis	analysis	NOUN
ajsts-5382	32	3	computer	computer	NOUN
ajsts-5382	32	4	vision	vision	NOUN
ajsts-5382	32	5	can	can	AUX
ajsts-5382	32	6	help	help	VERB
ajsts-5382	32	7	analyze	analyze	VERB
ajsts-5382	32	8	soil	soil	NOUN
ajsts-5382	32	9	conditions	condition	NOUN
ajsts-5382	32	10	.	.	PUNCT
ajsts-5382	33	1	nutrient	nutrient	NOUN
ajsts-5382	33	2	management	management	NOUN
ajsts-5382	33	3	computer	computer	NOUN
ajsts-5382	33	4	vision	vision	NOUN
ajsts-5382	33	5	can	can	AUX
ajsts-5382	33	6	help	help	AUX
ajsts-5382	33	7	identify	identify	VERB
ajsts-5382	33	8	nutrient	nutrient	ADJ
ajsts-5382	33	9	deficiencies	deficiency	NOUN
ajsts-5382	33	10	and	and	CCONJ
ajsts-5382	33	11	apply	apply	VERB
ajsts-5382	33	12	targeted	targeted	ADJ
ajsts-5382	33	13	fertilizers	fertilizer	NOUN
ajsts-5382	33	14	.	.	PUNCT
ajsts-5382	34	1	computer	computer	NOUN
ajsts-5382	34	2	vision	vision	NOUN
ajsts-5382	34	3	can	can	AUX
ajsts-5382	34	4	be	be	AUX
ajsts-5382	34	5	used	use	VERB
ajsts-5382	34	6	in	in	ADP
ajsts-5382	34	7	a	a	DET
ajsts-5382	34	8	variety	variety	NOUN
ajsts-5382	34	9	of	of	ADP
ajsts-5382	34	10	ways	way	NOUN
ajsts-5382	34	11	,	,	PUNCT
ajsts-5382	34	12	including	include	VERB
ajsts-5382	34	13	:	:	PUNCT
ajsts-5382	34	14	(	(	PUNCT
ajsts-5382	34	15	leibe	leibe	X
ajsts-5382	34	16	et	et	PROPN
ajsts-5382	34	17	al	al	PROPN
ajsts-5382	34	18	.	.	PROPN
ajsts-5382	34	19	,	,	PUNCT
ajsts-5382	34	20	2016	2016	NUM
ajsts-5382	34	21	)	)	PUNCT
ajsts-5382	34	22	1	1	NUM
ajsts-5382	34	23	.	.	PUNCT
ajsts-5382	35	1	uavs	uavs	PROPN
ajsts-5382	35	2	:	:	PUNCT
ajsts-5382	35	3	unmanned	unmanned	ADJ
ajsts-5382	35	4	aerial	aerial	ADJ
ajsts-5382	35	5	vehicles	vehicle	NOUN
ajsts-5382	35	6	(	(	PUNCT
ajsts-5382	35	7	uavs	uavs	NOUN
ajsts-5382	35	8	)	)	PUNCT
ajsts-5382	35	9	equipped	equip	VERB
ajsts-5382	35	10	with	with	ADP
ajsts-5382	35	11	computer	computer	NOUN
ajsts-5382	35	12	vision	vision	NOUN
ajsts-5382	35	13	systems	system	NOUN
ajsts-5382	35	14	can	can	AUX
ajsts-5382	35	15	help	help	VERB
ajsts-5382	35	16	farmers	farmer	NOUN
ajsts-5382	35	17	monitor	monitor	VERB
ajsts-5382	35	18	crops	crop	NOUN
ajsts-5382	35	19	and	and	CCONJ
ajsts-5382	35	20	assess	assess	VERB
ajsts-5382	35	21	plant	plant	NOUN
ajsts-5382	35	22	health	health	NOUN
ajsts-5382	35	23	.	.	PUNCT
ajsts-5382	36	1	2	2	X
ajsts-5382	36	2	.	.	X
ajsts-5382	36	3	mobile	mobile	ADJ
ajsts-5382	36	4	robots	robot	NOUN
ajsts-5382	36	5	:	:	PUNCT
ajsts-5382	36	6	farmers	farmer	NOUN
ajsts-5382	36	7	can	can	AUX
ajsts-5382	36	8	use	use	VERB
ajsts-5382	36	9	mobile	mobile	ADJ
ajsts-5382	36	10	robots	robot	NOUN
ajsts-5382	36	11	equipped	equip	VERB
ajsts-5382	36	12	with	with	ADP
ajsts-5382	36	13	computer	computer	NOUN
ajsts-5382	36	14	vision	vision	NOUN
ajsts-5382	36	15	to	to	PART
ajsts-5382	36	16	drive	drive	VERB
ajsts-5382	36	17	around	around	ADV
ajsts-5382	36	18	and	and	CCONJ
ajsts-5382	36	19	collect	collect	VERB
ajsts-5382	36	20	data	datum	NOUN
ajsts-5382	36	21	.	.	PUNCT
ajsts-5382	37	1	3	3	X
ajsts-5382	37	2	.	.	X
ajsts-5382	37	3	static	static	ADJ
ajsts-5382	37	4	cameras	camera	NOUN
ajsts-5382	37	5	:	:	PUNCT
ajsts-5382	37	6	farmers	farmer	NOUN
ajsts-5382	37	7	can	can	AUX
ajsts-5382	37	8	use	use	VERB
ajsts-5382	37	9	static	static	ADJ
ajsts-5382	37	10	cameras	camera	NOUN
ajsts-5382	37	11	to	to	PART
ajsts-5382	37	12	take	take	VERB
ajsts-5382	37	13	images	image	NOUN
ajsts-5382	37	14	of	of	ADP
ajsts-5382	37	15	crops	crop	NOUN
ajsts-5382	37	16	from	from	ADP
ajsts-5382	37	17	an	an	DET
ajsts-5382	37	18	advantageous	advantageous	ADJ
ajsts-5382	37	19	position	position	NOUN
ajsts-5382	37	20	.	.	PUNCT
ajsts-5382	38	1	the	the	DET
ajsts-5382	38	2	authors	author	NOUN
ajsts-5382	38	3	suggested	suggest	VERB
ajsts-5382	38	4	that	that	SCONJ
ajsts-5382	38	5	,	,	PUNCT
ajsts-5382	38	6	based	base	VERB
ajsts-5382	38	7	on	on	ADP
ajsts-5382	38	8	data	datum	NOUN
ajsts-5382	38	9	availability	availability	NOUN
ajsts-5382	38	10	image	image	NOUN
ajsts-5382	38	11	quality	quality	NOUN
ajsts-5382	38	12	many	many	ADJ
ajsts-5382	38	13	studies	study	NOUN
ajsts-5382	38	14	and	and	CCONJ
ajsts-5382	38	15	competitions	competition	NOUN
ajsts-5382	38	16	used	use	VERB
ajsts-5382	38	17	plant	plant	NOUN
ajsts-5382	38	18	image	image	NOUN
ajsts-5382	38	19	datasets	dataset	NOUN
ajsts-5382	38	20	with	with	ADP
ajsts-5382	38	21	a	a	DET
ajsts-5382	38	22	single	single	ADJ
ajsts-5382	38	23	background	background	NOUN
ajsts-5382	38	24	.	.	PUNCT
ajsts-5382	39	1	for	for	ADP
ajsts-5382	39	2	example	example	NOUN
ajsts-5382	39	3	,	,	PUNCT
ajsts-5382	39	4	the	the	DET
ajsts-5382	39	5	plant	plant	NOUN
ajsts-5382	39	6	village	village	NOUN
ajsts-5382	39	7	dataset	dataset	NOUN
ajsts-5382	39	8	contains	contain	VERB
ajsts-5382	39	9	many	many	ADJ
ajsts-5382	39	10	labelled	label	VERB
ajsts-5382	39	11	plants	plant	NOUN
ajsts-5382	39	12	leaf	leaf	NOUN
ajsts-5382	39	13	images	image	NOUN
ajsts-5382	39	14	from	from	ADP
ajsts-5382	39	15	various	various	ADJ
ajsts-5382	39	16	species	specie	NOUN
ajsts-5382	39	17	with	with	ADP
ajsts-5382	39	18	different	different	ADJ
ajsts-5382	39	19	diseases	disease	NOUN
ajsts-5382	39	20	,	,	PUNCT
ajsts-5382	39	21	but	but	CCONJ
ajsts-5382	39	22	the	the	DET
ajsts-5382	39	23	pictures	picture	NOUN
ajsts-5382	39	24	were	be	AUX
ajsts-5382	39	25	from	from	ADP
ajsts-5382	39	26	a	a	DET
ajsts-5382	39	27	controlled	control	VERB
ajsts-5382	39	28	environment	environment	NOUN
ajsts-5382	39	29	,	,	PUNCT
ajsts-5382	39	30	and	and	CCONJ
ajsts-5382	39	31	their	their	PRON
ajsts-5382	39	32	backgrounds	background	NOUN
ajsts-5382	39	33	are	be	AUX
ajsts-5382	39	34	very	very	ADV
ajsts-5382	39	35	simple	simple	ADJ
ajsts-5382	39	36	.	.	PUNCT
ajsts-5382	40	1	however	however	ADV
ajsts-5382	40	2	,	,	PUNCT
ajsts-5382	40	3	because	because	SCONJ
ajsts-5382	40	4	of	of	ADP
ajsts-5382	40	5	lighting	lighting	NOUN
ajsts-5382	40	6	,	,	PUNCT
ajsts-5382	40	7	occlusion	occlusion	NOUN
ajsts-5382	40	8	,	,	PUNCT
ajsts-5382	40	9	and	and	CCONJ
ajsts-5382	40	10	shadows	shadow	NOUN
ajsts-5382	40	11	in	in	ADP
ajsts-5382	40	12	the	the	DET
ajsts-5382	40	13	natural	natural	ADJ
ajsts-5382	40	14	atmosphere	atmosphere	NOUN
ajsts-5382	40	15	,	,	PUNCT
ajsts-5382	40	16	the	the	DET
ajsts-5382	40	17	image	image	NOUN
ajsts-5382	40	18	quality	quality	NOUN
ajsts-5382	40	19	and	and	CCONJ
ajsts-5382	40	20	visual	visual	ADJ
ajsts-5382	40	21	perception	perception	NOUN
ajsts-5382	40	22	ability	ability	NOUN
ajsts-5382	40	23	will	will	AUX
ajsts-5382	40	24	degenerate	degenerate	VERB
ajsts-5382	40	25	greatly	greatly	ADV
ajsts-5382	40	26	.	.	PUNCT
ajsts-5382	41	1	many	many	ADJ
ajsts-5382	41	2	noises	noise	NOUN
ajsts-5382	41	3	appear	appear	VERB
ajsts-5382	41	4	in	in	ADP
ajsts-5382	41	5	the	the	DET
ajsts-5382	41	6	images	image	NOUN
ajsts-5382	41	7	,	,	PUNCT
ajsts-5382	41	8	which	which	PRON
ajsts-5382	41	9	is	be	AUX
ajsts-5382	41	10	a	a	DET
ajsts-5382	41	11	big	big	ADJ
ajsts-5382	41	12	challenge	challenge	NOUN
ajsts-5382	41	13	for	for	ADP
ajsts-5382	41	14	automatically	automatically	ADV
ajsts-5382	41	15	analysing	analyse	VERB
ajsts-5382	41	16	unconstrained	unconstrained	ADJ
ajsts-5382	41	17	natural	natural	ADJ
ajsts-5382	41	18	images	image	NOUN
ajsts-5382	41	19	in	in	ADP
ajsts-5382	41	20	the	the	DET
ajsts-5382	41	21	field	field	NOUN
ajsts-5382	41	22	.	.	PUNCT
ajsts-5382	42	1	although	although	SCONJ
ajsts-5382	42	2	human	human	ADJ
ajsts-5382	42	3	visual	visual	ADJ
ajsts-5382	42	4	systems	system	NOUN
ajsts-5382	42	5	can	can	AUX
ajsts-5382	42	6	easily	easily	ADV
ajsts-5382	42	7	deal	deal	VERB
ajsts-5382	42	8	with	with	ADP
ajsts-5382	42	9	these	these	DET
ajsts-5382	42	10	problems	problem	NOUN
ajsts-5382	42	11	,	,	PUNCT
ajsts-5382	42	12	establishing	establish	VERB
ajsts-5382	42	13	a	a	DET
ajsts-5382	42	14	computational	computational	ADJ
ajsts-5382	42	15	model	model	NOUN
ajsts-5382	42	16	of	of	ADP
ajsts-5382	42	17	plant	plant	NOUN
ajsts-5382	42	18	phenotyping	phenotyping	NOUN
ajsts-5382	42	19	is	be	AUX
ajsts-5382	42	20	still	still	ADV
ajsts-5382	42	21	an	an	DET
ajsts-5382	42	22	open	open	ADV
ajsts-5382	42	23	-	-	PUNCT
ajsts-5382	42	24	ended	end	VERB
ajsts-5382	42	25	question	question	NOUN
ajsts-5382	42	26	(	(	PUNCT
ajsts-5382	42	27	hu	hu	PROPN
ajsts-5382	42	28	et	et	PROPN
ajsts-5382	42	29	al	al	PROPN
ajsts-5382	42	30	.	.	PROPN
ajsts-5382	42	31	,	,	PUNCT
ajsts-5382	42	32	2018	2018	NUM
ajsts-5382	42	33	)	)	PUNCT
ajsts-5382	42	34	.	.	PUNCT
ajsts-5382	43	1	image	image	NOUN
ajsts-5382	43	2	annotation	annotation	NOUN
ajsts-5382	43	3	deep	deep	ADJ
ajsts-5382	43	4	learning	learning	NOUN
ajsts-5382	43	5	needs	need	VERB
ajsts-5382	43	6	to	to	PART
ajsts-5382	43	7	learn	learn	VERB
ajsts-5382	43	8	features	feature	NOUN
ajsts-5382	43	9	from	from	ADP
ajsts-5382	43	10	sufficient	sufficient	ADJ
ajsts-5382	43	11	annotated	annotate	VERB
ajsts-5382	43	12	data	datum	NOUN
ajsts-5382	43	13	,	,	PUNCT
ajsts-5382	43	14	but	but	CCONJ
ajsts-5382	43	15	data	datum	NOUN
ajsts-5382	43	16	annotation	annotation	NOUN
ajsts-5382	43	17	faces	face	VERB
ajsts-5382	43	18	the	the	DET
ajsts-5382	43	19	following	follow	VERB
ajsts-5382	43	20	challenges	challenge	NOUN
ajsts-5382	43	21	:	:	PUNCT
ajsts-5382	43	22	a.	a.	NOUN
ajsts-5382	43	23	manual	manual	NOUN
ajsts-5382	43	24	annotation	annotation	NOUN
ajsts-5382	43	25	sometimes	sometimes	ADV
ajsts-5382	43	26	requires	require	VERB
ajsts-5382	43	27	a	a	DET
ajsts-5382	43	28	large	large	ADJ
ajsts-5382	43	29	amount	amount	NOUN
ajsts-5382	43	30	of	of	ADP
ajsts-5382	43	31	prior	prior	ADJ
ajsts-5382	43	32	or	or	CCONJ
ajsts-5382	43	33	professional	professional	ADJ
ajsts-5382	43	34	domain	domain	NOUN
ajsts-5382	43	35	knowledge	knowledge	NOUN
ajsts-5382	43	36	and	and	CCONJ
ajsts-5382	43	37	rich	rich	ADJ
ajsts-5382	43	38	working	working	NOUN
ajsts-5382	43	39	experience	experience	NOUN
ajsts-5382	43	40	.	.	PUNCT
ajsts-5382	44	1	b.	b.	PROPN
ajsts-5382	44	2	data	data	PROPN
ajsts-5382	44	3	annotation	annotation	NOUN
ajsts-5382	44	4	is	be	AUX
ajsts-5382	44	5	a	a	DET
ajsts-5382	44	6	time	time	NOUN
ajsts-5382	44	7	-	-	PUNCT
ajsts-5382	44	8	consuming	consume	VERB
ajsts-5382	44	9	and	and	CCONJ
ajsts-5382	44	10	hectic	hectic	ADJ
ajsts-5382	44	11	step	step	NOUN
ajsts-5382	44	12	,	,	PUNCT
ajsts-5382	44	13	especially	especially	ADV
ajsts-5382	44	14	in	in	ADP
ajsts-5382	44	15	object	object	NOUN
ajsts-5382	44	16	detection	detection	NOUN
ajsts-5382	44	17	and	and	CCONJ
ajsts-5382	44	18	image	image	NOUN
ajsts-5382	44	19	segmentation	segmentation	NOUN
ajsts-5382	44	20	.	.	PUNCT
ajsts-5382	45	1	detection	detection	NOUN
ajsts-5382	45	2	and	and	CCONJ
ajsts-5382	45	3	segmentation	segmentation	NOUN
ajsts-5382	45	4	require	require	VERB
ajsts-5382	45	5	instance	instance	NOUN
ajsts-5382	45	6	-	-	PUNCT
ajsts-5382	45	7	level	level	NOUN
ajsts-5382	45	8	(	(	PUNCT
ajsts-5382	45	9	boxes	box	NOUN
ajsts-5382	45	10	)	)	PUNCT
ajsts-5382	45	11	and	and	CCONJ
ajsts-5382	45	12	pixel	pixel	ADJ
ajsts-5382	45	13	-	-	PUNCT
ajsts-5382	45	14	level	level	NOUN
ajsts-5382	45	15	annotations	annotation	NOUN
ajsts-5382	45	16	(	(	PUNCT
ajsts-5382	45	17	masks	mask	NOUN
ajsts-5382	45	18	)	)	PUNCT
ajsts-5382	45	19	.	.	PUNCT
ajsts-5382	46	1	if	if	SCONJ
ajsts-5382	46	2	more	more	ADJ
ajsts-5382	46	3	and	and	CCONJ
ajsts-5382	46	4	more	more	ADJ
ajsts-5382	46	5	images	image	NOUN
ajsts-5382	46	6	are	be	AUX
ajsts-5382	46	7	to	to	PART
ajsts-5382	46	8	be	be	AUX
ajsts-5382	46	9	annotated	annotate	VERB
ajsts-5382	46	10	,	,	PUNCT
ajsts-5382	46	11	the	the	DET
ajsts-5382	46	12	workload	workload	NOUN
ajsts-5382	46	13	will	will	AUX
ajsts-5382	46	14	be	be	AUX
ajsts-5382	46	15	massive	massive	ADJ
ajsts-5382	46	16	,	,	PUNCT
ajsts-5382	46	17	while	while	SCONJ
ajsts-5382	46	18	efficiency	efficiency	NOUN
ajsts-5382	46	19	and	and	CCONJ
ajsts-5382	46	20	accuracy	accuracy	NOUN
ajsts-5382	46	21	can	can	AUX
ajsts-5382	46	22	not	not	PART
ajsts-5382	46	23	be	be	AUX
ajsts-5382	46	24	guaranteed	guarantee	VERB
ajsts-5382	46	25	(	(	PUNCT
ajsts-5382	46	26	lin	lin	PROPN
ajsts-5382	46	27	et	et	PROPN
ajsts-5382	46	28	al	al	PROPN
ajsts-5382	46	29	.	.	PROPN
ajsts-5382	46	30	,	,	PUNCT
ajsts-5382	46	31	2019	2019	NUM
ajsts-5382	46	32	)	)	PUNCT
ajsts-5382	46	33	.	.	PUNCT
ajsts-5382	47	1	c.	c.	NOUN
ajsts-5382	47	2	some	some	DET
ajsts-5382	47	3	images	image	NOUN
ajsts-5382	47	4	lack	lack	VERB
ajsts-5382	47	5	visual	visual	ADJ
ajsts-5382	47	6	cues	cue	NOUN
ajsts-5382	47	7	,	,	PUNCT
ajsts-5382	47	8	such	such	ADJ
ajsts-5382	47	9	as	as	ADP
ajsts-5382	47	10	hyperspectral	hyperspectral	ADJ
ajsts-5382	47	11	and	and	CCONJ
ajsts-5382	47	12	thermal	thermal	ADJ
ajsts-5382	47	13	imaging	imaging	NOUN
ajsts-5382	47	14	,	,	PUNCT
ajsts-5382	47	15	so	so	SCONJ
ajsts-5382	47	16	it	it	PRON
ajsts-5382	47	17	is	be	AUX
ajsts-5382	47	18	much	much	ADV
ajsts-5382	47	19	more	more	ADV
ajsts-5382	47	20	difficult	difficult	ADJ
ajsts-5382	47	21	to	to	PART
ajsts-5382	47	22	label	label	VERB
ajsts-5382	47	23	these	these	DET
ajsts-5382	47	24	data	datum	NOUN
ajsts-5382	47	25	than	than	ADP
ajsts-5382	47	26	rgb	rgb	PROPN
ajsts-5382	47	27	images	image	NOUN
ajsts-5382	47	28	.	.	PUNCT
ajsts-5382	48	1	online	online	ADJ
ajsts-5382	48	2	researchers	researcher	NOUN
ajsts-5382	48	3	have	have	AUX
ajsts-5382	48	4	deployed	deploy	VERB
ajsts-5382	48	5	a	a	DET
ajsts-5382	48	6	human	human	ADJ
ajsts-5382	48	7	-	-	PUNCT
ajsts-5382	48	8	machine	machine	NOUN
ajsts-5382	48	9	collaboration	collaboration	NOUN
ajsts-5382	48	10	interface	interface	NOUN
ajsts-5382	48	11	called	call	VERB
ajsts-5382	48	12	fluid	fluid	ADJ
ajsts-5382	48	13	annotation	annotation	NOUN
ajsts-5382	48	14	(	(	PUNCT
ajsts-5382	48	15	andriluka	andriluka	PROPN
ajsts-5382	48	16	et	et	PROPN
ajsts-5382	48	17	al	al	PROPN
ajsts-5382	48	18	.	.	PROPN
ajsts-5382	48	19	,	,	PUNCT
ajsts-5382	48	20	2018	2018	NUM
ajsts-5382	48	21	)	)	PUNCT
ajsts-5382	48	22	that	that	PRON
ajsts-5382	48	23	can	can	AUX
ajsts-5382	48	24	be	be	AUX
ajsts-5382	48	25	used	use	VERB
ajsts-5382	48	26	to	to	PART
ajsts-5382	48	27	annotate	annotate	VERB
ajsts-5382	48	28	the	the	DET
ajsts-5382	48	29	class	class	NOUN
ajsts-5382	48	30	label	label	NOUN
ajsts-5382	48	31	and	and	CCONJ
ajsts-5382	48	32	delineate	delineate	VERB
ajsts-5382	48	33	the	the	DET
ajsts-5382	48	34	contours	contours	NOUN
ajsts-5382	48	35	of	of	ADP
ajsts-5382	48	36	every	every	DET
ajsts-5382	48	37	object	object	NOUN
ajsts-5382	48	38	and	and	CCONJ
ajsts-5382	48	39	background	background	NOUN
ajsts-5382	48	40	in	in	ADP
ajsts-5382	48	41	an	an	DET
ajsts-5382	48	42	image	image	NOUN
ajsts-5382	48	43	(	(	PUNCT
ajsts-5382	48	44	bello	bello	PROPN
ajsts-5382	48	45	et	et	PROPN
ajsts-5382	48	46	al	al	PROPN
ajsts-5382	48	47	.	.	PROPN
ajsts-5382	48	48	,	,	PUNCT
ajsts-5382	48	49	2019	2019	NUM
ajsts-5382	48	50	)	)	PUNCT
ajsts-5382	48	51	.	.	PUNCT
ajsts-5382	49	1	the	the	DET
ajsts-5382	49	2	authors	author	NOUN
ajsts-5382	49	3	suggested	suggest	VERB
ajsts-5382	49	4	the	the	DET
ajsts-5382	49	5	data	data	NOUN
ajsts-5382	49	6	-	-	PUNCT
ajsts-5382	49	7	based	base	VERB
ajsts-5382	49	8	analysis	analysis	NOUN
ajsts-5382	49	9	algorithm	algorithm	NOUN
ajsts-5382	49	10	robustness	robustness	NOUN
ajsts-5382	49	11	at	at	ADP
ajsts-5382	49	12	present	present	ADJ
ajsts-5382	49	13	,	,	PUNCT
ajsts-5382	49	14	some	some	DET
ajsts-5382	49	15	mainstream	mainstream	NOUN
ajsts-5382	49	16	algorithms	algorithm	NOUN
ajsts-5382	49	17	perform	perform	VERB
ajsts-5382	49	18	well	well	ADV
ajsts-5382	49	19	on	on	ADP
ajsts-5382	49	20	particular	particular	ADJ
ajsts-5382	49	21	datasets	dataset	NOUN
ajsts-5382	49	22	,	,	PUNCT
ajsts-5382	49	23	and	and	CCONJ
ajsts-5382	49	24	most	most	ADJ
ajsts-5382	49	25	of	of	ADP
ajsts-5382	49	26	them	they	PRON
ajsts-5382	49	27	are	be	AUX
ajsts-5382	49	28	only	only	ADV
ajsts-5382	49	29	designed	design	VERB
ajsts-5382	49	30	for	for	ADP
ajsts-5382	49	31	specific	specific	ADJ
ajsts-5382	49	32	organs	organ	NOUN
ajsts-5382	49	33	or	or	CCONJ
ajsts-5382	49	34	specific	specific	ADJ
ajsts-5382	49	35	plant	plant	NOUN
ajsts-5382	49	36	species	specie	NOUN
ajsts-5382	49	37	.	.	PUNCT
ajsts-5382	50	1	due	due	ADP
ajsts-5382	50	2	to	to	ADP
ajsts-5382	50	3	the	the	DET
ajsts-5382	50	4	large	large	ADJ
ajsts-5382	50	5	differences	difference	NOUN
ajsts-5382	50	6	in	in	ADP
ajsts-5382	50	7	colour	colour	NOUN
ajsts-5382	50	8	,	,	PUNCT
ajsts-5382	50	9	shape	shape	NOUN
ajsts-5382	50	10	,	,	PUNCT
ajsts-5382	50	11	size	size	NOUN
ajsts-5382	50	12	,	,	PUNCT
ajsts-5382	50	13	and	and	CCONJ
ajsts-5382	50	14	other	other	ADJ
ajsts-5382	50	15	characteristics	characteristic	NOUN
ajsts-5382	50	16	between	between	ADP
ajsts-5382	50	17	different	different	ADJ
ajsts-5382	50	18	detection	detection	NOUN
ajsts-5382	50	19	objects	object	NOUN
ajsts-5382	50	20	,	,	PUNCT
ajsts-5382	50	21	these	these	DET
ajsts-5382	50	22	algorithms	algorithm	NOUN
ajsts-5382	50	23	do	do	AUX
ajsts-5382	50	24	not	not	PART
ajsts-5382	50	25	generalize	generalize	VERB
ajsts-5382	50	26	well	well	ADV
ajsts-5382	50	27	.	.	PUNCT
ajsts-5382	51	1	when	when	SCONJ
ajsts-5382	51	2	the	the	DET
ajsts-5382	51	3	dataset	dataset	NOUN
ajsts-5382	51	4	changes	change	NOUN
ajsts-5382	51	5	,	,	PUNCT
ajsts-5382	51	6	many	many	ADJ
ajsts-5382	51	7	algorithms	algorithm	NOUN
ajsts-5382	51	8	will	will	AUX
ajsts-5382	51	9	be	be	AUX
ajsts-5382	51	10	invalid	invalid	ADJ
ajsts-5382	51	11	,	,	PUNCT
ajsts-5382	51	12	so	so	SCONJ
ajsts-5382	51	13	researchers	researcher	NOUN
ajsts-5382	51	14	must	must	AUX
ajsts-5382	51	15	redesign	redesign	VERB
ajsts-5382	51	16	the	the	DET
ajsts-5382	51	17	feature	feature	NOUN
ajsts-5382	51	18	extractor	extractor	NOUN
ajsts-5382	51	19	and	and	CCONJ
ajsts-5382	51	20	readjust	readjust	VERB
ajsts-5382	51	21	the	the	DET
ajsts-5382	51	22	hyperparameters	hyperparameter	NOUN
ajsts-5382	51	23	.	.	PUNCT
ajsts-5382	52	1	for	for	ADP
ajsts-5382	52	2	stress	stress	NOUN
ajsts-5382	52	3	phenotyping	phenotyping	NOUN
ajsts-5382	52	4	,	,	PUNCT
ajsts-5382	52	5	the	the	DET
ajsts-5382	52	6	degree	degree	NOUN
ajsts-5382	52	7	of	of	ADP
ajsts-5382	52	8	plant	plant	NOUN
ajsts-5382	52	9	stress	stress	NOUN
ajsts-5382	52	10	changes	change	NOUN
ajsts-5382	52	11	over	over	ADP
ajsts-5382	52	12	time	time	NOUN
ajsts-5382	52	13	.	.	PUNCT
ajsts-5382	53	1	the	the	DET
ajsts-5382	53	2	model	model	NOUN
ajsts-5382	53	3	needs	need	VERB
ajsts-5382	53	4	to	to	PART
ajsts-5382	53	5	be	be	AUX
ajsts-5382	53	6	improved	improve	VERB
ajsts-5382	53	7	and	and	CCONJ
ajsts-5382	53	8	modified	modify	VERB
ajsts-5382	53	9	to	to	PART
ajsts-5382	53	10	be	be	AUX
ajsts-5382	53	11	dynamically	dynamically	ADV
ajsts-5382	53	12	analysed	analyse	VERB
ajsts-5382	53	13	throughout	throughout	ADP
ajsts-5382	53	14	the	the	DET
ajsts-5382	53	15	entire	entire	ADJ
ajsts-5382	53	16	cycle	cycle	NOUN
ajsts-5382	53	17	of	of	ADP
ajsts-5382	53	18	stress	stress	NOUN
ajsts-5382	53	19	,	,	PUNCT
ajsts-5382	53	20	which	which	PRON
ajsts-5382	53	21	is	be	AUX
ajsts-5382	53	22	a	a	DET
ajsts-5382	53	23	challenge	challenge	NOUN
ajsts-5382	53	24	for	for	ADP
ajsts-5382	53	25	designing	design	VERB
ajsts-5382	53	26	a	a	DET
ajsts-5382	53	27	processing	processing	NOUN
ajsts-5382	53	28	framework	framework	NOUN
ajsts-5382	53	29	(	(	PUNCT
ajsts-5382	53	30	li	li	PROPN
ajsts-5382	53	31	et	et	PROPN
ajsts-5382	53	32	al	al	PROPN
ajsts-5382	53	33	.	.	PROPN
ajsts-5382	53	34	,	,	PUNCT
ajsts-5382	53	35	2018	2018	NUM
ajsts-5382	53	36	)	)	PUNCT
ajsts-5382	53	37	.	.	PUNCT
ajsts-5382	54	1	deep	deep	ADJ
ajsts-5382	54	2	learning	learning	NOUN
ajsts-5382	54	3	firstly	firstly	ADV
ajsts-5382	54	4	,	,	PUNCT
ajsts-5382	54	5	deep	deep	ADJ
ajsts-5382	54	6	learning	learning	NOUN
ajsts-5382	54	7	-	-	PUNCT
ajsts-5382	54	8	based	base	VERB
ajsts-5382	54	9	algorithms	algorithm	NOUN
ajsts-5382	54	10	rely	rely	VERB
ajsts-5382	54	11	on	on	ADP
ajsts-5382	54	12	a	a	DET
ajsts-5382	54	13	big	big	ADJ
ajsts-5382	54	14	number	number	NOUN
ajsts-5382	54	15	of	of	ADP
ajsts-5382	54	16	labelled	label	VERB
ajsts-5382	54	17	sample	sample	NOUN
ajsts-5382	54	18	images	image	NOUN
ajsts-5382	54	19	,	,	PUNCT
ajsts-5382	54	20	which	which	PRON
ajsts-5382	54	21	makes	make	VERB
ajsts-5382	54	22	it	it	PRON
ajsts-5382	54	23	difficult	difficult	ADJ
ajsts-5382	54	24	to	to	PART
ajsts-5382	54	25	achieve	achieve	VERB
ajsts-5382	54	26	excellent	excellent	ADJ
ajsts-5382	54	27	results	result	NOUN
ajsts-5382	54	28	in	in	ADP
ajsts-5382	54	29	the	the	DET
ajsts-5382	54	30	following	follow	VERB
ajsts-5382	54	31	three	three	NUM
ajsts-5382	54	32	scenarios	scenario	NOUN
ajsts-5382	54	33	:	:	PUNCT
ajsts-5382	54	34	•	•	NUM
ajsts-5382	54	35	training	training	NOUN
ajsts-5382	54	36	samples	sample	NOUN
ajsts-5382	54	37	do	do	AUX
ajsts-5382	54	38	not	not	PART
ajsts-5382	54	39	exist	exist	VERB
ajsts-5382	54	40	in	in	ADP
ajsts-5382	54	41	some	some	DET
ajsts-5382	54	42	object	object	NOUN
ajsts-5382	54	43	categories	category	NOUN
ajsts-5382	54	44	.	.	PUNCT
ajsts-5382	55	1	•	•	INTJ
ajsts-5382	55	2	there	there	PRON
ajsts-5382	55	3	are	be	VERB
ajsts-5382	55	4	a	a	DET
ajsts-5382	55	5	few	few	ADJ
ajsts-5382	55	6	samples	sample	NOUN
ajsts-5382	55	7	in	in	ADP
ajsts-5382	55	8	object	object	NOUN
ajsts-5382	55	9	categories	category	NOUN
ajsts-5382	55	10	.	.	PUNCT
ajsts-5382	56	1	•	•	NUM
ajsts-5382	56	2	the	the	DET
ajsts-5382	56	3	sample	sample	NOUN
ajsts-5382	56	4	size	size	NOUN
ajsts-5382	56	5	of	of	ADP
ajsts-5382	56	6	different	different	ADJ
ajsts-5382	56	7	categories	category	NOUN
ajsts-5382	56	8	is	be	AUX
ajsts-5382	56	9	extremely	extremely	ADV
ajsts-5382	56	10	imbalanced	imbalanced	ADJ
ajsts-5382	56	11	.	.	PUNCT
ajsts-5382	57	1	then	then	ADV
ajsts-5382	57	2	,	,	PUNCT
ajsts-5382	57	3	some	some	DET
ajsts-5382	57	4	deep	deep	ADJ
ajsts-5382	57	5	learning	learning	NOUN
ajsts-5382	57	6	-	-	PUNCT
ajsts-5382	57	7	based	base	VERB
ajsts-5382	57	8	solutions	solution	NOUN
ajsts-5382	57	9	lack	lack	VERB
ajsts-5382	57	10	prior	prior	ADJ
ajsts-5382	57	11	knowledge	knowledge	NOUN
ajsts-5382	57	12	,	,	PUNCT
ajsts-5382	57	13	and	and	CCONJ
ajsts-5382	57	14	it	it	PRON
ajsts-5382	57	15	is	be	AUX
ajsts-5382	57	16	difficult	difficult	ADJ
ajsts-5382	57	17	to	to	PART
ajsts-5382	57	18	adaptively	adaptively	ADV
ajsts-5382	57	19	use	use	VERB
ajsts-5382	57	20	my	my	PRON
ajsts-5382	57	21	discriminative	discriminative	NOUN
ajsts-5382	57	22	visual	visual	ADJ
ajsts-5382	57	23	features	feature	NOUN
ajsts-5382	57	24	.	.	PUNCT
ajsts-5382	58	1	moreover	moreover	ADV
ajsts-5382	58	2	,	,	PUNCT
ajsts-5382	58	3	the	the	DET
ajsts-5382	58	4	deep	deep	ADJ
ajsts-5382	58	5	neural	neural	ADJ
ajsts-5382	58	6	network	network	NOUN
ajsts-5382	58	7	is	be	AUX
ajsts-5382	58	8	used	use	VERB
ajsts-5382	58	9	as	as	ADP
ajsts-5382	58	10	a	a	DET
ajsts-5382	58	11	“	"	PUNCT
ajsts-5382	58	12	black	black	ADJ
ajsts-5382	58	13	box	box	NOUN
ajsts-5382	58	14	”	"	PUNCT
ajsts-5382	58	15	,	,	PUNCT
ajsts-5382	58	16	which	which	PRON
ajsts-5382	58	17	can	can	AUX
ajsts-5382	58	18	not	not	PART
ajsts-5382	58	19	perform	perform	VERB
ajsts-5382	58	20	explicit	explicit	ADJ
ajsts-5382	58	21	reasoning	reasoning	NOUN
ajsts-5382	58	22	and	and	CCONJ
ajsts-5382	58	23	lacks	lack	VERB
ajsts-5382	58	24	interpretability	interpretability	NOUN
ajsts-5382	58	25	.	.	PUNCT
ajsts-5382	59	1	tasks	task	NOUN
ajsts-5382	59	2	like	like	ADP
ajsts-5382	59	3	gene	gene	NOUN
ajsts-5382	59	4	-	-	PUNCT
ajsts-5382	59	5	phenotype	phenotype	NOUN
ajsts-5382	59	6	association	association	NOUN
ajsts-5382	59	7	and	and	CCONJ
ajsts-5382	59	8	image	image	NOUN
ajsts-5382	59	9	description	description	NOUN
ajsts-5382	59	10	require	require	VERB
ajsts-5382	59	11	high	high	ADJ
ajsts-5382	59	12	-	-	PUNCT
ajsts-5382	59	13	level	level	NOUN
ajsts-5382	59	14	logical	logical	ADJ
ajsts-5382	59	15	reasoning	reasoning	NOUN
ajsts-5382	59	16	and	and	CCONJ
ajsts-5382	59	17	often	often	ADV
ajsts-5382	59	18	ca	can	AUX
ajsts-5382	59	19	n’t	not	PART
ajsts-5382	59	20	be	be	AUX
ajsts-5382	59	21	solved	solve	VERB
ajsts-5382	59	22	with	with	ADP
ajsts-5382	59	23	simple	simple	ADJ
ajsts-5382	59	24	classification	classification	NOUN
ajsts-5382	59	25	or	or	CCONJ
ajsts-5382	59	26	regression	regression	NOUN
ajsts-5382	59	27	methods	method	NOUN
ajsts-5382	59	28	.	.	PUNCT
ajsts-5382	60	1	pa	pa	PROPN
ajsts-5382	60	2	ge	ge	PROPN
ajsts-5382	60	3	59	59	NUM
ajsts-5382	60	4	https://journals.e-palli.com/home/index.php/ajsts	https://journals.e-palli.com/home/index.php/ajst	NOUN
ajsts-5382	60	5	am	be	AUX
ajsts-5382	60	6	.	.	PUNCT
ajsts-5382	61	1	j.	j.	PROPN
ajsts-5382	61	2	smart	smart	PROPN
ajsts-5382	61	3	.	.	PUNCT
ajsts-5382	62	1	technol	technol	PROPN
ajsts-5382	62	2	.	.	PUNCT
ajsts-5382	62	3	solutions	solution	NOUN
ajsts-5382	62	4	4(2	4(2	NUM
ajsts-5382	62	5	)	)	PUNCT
ajsts-5382	62	6	57	57	NUM
ajsts-5382	62	7	-	-	SYM
ajsts-5382	62	8	62	62	NUM
ajsts-5382	62	9	,	,	PUNCT
ajsts-5382	62	10	2025	2025	NUM
ajsts-5382	62	11	these	these	DET
ajsts-5382	62	12	problems	problem	NOUN
ajsts-5382	62	13	need	need	VERB
ajsts-5382	62	14	more	more	ADV
ajsts-5382	62	15	advanced	advanced	ADJ
ajsts-5382	62	16	approaches	approach	NOUN
ajsts-5382	62	17	,	,	PUNCT
ajsts-5382	62	18	such	such	ADJ
ajsts-5382	62	19	as	as	ADP
ajsts-5382	62	20	:	:	PUNCT
ajsts-5382	62	21	deep	deep	ADJ
ajsts-5382	62	22	learning	learning	NOUN
ajsts-5382	62	23	model	model	NOUN
ajsts-5382	62	24	,	,	PUNCT
ajsts-5382	62	25	multimodal	multimodal	ADJ
ajsts-5382	62	26	learning	learning	NOUN
ajsts-5382	62	27	,	,	PUNCT
ajsts-5382	62	28	graphbased	graphbased	ADJ
ajsts-5382	62	29	methods	method	NOUN
ajsts-5382	62	30	(	(	PUNCT
ajsts-5382	62	31	zagoruyko	zagoruyko	NOUN
ajsts-5382	62	32	et	et	PROPN
ajsts-5382	62	33	al	al	PROPN
ajsts-5382	62	34	.	.	PROPN
ajsts-5382	62	35	,	,	PUNCT
ajsts-5382	62	36	2017	2017	NUM
ajsts-5382	62	37	)	)	PUNCT
ajsts-5382	62	38	.	.	PUNCT
ajsts-5382	63	1	finally	finally	ADV
ajsts-5382	63	2	,	,	PUNCT
ajsts-5382	63	3	most	most	ADJ
ajsts-5382	63	4	3d	3d	NUM
ajsts-5382	63	5	point	point	NOUN
ajsts-5382	63	6	clouds	cloud	NOUN
ajsts-5382	63	7	are	be	AUX
ajsts-5382	63	8	still	still	ADV
ajsts-5382	63	9	analysed	analyse	VERB
ajsts-5382	63	10	by	by	ADP
ajsts-5382	63	11	utilizing	utilize	VERB
ajsts-5382	63	12	traditional	traditional	ADJ
ajsts-5382	63	13	3d	3d	NUM
ajsts-5382	63	14	processing	processing	NOUN
ajsts-5382	63	15	methods	method	NOUN
ajsts-5382	63	16	.	.	PUNCT
ajsts-5382	64	1	solutions	solution	NOUN
ajsts-5382	64	2	based	base	VERB
ajsts-5382	64	3	on	on	ADP
ajsts-5382	64	4	deep	deep	ADJ
ajsts-5382	64	5	learning	learning	NOUN
ajsts-5382	64	6	have	have	AUX
ajsts-5382	64	7	not	not	PART
ajsts-5382	64	8	been	be	AUX
ajsts-5382	64	9	popularized	popularize	VERB
ajsts-5382	64	10	in	in	ADP
ajsts-5382	64	11	plant	plant	NOUN
ajsts-5382	64	12	phenotyping	phenotyping	NOUN
ajsts-5382	64	13	.	.	PUNCT
ajsts-5382	65	1	the	the	DET
ajsts-5382	65	2	following	follow	VERB
ajsts-5382	65	3	research	research	NOUN
ajsts-5382	65	4	aspects	aspect	NOUN
ajsts-5382	65	5	are	be	AUX
ajsts-5382	65	6	worthy	worthy	ADJ
ajsts-5382	65	7	of	of	ADP
ajsts-5382	65	8	attention	attention	NOUN
ajsts-5382	65	9	in	in	ADP
ajsts-5382	65	10	the	the	DET
ajsts-5382	65	11	future	future	NOUN
ajsts-5382	65	12	.	.	PUNCT
ajsts-5382	66	1	1	1	X
ajsts-5382	66	2	.	.	X
ajsts-5382	66	3	plant	plant	NOUN
ajsts-5382	66	4	images	image	NOUN
ajsts-5382	66	5	with	with	ADP
ajsts-5382	66	6	complex	complex	ADJ
ajsts-5382	66	7	backgrounds	background	NOUN
ajsts-5382	66	8	require	require	VERB
ajsts-5382	66	9	effective	effective	ADJ
ajsts-5382	66	10	segmentation	segmentation	NOUN
ajsts-5382	66	11	of	of	ADP
ajsts-5382	66	12	the	the	DET
ajsts-5382	66	13	foreground	foreground	NOUN
ajsts-5382	66	14	and	and	CCONJ
ajsts-5382	66	15	background	background	NOUN
ajsts-5382	66	16	.	.	PUNCT
ajsts-5382	67	1	methods	method	NOUN
ajsts-5382	67	2	based	base	VERB
ajsts-5382	67	3	on	on	ADP
ajsts-5382	67	4	deep	deep	ADJ
ajsts-5382	67	5	learning	learning	NOUN
ajsts-5382	67	6	are	be	AUX
ajsts-5382	67	7	very	very	ADV
ajsts-5382	67	8	suitable	suitable	ADJ
ajsts-5382	67	9	for	for	ADP
ajsts-5382	67	10	image	image	NOUN
ajsts-5382	67	11	segmentation	segmentation	NOUN
ajsts-5382	67	12	,	,	PUNCT
ajsts-5382	67	13	but	but	CCONJ
ajsts-5382	67	14	image	image	NOUN
ajsts-5382	67	15	annotation	annotation	NOUN
ajsts-5382	67	16	becomes	become	VERB
ajsts-5382	67	17	the	the	DET
ajsts-5382	67	18	major	major	ADJ
ajsts-5382	67	19	limiting	limit	VERB
ajsts-5382	67	20	factor	factor	NOUN
ajsts-5382	67	21	for	for	ADP
ajsts-5382	67	22	applying	apply	VERB
ajsts-5382	67	23	deep	deep	ADJ
ajsts-5382	67	24	learning	learning	NOUN
ajsts-5382	67	25	in	in	ADP
ajsts-5382	67	26	plant	plant	NOUN
ajsts-5382	67	27	phenotyping	phenotype	VERB
ajsts-5382	67	28	.	.	PUNCT
ajsts-5382	68	1	to	to	PART
ajsts-5382	68	2	reduce	reduce	VERB
ajsts-5382	68	3	the	the	DET
ajsts-5382	68	4	requirements	requirement	NOUN
ajsts-5382	68	5	of	of	ADP
ajsts-5382	68	6	annotated	annotated	ADJ
ajsts-5382	68	7	data	datum	NOUN
ajsts-5382	68	8	,	,	PUNCT
ajsts-5382	68	9	the	the	DET
ajsts-5382	68	10	following	follow	VERB
ajsts-5382	68	11	solutions	solution	NOUN
ajsts-5382	68	12	were	be	AUX
ajsts-5382	68	13	proposed	propose	VERB
ajsts-5382	68	14	and	and	CCONJ
ajsts-5382	68	15	developed	develop	VERB
ajsts-5382	68	16	:	:	PUNCT
ajsts-5382	68	17	on	on	ADP
ajsts-5382	68	18	the	the	DET
ajsts-5382	68	19	one	one	NUM
ajsts-5382	68	20	hand	hand	NOUN
ajsts-5382	68	21	,	,	PUNCT
ajsts-5382	68	22	some	some	DET
ajsts-5382	68	23	image	image	NOUN
ajsts-5382	68	24	generation	generation	NOUN
ajsts-5382	68	25	strategies	strategy	NOUN
ajsts-5382	68	26	(	(	PUNCT
ajsts-5382	68	27	e.g.	e.g.	ADV
ajsts-5382	68	28	,	,	PUNCT
ajsts-5382	68	29	gans	gan	NOUN
ajsts-5382	68	30	)	)	PUNCT
ajsts-5382	68	31	can	can	AUX
ajsts-5382	68	32	be	be	AUX
ajsts-5382	68	33	applied	apply	VERB
ajsts-5382	68	34	to	to	PART
ajsts-5382	68	35	increase	increase	VERB
ajsts-5382	68	36	image	image	NOUN
ajsts-5382	68	37	diversity	diversity	NOUN
ajsts-5382	68	38	and	and	CCONJ
ajsts-5382	68	39	availability	availability	NOUN
ajsts-5382	68	40	.	.	PUNCT
ajsts-5382	69	1	on	on	ADP
ajsts-5382	69	2	the	the	DET
ajsts-5382	69	3	other	other	ADJ
ajsts-5382	69	4	hand	hand	NOUN
ajsts-5382	69	5	,	,	PUNCT
ajsts-5382	69	6	the	the	DET
ajsts-5382	69	7	dependence	dependence	NOUN
ajsts-5382	69	8	of	of	ADP
ajsts-5382	69	9	models	model	NOUN
ajsts-5382	69	10	on	on	ADP
ajsts-5382	69	11	data	datum	NOUN
ajsts-5382	69	12	can	can	AUX
ajsts-5382	69	13	be	be	AUX
ajsts-5382	69	14	reduced	reduce	VERB
ajsts-5382	69	15	by	by	ADP
ajsts-5382	69	16	improving	improve	VERB
ajsts-5382	69	17	algorithms	algorithm	NOUN
ajsts-5382	69	18	,	,	PUNCT
ajsts-5382	69	19	such	such	ADJ
ajsts-5382	69	20	as	as	ADP
ajsts-5382	69	21	zero	zero	NUM
ajsts-5382	69	22	sample	sample	NOUN
ajsts-5382	69	23	learning	learning	NOUN
ajsts-5382	69	24	,	,	PUNCT
ajsts-5382	69	25	small	small	ADJ
ajsts-5382	69	26	sample	sample	NOUN
ajsts-5382	69	27	learning	learning	NOUN
ajsts-5382	69	28	,	,	PUNCT
ajsts-5382	69	29	transfer	transfer	NOUN
ajsts-5382	69	30	learning	learning	NOUN
ajsts-5382	69	31	,	,	PUNCT
ajsts-5382	69	32	and	and	CCONJ
ajsts-5382	69	33	so	so	ADV
ajsts-5382	69	34	on	on	ADP
ajsts-5382	69	35	(	(	PUNCT
ajsts-5382	69	36	tan	tan	PROPN
ajsts-5382	69	37	&	&	CCONJ
ajsts-5382	69	38	le	le	PROPN
ajsts-5382	69	39	,	,	PUNCT
ajsts-5382	69	40	2019	2019	NUM
ajsts-5382	69	41	)	)	PUNCT
ajsts-5382	69	42	.	.	PUNCT
ajsts-5382	70	1	2	2	X
ajsts-5382	70	2	.	.	X
ajsts-5382	70	3	most	most	ADJ
ajsts-5382	70	4	existing	exist	VERB
ajsts-5382	70	5	deep	deep	ADJ
ajsts-5382	70	6	learning	learning	NOUN
ajsts-5382	70	7	algorithms	algorithm	NOUN
ajsts-5382	70	8	rely	rely	VERB
ajsts-5382	70	9	on	on	ADP
ajsts-5382	70	10	many	many	ADJ
ajsts-5382	70	11	labelled	label	VERB
ajsts-5382	70	12	images	image	NOUN
ajsts-5382	70	13	to	to	PART
ajsts-5382	70	14	fit	fit	VERB
ajsts-5382	70	15	many	many	ADJ
ajsts-5382	70	16	parameters	parameter	NOUN
ajsts-5382	70	17	for	for	ADP
ajsts-5382	70	18	prediction	prediction	NOUN
ajsts-5382	70	19	,	,	PUNCT
ajsts-5382	70	20	ignoring	ignore	VERB
ajsts-5382	70	21	the	the	DET
ajsts-5382	70	22	prior	prior	ADJ
ajsts-5382	70	23	knowledge	knowledge	NOUN
ajsts-5382	70	24	of	of	ADP
ajsts-5382	70	25	many	many	ADJ
ajsts-5382	70	26	domain	domain	NOUN
ajsts-5382	70	27	associations	association	NOUN
ajsts-5382	70	28	and	and	CCONJ
ajsts-5382	70	29	the	the	DET
ajsts-5382	70	30	intuitive	intuitive	ADJ
ajsts-5382	70	31	understanding	understanding	NOUN
ajsts-5382	70	32	of	of	ADP
ajsts-5382	70	33	decisionmaking	decisionmake	VERB
ajsts-5382	70	34	processes	process	NOUN
ajsts-5382	70	35	,	,	PUNCT
ajsts-5382	70	36	which	which	PRON
ajsts-5382	70	37	limits	limit	VERB
ajsts-5382	70	38	the	the	DET
ajsts-5382	70	39	interpretation	interpretation	NOUN
ajsts-5382	70	40	of	of	ADP
ajsts-5382	70	41	model	model	NOUN
ajsts-5382	70	42	functions	function	NOUN
ajsts-5382	70	43	to	to	ADP
ajsts-5382	70	44	a	a	DET
ajsts-5382	70	45	certain	certain	ADJ
ajsts-5382	70	46	extent	extent	NOUN
ajsts-5382	70	47	(	(	PUNCT
ajsts-5382	70	48	pharm	pharm	NOUN
ajsts-5382	70	49	,	,	PUNCT
ajsts-5382	70	50	2020	2020	NUM
ajsts-5382	70	51	)	)	PUNCT
ajsts-5382	70	52	.	.	PUNCT
ajsts-5382	71	1	3	3	X
ajsts-5382	71	2	.	.	X
ajsts-5382	71	3	cnn	cnn	PROPN
ajsts-5382	71	4	has	have	VERB
ajsts-5382	71	5	great	great	ADJ
ajsts-5382	71	6	potential	potential	NOUN
ajsts-5382	71	7	in	in	ADP
ajsts-5382	71	8	3d	3d	PROPN
ajsts-5382	71	9	reconstruction	reconstruction	NOUN
ajsts-5382	71	10	and	and	CCONJ
ajsts-5382	71	11	segmentation	segmentation	NOUN
ajsts-5382	71	12	.	.	PUNCT
ajsts-5382	72	1	some	some	DET
ajsts-5382	72	2	approaches	approach	NOUN
ajsts-5382	72	3	use	use	VERB
ajsts-5382	72	4	cnn	cnn	PROPN
ajsts-5382	72	5	to	to	PART
ajsts-5382	72	6	project	project	VERB
ajsts-5382	72	7	2d	2d	NUM
ajsts-5382	72	8	segments	segment	NOUN
ajsts-5382	72	9	onto	onto	ADP
ajsts-5382	72	10	3d	3d	NUM
ajsts-5382	72	11	representations	representation	NOUN
ajsts-5382	72	12	or	or	CCONJ
ajsts-5382	72	13	apply	apply	VERB
ajsts-5382	72	14	them	they	PRON
ajsts-5382	72	15	to	to	ADP
ajsts-5382	72	16	3d	3d	NUM
ajsts-5382	72	17	images	image	NOUN
ajsts-5382	72	18	directly	directly	ADV
ajsts-5382	72	19	.	.	PUNCT
ajsts-5382	73	1	thus	thus	ADV
ajsts-5382	73	2	,	,	PUNCT
ajsts-5382	73	3	a	a	DET
ajsts-5382	73	4	lot	lot	NOUN
ajsts-5382	73	5	of	of	ADP
ajsts-5382	73	6	3d	3d	NOUN
ajsts-5382	73	7	processing	processing	NOUN
ajsts-5382	73	8	work	work	NOUN
ajsts-5382	73	9	requires	require	VERB
ajsts-5382	73	10	to	to	ADP
ajsts-5382	73	11	application	application	NOUN
ajsts-5382	73	12	of	of	ADP
ajsts-5382	73	13	cnn	cnn	PROPN
ajsts-5382	73	14	architectures	architecture	NOUN
ajsts-5382	73	15	to	to	PART
ajsts-5382	73	16	characterize	characterize	VERB
ajsts-5382	73	17	and	and	CCONJ
ajsts-5382	73	18	understand	understand	VERB
ajsts-5382	73	19	plant	plant	NOUN
ajsts-5382	73	20	phenotypes	phenotype	NOUN
ajsts-5382	73	21	directly	directly	ADV
ajsts-5382	73	22	model	model	NOUN
ajsts-5382	73	23	of	of	ADP
ajsts-5382	73	24	iot	iot	PROPN
ajsts-5382	73	25	devices	device	NOUN
ajsts-5382	73	26	for	for	ADP
ajsts-5382	73	27	image	image	NOUN
ajsts-5382	73	28	extraction	extraction	NOUN
ajsts-5382	73	29	the	the	DET
ajsts-5382	73	30	author	author	NOUN
ajsts-5382	73	31	suggested	suggest	VERB
ajsts-5382	73	32	that	that	SCONJ
ajsts-5382	73	33	the	the	DET
ajsts-5382	73	34	rapid	rapid	ADJ
ajsts-5382	73	35	evolution	evolution	NOUN
ajsts-5382	73	36	of	of	ADP
ajsts-5382	73	37	iot	iot	PROPN
ajsts-5382	73	38	devices	device	NOUN
ajsts-5382	73	39	necessitates	necessitate	VERB
ajsts-5382	73	40	efficient	efficient	ADJ
ajsts-5382	73	41	image	image	NOUN
ajsts-5382	73	42	super	super	ADJ
ajsts-5382	73	43	-	-	ADJ
ajsts-5382	73	44	resolution	resolution	ADJ
ajsts-5382	73	45	techniques	technique	NOUN
ajsts-5382	73	46	,	,	PUNCT
ajsts-5382	73	47	while	while	SCONJ
ajsts-5382	73	48	existing	exist	VERB
ajsts-5382	73	49	advanced	advanced	ADJ
ajsts-5382	73	50	methods	method	NOUN
ajsts-5382	73	51	,	,	PUNCT
ajsts-5382	73	52	based	base	VERB
ajsts-5382	73	53	on	on	ADP
ajsts-5382	73	54	deep	deep	ADJ
ajsts-5382	73	55	convolutional	convolutional	ADJ
ajsts-5382	73	56	neural	neural	ADJ
ajsts-5382	73	57	networks	network	NOUN
ajsts-5382	73	58	,	,	PUNCT
ajsts-5382	73	59	are	be	AUX
ajsts-5382	73	60	too	too	ADV
ajsts-5382	73	61	resourceintensive	resourceintensive	NOUN
ajsts-5382	73	62	for	for	ADP
ajsts-5382	73	63	these	these	DET
ajsts-5382	73	64	circuit	circuit	NOUN
ajsts-5382	73	65	-	-	PUNCT
ajsts-5382	73	66	based	base	VERB
ajsts-5382	73	67	models	model	NOUN
ajsts-5382	73	68	,	,	PUNCT
ajsts-5382	73	69	and	and	CCONJ
ajsts-5382	73	70	this	this	DET
ajsts-5382	73	71	gap	gap	NOUN
ajsts-5382	73	72	illustrates	illustrate	VERB
ajsts-5382	73	73	the	the	DET
ajsts-5382	73	74	need	need	NOUN
ajsts-5382	73	75	for	for	ADP
ajsts-5382	73	76	a	a	DET
ajsts-5382	73	77	more	more	ADV
ajsts-5382	73	78	suitable	suitable	ADJ
ajsts-5382	73	79	solution	solution	NOUN
ajsts-5382	73	80	.	.	PUNCT
ajsts-5382	74	1	in	in	ADP
ajsts-5382	74	2	this	this	DET
ajsts-5382	74	3	study	study	NOUN
ajsts-5382	74	4	,	,	PUNCT
ajsts-5382	74	5	we	we	PRON
ajsts-5382	74	6	introduce	introduce	VERB
ajsts-5382	74	7	a	a	DET
ajsts-5382	74	8	lightweight	lightweight	NOUN
ajsts-5382	74	9	,	,	PUNCT
ajsts-5382	74	10	essentially	essentially	ADV
ajsts-5382	74	11	superresolution	superresolution	NOUN
ajsts-5382	74	12	model	model	NOUN
ajsts-5382	74	13	specially	specially	ADV
ajsts-5382	74	14	designed	design	VERB
ajsts-5382	74	15	for	for	ADP
ajsts-5382	74	16	iot	iot	ADJ
ajsts-5382	74	17	devices	device	NOUN
ajsts-5382	74	18	.	.	PUNCT
ajsts-5382	75	1	this	this	DET
ajsts-5382	75	2	model	model	NOUN
ajsts-5382	75	3	incorporates	incorporate	VERB
ajsts-5382	75	4	a	a	DET
ajsts-5382	75	5	novel	novel	ADJ
ajsts-5382	75	6	deep	deep	ADJ
ajsts-5382	75	7	residual	residual	ADJ
ajsts-5382	75	8	feature	feature	NOUN
ajsts-5382	75	9	distillation	distillation	NOUN
ajsts-5382	75	10	block	block	NOUN
ajsts-5382	75	11	(	(	PUNCT
ajsts-5382	75	12	drfdb	drfdb	NOUN
ajsts-5382	75	13	)	)	PUNCT
ajsts-5382	75	14	,	,	PUNCT
ajsts-5382	75	15	which	which	PRON
ajsts-5382	75	16	leverages	leverage	VERB
ajsts-5382	75	17	a	a	DET
ajsts-5382	75	18	depthwise	depthwise	NOUN
ajsts-5382	75	19	-	-	PUNCT
ajsts-5382	75	20	separable	separable	NOUN
ajsts-5382	75	21	convolution	convolution	NOUN
ajsts-5382	75	22	block	block	NOUN
ajsts-5382	75	23	(	(	PUNCT
ajsts-5382	75	24	dcb	dcb	NOUN
ajsts-5382	75	25	)	)	PUNCT
ajsts-5382	75	26	for	for	ADP
ajsts-5382	75	27	effective	effective	ADJ
ajsts-5382	75	28	feature	feature	NOUN
ajsts-5382	75	29	extraction	extraction	NOUN
ajsts-5382	75	30	.	.	PUNCT
ajsts-5382	76	1	determined	determined	ADJ
ajsts-5382	76	2	to	to	PART
ajsts-5382	76	3	reduce	reduce	VERB
ajsts-5382	76	4	computational	computational	ADJ
ajsts-5382	76	5	and	and	CCONJ
ajsts-5382	76	6	memory	memory	NOUN
ajsts-5382	76	7	demands	demand	NOUN
ajsts-5382	76	8	without	without	ADP
ajsts-5382	76	9	changes	change	NOUN
ajsts-5382	76	10	to	to	ADP
ajsts-5382	76	11	image	image	NOUN
ajsts-5382	76	12	quality	quality	NOUN
ajsts-5382	76	13	.	.	PUNCT
ajsts-5382	77	1	the	the	DET
ajsts-5382	77	2	model	model	NOUN
ajsts-5382	77	3	shows	show	VERB
ajsts-5382	77	4	improved	improved	ADJ
ajsts-5382	77	5	performance	performance	NOUN
ajsts-5382	77	6	metrics	metric	NOUN
ajsts-5382	77	7	like	like	ADP
ajsts-5382	77	8	psnr	psnr	NOUN
ajsts-5382	77	9	,	,	PUNCT
ajsts-5382	77	10	while	while	SCONJ
ajsts-5382	77	11	requiring	require	VERB
ajsts-5382	77	12	fewer	few	ADJ
ajsts-5382	77	13	parameters	parameter	NOUN
ajsts-5382	77	14	and	and	CCONJ
ajsts-5382	77	15	less	less	ADJ
ajsts-5382	77	16	memory	memory	NOUN
ajsts-5382	77	17	usage	usage	NOUN
ajsts-5382	77	18	,	,	PUNCT
ajsts-5382	77	19	making	make	VERB
ajsts-5382	77	20	it	it	PRON
ajsts-5382	77	21	highly	highly	ADV
ajsts-5382	77	22	suitable	suitable	ADJ
ajsts-5382	77	23	for	for	ADP
ajsts-5382	77	24	iot	iot	ADJ
ajsts-5382	77	25	applications	application	NOUN
ajsts-5382	77	26	.	.	PUNCT
ajsts-5382	78	1	this	this	DET
ajsts-5382	78	2	study	study	NOUN
ajsts-5382	78	3	presents	present	VERB
ajsts-5382	78	4	a	a	DET
ajsts-5382	78	5	breakthrough	breakthrough	NOUN
ajsts-5382	78	6	in	in	ADP
ajsts-5382	78	7	super	super	NOUN
ajsts-5382	78	8	-	-	NOUN
ajsts-5382	78	9	resolution	resolution	NOUN
ajsts-5382	78	10	for	for	ADP
ajsts-5382	78	11	iot	iot	NOUN
ajsts-5382	78	12	devices	device	NOUN
ajsts-5382	78	13	,	,	PUNCT
ajsts-5382	78	14	balancing	balance	VERB
ajsts-5382	78	15	high	high	ADJ
ajsts-5382	78	16	-	-	PUNCT
ajsts-5382	78	17	quality	quality	NOUN
ajsts-5382	78	18	image	image	NOUN
ajsts-5382	78	19	reconstruction	reconstruction	NOUN
ajsts-5382	78	20	with	with	ADP
ajsts-5382	78	21	the	the	DET
ajsts-5382	78	22	limited	limited	ADJ
ajsts-5382	78	23	resources	resource	NOUN
ajsts-5382	78	24	of	of	ADP
ajsts-5382	78	25	these	these	DET
ajsts-5382	78	26	devices	device	NOUN
ajsts-5382	78	27	(	(	PUNCT
ajsts-5382	78	28	gao	gao	PROPN
ajsts-5382	78	29	et	et	PROPN
ajsts-5382	78	30	al	al	PROPN
ajsts-5382	78	31	.	.	PROPN
ajsts-5382	78	32	,	,	PUNCT
ajsts-5382	78	33	2019	2019	NUM
ajsts-5382	78	34	)	)	PUNCT
ajsts-5382	78	35	.	.	PUNCT
ajsts-5382	79	1	materials	material	NOUN
ajsts-5382	79	2	and	and	CCONJ
ajsts-5382	79	3	methods	method	NOUN
ajsts-5382	79	4	resnn	resnn	NOUN
ajsts-5382	79	5	is	be	AUX
ajsts-5382	79	6	an	an	DET
ajsts-5382	79	7	artificial	artificial	ADJ
ajsts-5382	79	8	intelligence	intelligence	NOUN
ajsts-5382	79	9	method	method	NOUN
ajsts-5382	79	10	to	to	PART
ajsts-5382	79	11	help	help	VERB
ajsts-5382	79	12	in	in	ADP
ajsts-5382	79	13	the	the	DET
ajsts-5382	79	14	evaluation	evaluation	NOUN
ajsts-5382	79	15	of	of	ADP
ajsts-5382	79	16	the	the	DET
ajsts-5382	79	17	images	image	NOUN
ajsts-5382	79	18	of	of	ADP
ajsts-5382	79	19	the	the	DET
ajsts-5382	79	20	plant	plant	NOUN
ajsts-5382	79	21	soybean	soybean	NOUN
ajsts-5382	79	22	crop	crop	NOUN
ajsts-5382	79	23	.	.	PUNCT
ajsts-5382	80	1	a	a	DET
ajsts-5382	80	2	residual	residual	ADJ
ajsts-5382	80	3	neural	neural	ADJ
ajsts-5382	80	4	network	network	NOUN
ajsts-5382	80	5	(	(	PUNCT
ajsts-5382	80	6	resnet	resnet	NOUN
ajsts-5382	80	7	)	)	PUNCT
ajsts-5382	80	8	stacks	stack	VERB
ajsts-5382	80	9	residual	residual	ADJ
ajsts-5382	80	10	blocks	block	NOUN
ajsts-5382	80	11	on	on	ADP
ajsts-5382	80	12	top	top	NOUN
ajsts-5382	80	13	of	of	ADP
ajsts-5382	80	14	each	each	DET
ajsts-5382	80	15	other	other	ADJ
ajsts-5382	80	16	to	to	PART
ajsts-5382	80	17	form	form	VERB
ajsts-5382	80	18	a	a	DET
ajsts-5382	80	19	network	network	NOUN
ajsts-5382	80	20	.	.	PUNCT
ajsts-5382	81	1	the	the	DET
ajsts-5382	81	2	residual	residual	ADJ
ajsts-5382	81	3	neural	neural	ADJ
ajsts-5382	81	4	network	network	NOUN
ajsts-5382	81	5	to	to	PART
ajsts-5382	81	6	know	know	VERB
ajsts-5382	81	7	about	about	ADP
ajsts-5382	81	8	residual	residual	ADJ
ajsts-5382	81	9	neural	neural	ADJ
ajsts-5382	81	10	networks	network	NOUN
ajsts-5382	81	11	and	and	CCONJ
ajsts-5382	81	12	the	the	DET
ajsts-5382	81	13	most	most	ADV
ajsts-5382	81	14	popular	popular	ADJ
ajsts-5382	81	15	resnets	resnet	NOUN
ajsts-5382	81	16	,	,	PUNCT
ajsts-5382	81	17	including	include	VERB
ajsts-5382	81	18	resnet-34	resnet-34	PROPN
ajsts-5382	81	19	,	,	PUNCT
ajsts-5382	81	20	resnet-50	resnet-50	PROPN
ajsts-5382	81	21	,	,	PUNCT
ajsts-5382	81	22	and	and	CCONJ
ajsts-5382	81	23	resnet-101	resnet-101	NOUN
ajsts-5382	81	24	.	.	PUNCT
ajsts-5382	82	1	in	in	ADP
ajsts-5382	82	2	current	current	ADJ
ajsts-5382	82	3	years	year	NOUN
ajsts-5382	82	4	,	,	PUNCT
ajsts-5382	82	5	the	the	DET
ajsts-5382	82	6	field	field	NOUN
ajsts-5382	82	7	of	of	ADP
ajsts-5382	82	8	artificial	artificial	ADJ
ajsts-5382	82	9	intelligence	intelligence	NOUN
ajsts-5382	82	10	applied	apply	VERB
ajsts-5382	82	11	to	to	ADP
ajsts-5382	82	12	computer	computer	NOUN
ajsts-5382	82	13	vision	vision	NOUN
ajsts-5382	82	14	has	have	AUX
ajsts-5382	82	15	undergone	undergo	VERB
ajsts-5382	82	16	far	far	ADV
ajsts-5382	82	17	-	-	PUNCT
ajsts-5382	82	18	reaching	reach	VERB
ajsts-5382	82	19	transformations	transformation	NOUN
ajsts-5382	82	20	due	due	ADP
ajsts-5382	82	21	to	to	ADP
ajsts-5382	82	22	the	the	DET
ajsts-5382	82	23	introduction	introduction	NOUN
ajsts-5382	82	24	of	of	ADP
ajsts-5382	82	25	new	new	ADJ
ajsts-5382	82	26	technologies	technology	NOUN
ajsts-5382	82	27	(	(	PUNCT
ajsts-5382	82	28	xie	xie	PROPN
ajsts-5382	82	29	s	s	PROPN
ajsts-5382	82	30	,	,	PUNCT
ajsts-5382	82	31	zerhouni	zerhouni	PROPN
ajsts-5382	82	32	e	e	PROPN
ajsts-5382	82	33	,	,	PUNCT
ajsts-5382	82	34	huang	huang	PROPN
ajsts-5382	82	35	g	g	PROPN
ajsts-5382	82	36	,	,	PUNCT
ajsts-5382	82	37	2017	2017	NUM
ajsts-5382	82	38	)	)	PUNCT
ajsts-5382	82	39	.	.	PUNCT
ajsts-5382	83	1	a.	a.	NOUN
ajsts-5382	84	1	the	the	DET
ajsts-5382	84	2	rapid	rapid	ADJ
ajsts-5382	84	3	progress	progress	NOUN
ajsts-5382	84	4	in	in	ADP
ajsts-5382	84	5	deep	deep	ADJ
ajsts-5382	84	6	learning	learning	NOUN
ajsts-5382	84	7	has	have	AUX
ajsts-5382	84	8	enabled	enable	VERB
ajsts-5382	84	9	computer	computer	NOUN
ajsts-5382	84	10	vision	vision	NOUN
ajsts-5382	84	11	models	model	NOUN
ajsts-5382	84	12	to	to	PART
ajsts-5382	84	13	achieve	achieve	VERB
ajsts-5382	84	14	unprecedented	unprecedented	ADJ
ajsts-5382	84	15	levels	level	NOUN
ajsts-5382	84	16	of	of	ADP
ajsts-5382	84	17	accuracy	accuracy	NOUN
ajsts-5382	84	18	and	and	CCONJ
ajsts-5382	84	19	efficiency	efficiency	NOUN
ajsts-5382	84	20	in	in	ADP
ajsts-5382	84	21	tasks	task	NOUN
ajsts-5382	84	22	such	such	ADJ
ajsts-5382	84	23	as	as	ADP
ajsts-5382	84	24	image	image	NOUN
ajsts-5382	84	25	recognition	recognition	NOUN
ajsts-5382	84	26	,	,	PUNCT
ajsts-5382	84	27	object	object	NOUN
ajsts-5382	84	28	detection	detection	NOUN
ajsts-5382	84	29	,	,	PUNCT
ajsts-5382	84	30	and	and	CCONJ
ajsts-5382	84	31	face	face	NOUN
ajsts-5382	84	32	recognition	recognition	NOUN
ajsts-5382	84	33	,	,	PUNCT
ajsts-5382	84	34	surpassing	surpass	VERB
ajsts-5382	84	35	human	human	ADJ
ajsts-5382	84	36	capabilities	capability	NOUN
ajsts-5382	84	37	in	in	ADP
ajsts-5382	84	38	many	many	ADJ
ajsts-5382	84	39	cases	case	NOUN
ajsts-5382	84	40	.	.	PUNCT
ajsts-5382	85	1	b.	b.	PROPN
ajsts-5382	86	1	but	but	CCONJ
ajsts-5382	86	2	,	,	PUNCT
ajsts-5382	86	3	while	while	SCONJ
ajsts-5382	86	4	it	it	PRON
ajsts-5382	86	5	gives	give	VERB
ajsts-5382	86	6	us	we	PRON
ajsts-5382	86	7	the	the	DET
ajsts-5382	86	8	option	option	NOUN
ajsts-5382	86	9	of	of	ADP
ajsts-5382	86	10	adding	add	VERB
ajsts-5382	86	11	more	more	ADV
ajsts-5382	86	12	fully	fully	ADV
ajsts-5382	86	13	connected	connected	ADJ
ajsts-5382	86	14	layers	layer	NOUN
ajsts-5382	86	15	to	to	ADP
ajsts-5382	86	16	the	the	DET
ajsts-5382	86	17	cnns	cnn	NOUN
ajsts-5382	86	18	to	to	PART
ajsts-5382	86	19	solve	solve	VERB
ajsts-5382	86	20	more	more	ADV
ajsts-5382	86	21	complicated	complicated	ADJ
ajsts-5382	86	22	tasks	task	NOUN
ajsts-5382	86	23	in	in	ADP
ajsts-5382	86	24	computer	computer	NOUN
ajsts-5382	86	25	vision	vision	NOUN
ajsts-5382	86	26	,	,	PUNCT
ajsts-5382	86	27	it	it	PRON
ajsts-5382	86	28	comes	come	VERB
ajsts-5382	86	29	with	with	ADP
ajsts-5382	86	30	its	its	PRON
ajsts-5382	86	31	own	own	ADJ
ajsts-5382	86	32	set	set	NOUN
ajsts-5382	86	33	of	of	ADP
ajsts-5382	86	34	issues	issue	NOUN
ajsts-5382	86	35	.	.	PUNCT
ajsts-5382	87	1	it	it	PRON
ajsts-5382	87	2	has	have	AUX
ajsts-5382	87	3	been	be	AUX
ajsts-5382	87	4	observed	observe	VERB
ajsts-5382	87	5	that	that	SCONJ
ajsts-5382	87	6	training	training	NOUN
ajsts-5382	87	7	the	the	DET
ajsts-5382	87	8	nn	nn	PROPN
ajsts-5382	87	9	becomes	become	VERB
ajsts-5382	87	10	more	more	ADV
ajsts-5382	87	11	difficult	difficult	ADJ
ajsts-5382	87	12	with	with	ADP
ajsts-5382	87	13	the	the	DET
ajsts-5382	87	14	extension	extension	NOUN
ajsts-5382	87	15	in	in	ADP
ajsts-5382	87	16	the	the	DET
ajsts-5382	87	17	number	number	NOUN
ajsts-5382	87	18	of	of	ADP
ajsts-5382	87	19	added	add	VERB
ajsts-5382	87	20	layers	layer	NOUN
ajsts-5382	87	21	,	,	PUNCT
ajsts-5382	87	22	and	and	CCONJ
ajsts-5382	87	23	in	in	ADP
ajsts-5382	87	24	some	some	DET
ajsts-5382	87	25	cases	case	NOUN
ajsts-5382	87	26	,	,	PUNCT
ajsts-5382	87	27	the	the	DET
ajsts-5382	87	28	accuracy	accuracy	NOUN
ajsts-5382	87	29	dwindles	dwindle	VERB
ajsts-5382	87	30	as	as	ADV
ajsts-5382	87	31	well	well	ADV
ajsts-5382	87	32	.	.	PUNCT
ajsts-5382	88	1	c.	c.	NOUN
ajsts-5382	88	2	it	it	PRON
ajsts-5382	88	3	is	be	AUX
ajsts-5382	88	4	here	here	ADV
ajsts-5382	88	5	that	that	SCONJ
ajsts-5382	88	6	the	the	DET
ajsts-5382	88	7	use	use	NOUN
ajsts-5382	88	8	of	of	ADP
ajsts-5382	88	9	resnet	resnet	NOUN
ajsts-5382	88	10	assumes	assume	VERB
ajsts-5382	88	11	importance	importance	NOUN
ajsts-5382	88	12	.	.	PUNCT
ajsts-5382	89	1	deeper	deep	ADJ
ajsts-5382	89	2	neural	neural	ADJ
ajsts-5382	89	3	networks	network	NOUN
ajsts-5382	89	4	are	be	AUX
ajsts-5382	89	5	tough	tough	ADJ
ajsts-5382	89	6	to	to	PART
ajsts-5382	89	7	train	train	VERB
ajsts-5382	89	8	.	.	PUNCT
ajsts-5382	90	1	with	with	ADP
ajsts-5382	90	2	resnet	resnet	NOUN
ajsts-5382	90	3	,	,	PUNCT
ajsts-5382	90	4	it	it	PRON
ajsts-5382	90	5	becomes	become	VERB
ajsts-5382	90	6	easy	easy	ADJ
ajsts-5382	90	7	to	to	PART
ajsts-5382	90	8	surpass	surpass	VERB
ajsts-5382	90	9	the	the	DET
ajsts-5382	90	10	difficulties	difficulty	NOUN
ajsts-5382	90	11	of	of	ADP
ajsts-5382	90	12	training	training	NOUN
ajsts-5382	90	13	very	very	ADV
ajsts-5382	90	14	deep	deep	ADJ
ajsts-5382	90	15	neural	neural	ADJ
ajsts-5382	90	16	networks	network	NOUN
ajsts-5382	90	17	.	.	PUNCT
ajsts-5382	91	1	d.	d.	PROPN
ajsts-5382	91	2	when	when	SCONJ
ajsts-5382	91	3	working	work	VERB
ajsts-5382	91	4	with	with	ADP
ajsts-5382	91	5	deep	deep	ADJ
ajsts-5382	91	6	convolutional	convolutional	ADJ
ajsts-5382	91	7	neural	neural	ADJ
ajsts-5382	91	8	networks	network	NOUN
ajsts-5382	91	9	to	to	PART
ajsts-5382	91	10	break	break	VERB
ajsts-5382	91	11	a	a	DET
ajsts-5382	91	12	problem	problem	NOUN
ajsts-5382	91	13	related	relate	VERB
ajsts-5382	91	14	to	to	ADP
ajsts-5382	91	15	computer	computer	NOUN
ajsts-5382	91	16	vision	vision	NOUN
ajsts-5382	91	17	,	,	PUNCT
ajsts-5382	91	18	machine	machine	NOUN
ajsts-5382	91	19	learning	learn	VERB
ajsts-5382	91	20	experts	expert	NOUN
ajsts-5382	91	21	engage	engage	VERB
ajsts-5382	91	22	in	in	ADP
ajsts-5382	91	23	mounding	mound	VERB
ajsts-5382	91	24	further	further	ADJ
ajsts-5382	91	25	layers	layer	NOUN
ajsts-5382	91	26	.	.	PUNCT
ajsts-5382	92	1	these	these	DET
ajsts-5382	92	2	fresh	fresh	ADJ
ajsts-5382	92	3	layers	layer	NOUN
ajsts-5382	92	4	help	help	AUX
ajsts-5382	92	5	break	break	VERB
ajsts-5382	92	6	down	down	ADP
ajsts-5382	92	7	complex	complex	ADJ
ajsts-5382	92	8	problems	problem	NOUN
ajsts-5382	92	9	more	more	ADV
ajsts-5382	92	10	efficiently	efficiently	ADV
ajsts-5382	92	11	,	,	PUNCT
ajsts-5382	92	12	as	as	SCONJ
ajsts-5382	92	13	the	the	DET
ajsts-5382	92	14	different	different	ADJ
ajsts-5382	92	15	layers	layer	NOUN
ajsts-5382	92	16	can	can	AUX
ajsts-5382	92	17	be	be	AUX
ajsts-5382	92	18	trained	train	VERB
ajsts-5382	92	19	for	for	ADP
ajsts-5382	92	20	varying	vary	VERB
ajsts-5382	92	21	tasks	task	NOUN
ajsts-5382	92	22	to	to	PART
ajsts-5382	92	23	get	get	VERB
ajsts-5382	92	24	largely	largely	ADV
ajsts-5382	92	25	accurate	accurate	ADJ
ajsts-5382	92	26	results	result	NOUN
ajsts-5382	92	27	.	.	PUNCT
ajsts-5382	93	1	e.	e.	PROPN
ajsts-5382	93	2	while	while	SCONJ
ajsts-5382	93	3	the	the	DET
ajsts-5382	93	4	number	number	NOUN
ajsts-5382	93	5	of	of	ADP
ajsts-5382	93	6	piled	pile	VERB
ajsts-5382	93	7	layers	layer	NOUN
ajsts-5382	93	8	can	can	AUX
ajsts-5382	93	9	enrich	enrich	VERB
ajsts-5382	93	10	the	the	DET
ajsts-5382	93	11	features	feature	NOUN
ajsts-5382	93	12	of	of	ADP
ajsts-5382	93	13	the	the	DET
ajsts-5382	93	14	model	model	NOUN
ajsts-5382	93	15	,	,	PUNCT
ajsts-5382	93	16	a	a	DET
ajsts-5382	93	17	deeper	deep	ADJ
ajsts-5382	93	18	network	network	NOUN
ajsts-5382	93	19	can	can	AUX
ajsts-5382	93	20	show	show	VERB
ajsts-5382	93	21	the	the	DET
ajsts-5382	93	22	issue	issue	NOUN
ajsts-5382	93	23	of	of	ADP
ajsts-5382	93	24	declination	declination	NOUN
ajsts-5382	93	25	.	.	PUNCT
ajsts-5382	94	1	basically	basically	ADV
ajsts-5382	94	2	,	,	PUNCT
ajsts-5382	94	3	as	as	ADP
ajsts-5382	94	4	the	the	DET
ajsts-5382	94	5	number	number	NOUN
ajsts-5382	94	6	of	of	ADP
ajsts-5382	94	7	layers	layer	NOUN
ajsts-5382	94	8	of	of	ADP
ajsts-5382	94	9	the	the	DET
ajsts-5382	94	10	neural	neural	ADJ
ajsts-5382	94	11	network	network	NOUN
ajsts-5382	94	12	increases	increase	NOUN
ajsts-5382	94	13	,	,	PUNCT
ajsts-5382	94	14	the	the	DET
ajsts-5382	94	15	complexity	complexity	NOUN
ajsts-5382	94	16	of	of	ADP
ajsts-5382	94	17	situations	situation	NOUN
ajsts-5382	94	18	may	may	AUX
ajsts-5382	94	19	get	get	AUX
ajsts-5382	94	20	impregnated	impregnate	VERB
ajsts-5382	94	21	and	and	CCONJ
ajsts-5382	94	22	sluggishly	sluggishly	ADV
ajsts-5382	94	23	degrade	degrade	VERB
ajsts-5382	94	24	after	after	ADP
ajsts-5382	94	25	a	a	DET
ajsts-5382	94	26	point	point	NOUN
ajsts-5382	94	27	.	.	PUNCT
ajsts-5382	95	1	as	as	ADP
ajsts-5382	95	2	a	a	DET
ajsts-5382	95	3	result	result	NOUN
ajsts-5382	95	4	,	,	PUNCT
ajsts-5382	95	5	the	the	DET
ajsts-5382	95	6	performance	performance	NOUN
ajsts-5382	95	7	of	of	ADP
ajsts-5382	95	8	the	the	DET
ajsts-5382	95	9	model	model	NOUN
ajsts-5382	95	10	deteriorates	deteriorate	VERB
ajsts-5382	95	11	both	both	PRON
ajsts-5382	95	12	on	on	ADP
ajsts-5382	95	13	the	the	DET
ajsts-5382	95	14	training	training	NOUN
ajsts-5382	95	15	and	and	CCONJ
ajsts-5382	95	16	testing	testing	NOUN
ajsts-5382	95	17	data	datum	NOUN
ajsts-5382	95	18	.	.	PUNCT
ajsts-5382	96	1	f.	f.	PROPN
ajsts-5382	97	1	this	this	DET
ajsts-5382	97	2	declination	declination	NOUN
ajsts-5382	97	3	is	be	AUX
ajsts-5382	97	4	n’t	not	PART
ajsts-5382	97	5	a	a	DET
ajsts-5382	97	6	result	result	NOUN
ajsts-5382	97	7	of	of	ADP
ajsts-5382	97	8	overfitting	overfitte	VERB
ajsts-5382	97	9	.	.	PUNCT
ajsts-5382	98	1	rather	rather	ADV
ajsts-5382	98	2	,	,	PUNCT
ajsts-5382	98	3	it	it	PRON
ajsts-5382	98	4	may	may	AUX
ajsts-5382	98	5	affect	affect	VERB
ajsts-5382	98	6	the	the	DET
ajsts-5382	98	7	initialization	initialization	NOUN
ajsts-5382	98	8	of	of	ADP
ajsts-5382	98	9	the	the	DET
ajsts-5382	98	10	network	network	NOUN
ajsts-5382	98	11	,	,	PUNCT
ajsts-5382	98	12	optimization	optimization	NOUN
ajsts-5382	98	13	function	function	NOUN
ajsts-5382	98	14	,	,	PUNCT
ajsts-5382	98	15	or	or	CCONJ
ajsts-5382	98	16	,	,	PUNCT
ajsts-5382	98	17	more	more	ADV
ajsts-5382	98	18	importantly	importantly	ADV
ajsts-5382	98	19	,	,	PUNCT
ajsts-5382	98	20	the	the	DET
ajsts-5382	98	21	problem	problem	NOUN
ajsts-5382	98	22	of	of	ADP
ajsts-5382	98	23	evaporating	evaporate	VERB
ajsts-5382	98	24	or	or	CCONJ
ajsts-5382	98	25	exploding	explode	VERB
ajsts-5382	98	26	slant	slant	ADJ
ajsts-5382	98	27	various	various	ADJ
ajsts-5382	98	28	factors	factor	NOUN
ajsts-5382	98	29	based	base	VERB
ajsts-5382	98	30	on	on	ADP
ajsts-5382	98	31	types	type	NOUN
ajsts-5382	98	32	of	of	ADP
ajsts-5382	98	33	resnet	resnet	NOUN
ajsts-5382	98	34	are	be	AUX
ajsts-5382	98	35	as	as	SCONJ
ajsts-5382	98	36	follows	follow	VERB
ajsts-5382	98	37	resnet-50	resnet-50	NOUN
ajsts-5382	98	38	architecture	architecture	NOUN
ajsts-5382	98	39	:	:	PUNCT
ajsts-5382	98	40	bottleneck	bottleneck	NOUN
ajsts-5382	98	41	design	design	NOUN
ajsts-5382	98	42	resnet-50	resnet-50	PROPN
ajsts-5382	98	43	uses	use	VERB
ajsts-5382	98	44	a	a	DET
ajsts-5382	98	45	bottleneck	bottleneck	NOUN
ajsts-5382	98	46	design	design	NOUN
ajsts-5382	98	47	,	,	PUNCT
ajsts-5382	98	48	which	which	PRON
ajsts-5382	98	49	reduces	reduce	VERB
ajsts-5382	98	50	the	the	DET
ajsts-5382	98	51	number	number	NOUN
ajsts-5382	98	52	of	of	ADP
ajsts-5382	98	53	parameters	parameter	NOUN
ajsts-5382	98	54	and	and	CCONJ
ajsts-5382	98	55	computational	computational	ADJ
ajsts-5382	98	56	cost	cost	NOUN
ajsts-5382	98	57	.	.	PUNCT
ajsts-5382	99	1	3	3	NUM
ajsts-5382	99	2	-	-	PUNCT
ajsts-5382	99	3	layer	layer	NOUN
ajsts-5382	99	4	blocks	block	NOUN
ajsts-5382	99	5	:	:	PUNCT
ajsts-5382	100	1	resnet-50	resnet-50	NOUN
ajsts-5382	100	2	uses	use	VERB
ajsts-5382	100	3	a	a	DET
ajsts-5382	100	4	stack	stack	NOUN
ajsts-5382	100	5	of	of	ADP
ajsts-5382	100	6	3	3	NUM
ajsts-5382	100	7	layers	layer	NOUN
ajsts-5382	100	8	instead	instead	ADV
ajsts-5382	100	9	of	of	ADP
ajsts-5382	100	10	the	the	DET
ajsts-5382	100	11	earlier	early	ADJ
ajsts-5382	100	12	2	2	NUM
ajsts-5382	100	13	-	-	PUNCT
ajsts-5382	100	14	layer	layer	NOUN
ajsts-5382	100	15	blocks	block	NOUN
ajsts-5382	100	16	,	,	PUNCT
ajsts-5382	100	17	forming	form	VERB
ajsts-5382	100	18	a	a	DET
ajsts-5382	100	19	3	3	NUM
ajsts-5382	100	20	-	-	PUNCT
ajsts-5382	100	21	layer	layer	NOUN
ajsts-5382	100	22	bottleneck	bottleneck	NOUN
ajsts-5382	100	23	block	block	NOUN
ajsts-5382	100	24	.	.	PUNCT
ajsts-5382	101	1	higher	high	ADJ
ajsts-5382	101	2	accuracy	accuracy	NOUN
ajsts-5382	101	3	:	:	PUNCT
ajsts-5382	101	4	resnet-50	resnet-50	PROPN
ajsts-5382	101	5	achieves	achieve	VERB
ajsts-5382	101	6	much	much	ADV
ajsts-5382	101	7	higher	high	ADJ
ajsts-5382	101	8	accuracy	accuracy	NOUN
ajsts-5382	101	9	than	than	ADP
ajsts-5382	101	10	the	the	DET
ajsts-5382	101	11	34	34	NUM
ajsts-5382	101	12	-	-	PUNCT
ajsts-5382	101	13	layer	layer	NOUN
ajsts-5382	101	14	resnet	resnet	NOUN
ajsts-5382	101	15	model	model	NOUN
ajsts-5382	101	16	.	.	PUNCT
ajsts-5382	102	1	performance	performance	NOUN
ajsts-5382	102	2	:	:	PUNCT
ajsts-5382	102	3	the	the	DET
ajsts-5382	102	4	50	50	NUM
ajsts-5382	102	5	-	-	PUNCT
ajsts-5382	102	6	layer	layer	NOUN
ajsts-5382	102	7	resnet-50	resnet-50	PROPN
ajsts-5382	102	8	achieves	achieve	VERB
ajsts-5382	102	9	a	a	DET
ajsts-5382	102	10	performance	performance	NOUN
ajsts-5382	102	11	of	of	ADP
ajsts-5382	102	12	3.8	3.8	NUM
ajsts-5382	102	13	billion	billion	NUM
ajsts-5382	102	14	flops	flop	NOUN
ajsts-5382	102	15	.	.	PUNCT
ajsts-5382	103	1	resnet-101	resnet-101	NOUN
ajsts-5382	103	2	and	and	CCONJ
ajsts-5382	103	3	resnet-152	resnet-152	NOUN
ajsts-5382	103	4	architecture	architecture	NOUN
ajsts-5382	103	5	:	:	PUNCT
ajsts-5382	103	6	large	large	ADJ
ajsts-5382	103	7	residual	residual	ADJ
ajsts-5382	103	8	networks	network	NOUN
ajsts-5382	103	9	resnet-101	resnet-101	VERB
ajsts-5382	103	10	and	and	CCONJ
ajsts-5382	103	11	resnet-152	resnet-152	NOUN
ajsts-5382	103	12	are	be	AUX
ajsts-5382	103	13	constructed	construct	VERB
ajsts-5382	103	14	using	use	VERB
ajsts-5382	103	15	more	more	ADJ
ajsts-5382	103	16	pa	pa	PROPN
ajsts-5382	103	17	ge	ge	PROPN
ajsts-5382	103	18	60	60	NUM
ajsts-5382	103	19	https://journals.e-palli.com/home/index.php/ajsts	https://journals.e-palli.com/home/index.php/ajst	NOUN
ajsts-5382	103	20	am	be	AUX
ajsts-5382	103	21	.	.	PUNCT
ajsts-5382	104	1	j.	j.	PROPN
ajsts-5382	104	2	smart	smart	PROPN
ajsts-5382	104	3	.	.	PUNCT
ajsts-5382	105	1	technol	technol	PROPN
ajsts-5382	105	2	.	.	PUNCT
ajsts-5382	105	3	solutions	solution	NOUN
ajsts-5382	105	4	4(2	4(2	NUM
ajsts-5382	105	5	)	)	PUNCT
ajsts-5382	105	6	57	57	NUM
ajsts-5382	105	7	-	-	SYM
ajsts-5382	105	8	62	62	NUM
ajsts-5382	105	9	,	,	PUNCT
ajsts-5382	105	10	2025	2025	NUM
ajsts-5382	105	11	than	than	ADP
ajsts-5382	105	12	3	3	NUM
ajsts-5382	105	13	-	-	PUNCT
ajsts-5382	105	14	layer	layer	NOUN
ajsts-5382	105	15	blocks	block	NOUN
ajsts-5382	105	16	,	,	PUNCT
ajsts-5382	105	17	enabling	enable	VERB
ajsts-5382	105	18	deeper	deep	ADJ
ajsts-5382	105	19	networks	network	NOUN
ajsts-5382	105	20	with	with	ADP
ajsts-5382	105	21	lower	low	ADJ
ajsts-5382	105	22	complexity	complexity	NOUN
ajsts-5382	105	23	.	.	PUNCT
ajsts-5382	106	1	lower	low	ADJ
ajsts-5382	106	2	complexity	complexity	NOUN
ajsts-5382	106	3	:	:	PUNCT
ajsts-5382	106	4	despite	despite	SCONJ
ajsts-5382	106	5	increased	increase	VERB
ajsts-5382	106	6	network	network	NOUN
ajsts-5382	106	7	depth	depth	NOUN
ajsts-5382	106	8	,	,	PUNCT
ajsts-5382	106	9	the	the	DET
ajsts-5382	106	10	152	152	NUM
ajsts-5382	106	11	-	-	PUNCT
ajsts-5382	106	12	layer	layer	NOUN
ajsts-5382	106	13	resnet	resnet	NOUN
ajsts-5382	106	14	has	have	VERB
ajsts-5382	106	15	much	much	ADV
ajsts-5382	106	16	lower	low	ADJ
ajsts-5382	106	17	complexity	complexity	NOUN
ajsts-5382	106	18	(	(	PUNCT
ajsts-5382	106	19	11.3	11.3	NUM
ajsts-5382	106	20	billion	billion	NUM
ajsts-5382	106	21	flops	flop	NOUN
ajsts-5382	106	22	)	)	PUNCT
ajsts-5382	106	23	than	than	ADP
ajsts-5382	106	24	vgg-16	vgg-16	NOUN
ajsts-5382	106	25	or	or	CCONJ
ajsts-5382	106	26	vgg-19	vgg-19	NUM
ajsts-5382	106	27	nets	net	NOUN
ajsts-5382	106	28	(	(	PUNCT
ajsts-5382	106	29	15.3/19.6	15.3/19.6	NOUN
ajsts-5382	106	30	billion	billion	NUM
ajsts-5382	106	31	flops	flop	NOUN
ajsts-5382	106	32	)	)	PUNCT
ajsts-5382	106	33	.	.	PUNCT
ajsts-5382	107	1	resnet-50	resnet-50	PROPN
ajsts-5382	107	2	with	with	ADP
ajsts-5382	107	3	keras	keras	PROPN
ajsts-5382	107	4	:	:	PUNCT
ajsts-5382	108	1	keras	keras	PROPN
ajsts-5382	108	2	api	api	PROPN
ajsts-5382	108	3	keras	keras	PROPN
ajsts-5382	108	4	is	be	AUX
ajsts-5382	108	5	a	a	DET
ajsts-5382	108	6	popular	popular	ADJ
ajsts-5382	108	7	deep	deep	ADJ
ajsts-5382	108	8	learning	learning	NOUN
ajsts-5382	108	9	api	api	NOUN
ajsts-5382	108	10	known	know	VERB
ajsts-5382	108	11	for	for	ADP
ajsts-5382	108	12	its	its	PRON
ajsts-5382	108	13	simplicity	simplicity	NOUN
ajsts-5382	108	14	and	and	CCONJ
ajsts-5382	108	15	ease	ease	NOUN
ajsts-5382	108	16	of	of	ADP
ajsts-5382	108	17	use	use	NOUN
ajsts-5382	108	18	.	.	PUNCT
ajsts-5382	109	1	pre	pre	ADJ
ajsts-5382	109	2	-	-	ADJ
ajsts-5382	109	3	trained	train	VERB
ajsts-5382	109	4	models	model	NOUN
ajsts-5382	109	5	:	:	PUNCT
ajsts-5382	109	6	keras	keras	PROPN
ajsts-5382	109	7	comes	come	VERB
ajsts-5382	109	8	with	with	ADP
ajsts-5382	109	9	several	several	ADJ
ajsts-5382	109	10	pre	pre	ADJ
ajsts-5382	109	11	-	-	ADJ
ajsts-5382	109	12	trained	train	VERB
ajsts-5382	109	13	models	model	NOUN
ajsts-5382	109	14	,	,	PUNCT
ajsts-5382	109	15	including	include	VERB
ajsts-5382	109	16	resnet-50	resnet-50	PROPN
ajsts-5382	109	17	,	,	PUNCT
ajsts-5382	109	18	which	which	PRON
ajsts-5382	109	19	can	can	AUX
ajsts-5382	109	20	be	be	AUX
ajsts-5382	109	21	used	use	VERB
ajsts-5382	109	22	for	for	ADP
ajsts-5382	109	23	various	various	ADJ
ajsts-5382	109	24	experiments	experiment	NOUN
ajsts-5382	109	25	and	and	CCONJ
ajsts-5382	109	26	applications	application	NOUN
ajsts-5382	109	27	.	.	PUNCT
ajsts-5382	110	1	technical	technical	ADJ
ajsts-5382	110	2	approaches	approach	NOUN
ajsts-5382	110	3	for	for	ADP
ajsts-5382	110	4	validation	validation	NOUN
ajsts-5382	110	5	of	of	ADP
ajsts-5382	110	6	the	the	DET
ajsts-5382	110	7	soybean	soybean	NOUN
ajsts-5382	110	8	plant	plant	NOUN
ajsts-5382	110	9	and	and	CCONJ
ajsts-5382	110	10	the	the	DET
ajsts-5382	110	11	condition	condition	NOUN
ajsts-5382	110	12	of	of	ADP
ajsts-5382	110	13	its	its	PRON
ajsts-5382	110	14	roots	root	NOUN
ajsts-5382	110	15	the	the	DET
ajsts-5382	110	16	technology	technology	NOUN
ajsts-5382	110	17	of	of	ADP
ajsts-5382	110	18	computer	computer	NOUN
ajsts-5382	110	19	vision	vision	NOUN
ajsts-5382	110	20	and	and	CCONJ
ajsts-5382	110	21	the	the	DET
ajsts-5382	110	22	integration	integration	NOUN
ajsts-5382	110	23	of	of	ADP
ajsts-5382	110	24	the	the	DET
ajsts-5382	110	25	model	model	NOUN
ajsts-5382	110	26	of	of	ADP
ajsts-5382	110	27	resnet	resnet	NOUN
ajsts-5382	110	28	is	be	AUX
ajsts-5382	110	29	being	be	AUX
ajsts-5382	110	30	applied	apply	VERB
ajsts-5382	110	31	to	to	ADP
ajsts-5382	110	32	the	the	DET
ajsts-5382	110	33	farming	farming	NOUN
ajsts-5382	110	34	of	of	ADP
ajsts-5382	110	35	soybean	soybean	NOUN
ajsts-5382	110	36	crops	crop	NOUN
ajsts-5382	110	37	.	.	PUNCT
ajsts-5382	111	1	the	the	DET
ajsts-5382	111	2	adjustment	adjustment	NOUN
ajsts-5382	111	3	design	design	NOUN
ajsts-5382	111	4	for	for	ADP
ajsts-5382	111	5	the	the	DET
ajsts-5382	111	6	evaluation	evaluation	NOUN
ajsts-5382	111	7	supports	support	VERB
ajsts-5382	111	8	and	and	CCONJ
ajsts-5382	111	9	recognizes	recognize	VERB
ajsts-5382	111	10	the	the	DET
ajsts-5382	111	11	image	image	NOUN
ajsts-5382	111	12	data	data	NOUN
ajsts-5382	111	13	sets	set	NOUN
ajsts-5382	111	14	and	and	CCONJ
ajsts-5382	111	15	validates	validate	VERB
ajsts-5382	111	16	the	the	DET
ajsts-5382	111	17	progress	progress	NOUN
ajsts-5382	111	18	of	of	ADP
ajsts-5382	111	19	the	the	DET
ajsts-5382	111	20	soybean	soybean	NOUN
ajsts-5382	111	21	plants	plant	NOUN
ajsts-5382	111	22	.	.	PUNCT
ajsts-5382	112	1	recommended	recommend	VERB
ajsts-5382	112	2	the	the	DET
ajsts-5382	112	3	iot	iot	NOUN
ajsts-5382	112	4	and	and	CCONJ
ajsts-5382	112	5	resnet	resnet	NOUN
ajsts-5382	112	6	model	model	NOUN
ajsts-5382	112	7	based	base	VERB
ajsts-5382	112	8	on	on	ADP
ajsts-5382	112	9	a	a	DET
ajsts-5382	112	10	computer	computer	NOUN
ajsts-5382	112	11	vision	vision	NOUN
ajsts-5382	112	12	system	system	NOUN
ajsts-5382	112	13	is	be	AUX
ajsts-5382	112	14	as	as	ADP
ajsts-5382	112	15	below	below	ADP
ajsts-5382	112	16	block	block	NOUN
ajsts-5382	112	17	diagram	diagram	NOUN
ajsts-5382	112	18	,	,	PUNCT
ajsts-5382	112	19	where	where	SCONJ
ajsts-5382	112	20	the	the	DET
ajsts-5382	112	21	camera	camera	NOUN
ajsts-5382	112	22	is	be	AUX
ajsts-5382	112	23	built	build	VERB
ajsts-5382	112	24	for	for	ADP
ajsts-5382	112	25	extracting	extract	VERB
ajsts-5382	112	26	the	the	DET
ajsts-5382	112	27	images	image	NOUN
ajsts-5382	112	28	,	,	PUNCT
ajsts-5382	112	29	and	and	CCONJ
ajsts-5382	112	30	after	after	SCONJ
ajsts-5382	112	31	those	those	DET
ajsts-5382	112	32	images	image	NOUN
ajsts-5382	112	33	are	be	AUX
ajsts-5382	112	34	forwarded	forward	VERB
ajsts-5382	112	35	to	to	ADP
ajsts-5382	112	36	the	the	DET
ajsts-5382	112	37	memory	memory	NOUN
ajsts-5382	112	38	shuttle	shuttle	NOUN
ajsts-5382	112	39	of	of	ADP
ajsts-5382	112	40	memory	memory	NOUN
ajsts-5382	112	41	,	,	PUNCT
ajsts-5382	112	42	which	which	PRON
ajsts-5382	112	43	is	be	AUX
ajsts-5382	112	44	built	build	VERB
ajsts-5382	112	45	into	into	ADP
ajsts-5382	112	46	the	the	DET
ajsts-5382	112	47	circuit	circuit	NOUN
ajsts-5382	112	48	of	of	ADP
ajsts-5382	112	49	iot	iot	PROPN
ajsts-5382	112	50	devices	device	NOUN
ajsts-5382	112	51	.	.	PUNCT
ajsts-5382	113	1	the	the	DET
ajsts-5382	113	2	memory	memory	NOUN
ajsts-5382	113	3	transferring	transfer	VERB
ajsts-5382	113	4	the	the	DET
ajsts-5382	113	5	images	image	NOUN
ajsts-5382	113	6	to	to	ADP
ajsts-5382	113	7	the	the	DET
ajsts-5382	113	8	computer	computer	NOUN
ajsts-5382	113	9	system	system	NOUN
ajsts-5382	113	10	,	,	PUNCT
ajsts-5382	113	11	where	where	SCONJ
ajsts-5382	113	12	an	an	DET
ajsts-5382	113	13	algorithm	algorithm	NOUN
ajsts-5382	113	14	extracts	extract	VERB
ajsts-5382	113	15	the	the	DET
ajsts-5382	113	16	image	image	NOUN
ajsts-5382	113	17	-	-	PUNCT
ajsts-5382	113	18	based	base	VERB
ajsts-5382	113	19	data	datum	NOUN
ajsts-5382	113	20	of	of	ADP
ajsts-5382	113	21	the	the	DET
ajsts-5382	113	22	sets	set	NOUN
ajsts-5382	113	23	that	that	PRON
ajsts-5382	113	24	are	be	AUX
ajsts-5382	113	25	recognized	recognize	VERB
ajsts-5382	113	26	for	for	ADP
ajsts-5382	113	27	the	the	DET
ajsts-5382	113	28	image	image	NOUN
ajsts-5382	113	29	segmentation	segmentation	NOUN
ajsts-5382	113	30	.	.	PUNCT
ajsts-5382	114	1	the	the	DET
ajsts-5382	114	2	block	block	NOUN
ajsts-5382	114	3	diagram	diagram	NOUN
ajsts-5382	114	4	shows	show	VERB
ajsts-5382	114	5	the	the	DET
ajsts-5382	114	6	stepwise	stepwise	PROPN
ajsts-5382	114	7	uses	use	NOUN
ajsts-5382	114	8	of	of	ADP
ajsts-5382	114	9	the	the	DET
ajsts-5382	114	10	iot	iot	PROPN
ajsts-5382	114	11	model	model	NOUN
ajsts-5382	114	12	and	and	CCONJ
ajsts-5382	114	13	the	the	DET
ajsts-5382	114	14	process	process	NOUN
ajsts-5382	114	15	of	of	ADP
ajsts-5382	114	16	input	input	NOUN
ajsts-5382	114	17	values	value	NOUN
ajsts-5382	114	18	.	.	PUNCT
ajsts-5382	115	1	the	the	DET
ajsts-5382	115	2	block	block	NOUN
ajsts-5382	115	3	diagram	diagram	NOUN
ajsts-5382	115	4	also	also	ADV
ajsts-5382	115	5	integrates	integrate	VERB
ajsts-5382	115	6	the	the	DET
ajsts-5382	115	7	steps	step	NOUN
ajsts-5382	115	8	of	of	ADP
ajsts-5382	115	9	preprocessing	preprocesse	VERB
ajsts-5382	115	10	with	with	ADP
ajsts-5382	115	11	the	the	DET
ajsts-5382	115	12	help	help	NOUN
ajsts-5382	115	13	of	of	ADP
ajsts-5382	115	14	modules	module	NOUN
ajsts-5382	115	15	of	of	ADP
ajsts-5382	115	16	resnn	resnn	X
ajsts-5382	115	17	(	(	PUNCT
ajsts-5382	115	18	simonyan	simonyan	ADJ
ajsts-5382	115	19	&	&	CCONJ
ajsts-5382	115	20	zisserman	zisserman	PROPN
ajsts-5382	115	21	,	,	PUNCT
ajsts-5382	115	22	2014	2014	NUM
ajsts-5382	115	23	;	;	PUNCT
ajsts-5382	115	24	szegedy	szegedy	VERB
ajsts-5382	115	25	et	et	PROPN
ajsts-5382	115	26	al	al	PROPN
ajsts-5382	115	27	.	.	PROPN
ajsts-5382	115	28	,	,	PUNCT
ajsts-5382	115	29	2015	2015	NUM
ajsts-5382	115	30	)	)	PUNCT
ajsts-5382	115	31	.	.	PUNCT
ajsts-5382	116	1	figure	figure	VERB
ajsts-5382	116	2	2	2	NUM
ajsts-5382	116	3	:	:	PUNCT
ajsts-5382	116	4	model	model	NOUN
ajsts-5382	116	5	-	-	PUNCT
ajsts-5382	116	6	based	base	VERB
ajsts-5382	116	7	to	to	PART
ajsts-5382	116	8	define	define	VERB
ajsts-5382	116	9	the	the	DET
ajsts-5382	116	10	iot	iot	NOUN
ajsts-5382	116	11	and	and	CCONJ
ajsts-5382	116	12	resnn	resnn	NOUN
ajsts-5382	116	13	for	for	ADP
ajsts-5382	116	14	validating	validate	VERB
ajsts-5382	116	15	data	datum	NOUN
ajsts-5382	116	16	set	set	VERB
ajsts-5382	116	17	result	result	NOUN
ajsts-5382	116	18	and	and	CCONJ
ajsts-5382	116	19	discussion	discussion	NOUN
ajsts-5382	116	20	evaluation	evaluation	NOUN
ajsts-5382	116	21	and	and	CCONJ
ajsts-5382	116	22	analysis	analysis	NOUN
ajsts-5382	116	23	of	of	ADP
ajsts-5382	116	24	soybean	soybean	NOUN
ajsts-5382	116	25	roots	root	NOUN
ajsts-5382	116	26	using	use	VERB
ajsts-5382	116	27	resnn	resnn	NOUN
ajsts-5382	116	28	technology	technology	NOUN
ajsts-5382	116	29	renn	renn	NOUN
ajsts-5382	116	30	architecture	architecture	NOUN
ajsts-5382	116	31	consists	consist	VERB
ajsts-5382	116	32	of	of	ADP
ajsts-5382	116	33	residual	residual	ADJ
ajsts-5382	116	34	block	block	NOUN
ajsts-5382	116	35	residual	residual	ADJ
ajsts-5382	116	36	blocks	block	NOUN
ajsts-5382	116	37	are	be	AUX
ajsts-5382	116	38	the	the	DET
ajsts-5382	116	39	main	main	ADJ
ajsts-5382	116	40	components	component	NOUN
ajsts-5382	116	41	of	of	ADP
ajsts-5382	116	42	the	the	DET
ajsts-5382	116	43	residual	residual	ADJ
ajsts-5382	116	44	neural	neural	ADJ
ajsts-5382	116	45	network	network	NOUN
ajsts-5382	116	46	.	.	PUNCT
ajsts-5382	117	1	in	in	ADP
ajsts-5382	117	2	a	a	DET
ajsts-5382	117	3	classical	classical	ADJ
ajsts-5382	117	4	neural	neural	ADJ
ajsts-5382	117	5	network	network	NOUN
ajsts-5382	117	6	,	,	PUNCT
ajsts-5382	117	7	the	the	DET
ajsts-5382	117	8	input	input	NOUN
ajsts-5382	117	9	is	be	AUX
ajsts-5382	117	10	transformed	transform	VERB
ajsts-5382	117	11	by	by	ADP
ajsts-5382	117	12	a	a	DET
ajsts-5382	117	13	set	set	NOUN
ajsts-5382	117	14	of	of	ADP
ajsts-5382	117	15	convolutional	convolutional	ADJ
ajsts-5382	117	16	layers	layer	NOUN
ajsts-5382	117	17	then	then	ADV
ajsts-5382	117	18	it	it	PRON
ajsts-5382	117	19	is	be	AUX
ajsts-5382	117	20	passed	pass	VERB
ajsts-5382	117	21	to	to	ADP
ajsts-5382	117	22	the	the	DET
ajsts-5382	117	23	activation	activation	NOUN
ajsts-5382	117	24	function	function	NOUN
ajsts-5382	117	25	.	.	PUNCT
ajsts-5382	118	1	in	in	ADP
ajsts-5382	118	2	a	a	DET
ajsts-5382	118	3	residual	residual	ADJ
ajsts-5382	118	4	network	network	NOUN
ajsts-5382	118	5	,	,	PUNCT
ajsts-5382	118	6	the	the	DET
ajsts-5382	118	7	input	input	NOUN
ajsts-5382	118	8	to	to	ADP
ajsts-5382	118	9	the	the	DET
ajsts-5382	118	10	block	block	NOUN
ajsts-5382	118	11	is	be	AUX
ajsts-5382	118	12	added	add	VERB
ajsts-5382	118	13	to	to	ADP
ajsts-5382	118	14	the	the	DET
ajsts-5382	118	15	output	output	NOUN
ajsts-5382	118	16	of	of	ADP
ajsts-5382	118	17	the	the	DET
ajsts-5382	118	18	block	block	NOUN
ajsts-5382	118	19	,	,	PUNCT
ajsts-5382	118	20	creating	create	VERB
ajsts-5382	118	21	a	a	DET
ajsts-5382	118	22	residual	residual	ADJ
ajsts-5382	118	23	connection	connection	NOUN
ajsts-5382	118	24	.	.	PUNCT
ajsts-5382	119	1	the	the	DET
ajsts-5382	119	2	output	output	NOUN
ajsts-5382	119	3	of	of	ADP
ajsts-5382	119	4	the	the	DET
ajsts-5382	119	5	residual	residual	ADJ
ajsts-5382	119	6	block	block	NOUN
ajsts-5382	119	7	h(xi	h(xi	NOUN
ajsts-5382	119	8	)	)	PUNCT
ajsts-5382	119	9	can	can	AUX
ajsts-5382	119	10	be	be	AUX
ajsts-5382	119	11	represented	represent	VERB
ajsts-5382	119	12	by	by	ADP
ajsts-5382	119	13	:	:	PUNCT
ajsts-5382	119	14	h(xi	h(xi	NUM
ajsts-5382	119	15	)	)	PUNCT
ajsts-5382	119	16	=	=	SYM
ajsts-5382	119	17	f(xi	f(xi	PROPN
ajsts-5382	119	18	)	)	PUNCT
ajsts-5382	120	1	+	+	CCONJ
ajsts-5382	120	2	xi	xi	PART
ajsts-5382	120	3	f(xi	f(xi	PROPN
ajsts-5382	120	4	)	)	PUNCT
ajsts-5382	120	5	represents	represent	VERB
ajsts-5382	120	6	the	the	DET
ajsts-5382	120	7	residual	residual	ADJ
ajsts-5382	120	8	mapping	mapping	NOUN
ajsts-5382	120	9	learned	learn	VERB
ajsts-5382	120	10	by	by	ADP
ajsts-5382	120	11	the	the	DET
ajsts-5382	120	12	network	network	NOUN
ajsts-5382	120	13	.	.	PUNCT
ajsts-5382	121	1	the	the	DET
ajsts-5382	121	2	presence	presence	NOUN
ajsts-5382	121	3	of	of	ADP
ajsts-5382	121	4	the	the	DET
ajsts-5382	121	5	identity	identity	NOUN
ajsts-5382	121	6	term	term	NOUN
ajsts-5382	121	7	x	x	PUNCT
ajsts-5382	121	8	allows	allow	VERB
ajsts-5382	121	9	the	the	DET
ajsts-5382	121	10	gradient	gradient	NOUN
ajsts-5382	121	11	to	to	PART
ajsts-5382	121	12	flow	flow	VERB
ajsts-5382	121	13	more	more	ADV
ajsts-5382	121	14	easily	easily	ADV
ajsts-5382	121	15	.	.	PUNCT
ajsts-5382	122	1	s	s	VERB
ajsts-5382	122	2	connection	connection	NOUN
ajsts-5382	122	3	s	s	PART
ajsts-5382	122	4	connection	connection	NOUN
ajsts-5382	122	5	is	be	AUX
ajsts-5382	122	6	a	a	DET
ajsts-5382	122	7	skip	skip	ADJ
ajsts-5382	122	8	connection	connection	NOUN
ajsts-5382	122	9	that	that	PRON
ajsts-5382	122	10	helps	help	VERB
ajsts-5382	122	11	in	in	ADP
ajsts-5382	122	12	forming	form	VERB
ajsts-5382	122	13	the	the	DET
ajsts-5382	122	14	residual	residual	ADJ
ajsts-5382	122	15	blocks	block	NOUN
ajsts-5382	122	16	.	.	PUNCT
ajsts-5382	123	1	skip	skip	ADJ
ajsts-5382	123	2	connection	connection	NOUN
ajsts-5382	123	3	consists	consist	VERB
ajsts-5382	123	4	of	of	ADP
ajsts-5382	123	5	the	the	DET
ajsts-5382	123	6	input	input	NOUN
ajsts-5382	123	7	of	of	ADP
ajsts-5382	123	8	the	the	DET
ajsts-5382	123	9	residual	residual	ADJ
ajsts-5382	123	10	block	block	NOUN
ajsts-5382	123	11	that	that	PRON
ajsts-5382	123	12	is	be	AUX
ajsts-5382	123	13	bypassed	bypass	VERB
ajsts-5382	123	14	over	over	ADP
ajsts-5382	123	15	the	the	DET
ajsts-5382	123	16	convolutional	convolutional	ADJ
ajsts-5382	123	17	layer	layer	NOUN
ajsts-5382	123	18	and	and	CCONJ
ajsts-5382	123	19	added	add	VERB
ajsts-5382	123	20	to	to	ADP
ajsts-5382	123	21	the	the	DET
ajsts-5382	123	22	output	output	NOUN
ajsts-5382	123	23	of	of	ADP
ajsts-5382	123	24	the	the	DET
ajsts-5382	123	25	residual	residual	ADJ
ajsts-5382	123	26	block	block	NOUN
ajsts-5382	123	27	.	.	PUNCT
ajsts-5382	124	1	st	st	PROPN
ajsts-5382	124	2	layers	layers	PROPN
ajsts-5382	124	3	resnet	resnet	PROPN
ajsts-5382	124	4	architectures	architecture	NOUN
ajsts-5382	124	5	are	be	AUX
ajsts-5382	124	6	formed	form	VERB
ajsts-5382	124	7	by	by	ADP
ajsts-5382	124	8	stacking	stack	VERB
ajsts-5382	124	9	multiple	multiple	ADJ
ajsts-5382	124	10	residual	residual	ADJ
ajsts-5382	124	11	blocks	block	NOUN
ajsts-5382	124	12	together	together	ADV
ajsts-5382	124	13	.	.	PUNCT
ajsts-5382	125	1	using	use	VERB
ajsts-5382	125	2	these	these	DET
ajsts-5382	125	3	multiple	multiple	ADJ
ajsts-5382	125	4	residual	residual	ADJ
ajsts-5382	125	5	blocks	block	NOUN
ajsts-5382	125	6	together	together	ADV
ajsts-5382	125	7	,	,	PUNCT
ajsts-5382	125	8	resnet	resnet	NOUN
ajsts-5382	125	9	architecture	architecture	NOUN
ajsts-5382	125	10	can	can	AUX
ajsts-5382	125	11	be	be	AUX
ajsts-5382	125	12	built	build	VERB
ajsts-5382	125	13	very	very	ADV
ajsts-5382	125	14	deep	deep	ADJ
ajsts-5382	125	15	.	.	PUNCT
ajsts-5382	126	1	versions	version	NOUN
ajsts-5382	126	2	of	of	ADP
ajsts-5382	126	3	resnet	resnet	NOUN
ajsts-5382	126	4	with	with	ADP
ajsts-5382	126	5	50,101,152	50,101,152	NUM
ajsts-5382	126	6	layers	layer	NOUN
ajsts-5382	126	7	were	be	AUX
ajsts-5382	126	8	introduced	introduce	VERB
ajsts-5382	126	9	.	.	PUNCT
ajsts-5382	127	1	global	global	ADJ
ajsts-5382	127	2	average	average	ADJ
ajsts-5382	127	3	pooling(gap	pooling(gap	NOUN
ajsts-5382	127	4	)	)	PUNCT
ajsts-5382	127	5	resnet	resnet	NOUN
ajsts-5382	127	6	architectures	architecture	NOUN
ajsts-5382	127	7	typically	typically	ADV
ajsts-5382	127	8	utilize	utilize	VERB
ajsts-5382	127	9	global	global	ADJ
ajsts-5382	127	10	average	average	ADJ
ajsts-5382	127	11	pooling	pooling	NOUN
ajsts-5382	127	12	as	as	ADP
ajsts-5382	127	13	the	the	DET
ajsts-5382	127	14	final	final	ADJ
ajsts-5382	127	15	layer	layer	NOUN
ajsts-5382	127	16	before	before	ADP
ajsts-5382	127	17	the	the	DET
ajsts-5382	127	18	fully	fully	ADV
ajsts-5382	127	19	connected	connected	ADJ
ajsts-5382	127	20	layer	layer	NOUN
ajsts-5382	127	21	.	.	PUNCT
ajsts-5382	128	1	gap	gap	NOUN
ajsts-5382	128	2	reduces	reduce	VERB
ajsts-5382	128	3	spatial	spatial	ADJ
ajsts-5382	128	4	dimensions	dimension	NOUN
ajsts-5382	128	5	to	to	ADP
ajsts-5382	128	6	a	a	DET
ajsts-5382	128	7	single	single	ADJ
ajsts-5382	128	8	value	value	NOUN
ajsts-5382	128	9	per	per	ADP
ajsts-5382	128	10	feature	feature	NOUN
ajsts-5382	128	11	map	map	NOUN
ajsts-5382	128	12	,	,	PUNCT
ajsts-5382	128	13	providing	provide	VERB
ajsts-5382	128	14	a	a	DET
ajsts-5382	128	15	compact	compact	ADJ
ajsts-5382	128	16	representation	representation	NOUN
ajsts-5382	128	17	of	of	ADP
ajsts-5382	128	18	the	the	DET
ajsts-5382	128	19	entire	entire	ADJ
ajsts-5382	128	20	feature	feature	NOUN
ajsts-5382	128	21	map	map	NOUN
ajsts-5382	128	22	(	(	PUNCT
ajsts-5382	128	23	zhang	zhang	X
ajsts-5382	128	24	et	et	PROPN
ajsts-5382	128	25	al	al	PROPN
ajsts-5382	128	26	.	.	PROPN
ajsts-5382	128	27	,	,	PUNCT
ajsts-5382	128	28	2019	2019	NUM
ajsts-5382	128	29	)	)	PUNCT
ajsts-5382	128	30	.	.	PUNCT
ajsts-5382	129	1	healthy	healthy	ADJ
ajsts-5382	129	2	soybean	soybean	NOUN
ajsts-5382	129	3	roots	root	NOUN
ajsts-5382	129	4	have	have	VERB
ajsts-5382	129	5	the	the	DET
ajsts-5382	129	6	following	follow	VERB
ajsts-5382	129	7	characteristics	characteristic	NOUN
ajsts-5382	129	8	(	(	PUNCT
ajsts-5382	129	9	chen	chen	PROPN
ajsts-5382	129	10	et	et	PROPN
ajsts-5382	129	11	al	al	PROPN
ajsts-5382	129	12	.	.	PROPN
ajsts-5382	129	13	,	,	PUNCT
ajsts-5382	129	14	2020	2020	NUM
ajsts-5382	129	15	)	)	PUNCT
ajsts-5382	129	16	•	•	NUM
ajsts-5382	129	17	depth	depth	NOUN
ajsts-5382	129	18	:	:	PUNCT
ajsts-5382	129	19	soybean	soybean	NOUN
ajsts-5382	129	20	roots	root	NOUN
ajsts-5382	129	21	typically	typically	ADV
ajsts-5382	129	22	grow	grow	VERB
ajsts-5382	129	23	to	to	ADP
ajsts-5382	129	24	a	a	DET
ajsts-5382	129	25	depth	depth	NOUN
ajsts-5382	129	26	of	of	ADP
ajsts-5382	129	27	2–3	2–3	NUM
ajsts-5382	129	28	feet	foot	NOUN
ajsts-5382	129	29	,	,	PUNCT
ajsts-5382	129	30	but	but	CCONJ
ajsts-5382	129	31	most	most	ADJ
ajsts-5382	129	32	of	of	ADP
ajsts-5382	129	33	the	the	DET
ajsts-5382	129	34	roots	root	NOUN
ajsts-5382	129	35	are	be	AUX
ajsts-5382	129	36	in	in	ADP
ajsts-5382	129	37	the	the	DET
ajsts-5382	129	38	top	top	ADJ
ajsts-5382	129	39	6–12	6–12	NOUN
ajsts-5382	129	40	inches	inch	NOUN
ajsts-5382	129	41	of	of	ADP
ajsts-5382	129	42	soil	soil	NOUN
ajsts-5382	129	43	.	.	PUNCT
ajsts-5382	130	1	•	•	NOUN
ajsts-5382	130	2	nodules	nodule	NOUN
ajsts-5382	130	3	:	:	PUNCT
ajsts-5382	130	4	a	a	DET
ajsts-5382	130	5	healthy	healthy	ADJ
ajsts-5382	130	6	soybean	soybean	NOUN
ajsts-5382	130	7	plant	plant	NOUN
ajsts-5382	130	8	should	should	AUX
ajsts-5382	130	9	have	have	AUX
ajsts-5382	130	10	6–20	6–20	VERB
ajsts-5382	130	11	large	large	ADJ
ajsts-5382	130	12	nodules	nodule	NOUN
ajsts-5382	130	13	on	on	ADP
ajsts-5382	130	14	the	the	DET
ajsts-5382	130	15	main	main	ADJ
ajsts-5382	130	16	tap	tap	NOUN
ajsts-5382	130	17	root	root	NOUN
ajsts-5382	130	18	and	and	CCONJ
ajsts-5382	130	19	smaller	small	ADJ
ajsts-5382	130	20	nodules	nodule	NOUN
ajsts-5382	130	21	on	on	ADP
ajsts-5382	130	22	the	the	DET
ajsts-5382	130	23	auxiliary	auxiliary	ADJ
ajsts-5382	130	24	roots	root	NOUN
ajsts-5382	130	25	.	.	PUNCT
ajsts-5382	131	1	nodules	nodule	NOUN
ajsts-5382	131	2	are	be	AUX
ajsts-5382	131	3	formed	form	VERB
ajsts-5382	131	4	by	by	ADP
ajsts-5382	131	5	bacteria	bacteria	NOUN
ajsts-5382	131	6	in	in	ADP
ajsts-5382	131	7	the	the	DET
ajsts-5382	131	8	soil	soil	NOUN
ajsts-5382	131	9	and	and	CCONJ
ajsts-5382	131	10	provide	provide	VERB
ajsts-5382	131	11	much	much	ADJ
ajsts-5382	131	12	of	of	ADP
ajsts-5382	131	13	the	the	DET
ajsts-5382	131	14	plant	plant	NOUN
ajsts-5382	131	15	’s	’s	PART
ajsts-5382	131	16	nitrogen	nitrogen	NOUN
ajsts-5382	131	17	supply	supply	NOUN
ajsts-5382	131	18	.	.	PUNCT
ajsts-5382	132	1	pa	pa	PROPN
ajsts-5382	132	2	ge	ge	PROPN
ajsts-5382	132	3	61	61	NUM
ajsts-5382	132	4	https://journals.e-palli.com/home/index.php/ajsts	https://journals.e-palli.com/home/index.php/ajst	NOUN
ajsts-5382	132	5	am	be	AUX
ajsts-5382	132	6	.	.	PUNCT
ajsts-5382	133	1	j.	j.	PROPN
ajsts-5382	133	2	smart	smart	PROPN
ajsts-5382	133	3	.	.	PUNCT
ajsts-5382	134	1	technol	technol	PROPN
ajsts-5382	134	2	.	.	PUNCT
ajsts-5382	134	3	solutions	solution	NOUN
ajsts-5382	134	4	4(2	4(2	NUM
ajsts-5382	134	5	)	)	PUNCT
ajsts-5382	134	6	57	57	NUM
ajsts-5382	134	7	-	-	SYM
ajsts-5382	134	8	62	62	NUM
ajsts-5382	134	9	,	,	PUNCT
ajsts-5382	134	10	2025	2025	NUM
ajsts-5382	134	11	•	•	NUM
ajsts-5382	134	12	colour	colour	NOUN
ajsts-5382	134	13	:	:	PUNCT
ajsts-5382	134	14	a	a	DET
ajsts-5382	134	15	healthy	healthy	ADJ
ajsts-5382	134	16	nodule	nodule	NOUN
ajsts-5382	134	17	is	be	AUX
ajsts-5382	134	18	red	red	ADJ
ajsts-5382	134	19	or	or	CCONJ
ajsts-5382	134	20	pink	pink	ADJ
ajsts-5382	134	21	,	,	PUNCT
ajsts-5382	134	22	which	which	PRON
ajsts-5382	134	23	indicates	indicate	VERB
ajsts-5382	134	24	active	active	ADJ
ajsts-5382	134	25	nitrogen	nitrogen	NOUN
ajsts-5382	134	26	fixation	fixation	NOUN
ajsts-5382	134	27	.	.	PUNCT
ajsts-5382	135	1	a	a	DET
ajsts-5382	135	2	white	white	ADJ
ajsts-5382	135	3	or	or	CCONJ
ajsts-5382	135	4	gray	gray	ADJ
ajsts-5382	135	5	nodule	nodule	NOUN
ajsts-5382	135	6	is	be	AUX
ajsts-5382	135	7	immature	immature	ADJ
ajsts-5382	135	8	and	and	CCONJ
ajsts-5382	135	9	should	should	AUX
ajsts-5382	135	10	be	be	AUX
ajsts-5382	135	11	checked	check	VERB
ajsts-5382	135	12	again	again	ADV
ajsts-5382	135	13	in	in	ADP
ajsts-5382	135	14	a	a	DET
ajsts-5382	135	15	week	week	NOUN
ajsts-5382	135	16	.	.	PUNCT
ajsts-5382	136	1	a	a	DET
ajsts-5382	136	2	green	green	ADJ
ajsts-5382	136	3	,	,	PUNCT
ajsts-5382	136	4	brown	brown	ADJ
ajsts-5382	136	5	,	,	PUNCT
ajsts-5382	136	6	or	or	CCONJ
ajsts-5382	136	7	mushy	mushy	ADJ
ajsts-5382	136	8	nodule	nodule	NOUN
ajsts-5382	136	9	is	be	AUX
ajsts-5382	136	10	dead	dead	ADJ
ajsts-5382	136	11	.	.	PUNCT
ajsts-5382	137	1	•	•	NUM
ajsts-5382	137	2	root	root	NOUN
ajsts-5382	137	3	type	type	NOUN
ajsts-5382	137	4	:	:	PUNCT
ajsts-5382	137	5	soybeans	soybean	NOUN
ajsts-5382	137	6	have	have	AUX
ajsts-5382	137	7	both	both	CCONJ
ajsts-5382	137	8	deep	deep	ADJ
ajsts-5382	137	9	,	,	PUNCT
ajsts-5382	137	10	vertical	vertical	ADJ
ajsts-5382	137	11	roots	root	NOUN
ajsts-5382	137	12	and	and	CCONJ
ajsts-5382	137	13	shallow	shallow	ADJ
ajsts-5382	137	14	,	,	PUNCT
ajsts-5382	137	15	lateral	lateral	ADJ
ajsts-5382	137	16	roots	root	NOUN
ajsts-5382	137	17	.	.	PUNCT
ajsts-5382	138	1	the	the	DET
ajsts-5382	138	2	deep	deep	ADJ
ajsts-5382	138	3	roots	root	NOUN
ajsts-5382	138	4	access	access	NOUN
ajsts-5382	138	5	water	water	NOUN
ajsts-5382	138	6	from	from	ADP
ajsts-5382	138	7	deeper	deep	ADJ
ajsts-5382	138	8	soil	soil	NOUN
ajsts-5382	138	9	layers	layer	NOUN
ajsts-5382	138	10	,	,	PUNCT
ajsts-5382	138	11	while	while	SCONJ
ajsts-5382	138	12	the	the	DET
ajsts-5382	138	13	shallow	shallow	ADJ
ajsts-5382	138	14	roots	root	NOUN
ajsts-5382	138	15	increase	increase	VERB
ajsts-5382	138	16	the	the	DET
ajsts-5382	138	17	plant	plant	NOUN
ajsts-5382	138	18	’s	’s	PART
ajsts-5382	138	19	ability	ability	NOUN
ajsts-5382	138	20	to	to	PART
ajsts-5382	138	21	absorb	absorb	VERB
ajsts-5382	138	22	nutrients	nutrient	NOUN
ajsts-5382	138	23	from	from	ADP
ajsts-5382	138	24	the	the	DET
ajsts-5382	138	25	topsoil	topsoil	NOUN
ajsts-5382	138	26	.	.	PUNCT
ajsts-5382	139	1	figure	figure	VERB
ajsts-5382	139	2	3	3	NUM
ajsts-5382	139	3	:	:	PUNCT
ajsts-5382	139	4	images	image	NOUN
ajsts-5382	139	5	of	of	ADP
ajsts-5382	139	6	standardized	standardized	ADJ
ajsts-5382	139	7	formation	formation	NOUN
ajsts-5382	139	8	of	of	ADP
ajsts-5382	139	9	soybean	soybean	NOUN
ajsts-5382	139	10	plant	plant	NOUN
ajsts-5382	139	11	y	y	PROPN
ajsts-5382	139	12	(	(	PUNCT
ajsts-5382	139	13	output	output	PROPN
ajsts-5382	139	14	)	)	PUNCT
ajsts-5382	139	15	=	=	SYM
ajsts-5382	140	1	x+f(x	x+f(x	X
ajsts-5382	140	2	)	)	PUNCT
ajsts-5382	140	3	renn	renn	PROPN
ajsts-5382	140	4	model	model	PROPN
ajsts-5382	140	5	for	for	ADP
ajsts-5382	140	6	evaluation	evaluation	NOUN
ajsts-5382	140	7	and	and	CCONJ
ajsts-5382	140	8	image	image	NOUN
ajsts-5382	140	9	-	-	PUNCT
ajsts-5382	140	10	based	base	VERB
ajsts-5382	140	11	analysis	analysis	NOUN
ajsts-5382	140	12	the	the	DET
ajsts-5382	140	13	effective	effective	ADJ
ajsts-5382	140	14	and	and	CCONJ
ajsts-5382	140	15	productive	productive	ADJ
ajsts-5382	140	16	extraction	extraction	NOUN
ajsts-5382	140	17	of	of	ADP
ajsts-5382	140	18	the	the	DET
ajsts-5382	140	19	root	root	NOUN
ajsts-5382	140	20	image	image	NOUN
ajsts-5382	140	21	,	,	PUNCT
ajsts-5382	140	22	so	so	CCONJ
ajsts-5382	140	23	the	the	DET
ajsts-5382	140	24	progress	progress	NOUN
ajsts-5382	140	25	and	and	CCONJ
ajsts-5382	140	26	evaluation	evaluation	NOUN
ajsts-5382	140	27	of	of	ADP
ajsts-5382	140	28	the	the	DET
ajsts-5382	140	29	roots	root	NOUN
ajsts-5382	140	30	help	help	VERB
ajsts-5382	140	31	and	and	CCONJ
ajsts-5382	140	32	are	be	AUX
ajsts-5382	140	33	more	more	ADV
ajsts-5382	140	34	supportive	supportive	ADJ
ajsts-5382	140	35	of	of	ADP
ajsts-5382	140	36	the	the	DET
ajsts-5382	140	37	progress	progress	NOUN
ajsts-5382	140	38	of	of	ADP
ajsts-5382	140	39	the	the	DET
ajsts-5382	140	40	plant	plant	NOUN
ajsts-5382	140	41	.	.	PUNCT
ajsts-5382	141	1	that	that	DET
ajsts-5382	141	2	plant	plant	NOUN
ajsts-5382	141	3	’s	’s	PART
ajsts-5382	141	4	progress	progress	NOUN
ajsts-5382	141	5	directly	directly	ADV
ajsts-5382	141	6	raises	raise	VERB
ajsts-5382	141	7	the	the	DET
ajsts-5382	141	8	production	production	NOUN
ajsts-5382	141	9	of	of	ADP
ajsts-5382	141	10	the	the	DET
ajsts-5382	141	11	soybean	soybean	NOUN
ajsts-5382	141	12	.	.	PUNCT
ajsts-5382	142	1	here	here	ADV
ajsts-5382	142	2	are	be	AUX
ajsts-5382	142	3	illustrated	illustrate	VERB
ajsts-5382	142	4	the	the	DET
ajsts-5382	142	5	key	key	ADJ
ajsts-5382	142	6	facts	fact	NOUN
ajsts-5382	142	7	for	for	ADP
ajsts-5382	142	8	resnn	resnn	NOUN
ajsts-5382	142	9	,	,	PUNCT
ajsts-5382	142	10	which	which	PRON
ajsts-5382	142	11	is	be	AUX
ajsts-5382	142	12	supportive	supportive	ADJ
ajsts-5382	142	13	of	of	ADP
ajsts-5382	142	14	the	the	DET
ajsts-5382	142	15	evaluation	evaluation	NOUN
ajsts-5382	142	16	of	of	ADP
ajsts-5382	142	17	the	the	DET
ajsts-5382	142	18	soybean	soybean	NOUN
ajsts-5382	142	19	plants	plant	NOUN
ajsts-5382	142	20	in	in	ADP
ajsts-5382	142	21	the	the	DET
ajsts-5382	142	22	future	future	ADJ
ajsts-5382	142	23	study	study	NOUN
ajsts-5382	142	24	and	and	CCONJ
ajsts-5382	142	25	project	project	NOUN
ajsts-5382	142	26	of	of	ADP
ajsts-5382	142	27	iot	iot	ADJ
ajsts-5382	142	28	deployments	deployment	NOUN
ajsts-5382	142	29	.	.	PUNCT
ajsts-5382	143	1	•	•	NUM
ajsts-5382	143	2	resnets	resnet	NOUN
ajsts-5382	143	3	(	(	PUNCT
ajsts-5382	143	4	residual	residual	ADJ
ajsts-5382	143	5	networks	network	NOUN
ajsts-5382	143	6	)	)	PUNCT
ajsts-5382	143	7	are	be	AUX
ajsts-5382	143	8	a	a	DET
ajsts-5382	143	9	variant	variant	NOUN
ajsts-5382	143	10	of	of	ADP
ajsts-5382	143	11	deep	deep	ADJ
ajsts-5382	143	12	learning	learning	NOUN
ajsts-5382	143	13	algorithms	algorithm	NOUN
ajsts-5382	143	14	that	that	PRON
ajsts-5382	143	15	are	be	AUX
ajsts-5382	143	16	particularly	particularly	ADV
ajsts-5382	143	17	for	for	ADP
ajsts-5382	143	18	image	image	NOUN
ajsts-5382	143	19	recognition	recognition	NOUN
ajsts-5382	143	20	and	and	CCONJ
ajsts-5382	143	21	processing	processing	NOUN
ajsts-5382	143	22	tasks	task	NOUN
ajsts-5382	143	23	.	.	PUNCT
ajsts-5382	144	1	resnets	resnet	NOUN
ajsts-5382	144	2	are	be	AUX
ajsts-5382	144	3	known	know	VERB
ajsts-5382	144	4	for	for	ADP
ajsts-5382	144	5	their	their	PRON
ajsts-5382	144	6	make	make	NOUN
ajsts-5382	144	7	to	to	PART
ajsts-5382	144	8	train	train	VERB
ajsts-5382	144	9	very	very	ADV
ajsts-5382	144	10	deep	deep	ADJ
ajsts-5382	144	11	networks	network	NOUN
ajsts-5382	144	12	without	without	ADP
ajsts-5382	144	13	overfitting	overfitte	VERB
ajsts-5382	144	14	•	•	NUM
ajsts-5382	144	15	resnets	resnet	NOUN
ajsts-5382	144	16	are	be	AUX
ajsts-5382	144	17	helpful	helpful	ADJ
ajsts-5382	144	18	for	for	ADP
ajsts-5382	144	19	detection	detection	NOUN
ajsts-5382	144	20	tasks	task	NOUN
ajsts-5382	144	21	.	.	PUNCT
ajsts-5382	145	1	key	key	ADJ
ajsts-5382	145	2	point	point	NOUN
ajsts-5382	145	3	detection	detection	NOUN
ajsts-5382	145	4	is	be	AUX
ajsts-5382	145	5	the	the	DET
ajsts-5382	145	6	task	task	NOUN
ajsts-5382	145	7	of	of	ADP
ajsts-5382	145	8	locating	locate	VERB
ajsts-5382	145	9	points	point	NOUN
ajsts-5382	145	10	on	on	ADP
ajsts-5382	145	11	an	an	DET
ajsts-5382	145	12	object	object	NOUN
ajsts-5382	145	13	in	in	ADP
ajsts-5382	145	14	an	an	DET
ajsts-5382	145	15	image	image	NOUN
ajsts-5382	145	16	.	.	PUNCT
ajsts-5382	146	1	for	for	ADP
ajsts-5382	146	2	example	example	NOUN
ajsts-5382	146	3	,	,	PUNCT
ajsts-5382	146	4	detection	detection	NOUN
ajsts-5382	146	5	can	can	AUX
ajsts-5382	146	6	be	be	AUX
ajsts-5382	146	7	used	use	VERB
ajsts-5382	146	8	to	to	PART
ajsts-5382	146	9	locate	locate	VERB
ajsts-5382	146	10	the	the	DET
ajsts-5382	146	11	eyes	eye	NOUN
ajsts-5382	146	12	,	,	PUNCT
ajsts-5382	146	13	nose	nose	NOUN
ajsts-5382	146	14	,	,	PUNCT
ajsts-5382	146	15	and	and	CCONJ
ajsts-5382	146	16	mouth	mouth	NOUN
ajsts-5382	146	17	on	on	ADP
ajsts-5382	146	18	a	a	DET
ajsts-5382	146	19	human	human	ADJ
ajsts-5382	146	20	face	face	NOUN
ajsts-5382	146	21	.	.	PUNCT
ajsts-5382	147	1	•	•	NUM
ajsts-5382	147	2	resnets	resnet	NOUN
ajsts-5382	147	3	are	be	AUX
ajsts-5382	147	4	well	well	ADV
ajsts-5382	147	5	-	-	PUNCT
ajsts-5382	147	6	suited	suited	ADJ
ajsts-5382	147	7	because	because	SCONJ
ajsts-5382	147	8	they	they	PRON
ajsts-5382	147	9	can	can	AUX
ajsts-5382	147	10	learn	learn	VERB
ajsts-5382	147	11	to	to	PART
ajsts-5382	147	12	extract	extract	VERB
ajsts-5382	147	13	from	from	ADP
ajsts-5382	147	14	images	image	NOUN
ajsts-5382	147	15	at	at	ADP
ajsts-5382	147	16	different	different	ADJ
ajsts-5382	147	17	scales	scale	NOUN
ajsts-5382	147	18	.	.	PUNCT
ajsts-5382	148	1	references	reference	NOUN
ajsts-5382	148	2	bello	bello	PROPN
ajsts-5382	148	3	,	,	PUNCT
ajsts-5382	148	4	i.	i.	PROPN
ajsts-5382	148	5	,	,	PUNCT
ajsts-5382	148	6	zoph	zoph	PROPN
ajsts-5382	148	7	,	,	PUNCT
ajsts-5382	148	8	b.	b.	PROPN
ajsts-5382	148	9	,	,	PUNCT
ajsts-5382	148	10	vaswani	vaswani	NOUN
ajsts-5382	148	11	,	,	PUNCT
ajsts-5382	148	12	a.	a.	NOUN
ajsts-5382	148	13	,	,	PUNCT
ajsts-5382	148	14	shlens	shlens	PROPN
ajsts-5382	148	15	,	,	PUNCT
ajsts-5382	148	16	j.	j.	PROPN
ajsts-5382	148	17	,	,	PUNCT
ajsts-5382	148	18	&	&	CCONJ
ajsts-5382	148	19	le	le	PROPN
ajsts-5382	148	20	,	,	PUNCT
ajsts-5382	148	21	q.	q.	PROPN
ajsts-5382	148	22	v.	v.	PROPN
ajsts-5382	148	23	(	(	PUNCT
ajsts-5382	148	24	2019	2019	NUM
ajsts-5382	148	25	)	)	PUNCT
ajsts-5382	148	26	.	.	PUNCT
ajsts-5382	149	1	attention	attention	NOUN
ajsts-5382	149	2	augmented	augment	VERB
ajsts-5382	149	3	convolutional	convolutional	ADJ
ajsts-5382	149	4	networks	network	NOUN
ajsts-5382	149	5	.	.	PUNCT
ajsts-5382	150	1	in	in	ADP
ajsts-5382	150	2	proceedings	proceeding	NOUN
ajsts-5382	150	3	of	of	ADP
ajsts-5382	150	4	the	the	DET
ajsts-5382	150	5	ieee	ieee	NOUN
ajsts-5382	150	6	/	/	SYM
ajsts-5382	150	7	cvf	cvf	NOUN
ajsts-5382	150	8	international	international	ADJ
ajsts-5382	150	9	conference	conference	NOUN
ajsts-5382	150	10	on	on	ADP
ajsts-5382	150	11	computer	computer	NOUN
ajsts-5382	150	12	vision	vision	NOUN
ajsts-5382	150	13	(	(	PUNCT
ajsts-5382	150	14	pp	pp	ADJ
ajsts-5382	150	15	.	.	PUNCT
ajsts-5382	150	16	3286–3295	3286–3295	NUM
ajsts-5382	150	17	)	)	PUNCT
ajsts-5382	150	18	.	.	PUNCT
ajsts-5382	151	1	ieee	ieee	PROPN
ajsts-5382	151	2	.	.	PUNCT
ajsts-5382	152	1	chen	chen	PROPN
ajsts-5382	152	2	,	,	PUNCT
ajsts-5382	152	3	b.	b.	PROPN
ajsts-5382	152	4	,	,	PUNCT
ajsts-5382	152	5	ghiasi	ghiasi	NOUN
ajsts-5382	152	6	,	,	PUNCT
ajsts-5382	152	7	g.	g.	PROPN
ajsts-5382	152	8	,	,	PUNCT
ajsts-5382	152	9	liu	liu	PROPN
ajsts-5382	152	10	,	,	PUNCT
ajsts-5382	152	11	h.	h.	PROPN
ajsts-5382	152	12	,	,	PUNCT
ajsts-5382	152	13	lin	lin	PROPN
ajsts-5382	152	14	,	,	PUNCT
ajsts-5382	152	15	t.-y	t.-y	NOUN
ajsts-5382	152	16	.	.	PROPN
ajsts-5382	152	17	,	,	PUNCT
ajsts-5382	152	18	kalenichenko	kalenichenko	PROPN
ajsts-5382	152	19	,	,	PUNCT
ajsts-5382	152	20	d.	d.	PROPN
ajsts-5382	152	21	,	,	PUNCT
ajsts-5382	152	22	adam	adam	PROPN
ajsts-5382	152	23	,	,	PUNCT
ajsts-5382	152	24	h.	h.	PROPN
ajsts-5382	152	25	,	,	PUNCT
ajsts-5382	152	26	&	&	CCONJ
ajsts-5382	152	27	le	le	PROPN
ajsts-5382	152	28	,	,	PUNCT
ajsts-5382	152	29	q.	q.	PROPN
ajsts-5382	152	30	v.	v.	PROPN
ajsts-5382	152	31	(	(	PUNCT
ajsts-5382	152	32	2020	2020	NUM
ajsts-5382	152	33	)	)	PUNCT
ajsts-5382	152	34	.	.	PUNCT
ajsts-5382	153	1	mnasfpn	mnasfpn	PROPN
ajsts-5382	153	2	:	:	PUNCT
ajsts-5382	153	3	learning	learn	VERB
ajsts-5382	153	4	latency	latency	NOUN
ajsts-5382	153	5	-	-	PUNCT
ajsts-5382	153	6	aware	aware	ADJ
ajsts-5382	153	7	pyramid	pyramid	NOUN
ajsts-5382	153	8	architecture	architecture	NOUN
ajsts-5382	153	9	for	for	ADP
ajsts-5382	153	10	object	object	NOUN
ajsts-5382	153	11	detection	detection	NOUN
ajsts-5382	153	12	on	on	ADP
ajsts-5382	153	13	mobile	mobile	ADJ
ajsts-5382	153	14	devices	device	NOUN
ajsts-5382	153	15	.	.	PUNCT
ajsts-5382	154	1	in	in	ADP
ajsts-5382	154	2	proceedings	proceeding	NOUN
ajsts-5382	154	3	of	of	ADP
ajsts-5382	154	4	the	the	DET
ajsts-5382	154	5	ieee	ieee	NOUN
ajsts-5382	154	6	/	/	SYM
ajsts-5382	154	7	cvf	cvf	NOUN
ajsts-5382	154	8	conference	conference	NOUN
ajsts-5382	154	9	on	on	ADP
ajsts-5382	154	10	computer	computer	NOUN
ajsts-5382	154	11	vision	vision	NOUN
ajsts-5382	154	12	and	and	CCONJ
ajsts-5382	154	13	pattern	pattern	NOUN
ajsts-5382	154	14	recognition	recognition	NOUN
ajsts-5382	154	15	(	(	PUNCT
ajsts-5382	154	16	pp	pp	ADJ
ajsts-5382	154	17	.	.	PUNCT
ajsts-5382	154	18	13607–13616	13607–13616	NUM
ajsts-5382	154	19	)	)	PUNCT
ajsts-5382	154	20	.	.	PUNCT
ajsts-5382	155	1	ieee	ieee	PROPN
ajsts-5382	155	2	.	.	PUNCT
ajsts-5382	156	1	deng	deng	PROPN
ajsts-5382	156	2	,	,	PUNCT
ajsts-5382	156	3	j.	j.	PROPN
ajsts-5382	156	4	,	,	PUNCT
ajsts-5382	156	5	dong	dong	PROPN
ajsts-5382	156	6	,	,	PUNCT
ajsts-5382	156	7	w.	w.	PROPN
ajsts-5382	156	8	,	,	PUNCT
ajsts-5382	156	9	socher	socher	PROPN
ajsts-5382	156	10	,	,	PUNCT
ajsts-5382	156	11	r.	r.	PROPN
ajsts-5382	156	12	,	,	PUNCT
ajsts-5382	156	13	li	li	PROPN
ajsts-5382	156	14	,	,	PUNCT
ajsts-5382	156	15	l.-j	l.-j	PROPN
ajsts-5382	156	16	.	.	PROPN
ajsts-5382	156	17	,	,	PUNCT
ajsts-5382	156	18	li	li	PROPN
ajsts-5382	156	19	,	,	PUNCT
ajsts-5382	156	20	k.	k.	PROPN
ajsts-5382	156	21	,	,	PUNCT
ajsts-5382	156	22	&	&	CCONJ
ajsts-5382	156	23	fei	fei	PROPN
ajsts-5382	156	24	-	-	PUNCT
ajsts-5382	156	25	fei	fei	PROPN
ajsts-5382	156	26	,	,	PUNCT
ajsts-5382	156	27	l.	l.	PROPN
ajsts-5382	156	28	(	(	PUNCT
ajsts-5382	156	29	2009	2009	NUM
ajsts-5382	156	30	,	,	PUNCT
ajsts-5382	156	31	june	june	PROPN
ajsts-5382	156	32	20	20	NUM
ajsts-5382	156	33	)	)	PUNCT
ajsts-5382	156	34	.	.	PUNCT
ajsts-5382	157	1	imagenet	imagenet	NOUN
ajsts-5382	157	2	:	:	PUNCT
ajsts-5382	157	3	a	a	DET
ajsts-5382	157	4	large	large	ADJ
ajsts-5382	157	5	-	-	PUNCT
ajsts-5382	157	6	scale	scale	NOUN
ajsts-5382	157	7	hierarchical	hierarchical	ADJ
ajsts-5382	157	8	image	image	NOUN
ajsts-5382	157	9	database	database	NOUN
ajsts-5382	157	10	.	.	PUNCT
ajsts-5382	158	1	in	in	ADP
ajsts-5382	158	2	2009	2009	NUM
ajsts-5382	158	3	ieee	ieee	NOUN
ajsts-5382	158	4	conference	conference	NOUN
ajsts-5382	158	5	on	on	ADP
ajsts-5382	158	6	computer	computer	NOUN
ajsts-5382	158	7	vision	vision	NOUN
ajsts-5382	158	8	and	and	CCONJ
ajsts-5382	158	9	pattern	pattern	NOUN
ajsts-5382	158	10	recognition	recognition	NOUN
ajsts-5382	158	11	(	(	PUNCT
ajsts-5382	158	12	pp	pp	ADJ
ajsts-5382	158	13	.	.	PUNCT
ajsts-5382	159	1	248–255	248–255	NUM
ajsts-5382	159	2	)	)	PUNCT
ajsts-5382	159	3	.	.	PUNCT
ajsts-5382	160	1	ieee	ieee	PROPN
ajsts-5382	160	2	.	.	PUNCT
ajsts-5382	161	1	devries	devries	PROPN
ajsts-5382	161	2	,	,	PUNCT
ajsts-5382	161	3	t.	t.	PROPN
ajsts-5382	161	4	,	,	PUNCT
ajsts-5382	161	5	&	&	CCONJ
ajsts-5382	161	6	taylor	taylor	PROPN
ajsts-5382	161	7	,	,	PUNCT
ajsts-5382	161	8	g.	g.	PROPN
ajsts-5382	161	9	w.	w.	PROPN
ajsts-5382	161	10	(	(	PUNCT
ajsts-5382	161	11	2017	2017	NUM
ajsts-5382	161	12	,	,	PUNCT
ajsts-5382	161	13	august	august	PROPN
ajsts-5382	161	14	15	15	NUM
ajsts-5382	161	15	)	)	PUNCT
ajsts-5382	161	16	.	.	PUNCT
ajsts-5382	162	1	improved	improve	VERB
ajsts-5382	162	2	regularization	regularization	NOUN
ajsts-5382	162	3	of	of	ADP
ajsts-5382	162	4	convolutional	convolutional	ADJ
ajsts-5382	162	5	neural	neural	ADJ
ajsts-5382	162	6	networks	network	NOUN
ajsts-5382	162	7	with	with	ADP
ajsts-5382	162	8	considering	consider	VERB
ajsts-5382	162	9	,	,	PUNCT
ajsts-5382	162	10	farming	farm	VERB
ajsts-5382	162	11	side	side	NOUN
ajsts-5382	162	12	s1	s1	NOUN
ajsts-5382	162	13	:	:	PUNCT
ajsts-5382	162	14	images	image	NOUN
ajsts-5382	162	15	inputs	input	VERB
ajsts-5382	162	16	ms	ms	NOUN
ajsts-5382	162	17	:	:	PUNCT
ajsts-5382	162	18	length	length	PROPN
ajsts-5382	162	19	t1	t1	NOUN
ajsts-5382	162	20	:	:	PUNCT
ajsts-5382	162	21	root	root	NOUN
ajsts-5382	162	22	size	size	NOUN
ajsts-5382	162	23	r_lat	r_lat	PROPN
ajsts-5382	162	24	,	,	PUNCT
ajsts-5382	162	25	r_nod	r_nod	PROPN
ajsts-5382	162	26	,	,	PUNCT
ajsts-5382	162	27	r_bra	r_bra	X
ajsts-5382	162	28	in	in	ADP
ajsts-5382	162	29	the	the	DET
ajsts-5382	162	30	process	process	NOUN
ajsts-5382	162	31	of	of	ADP
ajsts-5382	162	32	resnn	resnn	NOUN
ajsts-5382	162	33	,	,	PUNCT
ajsts-5382	162	34	the	the	DET
ajsts-5382	162	35	extraction	extraction	NOUN
ajsts-5382	162	36	of	of	ADP
ajsts-5382	162	37	images	image	NOUN
ajsts-5382	162	38	is	be	AUX
ajsts-5382	162	39	consolidated	consolidate	VERB
ajsts-5382	162	40	from	from	ADP
ajsts-5382	162	41	the	the	DET
ajsts-5382	162	42	m1	m1	PROPN
ajsts-5382	162	43	position	position	NOUN
ajsts-5382	162	44	to	to	ADP
ajsts-5382	162	45	the	the	DET
ajsts-5382	162	46	ms	ms	PROPN
ajsts-5382	162	47	position	position	NOUN
ajsts-5382	162	48	.	.	PUNCT
ajsts-5382	163	1	after	after	ADP
ajsts-5382	163	2	that	that	PRON
ajsts-5382	163	3	,	,	PUNCT
ajsts-5382	163	4	the	the	DET
ajsts-5382	163	5	land	land	NOUN
ajsts-5382	163	6	-	-	PUNCT
ajsts-5382	163	7	side	side	NOUN
ajsts-5382	163	8	-	-	PUNCT
ajsts-5382	163	9	wise	wise	ADJ
ajsts-5382	163	10	extraction	extraction	NOUN
ajsts-5382	163	11	is	be	AUX
ajsts-5382	163	12	in	in	ADP
ajsts-5382	163	13	observation	observation	NOUN
ajsts-5382	163	14	for	for	ADP
ajsts-5382	163	15	the	the	DET
ajsts-5382	163	16	same	same	ADJ
ajsts-5382	163	17	,	,	PUNCT
ajsts-5382	163	18	considering	consider	VERB
ajsts-5382	163	19	the	the	DET
ajsts-5382	163	20	s1	s1	PROPN
ajsts-5382	163	21	to	to	ADP
ajsts-5382	163	22	s	s	PROPN
ajsts-5382	163	23	nth	nth	NOUN
ajsts-5382	163	24	side	side	NOUN
ajsts-5382	163	25	.	.	PUNCT
ajsts-5382	164	1	whereas	whereas	SCONJ
ajsts-5382	164	2	the	the	DET
ajsts-5382	164	3	root	root	NOUN
ajsts-5382	164	4	observation	observation	NOUN
ajsts-5382	164	5	key	key	ADJ
ajsts-5382	164	6	points	point	NOUN
ajsts-5382	164	7	are	be	AUX
ajsts-5382	164	8	evaluated	evaluate	VERB
ajsts-5382	164	9	and	and	CCONJ
ajsts-5382	164	10	analyzed	analyze	VERB
ajsts-5382	164	11	to	to	PART
ajsts-5382	164	12	add	add	VERB
ajsts-5382	164	13	f(x	f(x	PROPN
ajsts-5382	164	14	)	)	PUNCT
ajsts-5382	165	1	=	=	SYM
ajsts-5382	165	2	t1+r_lat	t1+r_lat	ADJ
ajsts-5382	165	3	,	,	PUNCT
ajsts-5382	165	4	similarly	similarly	ADV
ajsts-5382	165	5	add	add	VERB
ajsts-5382	165	6	f(y)=	f(y)=	NOUN
ajsts-5382	165	7	t1+r_nod	t1+r_nod	PROPN
ajsts-5382	165	8	and	and	CCONJ
ajsts-5382	165	9	f(z)=	f(z)=	PROPN
ajsts-5382	165	10	t1+r_bra	t1+r_bra	PROPN
ajsts-5382	165	11	.	.	PUNCT
ajsts-5382	166	1	the	the	DET
ajsts-5382	166	2	functions	function	NOUN
ajsts-5382	166	3	f(x	f(x	PROPN
ajsts-5382	166	4	)	)	PUNCT
ajsts-5382	167	1	=	=	PRON
ajsts-5382	167	2	partially	partially	ADV
ajsts-5382	167	3	integrated	integrate	VERB
ajsts-5382	167	4	mapping	mapping	NOUN
ajsts-5382	167	5	and	and	CCONJ
ajsts-5382	167	6	putting	put	VERB
ajsts-5382	167	7	the	the	DET
ajsts-5382	167	8	evaluation	evaluation	NOUN
ajsts-5382	167	9	steps	step	NOUN
ajsts-5382	167	10	for	for	ADP
ajsts-5382	167	11	states	state	NOUN
ajsts-5382	167	12	lateral	lateral	ADJ
ajsts-5382	167	13	roots	root	NOUN
ajsts-5382	167	14	,	,	PUNCT
ajsts-5382	167	15	states	state	VERB
ajsts-5382	167	16	nodules	nodule	NOUN
ajsts-5382	167	17	,	,	PUNCT
ajsts-5382	167	18	and	and	CCONJ
ajsts-5382	167	19	states	state	VERB
ajsts-5382	167	20	branchtop	branchtop	NOUN
ajsts-5382	167	21	root	root	NOUN
ajsts-5382	167	22	.	.	PUNCT
ajsts-5382	168	1	therefore	therefore	ADV
ajsts-5382	168	2	,	,	PUNCT
ajsts-5382	168	3	output	output	NOUN
ajsts-5382	168	4	evaluation	evaluation	NOUN
ajsts-5382	168	5	y	y	PROPN
ajsts-5382	168	6	=	=	SYM
ajsts-5382	168	7	f	f	PROPN
ajsts-5382	168	8	(	(	PUNCT
ajsts-5382	168	9	x	x	X
ajsts-5382	168	10	)	)	PUNCT
ajsts-5382	169	1	+	+	NOUN
ajsts-5382	169	2	f	f	X
ajsts-5382	169	3	(	(	PUNCT
ajsts-5382	169	4	y	y	PROPN
ajsts-5382	169	5	)	)	PUNCT
ajsts-5382	169	6	+	+	NOUN
ajsts-5382	169	7	f	f	X
ajsts-5382	169	8	(	(	PUNCT
ajsts-5382	169	9	z	z	NOUN
ajsts-5382	169	10	)	)	PUNCT
ajsts-5382	169	11	same	same	ADJ
ajsts-5382	169	12	way	way	NOUN
ajsts-5382	169	13	,	,	PUNCT
ajsts-5382	169	14	the	the	DET
ajsts-5382	169	15	changes	change	NOUN
ajsts-5382	169	16	in	in	ADP
ajsts-5382	169	17	image	image	NOUN
ajsts-5382	169	18	observation	observation	NOUN
ajsts-5382	169	19	,	,	PUNCT
ajsts-5382	169	20	the	the	DET
ajsts-5382	169	21	values	value	NOUN
ajsts-5382	169	22	are	be	AUX
ajsts-5382	169	23	integrated	integrate	VERB
ajsts-5382	169	24	,	,	PUNCT
ajsts-5382	169	25	and	and	CCONJ
ajsts-5382	169	26	the	the	DET
ajsts-5382	169	27	analysis	analysis	NOUN
ajsts-5382	169	28	of	of	ADP
ajsts-5382	169	29	the	the	DET
ajsts-5382	169	30	present	present	ADJ
ajsts-5382	169	31	image	image	NOUN
ajsts-5382	169	32	data	datum	NOUN
ajsts-5382	169	33	set	set	NOUN
ajsts-5382	169	34	would	would	AUX
ajsts-5382	169	35	be	be	AUX
ajsts-5382	169	36	responsible	responsible	ADJ
ajsts-5382	169	37	for	for	ADP
ajsts-5382	169	38	the	the	DET
ajsts-5382	169	39	analysis	analysis	NOUN
ajsts-5382	169	40	of	of	ADP
ajsts-5382	169	41	the	the	DET
ajsts-5382	169	42	healthy	healthy	ADJ
ajsts-5382	169	43	condition	condition	NOUN
ajsts-5382	169	44	of	of	ADP
ajsts-5382	169	45	the	the	DET
ajsts-5382	169	46	roots	root	NOUN
ajsts-5382	169	47	,	,	PUNCT
ajsts-5382	169	48	and	and	CCONJ
ajsts-5382	169	49	also	also	ADV
ajsts-5382	169	50	changes	change	VERB
ajsts-5382	169	51	in	in	ADP
ajsts-5382	169	52	the	the	DET
ajsts-5382	169	53	image	image	NOUN
ajsts-5382	169	54	data	datum	NOUN
ajsts-5382	169	55	set	set	VERB
ajsts-5382	169	56	to	to	PART
ajsts-5382	169	57	observe	observe	VERB
ajsts-5382	169	58	the	the	DET
ajsts-5382	169	59	desired	desire	VERB
ajsts-5382	169	60	diseases	disease	NOUN
ajsts-5382	169	61	and	and	CCONJ
ajsts-5382	169	62	progress	progress	NOUN
ajsts-5382	169	63	of	of	ADP
ajsts-5382	169	64	the	the	DET
ajsts-5382	169	65	plant	plant	NOUN
ajsts-5382	169	66	.	.	PUNCT
ajsts-5382	170	1	conclusion	conclusion	NOUN
ajsts-5382	170	2	the	the	DET
ajsts-5382	170	3	observation	observation	NOUN
ajsts-5382	170	4	implementation	implementation	NOUN
ajsts-5382	170	5	is	be	AUX
ajsts-5382	170	6	still	still	ADV
ajsts-5382	170	7	in	in	ADP
ajsts-5382	170	8	process	process	NOUN
ajsts-5382	170	9	for	for	ADP
ajsts-5382	170	10	pa	pa	PROPN
ajsts-5382	170	11	ge	ge	PROPN
ajsts-5382	170	12	62	62	NUM
ajsts-5382	170	13	https://journals.e-palli.com/home/index.php/ajsts	https://journals.e-palli.com/home/index.php/ajst	NOUN
ajsts-5382	170	14	am	be	AUX
ajsts-5382	170	15	.	.	PUNCT
ajsts-5382	171	1	j.	j.	PROPN
ajsts-5382	171	2	smart	smart	PROPN
ajsts-5382	171	3	.	.	PUNCT
ajsts-5382	172	1	technol	technol	PROPN
ajsts-5382	172	2	.	.	PUNCT
ajsts-5382	172	3	solutions	solution	NOUN
ajsts-5382	172	4	4(2	4(2	NUM
ajsts-5382	172	5	)	)	PUNCT
ajsts-5382	172	6	57	57	NUM
ajsts-5382	172	7	-	-	SYM
ajsts-5382	172	8	62	62	NUM
ajsts-5382	172	9	,	,	PUNCT
ajsts-5382	172	10	2025	2025	NUM
ajsts-5382	172	11	cutout	cutout	NOUN
ajsts-5382	172	12	.	.	PUNCT
ajsts-5382	173	1	arxiv	arxiv	PROPN
ajsts-5382	173	2	preprint	preprint	PROPN
ajsts-5382	173	3	arxiv:1708.04552	arxiv:1708.04552	NOUN
ajsts-5382	173	4	.	.	PUNCT
ajsts-5382	174	1	farooq	farooq	PROPN
ajsts-5382	174	2	,	,	PUNCT
ajsts-5382	174	3	m.	m.	NOUN
ajsts-5382	174	4	,	,	PUNCT
ajsts-5382	174	5	&	&	CCONJ
ajsts-5382	174	6	hafeez	hafeez	PROPN
ajsts-5382	174	7	,	,	PUNCT
ajsts-5382	174	8	a.	a.	NOUN
ajsts-5382	174	9	(	(	PUNCT
ajsts-5382	174	10	2020	2020	NUM
ajsts-5382	174	11	,	,	PUNCT
ajsts-5382	174	12	march	march	PROPN
ajsts-5382	174	13	31	31	NUM
ajsts-5382	174	14	)	)	PUNCT
ajsts-5382	174	15	.	.	PUNCT
ajsts-5382	175	1	covid	covid	PROPN
ajsts-5382	175	2	-	-	PUNCT
ajsts-5382	175	3	resnet	resnet	NOUN
ajsts-5382	175	4	:	:	PUNCT
ajsts-5382	175	5	a	a	DET
ajsts-5382	175	6	deep	deep	ADJ
ajsts-5382	175	7	learning	learning	NOUN
ajsts-5382	175	8	framework	framework	NOUN
ajsts-5382	175	9	for	for	ADP
ajsts-5382	175	10	screening	screening	NOUN
ajsts-5382	175	11	of	of	ADP
ajsts-5382	175	12	covid-19	covid-19	PROPN
ajsts-5382	175	13	from	from	ADP
ajsts-5382	175	14	radiographs	radiograph	NOUN
ajsts-5382	175	15	.	.	PUNCT
ajsts-5382	176	1	arxiv	arxiv	PROPN
ajsts-5382	176	2	preprint	preprint	PROPN
ajsts-5382	176	3	arxiv:2003.14395	arxiv:2003.14395	PROPN
ajsts-5382	176	4	.	.	PUNCT
ajsts-5382	177	1	gao	gao	PROPN
ajsts-5382	177	2	,	,	PUNCT
ajsts-5382	177	3	s.	s.	PROPN
ajsts-5382	177	4	h.	h.	PROPN
ajsts-5382	177	5	,	,	PUNCT
ajsts-5382	177	6	cheng	cheng	PROPN
ajsts-5382	177	7	,	,	PUNCT
ajsts-5382	177	8	m.	m.	NOUN
ajsts-5382	177	9	m.	m.	NOUN
ajsts-5382	177	10	,	,	PUNCT
ajsts-5382	177	11	zhao	zhao	PROPN
ajsts-5382	177	12	,	,	PUNCT
ajsts-5382	177	13	k.	k.	PROPN
ajsts-5382	177	14	,	,	PUNCT
ajsts-5382	177	15	zhang	zhang	PROPN
ajsts-5382	177	16	,	,	PUNCT
ajsts-5382	177	17	x.	x.	PROPN
ajsts-5382	177	18	y.	y.	PROPN
ajsts-5382	177	19	,	,	PUNCT
ajsts-5382	177	20	yang	yang	PROPN
ajsts-5382	177	21	,	,	PUNCT
ajsts-5382	177	22	m.	m.	PROPN
ajsts-5382	177	23	h.	h.	PROPN
ajsts-5382	177	24	,	,	PUNCT
ajsts-5382	177	25	&	&	CCONJ
ajsts-5382	177	26	torr	torr	PROPN
ajsts-5382	177	27	,	,	PUNCT
ajsts-5382	177	28	p.	p.	PROPN
ajsts-5382	177	29	h.	h.	PROPN
ajsts-5382	177	30	s.	s.	PROPN
ajsts-5382	177	31	(	(	PUNCT
ajsts-5382	177	32	2021	2021	NUM
ajsts-5382	177	33	)	)	PUNCT
ajsts-5382	177	34	.	.	PUNCT
ajsts-5382	178	1	res2net	res2net	NOUN
ajsts-5382	178	2	:	:	PUNCT
ajsts-5382	178	3	a	a	DET
ajsts-5382	178	4	new	new	ADJ
ajsts-5382	178	5	multiscale	multiscale	ADJ
ajsts-5382	178	6	backbone	backbone	NOUN
ajsts-5382	178	7	architecture	architecture	NOUN
ajsts-5382	178	8	.	.	PUNCT
ajsts-5382	179	1	ieee	ieee	NOUN
ajsts-5382	179	2	transactions	transaction	NOUN
ajsts-5382	179	3	on	on	ADP
ajsts-5382	179	4	pattern	pattern	NOUN
ajsts-5382	179	5	analysis	analysis	NOUN
ajsts-5382	179	6	and	and	CCONJ
ajsts-5382	179	7	machine	machine	NOUN
ajsts-5382	179	8	intelligence	intelligence	NOUN
ajsts-5382	179	9	,	,	PUNCT
ajsts-5382	179	10	43(2	43(2	PROPN
ajsts-5382	179	11	)	)	PUNCT
ajsts-5382	179	12	,	,	PUNCT
ajsts-5382	179	13	652–662	652–662	NUM
ajsts-5382	179	14	.	.	PUNCT
ajsts-5382	180	1	he	he	PRON
ajsts-5382	180	2	,	,	PUNCT
ajsts-5382	180	3	k.	k.	PROPN
ajsts-5382	180	4	,	,	PUNCT
ajsts-5382	180	5	zhang	zhang	PROPN
ajsts-5382	180	6	,	,	PUNCT
ajsts-5382	180	7	x.	x.	PROPN
ajsts-5382	180	8	,	,	PUNCT
ajsts-5382	180	9	ren	ren	PROPN
ajsts-5382	180	10	,	,	PUNCT
ajsts-5382	180	11	s.	s.	PROPN
ajsts-5382	180	12	,	,	PUNCT
ajsts-5382	180	13	&	&	CCONJ
ajsts-5382	180	14	sun	sun	PROPN
ajsts-5382	180	15	,	,	PUNCT
ajsts-5382	180	16	j.	j.	PROPN
ajsts-5382	180	17	(	(	PUNCT
ajsts-5382	180	18	2016	2016	NUM
ajsts-5382	180	19	)	)	PUNCT
ajsts-5382	180	20	.	.	PUNCT
ajsts-5382	181	1	deep	deep	ADJ
ajsts-5382	181	2	residual	residual	ADJ
ajsts-5382	181	3	learning	learning	NOUN
ajsts-5382	181	4	for	for	ADP
ajsts-5382	181	5	image	image	NOUN
ajsts-5382	181	6	recognition	recognition	NOUN
ajsts-5382	181	7	.	.	PUNCT
ajsts-5382	182	1	in	in	ADP
ajsts-5382	182	2	proceedings	proceeding	NOUN
ajsts-5382	182	3	of	of	ADP
ajsts-5382	182	4	the	the	DET
ajsts-5382	182	5	ieee	ieee	NOUN
ajsts-5382	182	6	conference	conference	NOUN
ajsts-5382	182	7	on	on	ADP
ajsts-5382	182	8	computer	computer	NOUN
ajsts-5382	182	9	vision	vision	NOUN
ajsts-5382	182	10	and	and	CCONJ
ajsts-5382	182	11	pattern	pattern	NOUN
ajsts-5382	182	12	recognition	recognition	NOUN
ajsts-5382	182	13	(	(	PUNCT
ajsts-5382	182	14	pp	pp	ADJ
ajsts-5382	182	15	.	.	PUNCT
ajsts-5382	183	1	770–778	770–778	NUM
ajsts-5382	183	2	)	)	PUNCT
ajsts-5382	183	3	.	.	PUNCT
ajsts-5382	184	1	ieee	ieee	PROPN
ajsts-5382	184	2	.	.	PUNCT
ajsts-5382	185	1	hu	hu	PROPN
ajsts-5382	185	2	,	,	PUNCT
ajsts-5382	185	3	j.	j.	PROPN
ajsts-5382	185	4	,	,	PUNCT
ajsts-5382	185	5	shen	shen	PROPN
ajsts-5382	185	6	,	,	PUNCT
ajsts-5382	185	7	l.	l.	PROPN
ajsts-5382	185	8	,	,	PUNCT
ajsts-5382	185	9	&	&	CCONJ
ajsts-5382	185	10	sun	sun	PROPN
ajsts-5382	185	11	,	,	PUNCT
ajsts-5382	185	12	g.	g.	PROPN
ajsts-5382	185	13	(	(	PUNCT
ajsts-5382	185	14	2018	2018	NUM
ajsts-5382	185	15	)	)	PUNCT
ajsts-5382	185	16	.	.	PUNCT
ajsts-5382	186	1	squeeze	squeeze	NOUN
ajsts-5382	186	2	-	-	PUNCT
ajsts-5382	186	3	and	and	CCONJ
ajsts-5382	186	4	-	-	PUNCT
ajsts-5382	186	5	excitation	excitation	NOUN
ajsts-5382	186	6	networks	network	NOUN
ajsts-5382	186	7	.	.	PUNCT
ajsts-5382	187	1	in	in	ADP
ajsts-5382	187	2	proceedings	proceeding	NOUN
ajsts-5382	187	3	of	of	ADP
ajsts-5382	187	4	the	the	DET
ajsts-5382	187	5	ieee	ieee	NOUN
ajsts-5382	187	6	conference	conference	NOUN
ajsts-5382	187	7	on	on	ADP
ajsts-5382	187	8	computer	computer	NOUN
ajsts-5382	187	9	vision	vision	NOUN
ajsts-5382	187	10	and	and	CCONJ
ajsts-5382	187	11	pattern	pattern	NOUN
ajsts-5382	187	12	recognition	recognition	NOUN
ajsts-5382	187	13	(	(	PUNCT
ajsts-5382	187	14	pp	pp	ADJ
ajsts-5382	187	15	.	.	PUNCT
ajsts-5382	188	1	7132–7141	7132–7141	NUM
ajsts-5382	188	2	)	)	PUNCT
ajsts-5382	188	3	.	.	PUNCT
ajsts-5382	189	1	ieee	ieee	PROPN
ajsts-5382	189	2	.	.	PUNCT
ajsts-5382	190	1	huang	huang	PROPN
ajsts-5382	190	2	,	,	PUNCT
ajsts-5382	190	3	g.	g.	PROPN
ajsts-5382	190	4	,	,	PUNCT
ajsts-5382	190	5	liu	liu	PROPN
ajsts-5382	190	6	,	,	PUNCT
ajsts-5382	190	7	z.	z.	PROPN
ajsts-5382	190	8	,	,	PUNCT
ajsts-5382	190	9	van	van	PROPN
ajsts-5382	190	10	der	der	NOUN
ajsts-5382	190	11	maaten	maaten	VERB
ajsts-5382	190	12	,	,	PUNCT
ajsts-5382	190	13	l.	l.	PROPN
ajsts-5382	190	14	,	,	PUNCT
ajsts-5382	190	15	&	&	CCONJ
ajsts-5382	190	16	weinberger	weinberger	PROPN
ajsts-5382	190	17	,	,	PUNCT
ajsts-5382	190	18	k.	k.	PROPN
ajsts-5382	190	19	q.	q.	PROPN
ajsts-5382	190	20	(	(	PUNCT
ajsts-5382	190	21	2017	2017	NUM
ajsts-5382	190	22	)	)	PUNCT
ajsts-5382	190	23	.	.	PUNCT
ajsts-5382	191	1	densely	densely	ADV
ajsts-5382	191	2	connected	connect	VERB
ajsts-5382	191	3	convolutional	convolutional	ADJ
ajsts-5382	191	4	networks	network	NOUN
ajsts-5382	191	5	.	.	PUNCT
ajsts-5382	192	1	in	in	ADP
ajsts-5382	192	2	proceedings	proceeding	NOUN
ajsts-5382	192	3	of	of	ADP
ajsts-5382	192	4	the	the	DET
ajsts-5382	192	5	ieee	ieee	NOUN
ajsts-5382	192	6	conference	conference	NOUN
ajsts-5382	192	7	on	on	ADP
ajsts-5382	192	8	computer	computer	NOUN
ajsts-5382	192	9	vision	vision	NOUN
ajsts-5382	192	10	and	and	CCONJ
ajsts-5382	192	11	pattern	pattern	NOUN
ajsts-5382	192	12	recognition	recognition	NOUN
ajsts-5382	192	13	(	(	PUNCT
ajsts-5382	192	14	pp	pp	ADJ
ajsts-5382	192	15	.	.	PUNCT
ajsts-5382	192	16	4700–4708	4700–4708	NUM
ajsts-5382	192	17	)	)	PUNCT
ajsts-5382	192	18	.	.	PUNCT
ajsts-5382	193	1	ieee	ieee	PROPN
ajsts-5382	193	2	.	.	PUNCT
ajsts-5382	194	1	krizhevsky	krizhevsky	PROPN
ajsts-5382	194	2	,	,	PUNCT
ajsts-5382	194	3	a.	a.	PROPN
ajsts-5382	194	4	,	,	PUNCT
ajsts-5382	194	5	sutskever	sutskever	PROPN
ajsts-5382	194	6	,	,	PUNCT
ajsts-5382	194	7	i.	i.	PROPN
ajsts-5382	194	8	,	,	PUNCT
ajsts-5382	194	9	&	&	CCONJ
ajsts-5382	194	10	hinton	hinton	PROPN
ajsts-5382	194	11	,	,	PUNCT
ajsts-5382	194	12	g.	g.	PROPN
ajsts-5382	194	13	e.	e.	PROPN
ajsts-5382	194	14	(	(	PUNCT
ajsts-5382	194	15	2017	2017	NUM
ajsts-5382	194	16	)	)	PUNCT
ajsts-5382	194	17	.	.	PUNCT
ajsts-5382	195	1	imagenet	imagenet	PROPN
ajsts-5382	195	2	classification	classification	NOUN
ajsts-5382	195	3	with	with	ADP
ajsts-5382	195	4	deep	deep	ADJ
ajsts-5382	195	5	convolutional	convolutional	ADJ
ajsts-5382	195	6	neural	neural	ADJ
ajsts-5382	195	7	networks	network	NOUN
ajsts-5382	195	8	.	.	PUNCT
ajsts-5382	196	1	communications	communication	NOUN
ajsts-5382	196	2	of	of	ADP
ajsts-5382	196	3	the	the	DET
ajsts-5382	196	4	acm	acm	NOUN
ajsts-5382	196	5	,	,	PUNCT
ajsts-5382	196	6	60(6	60(6	NOUN
ajsts-5382	196	7	)	)	PUNCT
ajsts-5382	196	8	,	,	PUNCT
ajsts-5382	196	9	84–90	84–90	NUM
ajsts-5382	196	10	.	.	PUNCT
ajsts-5382	197	1	leibe	leibe	PROPN
ajsts-5382	197	2	,	,	PUNCT
ajsts-5382	197	3	b.	b.	PROPN
ajsts-5382	197	4	,	,	PUNCT
ajsts-5382	197	5	matas	matas	PROPN
ajsts-5382	197	6	,	,	PUNCT
ajsts-5382	197	7	j.	j.	PROPN
ajsts-5382	197	8	,	,	PUNCT
ajsts-5382	197	9	sebe	sebe	PROPN
ajsts-5382	197	10	,	,	PUNCT
ajsts-5382	197	11	n.	n.	NOUN
ajsts-5382	197	12	,	,	PUNCT
ajsts-5382	197	13	&	&	CCONJ
ajsts-5382	197	14	welling	well	VERB
ajsts-5382	197	15	,	,	PUNCT
ajsts-5382	197	16	m.	m.	NOUN
ajsts-5382	197	17	(	(	PUNCT
ajsts-5382	197	18	eds	ed	NOUN
ajsts-5382	197	19	.	.	PUNCT
ajsts-5382	197	20	)	)	PUNCT
ajsts-5382	197	21	.	.	PUNCT
ajsts-5382	198	1	(	(	PUNCT
ajsts-5382	198	2	2016	2016	NUM
ajsts-5382	198	3	,	,	PUNCT
ajsts-5382	198	4	september	september	PROPN
ajsts-5382	198	5	16	16	NUM
ajsts-5382	198	6	)	)	PUNCT
ajsts-5382	198	7	.	.	PUNCT
ajsts-5382	199	1	computer	computer	NOUN
ajsts-5382	199	2	vision	vision	NOUN
ajsts-5382	199	3	–	–	PUNCT
ajsts-5382	199	4	eccv	eccv	NOUN
ajsts-5382	199	5	2016	2016	NUM
ajsts-5382	199	6	:	:	PUNCT
ajsts-5382	199	7	14th	14th	ADJ
ajsts-5382	199	8	european	european	ADJ
ajsts-5382	199	9	conference	conference	PROPN
ajsts-5382	199	10	,	,	PUNCT
ajsts-5382	199	11	amsterdam	amsterdam	PROPN
ajsts-5382	199	12	,	,	PUNCT
ajsts-5382	199	13	the	the	DET
ajsts-5382	199	14	netherlands	netherlands	PROPN
ajsts-5382	199	15	,	,	PUNCT
ajsts-5382	199	16	october	october	PROPN
ajsts-5382	199	17	11–14	11–14	NUM
ajsts-5382	199	18	,	,	PUNCT
ajsts-5382	199	19	2016	2016	NUM
ajsts-5382	199	20	,	,	PUNCT
ajsts-5382	199	21	proceedings	proceeding	NOUN
ajsts-5382	199	22	,	,	PUNCT
ajsts-5382	199	23	part	part	NOUN
ajsts-5382	199	24	iv	iv	NOUN
ajsts-5382	199	25	.	.	PUNCT
ajsts-5382	199	26	springer	springer	PROPN
ajsts-5382	199	27	.	.	PUNCT
ajsts-5382	200	1	li	li	PROPN
ajsts-5382	200	2	,	,	PUNCT
ajsts-5382	200	3	z.	z.	PROPN
ajsts-5382	200	4	,	,	PUNCT
ajsts-5382	200	5	sang	sing	VERB
ajsts-5382	200	6	,	,	PUNCT
ajsts-5382	200	7	n.	n.	PROPN
ajsts-5382	200	8	,	,	PUNCT
ajsts-5382	200	9	chen	chen	PROPN
ajsts-5382	200	10	,	,	PUNCT
ajsts-5382	200	11	k.	k.	PROPN
ajsts-5382	200	12	,	,	PUNCT
ajsts-5382	200	13	gao	gao	PROPN
ajsts-5382	200	14	,	,	PUNCT
ajsts-5382	200	15	c.	c.	PROPN
ajsts-5382	200	16	,	,	PUNCT
ajsts-5382	200	17	&	&	CCONJ
ajsts-5382	200	18	wang	wang	PROPN
ajsts-5382	200	19	,	,	PUNCT
ajsts-5382	200	20	r.	r.	PROPN
ajsts-5382	200	21	(	(	PUNCT
ajsts-5382	200	22	2018	2018	NUM
ajsts-5382	200	23	,	,	PUNCT
ajsts-5382	200	24	march	march	PROPN
ajsts-5382	200	25	8)	8)	NUM
ajsts-5382	200	26	.	.	PUNCT
ajsts-5382	201	1	learning	learn	VERB
ajsts-5382	201	2	deep	deep	ADJ
ajsts-5382	201	3	features	feature	NOUN
ajsts-5382	201	4	with	with	ADP
ajsts-5382	201	5	adaptive	adaptive	ADJ
ajsts-5382	201	6	triplet	triplet	NOUN
ajsts-5382	201	7	loss	loss	NOUN
ajsts-5382	201	8	for	for	ADP
ajsts-5382	201	9	person	person	NOUN
ajsts-5382	201	10	reidentification	reidentification	NOUN
ajsts-5382	201	11	.	.	PUNCT
ajsts-5382	202	1	in	in	ADP
ajsts-5382	202	2	mippr	mippr	NOUN
ajsts-5382	202	3	2017	2017	NUM
ajsts-5382	202	4	:	:	PUNCT
ajsts-5382	202	5	pattern	pattern	NOUN
ajsts-5382	202	6	recognition	recognition	NOUN
ajsts-5382	202	7	and	and	CCONJ
ajsts-5382	202	8	computer	computer	NOUN
ajsts-5382	202	9	vision	vision	NOUN
ajsts-5382	202	10	(	(	PUNCT
ajsts-5382	202	11	vol	vol	NOUN
ajsts-5382	202	12	.	.	PROPN
ajsts-5382	202	13	10609	10609	NUM
ajsts-5382	202	14	,	,	PUNCT
ajsts-5382	202	15	pp	pp	ADP
ajsts-5382	202	16	.	.	PUNCT
ajsts-5382	202	17	90–95	90–95	NUM
ajsts-5382	202	18	)	)	PUNCT
ajsts-5382	202	19	.	.	PUNCT
ajsts-5382	203	1	spie	spie	PROPN
ajsts-5382	203	2	.	.	PUNCT
ajsts-5382	204	1	lin	lin	PROPN
ajsts-5382	204	2	,	,	PUNCT
ajsts-5382	204	3	s.	s.	PROPN
ajsts-5382	204	4	,	,	PUNCT
ajsts-5382	204	5	ji	ji	PROPN
ajsts-5382	204	6	,	,	PUNCT
ajsts-5382	204	7	r.	r.	PROPN
ajsts-5382	204	8	,	,	PUNCT
ajsts-5382	204	9	yan	yan	PROPN
ajsts-5382	204	10	,	,	PUNCT
ajsts-5382	204	11	c.	c.	PROPN
ajsts-5382	204	12	,	,	PUNCT
ajsts-5382	204	13	zhang	zhang	PROPN
ajsts-5382	204	14	,	,	PUNCT
ajsts-5382	204	15	b.	b.	PROPN
ajsts-5382	204	16	,	,	PUNCT
ajsts-5382	204	17	cao	cao	PROPN
ajsts-5382	204	18	,	,	PUNCT
ajsts-5382	204	19	l.	l.	PROPN
ajsts-5382	204	20	,	,	PUNCT
ajsts-5382	204	21	ye	ye	PROPN
ajsts-5382	204	22	,	,	PUNCT
ajsts-5382	204	23	q.	q.	PROPN
ajsts-5382	204	24	,	,	PUNCT
ajsts-5382	204	25	huang	huang	PROPN
ajsts-5382	204	26	,	,	PUNCT
ajsts-5382	204	27	f.	f.	PROPN
ajsts-5382	204	28	,	,	PUNCT
ajsts-5382	204	29	&	&	CCONJ
ajsts-5382	204	30	doermann	doermann	PROPN
ajsts-5382	204	31	,	,	PUNCT
ajsts-5382	204	32	d.	d.	PROPN
ajsts-5382	204	33	(	(	PUNCT
ajsts-5382	204	34	2019	2019	NUM
ajsts-5382	204	35	)	)	PUNCT
ajsts-5382	204	36	.	.	PUNCT
ajsts-5382	205	1	towards	towards	ADP
ajsts-5382	205	2	optimal	optimal	ADJ
ajsts-5382	205	3	structured	structured	ADJ
ajsts-5382	205	4	cnn	cnn	PROPN
ajsts-5382	205	5	pruning	prune	VERB
ajsts-5382	205	6	via	via	ADP
ajsts-5382	205	7	generative	generative	ADJ
ajsts-5382	205	8	adversarial	adversarial	ADJ
ajsts-5382	205	9	learning	learning	NOUN
ajsts-5382	205	10	.	.	PUNCT
ajsts-5382	206	1	in	in	ADP
ajsts-5382	206	2	proceedings	proceeding	NOUN
ajsts-5382	206	3	of	of	ADP
ajsts-5382	206	4	the	the	DET
ajsts-5382	206	5	ieee	ieee	NOUN
ajsts-5382	206	6	/	/	SYM
ajsts-5382	206	7	cvf	cvf	NOUN
ajsts-5382	206	8	conference	conference	NOUN
ajsts-5382	206	9	on	on	ADP
ajsts-5382	206	10	computer	computer	NOUN
ajsts-5382	206	11	vision	vision	NOUN
ajsts-5382	206	12	and	and	CCONJ
ajsts-5382	206	13	pattern	pattern	NOUN
ajsts-5382	206	14	recognition	recognition	NOUN
ajsts-5382	206	15	(	(	PUNCT
ajsts-5382	206	16	pp	pp	ADJ
ajsts-5382	206	17	.	.	PUNCT
ajsts-5382	206	18	2790–2799	2790–2799	NUM
ajsts-5382	206	19	)	)	PUNCT
ajsts-5382	206	20	.	.	PUNCT
ajsts-5382	207	1	ieee	ieee	PROPN
ajsts-5382	207	2	.	.	PUNCT
ajsts-5382	208	1	nam	nam	PROPN
ajsts-5382	208	2	,	,	PUNCT
ajsts-5382	208	3	h.	h.	PROPN
ajsts-5382	208	4	,	,	PUNCT
ajsts-5382	208	5	ha	ha	INTJ
ajsts-5382	208	6	,	,	PUNCT
ajsts-5382	208	7	j.	j.	PROPN
ajsts-5382	208	8	w.	w.	PROPN
ajsts-5382	208	9	,	,	PUNCT
ajsts-5382	208	10	&	&	CCONJ
ajsts-5382	208	11	kim	kim	PROPN
ajsts-5382	208	12	,	,	PUNCT
ajsts-5382	208	13	j.	j.	PROPN
ajsts-5382	208	14	(	(	PUNCT
ajsts-5382	208	15	2017	2017	NUM
ajsts-5382	208	16	)	)	PUNCT
ajsts-5382	208	17	.	.	PUNCT
ajsts-5382	209	1	dual	dual	ADJ
ajsts-5382	209	2	attention	attention	NOUN
ajsts-5382	209	3	networks	network	NOUN
ajsts-5382	209	4	for	for	ADP
ajsts-5382	209	5	multimodal	multimodal	NOUN
ajsts-5382	209	6	reasoning	reasoning	NOUN
ajsts-5382	209	7	and	and	CCONJ
ajsts-5382	209	8	matching	matching	NOUN
ajsts-5382	209	9	.	.	PUNCT
ajsts-5382	210	1	in	in	ADP
ajsts-5382	210	2	proceedings	proceeding	NOUN
ajsts-5382	210	3	of	of	ADP
ajsts-5382	210	4	the	the	DET
ajsts-5382	210	5	ieee	ieee	NOUN
ajsts-5382	210	6	conference	conference	NOUN
ajsts-5382	210	7	on	on	ADP
ajsts-5382	210	8	computer	computer	NOUN
ajsts-5382	210	9	vision	vision	NOUN
ajsts-5382	210	10	and	and	CCONJ
ajsts-5382	210	11	pattern	pattern	NOUN
ajsts-5382	210	12	recognition	recognition	NOUN
ajsts-5382	210	13	(	(	PUNCT
ajsts-5382	210	14	pp	pp	ADJ
ajsts-5382	210	15	.	.	PUNCT
ajsts-5382	211	1	299–307	299–307	NUM
ajsts-5382	211	2	)	)	PUNCT
ajsts-5382	211	3	.	.	PUNCT
ajsts-5382	212	1	ieee	ieee	PROPN
ajsts-5382	212	2	.	.	PUNCT
ajsts-5382	213	1	pham	pham	PROPN
ajsts-5382	213	2	,	,	PUNCT
ajsts-5382	213	3	t.	t.	PROPN
ajsts-5382	213	4	d.	d.	PROPN
ajsts-5382	213	5	(	(	PUNCT
ajsts-5382	213	6	2020	2020	NUM
ajsts-5382	213	7	)	)	PUNCT
ajsts-5382	213	8	.	.	PUNCT
ajsts-5382	214	1	a	a	DET
ajsts-5382	214	2	comprehensive	comprehensive	ADJ
ajsts-5382	214	3	study	study	NOUN
ajsts-5382	214	4	on	on	ADP
ajsts-5382	214	5	the	the	DET
ajsts-5382	214	6	classification	classification	NOUN
ajsts-5382	214	7	of	of	ADP
ajsts-5382	214	8	covid-19	covid-19	PROPN
ajsts-5382	214	9	on	on	ADP
ajsts-5382	214	10	computed	computed	ADJ
ajsts-5382	214	11	tomography	tomography	NOUN
ajsts-5382	214	12	with	with	ADP
ajsts-5382	214	13	pre	pre	ADJ
ajsts-5382	214	14	-	-	ADJ
ajsts-5382	214	15	trained	train	VERB
ajsts-5382	214	16	convolutional	convolutional	ADJ
ajsts-5382	214	17	neural	neural	ADJ
ajsts-5382	214	18	networks	network	NOUN
ajsts-5382	214	19	.	.	PUNCT
ajsts-5382	215	1	scientific	scientific	ADJ
ajsts-5382	215	2	reports	report	NOUN
ajsts-5382	215	3	,	,	PUNCT
ajsts-5382	215	4	10(1	10(1	NUM
ajsts-5382	215	5	)	)	PUNCT
ajsts-5382	215	6	,	,	PUNCT
ajsts-5382	215	7	1–8	1–8	X
ajsts-5382	215	8	.	.	PUNCT
ajsts-5382	215	9	roy	roy	PROPN
ajsts-5382	215	10	,	,	PUNCT
ajsts-5382	215	11	s.	s.	PROPN
ajsts-5382	215	12	k.	k.	PROPN
ajsts-5382	215	13	,	,	PUNCT
ajsts-5382	215	14	manna	manna	PROPN
ajsts-5382	215	15	,	,	PUNCT
ajsts-5382	215	16	s.	s.	PROPN
ajsts-5382	215	17	,	,	PUNCT
ajsts-5382	215	18	song	song	NOUN
ajsts-5382	215	19	,	,	PUNCT
ajsts-5382	215	20	t.	t.	PROPN
ajsts-5382	215	21	,	,	PUNCT
ajsts-5382	215	22	&	&	CCONJ
ajsts-5382	215	23	bruzzone	bruzzone	NOUN
ajsts-5382	215	24	,	,	PUNCT
ajsts-5382	215	25	l.	l.	PROPN
ajsts-5382	215	26	(	(	PUNCT
ajsts-5382	215	27	2020	2020	NUM
ajsts-5382	215	28	)	)	PUNCT
ajsts-5382	215	29	.	.	PUNCT
ajsts-5382	216	1	attention	attention	NOUN
ajsts-5382	216	2	-	-	PUNCT
ajsts-5382	216	3	based	base	VERB
ajsts-5382	216	4	adaptive	adaptive	ADJ
ajsts-5382	216	5	spectral	spectral	ADJ
ajsts-5382	216	6	-	-	PUNCT
ajsts-5382	216	7	spatial	spatial	ADJ
ajsts-5382	216	8	kernel	kernel	NOUN
ajsts-5382	216	9	resnet	resnet	NOUN
ajsts-5382	216	10	for	for	ADP
ajsts-5382	216	11	hyperspectral	hyperspectral	ADJ
ajsts-5382	216	12	image	image	NOUN
ajsts-5382	216	13	classification	classification	NOUN
ajsts-5382	216	14	.	.	PUNCT
ajsts-5382	217	1	ieee	ieee	NOUN
ajsts-5382	217	2	transactions	transaction	NOUN
ajsts-5382	217	3	on	on	ADP
ajsts-5382	217	4	geoscience	geoscience	NOUN
ajsts-5382	217	5	and	and	CCONJ
ajsts-5382	217	6	remote	remote	ADJ
ajsts-5382	217	7	sensing	sensing	NOUN
ajsts-5382	217	8	,	,	PUNCT
ajsts-5382	217	9	59(9	59(9	NUM
ajsts-5382	217	10	)	)	PUNCT
ajsts-5382	217	11	,	,	PUNCT
ajsts-5382	217	12	7831–7843	7831–7843	X
ajsts-5382	217	13	.	.	PUNCT
ajsts-5382	217	14	simonyan	simonyan	PROPN
ajsts-5382	217	15	,	,	PUNCT
ajsts-5382	217	16	k.	k.	PROPN
ajsts-5382	217	17	,	,	PUNCT
ajsts-5382	217	18	&	&	CCONJ
ajsts-5382	217	19	zisserman	zisserman	PROPN
ajsts-5382	217	20	,	,	PUNCT
ajsts-5382	217	21	a.	a.	NOUN
ajsts-5382	217	22	(	(	PUNCT
ajsts-5382	217	23	2014	2014	NUM
ajsts-5382	217	24	,	,	PUNCT
ajsts-5382	217	25	september	september	PROPN
ajsts-5382	217	26	4	4	NUM
ajsts-5382	217	27	)	)	PUNCT
ajsts-5382	217	28	.	.	PUNCT
ajsts-5382	218	1	very	very	ADV
ajsts-5382	218	2	deep	deep	ADJ
ajsts-5382	218	3	convolutional	convolutional	ADJ
ajsts-5382	218	4	networks	network	NOUN
ajsts-5382	218	5	for	for	ADP
ajsts-5382	218	6	large	large	ADJ
ajsts-5382	218	7	-	-	PUNCT
ajsts-5382	218	8	scale	scale	NOUN
ajsts-5382	218	9	image	image	NOUN
ajsts-5382	218	10	recognition	recognition	NOUN
ajsts-5382	218	11	.	.	PUNCT
ajsts-5382	219	1	arxiv	arxiv	PROPN
ajsts-5382	219	2	preprint	preprint	PROPN
ajsts-5382	219	3	arxiv:1409.1556	arxiv:1409.1556	NOUN
ajsts-5382	219	4	.	.	PUNCT
ajsts-5382	220	1	szegedy	szegedy	PROPN
ajsts-5382	220	2	,	,	PUNCT
ajsts-5382	220	3	c.	c.	PROPN
ajsts-5382	220	4	,	,	PUNCT
ajsts-5382	220	5	liu	liu	PROPN
ajsts-5382	220	6	,	,	PUNCT
ajsts-5382	220	7	w.	w.	PROPN
ajsts-5382	220	8	,	,	PUNCT
ajsts-5382	220	9	jia	jia	PROPN
ajsts-5382	220	10	,	,	PUNCT
ajsts-5382	220	11	y.	y.	PROPN
ajsts-5382	220	12	,	,	PUNCT
ajsts-5382	220	13	sermanet	sermanet	NOUN
ajsts-5382	220	14	,	,	PUNCT
ajsts-5382	220	15	p.	p.	PROPN
ajsts-5382	220	16	,	,	PUNCT
ajsts-5382	220	17	reed	reed	PROPN
ajsts-5382	220	18	,	,	PUNCT
ajsts-5382	220	19	s.	s.	PROPN
ajsts-5382	220	20	,	,	PUNCT
ajsts-5382	220	21	anguelov	anguelov	PROPN
ajsts-5382	220	22	,	,	PUNCT
ajsts-5382	220	23	d.	d.	PROPN
ajsts-5382	220	24	,	,	PUNCT
ajsts-5382	220	25	erhan	erhan	PROPN
ajsts-5382	220	26	,	,	PUNCT
ajsts-5382	220	27	d.	d.	PROPN
ajsts-5382	220	28	,	,	PUNCT
ajsts-5382	220	29	vanhoucke	vanhoucke	PROPN
ajsts-5382	220	30	,	,	PUNCT
ajsts-5382	220	31	v.	v.	ADV
ajsts-5382	220	32	,	,	PUNCT
ajsts-5382	220	33	&	&	CCONJ
ajsts-5382	220	34	rabinovich	rabinovich	PROPN
ajsts-5382	220	35	,	,	PUNCT
ajsts-5382	220	36	a.	a.	PROPN
ajsts-5382	220	37	(	(	PUNCT
ajsts-5382	220	38	2015	2015	NUM
ajsts-5382	220	39	)	)	PUNCT
ajsts-5382	220	40	.	.	PUNCT
ajsts-5382	221	1	going	go	VERB
ajsts-5382	221	2	deeper	deeply	ADV
ajsts-5382	221	3	with	with	ADP
ajsts-5382	221	4	convolutions	convolution	NOUN
ajsts-5382	221	5	.	.	PUNCT
ajsts-5382	222	1	in	in	ADP
ajsts-5382	222	2	proceedings	proceeding	NOUN
ajsts-5382	222	3	of	of	ADP
ajsts-5382	222	4	the	the	DET
ajsts-5382	222	5	ieee	ieee	NOUN
ajsts-5382	222	6	conference	conference	NOUN
ajsts-5382	222	7	on	on	ADP
ajsts-5382	222	8	computer	computer	NOUN
ajsts-5382	222	9	vision	vision	NOUN
ajsts-5382	222	10	and	and	CCONJ
ajsts-5382	222	11	pattern	pattern	NOUN
ajsts-5382	222	12	recognition	recognition	NOUN
ajsts-5382	222	13	(	(	PUNCT
ajsts-5382	222	14	pp	pp	ADJ
ajsts-5382	222	15	.	.	PUNCT
ajsts-5382	222	16	1–9	1–9	NUM
ajsts-5382	222	17	)	)	PUNCT
ajsts-5382	222	18	.	.	PUNCT
ajsts-5382	223	1	ieee	ieee	PROPN
ajsts-5382	223	2	.	.	PUNCT
ajsts-5382	224	1	tan	tan	PROPN
ajsts-5382	224	2	,	,	PUNCT
ajsts-5382	224	3	m.	m.	NOUN
ajsts-5382	224	4	,	,	PUNCT
ajsts-5382	224	5	&	&	CCONJ
ajsts-5382	224	6	le	le	PROPN
ajsts-5382	224	7	,	,	PUNCT
ajsts-5382	224	8	q.	q.	PROPN
ajsts-5382	224	9	(	(	PUNCT
ajsts-5382	224	10	2019	2019	NUM
ajsts-5382	224	11	,	,	PUNCT
ajsts-5382	224	12	may	may	AUX
ajsts-5382	224	13	24	24	NUM
ajsts-5382	224	14	)	)	PUNCT
ajsts-5382	224	15	.	.	PUNCT
ajsts-5382	225	1	efficientnet	efficientnet	PROPN
ajsts-5382	225	2	:	:	PUNCT
ajsts-5382	225	3	rethinking	rethink	VERB
ajsts-5382	225	4	model	model	NOUN
ajsts-5382	225	5	scaling	scale	VERB
ajsts-5382	225	6	for	for	ADP
ajsts-5382	225	7	convolutional	convolutional	ADJ
ajsts-5382	225	8	neural	neural	ADJ
ajsts-5382	225	9	networks	network	NOUN
ajsts-5382	225	10	.	.	PUNCT
ajsts-5382	226	1	in	in	ADP
ajsts-5382	226	2	international	international	ADJ
ajsts-5382	226	3	conference	conference	NOUN
ajsts-5382	226	4	on	on	ADP
ajsts-5382	226	5	machine	machine	NOUN
ajsts-5382	226	6	learning	learning	NOUN
ajsts-5382	226	7	(	(	PUNCT
ajsts-5382	226	8	pp	pp	ADJ
ajsts-5382	226	9	.	.	PUNCT
ajsts-5382	226	10	6105–6114	6105–6114	NUM
ajsts-5382	226	11	)	)	PUNCT
ajsts-5382	226	12	.	.	PUNCT
ajsts-5382	227	1	pmlr	pmlr	PROPN
ajsts-5382	227	2	.	.	PUNCT
ajsts-5382	228	1	tseng	tseng	PROPN
ajsts-5382	228	2	,	,	PUNCT
ajsts-5382	228	3	h.	h.	PROPN
ajsts-5382	228	4	y.	y.	PROPN
ajsts-5382	228	5	,	,	PUNCT
ajsts-5382	228	6	lee	lee	PROPN
ajsts-5382	228	7	,	,	PUNCT
ajsts-5382	228	8	h.	h.	PROPN
ajsts-5382	228	9	y.	y.	PROPN
ajsts-5382	228	10	,	,	PUNCT
ajsts-5382	228	11	huang	huang	PROPN
ajsts-5382	228	12	,	,	PUNCT
ajsts-5382	228	13	j.	j.	PROPN
ajsts-5382	228	14	b.	b.	PROPN
ajsts-5382	228	15	,	,	PUNCT
ajsts-5382	228	16	&	&	CCONJ
ajsts-5382	228	17	yang	yang	PROPN
ajsts-5382	228	18	,	,	PUNCT
ajsts-5382	228	19	m.	m.	PROPN
ajsts-5382	228	20	h.	h.	PROPN
ajsts-5382	228	21	(	(	PUNCT
ajsts-5382	228	22	2020	2020	NUM
ajsts-5382	228	23	)	)	PUNCT
ajsts-5382	228	24	.	.	PUNCT
ajsts-5382	229	1	cross	cross	ADJ
ajsts-5382	229	2	-	-	ADJ
ajsts-5382	229	3	domain	domain	ADJ
ajsts-5382	229	4	few	few	ADJ
ajsts-5382	229	5	-	-	PUNCT
ajsts-5382	229	6	shot	shot	NOUN
ajsts-5382	229	7	classification	classification	NOUN
ajsts-5382	229	8	via	via	ADP
ajsts-5382	229	9	learned	learn	VERB
ajsts-5382	229	10	feature	feature	NOUN
ajsts-5382	229	11	-	-	PUNCT
ajsts-5382	229	12	wise	wise	ADJ
ajsts-5382	229	13	transformation	transformation	NOUN
ajsts-5382	229	14	.	.	PUNCT
ajsts-5382	230	1	arxiv	arxiv	PROPN
ajsts-5382	230	2	preprint	preprint	VERB
ajsts-5382	230	3	arxiv:2001.08735	arxiv:2001.08735	NOUN
ajsts-5382	230	4	.	.	PUNCT
ajsts-5382	231	1	wang	wang	PROPN
ajsts-5382	231	2	,	,	PUNCT
ajsts-5382	231	3	z.	z.	PROPN
ajsts-5382	231	4	,	,	PUNCT
ajsts-5382	231	5	yu	yu	PROPN
ajsts-5382	231	6	,	,	PUNCT
ajsts-5382	231	7	z.	z.	PROPN
ajsts-5382	231	8	,	,	PUNCT
ajsts-5382	231	9	zhao	zhao	PROPN
ajsts-5382	231	10	,	,	PUNCT
ajsts-5382	231	11	c.	c.	PROPN
ajsts-5382	231	12	,	,	PUNCT
ajsts-5382	231	13	zhu	zhu	PROPN
ajsts-5382	231	14	,	,	PUNCT
ajsts-5382	231	15	x.	x.	PROPN
ajsts-5382	231	16	,	,	PUNCT
ajsts-5382	231	17	qin	qin	PROPN
ajsts-5382	231	18	,	,	PUNCT
ajsts-5382	231	19	y.	y.	PROPN
ajsts-5382	231	20	,	,	PUNCT
ajsts-5382	231	21	zhou	zhou	PROPN
ajsts-5382	231	22	,	,	PUNCT
ajsts-5382	231	23	q.	q.	PROPN
ajsts-5382	231	24	,	,	PUNCT
ajsts-5382	231	25	zhou	zhou	PROPN
ajsts-5382	231	26	,	,	PUNCT
ajsts-5382	231	27	f.	f.	PROPN
ajsts-5382	231	28	,	,	PUNCT
ajsts-5382	231	29	&	&	CCONJ
ajsts-5382	231	30	lei	lei	PROPN
ajsts-5382	231	31	,	,	PUNCT
ajsts-5382	231	32	z.	z.	PROPN
ajsts-5382	231	33	(	(	PUNCT
ajsts-5382	231	34	2020	2020	NUM
ajsts-5382	231	35	)	)	PUNCT
ajsts-5382	231	36	.	.	PUNCT
ajsts-5382	232	1	deep	deep	ADJ
ajsts-5382	232	2	spatial	spatial	ADJ
ajsts-5382	232	3	gradient	gradient	NOUN
ajsts-5382	232	4	and	and	CCONJ
ajsts-5382	232	5	temporal	temporal	ADJ
ajsts-5382	232	6	depth	depth	NOUN
ajsts-5382	232	7	learning	learning	NOUN
ajsts-5382	232	8	for	for	ADP
ajsts-5382	232	9	face	face	NOUN
ajsts-5382	232	10	anti	anti	ADJ
ajsts-5382	232	11	-	-	ADJ
ajsts-5382	232	12	spoofing	spoofing	ADJ
ajsts-5382	232	13	.	.	PUNCT
ajsts-5382	233	1	in	in	ADP
ajsts-5382	233	2	proceedings	proceeding	NOUN
ajsts-5382	233	3	of	of	ADP
ajsts-5382	233	4	the	the	DET
ajsts-5382	233	5	ieee	ieee	NOUN
ajsts-5382	233	6	/	/	SYM
ajsts-5382	233	7	cvf	cvf	NOUN
ajsts-5382	233	8	conference	conference	NOUN
ajsts-5382	233	9	on	on	ADP
ajsts-5382	233	10	computer	computer	NOUN
ajsts-5382	233	11	vision	vision	NOUN
ajsts-5382	233	12	and	and	CCONJ
ajsts-5382	233	13	pattern	pattern	NOUN
ajsts-5382	233	14	recognition	recognition	NOUN
ajsts-5382	233	15	(	(	PUNCT
ajsts-5382	233	16	pp	pp	ADJ
ajsts-5382	233	17	.	.	PUNCT
ajsts-5382	233	18	5042–5051	5042–5051	NUM
ajsts-5382	233	19	)	)	PUNCT
ajsts-5382	233	20	.	.	PUNCT
ajsts-5382	234	1	ieee	ieee	PROPN
ajsts-5382	234	2	.	.	PUNCT
ajsts-5382	235	1	xie	xie	PROPN
ajsts-5382	235	2	,	,	PUNCT
ajsts-5382	235	3	s.	s.	PROPN
ajsts-5382	235	4	,	,	PUNCT
ajsts-5382	235	5	girshick	girshick	PROPN
ajsts-5382	235	6	,	,	PUNCT
ajsts-5382	235	7	r.	r.	PROPN
ajsts-5382	235	8	,	,	PUNCT
ajsts-5382	235	9	dollár	dollár	NOUN
ajsts-5382	235	10	,	,	PUNCT
ajsts-5382	235	11	p.	p.	PROPN
ajsts-5382	235	12	,	,	PUNCT
ajsts-5382	235	13	tu	tu	PROPN
ajsts-5382	235	14	,	,	PUNCT
ajsts-5382	235	15	z.	z.	PROPN
ajsts-5382	235	16	,	,	PUNCT
ajsts-5382	235	17	&	&	CCONJ
ajsts-5382	235	18	he	he	PRON
ajsts-5382	235	19	,	,	PUNCT
ajsts-5382	235	20	k.	k.	PROPN
ajsts-5382	235	21	(	(	PUNCT
ajsts-5382	235	22	2017	2017	NUM
ajsts-5382	235	23	)	)	PUNCT
ajsts-5382	235	24	.	.	PUNCT
ajsts-5382	235	25	aggregated	aggregate	VERB
ajsts-5382	235	26	residual	residual	ADJ
ajsts-5382	235	27	transformations	transformation	NOUN
ajsts-5382	235	28	for	for	ADP
ajsts-5382	235	29	deep	deep	ADJ
ajsts-5382	235	30	neural	neural	ADJ
ajsts-5382	235	31	networks	network	NOUN
ajsts-5382	235	32	.	.	PUNCT
ajsts-5382	236	1	in	in	ADP
ajsts-5382	236	2	proceedings	proceeding	NOUN
ajsts-5382	236	3	of	of	ADP
ajsts-5382	236	4	the	the	DET
ajsts-5382	236	5	ieee	ieee	NOUN
ajsts-5382	236	6	conference	conference	NOUN
ajsts-5382	236	7	on	on	ADP
ajsts-5382	236	8	computer	computer	NOUN
ajsts-5382	236	9	vision	vision	NOUN
ajsts-5382	236	10	and	and	CCONJ
ajsts-5382	236	11	pattern	pattern	NOUN
ajsts-5382	236	12	recognition	recognition	NOUN
ajsts-5382	236	13	(	(	PUNCT
ajsts-5382	236	14	pp	pp	ADJ
ajsts-5382	236	15	.	.	PUNCT
ajsts-5382	236	16	1492–1500	1492–1500	NUM
ajsts-5382	236	17	)	)	PUNCT
ajsts-5382	236	18	.	.	PUNCT
ajsts-5382	237	1	ieee	ieee	PROPN
ajsts-5382	237	2	.	.	PUNCT
ajsts-5382	238	1	zagoruyko	zagoruyko	PROPN
ajsts-5382	238	2	,	,	PUNCT
ajsts-5382	238	3	s.	s.	PROPN
ajsts-5382	238	4	,	,	PUNCT
ajsts-5382	238	5	&	&	CCONJ
ajsts-5382	238	6	komodakis	komodakis	PROPN
ajsts-5382	238	7	,	,	PUNCT
ajsts-5382	238	8	n.	n.	PROPN
ajsts-5382	238	9	(	(	PUNCT
ajsts-5382	238	10	2016	2016	NUM
ajsts-5382	238	11	,	,	PUNCT
ajsts-5382	238	12	may	may	AUX
ajsts-5382	238	13	23	23	NUM
ajsts-5382	238	14	)	)	PUNCT
ajsts-5382	238	15	.	.	PUNCT
ajsts-5382	239	1	wide	wide	ADJ
ajsts-5382	239	2	residual	residual	ADJ
ajsts-5382	239	3	networks	network	NOUN
ajsts-5382	239	4	.	.	PUNCT
ajsts-5382	240	1	arxiv	arxiv	PROPN
ajsts-5382	240	2	preprint	preprint	PROPN
ajsts-5382	240	3	arxiv:1605.07146	arxiv:1605.07146	PROPN
ajsts-5382	240	4	.	.	PUNCT
ajsts-5382	241	1	zerhouni	zerhouni	PROPN
ajsts-5382	241	2	,	,	PUNCT
ajsts-5382	241	3	e.	e.	PROPN
ajsts-5382	241	4	,	,	PUNCT
ajsts-5382	241	5	lányi	lányi	PROPN
ajsts-5382	241	6	,	,	PUNCT
ajsts-5382	241	7	d.	d.	PROPN
ajsts-5382	241	8	,	,	PUNCT
ajsts-5382	241	9	viana	viana	PROPN
ajsts-5382	241	10	,	,	PUNCT
ajsts-5382	241	11	m.	m.	NOUN
ajsts-5382	241	12	,	,	PUNCT
ajsts-5382	241	13	&	&	CCONJ
ajsts-5382	241	14	gabrani	gabrani	PROPN
ajsts-5382	241	15	,	,	PUNCT
ajsts-5382	241	16	m.	m.	NOUN
ajsts-5382	241	17	(	(	PUNCT
ajsts-5382	241	18	2017	2017	NUM
ajsts-5382	241	19	,	,	PUNCT
ajsts-5382	241	20	april	april	PROPN
ajsts-5382	241	21	18	18	NUM
ajsts-5382	241	22	)	)	PUNCT
ajsts-5382	241	23	.	.	PUNCT
ajsts-5382	242	1	wide	wide	ADJ
ajsts-5382	242	2	residual	residual	ADJ
ajsts-5382	242	3	networks	network	NOUN
ajsts-5382	242	4	for	for	ADP
ajsts-5382	242	5	mitosis	mitosis	NOUN
ajsts-5382	242	6	detection	detection	NOUN
ajsts-5382	242	7	.	.	PUNCT
ajsts-5382	243	1	in	in	ADP
ajsts-5382	243	2	2017	2017	NUM
ajsts-5382	243	3	ieee	ieee	NOUN
ajsts-5382	243	4	14th	14th	ADJ
ajsts-5382	243	5	international	international	ADJ
ajsts-5382	243	6	symposium	symposium	NOUN
ajsts-5382	243	7	on	on	ADP
ajsts-5382	243	8	biomedical	biomedical	ADJ
ajsts-5382	243	9	imaging	imaging	NOUN
ajsts-5382	243	10	(	(	PUNCT
ajsts-5382	243	11	isbi	isbi	NOUN
ajsts-5382	243	12	)	)	PUNCT
ajsts-5382	243	13	(	(	PUNCT
ajsts-5382	243	14	pp	pp	ADP
ajsts-5382	243	15	.	.	PUNCT
ajsts-5382	244	1	924–928	924–928	NUM
ajsts-5382	244	2	)	)	PUNCT
ajsts-5382	244	3	.	.	PUNCT
ajsts-5382	245	1	ieee	ieee	PROPN
ajsts-5382	245	2	.	.	PUNCT
ajsts-5382	246	1	zhang	zhang	PROPN
ajsts-5382	246	2	,	,	PUNCT
ajsts-5382	246	3	h.	h.	PROPN
ajsts-5382	246	4	,	,	PUNCT
ajsts-5382	246	5	wu	wu	PROPN
ajsts-5382	246	6	,	,	PUNCT
ajsts-5382	246	7	c.	c.	PROPN
ajsts-5382	246	8	,	,	PUNCT
ajsts-5382	246	9	zhang	zhang	PROPN
ajsts-5382	246	10	,	,	PUNCT
ajsts-5382	246	11	z.	z.	PROPN
ajsts-5382	246	12	,	,	PUNCT
ajsts-5382	246	13	zhu	zhu	PROPN
ajsts-5382	246	14	,	,	PUNCT
ajsts-5382	246	15	y.	y.	PROPN
ajsts-5382	246	16	,	,	PUNCT
ajsts-5382	246	17	lin	lin	PROPN
ajsts-5382	246	18	,	,	PUNCT
ajsts-5382	246	19	h.	h.	PROPN
ajsts-5382	246	20	,	,	PUNCT
ajsts-5382	246	21	zhang	zhang	PROPN
ajsts-5382	246	22	,	,	PUNCT
ajsts-5382	246	23	z.	z.	PROPN
ajsts-5382	246	24	,	,	PUNCT
ajsts-5382	246	25	sun	sun	PROPN
ajsts-5382	246	26	,	,	PUNCT
ajsts-5382	246	27	y.	y.	PROPN
ajsts-5382	246	28	,	,	PUNCT
ajsts-5382	246	29	he	he	PRON
ajsts-5382	246	30	,	,	PUNCT
ajsts-5382	246	31	t.	t.	PROPN
ajsts-5382	246	32	,	,	PUNCT
ajsts-5382	246	33	mueller	mueller	PROPN
ajsts-5382	246	34	,	,	PUNCT
ajsts-5382	246	35	j.	j.	PROPN
ajsts-5382	246	36	,	,	PUNCT
ajsts-5382	246	37	manmatha	manmatha	NOUN
ajsts-5382	246	38	,	,	PUNCT
ajsts-5382	246	39	r.	r.	PROPN
ajsts-5382	246	40	,	,	PUNCT
ajsts-5382	246	41	&	&	CCONJ
ajsts-5382	246	42	li	li	PROPN
ajsts-5382	246	43	,	,	PUNCT
ajsts-5382	246	44	m.	m.	NOUN
ajsts-5382	246	45	(	(	PUNCT
ajsts-5382	246	46	2022	2022	NUM
ajsts-5382	246	47	)	)	PUNCT
ajsts-5382	246	48	.	.	PUNCT
ajsts-5382	247	1	resnest	resnest	NOUN
ajsts-5382	247	2	:	:	PUNCT
ajsts-5382	247	3	split	split	ADJ
ajsts-5382	247	4	-	-	PUNCT
ajsts-5382	247	5	attention	attention	NOUN
ajsts-5382	247	6	networks	network	NOUN
ajsts-5382	247	7	.	.	PUNCT
ajsts-5382	248	1	in	in	ADP
ajsts-5382	248	2	proceedings	proceeding	NOUN
ajsts-5382	248	3	of	of	ADP
ajsts-5382	248	4	the	the	DET
ajsts-5382	248	5	ieee	ieee	NOUN
ajsts-5382	248	6	/	/	SYM
ajsts-5382	248	7	cvf	cvf	NOUN
ajsts-5382	248	8	conference	conference	NOUN
ajsts-5382	248	9	on	on	ADP
ajsts-5382	248	10	computer	computer	NOUN
ajsts-5382	248	11	vision	vision	NOUN
ajsts-5382	248	12	and	and	CCONJ
ajsts-5382	248	13	pattern	pattern	NOUN
ajsts-5382	248	14	recognition	recognition	NOUN
ajsts-5382	248	15	(	(	PUNCT
ajsts-5382	248	16	pp	pp	ADJ
ajsts-5382	248	17	.	.	PUNCT
ajsts-5382	249	1	2736–2746	2736–2746	NUM
ajsts-5382	249	2	)	)	PUNCT
ajsts-5382	249	3	.	.	PUNCT
ajsts-5382	250	1	ieee	ieee	PROPN
ajsts-5382	250	2	.	.	PUNCT
ajsts-5382	251	1	zhang	zhang	PROPN
ajsts-5382	251	2	,	,	PUNCT
ajsts-5382	251	3	k.	k.	PROPN
ajsts-5382	251	4	,	,	PUNCT
ajsts-5382	251	5	sun	sun	PROPN
ajsts-5382	251	6	,	,	PUNCT
ajsts-5382	251	7	m.	m.	NOUN
ajsts-5382	251	8	,	,	PUNCT
ajsts-5382	251	9	han	han	PROPN
ajsts-5382	251	10	,	,	PUNCT
ajsts-5382	251	11	t.	t.	PROPN
ajsts-5382	251	12	x.	x.	PROPN
ajsts-5382	251	13	,	,	PUNCT
ajsts-5382	251	14	yuan	yuan	PROPN
ajsts-5382	251	15	,	,	PUNCT
ajsts-5382	251	16	x.	x.	PROPN
ajsts-5382	251	17	,	,	PUNCT
ajsts-5382	251	18	guo	guo	PROPN
ajsts-5382	251	19	,	,	PUNCT
ajsts-5382	251	20	l.	l.	PROPN
ajsts-5382	251	21	,	,	PUNCT
ajsts-5382	251	22	&	&	CCONJ
ajsts-5382	251	23	liu	liu	PROPN
ajsts-5382	251	24	,	,	PUNCT
ajsts-5382	251	25	t.	t.	PROPN
ajsts-5382	251	26	(	(	PUNCT
ajsts-5382	251	27	2017	2017	NUM
ajsts-5382	251	28	)	)	PUNCT
ajsts-5382	251	29	.	.	PUNCT
ajsts-5382	252	1	residual	residual	ADJ
ajsts-5382	252	2	networks	network	NOUN
ajsts-5382	252	3	of	of	ADP
ajsts-5382	252	4	residual	residual	ADJ
ajsts-5382	252	5	networks	network	NOUN
ajsts-5382	252	6	:	:	PUNCT
ajsts-5382	252	7	multilevel	multilevel	VERB
ajsts-5382	252	8	residual	residual	ADJ
ajsts-5382	252	9	networks	network	NOUN
ajsts-5382	252	10	.	.	PUNCT
ajsts-5382	253	1	ieee	ieee	NOUN
ajsts-5382	253	2	transactions	transaction	NOUN
ajsts-5382	253	3	on	on	ADP
ajsts-5382	253	4	circuits	circuit	NOUN
ajsts-5382	253	5	and	and	CCONJ
ajsts-5382	253	6	systems	system	NOUN
ajsts-5382	253	7	for	for	ADP
ajsts-5382	253	8	video	video	NOUN
ajsts-5382	253	9	technology	technology	NOUN
ajsts-5382	253	10	,	,	PUNCT
ajsts-5382	253	11	28(6	28(6	NUM
ajsts-5382	253	12	)	)	PUNCT
ajsts-5382	253	13	,	,	PUNCT
ajsts-5382	253	14	1303–1314	1303–1314	NUM
ajsts-5382	253	15	.	.	PUNCT
ajsts-5382	254	1	zhong	zhong	PROPN
ajsts-5382	254	2	,	,	PUNCT
ajsts-5382	254	3	x.	x.	PROPN
ajsts-5382	254	4	,	,	PUNCT
ajsts-5382	254	5	gong	gong	PROPN
ajsts-5382	254	6	,	,	PUNCT
ajsts-5382	254	7	o.	o.	PROPN
ajsts-5382	254	8	,	,	PUNCT
ajsts-5382	254	9	huang	huang	PROPN
ajsts-5382	254	10	,	,	PUNCT
ajsts-5382	254	11	w.	w.	PROPN
ajsts-5382	254	12	,	,	PUNCT
ajsts-5382	254	13	li	li	PROPN
ajsts-5382	254	14	,	,	PUNCT
ajsts-5382	254	15	l.	l.	PROPN
ajsts-5382	254	16	,	,	PUNCT
ajsts-5382	254	17	&	&	CCONJ
ajsts-5382	254	18	xia	xia	PROPN
ajsts-5382	254	19	,	,	PUNCT
ajsts-5382	254	20	h.	h.	PROPN
ajsts-5382	254	21	(	(	PUNCT
ajsts-5382	254	22	2019	2019	NUM
ajsts-5382	254	23	,	,	PUNCT
ajsts-5382	254	24	september	september	PROPN
ajsts-5382	254	25	22	22	NUM
ajsts-5382	254	26	)	)	PUNCT
ajsts-5382	254	27	.	.	PUNCT
ajsts-5382	255	1	squeeze	squeeze	NOUN
ajsts-5382	255	2	-	-	PUNCT
ajsts-5382	255	3	and	and	CCONJ
ajsts-5382	255	4	-	-	PUNCT
ajsts-5382	255	5	excitation	excitation	NOUN
ajsts-5382	255	6	wide	wide	ADJ
ajsts-5382	255	7	residual	residual	ADJ
ajsts-5382	255	8	networks	network	NOUN
ajsts-5382	255	9	in	in	ADP
ajsts-5382	255	10	image	image	NOUN
ajsts-5382	255	11	classification	classification	NOUN
ajsts-5382	255	12	.	.	PUNCT
ajsts-5382	256	1	in	in	ADP
ajsts-5382	256	2	2019	2019	NUM
ajsts-5382	256	3	ieee	ieee	NOUN
ajsts-5382	256	4	international	international	ADJ
ajsts-5382	256	5	conference	conference	NOUN
ajsts-5382	256	6	on	on	ADP
ajsts-5382	256	7	image	image	NOUN
ajsts-5382	256	8	processing	processing	NOUN
ajsts-5382	256	9	(	(	PUNCT
ajsts-5382	256	10	icip	icip	PROPN
ajsts-5382	256	11	)	)	PUNCT
ajsts-5382	256	12	(	(	PUNCT
ajsts-5382	256	13	pp	pp	ADV
ajsts-5382	256	14	.	.	PUNCT
ajsts-5382	257	1	395–399	395–399	NUM
ajsts-5382	257	2	)	)	PUNCT
ajsts-5382	257	3	.	.	PUNCT
ajsts-5382	258	1	ieee	ieee	PROPN
ajsts-5382	258	2	.	.	PUNCT