id	sid	tid	token	lemma	pos
cord-024346-shauvo3j	1	1	key	key	JJ
cord-024346-shauvo3j	2	1	:	:	:
cord-024346-shauvo3j	2	2	cord-024346-shauvo3j	cord-024346-shauvo3j	NNS
cord-024346-shauvo3j	2	3	authors	author	NNS
cord-024346-shauvo3j	2	4	:	:	:
cord-024346-shauvo3j	2	5	Kruglov	Kruglov	NNP
cord-024346-shauvo3j	2	6	,	,	,
cord-024346-shauvo3j	2	7	Vasiliy	Vasiliy	NNP
cord-024346-shauvo3j	2	8	N.	N.	NNP
cord-024346-shauvo3j	2	9	title	title	NN
cord-024346-shauvo3j	2	10	:	:	:
cord-024346-shauvo3j	3	1	Using	use	VBG
cord-024346-shauvo3j	3	2	Open	Open	NNP
cord-024346-shauvo3j	3	3	Source	Source	NNP
cord-024346-shauvo3j	3	4	Libraries	Libraries	NNPS
cord-024346-shauvo3j	3	5	in	in	IN
cord-024346-shauvo3j	3	6	the	the	DT
cord-024346-shauvo3j	3	7	Development	Development	NNP
cord-024346-shauvo3j	3	8	of	of	IN
cord-024346-shauvo3j	3	9	Control	Control	NNP
cord-024346-shauvo3j	3	10	Systems	Systems	NNPS
cord-024346-shauvo3j	3	11	Based	Based	NNP
cord-024346-shauvo3j	3	12	on	on	IN
cord-024346-shauvo3j	3	13	Machine	Machine	NNP
cord-024346-shauvo3j	3	14	Vision	Vision	NNP
cord-024346-shauvo3j	3	15	date	date	NN
cord-024346-shauvo3j	4	1	:	:	:
cord-024346-shauvo3j	4	2	2020	2020	CD
cord-024346-shauvo3j	4	3	-	-	HYPH
cord-024346-shauvo3j	4	4	05	05	CD
cord-024346-shauvo3j	4	5	-	-	HYPH
cord-024346-shauvo3j	4	6	05	05	CD
cord-024346-shauvo3j	4	7	journal	journal	NN
cord-024346-shauvo3j	4	8	:	:	:
cord-024346-shauvo3j	5	1	Open	open	JJ
cord-024346-shauvo3j	5	2	Source	Source	NNP
cord-024346-shauvo3j	5	3	Systems	Systems	NNPS
cord-024346-shauvo3j	5	4	DOI	doi	NN
cord-024346-shauvo3j	5	5	:	:	:
cord-024346-shauvo3j	5	6	10.1007/978	10.1007/978	CD
cord-024346-shauvo3j	5	7	-	-	HYPH
cord-024346-shauvo3j	5	8	3	3	CD
cord-024346-shauvo3j	5	9	-	-	HYPH
cord-024346-shauvo3j	5	10	030	030	CD
cord-024346-shauvo3j	5	11	-	-	HYPH
cord-024346-shauvo3j	5	12	47240	47240	CD
cord-024346-shauvo3j	5	13	-	-	HYPH
cord-024346-shauvo3j	5	14	5_7	5_7	CD
cord-024346-shauvo3j	5	15	sha	sha	NNP
cord-024346-shauvo3j	5	16	:	:	:
cord-024346-shauvo3j	5	17	cec99e62392e9aff0762330145bbc64c4055250b	cec99e62392e9aff0762330145bbc64c4055250b	ADD
cord-024346-shauvo3j	5	18	doc_id	doc_id	CD
cord-024346-shauvo3j	5	19	:	:	:
cord-024346-shauvo3j	5	20	24346	24346	CD
cord-024346-shauvo3j	5	21	cord_uid	cord_uid	FW
cord-024346-shauvo3j	5	22	:	:	:
cord-024346-shauvo3j	6	1	shauvo3j	shauvo3j	NNP
cord-024346-shauvo3j	7	1	The	the	DT
cord-024346-shauvo3j	7	2	possibility	possibility	NN
cord-024346-shauvo3j	7	3	of	of	IN
cord-024346-shauvo3j	7	4	the	the	DT
cord-024346-shauvo3j	7	5	boundaries	boundary	NNS
cord-024346-shauvo3j	7	6	detection	detection	NN
cord-024346-shauvo3j	7	7	in	in	IN
cord-024346-shauvo3j	7	8	the	the	DT
cord-024346-shauvo3j	7	9	images	image	NNS
cord-024346-shauvo3j	7	10	of	of	IN
cord-024346-shauvo3j	7	11	crushed	crush	VBN
cord-024346-shauvo3j	7	12	ore	ore	NN
cord-024346-shauvo3j	7	13	particles	particle	NNS
cord-024346-shauvo3j	7	14	using	use	VBG
cord-024346-shauvo3j	7	15	a	a	DT
cord-024346-shauvo3j	7	16	convolutional	convolutional	JJ
cord-024346-shauvo3j	7	17	neural	neural	JJ
cord-024346-shauvo3j	7	18	network	network	NN
cord-024346-shauvo3j	7	19	is	be	VBZ
cord-024346-shauvo3j	7	20	analyzed	analyze	VBN
cord-024346-shauvo3j	7	21	.	.	.
cord-024346-shauvo3j	8	1	The	the	DT
cord-024346-shauvo3j	8	2	structure	structure	NN
cord-024346-shauvo3j	8	3	of	of	IN
cord-024346-shauvo3j	8	4	the	the	DT
cord-024346-shauvo3j	8	5	neural	neural	JJ
cord-024346-shauvo3j	8	6	network	network	NN
cord-024346-shauvo3j	8	7	is	be	VBZ
cord-024346-shauvo3j	8	8	given	give	VBN
cord-024346-shauvo3j	8	9	.	.	.
cord-024346-shauvo3j	9	1	The	the	DT
cord-024346-shauvo3j	9	2	construction	construction	NN
cord-024346-shauvo3j	9	3	of	of	IN
cord-024346-shauvo3j	9	4	training	training	NN
cord-024346-shauvo3j	9	5	and	and	CC
cord-024346-shauvo3j	9	6	test	test	NN
cord-024346-shauvo3j	9	7	datasets	dataset	NNS
cord-024346-shauvo3j	9	8	of	of	IN
cord-024346-shauvo3j	9	9	ore	ore	NN
cord-024346-shauvo3j	9	10	particle	particle	NN
cord-024346-shauvo3j	9	11	images	image	NNS
cord-024346-shauvo3j	9	12	is	be	VBZ
cord-024346-shauvo3j	9	13	described	describe	VBN
cord-024346-shauvo3j	9	14	.	.	.
cord-024346-shauvo3j	10	1	Various	various	JJ
cord-024346-shauvo3j	10	2	modifications	modification	NNS
cord-024346-shauvo3j	10	3	of	of	IN
cord-024346-shauvo3j	10	4	the	the	DT
cord-024346-shauvo3j	10	5	underlying	underlying	JJ
cord-024346-shauvo3j	10	6	neural	neural	JJ
cord-024346-shauvo3j	10	7	network	network	NN
cord-024346-shauvo3j	10	8	have	have	VBP
cord-024346-shauvo3j	10	9	been	be	VBN
cord-024346-shauvo3j	10	10	investigated	investigate	VBN
cord-024346-shauvo3j	10	11	.	.	.
cord-024346-shauvo3j	11	1	Experimental	experimental	JJ
cord-024346-shauvo3j	11	2	results	result	NNS
cord-024346-shauvo3j	11	3	are	be	VBP
cord-024346-shauvo3j	11	4	presented	present	VBN
cord-024346-shauvo3j	11	5	.	.	.
cord-024346-shauvo3j	12	1	When	when	WRB
cord-024346-shauvo3j	12	2	processing	process	VBG
cord-024346-shauvo3j	12	3	crushed	crush	VBN
cord-024346-shauvo3j	12	4	ore	ore	NN
cord-024346-shauvo3j	12	5	mass	mass	NN
cord-024346-shauvo3j	12	6	at	at	IN
cord-024346-shauvo3j	12	7	ore	ore	NN
cord-024346-shauvo3j	12	8	mining	mining	NN
cord-024346-shauvo3j	12	9	and	and	CC
cord-024346-shauvo3j	12	10	processing	processing	NN
cord-024346-shauvo3j	12	11	enterprises	enterprise	NNS
cord-024346-shauvo3j	12	12	,	,	,
cord-024346-shauvo3j	12	13	one	one	CD
cord-024346-shauvo3j	12	14	of	of	IN
cord-024346-shauvo3j	12	15	the	the	DT
cord-024346-shauvo3j	12	16	main	main	JJ
cord-024346-shauvo3j	12	17	indicators	indicator	NNS
cord-024346-shauvo3j	12	18	of	of	IN
cord-024346-shauvo3j	12	19	the	the	DT
cord-024346-shauvo3j	12	20	quality	quality	NN
cord-024346-shauvo3j	12	21	of	of	IN
cord-024346-shauvo3j	12	22	work	work	NN
cord-024346-shauvo3j	12	23	of	of	IN
cord-024346-shauvo3j	12	24	both	both	DT
cord-024346-shauvo3j	12	25	equipment	equipment	NN
cord-024346-shauvo3j	12	26	and	and	CC
cord-024346-shauvo3j	12	27	personnel	personnel	NNS
cord-024346-shauvo3j	12	28	is	be	VBZ
cord-024346-shauvo3j	12	29	the	the	DT
cord-024346-shauvo3j	12	30	assessment	assessment	NN
cord-024346-shauvo3j	12	31	of	of	IN
cord-024346-shauvo3j	12	32	the	the	DT
cord-024346-shauvo3j	12	33	size	size	NN
cord-024346-shauvo3j	12	34	of	of	IN
cord-024346-shauvo3j	12	35	the	the	DT
cord-024346-shauvo3j	12	36	crushed	crush	VBN
cord-024346-shauvo3j	12	37	material	material	NN
cord-024346-shauvo3j	12	38	at	at	IN
cord-024346-shauvo3j	12	39	each	each	DT
cord-024346-shauvo3j	12	40	stage	stage	NN
cord-024346-shauvo3j	12	41	of	of	IN
cord-024346-shauvo3j	12	42	the	the	DT
cord-024346-shauvo3j	12	43	technological	technological	JJ
cord-024346-shauvo3j	12	44	process	process	NN
cord-024346-shauvo3j	12	45	.	.	.
cord-024346-shauvo3j	13	1	This	this	DT
cord-024346-shauvo3j	13	2	is	be	VBZ
cord-024346-shauvo3j	13	3	due	due	JJ
cord-024346-shauvo3j	13	4	to	to	IN
cord-024346-shauvo3j	13	5	the	the	DT
cord-024346-shauvo3j	13	6	need	need	NN
cord-024346-shauvo3j	13	7	to	to	TO
cord-024346-shauvo3j	13	8	reduce	reduce	VB
cord-024346-shauvo3j	13	9	material	material	NN
cord-024346-shauvo3j	13	10	and	and	CC
cord-024346-shauvo3j	13	11	energy	energy	NN
cord-024346-shauvo3j	13	12	costs	cost	NNS
cord-024346-shauvo3j	13	13	for	for	IN
cord-024346-shauvo3j	13	14	the	the	DT
cord-024346-shauvo3j	13	15	production	production	NN
cord-024346-shauvo3j	13	16	of	of	IN
cord-024346-shauvo3j	13	17	a	a	DT
cord-024346-shauvo3j	13	18	product	product	NN
cord-024346-shauvo3j	13	19	unit	unit	NN
cord-024346-shauvo3j	13	20	manufactured	manufacture	VBN
cord-024346-shauvo3j	13	21	by	by	IN
cord-024346-shauvo3j	13	22	the	the	DT
cord-024346-shauvo3j	13	23	plant	plant	NN
cord-024346-shauvo3j	13	24	:	:	:
cord-024346-shauvo3j	13	25	concentrate	concentrate	VB
cord-024346-shauvo3j	13	26	,	,	,
cord-024346-shauvo3j	13	27	sinter	sinter	NN
cord-024346-shauvo3j	13	28	or	or	CC
cord-024346-shauvo3j	13	29	pellets	pellet	NNS
cord-024346-shauvo3j	13	30	.	.	.
cord-024346-shauvo3j	14	1	The	the	DT
cord-024346-shauvo3j	14	2	traditional	traditional	JJ
cord-024346-shauvo3j	14	3	approach	approach	NN
cord-024346-shauvo3j	14	4	to	to	IN
cord-024346-shauvo3j	14	5	the	the	DT
cord-024346-shauvo3j	14	6	problem	problem	NN
cord-024346-shauvo3j	14	7	of	of	IN
cord-024346-shauvo3j	14	8	evaluating	evaluate	VBG
cord-024346-shauvo3j	14	9	the	the	DT
cord-024346-shauvo3j	14	10	size	size	NN
cord-024346-shauvo3j	14	11	of	of	IN
cord-024346-shauvo3j	14	12	crushed	crush	VBN
cord-024346-shauvo3j	14	13	material	material	NN
cord-024346-shauvo3j	14	14	is	be	VBZ
cord-024346-shauvo3j	14	15	manual	manual	JJ
cord-024346-shauvo3j	14	16	sampling	sampling	NN
cord-024346-shauvo3j	14	17	with	with	IN
cord-024346-shauvo3j	14	18	subsequent	subsequent	JJ
cord-024346-shauvo3j	14	19	sieving	sieving	NN
cord-024346-shauvo3j	14	20	with	with	IN
cord-024346-shauvo3j	14	21	sieves	sieve	NNS
cord-024346-shauvo3j	14	22	of	of	IN
cord-024346-shauvo3j	14	23	various	various	JJ
cord-024346-shauvo3j	14	24	sizes	size	NNS
cord-024346-shauvo3j	14	25	.	.	.
cord-024346-shauvo3j	15	1	The	the	DT
cord-024346-shauvo3j	15	2	determination	determination	NN
cord-024346-shauvo3j	15	3	of	of	IN
cord-024346-shauvo3j	15	4	the	the	DT
cord-024346-shauvo3j	15	5	grain	grain	NN
cord-024346-shauvo3j	15	6	-	-	HYPH
cord-024346-shauvo3j	15	7	size	size	NN
cord-024346-shauvo3j	15	8	distribution	distribution	NN
cord-024346-shauvo3j	15	9	of	of	IN
cord-024346-shauvo3j	15	10	the	the	DT
cord-024346-shauvo3j	15	11	crushed	crush	VBN
cord-024346-shauvo3j	15	12	material	material	NN
cord-024346-shauvo3j	15	13	in	in	IN
cord-024346-shauvo3j	15	14	this	this	DT
cord-024346-shauvo3j	15	15	way	way	NN
cord-024346-shauvo3j	15	16	entails	entail	VBZ
cord-024346-shauvo3j	15	17	a	a	DT
cord-024346-shauvo3j	15	18	number	number	NN
cord-024346-shauvo3j	15	19	of	of	IN
cord-024346-shauvo3j	15	20	negative	negative	JJ
cord-024346-shauvo3j	15	21	factors	factor	NNS
cord-024346-shauvo3j	15	22	:	:	:
cord-024346-shauvo3j	15	23	-the	-the	ADD
cord-024346-shauvo3j	15	24	complexity	complexity	NN
cord-024346-shauvo3j	15	25	of	of	IN
cord-024346-shauvo3j	15	26	the	the	DT
cord-024346-shauvo3j	15	27	measurement	measurement	NN
cord-024346-shauvo3j	15	28	process	process	NN
cord-024346-shauvo3j	15	29	;	;	:
cord-024346-shauvo3j	15	30	-the	-the	WDT
cord-024346-shauvo3j	15	31	inability	inability	NN
cord-024346-shauvo3j	15	32	to	to	TO
cord-024346-shauvo3j	15	33	conduct	conduct	VB
cord-024346-shauvo3j	15	34	objective	objective	JJ
cord-024346-shauvo3j	15	35	measurements	measurement	NNS
cord-024346-shauvo3j	15	36	with	with	IN
cord-024346-shauvo3j	15	37	sufficient	sufficient	JJ
cord-024346-shauvo3j	15	38	frequency	frequency	NN
cord-024346-shauvo3j	15	39	;	;	:
cord-024346-shauvo3j	15	40	-the	-the	ADD
cord-024346-shauvo3j	15	41	human	human	JJ
cord-024346-shauvo3j	15	42	error	error	NN
cord-024346-shauvo3j	15	43	factor	factor	NN
cord-024346-shauvo3j	15	44	at	at	IN
cord-024346-shauvo3j	15	45	the	the	DT
cord-024346-shauvo3j	15	46	stages	stage	NNS
cord-024346-shauvo3j	15	47	of	of	IN
cord-024346-shauvo3j	15	48	both	both	DT
cord-024346-shauvo3j	15	49	data	datum	NNS
cord-024346-shauvo3j	15	50	collection	collection	NN
cord-024346-shauvo3j	15	51	and	and	CC
cord-024346-shauvo3j	15	52	processing	processing	NN
cord-024346-shauvo3j	15	53	.	.	.
cord-024346-shauvo3j	16	1	These	these	DT
cord-024346-shauvo3j	16	2	shortcomings	shortcoming	NNS
cord-024346-shauvo3j	16	3	do	do	VBP
cord-024346-shauvo3j	16	4	not	not	RB
cord-024346-shauvo3j	16	5	allow	allow	VB
cord-024346-shauvo3j	16	6	you	-PRON-	PRP
cord-024346-shauvo3j	16	7	to	to	TO
cord-024346-shauvo3j	16	8	quickly	quickly	RB
cord-024346-shauvo3j	16	9	adjust	adjust	VB
cord-024346-shauvo3j	16	10	the	the	DT
cord-024346-shauvo3j	16	11	performance	performance	NN
cord-024346-shauvo3j	16	12	of	of	IN
cord-024346-shauvo3j	16	13	crushing	crush	VBG
cord-024346-shauvo3j	16	14	equipment	equipment	NN
cord-024346-shauvo3j	16	15	.	.	.
cord-024346-shauvo3j	17	1	The	the	DT
cord-024346-shauvo3j	17	2	need	need	NN
cord-024346-shauvo3j	17	3	for	for	IN
cord-024346-shauvo3j	17	4	obtaining	obtain	VBG
cord-024346-shauvo3j	17	5	data	datum	NNS
cord-024346-shauvo3j	17	6	on	on	IN
cord-024346-shauvo3j	17	7	the	the	DT
cord-024346-shauvo3j	17	8	coarseness	coarseness	NN
cord-024346-shauvo3j	17	9	of	of	IN
cord-024346-shauvo3j	17	10	crushed	crush	VBN
cord-024346-shauvo3j	17	11	material	material	NN
cord-024346-shauvo3j	17	12	in	in	IN
cord-024346-shauvo3j	17	13	real	real	JJ
cord-024346-shauvo3j	17	14	time	time	NN
cord-024346-shauvo3j	17	15	necessitated	necessitate	VBD
cord-024346-shauvo3j	17	16	the	the	DT
cord-024346-shauvo3j	17	17	creation	creation	NN
cord-024346-shauvo3j	17	18	of	of	IN
cord-024346-shauvo3j	17	19	devices	device	NNS
cord-024346-shauvo3j	17	20	for	for	IN
cord-024346-shauvo3j	17	21	in	in	IN
cord-024346-shauvo3j	17	22	situ	situ	NN
cord-024346-shauvo3j	17	23	assessment	assessment	NN
cord-024346-shauvo3j	17	24	of	of	IN
cord-024346-shauvo3j	17	25	parameters	parameter	NNS
cord-024346-shauvo3j	17	26	such	such	JJ
cord-024346-shauvo3j	17	27	as	as	IN
cord-024346-shauvo3j	17	28	the	the	DT
cord-024346-shauvo3j	17	29	grain	grain	NN
cord-024346-shauvo3j	17	30	-	-	HYPH
cord-024346-shauvo3j	17	31	size	size	NN
cord-024346-shauvo3j	17	32	distribution	distribution	NN
cord-024346-shauvo3j	17	33	of	of	IN
cord-024346-shauvo3j	17	34	ore	ore	NN
cord-024346-shauvo3j	17	35	particles	particle	NNS
cord-024346-shauvo3j	17	36	,	,	,
cord-024346-shauvo3j	17	37	weight	weight	NN
cord-024346-shauvo3j	17	38	-	-	HYPH
cord-024346-shauvo3j	17	39	average	average	JJ
cord-024346-shauvo3j	17	40	ore	ore	NN
cord-024346-shauvo3j	17	41	particle	particle	NN
cord-024346-shauvo3j	17	42	and	and	CC
cord-024346-shauvo3j	17	43	the	the	DT
cord-024346-shauvo3j	17	44	percentage	percentage	NN
cord-024346-shauvo3j	17	45	of	of	IN
cord-024346-shauvo3j	17	46	the	the	DT
cord-024346-shauvo3j	17	47	targeted	target	VBN
cord-024346-shauvo3j	17	48	class	class	NN
cord-024346-shauvo3j	17	49	.	.	.
cord-024346-shauvo3j	18	1	The	the	DT
cord-024346-shauvo3j	18	2	machine	machine	NN
cord-024346-shauvo3j	18	3	vision	vision	NN
cord-024346-shauvo3j	18	4	systems	system	NNS
cord-024346-shauvo3j	18	5	are	be	VBP
cord-024346-shauvo3j	18	6	able	able	JJ
cord-024346-shauvo3j	18	7	to	to	TO
cord-024346-shauvo3j	18	8	provide	provide	VB
cord-024346-shauvo3j	18	9	such	such	JJ
cord-024346-shauvo3j	18	10	functionality	functionality	NN
cord-024346-shauvo3j	18	11	.	.	.
cord-024346-shauvo3j	19	1	They	-PRON-	PRP
cord-024346-shauvo3j	19	2	have	have	VBP
cord-024346-shauvo3j	19	3	high	high	JJ
cord-024346-shauvo3j	19	4	reliability	reliability	NN
cord-024346-shauvo3j	19	5	,	,	,
cord-024346-shauvo3j	19	6	performance	performance	NN
cord-024346-shauvo3j	19	7	and	and	CC
cord-024346-shauvo3j	19	8	accuracy	accuracy	NN
cord-024346-shauvo3j	19	9	in	in	IN
cord-024346-shauvo3j	19	10	determining	determine	VBG
cord-024346-shauvo3j	19	11	the	the	DT
cord-024346-shauvo3j	19	12	geometric	geometric	JJ
cord-024346-shauvo3j	19	13	dimensions	dimension	NNS
cord-024346-shauvo3j	19	14	of	of	IN
cord-024346-shauvo3j	19	15	ore	ore	NN
cord-024346-shauvo3j	19	16	particles	particle	NNS
cord-024346-shauvo3j	19	17	.	.	.
cord-024346-shauvo3j	20	1	At	at	IN
cord-024346-shauvo3j	20	2	the	the	DT
cord-024346-shauvo3j	20	3	moment	moment	NN
cord-024346-shauvo3j	20	4	,	,	,
cord-024346-shauvo3j	20	5	several	several	JJ
cord-024346-shauvo3j	20	6	vision	vision	NN
cord-024346-shauvo3j	20	7	systems	system	NNS
cord-024346-shauvo3j	20	8	have	have	VBP
cord-024346-shauvo3j	20	9	been	be	VBN
cord-024346-shauvo3j	20	10	developed	develop	VBN
cord-024346-shauvo3j	20	11	and	and	CC
cord-024346-shauvo3j	20	12	implemented	implement	VBN
cord-024346-shauvo3j	20	13	for	for	IN
cord-024346-shauvo3j	20	14	the	the	DT
cord-024346-shauvo3j	20	15	operational	operational	JJ
cord-024346-shauvo3j	20	16	control	control	NN
cord-024346-shauvo3j	20	17	of	of	IN
cord-024346-shauvo3j	20	18	the	the	DT
cord-024346-shauvo3j	20	19	particle	particle	NN
cord-024346-shauvo3j	20	20	size	size	NN
cord-024346-shauvo3j	20	21	distribution	distribution	NN
cord-024346-shauvo3j	20	22	of	of	IN
cord-024346-shauvo3j	20	23	crushed	crush	VBN
cord-024346-shauvo3j	20	24	or	or	CC
cord-024346-shauvo3j	20	25	granular	granular	JJ
cord-024346-shauvo3j	20	26	material	material	NN
cord-024346-shauvo3j	20	27	.	.	.
cord-024346-shauvo3j	21	1	In	in	IN
cord-024346-shauvo3j	21	2	[	[	-LRB-
cord-024346-shauvo3j	21	3	9	9	CD
cord-024346-shauvo3j	21	4	]	]	-RRB-
cord-024346-shauvo3j	21	5	,	,	,
cord-024346-shauvo3j	21	6	a	a	DT
cord-024346-shauvo3j	21	7	brief	brief	JJ
cord-024346-shauvo3j	21	8	description	description	NN
cord-024346-shauvo3j	21	9	and	and	CC
cord-024346-shauvo3j	21	10	comparative	comparative	JJ
cord-024346-shauvo3j	21	11	analysis	analysis	NN
cord-024346-shauvo3j	21	12	of	of	IN
cord-024346-shauvo3j	21	13	such	such	JJ
cord-024346-shauvo3j	21	14	systems	system	NNS
cord-024346-shauvo3j	21	15	as	as	IN
cord-024346-shauvo3j	21	16	:	:	:
cord-024346-shauvo3j	21	17	SPLIT	split	VB
cord-024346-shauvo3j	21	18	,	,	,
cord-024346-shauvo3j	21	19	WIPFRAG	WIPFRAG	NNP
cord-024346-shauvo3j	21	20	,	,	,
cord-024346-shauvo3j	21	21	FRAGSCAN	FRAGSCAN	NNP
cord-024346-shauvo3j	21	22	,	,	,
cord-024346-shauvo3j	21	23	CIAS	CIAS	NNP
cord-024346-shauvo3j	21	24	,	,	,
cord-024346-shauvo3j	21	25	IPACS	IPACS	NNP
cord-024346-shauvo3j	21	26	,	,	,
cord-024346-shauvo3j	21	27	TUCIPS	TUCIPS	NNP
cord-024346-shauvo3j	21	28	is	be	VBZ
cord-024346-shauvo3j	21	29	given	give	VBN
cord-024346-shauvo3j	21	30	.	.	.
cord-024346-shauvo3j	22	1	Common	common	JJ
cord-024346-shauvo3j	22	2	to	to	IN
cord-024346-shauvo3j	22	3	the	the	DT
cord-024346-shauvo3j	22	4	algorithmic	algorithmic	JJ
cord-024346-shauvo3j	22	5	part	part	NN
cord-024346-shauvo3j	22	6	of	of	IN
cord-024346-shauvo3j	22	7	these	these	DT
cord-024346-shauvo3j	22	8	systems	system	NNS
cord-024346-shauvo3j	22	9	is	be	VBZ
cord-024346-shauvo3j	22	10	the	the	DT
cord-024346-shauvo3j	22	11	stage	stage	NN
cord-024346-shauvo3j	22	12	of	of	IN
cord-024346-shauvo3j	22	13	dividing	divide	VBG
cord-024346-shauvo3j	22	14	the	the	DT
cord-024346-shauvo3j	22	15	entire	entire	JJ
cord-024346-shauvo3j	22	16	image	image	NN
cord-024346-shauvo3j	22	17	of	of	IN
cord-024346-shauvo3j	22	18	the	the	DT
cord-024346-shauvo3j	22	19	crushed	crush	VBN
cord-024346-shauvo3j	22	20	ore	ore	NN
cord-024346-shauvo3j	22	21	mass	mass	NN
cord-024346-shauvo3j	22	22	into	into	IN
cord-024346-shauvo3j	22	23	fragments	fragment	NNS
cord-024346-shauvo3j	22	24	corresponding	correspond	VBG
cord-024346-shauvo3j	22	25	to	to	IN
cord-024346-shauvo3j	22	26	individual	individual	JJ
cord-024346-shauvo3j	22	27	particles	particle	NNS
cord-024346-shauvo3j	22	28	with	with	IN
cord-024346-shauvo3j	22	29	the	the	DT
cord-024346-shauvo3j	22	30	subsequent	subsequent	JJ
cord-024346-shauvo3j	22	31	determination	determination	NN
cord-024346-shauvo3j	22	32	of	of	IN
cord-024346-shauvo3j	22	33	their	-PRON-	PRP$
cord-024346-shauvo3j	22	34	geometric	geometric	JJ
cord-024346-shauvo3j	22	35	sizes	size	NNS
cord-024346-shauvo3j	22	36	.	.	.
cord-024346-shauvo3j	23	1	Such	such	JJ
cord-024346-shauvo3j	23	2	a	a	DT
cord-024346-shauvo3j	23	3	segmentation	segmentation	NN
cord-024346-shauvo3j	23	4	procedure	procedure	NN
cord-024346-shauvo3j	23	5	can	can	MD
cord-024346-shauvo3j	23	6	be	be	VB
cord-024346-shauvo3j	23	7	solved	solve	VBN
cord-024346-shauvo3j	23	8	by	by	IN
cord-024346-shauvo3j	23	9	different	different	JJ
cord-024346-shauvo3j	23	10	approaches	approach	NNS
cord-024346-shauvo3j	23	11	,	,	,
cord-024346-shauvo3j	23	12	one	one	CD
cord-024346-shauvo3j	23	13	of	of	IN
cord-024346-shauvo3j	23	14	which	which	WDT
cord-024346-shauvo3j	23	15	is	be	VBZ
cord-024346-shauvo3j	23	16	to	to	TO
cord-024346-shauvo3j	23	17	highlight	highlight	VB
cord-024346-shauvo3j	23	18	the	the	DT
cord-024346-shauvo3j	23	19	boundaries	boundary	NNS
cord-024346-shauvo3j	23	20	between	between	IN
cord-024346-shauvo3j	23	21	fragments	fragment	NNS
cord-024346-shauvo3j	23	22	of	of	IN
cord-024346-shauvo3j	23	23	images	image	NNS
cord-024346-shauvo3j	23	24	of	of	IN
cord-024346-shauvo3j	23	25	ore	ore	NN
cord-024346-shauvo3j	23	26	particles	particle	NNS
cord-024346-shauvo3j	23	27	.	.	.
cord-024346-shauvo3j	24	1	Classical	classical	JJ
cord-024346-shauvo3j	24	2	methods	method	NNS
cord-024346-shauvo3j	24	3	for	for	IN
cord-024346-shauvo3j	24	4	borders	border	NNS
cord-024346-shauvo3j	24	5	highlighting	highlight	VBG
cord-024346-shauvo3j	24	6	based	base	VBN
cord-024346-shauvo3j	24	7	on	on	IN
cord-024346-shauvo3j	24	8	the	the	DT
cord-024346-shauvo3j	24	9	assessment	assessment	NN
cord-024346-shauvo3j	24	10	of	of	IN
cord-024346-shauvo3j	24	11	changes	change	NNS
cord-024346-shauvo3j	24	12	in	in	IN
cord-024346-shauvo3j	24	13	brightness	brightness	NN
cord-024346-shauvo3j	24	14	of	of	IN
cord-024346-shauvo3j	24	15	neighboring	neighboring	NN
cord-024346-shauvo3j	24	16	pixels	pixel	NNS
cord-024346-shauvo3j	24	17	,	,	,
cord-024346-shauvo3j	24	18	which	which	WDT
cord-024346-shauvo3j	24	19	implies	imply	VBZ
cord-024346-shauvo3j	24	20	the	the	DT
cord-024346-shauvo3j	24	21	use	use	NN
cord-024346-shauvo3j	24	22	of	of	IN
cord-024346-shauvo3j	24	23	mathematical	mathematical	JJ
cord-024346-shauvo3j	24	24	algorithms	algorithm	NNS
cord-024346-shauvo3j	24	25	based	base	VBN
cord-024346-shauvo3j	24	26	on	on	IN
cord-024346-shauvo3j	24	27	differentiation	differentiation	NN
cord-024346-shauvo3j	24	28	[	[	-LRB-
cord-024346-shauvo3j	24	29	4	4	CD
cord-024346-shauvo3j	24	30	,	,	,
cord-024346-shauvo3j	24	31	8	8	CD
cord-024346-shauvo3j	24	32	]	]	-RRB-
cord-024346-shauvo3j	24	33	.	.	.
cord-024346-shauvo3j	25	1	Figure	figure	NN
cord-024346-shauvo3j	25	2	1	1	CD
cord-024346-shauvo3j	25	3	shows	show	VBZ
cord-024346-shauvo3j	25	4	typical	typical	JJ
cord-024346-shauvo3j	25	5	images	image	NNS
cord-024346-shauvo3j	25	6	of	of	IN
cord-024346-shauvo3j	25	7	crushed	crush	VBN
cord-024346-shauvo3j	25	8	ore	ore	NN
cord-024346-shauvo3j	25	9	moving	move	VBG
cord-024346-shauvo3j	25	10	on	on	IN
cord-024346-shauvo3j	25	11	a	a	DT
cord-024346-shauvo3j	25	12	conveyor	conveyor	JJ
cord-024346-shauvo3j	25	13	belt	belt	NN
cord-024346-shauvo3j	25	14	.	.	.
cord-024346-shauvo3j	26	1	Algorithms	algorithm	NNS
cord-024346-shauvo3j	26	2	from	from	IN
cord-024346-shauvo3j	26	3	the	the	DT
cord-024346-shauvo3j	26	4	OpenCV	OpenCV	NNP
cord-024346-shauvo3j	26	5	library	library	NN
cord-024346-shauvo3j	26	6	,	,	,
cord-024346-shauvo3j	26	7	the	the	DT
cord-024346-shauvo3j	26	8	Sobel	Sobel	NNP
cord-024346-shauvo3j	26	9	and	and	CC
cord-024346-shauvo3j	26	10	Canny	canny	JJ
cord-024346-shauvo3j	26	11	filters	filter	NNS
cord-024346-shauvo3j	26	12	in	in	IN
cord-024346-shauvo3j	26	13	particular	particular	JJ
cord-024346-shauvo3j	26	14	,	,	,
cord-024346-shauvo3j	26	15	used	use	VBN
cord-024346-shauvo3j	26	16	to	to	TO
cord-024346-shauvo3j	26	17	detect	detect	VB
cord-024346-shauvo3j	26	18	borders	border	NNS
cord-024346-shauvo3j	26	19	on	on	IN
cord-024346-shauvo3j	26	20	the	the	DT
cord-024346-shauvo3j	26	21	presented	present	VBN
cord-024346-shauvo3j	26	22	images	image	NNS
cord-024346-shauvo3j	26	23	,	,	,
cord-024346-shauvo3j	26	24	have	have	VBP
cord-024346-shauvo3j	26	25	identified	identify	VBN
cord-024346-shauvo3j	26	26	many	many	JJ
cord-024346-shauvo3j	26	27	false	false	JJ
cord-024346-shauvo3j	26	28	boundaries	boundary	NNS
cord-024346-shauvo3j	26	29	and	and	CC
cord-024346-shauvo3j	26	30	can	can	MD
cord-024346-shauvo3j	26	31	not	not	RB
cord-024346-shauvo3j	26	32	be	be	VB
cord-024346-shauvo3j	26	33	used	use	VBN
cord-024346-shauvo3j	26	34	in	in	IN
cord-024346-shauvo3j	26	35	practice	practice	NN
cord-024346-shauvo3j	26	36	.	.	.
cord-024346-shauvo3j	27	1	This	this	DT
cord-024346-shauvo3j	27	2	paper	paper	NN
cord-024346-shauvo3j	27	3	presents	present	VBZ
cord-024346-shauvo3j	27	4	the	the	DT
cord-024346-shauvo3j	27	5	results	result	NNS
cord-024346-shauvo3j	27	6	of	of	IN
cord-024346-shauvo3j	27	7	recognizing	recognize	VBG
cord-024346-shauvo3j	27	8	the	the	DT
cord-024346-shauvo3j	27	9	boundaries	boundary	NNS
cord-024346-shauvo3j	27	10	of	of	IN
cord-024346-shauvo3j	27	11	images	image	NNS
cord-024346-shauvo3j	27	12	of	of	IN
cord-024346-shauvo3j	27	13	stones	stone	NNS
cord-024346-shauvo3j	27	14	based	base	VBN
cord-024346-shauvo3j	27	15	on	on	IN
cord-024346-shauvo3j	27	16	a	a	DT
cord-024346-shauvo3j	27	17	neural	neural	JJ
cord-024346-shauvo3j	27	18	network	network	NN
cord-024346-shauvo3j	27	19	.	.	.
cord-024346-shauvo3j	28	1	This	this	DT
cord-024346-shauvo3j	28	2	approach	approach	NN
cord-024346-shauvo3j	28	3	has	have	VBZ
cord-024346-shauvo3j	28	4	been	be	VBN
cord-024346-shauvo3j	28	5	less	less	RBR
cord-024346-shauvo3j	28	6	studied	study	VBN
cord-024346-shauvo3j	28	7	and	and	CC
cord-024346-shauvo3j	28	8	described	describe	VBN
cord-024346-shauvo3j	28	9	in	in	IN
cord-024346-shauvo3j	28	10	the	the	DT
cord-024346-shauvo3j	28	11	literature	literature	NN
cord-024346-shauvo3j	28	12	,	,	,
cord-024346-shauvo3j	28	13	however	however	RB
cord-024346-shauvo3j	28	14	,	,	,
cord-024346-shauvo3j	28	15	it	-PRON-	PRP
cord-024346-shauvo3j	28	16	has	have	VBZ
cord-024346-shauvo3j	28	17	recently	recently	RB
cord-024346-shauvo3j	28	18	acquired	acquire	VBN
cord-024346-shauvo3j	28	19	great	great	JJ
cord-024346-shauvo3j	28	20	significance	significance	NN
cord-024346-shauvo3j	28	21	in	in	IN
cord-024346-shauvo3j	28	22	connection	connection	NN
cord-024346-shauvo3j	28	23	with	with	IN
cord-024346-shauvo3j	28	24	its	-PRON-	PRP$
cord-024346-shauvo3j	28	25	versatility	versatility	NN
cord-024346-shauvo3j	28	26	and	and	CC
cord-024346-shauvo3j	28	27	continues	continue	VBZ
cord-024346-shauvo3j	28	28	to	to	TO
cord-024346-shauvo3j	28	29	actively	actively	RB
cord-024346-shauvo3j	28	30	develop	develop	VB
cord-024346-shauvo3j	28	31	with	with	IN
cord-024346-shauvo3j	28	32	the	the	DT
cord-024346-shauvo3j	28	33	increasing	increase	VBG
cord-024346-shauvo3j	28	34	of	of	IN
cord-024346-shauvo3j	28	35	a	a	DT
cord-024346-shauvo3j	28	36	hardware	hardware	NN
cord-024346-shauvo3j	28	37	performance	performance	NN
cord-024346-shauvo3j	28	38	[	[	-LRB-
cord-024346-shauvo3j	28	39	3	3	CD
cord-024346-shauvo3j	28	40	,	,	,
cord-024346-shauvo3j	28	41	5	5	CD
cord-024346-shauvo3j	28	42	]	]	-RRB-
cord-024346-shauvo3j	28	43	.	.	.
cord-024346-shauvo3j	29	1	To	to	TO
cord-024346-shauvo3j	29	2	build	build	VB
cord-024346-shauvo3j	29	3	a	a	DT
cord-024346-shauvo3j	29	4	neural	neural	JJ
cord-024346-shauvo3j	29	5	network	network	NN
cord-024346-shauvo3j	29	6	and	and	CC
cord-024346-shauvo3j	29	7	apply	apply	VB
cord-024346-shauvo3j	29	8	machine	machine	NN
cord-024346-shauvo3j	29	9	learning	learning	NN
cord-024346-shauvo3j	29	10	methods	method	NNS
cord-024346-shauvo3j	29	11	,	,	,
cord-024346-shauvo3j	29	12	a	a	DT
cord-024346-shauvo3j	29	13	sample	sample	NN
cord-024346-shauvo3j	29	14	of	of	IN
cord-024346-shauvo3j	29	15	images	image	NNS
cord-024346-shauvo3j	29	16	of	of	IN
cord-024346-shauvo3j	29	17	crushed	crush	VBN
cord-024346-shauvo3j	29	18	ore	ore	NN
cord-024346-shauvo3j	29	19	stones	stone	NNS
cord-024346-shauvo3j	29	20	in	in	IN
cord-024346-shauvo3j	29	21	gray	gray	JJ
cord-024346-shauvo3j	29	22	scale	scale	NN
cord-024346-shauvo3j	29	23	was	be	VBD
cord-024346-shauvo3j	29	24	formed	form	VBN
cord-024346-shauvo3j	29	25	.	.	.
cord-024346-shauvo3j	30	1	The	the	DT
cord-024346-shauvo3j	30	2	recognition	recognition	NN
cord-024346-shauvo3j	30	3	of	of	IN
cord-024346-shauvo3j	30	4	the	the	DT
cord-024346-shauvo3j	30	5	boundaries	boundary	NNS
cord-024346-shauvo3j	30	6	of	of	IN
cord-024346-shauvo3j	30	7	the	the	DT
cord-024346-shauvo3j	30	8	ore	ore	NN
cord-024346-shauvo3j	30	9	particles	particle	NNS
cord-024346-shauvo3j	30	10	must	must	MD
cord-024346-shauvo3j	30	11	be	be	VB
cord-024346-shauvo3j	30	12	performed	perform	VBN
cord-024346-shauvo3j	30	13	for	for	IN
cord-024346-shauvo3j	30	14	stones	stone	NNS
cord-024346-shauvo3j	30	15	of	of	IN
cord-024346-shauvo3j	30	16	arbitrary	arbitrary	JJ
cord-024346-shauvo3j	30	17	size	size	NN
cord-024346-shauvo3j	30	18	and	and	CC
cord-024346-shauvo3j	30	19	configuration	configuration	NN
cord-024346-shauvo3j	30	20	on	on	IN
cord-024346-shauvo3j	30	21	a	a	DT
cord-024346-shauvo3j	30	22	video	video	NN
cord-024346-shauvo3j	30	23	frame	frame	NN
cord-024346-shauvo3j	30	24	with	with	IN
cord-024346-shauvo3j	30	25	ratio	ratio	NN
cord-024346-shauvo3j	30	26	768	768	CD
cord-024346-shauvo3j	30	27	×	×	NN
cord-024346-shauvo3j	30	28	576	576	CD
cord-024346-shauvo3j	30	29	pixels	pixel	NNS
cord-024346-shauvo3j	30	30	.	.	.
cord-024346-shauvo3j	31	1	To	to	TO
cord-024346-shauvo3j	31	2	solve	solve	VB
cord-024346-shauvo3j	31	3	this	this	DT
cord-024346-shauvo3j	31	4	problem	problem	NN
cord-024346-shauvo3j	31	5	with	with	IN
cord-024346-shauvo3j	31	6	the	the	DT
cord-024346-shauvo3j	31	7	help	help	NN
cord-024346-shauvo3j	31	8	of	of	IN
cord-024346-shauvo3j	31	9	neural	neural	JJ
cord-024346-shauvo3j	31	10	networks	network	NNS
cord-024346-shauvo3j	31	11	,	,	,
cord-024346-shauvo3j	31	12	it	-PRON-	PRP
cord-024346-shauvo3j	31	13	is	be	VBZ
cord-024346-shauvo3j	31	14	necessary	necessary	JJ
cord-024346-shauvo3j	31	15	to	to	TO
cord-024346-shauvo3j	31	16	determine	determine	VB
cord-024346-shauvo3j	31	17	what	what	WDT
cord-024346-shauvo3j	31	18	type	type	NN
cord-024346-shauvo3j	31	19	of	of	IN
cord-024346-shauvo3j	31	20	neural	neural	JJ
cord-024346-shauvo3j	31	21	network	network	NN
cord-024346-shauvo3j	31	22	to	to	TO
cord-024346-shauvo3j	31	23	use	use	VB
cord-024346-shauvo3j	31	24	,	,	,
cord-024346-shauvo3j	31	25	what	what	WP
cord-024346-shauvo3j	31	26	will	will	MD
cord-024346-shauvo3j	31	27	be	be	VB
cord-024346-shauvo3j	31	28	the	the	DT
cord-024346-shauvo3j	31	29	input	input	NN
cord-024346-shauvo3j	31	30	information	information	NN
cord-024346-shauvo3j	31	31	and	and	CC
cord-024346-shauvo3j	31	32	what	what	WP
cord-024346-shauvo3j	31	33	result	result	NN
cord-024346-shauvo3j	31	34	we	-PRON-	PRP
cord-024346-shauvo3j	31	35	want	want	VBP
cord-024346-shauvo3j	31	36	to	to	TO
cord-024346-shauvo3j	31	37	get	get	VB
cord-024346-shauvo3j	31	38	as	as	IN
cord-024346-shauvo3j	31	39	the	the	DT
cord-024346-shauvo3j	31	40	output	output	NN
cord-024346-shauvo3j	31	41	of	of	IN
cord-024346-shauvo3j	31	42	the	the	DT
cord-024346-shauvo3j	31	43	neural	neural	JJ
cord-024346-shauvo3j	31	44	network	network	NN
cord-024346-shauvo3j	31	45	processing	processing	NN
cord-024346-shauvo3j	31	46	.	.	.
cord-024346-shauvo3j	32	1	Analysis	analysis	NN
cord-024346-shauvo3j	32	2	of	of	IN
cord-024346-shauvo3j	32	3	literary	literary	JJ
cord-024346-shauvo3j	32	4	sources	source	NNS
cord-024346-shauvo3j	32	5	showed	show	VBD
cord-024346-shauvo3j	32	6	that	that	IN
cord-024346-shauvo3j	32	7	convolutional	convolutional	JJ
cord-024346-shauvo3j	32	8	neural	neural	JJ
cord-024346-shauvo3j	32	9	networks	network	NNS
cord-024346-shauvo3j	32	10	are	be	VBP
cord-024346-shauvo3j	32	11	the	the	DT
cord-024346-shauvo3j	32	12	most	most	RBS
cord-024346-shauvo3j	32	13	promising	promising	JJ
cord-024346-shauvo3j	32	14	when	when	WRB
cord-024346-shauvo3j	32	15	processing	processing	NN
cord-024346-shauvo3j	32	16	images	image	NNS
cord-024346-shauvo3j	32	17	[	[	-LRB-
cord-024346-shauvo3j	32	18	3	3	CD
cord-024346-shauvo3j	32	19	,	,	,
cord-024346-shauvo3j	32	20	[	[	-LRB-
cord-024346-shauvo3j	32	21	5	5	CD
cord-024346-shauvo3j	32	22	]	]	-RRB-
cord-024346-shauvo3j	32	23	[	[	-LRB-
cord-024346-shauvo3j	32	24	6	6	CD
cord-024346-shauvo3j	32	25	]	]	-RRB-
cord-024346-shauvo3j	32	26	[	[	-LRB-
cord-024346-shauvo3j	32	27	7	7	CD
cord-024346-shauvo3j	32	28	]	]	-RRB-
cord-024346-shauvo3j	32	29	.	.	.
cord-024346-shauvo3j	33	1	Convolutional	Convolutional	NNP
cord-024346-shauvo3j	33	2	neural	neural	JJ
cord-024346-shauvo3j	33	3	network	network	NN
cord-024346-shauvo3j	33	4	is	be	VBZ
cord-024346-shauvo3j	33	5	a	a	DT
cord-024346-shauvo3j	33	6	special	special	JJ
cord-024346-shauvo3j	33	7	architecture	architecture	NN
cord-024346-shauvo3j	33	8	of	of	IN
cord-024346-shauvo3j	33	9	artificial	artificial	JJ
cord-024346-shauvo3j	33	10	neural	neural	JJ
cord-024346-shauvo3j	33	11	networks	network	NNS
cord-024346-shauvo3j	33	12	aimed	aim	VBN
cord-024346-shauvo3j	33	13	at	at	IN
cord-024346-shauvo3j	33	14	efficient	efficient	JJ
cord-024346-shauvo3j	33	15	pattern	pattern	NN
cord-024346-shauvo3j	33	16	recognition	recognition	NN
cord-024346-shauvo3j	33	17	.	.	.
cord-024346-shauvo3j	34	1	This	this	DT
cord-024346-shauvo3j	34	2	architecture	architecture	NN
cord-024346-shauvo3j	34	3	manages	manage	VBZ
cord-024346-shauvo3j	34	4	to	to	TO
cord-024346-shauvo3j	34	5	recognize	recognize	VB
cord-024346-shauvo3j	34	6	objects	object	NNS
cord-024346-shauvo3j	34	7	in	in	IN
cord-024346-shauvo3j	34	8	images	image	NNS
cord-024346-shauvo3j	34	9	much	much	RB
cord-024346-shauvo3j	34	10	more	more	RBR
cord-024346-shauvo3j	34	11	accurately	accurately	RB
cord-024346-shauvo3j	34	12	,	,	,
cord-024346-shauvo3j	34	13	since	since	IN
cord-024346-shauvo3j	34	14	,	,	,
cord-024346-shauvo3j	34	15	unlike	unlike	IN
cord-024346-shauvo3j	34	16	the	the	DT
cord-024346-shauvo3j	34	17	multilayer	multilayer	JJ
cord-024346-shauvo3j	34	18	perceptron	perceptron	NN
cord-024346-shauvo3j	34	19	,	,	,
cord-024346-shauvo3j	34	20	two	two	CD
cord-024346-shauvo3j	34	21	-	-	HYPH
cord-024346-shauvo3j	34	22	dimensional	dimensional	JJ
cord-024346-shauvo3j	34	23	image	image	NN
cord-024346-shauvo3j	34	24	topology	topology	NN
cord-024346-shauvo3j	34	25	is	be	VBZ
cord-024346-shauvo3j	34	26	considered	consider	VBN
cord-024346-shauvo3j	34	27	.	.	.
cord-024346-shauvo3j	35	1	At	at	IN
cord-024346-shauvo3j	35	2	the	the	DT
cord-024346-shauvo3j	35	3	same	same	JJ
cord-024346-shauvo3j	35	4	time	time	NN
cord-024346-shauvo3j	35	5	,	,	,
cord-024346-shauvo3j	35	6	convolutional	convolutional	NN
cord-024346-shauvo3j	35	7	networks	network	NNS
cord-024346-shauvo3j	35	8	are	be	VBP
cord-024346-shauvo3j	35	9	resistant	resistant	JJ
cord-024346-shauvo3j	35	10	to	to	IN
cord-024346-shauvo3j	35	11	small	small	JJ
cord-024346-shauvo3j	35	12	displacements	displacement	NNS
cord-024346-shauvo3j	35	13	,	,	,
cord-024346-shauvo3j	35	14	zooming	zooming	NN
cord-024346-shauvo3j	35	15	,	,	,
cord-024346-shauvo3j	35	16	and	and	CC
cord-024346-shauvo3j	35	17	rotation	rotation	NN
cord-024346-shauvo3j	35	18	of	of	IN
cord-024346-shauvo3j	35	19	objects	object	NNS
cord-024346-shauvo3j	35	20	in	in	IN
cord-024346-shauvo3j	35	21	the	the	DT
cord-024346-shauvo3j	35	22	input	input	NN
cord-024346-shauvo3j	35	23	images	image	NNS
cord-024346-shauvo3j	35	24	.	.	.
cord-024346-shauvo3j	36	1	It	-PRON-	PRP
cord-024346-shauvo3j	36	2	is	be	VBZ
cord-024346-shauvo3j	36	3	this	this	DT
cord-024346-shauvo3j	36	4	type	type	NN
cord-024346-shauvo3j	36	5	of	of	IN
cord-024346-shauvo3j	36	6	neural	neural	JJ
cord-024346-shauvo3j	36	7	network	network	NN
cord-024346-shauvo3j	36	8	that	that	WDT
cord-024346-shauvo3j	36	9	will	will	MD
cord-024346-shauvo3j	36	10	be	be	VB
cord-024346-shauvo3j	36	11	used	use	VBN
cord-024346-shauvo3j	36	12	in	in	IN
cord-024346-shauvo3j	36	13	constructing	construct	VBG
cord-024346-shauvo3j	36	14	a	a	DT
cord-024346-shauvo3j	36	15	model	model	NN
cord-024346-shauvo3j	36	16	for	for	IN
cord-024346-shauvo3j	36	17	recognizing	recognize	VBG
cord-024346-shauvo3j	36	18	boundary	boundary	JJ
cord-024346-shauvo3j	36	19	points	point	NNS
cord-024346-shauvo3j	36	20	of	of	IN
cord-024346-shauvo3j	36	21	fragments	fragment	NNS
cord-024346-shauvo3j	36	22	of	of	IN
cord-024346-shauvo3j	36	23	stone	stone	NN
cord-024346-shauvo3j	36	24	images	image	NNS
cord-024346-shauvo3j	36	25	.	.	.
cord-024346-shauvo3j	37	1	Algorithms	algorithm	NNS
cord-024346-shauvo3j	37	2	for	for	IN
cord-024346-shauvo3j	37	3	extracting	extract	VBG
cord-024346-shauvo3j	37	4	the	the	DT
cord-024346-shauvo3j	37	5	boundaries	boundary	NNS
cord-024346-shauvo3j	37	6	of	of	IN
cord-024346-shauvo3j	37	7	regions	region	NNS
cord-024346-shauvo3j	37	8	as	as	IN
cord-024346-shauvo3j	37	9	source	source	NN
cord-024346-shauvo3j	37	10	data	datum	NNS
cord-024346-shauvo3j	37	11	use	use	VBP
cord-024346-shauvo3j	37	12	image	image	NN
cord-024346-shauvo3j	37	13	regions	region	NNS
cord-024346-shauvo3j	37	14	having	have	VBG
cord-024346-shauvo3j	37	15	sizes	size	NNS
cord-024346-shauvo3j	37	16	of	of	IN
cord-024346-shauvo3j	37	17	3	3	CD
cord-024346-shauvo3j	37	18	×	×	NN
cord-024346-shauvo3j	37	19	3	3	CD
cord-024346-shauvo3j	37	20	or	or	CC
cord-024346-shauvo3j	37	21	5	5	CD
cord-024346-shauvo3j	37	22	×	×	NN
cord-024346-shauvo3j	37	23	5	5	CD
cord-024346-shauvo3j	37	24	.	.	.
cord-024346-shauvo3j	38	1	If	if	IN
cord-024346-shauvo3j	38	2	the	the	DT
cord-024346-shauvo3j	38	3	algorithm	algorithm	NN
cord-024346-shauvo3j	38	4	provides	provide	VBZ
cord-024346-shauvo3j	38	5	for	for	IN
cord-024346-shauvo3j	38	6	integration	integration	NN
cord-024346-shauvo3j	38	7	operations	operation	NNS
cord-024346-shauvo3j	38	8	,	,	,
cord-024346-shauvo3j	38	9	then	then	RB
cord-024346-shauvo3j	38	10	the	the	DT
cord-024346-shauvo3j	38	11	window	window	NN
cord-024346-shauvo3j	38	12	size	size	NN
cord-024346-shauvo3j	38	13	increases	increase	NNS
cord-024346-shauvo3j	38	14	.	.	.
cord-024346-shauvo3j	39	1	An	an	DT
cord-024346-shauvo3j	39	2	analysis	analysis	NN
cord-024346-shauvo3j	39	3	of	of	IN
cord-024346-shauvo3j	39	4	the	the	DT
cord-024346-shauvo3j	39	5	subject	subject	JJ
cord-024346-shauvo3j	39	6	area	area	NN
cord-024346-shauvo3j	39	7	for	for	IN
cord-024346-shauvo3j	39	8	which	which	WDT
cord-024346-shauvo3j	39	9	this	this	DT
cord-024346-shauvo3j	39	10	neural	neural	JJ
cord-024346-shauvo3j	39	11	network	network	NN
cord-024346-shauvo3j	39	12	is	be	VBZ
cord-024346-shauvo3j	39	13	designed	design	VBN
cord-024346-shauvo3j	39	14	(	(	-LRB-
cord-024346-shauvo3j	39	15	a	a	DT
cord-024346-shauvo3j	39	16	cascade	cascade	NN
cord-024346-shauvo3j	39	17	of	of	IN
cord-024346-shauvo3j	39	18	secondary	secondary	JJ
cord-024346-shauvo3j	39	19	and	and	CC
cord-024346-shauvo3j	39	20	fine	fine	JJ
cord-024346-shauvo3j	39	21	ore	ore	NN
cord-024346-shauvo3j	39	22	crushing	crushing	NN
cord-024346-shauvo3j	39	23	)	)	-RRB-
cord-024346-shauvo3j	39	24	showed	show	VBD
cord-024346-shauvo3j	39	25	:	:	:
cord-024346-shauvo3j	39	26	for	for	IN
cord-024346-shauvo3j	39	27	images	image	NNS
cord-024346-shauvo3j	39	28	of	of	IN
cord-024346-shauvo3j	39	29	768	768	CD
cord-024346-shauvo3j	39	30	×	×	NN
cord-024346-shauvo3j	39	31	576	576	CD
cord-024346-shauvo3j	39	32	pixels	pixel	NNS
cord-024346-shauvo3j	39	33	and	and	CC
cord-024346-shauvo3j	39	34	visible	visible	JJ
cord-024346-shauvo3j	39	35	images	image	NNS
cord-024346-shauvo3j	39	36	of	of	IN
cord-024346-shauvo3j	39	37	ore	ore	NN
cord-024346-shauvo3j	39	38	pieces	piece	NNS
cord-024346-shauvo3j	39	39	,	,	,
cord-024346-shauvo3j	39	40	it	-PRON-	PRP
cord-024346-shauvo3j	39	41	is	be	VBZ
cord-024346-shauvo3j	39	42	preferable	preferable	JJ
cord-024346-shauvo3j	39	43	to	to	TO
cord-024346-shauvo3j	39	44	analyze	analyze	VB
cord-024346-shauvo3j	39	45	fragments	fragment	NNS
cord-024346-shauvo3j	39	46	with	with	IN
cord-024346-shauvo3j	39	47	dimensions	dimension	NNS
cord-024346-shauvo3j	39	48	of	of	IN
cord-024346-shauvo3j	39	49	50	50	CD
cord-024346-shauvo3j	39	50	×	×	NN
cord-024346-shauvo3j	39	51	50	50	CD
cord-024346-shauvo3j	39	52	pixels	pixel	NNS
cord-024346-shauvo3j	39	53	.	.	.
cord-024346-shauvo3j	40	1	Thus	thus	RB
cord-024346-shauvo3j	40	2	,	,	,
cord-024346-shauvo3j	40	3	the	the	DT
cord-024346-shauvo3j	40	4	input	input	NN
cord-024346-shauvo3j	40	5	data	datum	NNS
cord-024346-shauvo3j	40	6	for	for	IN
cord-024346-shauvo3j	40	7	constructing	construct	VBG
cord-024346-shauvo3j	40	8	the	the	DT
cord-024346-shauvo3j	40	9	boundaries	boundary	NNS
cord-024346-shauvo3j	40	10	of	of	IN
cord-024346-shauvo3j	40	11	stones	stone	NNS
cord-024346-shauvo3j	40	12	areas	area	NNS
cord-024346-shauvo3j	40	13	will	will	MD
cord-024346-shauvo3j	40	14	be	be	VB
cord-024346-shauvo3j	40	15	an	an	DT
cord-024346-shauvo3j	40	16	array	array	NN
cord-024346-shauvo3j	40	17	of	of	IN
cord-024346-shauvo3j	40	18	images	image	NNS
cord-024346-shauvo3j	40	19	consisting	consist	VBG
cord-024346-shauvo3j	40	20	of	of	IN
cord-024346-shauvo3j	40	21	(	(	-LRB-
cord-024346-shauvo3j	40	22	768	768	CD
cord-024346-shauvo3j	40	23	−	−	NN
cord-024346-shauvo3j	40	24	50)*(576	50)*(576	NNP
cord-024346-shauvo3j	40	25	−	−	CD
cord-024346-shauvo3j	40	26	50	50	CD
cord-024346-shauvo3j	40	27	)	)	-RRB-
cord-024346-shauvo3j	41	1	=	=	NFP
cord-024346-shauvo3j	42	1	377668	377668	CD
cord-024346-shauvo3j	42	2	halftone	halftone	NN
cord-024346-shauvo3j	42	3	fragments	fragment	NNS
cord-024346-shauvo3j	42	4	measuring	measure	VBG
cord-024346-shauvo3j	42	5	50	50	CD
cord-024346-shauvo3j	42	6	×	×	NN
cord-024346-shauvo3j	42	7	50	50	CD
cord-024346-shauvo3j	42	8	pixels	pixel	NNS
cord-024346-shauvo3j	42	9	.	.	.
cord-024346-shauvo3j	43	1	In	in	IN
cord-024346-shauvo3j	43	2	each	each	DT
cord-024346-shauvo3j	43	3	of	of	IN
cord-024346-shauvo3j	43	4	these	these	DT
cord-024346-shauvo3j	43	5	fragments	fragment	NNS
cord-024346-shauvo3j	43	6	,	,	,
cord-024346-shauvo3j	43	7	the	the	DT
cord-024346-shauvo3j	43	8	central	central	JJ
cord-024346-shauvo3j	43	9	point	point	NN
cord-024346-shauvo3j	43	10	either	either	CC
cord-024346-shauvo3j	43	11	belongs	belong	VBZ
cord-024346-shauvo3j	43	12	to	to	IN
cord-024346-shauvo3j	43	13	the	the	DT
cord-024346-shauvo3j	43	14	boundary	boundary	NN
cord-024346-shauvo3j	43	15	of	of	IN
cord-024346-shauvo3j	43	16	the	the	DT
cord-024346-shauvo3j	43	17	regions	region	NNS
cord-024346-shauvo3j	43	18	or	or	CC
cord-024346-shauvo3j	43	19	not	not	RB
cord-024346-shauvo3j	43	20	.	.	.
cord-024346-shauvo3j	44	1	Based	base	VBN
cord-024346-shauvo3j	44	2	on	on	IN
cord-024346-shauvo3j	44	3	this	this	DT
cord-024346-shauvo3j	44	4	assumption	assumption	NN
cord-024346-shauvo3j	44	5	,	,	,
cord-024346-shauvo3j	44	6	all	all	DT
cord-024346-shauvo3j	44	7	images	image	NNS
cord-024346-shauvo3j	44	8	can	can	MD
cord-024346-shauvo3j	44	9	be	be	VB
cord-024346-shauvo3j	44	10	divided	divide	VBN
cord-024346-shauvo3j	44	11	into	into	IN
cord-024346-shauvo3j	44	12	two	two	CD
cord-024346-shauvo3j	44	13	classes	class	NNS
cord-024346-shauvo3j	44	14	.	.	.
cord-024346-shauvo3j	45	1	To	to	TO
cord-024346-shauvo3j	45	2	mark	mark	VB
cord-024346-shauvo3j	45	3	the	the	DT
cord-024346-shauvo3j	45	4	images	image	NNS
cord-024346-shauvo3j	45	5	into	into	IN
cord-024346-shauvo3j	45	6	classes	class	NNS
cord-024346-shauvo3j	45	7	on	on	IN
cord-024346-shauvo3j	45	8	the	the	DT
cord-024346-shauvo3j	45	9	source	source	NN
cord-024346-shauvo3j	45	10	images	image	NNS
cord-024346-shauvo3j	45	11	,	,	,
cord-024346-shauvo3j	45	12	the	the	DT
cord-024346-shauvo3j	45	13	borders	border	NNS
cord-024346-shauvo3j	45	14	of	of	IN
cord-024346-shauvo3j	45	15	the	the	DT
cord-024346-shauvo3j	45	16	stones	stone	NNS
cord-024346-shauvo3j	45	17	were	be	VBD
cord-024346-shauvo3j	45	18	drawn	draw	VBN
cord-024346-shauvo3j	45	19	using	use	VBG
cord-024346-shauvo3j	45	20	a	a	DT
cord-024346-shauvo3j	45	21	red	red	JJ
cord-024346-shauvo3j	45	22	line	line	NN
cord-024346-shauvo3j	45	23	with	with	IN
cord-024346-shauvo3j	45	24	a	a	DT
cord-024346-shauvo3j	45	25	width	width	NN
cord-024346-shauvo3j	45	26	of	of	IN
cord-024346-shauvo3j	45	27	5	5	CD
cord-024346-shauvo3j	45	28	pixels	pixel	NNS
cord-024346-shauvo3j	45	29	.	.	.
cord-024346-shauvo3j	46	1	This	this	DT
cord-024346-shauvo3j	46	2	procedure	procedure	NN
cord-024346-shauvo3j	46	3	was	be	VBD
cord-024346-shauvo3j	46	4	performed	perform	VBN
cord-024346-shauvo3j	46	5	manually	manually	RB
cord-024346-shauvo3j	46	6	with	with	IN
cord-024346-shauvo3j	46	7	the	the	DT
cord-024346-shauvo3j	46	8	Microsoft	Microsoft	NNP
cord-024346-shauvo3j	46	9	Paint	Paint	NNP
cord-024346-shauvo3j	46	10	program	program	NN
cord-024346-shauvo3j	46	11	.	.	.
cord-024346-shauvo3j	47	1	An	an	DT
cord-024346-shauvo3j	47	2	example	example	NN
cord-024346-shauvo3j	47	3	of	of	IN
cord-024346-shauvo3j	47	4	the	the	DT
cord-024346-shauvo3j	47	5	original	original	JJ
cord-024346-shauvo3j	47	6	and	and	CC
cord-024346-shauvo3j	47	7	marked	marked	JJ
cord-024346-shauvo3j	47	8	image	image	NN
cord-024346-shauvo3j	47	9	is	be	VBZ
cord-024346-shauvo3j	47	10	shown	show	VBN
cord-024346-shauvo3j	47	11	in	in	IN
cord-024346-shauvo3j	47	12	Fig	Fig	NNP
cord-024346-shauvo3j	47	13	.	.	.
cord-024346-shauvo3j	48	1	2	2	LS
cord-024346-shauvo3j	48	2	.	.	.
cord-024346-shauvo3j	49	1	Then	then	RB
cord-024346-shauvo3j	49	2	Python	Python	NNP
cord-024346-shauvo3j	49	3	script	script	NN
cord-024346-shauvo3j	49	4	was	be	VBD
cord-024346-shauvo3j	49	5	a	a	DT
cord-024346-shauvo3j	49	6	projected	project	VBN
cord-024346-shauvo3j	49	7	,	,	,
cord-024346-shauvo3j	49	8	which	which	WDT
cord-024346-shauvo3j	49	9	processed	process	VBD
cord-024346-shauvo3j	49	10	the	the	DT
cord-024346-shauvo3j	49	11	original	original	JJ
cord-024346-shauvo3j	49	12	image	image	NN
cord-024346-shauvo3j	49	13	to	to	TO
cord-024346-shauvo3j	49	14	highlight	highlight	VB
cord-024346-shauvo3j	49	15	50	50	CD
cord-024346-shauvo3j	49	16	×	×	NN
cord-024346-shauvo3j	49	17	50	50	CD
cord-024346-shauvo3j	49	18	pixels	pixel	NNS
cord-024346-shauvo3j	49	19	fragments	fragment	NNS
cord-024346-shauvo3j	49	20	and	and	CC
cord-024346-shauvo3j	49	21	based	base	VBN
cord-024346-shauvo3j	49	22	on	on	IN
cord-024346-shauvo3j	49	23	the	the	DT
cord-024346-shauvo3j	49	24	markup	markup	NN
cord-024346-shauvo3j	49	25	image	image	NN
cord-024346-shauvo3j	49	26	sorted	sort	VBD
cord-024346-shauvo3j	49	27	fragments	fragment	NNS
cord-024346-shauvo3j	49	28	into	into	IN
cord-024346-shauvo3j	49	29	classes	class	NNS
cord-024346-shauvo3j	49	30	preserving	preserve	VBG
cord-024346-shauvo3j	49	31	them	-PRON-	PRP
cord-024346-shauvo3j	49	32	in	in	IN
cord-024346-shauvo3j	49	33	different	different	JJ
cord-024346-shauvo3j	49	34	directories	directory	NNS
cord-024346-shauvo3j	49	35	To	to	TO
cord-024346-shauvo3j	49	36	write	write	VB
cord-024346-shauvo3j	49	37	the	the	DT
cord-024346-shauvo3j	49	38	scripts	script	NNS
cord-024346-shauvo3j	49	39	,	,	,
cord-024346-shauvo3j	49	40	we	-PRON-	PRP
cord-024346-shauvo3j	49	41	used	use	VBD
cord-024346-shauvo3j	49	42	the	the	DT
cord-024346-shauvo3j	49	43	Python	Python	NNP
cord-024346-shauvo3j	49	44	3	3	CD
cord-024346-shauvo3j	49	45	programming	programming	NN
cord-024346-shauvo3j	49	46	language	language	NN
cord-024346-shauvo3j	49	47	and	and	CC
cord-024346-shauvo3j	49	48	the	the	DT
cord-024346-shauvo3j	49	49	Jupyter	Jupyter	NNP
cord-024346-shauvo3j	49	50	Notebook	Notebook	NNP
cord-024346-shauvo3j	49	51	IDE	IDE	NNP
cord-024346-shauvo3j	49	52	.	.	.
cord-024346-shauvo3j	50	1	Thus	thus	RB
cord-024346-shauvo3j	50	2	,	,	,
cord-024346-shauvo3j	50	3	two	two	CD
cord-024346-shauvo3j	50	4	data	datum	NNS
cord-024346-shauvo3j	50	5	samples	sample	NNS
cord-024346-shauvo3j	50	6	were	be	VBD
cord-024346-shauvo3j	50	7	obtained	obtain	VBN
cord-024346-shauvo3j	50	8	:	:	:
cord-024346-shauvo3j	50	9	training	training	NN
cord-024346-shauvo3j	50	10	dataset	dataset	NN
cord-024346-shauvo3j	50	11	and	and	CC
cord-024346-shauvo3j	50	12	test	test	NN
cord-024346-shauvo3j	50	13	dataset	dataset	NN
cord-024346-shauvo3j	50	14	for	for	IN
cord-024346-shauvo3j	50	15	the	the	DT
cord-024346-shauvo3j	50	16	assessment	assessment	NN
cord-024346-shauvo3j	50	17	of	of	IN
cord-024346-shauvo3j	50	18	the	the	DT
cord-024346-shauvo3j	50	19	network	network	NN
cord-024346-shauvo3j	50	20	accuracy	accuracy	NN
cord-024346-shauvo3j	50	21	.	.	.
cord-024346-shauvo3j	51	1	As	as	IN
cord-024346-shauvo3j	51	2	noted	note	VBN
cord-024346-shauvo3j	51	3	above	above	RB
cord-024346-shauvo3j	51	4	,	,	,
cord-024346-shauvo3j	51	5	the	the	DT
cord-024346-shauvo3j	51	6	architecture	architecture	NN
cord-024346-shauvo3j	51	7	of	of	IN
cord-024346-shauvo3j	51	8	the	the	DT
cord-024346-shauvo3j	51	9	neural	neural	JJ
cord-024346-shauvo3j	51	10	network	network	NN
cord-024346-shauvo3j	51	11	was	be	VBD
cord-024346-shauvo3j	51	12	built	build	VBN
cord-024346-shauvo3j	51	13	on	on	IN
cord-024346-shauvo3j	51	14	a	a	DT
cord-024346-shauvo3j	51	15	convolutional	convolutional	NN
cord-024346-shauvo3j	51	16	principle	principle	NN
cord-024346-shauvo3j	51	17	.	.	.
cord-024346-shauvo3j	52	1	The	the	DT
cord-024346-shauvo3j	52	2	structure	structure	NN
cord-024346-shauvo3j	52	3	of	of	IN
cord-024346-shauvo3j	52	4	the	the	DT
cord-024346-shauvo3j	52	5	basic	basic	JJ
cord-024346-shauvo3j	52	6	network	network	NN
cord-024346-shauvo3j	52	7	architecture	architecture	NN
cord-024346-shauvo3j	52	8	is	be	VBZ
cord-024346-shauvo3j	52	9	shown	show	VBN
cord-024346-shauvo3j	52	10	in	in	IN
cord-024346-shauvo3j	52	11	Fig	Fig	NNP
cord-024346-shauvo3j	52	12	.	.	.
cord-024346-shauvo3j	53	1	3	3	LS
cord-024346-shauvo3j	53	2	[	[	-LRB-
cord-024346-shauvo3j	53	3	7	7	CD
cord-024346-shauvo3j	53	4	]	]	-RRB-
cord-024346-shauvo3j	53	5	.	.	.
cord-024346-shauvo3j	54	1	The	the	DT
cord-024346-shauvo3j	54	2	network	network	NN
cord-024346-shauvo3j	54	3	includes	include	VBZ
cord-024346-shauvo3j	54	4	an	an	DT
cord-024346-shauvo3j	54	5	input	input	NN
cord-024346-shauvo3j	54	6	layer	layer	NN
cord-024346-shauvo3j	54	7	in	in	IN
cord-024346-shauvo3j	54	8	the	the	DT
cord-024346-shauvo3j	54	9	format	format	NN
cord-024346-shauvo3j	54	10	of	of	IN
cord-024346-shauvo3j	54	11	the	the	DT
cord-024346-shauvo3j	54	12	tensor	tensor	NN
cord-024346-shauvo3j	54	13	50	50	CD
cord-024346-shauvo3j	54	14	×	×	NN
cord-024346-shauvo3j	54	15	50	50	CD
cord-024346-shauvo3j	54	16	×	×	NN
cord-024346-shauvo3j	54	17	1	1	CD
cord-024346-shauvo3j	54	18	.	.	.
cord-024346-shauvo3j	55	1	The	the	DT
cord-024346-shauvo3j	55	2	following	follow	VBG
cord-024346-shauvo3j	55	3	are	be	VBP
cord-024346-shauvo3j	55	4	several	several	JJ
cord-024346-shauvo3j	55	5	convolutional	convolutional	NN
cord-024346-shauvo3j	55	6	and	and	CC
cord-024346-shauvo3j	55	7	pooling	pooling	NN
cord-024346-shauvo3j	55	8	layers	layer	NNS
cord-024346-shauvo3j	55	9	.	.	.
cord-024346-shauvo3j	56	1	After	after	IN
cord-024346-shauvo3j	56	2	that	that	DT
cord-024346-shauvo3j	56	3	,	,	,
cord-024346-shauvo3j	56	4	the	the	DT
cord-024346-shauvo3j	56	5	network	network	NN
cord-024346-shauvo3j	56	6	unfolds	unfold	VBZ
cord-024346-shauvo3j	56	7	in	in	IN
cord-024346-shauvo3j	56	8	one	one	CD
cord-024346-shauvo3j	56	9	fully	fully	RB
cord-024346-shauvo3j	56	10	connected	connect	VBN
cord-024346-shauvo3j	56	11	layer	layer	NN
cord-024346-shauvo3j	56	12	,	,	,
cord-024346-shauvo3j	56	13	the	the	DT
cord-024346-shauvo3j	56	14	outputs	output	NNS
cord-024346-shauvo3j	56	15	of	of	IN
cord-024346-shauvo3j	56	16	which	which	WDT
cord-024346-shauvo3j	56	17	converge	converge	VBP
cord-024346-shauvo3j	56	18	into	into	IN
cord-024346-shauvo3j	56	19	one	one	CD
cord-024346-shauvo3j	56	20	neuron	neuron	NN
cord-024346-shauvo3j	56	21	,	,	,
cord-024346-shauvo3j	56	22	to	to	TO
cord-024346-shauvo3j	56	23	which	which	WDT
cord-024346-shauvo3j	56	24	the	the	DT
cord-024346-shauvo3j	56	25	activation	activation	NN
cord-024346-shauvo3j	56	26	function	function	NN
cord-024346-shauvo3j	56	27	,	,	,
cord-024346-shauvo3j	56	28	the	the	DT
cord-024346-shauvo3j	56	29	sigmoid	sigmoid	NN
cord-024346-shauvo3j	56	30	,	,	,
cord-024346-shauvo3j	56	31	will	will	MD
cord-024346-shauvo3j	56	32	be	be	VB
cord-024346-shauvo3j	56	33	applied	apply	VBN
cord-024346-shauvo3j	56	34	.	.	.
cord-024346-shauvo3j	57	1	At	at	IN
cord-024346-shauvo3j	57	2	the	the	DT
cord-024346-shauvo3j	57	3	output	output	NN
cord-024346-shauvo3j	57	4	,	,	,
cord-024346-shauvo3j	57	5	we	-PRON-	PRP
cord-024346-shauvo3j	57	6	obtain	obtain	VBP
cord-024346-shauvo3j	57	7	the	the	DT
cord-024346-shauvo3j	57	8	probability	probability	NN
cord-024346-shauvo3j	57	9	that	that	IN
cord-024346-shauvo3j	57	10	the	the	DT
cord-024346-shauvo3j	57	11	center	center	NN
cord-024346-shauvo3j	57	12	point	point	NN
cord-024346-shauvo3j	57	13	of	of	IN
cord-024346-shauvo3j	57	14	the	the	DT
cord-024346-shauvo3j	57	15	input	input	NN
cord-024346-shauvo3j	57	16	fragment	fragment	NN
cord-024346-shauvo3j	57	17	belongs	belong	VBZ
cord-024346-shauvo3j	57	18	to	to	IN
cord-024346-shauvo3j	57	19	the	the	DT
cord-024346-shauvo3j	57	20	"	"	``
cord-024346-shauvo3j	57	21	boundary	boundary	JJ
cord-024346-shauvo3j	57	22	point	point	NN
cord-024346-shauvo3j	57	23	"	"	''
cord-024346-shauvo3j	57	24	class	class	NN
cord-024346-shauvo3j	57	25	.	.	.
cord-024346-shauvo3j	58	1	The	the	DT
cord-024346-shauvo3j	58	2	Keras	Keras	NNPS
cord-024346-shauvo3j	58	3	open	open	JJ
cord-024346-shauvo3j	58	4	source	source	NN
cord-024346-shauvo3j	58	5	library	library	NN
cord-024346-shauvo3j	58	6	was	be	VBD
cord-024346-shauvo3j	58	7	used	use	VBN
cord-024346-shauvo3j	58	8	to	to	TO
cord-024346-shauvo3j	58	9	develop	develop	VB
cord-024346-shauvo3j	58	10	and	and	CC
cord-024346-shauvo3j	58	11	train	train	VB
cord-024346-shauvo3j	58	12	a	a	DT
cord-024346-shauvo3j	58	13	convolutional	convolutional	JJ
cord-024346-shauvo3j	58	14	neural	neural	JJ
cord-024346-shauvo3j	58	15	network	network	NN
cord-024346-shauvo3j	58	16	[	[	-LRB-
cord-024346-shauvo3j	58	17	1	1	CD
cord-024346-shauvo3j	58	18	,	,	,
cord-024346-shauvo3j	58	19	2	2	CD
cord-024346-shauvo3j	58	20	,	,	,
cord-024346-shauvo3j	58	21	6	6	CD
cord-024346-shauvo3j	58	22	,	,	,
cord-024346-shauvo3j	58	23	10	10	CD
cord-024346-shauvo3j	58	24	]	]	-RRB-
cord-024346-shauvo3j	58	25	.	.	.
cord-024346-shauvo3j	59	1	The	the	DT
cord-024346-shauvo3j	59	2	basic	basic	JJ
cord-024346-shauvo3j	59	3	convolutional	convolutional	NN
cord-024346-shauvo3j	59	4	neural	neural	JJ
cord-024346-shauvo3j	59	5	network	network	NN
cord-024346-shauvo3j	59	6	was	be	VBD
cord-024346-shauvo3j	59	7	trained	train	VBN
cord-024346-shauvo3j	59	8	with	with	IN
cord-024346-shauvo3j	59	9	the	the	DT
cord-024346-shauvo3j	59	10	following	follow	VBG
cord-024346-shauvo3j	59	11	parameters	parameter	NNS
cord-024346-shauvo3j	59	12	:	:	:
cord-024346-shauvo3j	59	13	-10	-10	NN
cord-024346-shauvo3j	59	14	epoch	epoch	NN
cord-024346-shauvo3j	59	15	;	;	.
cord-024346-shauvo3j	60	1	-error	-error	:
cord-024346-shauvo3j	60	2	-binary	-binary	JJ
cord-024346-shauvo3j	60	3	cross	cross	JJ
cord-024346-shauvo3j	60	4	-	-	NN
cord-024346-shauvo3j	60	5	entropy	entropy	JJ
cord-024346-shauvo3j	61	1	;	;	:
cord-024346-shauvo3j	61	2	-quality	-quality	NN
cord-024346-shauvo3j	61	3	metric	metric	JJ
cord-024346-shauvo3j	61	4	-accuracy	-accuracy	NN
cord-024346-shauvo3j	62	1	(	(	-LRB-
cord-024346-shauvo3j	62	2	percentage	percentage	NN
cord-024346-shauvo3j	62	3	of	of	IN
cord-024346-shauvo3j	62	4	correct	correct	JJ
cord-024346-shauvo3j	62	5	answers	answer	NNS
cord-024346-shauvo3j	62	6	)	)	-RRB-
cord-024346-shauvo3j	62	7	;	;	:
cord-024346-shauvo3j	62	8	-optimization	-optimization	NN
cord-024346-shauvo3j	62	9	algorithm	algorithm	NN
cord-024346-shauvo3j	62	10	-RMSprop	-rmsprop	NN
cord-024346-shauvo3j	62	11	.	.	.
cord-024346-shauvo3j	63	1	The	the	DT
cord-024346-shauvo3j	63	2	accuracy	accuracy	NN
cord-024346-shauvo3j	63	3	on	on	IN
cord-024346-shauvo3j	63	4	the	the	DT
cord-024346-shauvo3j	63	5	reference	reference	NN
cord-024346-shauvo3j	63	6	data	datum	NNS
cord-024346-shauvo3j	63	7	set	set	NN
cord-024346-shauvo3j	63	8	provided	provide	VBN
cord-024346-shauvo3j	63	9	by	by	IN
cord-024346-shauvo3j	63	10	the	the	DT
cord-024346-shauvo3j	63	11	base	base	NN
cord-024346-shauvo3j	63	12	model	model	NN
cord-024346-shauvo3j	63	13	is	be	VBZ
cord-024346-shauvo3j	63	14	90.8	90.8	CD
cord-024346-shauvo3j	63	15	%	%	NN
cord-024346-shauvo3j	63	16	.	.	.
cord-024346-shauvo3j	64	1	In	in	IN
cord-024346-shauvo3j	64	2	order	order	NN
cord-024346-shauvo3j	64	3	to	to	TO
cord-024346-shauvo3j	64	4	improve	improve	VB
cord-024346-shauvo3j	64	5	the	the	DT
cord-024346-shauvo3j	64	6	accuracy	accuracy	NN
cord-024346-shauvo3j	64	7	of	of	IN
cord-024346-shauvo3j	64	8	predictions	prediction	NNS
cord-024346-shauvo3j	64	9	,	,	,
cord-024346-shauvo3j	64	10	a	a	DT
cord-024346-shauvo3j	64	11	script	script	NN
cord-024346-shauvo3j	64	12	was	be	VBD
cord-024346-shauvo3j	64	13	written	write	VBN
cord-024346-shauvo3j	64	14	that	that	IN
cord-024346-shauvo3j	64	15	trains	train	NNS
cord-024346-shauvo3j	64	16	models	model	NNS
cord-024346-shauvo3j	64	17	on	on	IN
cord-024346-shauvo3j	64	18	several	several	JJ
cord-024346-shauvo3j	64	19	configurations	configuration	NNS
cord-024346-shauvo3j	64	20	,	,	,
cord-024346-shauvo3j	64	21	and	and	CC
cord-024346-shauvo3j	64	22	also	also	RB
cord-024346-shauvo3j	64	23	checks	check	VBZ
cord-024346-shauvo3j	64	24	the	the	DT
cord-024346-shauvo3j	64	25	quality	quality	NN
cord-024346-shauvo3j	64	26	of	of	IN
cord-024346-shauvo3j	64	27	the	the	DT
cord-024346-shauvo3j	64	28	model	model	NN
cord-024346-shauvo3j	64	29	on	on	IN
cord-024346-shauvo3j	64	30	a	a	DT
cord-024346-shauvo3j	64	31	test	test	NN
cord-024346-shauvo3j	64	32	dataset	dataset	NN
cord-024346-shauvo3j	64	33	.	.	.
cord-024346-shauvo3j	65	1	To	to	TO
cord-024346-shauvo3j	65	2	improve	improve	VB
cord-024346-shauvo3j	65	3	the	the	DT
cord-024346-shauvo3j	65	4	accuracy	accuracy	NN
cord-024346-shauvo3j	65	5	of	of	IN
cord-024346-shauvo3j	65	6	the	the	DT
cord-024346-shauvo3j	65	7	predictions	prediction	NNS
cord-024346-shauvo3j	65	8	of	of	IN
cord-024346-shauvo3j	65	9	the	the	DT
cord-024346-shauvo3j	65	10	convolutional	convolutional	JJ
cord-024346-shauvo3j	65	11	neural	neural	JJ
cord-024346-shauvo3j	65	12	network	network	NN
cord-024346-shauvo3j	65	13	,	,	,
cord-024346-shauvo3j	65	14	the	the	DT
cord-024346-shauvo3j	65	15	following	follow	VBG
cord-024346-shauvo3j	65	16	parameters	parameter	NNS
cord-024346-shauvo3j	65	17	were	be	VBD
cord-024346-shauvo3j	65	18	varied	varied	JJ
cord-024346-shauvo3j	65	19	with	with	IN
cord-024346-shauvo3j	65	20	respect	respect	NN
cord-024346-shauvo3j	65	21	to	to	IN
cord-024346-shauvo3j	65	22	the	the	DT
cord-024346-shauvo3j	65	23	base	base	NN
cord-024346-shauvo3j	65	24	model	model	NN
cord-024346-shauvo3j	65	25	:	:	:
cord-024346-shauvo3j	66	1	-increasing	-increase	VBG
cord-024346-shauvo3j	67	1	the	the	DT
cord-024346-shauvo3j	67	2	number	number	NN
cord-024346-shauvo3j	67	3	of	of	IN
cord-024346-shauvo3j	67	4	layers	layer	NNS
cord-024346-shauvo3j	67	5	:	:	:
cord-024346-shauvo3j	68	1	+1	+1	NFP
cord-024346-shauvo3j	69	1	convolutional	convolutional	NN
cord-024346-shauvo3j	69	2	+1	+1	HYPH
cord-024346-shauvo3j	69	3	pooling	pooling	NN
cord-024346-shauvo3j	69	4	;	;	.
cord-024346-shauvo3j	70	1	-increasing	-increase	VBG
cord-024346-shauvo3j	71	1	of	of	IN
cord-024346-shauvo3j	71	2	the	the	DT
cord-024346-shauvo3j	71	3	number	number	NN
cord-024346-shauvo3j	71	4	of	of	IN
cord-024346-shauvo3j	71	5	filters	filter	NNS
cord-024346-shauvo3j	71	6	:	:	:
cord-024346-shauvo3j	71	7	+32	+32	XX
cord-024346-shauvo3j	71	8	in	in	IN
cord-024346-shauvo3j	71	9	each	each	DT
cord-024346-shauvo3j	71	10	layer	layer	NN
cord-024346-shauvo3j	71	11	;	;	:
cord-024346-shauvo3j	71	12	-increasing	-increase	VBG
cord-024346-shauvo3j	71	13	the	the	DT
cord-024346-shauvo3j	71	14	size	size	NN
cord-024346-shauvo3j	71	15	of	of	IN
cord-024346-shauvo3j	71	16	the	the	DT
cord-024346-shauvo3j	71	17	filter	filter	NN
cord-024346-shauvo3j	71	18	up	up	IN
cord-024346-shauvo3j	71	19	to	to	TO
cord-024346-shauvo3j	71	20	5	5	CD
cord-024346-shauvo3j	71	21	*	*	SYM
cord-024346-shauvo3j	71	22	5	5	CD
cord-024346-shauvo3j	71	23	;	;	:
cord-024346-shauvo3j	71	24	-increasing	-increase	VBG
cord-024346-shauvo3j	71	25	the	the	DT
cord-024346-shauvo3j	71	26	number	number	NN
cord-024346-shauvo3j	71	27	of	of	IN
cord-024346-shauvo3j	71	28	epochs	epoch	NNS
cord-024346-shauvo3j	71	29	up	up	IN
cord-024346-shauvo3j	71	30	to	to	TO
cord-024346-shauvo3j	71	31	30	30	CD
cord-024346-shauvo3j	71	32	;	;	:
cord-024346-shauvo3j	71	33	-decreasing	-decrease	VBG
cord-024346-shauvo3j	71	34	in	in	IN
cord-024346-shauvo3j	71	35	the	the	DT
cord-024346-shauvo3j	71	36	number	number	NN
cord-024346-shauvo3j	71	37	of	of	IN
cord-024346-shauvo3j	71	38	layers	layer	NNS
cord-024346-shauvo3j	71	39	.	.	.
cord-024346-shauvo3j	72	1	These	these	DT
cord-024346-shauvo3j	72	2	modifications	modification	NNS
cord-024346-shauvo3j	72	3	of	of	IN
cord-024346-shauvo3j	72	4	the	the	DT
cord-024346-shauvo3j	72	5	base	base	NN
cord-024346-shauvo3j	72	6	convolutional	convolutional	NN
cord-024346-shauvo3j	72	7	neural	neural	JJ
cord-024346-shauvo3j	72	8	network	network	NN
cord-024346-shauvo3j	72	9	did	do	VBD
cord-024346-shauvo3j	72	10	not	not	RB
cord-024346-shauvo3j	72	11	lead	lead	VB
cord-024346-shauvo3j	72	12	to	to	IN
cord-024346-shauvo3j	72	13	an	an	DT
cord-024346-shauvo3j	72	14	improvement	improvement	NN
cord-024346-shauvo3j	72	15	in	in	IN
cord-024346-shauvo3j	72	16	its	-PRON-	PRP$
cord-024346-shauvo3j	72	17	performance	performance	NN
cord-024346-shauvo3j	72	18	-all	-all	:
cord-024346-shauvo3j	72	19	models	model	NNS
cord-024346-shauvo3j	72	20	had	have	VBD
cord-024346-shauvo3j	72	21	the	the	DT
cord-024346-shauvo3j	72	22	worst	bad	JJS
cord-024346-shauvo3j	72	23	quality	quality	NN
cord-024346-shauvo3j	72	24	on	on	IN
cord-024346-shauvo3j	72	25	the	the	DT
cord-024346-shauvo3j	72	26	test	test	NN
cord-024346-shauvo3j	72	27	sample	sample	NN
cord-024346-shauvo3j	72	28	(	(	-LRB-
cord-024346-shauvo3j	72	29	in	in	IN
cord-024346-shauvo3j	72	30	the	the	DT
cord-024346-shauvo3j	72	31	region	region	NN
cord-024346-shauvo3j	72	32	of	of	IN
cord-024346-shauvo3j	72	33	88	88	CD
cord-024346-shauvo3j	72	34	-	-	SYM
cord-024346-shauvo3j	72	35	90	90	CD
cord-024346-shauvo3j	72	36	%	%	NN
cord-024346-shauvo3j	72	37	accuracy	accuracy	NN
cord-024346-shauvo3j	72	38	)	)	-RRB-
cord-024346-shauvo3j	72	39	.	.	.
cord-024346-shauvo3j	73	1	The	the	DT
cord-024346-shauvo3j	73	2	model	model	NN
cord-024346-shauvo3j	73	3	of	of	IN
cord-024346-shauvo3j	73	4	the	the	DT
cord-024346-shauvo3j	73	5	convolutional	convolutional	JJ
cord-024346-shauvo3j	73	6	neural	neural	JJ
cord-024346-shauvo3j	73	7	network	network	NN
cord-024346-shauvo3j	73	8	,	,	,
cord-024346-shauvo3j	73	9	which	which	WDT
cord-024346-shauvo3j	73	10	showed	show	VBD
cord-024346-shauvo3j	73	11	the	the	DT
cord-024346-shauvo3j	73	12	best	good	JJS
cord-024346-shauvo3j	73	13	quality	quality	NN
cord-024346-shauvo3j	73	14	,	,	,
cord-024346-shauvo3j	73	15	was	be	VBD
cord-024346-shauvo3j	73	16	the	the	DT
cord-024346-shauvo3j	73	17	base	base	NN
cord-024346-shauvo3j	73	18	model	model	NN
cord-024346-shauvo3j	73	19	.	.	.
cord-024346-shauvo3j	74	1	Its	-PRON-	PRP$
cord-024346-shauvo3j	74	2	quality	quality	NN
cord-024346-shauvo3j	74	3	in	in	IN
cord-024346-shauvo3j	74	4	the	the	DT
cord-024346-shauvo3j	74	5	training	training	NN
cord-024346-shauvo3j	74	6	sample	sample	NN
cord-024346-shauvo3j	74	7	is	be	VBZ
cord-024346-shauvo3j	74	8	estimated	estimate	VBN
cord-024346-shauvo3j	74	9	at	at	IN
cord-024346-shauvo3j	74	10	90.8	90.8	CD
cord-024346-shauvo3j	74	11	%	%	NN
cord-024346-shauvo3j	74	12	,	,	,
cord-024346-shauvo3j	74	13	and	and	CC
cord-024346-shauvo3j	74	14	in	in	IN
cord-024346-shauvo3j	74	15	the	the	DT
cord-024346-shauvo3j	74	16	test	test	NN
cord-024346-shauvo3j	74	17	sample	sample	NN
cord-024346-shauvo3j	74	18	-at	-at	:
cord-024346-shauvo3j	74	19	83	83	CD
cord-024346-shauvo3j	74	20	%	%	NN
cord-024346-shauvo3j	74	21	.	.	.
cord-024346-shauvo3j	75	1	None	none	NN
cord-024346-shauvo3j	75	2	of	of	IN
cord-024346-shauvo3j	75	3	the	the	DT
cord-024346-shauvo3j	75	4	other	other	JJ
cord-024346-shauvo3j	75	5	models	model	NNS
cord-024346-shauvo3j	75	6	were	be	VBD
cord-024346-shauvo3j	75	7	able	able	JJ
cord-024346-shauvo3j	75	8	to	to	TO
cord-024346-shauvo3j	75	9	surpass	surpass	VB
cord-024346-shauvo3j	75	10	this	this	DT
cord-024346-shauvo3j	75	11	figure	figure	NN
cord-024346-shauvo3j	75	12	.	.	.
cord-024346-shauvo3j	76	1	Data	datum	NNS
cord-024346-shauvo3j	76	2	on	on	IN
cord-024346-shauvo3j	76	3	accuracy	accuracy	NN
cord-024346-shauvo3j	76	4	and	and	CC
cord-024346-shauvo3j	76	5	epoch	epoch	NN
cord-024346-shauvo3j	76	6	error	error	NN
cord-024346-shauvo3j	76	7	are	be	VBP
cord-024346-shauvo3j	76	8	shown	show	VBN
cord-024346-shauvo3j	76	9	in	in	IN
cord-024346-shauvo3j	76	10	Fig	Fig	NNP
cord-024346-shauvo3j	76	11	.	.	.
cord-024346-shauvo3j	77	1	4	4	CD
cord-024346-shauvo3j	77	2	and	and	CC
cord-024346-shauvo3j	77	3	5	5	CD
cord-024346-shauvo3j	77	4	.	.	.
cord-024346-shauvo3j	78	1	If	if	IN
cord-024346-shauvo3j	78	2	you	-PRON-	PRP
cord-024346-shauvo3j	78	3	continue	continue	VBP
cord-024346-shauvo3j	78	4	to	to	TO
cord-024346-shauvo3j	78	5	study	study	VB
cord-024346-shauvo3j	78	6	for	for	IN
cord-024346-shauvo3j	78	7	more	more	JJR
cord-024346-shauvo3j	78	8	than	than	IN
cord-024346-shauvo3j	78	9	10	10	CD
cord-024346-shauvo3j	78	10	epochs	epoch	NNS
cord-024346-shauvo3j	78	11	,	,	,
cord-024346-shauvo3j	78	12	then	then	RB
cord-024346-shauvo3j	78	13	the	the	DT
cord-024346-shauvo3j	78	14	effect	effect	NN
cord-024346-shauvo3j	78	15	of	of	IN
cord-024346-shauvo3j	78	16	retraining	retraining	NN
cord-024346-shauvo3j	78	17	occurs	occur	VBZ
cord-024346-shauvo3j	78	18	:	:	:
cord-024346-shauvo3j	78	19	the	the	DT
cord-024346-shauvo3j	78	20	error	error	NN
cord-024346-shauvo3j	78	21	drops	drop	VBZ
cord-024346-shauvo3j	78	22	,	,	,
cord-024346-shauvo3j	78	23	and	and	CC
cord-024346-shauvo3j	78	24	accuracy	accuracy	NN
cord-024346-shauvo3j	78	25	increases	increase	VBZ
cord-024346-shauvo3j	78	26	only	only	RB
cord-024346-shauvo3j	78	27	on	on	IN
cord-024346-shauvo3j	78	28	training	training	NN
cord-024346-shauvo3j	78	29	samples	sample	NNS
cord-024346-shauvo3j	78	30	,	,	,
cord-024346-shauvo3j	78	31	but	but	CC
cord-024346-shauvo3j	78	32	not	not	RB
cord-024346-shauvo3j	78	33	on	on	IN
cord-024346-shauvo3j	78	34	test	test	NN
cord-024346-shauvo3j	78	35	ones	one	NNS
cord-024346-shauvo3j	78	36	.	.	.
cord-024346-shauvo3j	79	1	Figure	figure	NN
cord-024346-shauvo3j	79	2	6	6	CD
cord-024346-shauvo3j	79	3	shows	show	NNS
cord-024346-shauvo3j	79	4	examples	example	NNS
cord-024346-shauvo3j	79	5	of	of	IN
cord-024346-shauvo3j	79	6	images	image	NNS
cord-024346-shauvo3j	79	7	with	with	IN
cord-024346-shauvo3j	79	8	neural	neural	JJ
cord-024346-shauvo3j	79	9	network	network	NN
cord-024346-shauvo3j	79	10	boundaries	boundary	NNS
cord-024346-shauvo3j	79	11	.	.	.
cord-024346-shauvo3j	80	1	As	as	IN
cord-024346-shauvo3j	80	2	you	-PRON-	PRP
cord-024346-shauvo3j	80	3	can	can	MD
cord-024346-shauvo3j	80	4	see	see	VB
cord-024346-shauvo3j	80	5	from	from	IN
cord-024346-shauvo3j	80	6	the	the	DT
cord-024346-shauvo3j	80	7	images	image	NNS
cord-024346-shauvo3j	80	8	,	,	,
cord-024346-shauvo3j	80	9	not	not	RB
cord-024346-shauvo3j	80	10	all	all	PDT
cord-024346-shauvo3j	80	11	the	the	DT
cord-024346-shauvo3j	80	12	borders	border	NNS
cord-024346-shauvo3j	80	13	are	be	VBP
cord-024346-shauvo3j	80	14	closed	closed	JJ
cord-024346-shauvo3j	80	15	.	.	.
cord-024346-shauvo3j	81	1	The	the	DT
cord-024346-shauvo3j	81	2	boundary	boundary	JJ
cord-024346-shauvo3j	81	3	discontinuities	discontinuity	NNS
cord-024346-shauvo3j	81	4	are	be	VBP
cord-024346-shauvo3j	81	5	too	too	RB
cord-024346-shauvo3j	81	6	large	large	JJ
cord-024346-shauvo3j	81	7	to	to	TO
cord-024346-shauvo3j	81	8	be	be	VB
cord-024346-shauvo3j	81	9	closed	close	VBN
cord-024346-shauvo3j	81	10	using	use	VBG
cord-024346-shauvo3j	81	11	morphological	morphological	JJ
cord-024346-shauvo3j	81	12	operations	operation	NNS
cord-024346-shauvo3j	81	13	on	on	IN
cord-024346-shauvo3j	81	14	binary	binary	JJ
cord-024346-shauvo3j	81	15	masks	mask	NNS
cord-024346-shauvo3j	81	16	;	;	:
cord-024346-shauvo3j	81	17	however	however	RB
cord-024346-shauvo3j	81	18	,	,	,
cord-024346-shauvo3j	81	19	the	the	DT
cord-024346-shauvo3j	81	20	use	use	NN
cord-024346-shauvo3j	81	21	of	of	IN
cord-024346-shauvo3j	81	22	the	the	DT
cord-024346-shauvo3j	81	23	"	"	``
cord-024346-shauvo3j	81	24	watershed	watershed	NN
cord-024346-shauvo3j	81	25	"	"	''
cord-024346-shauvo3j	81	26	algorithm	algorithm	NN
cord-024346-shauvo3j	81	27	[	[	-LRB-
cord-024346-shauvo3j	81	28	8	8	CD
cord-024346-shauvo3j	81	29	]	]	-RRB-
cord-024346-shauvo3j	81	30	will	will	MD
cord-024346-shauvo3j	81	31	reduce	reduce	VB
cord-024346-shauvo3j	81	32	the	the	DT
cord-024346-shauvo3j	81	33	identification	identification	NN
cord-024346-shauvo3j	81	34	error	error	NN
cord-024346-shauvo3j	81	35	of	of	IN
cord-024346-shauvo3j	81	36	the	the	DT
cord-024346-shauvo3j	81	37	boundary	boundary	JJ
cord-024346-shauvo3j	81	38	points	point	NNS
cord-024346-shauvo3j	81	39	.	.	.
cord-024346-shauvo3j	82	1	In	in	IN
cord-024346-shauvo3j	82	2	this	this	DT
cord-024346-shauvo3j	82	3	work	work	NN
cord-024346-shauvo3j	82	4	,	,	,
cord-024346-shauvo3j	82	5	a	a	DT
cord-024346-shauvo3j	82	6	convolutional	convolutional	JJ
cord-024346-shauvo3j	82	7	neural	neural	JJ
cord-024346-shauvo3j	82	8	network	network	NN
cord-024346-shauvo3j	82	9	was	be	VBD
cord-024346-shauvo3j	82	10	developed	develop	VBN
cord-024346-shauvo3j	82	11	and	and	CC
cord-024346-shauvo3j	82	12	tested	test	VBN
cord-024346-shauvo3j	82	13	to	to	TO
cord-024346-shauvo3j	82	14	recognize	recognize	VB
cord-024346-shauvo3j	82	15	boundaries	boundary	NNS
cord-024346-shauvo3j	82	16	on	on	IN
cord-024346-shauvo3j	82	17	images	image	NNS
cord-024346-shauvo3j	82	18	of	of	IN
cord-024346-shauvo3j	82	19	crushed	crush	VBN
cord-024346-shauvo3j	82	20	ore	ore	NN
cord-024346-shauvo3j	82	21	stones	stone	NNS
cord-024346-shauvo3j	82	22	.	.	.
cord-024346-shauvo3j	83	1	For	for	IN
cord-024346-shauvo3j	83	2	the	the	DT
cord-024346-shauvo3j	83	3	task	task	NN
cord-024346-shauvo3j	83	4	of	of	IN
cord-024346-shauvo3j	83	5	constructing	construct	VBG
cord-024346-shauvo3j	83	6	a	a	DT
cord-024346-shauvo3j	83	7	convolutional	convolutional	JJ
cord-024346-shauvo3j	83	8	neural	neural	JJ
cord-024346-shauvo3j	83	9	network	network	NN
cord-024346-shauvo3j	83	10	model	model	NN
cord-024346-shauvo3j	83	11	,	,	,
cord-024346-shauvo3j	83	12	two	two	CD
cord-024346-shauvo3j	83	13	data	datum	NNS
cord-024346-shauvo3j	83	14	samples	sample	NNS
cord-024346-shauvo3j	83	15	were	be	VBD
cord-024346-shauvo3j	83	16	generated	generate	VBN
cord-024346-shauvo3j	83	17	:	:	:
cord-024346-shauvo3j	83	18	training	training	NN
cord-024346-shauvo3j	83	19	and	and	CC
cord-024346-shauvo3j	83	20	test	test	NN
cord-024346-shauvo3j	83	21	dataset	dataset	NN
cord-024346-shauvo3j	83	22	.	.	.
cord-024346-shauvo3j	84	1	When	when	WRB
cord-024346-shauvo3j	84	2	building	build	VBG
cord-024346-shauvo3j	84	3	the	the	DT
cord-024346-shauvo3j	84	4	model	model	NN
cord-024346-shauvo3j	84	5	,	,	,
cord-024346-shauvo3j	84	6	the	the	DT
cord-024346-shauvo3j	84	7	basic	basic	JJ
cord-024346-shauvo3j	84	8	version	version	NN
cord-024346-shauvo3j	84	9	of	of	IN
cord-024346-shauvo3j	84	10	the	the	DT
cord-024346-shauvo3j	84	11	convolutional	convolutional	JJ
cord-024346-shauvo3j	84	12	neural	neural	JJ
cord-024346-shauvo3j	84	13	network	network	NN
cord-024346-shauvo3j	84	14	structure	structure	NN
cord-024346-shauvo3j	84	15	was	be	VBD
cord-024346-shauvo3j	84	16	implemented	implement	VBN
cord-024346-shauvo3j	84	17	.	.	.
cord-024346-shauvo3j	85	1	In	in	IN
cord-024346-shauvo3j	85	2	order	order	NN
cord-024346-shauvo3j	85	3	to	to	TO
cord-024346-shauvo3j	85	4	improve	improve	VB
cord-024346-shauvo3j	85	5	the	the	DT
cord-024346-shauvo3j	85	6	quality	quality	NN
cord-024346-shauvo3j	85	7	of	of	IN
cord-024346-shauvo3j	85	8	model	model	NN
cord-024346-shauvo3j	85	9	recognition	recognition	NN
cord-024346-shauvo3j	85	10	,	,	,
cord-024346-shauvo3j	85	11	a	a	DT
cord-024346-shauvo3j	85	12	configuration	configuration	NN
cord-024346-shauvo3j	85	13	of	of	IN
cord-024346-shauvo3j	85	14	various	various	JJ
cord-024346-shauvo3j	85	15	models	model	NNS
cord-024346-shauvo3j	85	16	was	be	VBD
cord-024346-shauvo3j	85	17	devised	devise	VBN
cord-024346-shauvo3j	85	18	with	with	IN
cord-024346-shauvo3j	85	19	deviations	deviation	NNS
cord-024346-shauvo3j	85	20	from	from	IN
cord-024346-shauvo3j	85	21	the	the	DT
cord-024346-shauvo3j	85	22	basic	basic	JJ
cord-024346-shauvo3j	85	23	architecture	architecture	NN
cord-024346-shauvo3j	85	24	.	.	.
cord-024346-shauvo3j	86	1	An	an	DT
cord-024346-shauvo3j	86	2	algorithm	algorithm	NN
cord-024346-shauvo3j	86	3	for	for	IN
cord-024346-shauvo3j	86	4	training	training	NN
cord-024346-shauvo3j	86	5	and	and	CC
cord-024346-shauvo3j	86	6	searching	search	VBG
cord-024346-shauvo3j	86	7	for	for	IN
cord-024346-shauvo3j	86	8	the	the	DT
cord-024346-shauvo3j	86	9	best	good	JJS
cord-024346-shauvo3j	86	10	model	model	NN
cord-024346-shauvo3j	86	11	by	by	IN
cord-024346-shauvo3j	86	12	enumerating	enumerate	VBG
cord-024346-shauvo3j	86	13	configurations	configuration	NNS
cord-024346-shauvo3j	86	14	was	be	VBD
cord-024346-shauvo3j	86	15	implemented	implement	VBN
cord-024346-shauvo3j	86	16	.	.	.
cord-024346-shauvo3j	87	1	In	in	IN
cord-024346-shauvo3j	87	2	the	the	DT
cord-024346-shauvo3j	87	3	course	course	NN
cord-024346-shauvo3j	87	4	of	of	IN
cord-024346-shauvo3j	87	5	the	the	DT
cord-024346-shauvo3j	87	6	research	research	NN
cord-024346-shauvo3j	87	7	,	,	,
cord-024346-shauvo3j	87	8	it	-PRON-	PRP
cord-024346-shauvo3j	87	9	was	be	VBD
cord-024346-shauvo3j	87	10	found	find	VBN
cord-024346-shauvo3j	87	11	that	that	IN
cord-024346-shauvo3j	87	12	the	the	DT
cord-024346-shauvo3j	87	13	basic	basic	JJ
cord-024346-shauvo3j	87	14	model	model	NN
cord-024346-shauvo3j	87	15	has	have	VBZ
cord-024346-shauvo3j	87	16	the	the	DT
cord-024346-shauvo3j	87	17	best	good	JJS
cord-024346-shauvo3j	87	18	quality	quality	NN
cord-024346-shauvo3j	87	19	for	for	IN
cord-024346-shauvo3j	87	20	recognizing	recognize	VBG
cord-024346-shauvo3j	87	21	boundary	boundary	JJ
cord-024346-shauvo3j	87	22	points	point	NNS
cord-024346-shauvo3j	87	23	.	.	.
cord-024346-shauvo3j	88	1	It	-PRON-	PRP
cord-024346-shauvo3j	88	2	shows	show	VBZ
cord-024346-shauvo3j	88	3	the	the	DT
cord-024346-shauvo3j	88	4	accuracy	accuracy	NN
cord-024346-shauvo3j	88	5	of	of	IN
cord-024346-shauvo3j	88	6	the	the	DT
cord-024346-shauvo3j	88	7	predictions	prediction	NNS
cord-024346-shauvo3j	88	8	for	for	IN
cord-024346-shauvo3j	88	9	the	the	DT
cord-024346-shauvo3j	88	10	targeted	target	VBN
cord-024346-shauvo3j	88	11	class	class	NN
cord-024346-shauvo3j	88	12	at	at	IN
cord-024346-shauvo3j	88	13	83	83	CD
cord-024346-shauvo3j	88	14	%	%	NN
cord-024346-shauvo3j	88	15	.	.	.
cord-024346-shauvo3j	89	1	Based	base	VBN
cord-024346-shauvo3j	89	2	on	on	IN
cord-024346-shauvo3j	89	3	the	the	DT
cord-024346-shauvo3j	89	4	drawn	draw	VBN
cord-024346-shauvo3j	89	5	borders	border	NNS
cord-024346-shauvo3j	89	6	on	on	IN
cord-024346-shauvo3j	89	7	the	the	DT
cord-024346-shauvo3j	89	8	test	test	NN
cord-024346-shauvo3j	89	9	images	image	NNS
cord-024346-shauvo3j	89	10	,	,	,
cord-024346-shauvo3j	89	11	it	-PRON-	PRP
cord-024346-shauvo3j	89	12	can	can	MD
cord-024346-shauvo3j	89	13	be	be	VB
cord-024346-shauvo3j	89	14	concluded	conclude	VBN
cord-024346-shauvo3j	89	15	that	that	IN
cord-024346-shauvo3j	89	16	the	the	DT
cord-024346-shauvo3j	89	17	convolutional	convolutional	JJ
cord-024346-shauvo3j	89	18	neural	neural	JJ
cord-024346-shauvo3j	89	19	network	network	NN
cord-024346-shauvo3j	89	20	is	be	VBZ
cord-024346-shauvo3j	89	21	able	able	JJ
cord-024346-shauvo3j	89	22	to	to	TO
cord-024346-shauvo3j	89	23	correctly	correctly	RB
cord-024346-shauvo3j	89	24	identify	identify	VB
cord-024346-shauvo3j	89	25	the	the	DT
cord-024346-shauvo3j	89	26	boundary	boundary	JJ
cord-024346-shauvo3j	89	27	points	point	NNS
cord-024346-shauvo3j	89	28	with	with	IN
cord-024346-shauvo3j	89	29	a	a	DT
cord-024346-shauvo3j	89	30	high	high	JJ
cord-024346-shauvo3j	89	31	probability	probability	NN
cord-024346-shauvo3j	89	32	.	.	.
cord-024346-shauvo3j	90	1	It	-PRON-	PRP
cord-024346-shauvo3j	90	2	rarely	rarely	RB
cord-024346-shauvo3j	90	3	makes	make	VBZ
cord-024346-shauvo3j	90	4	mistakes	mistake	NNS
cord-024346-shauvo3j	90	5	for	for	IN
cord-024346-shauvo3j	90	6	cases	case	NNS
cord-024346-shauvo3j	90	7	when	when	WRB
cord-024346-shauvo3j	90	8	there	there	EX
cord-024346-shauvo3j	90	9	is	be	VBZ
cord-024346-shauvo3j	90	10	no	no	DT
cord-024346-shauvo3j	90	11	boundary	boundary	JJ
cord-024346-shauvo3j	90	12	(	(	-LRB-
cord-024346-shauvo3j	90	13	false	false	JJ
cord-024346-shauvo3j	90	14	positive	positive	JJ
cord-024346-shauvo3j	90	15	)	)	-RRB-
cord-024346-shauvo3j	90	16	,	,	,
cord-024346-shauvo3j	90	17	but	but	CC
cord-024346-shauvo3j	90	18	often	often	RB
cord-024346-shauvo3j	90	19	makes	make	VBZ
cord-024346-shauvo3j	90	20	mistakes	mistake	NNS
cord-024346-shauvo3j	90	21	when	when	WRB
cord-024346-shauvo3j	90	22	recognizing	recognize	VBG
cord-024346-shauvo3j	90	23	real	real	JJ
cord-024346-shauvo3j	90	24	boundary	boundary	JJ
cord-024346-shauvo3j	90	25	points	point	NNS
cord-024346-shauvo3j	90	26	(	(	-LRB-
cord-024346-shauvo3j	90	27	false	false	JJ
cord-024346-shauvo3j	90	28	negative	negative	JJ
cord-024346-shauvo3j	90	29	)	)	-RRB-
cord-024346-shauvo3j	90	30	.	.	.
cord-024346-shauvo3j	91	1	The	the	DT
cord-024346-shauvo3j	91	2	boundary	boundary	NN
cord-024346-shauvo3j	91	3	breaks	break	NNS
cord-024346-shauvo3j	91	4	are	be	VBP
cord-024346-shauvo3j	91	5	too	too	RB
cord-024346-shauvo3j	91	6	large	large	JJ
cord-024346-shauvo3j	91	7	to	to	TO
cord-024346-shauvo3j	91	8	be	be	VB
cord-024346-shauvo3j	91	9	closed	close	VBN
cord-024346-shauvo3j	91	10	using	use	VBG
cord-024346-shauvo3j	91	11	morphological	morphological	JJ
cord-024346-shauvo3j	91	12	operations	operation	NNS
cord-024346-shauvo3j	91	13	on	on	IN
cord-024346-shauvo3j	91	14	binary	binary	JJ
cord-024346-shauvo3j	91	15	masks	mask	NNS
cord-024346-shauvo3j	91	16	,	,	,
cord-024346-shauvo3j	91	17	however	however	RB
cord-024346-shauvo3j	91	18	,	,	,
cord-024346-shauvo3j	91	19	the	the	DT
cord-024346-shauvo3j	91	20	use	use	NN
cord-024346-shauvo3j	91	21	of	of	IN
cord-024346-shauvo3j	91	22	the	the	DT
cord-024346-shauvo3j	91	23	"	"	``
cord-024346-shauvo3j	91	24	watershed	watershed	NN
cord-024346-shauvo3j	91	25	"	"	''
cord-024346-shauvo3j	91	26	algorithm	algorithm	NN
cord-024346-shauvo3j	91	27	will	will	MD
cord-024346-shauvo3j	91	28	reduce	reduce	VB
cord-024346-shauvo3j	91	29	the	the	DT
cord-024346-shauvo3j	91	30	identification	identification	NN
cord-024346-shauvo3j	91	31	error	error	NN
cord-024346-shauvo3j	91	32	for	for	IN
cord-024346-shauvo3j	91	33	boundary	boundary	JJ
cord-024346-shauvo3j	91	34	points	point	NNS
cord-024346-shauvo3j	91	35	.	.	.
cord-024346-shauvo3j	92	1	Funding	funding	NN
cord-024346-shauvo3j	92	2	.	.	.
cord-024346-shauvo3j	93	1	The	the	DT
cord-024346-shauvo3j	93	2	work	work	NN
cord-024346-shauvo3j	93	3	was	be	VBD
cord-024346-shauvo3j	93	4	performed	perform	VBN
cord-024346-shauvo3j	93	5	under	under	IN
cord-024346-shauvo3j	93	6	state	state	NN
cord-024346-shauvo3j	93	7	contract	contract	NN
cord-024346-shauvo3j	93	8	3170ΓC1/48564	3170γc1/48564	CD
cord-024346-shauvo3j	93	9	,	,	,
cord-024346-shauvo3j	93	10	grant	grant	NN
cord-024346-shauvo3j	93	11	from	from	IN
cord-024346-shauvo3j	93	12	the	the	DT
cord-024346-shauvo3j	93	13	FASIE	FASIE	NNP
cord-024346-shauvo3j	93	14	.	.	.
cord-024346-shauvo3j	94	1	Keras	Keras	NNP
cord-024346-shauvo3j	94	2	:	:	:
cord-024346-shauvo3j	95	1	The	the	DT
cord-024346-shauvo3j	95	2	python	python	NN
cord-024346-shauvo3j	95	3	deep	deep	JJ
cord-024346-shauvo3j	95	4	learning	learning	NN
cord-024346-shauvo3j	95	5	library	library	NN
cord-024346-shauvo3j	95	6	Deep	Deep	NNP
cord-024346-shauvo3j	95	7	Learning	learn	VBG
cord-024346-shauvo3j	95	8	with	with	IN
cord-024346-shauvo3j	95	9	Python	Python	NNP
cord-024346-shauvo3j	95	10	,	,	,
cord-024346-shauvo3j	95	11	1st	1st	JJ
cord-024346-shauvo3j	95	12	edn	edn	NNP
cord-024346-shauvo3j	95	13	Machine	Machine	NNP
cord-024346-shauvo3j	95	14	Learning	Learning	NNP
cord-024346-shauvo3j	95	15	:	:	:
cord-024346-shauvo3j	96	1	The	the	DT
cord-024346-shauvo3j	96	2	Art	Art	NNP
cord-024346-shauvo3j	96	3	and	and	CC
cord-024346-shauvo3j	96	4	Science	Science	NNP
cord-024346-shauvo3j	96	5	of	of	IN
cord-024346-shauvo3j	96	6	Algorithms	Algorithms	NNP
cord-024346-shauvo3j	96	7	that	that	WDT
cord-024346-shauvo3j	96	8	Make	make	VBP
cord-024346-shauvo3j	96	9	Sense	sense	NN
cord-024346-shauvo3j	96	10	of	of	IN
cord-024346-shauvo3j	96	11	Data	Data	NNP
cord-024346-shauvo3j	96	12	Digital	Digital	NNP
cord-024346-shauvo3j	96	13	Image	image	NN
cord-024346-shauvo3j	97	1	Processing	process	VBG
cord-024346-shauvo3j	97	2	Hands	Hands	NNPS
cord-024346-shauvo3j	97	3	-	-	HYPH
cord-024346-shauvo3j	97	4	On	on	IN
cord-024346-shauvo3j	97	5	Machine	machine	NN
cord-024346-shauvo3j	97	6	Learning	learn	VBG
cord-024346-shauvo3j	97	7	with	with	IN
cord-024346-shauvo3j	97	8	Scikit	Scikit	NNP
cord-024346-shauvo3j	97	9	-	-	HYPH
cord-024346-shauvo3j	97	10	Learn	Learn	NNP
cord-024346-shauvo3j	97	11	and	and	CC
cord-024346-shauvo3j	97	12	TensorFlow	TensorFlow	NNP
cord-024346-shauvo3j	97	13	:	:	:
cord-024346-shauvo3j	97	14	Concepts	concept	NNS
cord-024346-shauvo3j	97	15	,	,	,
cord-024346-shauvo3j	97	16	Tools	Tools	NNPS
cord-024346-shauvo3j	97	17	,	,	,
cord-024346-shauvo3j	97	18	and	and	CC
cord-024346-shauvo3j	97	19	Techniques	technique	NNS
cord-024346-shauvo3j	97	20	to	to	TO
cord-024346-shauvo3j	97	21	Build	build	VB
cord-024346-shauvo3j	97	22	Intelligent	Intelligent	NNP
cord-024346-shauvo3j	97	23	Systems	Systems	NNPS
cord-024346-shauvo3j	97	24	Deep	Deep	NNP
cord-024346-shauvo3j	97	25	learning	learn	VBG
cord-024346-shauvo3j	97	26	with	with	IN
cord-024346-shauvo3j	97	27	Keras	Keras	NNP
cord-024346-shauvo3j	97	28	:	:	:
cord-024346-shauvo3j	98	1	Implement	implement	VB
cord-024346-shauvo3j	98	2	Neural	Neural	NNP
cord-024346-shauvo3j	98	3	Networks	Networks	NNP
cord-024346-shauvo3j	98	4	with	with	IN
cord-024346-shauvo3j	98	5	Keras	Keras	NNP
cord-024346-shauvo3j	98	6	on	on	IN
cord-024346-shauvo3j	98	7	Theano	Theano	NNP
cord-024346-shauvo3j	98	8	and	and	CC
cord-024346-shauvo3j	98	9	TensorFlow	TensorFlow	NNP
cord-024346-shauvo3j	98	10	Comprehensive	Comprehensive	NNP
cord-024346-shauvo3j	98	11	guide	guide	NN
cord-024346-shauvo3j	98	12	to	to	IN
cord-024346-shauvo3j	98	13	convolutional	convolutional	JJ
cord-024346-shauvo3j	98	14	neural	neural	JJ
cord-024346-shauvo3j	98	15	networks	network	NNS
cord-024346-shauvo3j	99	1	-the	-the	NFP
cord-024346-shauvo3j	100	1	eli5	eli5	JJ
cord-024346-shauvo3j	100	2	way	way	NNP
cord-024346-shauvo3j	100	3	Image	Image	NNP
cord-024346-shauvo3j	100	4	Processing	Processing	NNP
cord-024346-shauvo3j	100	5	,	,	,
cord-024346-shauvo3j	100	6	Analysis	Analysis	NNP
cord-024346-shauvo3j	100	7	and	and	CC
cord-024346-shauvo3j	100	8	Machine	Machine	NNP
cord-024346-shauvo3j	100	9	Vision	Vision	NNP
cord-024346-shauvo3j	100	10	Identifying	identifying	NN
cord-024346-shauvo3j	100	11	,	,	,
cord-024346-shauvo3j	100	12	visualizing	visualize	VBG
cord-024346-shauvo3j	100	13	,	,	,
cord-024346-shauvo3j	100	14	and	and	CC
cord-024346-shauvo3j	100	15	comparing	compare	VBG
cord-024346-shauvo3j	100	16	regions	region	NNS
cord-024346-shauvo3j	100	17	in	in	IN
cord-024346-shauvo3j	100	18	irregularly	irregularly	RB
cord-024346-shauvo3j	100	19	spaced	space	VBN
cord-024346-shauvo3j	100	20	3D	3D	NNP
cord-024346-shauvo3j	100	21	surface	surface	NN
cord-024346-shauvo3j	100	22	data	datum	NNS
cord-024346-shauvo3j	100	23	Python	Python	NNP
cord-024346-shauvo3j	100	24	Data	Data	NNP
cord-024346-shauvo3j	100	25	Science	Science	NNP
cord-024346-shauvo3j	100	26	Handbook	Handbook	NNP
cord-024346-shauvo3j	100	27	:	:	:
cord-024346-shauvo3j	101	1	Essential	Essential	NNP
cord-024346-shauvo3j	101	2	Tools	tool	NNS
cord-024346-shauvo3j	101	3	for	for	IN
cord-024346-shauvo3j	101	4	Working	Working	NNP
cord-024346-shauvo3j	101	5	with	with	IN
cord-024346-shauvo3j	101	6	Data	Data	NNP
cord-024346-shauvo3j	101	7	,	,	,
cord-024346-shauvo3j	101	8	1st	1st	JJ
cord-024346-shauvo3j	101	9	edn	edn	NN