id	sid	tid	token	lemma	pos
app01-10214	1	1	acta	acta	PROPN
app01-10214	1	2	polytechnica	polytechnica	PROPN
app01-10214	1	3	ctu	ctu	NOUN
app01-10214	1	4	proceedings	proceeding	NOUN
app01-10214	1	5	https://doi.org/10.14311/app.2024.49.0085	https://doi.org/10.14311/app.2024.49.0085	ADP
app01-10214	1	6	acta	acta	PROPN
app01-10214	1	7	polytechnica	polytechnica	PROPN
app01-10214	1	8	ctu	ctu	NOUN
app01-10214	1	9	proceedings	proceeding	NOUN
app01-10214	1	10	49:85–91	49:85–91	NUM
app01-10214	1	11	,	,	PUNCT
app01-10214	1	12	2024	2024	NUM
app01-10214	1	13	©	©	ADP
app01-10214	1	14	2024	2024	NUM
app01-10214	1	15	the	the	DET
app01-10214	1	16	author(s	author(s	NOUN
app01-10214	1	17	)	)	PUNCT
app01-10214	1	18	.	.	PUNCT
app01-10214	2	1	licensed	license	VERB
app01-10214	2	2	under	under	ADP
app01-10214	2	3	a	a	DET
app01-10214	2	4	cc	cc	NOUN
app01-10214	2	5	-	-	PUNCT
app01-10214	2	6	by	by	ADP
app01-10214	2	7	4.0	4.0	NUM
app01-10214	2	8	licence	licence	NOUN
app01-10214	2	9	published	publish	VERB
app01-10214	2	10	by	by	ADP
app01-10214	2	11	the	the	DET
app01-10214	2	12	czech	czech	PROPN
app01-10214	2	13	technical	technical	PROPN
app01-10214	2	14	university	university	PROPN
app01-10214	2	15	in	in	ADP
app01-10214	2	16	prague	prague	PROPN
app01-10214	2	17	reconstruction	reconstruction	NOUN
app01-10214	2	18	of	of	ADP
app01-10214	2	19	concrete	concrete	ADJ
app01-10214	2	20	morphology	morphology	NOUN
app01-10214	2	21	using	use	VERB
app01-10214	2	22	deep	deep	ADJ
app01-10214	2	23	learning	learning	NOUN
app01-10214	2	24	ondřej	ondřej	NOUN
app01-10214	2	25	šperl	šperl	PROPN
app01-10214	2	26	,	,	PUNCT
app01-10214	2	27	jan	jan	PROPN
app01-10214	2	28	sýkora∗	sýkora∗	PROPN
app01-10214	2	29	czech	czech	PROPN
app01-10214	2	30	technical	technical	PROPN
app01-10214	2	31	university	university	PROPN
app01-10214	2	32	in	in	ADP
app01-10214	2	33	prague	prague	PROPN
app01-10214	2	34	,	,	PUNCT
app01-10214	2	35	faculty	faculty	NOUN
app01-10214	2	36	of	of	ADP
app01-10214	2	37	civil	civil	ADJ
app01-10214	2	38	engineering	engineering	NOUN
app01-10214	2	39	,	,	PUNCT
app01-10214	2	40	department	department	NOUN
app01-10214	2	41	of	of	ADP
app01-10214	2	42	mechanics	mechanic	NOUN
app01-10214	2	43	,	,	PUNCT
app01-10214	2	44	thákurova	thákurova	X
app01-10214	2	45	7	7	NUM
app01-10214	2	46	,	,	PUNCT
app01-10214	2	47	160	160	NUM
app01-10214	2	48	00	00	NUM
app01-10214	2	49	prague	prague	PROPN
app01-10214	2	50	,	,	PUNCT
app01-10214	2	51	czech	czech	PROPN
app01-10214	2	52	republic	republic	NOUN
app01-10214	2	53	∗	∗	NOUN
app01-10214	2	54	corresponding	correspond	VERB
app01-10214	2	55	author	author	NOUN
app01-10214	2	56	:	:	PUNCT
app01-10214	2	57	jan.sykora.1@fsv.cvut.cz	jan.sykora.1@fsv.cvut.cz	NOUN
app01-10214	2	58	abstract	abstract	ADJ
app01-10214	2	59	.	.	PUNCT
app01-10214	3	1	in	in	ADP
app01-10214	3	2	this	this	DET
app01-10214	3	3	contribution	contribution	NOUN
app01-10214	3	4	,	,	PUNCT
app01-10214	3	5	the	the	DET
app01-10214	3	6	concrete	concrete	ADJ
app01-10214	3	7	morphology	morphology	NOUN
app01-10214	3	8	is	be	AUX
app01-10214	3	9	reconstructed	reconstruct	VERB
app01-10214	3	10	with	with	ADP
app01-10214	3	11	a	a	DET
app01-10214	3	12	simple	simple	ADJ
app01-10214	3	13	algorithm	algorithm	NOUN
app01-10214	3	14	selecting	select	VERB
app01-10214	3	15	a	a	DET
app01-10214	3	16	pixel	pixel	NOUN
app01-10214	3	17	value	value	NOUN
app01-10214	3	18	based	base	VERB
app01-10214	3	19	on	on	ADP
app01-10214	3	20	the	the	DET
app01-10214	3	21	small	small	ADJ
app01-10214	3	22	set	set	NOUN
app01-10214	3	23	of	of	ADP
app01-10214	3	24	surrounding	surround	VERB
app01-10214	3	25	pixels	pixel	NOUN
app01-10214	3	26	.	.	PUNCT
app01-10214	4	1	a	a	DET
app01-10214	4	2	deep	deep	ADJ
app01-10214	4	3	neural	neural	ADJ
app01-10214	4	4	network	network	NOUN
app01-10214	4	5	(	(	PUNCT
app01-10214	4	6	dnn	dnn	PROPN
app01-10214	4	7	)	)	PUNCT
app01-10214	4	8	is	be	AUX
app01-10214	4	9	used	use	VERB
app01-10214	4	10	as	as	ADP
app01-10214	4	11	a	a	DET
app01-10214	4	12	classifier	classifier	NOUN
app01-10214	4	13	,	,	PUNCT
app01-10214	4	14	and	and	CCONJ
app01-10214	4	15	the	the	DET
app01-10214	4	16	authors	author	NOUN
app01-10214	4	17	focus	focus	VERB
app01-10214	4	18	on	on	ADP
app01-10214	4	19	studying	study	VERB
app01-10214	4	20	different	different	ADJ
app01-10214	4	21	dnn	dnn	PROPN
app01-10214	4	22	architectures	architecture	NOUN
app01-10214	4	23	.	.	PUNCT
app01-10214	5	1	the	the	DET
app01-10214	5	2	performance	performance	NOUN
app01-10214	5	3	of	of	ADP
app01-10214	5	4	the	the	DET
app01-10214	5	5	proposed	propose	VERB
app01-10214	5	6	algorithm	algorithm	NOUN
app01-10214	5	7	is	be	AUX
app01-10214	5	8	evaluated	evaluate	VERB
app01-10214	5	9	on	on	ADP
app01-10214	5	10	several	several	ADJ
app01-10214	5	11	statistical	statistical	ADJ
app01-10214	5	12	descriptors	descriptor	NOUN
app01-10214	5	13	and	and	CCONJ
app01-10214	5	14	the	the	DET
app01-10214	5	15	grain	grain	NOUN
app01-10214	5	16	size	size	NOUN
app01-10214	5	17	distribution	distribution	NOUN
app01-10214	5	18	curve	curve	NOUN
app01-10214	5	19	.	.	PUNCT
app01-10214	6	1	keywords	keyword	NOUN
app01-10214	6	2	:	:	PUNCT
app01-10214	6	3	reconstruction	reconstruction	NOUN
app01-10214	6	4	,	,	PUNCT
app01-10214	6	5	concrete	concrete	ADJ
app01-10214	6	6	,	,	PUNCT
app01-10214	6	7	deep	deep	ADJ
app01-10214	6	8	learning	learning	NOUN
app01-10214	6	9	,	,	PUNCT
app01-10214	6	10	convolutional	convolutional	ADJ
app01-10214	6	11	neural	neural	ADJ
app01-10214	6	12	network	network	NOUN
app01-10214	6	13	.	.	PUNCT
app01-10214	7	1	1	1	X
app01-10214	7	2	.	.	X
app01-10214	7	3	introduction	introduction	VERB
app01-10214	7	4	the	the	DET
app01-10214	7	5	reconstruction	reconstruction	NOUN
app01-10214	7	6	of	of	ADP
app01-10214	7	7	material	material	NOUN
app01-10214	7	8	morphology	morphology	NOUN
app01-10214	7	9	has	have	AUX
app01-10214	7	10	become	become	VERB
app01-10214	7	11	an	an	DET
app01-10214	7	12	essential	essential	ADJ
app01-10214	7	13	part	part	NOUN
app01-10214	7	14	of	of	ADP
app01-10214	7	15	the	the	DET
app01-10214	7	16	numerical	numerical	ADJ
app01-10214	7	17	computational	computational	ADJ
app01-10214	7	18	modeling	modeling	NOUN
app01-10214	7	19	of	of	ADP
app01-10214	7	20	heterogeneous	heterogeneous	ADJ
app01-10214	7	21	materials	material	NOUN
app01-10214	7	22	.	.	PUNCT
app01-10214	8	1	the	the	DET
app01-10214	8	2	first	first	ADJ
app01-10214	8	3	reconstruction	reconstruction	NOUN
app01-10214	8	4	algorithms	algorithm	NOUN
app01-10214	8	5	employed	employ	VERB
app01-10214	8	6	optimization	optimization	NOUN
app01-10214	8	7	routines	routine	NOUN
app01-10214	8	8	to	to	PART
app01-10214	8	9	minimize	minimize	VERB
app01-10214	8	10	selected	select	VERB
app01-10214	8	11	statistical	statistical	ADJ
app01-10214	8	12	descriptors	descriptor	NOUN
app01-10214	8	13	,	,	PUNCT
app01-10214	8	14	see	see	VERB
app01-10214	8	15	[	[	X
app01-10214	8	16	1–4	1–4	NOUN
app01-10214	8	17	]	]	X
app01-10214	8	18	.	.	PUNCT
app01-10214	9	1	the	the	DET
app01-10214	9	2	drawback	drawback	NOUN
app01-10214	9	3	of	of	ADP
app01-10214	9	4	such	such	DET
app01-10214	9	5	an	an	DET
app01-10214	9	6	approach	approach	NOUN
app01-10214	9	7	is	be	AUX
app01-10214	9	8	the	the	DET
app01-10214	9	9	exhaustive	exhaustive	ADJ
app01-10214	9	10	computational	computational	ADJ
app01-10214	9	11	time	time	NOUN
app01-10214	9	12	caused	cause	VERB
app01-10214	9	13	by	by	ADP
app01-10214	9	14	sequential	sequential	ADJ
app01-10214	9	15	pixel	pixel	PROPN
app01-10214	9	16	-	-	PUNCT
app01-10214	9	17	bypixel	bypixel	ADJ
app01-10214	9	18	replacement	replacement	NOUN
app01-10214	9	19	with	with	ADP
app01-10214	9	20	subsequent	subsequent	ADJ
app01-10214	9	21	evaluation	evaluation	NOUN
app01-10214	9	22	of	of	ADP
app01-10214	9	23	statistical	statistical	ADJ
app01-10214	9	24	descriptors	descriptor	NOUN
app01-10214	9	25	.	.	PUNCT
app01-10214	10	1	the	the	DET
app01-10214	10	2	second	second	ADJ
app01-10214	10	3	strategy	strategy	NOUN
app01-10214	10	4	concentrated	concentrate	VERB
app01-10214	10	5	on	on	ADP
app01-10214	10	6	material	material	ADJ
app01-10214	10	7	description	description	NOUN
app01-10214	10	8	using	use	VERB
app01-10214	10	9	random	random	ADJ
app01-10214	10	10	fields	field	NOUN
app01-10214	10	11	with	with	ADP
app01-10214	10	12	optimized	optimize	VERB
app01-10214	10	13	image	image	NOUN
app01-10214	10	14	-	-	PUNCT
app01-10214	10	15	based	base	VERB
app01-10214	10	16	correlation	correlation	NOUN
app01-10214	10	17	kernels	kernel	NOUN
app01-10214	10	18	,	,	PUNCT
app01-10214	10	19	see	see	VERB
app01-10214	10	20	[	[	X
app01-10214	10	21	5	5	NUM
app01-10214	10	22	]	]	PUNCT
app01-10214	10	23	.	.	PUNCT
app01-10214	11	1	this	this	DET
app01-10214	11	2	method	method	NOUN
app01-10214	11	3	dramatically	dramatically	ADV
app01-10214	11	4	reduces	reduce	VERB
app01-10214	11	5	the	the	DET
app01-10214	11	6	dimensionality	dimensionality	NOUN
app01-10214	11	7	of	of	ADP
app01-10214	11	8	the	the	DET
app01-10214	11	9	problem	problem	NOUN
app01-10214	11	10	[	[	X
app01-10214	11	11	6	6	NUM
app01-10214	11	12	]	]	PUNCT
app01-10214	11	13	,	,	PUNCT
app01-10214	11	14	however	however	ADV
app01-10214	11	15	,	,	PUNCT
app01-10214	11	16	it	it	PRON
app01-10214	11	17	has	have	VERB
app01-10214	11	18	the	the	DET
app01-10214	11	19	disadvantage	disadvantage	NOUN
app01-10214	11	20	of	of	ADP
app01-10214	11	21	preserving	preserve	VERB
app01-10214	11	22	maximal	maximal	ADJ
app01-10214	11	23	second	second	ADJ
app01-10214	11	24	-	-	PUNCT
app01-10214	11	25	order	order	NOUN
app01-10214	11	26	statistical	statistical	ADJ
app01-10214	11	27	moments	moment	NOUN
app01-10214	11	28	.	.	PUNCT
app01-10214	12	1	the	the	DET
app01-10214	12	2	last	last	ADJ
app01-10214	12	3	approach	approach	NOUN
app01-10214	12	4	is	be	AUX
app01-10214	12	5	texture	texture	ADJ
app01-10214	12	6	synthesis	synthesis	NOUN
app01-10214	12	7	,	,	PUNCT
app01-10214	12	8	which	which	PRON
app01-10214	12	9	exploits	exploit	VERB
app01-10214	12	10	the	the	DET
app01-10214	12	11	relatively	relatively	ADV
app01-10214	12	12	simple	simple	ADJ
app01-10214	12	13	principle	principle	NOUN
app01-10214	12	14	of	of	ADP
app01-10214	12	15	texture	texture	ADJ
app01-10214	12	16	locality	locality	NOUN
app01-10214	12	17	and	and	CCONJ
app01-10214	12	18	stationarity	stationarity	NOUN
app01-10214	12	19	for	for	ADP
app01-10214	12	20	material	material	NOUN
app01-10214	12	21	reconstruction	reconstruction	NOUN
app01-10214	12	22	,	,	PUNCT
app01-10214	12	23	see	see	VERB
app01-10214	12	24	[	[	X
app01-10214	12	25	7–9	7–9	NOUN
app01-10214	12	26	]	]	X
app01-10214	12	27	.	.	PUNCT
app01-10214	13	1	locality	locality	NOUN
app01-10214	13	2	means	mean	VERB
app01-10214	13	3	that	that	SCONJ
app01-10214	13	4	a	a	DET
app01-10214	13	5	random	random	ADJ
app01-10214	13	6	pixel	pixel	NOUN
app01-10214	13	7	inside	inside	ADP
app01-10214	13	8	the	the	DET
app01-10214	13	9	texture	texture	NOUN
app01-10214	13	10	is	be	AUX
app01-10214	13	11	related	relate	VERB
app01-10214	13	12	only	only	ADV
app01-10214	13	13	to	to	ADP
app01-10214	13	14	a	a	DET
app01-10214	13	15	small	small	ADJ
app01-10214	13	16	set	set	NOUN
app01-10214	13	17	of	of	ADP
app01-10214	13	18	surrounding	surround	VERB
app01-10214	13	19	pixels	pixel	NOUN
app01-10214	13	20	(	(	PUNCT
app01-10214	13	21	see	see	VERB
app01-10214	13	22	[	[	X
app01-10214	13	23	10	10	NUM
app01-10214	13	24	]	]	NUM
app01-10214	13	25	)	)	PUNCT
app01-10214	13	26	,	,	PUNCT
app01-10214	13	27	and	and	CCONJ
app01-10214	13	28	stationarity	stationarity	NOUN
app01-10214	13	29	can	can	AUX
app01-10214	13	30	be	be	AUX
app01-10214	13	31	explained	explain	VERB
app01-10214	13	32	by	by	ADP
app01-10214	13	33	the	the	DET
app01-10214	13	34	following	follow	VERB
app01-10214	13	35	example	example	NOUN
app01-10214	13	36	.	.	PUNCT
app01-10214	14	1	assume	assume	VERB
app01-10214	14	2	a	a	DET
app01-10214	14	3	movable	movable	ADJ
app01-10214	14	4	window	window	NOUN
app01-10214	14	5	placed	place	VERB
app01-10214	14	6	in	in	ADP
app01-10214	14	7	different	different	ADJ
app01-10214	14	8	positions	position	NOUN
app01-10214	14	9	in	in	ADP
app01-10214	14	10	the	the	DET
app01-10214	14	11	texture	texture	NOUN
app01-10214	14	12	.	.	PUNCT
app01-10214	15	1	the	the	DET
app01-10214	15	2	regions	region	NOUN
app01-10214	15	3	of	of	ADP
app01-10214	15	4	texture	texture	NOUN
app01-10214	15	5	marked	mark	VERB
app01-10214	15	6	by	by	ADP
app01-10214	15	7	the	the	DET
app01-10214	15	8	movable	movable	ADJ
app01-10214	15	9	window	window	NOUN
app01-10214	15	10	seem	seem	VERB
app01-10214	15	11	to	to	PART
app01-10214	15	12	be	be	AUX
app01-10214	15	13	always	always	ADV
app01-10214	15	14	similar	similar	ADJ
app01-10214	15	15	contrary	contrary	ADV
app01-10214	15	16	to	to	ADP
app01-10214	15	17	the	the	DET
app01-10214	15	18	situation	situation	NOUN
app01-10214	15	19	of	of	ADP
app01-10214	15	20	the	the	DET
app01-10214	15	21	general	general	ADJ
app01-10214	15	22	image	image	NOUN
app01-10214	15	23	,	,	PUNCT
app01-10214	15	24	where	where	SCONJ
app01-10214	15	25	the	the	DET
app01-10214	15	26	observed	observed	ADJ
app01-10214	15	27	regions	region	NOUN
app01-10214	15	28	are	be	AUX
app01-10214	15	29	clearly	clearly	ADV
app01-10214	15	30	different	different	ADJ
app01-10214	15	31	.	.	PUNCT
app01-10214	16	1	our	our	PRON
app01-10214	16	2	aim	aim	NOUN
app01-10214	16	3	is	be	AUX
app01-10214	16	4	to	to	PART
app01-10214	16	5	reconstruct	reconstruct	VERB
app01-10214	16	6	the	the	DET
app01-10214	16	7	image	image	NOUN
app01-10214	16	8	using	use	VERB
app01-10214	16	9	the	the	DET
app01-10214	16	10	latter	latter	ADV
app01-10214	16	11	-	-	PUNCT
app01-10214	16	12	mentioned	mention	VERB
app01-10214	16	13	approach	approach	NOUN
app01-10214	16	14	,	,	PUNCT
app01-10214	16	15	focusing	focus	VERB
app01-10214	16	16	on	on	ADP
app01-10214	16	17	different	different	ADJ
app01-10214	16	18	dnn	dnn	PROPN
app01-10214	16	19	architectures	architecture	NOUN
app01-10214	16	20	,	,	PUNCT
app01-10214	16	21	see	see	VERB
app01-10214	16	22	[	[	X
app01-10214	16	23	11	11	NUM
app01-10214	16	24	]	]	PUNCT
app01-10214	16	25	,	,	PUNCT
app01-10214	16	26	and	and	CCONJ
app01-10214	16	27	the	the	DET
app01-10214	16	28	influence	influence	NOUN
app01-10214	16	29	of	of	ADP
app01-10214	16	30	their	their	PRON
app01-10214	16	31	hyperparameters	hyperparameter	NOUN
app01-10214	16	32	on	on	ADP
app01-10214	16	33	the	the	DET
app01-10214	16	34	resulting	result	VERB
app01-10214	16	35	concrete	concrete	ADJ
app01-10214	16	36	morphology	morphology	NOUN
app01-10214	16	37	.	.	PUNCT
app01-10214	17	1	the	the	DET
app01-10214	17	2	authors	author	NOUN
app01-10214	17	3	are	be	AUX
app01-10214	17	4	aware	aware	ADJ
app01-10214	17	5	of	of	ADP
app01-10214	17	6	more	more	ADV
app01-10214	17	7	progressive	progressive	ADJ
app01-10214	17	8	techniques	technique	NOUN
app01-10214	17	9	,	,	PUNCT
app01-10214	17	10	such	such	ADJ
app01-10214	17	11	as	as	ADP
app01-10214	17	12	generative	generative	ADJ
app01-10214	17	13	adversarial	adversarial	ADJ
app01-10214	17	14	networks	network	NOUN
app01-10214	17	15	or	or	CCONJ
app01-10214	17	16	diffusion	diffusion	NOUN
app01-10214	17	17	models	model	NOUN
app01-10214	17	18	,	,	PUNCT
app01-10214	17	19	see	see	VERB
app01-10214	17	20	[	[	X
app01-10214	17	21	12–14	12–14	NUM
app01-10214	17	22	]	]	PUNCT
app01-10214	17	23	,	,	PUNCT
app01-10214	17	24	requiring	require	VERB
app01-10214	17	25	a	a	DET
app01-10214	17	26	relatively	relatively	ADV
app01-10214	17	27	rich	rich	ADJ
app01-10214	17	28	dataset	dataset	NOUN
app01-10214	17	29	of	of	ADP
app01-10214	17	30	images	image	NOUN
app01-10214	17	31	used	use	VERB
app01-10214	17	32	for	for	ADP
app01-10214	17	33	their	their	PRON
app01-10214	17	34	training	training	NOUN
app01-10214	17	35	process	process	NOUN
app01-10214	17	36	,	,	PUNCT
app01-10214	17	37	that	that	PRON
app01-10214	17	38	might	might	AUX
app01-10214	17	39	not	not	PART
app01-10214	17	40	always	always	ADV
app01-10214	17	41	be	be	AUX
app01-10214	17	42	available	available	ADJ
app01-10214	17	43	.	.	PUNCT
app01-10214	18	1	2	2	X
app01-10214	18	2	.	.	X
app01-10214	18	3	methodology	methodology	NOUN
app01-10214	18	4	the	the	DET
app01-10214	18	5	reconstruction	reconstruction	NOUN
app01-10214	18	6	of	of	ADP
app01-10214	18	7	the	the	DET
app01-10214	18	8	concrete	concrete	ADJ
app01-10214	18	9	cross	cross	NOUN
app01-10214	18	10	-	-	NOUN
app01-10214	18	11	section	section	NOUN
app01-10214	18	12	is	be	AUX
app01-10214	18	13	based	base	VERB
app01-10214	18	14	on	on	ADP
app01-10214	18	15	the	the	DET
app01-10214	18	16	algorithm	algorithm	NOUN
app01-10214	18	17	shown	show	VERB
app01-10214	18	18	in	in	ADP
app01-10214	18	19	figure	figure	NOUN
app01-10214	18	20	1	1	NUM
app01-10214	18	21	.	.	PUNCT
app01-10214	19	1	as	as	ADP
app01-10214	19	2	an	an	DET
app01-10214	19	3	input	input	NOUN
app01-10214	19	4	to	to	ADP
app01-10214	19	5	the	the	DET
app01-10214	19	6	computation	computation	NOUN
app01-10214	19	7	,	,	PUNCT
app01-10214	19	8	we	we	PRON
app01-10214	19	9	use	use	VERB
app01-10214	19	10	a	a	DET
app01-10214	19	11	sample	sample	NOUN
app01-10214	19	12	of	of	ADP
app01-10214	19	13	the	the	DET
app01-10214	19	14	concrete	concrete	ADJ
app01-10214	19	15	cross	cross	NOUN
app01-10214	19	16	-	-	NOUN
app01-10214	19	17	section	section	NOUN
app01-10214	19	18	characterized	characterize	VERB
app01-10214	19	19	by	by	ADP
app01-10214	19	20	a	a	DET
app01-10214	19	21	two	two	NUM
app01-10214	19	22	-	-	PUNCT
app01-10214	19	23	dimensional	dimensional	ADJ
app01-10214	19	24	image	image	NOUN
app01-10214	19	25	,	,	PUNCT
app01-10214	19	26	introduced	introduce	VERB
app01-10214	19	27	in	in	ADP
app01-10214	19	28	the	the	DET
app01-10214	19	29	algorithm	algorithm	NOUN
app01-10214	19	30	by	by	ADP
app01-10214	19	31	a	a	DET
app01-10214	19	32	matrix	matrix	NOUN
app01-10214	19	33	of	of	ADP
app01-10214	19	34	values	value	NOUN
app01-10214	19	35	0	0	NUM
app01-10214	20	1	and	and	CCONJ
app01-10214	20	2	1	1	NUM
app01-10214	20	3	representing	represent	VERB
app01-10214	20	4	the	the	DET
app01-10214	20	5	black	black	ADJ
app01-10214	20	6	and	and	CCONJ
app01-10214	20	7	white	white	ADJ
app01-10214	20	8	colors	color	NOUN
app01-10214	20	9	.	.	PUNCT
app01-10214	21	1	the	the	DET
app01-10214	21	2	input	input	NOUN
app01-10214	21	3	and	and	CCONJ
app01-10214	21	4	output	output	NOUN
app01-10214	21	5	data	datum	NOUN
app01-10214	21	6	used	use	VERB
app01-10214	21	7	for	for	ADP
app01-10214	21	8	training	train	VERB
app01-10214	21	9	the	the	DET
app01-10214	21	10	model	model	NOUN
app01-10214	21	11	are	be	AUX
app01-10214	21	12	generated	generate	VERB
app01-10214	21	13	from	from	ADP
app01-10214	21	14	the	the	DET
app01-10214	21	15	original	original	ADJ
app01-10214	21	16	image	image	NOUN
app01-10214	21	17	.	.	PUNCT
app01-10214	22	1	the	the	DET
app01-10214	22	2	size	size	NOUN
app01-10214	22	3	of	of	ADP
app01-10214	22	4	the	the	DET
app01-10214	22	5	dataset	dataset	NOUN
app01-10214	22	6	depends	depend	VERB
app01-10214	22	7	on	on	ADP
app01-10214	22	8	the	the	DET
app01-10214	22	9	parameters	parameter	NOUN
app01-10214	22	10	of	of	ADP
app01-10214	22	11	the	the	DET
app01-10214	22	12	computation	computation	NOUN
app01-10214	22	13	;	;	PUNCT
app01-10214	22	14	however	however	ADV
app01-10214	22	15	,	,	PUNCT
app01-10214	22	16	it	it	PRON
app01-10214	22	17	can	can	AUX
app01-10214	22	18	be	be	AUX
app01-10214	22	19	estimated	estimate	VERB
app01-10214	22	20	that	that	SCONJ
app01-10214	22	21	for	for	ADP
app01-10214	22	22	images	image	NOUN
app01-10214	22	23	ranging	range	VERB
app01-10214	22	24	from	from	ADP
app01-10214	22	25	200×200	200×200	NUM
app01-10214	22	26	to	to	ADP
app01-10214	22	27	400×400	400×400	DET
app01-10214	22	28	px	px	NOUN
app01-10214	22	29	,	,	PUNCT
app01-10214	22	30	the	the	DET
app01-10214	22	31	size	size	NOUN
app01-10214	22	32	of	of	ADP
app01-10214	22	33	the	the	DET
app01-10214	22	34	dataset	dataset	NOUN
app01-10214	22	35	is	be	AUX
app01-10214	22	36	around	around	ADP
app01-10214	22	37	tens	ten	NOUN
app01-10214	22	38	of	of	ADP
app01-10214	22	39	thousands	thousand	NOUN
app01-10214	22	40	.	.	PUNCT
app01-10214	23	1	the	the	DET
app01-10214	23	2	model	model	NOUN
app01-10214	23	3	here	here	ADV
app01-10214	23	4	is	be	AUX
app01-10214	23	5	defined	define	VERB
app01-10214	23	6	as	as	ADP
app01-10214	23	7	a	a	DET
app01-10214	23	8	classification	classification	NOUN
app01-10214	23	9	tool	tool	NOUN
app01-10214	23	10	determining	determine	VERB
app01-10214	23	11	,	,	PUNCT
app01-10214	23	12	based	base	VERB
app01-10214	23	13	on	on	ADP
app01-10214	23	14	a	a	DET
app01-10214	23	15	given	give	VERB
app01-10214	23	16	pixel	pixel	ADJ
app01-10214	23	17	neighborhood	neighborhood	NOUN
app01-10214	23	18	,	,	PUNCT
app01-10214	23	19	whether	whether	SCONJ
app01-10214	23	20	a	a	DET
app01-10214	23	21	pixel	pixel	NOUN
app01-10214	23	22	at	at	ADP
app01-10214	23	23	a	a	DET
app01-10214	23	24	given	give	VERB
app01-10214	23	25	position	position	NOUN
app01-10214	23	26	has	have	VERB
app01-10214	23	27	a	a	DET
app01-10214	23	28	value	value	NOUN
app01-10214	23	29	of	of	ADP
app01-10214	23	30	0	0	NUM
app01-10214	23	31	or	or	CCONJ
app01-10214	23	32	1	1	NUM
app01-10214	23	33	.	.	PUNCT
app01-10214	24	1	the	the	DET
app01-10214	24	2	reconstruction	reconstruction	NOUN
app01-10214	24	3	algorithm	algorithm	NOUN
app01-10214	24	4	then	then	ADV
app01-10214	24	5	uses	use	VERB
app01-10214	24	6	the	the	DET
app01-10214	24	7	trained	train	VERB
app01-10214	24	8	classifier	classifier	NOUN
app01-10214	24	9	and	and	CCONJ
app01-10214	24	10	the	the	DET
app01-10214	24	11	edges	edge	NOUN
app01-10214	24	12	of	of	ADP
app01-10214	24	13	the	the	DET
app01-10214	24	14	original	original	ADJ
app01-10214	24	15	image	image	NOUN
app01-10214	24	16	for	for	ADP
app01-10214	24	17	the	the	DET
app01-10214	24	18	prediction	prediction	NOUN
app01-10214	24	19	of	of	ADP
app01-10214	24	20	a	a	DET
app01-10214	24	21	new	new	ADJ
app01-10214	24	22	concrete	concrete	ADJ
app01-10214	24	23	cross	cross	NOUN
app01-10214	24	24	-	-	NOUN
app01-10214	24	25	section	section	NOUN
app01-10214	24	26	.	.	PUNCT
app01-10214	25	1	the	the	DET
app01-10214	25	2	quality	quality	NOUN
app01-10214	25	3	of	of	ADP
app01-10214	25	4	the	the	DET
app01-10214	25	5	new	new	ADJ
app01-10214	25	6	morphology	morphology	NOUN
app01-10214	25	7	is	be	AUX
app01-10214	25	8	evaluated	evaluate	VERB
app01-10214	25	9	on	on	ADP
app01-10214	25	10	our	our	PRON
app01-10214	25	11	selected	select	VERB
app01-10214	25	12	statistical	statistical	ADJ
app01-10214	25	13	descriptors	descriptor	NOUN
app01-10214	25	14	.	.	PUNCT
app01-10214	26	1	the	the	DET
app01-10214	26	2	aim	aim	NOUN
app01-10214	26	3	of	of	ADP
app01-10214	26	4	the	the	DET
app01-10214	26	5	reconstruction	reconstruction	NOUN
app01-10214	26	6	is	be	AUX
app01-10214	26	7	to	to	PART
app01-10214	26	8	generate	generate	VERB
app01-10214	26	9	a	a	DET
app01-10214	26	10	similar	similar	ADJ
app01-10214	26	11	sample	sample	NOUN
app01-10214	26	12	with	with	ADP
app01-10214	26	13	a	a	DET
app01-10214	26	14	statistically	statistically	ADV
app01-10214	26	15	and	and	CCONJ
app01-10214	26	16	physically	physically	ADV
app01-10214	26	17	equivalent	equivalent	ADJ
app01-10214	26	18	structure	structure	NOUN
app01-10214	26	19	with	with	ADP
app01-10214	26	20	respect	respect	NOUN
app01-10214	26	21	to	to	ADP
app01-10214	26	22	the	the	DET
app01-10214	26	23	studied	studied	ADJ
app01-10214	26	24	medium	medium	NOUN
app01-10214	26	25	.	.	PUNCT
app01-10214	27	1	the	the	DET
app01-10214	27	2	pixel	pixel	PROPN
app01-10214	27	3	neighborhood	neighborhood	NOUN
app01-10214	27	4	is	be	AUX
app01-10214	27	5	an	an	DET
app01-10214	27	6	important	important	ADJ
app01-10214	27	7	parameter	parameter	NOUN
app01-10214	27	8	of	of	ADP
app01-10214	27	9	the	the	DET
app01-10214	27	10	reconstruction	reconstruction	NOUN
app01-10214	27	11	algorithm	algorithm	NOUN
app01-10214	27	12	.	.	PUNCT
app01-10214	28	1	figure	figure	NOUN
app01-10214	28	2	2	2	NUM
app01-10214	28	3	shows	show	VERB
app01-10214	28	4	the	the	DET
app01-10214	28	5	template	template	NOUN
app01-10214	28	6	as	as	ADP
app01-10214	28	7	a	a	DET
app01-10214	28	8	function	function	NOUN
app01-10214	28	9	of	of	ADP
app01-10214	28	10	the	the	DET
app01-10214	28	11	parameters	parameter	NOUN
app01-10214	28	12	w	w	PROPN
app01-10214	28	13	and	and	CCONJ
app01-10214	28	14	h.	h.	NOUN
app01-10214	28	15	these	these	DET
app01-10214	28	16	two	two	NUM
app01-10214	28	17	parameters	parameter	NOUN
app01-10214	28	18	define	define	VERB
app01-10214	28	19	its	its	PRON
app01-10214	28	20	dimension	dimension	NOUN
app01-10214	28	21	,	,	PUNCT
app01-10214	28	22	which	which	PRON
app01-10214	28	23	significantly	significantly	ADV
app01-10214	28	24	affects	affect	VERB
app01-10214	28	25	the	the	DET
app01-10214	28	26	properties	property	NOUN
app01-10214	28	27	of	of	ADP
app01-10214	28	28	the	the	DET
app01-10214	28	29	entire	entire	ADJ
app01-10214	28	30	reconstruction	reconstruction	NOUN
app01-10214	28	31	.	.	PUNCT
app01-10214	29	1	the	the	DET
app01-10214	29	2	pixel	pixel	PROPN
app01-10214	29	3	neighborhood	neighborhood	NOUN
app01-10214	29	4	has	have	VERB
app01-10214	29	5	two	two	NUM
app01-10214	29	6	major	major	ADJ
app01-10214	29	7	features	feature	NOUN
app01-10214	29	8	:	:	PUNCT
app01-10214	29	9	(	(	PUNCT
app01-10214	29	10	1	1	NUM
app01-10214	29	11	.	.	PUNCT
app01-10214	29	12	)	)	PUNCT
app01-10214	30	1	it	it	PRON
app01-10214	30	2	specifies	specify	VERB
app01-10214	30	3	the	the	DET
app01-10214	30	4	number	number	NOUN
app01-10214	30	5	of	of	ADP
app01-10214	30	6	input	input	NOUN
app01-10214	30	7	values	value	NOUN
app01-10214	30	8	of	of	ADP
app01-10214	30	9	pixels	pixel	NOUN
app01-10214	30	10	needed	need	VERB
app01-10214	30	11	for	for	ADP
app01-10214	30	12	the	the	DET
app01-10214	30	13	output	output	NOUN
app01-10214	30	14	value	value	NOUN
app01-10214	30	15	.	.	PUNCT
app01-10214	31	1	yellow	yellow	ADJ
app01-10214	31	2	-	-	PUNCT
app01-10214	31	3	labeled	label	VERB
app01-10214	31	4	pixels	pixel	NOUN
app01-10214	31	5	in	in	ADP
app01-10214	31	6	the	the	DET
app01-10214	31	7	scheme	scheme	NOUN
app01-10214	31	8	are	be	AUX
app01-10214	31	9	our	our	PRON
app01-10214	31	10	input	input	NOUN
app01-10214	31	11	values	value	NOUN
app01-10214	31	12	,	,	PUNCT
app01-10214	31	13	and	and	CCONJ
app01-10214	31	14	the	the	DET
app01-10214	31	15	redlabeled	redlabele	VERB
app01-10214	31	16	pixel	pixel	NOUN
app01-10214	31	17	is	be	AUX
app01-10214	31	18	the	the	DET
app01-10214	31	19	output	output	NOUN
app01-10214	31	20	value	value	NOUN
app01-10214	31	21	.	.	PUNCT
app01-10214	32	1	since	since	SCONJ
app01-10214	32	2	the	the	DET
app01-10214	32	3	values	value	NOUN
app01-10214	32	4	of	of	ADP
app01-10214	32	5	the	the	DET
app01-10214	32	6	yellow	yellow	ADV
app01-10214	32	7	-	-	PUNCT
app01-10214	32	8	labeled	label	VERB
app01-10214	32	9	pixels	pixel	NOUN
app01-10214	32	10	have	have	VERB
app01-10214	32	11	to	to	PART
app01-10214	32	12	be	be	AUX
app01-10214	32	13	known	know	VERB
app01-10214	32	14	,	,	PUNCT
app01-10214	32	15	the	the	DET
app01-10214	32	16	reconstruction	reconstruction	NOUN
app01-10214	32	17	algorithm	algorithm	NOUN
app01-10214	32	18	must	must	AUX
app01-10214	32	19	always	always	ADV
app01-10214	32	20	have	have	VERB
app01-10214	32	21	the	the	DET
app01-10214	32	22	edges	edge	NOUN
app01-10214	32	23	of	of	ADP
app01-10214	32	24	the	the	DET
app01-10214	32	25	original	original	ADJ
app01-10214	32	26	image	image	NOUN
app01-10214	32	27	enabling	enable	VERB
app01-10214	32	28	the	the	DET
app01-10214	32	29	prediction	prediction	NOUN
app01-10214	32	30	of	of	ADP
app01-10214	32	31	the	the	DET
app01-10214	32	32	first	first	ADJ
app01-10214	32	33	red	red	ADJ
app01-10214	32	34	pixel	pixel	PROPN
app01-10214	32	35	.	.	PUNCT
app01-10214	33	1	thus	thus	ADV
app01-10214	33	2	,	,	PUNCT
app01-10214	33	3	the	the	DET
app01-10214	33	4	parameters	parameter	NOUN
app01-10214	33	5	w	w	PROPN
app01-10214	33	6	and	and	CCONJ
app01-10214	33	7	h	h	NOUN
app01-10214	33	8	also	also	ADV
app01-10214	33	9	characterize	characterize	VERB
app01-10214	33	10	the	the	DET
app01-10214	33	11	sizes	size	NOUN
app01-10214	33	12	of	of	ADP
app01-10214	33	13	the	the	DET
app01-10214	33	14	boundary	boundary	ADJ
app01-10214	33	15	regions	region	NOUN
app01-10214	33	16	of	of	ADP
app01-10214	33	17	the	the	DET
app01-10214	33	18	original	original	ADJ
app01-10214	33	19	image	image	NOUN
app01-10214	33	20	,	,	PUNCT
app01-10214	33	21	which	which	PRON
app01-10214	33	22	are	be	AUX
app01-10214	33	23	needed	need	VERB
app01-10214	33	24	for	for	ADP
app01-10214	33	25	the	the	DET
app01-10214	33	26	start	start	NOUN
app01-10214	33	27	of	of	ADP
app01-10214	33	28	the	the	DET
app01-10214	33	29	reconstruction	reconstruction	NOUN
app01-10214	33	30	algorithm	algorithm	NOUN
app01-10214	33	31	.	.	PUNCT
app01-10214	34	1	85	85	NUM
app01-10214	34	2	https://doi.org/10.14311/app.2024.49.0085	https://doi.org/10.14311/app.2024.49.0085	NOUN
app01-10214	34	3	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
app01-10214	34	4	https://www.cvut.cz/en	https://www.cvut.cz/en	PROPN
app01-10214	34	5	ondřej	ondřej	NOUN
app01-10214	34	6	šperl	šperl	PROPN
app01-10214	34	7	,	,	PUNCT
app01-10214	34	8	jan	jan	PROPN
app01-10214	34	9	sýkora	sýkora	PROPN
app01-10214	34	10	acta	acta	PROPN
app01-10214	34	11	polytechnica	polytechnica	PROPN
app01-10214	34	12	ctu	ctu	PROPN
app01-10214	34	13	proceedings	proceeding	NOUN
app01-10214	34	14	figure	figure	VERB
app01-10214	34	15	1	1	NUM
app01-10214	34	16	.	.	PUNCT
app01-10214	35	1	algorithmic	algorithmic	ADJ
app01-10214	35	2	framework	framework	NOUN
app01-10214	35	3	.	.	PUNCT
app01-10214	36	1	figure	figure	NOUN
app01-10214	36	2	2	2	NUM
app01-10214	36	3	.	.	PUNCT
app01-10214	36	4	template	template	NOUN
app01-10214	36	5	determining	determine	VERB
app01-10214	36	6	set	set	NOUN
app01-10214	36	7	of	of	ADP
app01-10214	36	8	surrounding	surround	VERB
app01-10214	36	9	pixels	pixel	NOUN
app01-10214	36	10	.	.	PUNCT
app01-10214	37	1	(	(	PUNCT
app01-10214	37	2	2	2	NUM
app01-10214	37	3	.	.	PUNCT
app01-10214	37	4	)	)	PUNCT
app01-10214	38	1	moreover	moreover	ADV
app01-10214	38	2	,	,	PUNCT
app01-10214	38	3	it	it	PRON
app01-10214	38	4	defines	define	VERB
app01-10214	38	5	a	a	DET
app01-10214	38	6	template	template	NOUN
app01-10214	38	7	that	that	PRON
app01-10214	38	8	moves	move	VERB
app01-10214	38	9	pixelby	pixelby	NOUN
app01-10214	38	10	-	-	PUNCT
app01-10214	38	11	pixel	pixel	NOUN
app01-10214	38	12	within	within	ADP
app01-10214	38	13	the	the	DET
app01-10214	38	14	reconstructed	reconstructed	ADJ
app01-10214	38	15	image	image	NOUN
app01-10214	38	16	and	and	CCONJ
app01-10214	38	17	predicts	predict	VERB
app01-10214	38	18	the	the	DET
app01-10214	38	19	value	value	NOUN
app01-10214	38	20	of	of	ADP
app01-10214	38	21	the	the	DET
app01-10214	38	22	red	red	ADJ
app01-10214	38	23	-	-	PUNCT
app01-10214	38	24	labeled	label	VERB
app01-10214	38	25	pixel	pixel	NOUN
app01-10214	38	26	.	.	PUNCT
app01-10214	39	1	it	it	PRON
app01-10214	39	2	can	can	AUX
app01-10214	39	3	be	be	AUX
app01-10214	39	4	seen	see	VERB
app01-10214	39	5	from	from	ADP
app01-10214	39	6	the	the	DET
app01-10214	39	7	scheme	scheme	NOUN
app01-10214	39	8	that	that	SCONJ
app01-10214	39	9	the	the	DET
app01-10214	39	10	rectangle	rectangle	NOUN
app01-10214	39	11	of	of	ADP
app01-10214	39	12	size	size	NOUN
app01-10214	39	13	(	(	PUNCT
app01-10214	39	14	2w	2w	NUM
app01-10214	39	15	+	+	CCONJ
app01-10214	39	16	1	1	NUM
app01-10214	39	17	)	)	PUNCT
app01-10214	39	18	·	·	PUNCT
app01-10214	39	19	(	(	PUNCT
app01-10214	39	20	h	h	NOUN
app01-10214	39	21	+	+	NOUN
app01-10214	39	22	1	1	X
app01-10214	39	23	)	)	PUNCT
app01-10214	39	24	is	be	AUX
app01-10214	39	25	used	use	VERB
app01-10214	39	26	as	as	ADP
app01-10214	39	27	a	a	DET
app01-10214	39	28	template	template	NOUN
app01-10214	39	29	,	,	PUNCT
app01-10214	39	30	and	and	CCONJ
app01-10214	39	31	for	for	ADP
app01-10214	39	32	this	this	DET
app01-10214	39	33	reason	reason	NOUN
app01-10214	39	34	,	,	PUNCT
app01-10214	39	35	we	we	PRON
app01-10214	39	36	have	have	VERB
app01-10214	39	37	to	to	PART
app01-10214	39	38	use	use	VERB
app01-10214	39	39	blue	blue	ADV
app01-10214	39	40	-	-	PUNCT
app01-10214	39	41	labeled	label	VERB
app01-10214	39	42	and	and	CCONJ
app01-10214	39	43	red	red	ADJ
app01-10214	39	44	-	-	PUNCT
app01-10214	39	45	labeled	label	VERB
app01-10214	39	46	pixels	pixel	NOUN
app01-10214	39	47	as	as	ADP
app01-10214	39	48	input	input	NOUN
app01-10214	39	49	values	value	NOUN
app01-10214	39	50	.	.	PUNCT
app01-10214	40	1	these	these	PRON
app01-10214	40	2	are	be	AUX
app01-10214	40	3	the	the	DET
app01-10214	40	4	values	value	NOUN
app01-10214	40	5	that	that	PRON
app01-10214	40	6	are	be	AUX
app01-10214	40	7	not	not	PART
app01-10214	40	8	taken	take	VERB
app01-10214	40	9	from	from	ADP
app01-10214	40	10	the	the	DET
app01-10214	40	11	original	original	ADJ
app01-10214	40	12	image	image	NOUN
app01-10214	40	13	but	but	CCONJ
app01-10214	40	14	are	be	AUX
app01-10214	40	15	randomly	randomly	ADV
app01-10214	40	16	and	and	CCONJ
app01-10214	40	17	independently	independently	ADV
app01-10214	40	18	generated	generate	VERB
app01-10214	40	19	from	from	ADP
app01-10214	40	20	a	a	DET
app01-10214	40	21	uniform	uniform	ADJ
app01-10214	40	22	distribution	distribution	NOUN
app01-10214	40	23	satisfying	satisfy	VERB
app01-10214	40	24	the	the	DET
app01-10214	40	25	volume	volume	NOUN
app01-10214	40	26	representation	representation	NOUN
app01-10214	40	27	of	of	ADP
app01-10214	40	28	0	0	NUM
app01-10214	40	29	and	and	CCONJ
app01-10214	40	30	1	1	NUM
app01-10214	40	31	values	value	NOUN
app01-10214	40	32	in	in	ADP
app01-10214	40	33	the	the	DET
app01-10214	40	34	original	original	ADJ
app01-10214	40	35	image	image	NOUN
app01-10214	40	36	.	.	PUNCT
app01-10214	41	1	once	once	SCONJ
app01-10214	41	2	the	the	DET
app01-10214	41	3	pixel	pixel	PROPN
app01-10214	41	4	neighborhood	neighborhood	NOUN
app01-10214	41	5	is	be	AUX
app01-10214	41	6	set	set	VERB
app01-10214	41	7	and	and	CCONJ
app01-10214	41	8	the	the	DET
app01-10214	41	9	classifier	classifier	NOUN
app01-10214	41	10	is	be	AUX
app01-10214	41	11	trained	train	VERB
app01-10214	41	12	,	,	PUNCT
app01-10214	41	13	the	the	DET
app01-10214	41	14	reconstruction	reconstruction	NOUN
app01-10214	41	15	algorithm	algorithm	NOUN
app01-10214	41	16	starts	start	VERB
app01-10214	41	17	the	the	DET
app01-10214	41	18	execution	execution	NOUN
app01-10214	41	19	with	with	ADP
app01-10214	41	20	the	the	DET
app01-10214	41	21	given	give	VERB
app01-10214	41	22	template	template	NOUN
app01-10214	41	23	from	from	ADP
app01-10214	41	24	the	the	DET
app01-10214	41	25	upper	upper	ADJ
app01-10214	41	26	left	left	ADJ
app01-10214	41	27	corner	corner	NOUN
app01-10214	41	28	of	of	ADP
app01-10214	41	29	the	the	DET
app01-10214	41	30	initial	initial	ADJ
app01-10214	41	31	image	image	NOUN
app01-10214	41	32	.	.	PUNCT
app01-10214	42	1	the	the	DET
app01-10214	42	2	initial	initial	ADJ
app01-10214	42	3	image	image	NOUN
app01-10214	42	4	is	be	AUX
app01-10214	42	5	shown	show	VERB
app01-10214	42	6	in	in	ADP
app01-10214	42	7	figure	figure	NOUN
app01-10214	42	8	1	1	NUM
app01-10214	42	9	,	,	PUNCT
app01-10214	42	10	with	with	ADP
app01-10214	42	11	the	the	DET
app01-10214	42	12	edges	edge	NOUN
app01-10214	42	13	representing	represent	VERB
app01-10214	42	14	the	the	DET
app01-10214	42	15	morphology	morphology	NOUN
app01-10214	42	16	of	of	ADP
app01-10214	42	17	the	the	DET
app01-10214	42	18	original	original	ADJ
app01-10214	42	19	media	medium	NOUN
app01-10214	42	20	and	and	CCONJ
app01-10214	42	21	the	the	DET
app01-10214	42	22	rest	rest	NOUN
app01-10214	42	23	being	be	AUX
app01-10214	42	24	randomly	randomly	ADV
app01-10214	42	25	determined	determine	VERB
app01-10214	42	26	pixels	pixel	NOUN
app01-10214	42	27	so	so	SCONJ
app01-10214	42	28	as	as	SCONJ
app01-10214	42	29	to	to	PART
app01-10214	42	30	preserve	preserve	VERB
app01-10214	42	31	the	the	DET
app01-10214	42	32	volume	volume	NOUN
app01-10214	42	33	representation	representation	NOUN
app01-10214	42	34	.	.	PUNCT
app01-10214	43	1	the	the	DET
app01-10214	43	2	red	red	ADJ
app01-10214	43	3	-	-	PUNCT
app01-10214	43	4	labeled	label	VERB
app01-10214	43	5	pixel	pixel	NOUN
app01-10214	43	6	is	be	AUX
app01-10214	43	7	computed	compute	VERB
app01-10214	43	8	with	with	ADP
app01-10214	43	9	the	the	DET
app01-10214	43	10	help	help	NOUN
app01-10214	43	11	of	of	ADP
app01-10214	43	12	the	the	DET
app01-10214	43	13	classifier	classifier	NOUN
app01-10214	43	14	specifying	specify	VERB
app01-10214	43	15	the	the	DET
app01-10214	43	16	probability	probability	NOUN
app01-10214	43	17	of	of	ADP
app01-10214	43	18	0	0	NUM
app01-10214	43	19	and	and	CCONJ
app01-10214	43	20	1	1	NUM
app01-10214	43	21	for	for	ADP
app01-10214	43	22	a	a	DET
app01-10214	43	23	given	give	VERB
app01-10214	43	24	vicinity	vicinity	NOUN
app01-10214	43	25	and	and	CCONJ
app01-10214	43	26	the	the	DET
app01-10214	43	27	pseudo	pseudo	NOUN
app01-10214	43	28	-	-	ADJ
app01-10214	43	29	random	random	ADJ
app01-10214	43	30	number	number	NOUN
app01-10214	43	31	generator	generator	NOUN
app01-10214	43	32	determining	determine	VERB
app01-10214	43	33	the	the	DET
app01-10214	43	34	final	final	ADJ
app01-10214	43	35	value	value	NOUN
app01-10214	43	36	.	.	PUNCT
app01-10214	44	1	the	the	DET
app01-10214	44	2	newly	newly	ADV
app01-10214	44	3	determined	determine	VERB
app01-10214	44	4	red	red	ADJ
app01-10214	44	5	-	-	PUNCT
app01-10214	44	6	labeled	label	VERB
app01-10214	44	7	pixel	pixel	NOUN
app01-10214	44	8	becomes	become	VERB
app01-10214	44	9	the	the	DET
app01-10214	44	10	yellow	yellow	ADV
app01-10214	44	11	-	-	PUNCT
app01-10214	44	12	labeled	label	VERB
app01-10214	44	13	pixel	pixel	NOUN
app01-10214	44	14	,	,	PUNCT
app01-10214	44	15	and	and	CCONJ
app01-10214	44	16	then	then	ADV
app01-10214	44	17	the	the	DET
app01-10214	44	18	template	template	NOUN
app01-10214	44	19	is	be	AUX
app01-10214	44	20	shifted	shift	VERB
app01-10214	44	21	one	one	NUM
app01-10214	44	22	pixel	pixel	NOUN
app01-10214	44	23	further	far	ADV
app01-10214	44	24	to	to	ADP
app01-10214	44	25	the	the	DET
app01-10214	44	26	right	right	NOUN
app01-10214	44	27	.	.	PUNCT
app01-10214	45	1	the	the	DET
app01-10214	45	2	value	value	NOUN
app01-10214	45	3	of	of	ADP
app01-10214	45	4	all	all	DET
app01-10214	45	5	reconstructed	reconstructed	ADJ
app01-10214	45	6	pixels	pixel	NOUN
app01-10214	45	7	is	be	AUX
app01-10214	45	8	successively	successively	ADV
app01-10214	45	9	identified	identify	VERB
app01-10214	45	10	in	in	ADP
app01-10214	45	11	this	this	DET
app01-10214	45	12	fashion	fashion	NOUN
app01-10214	45	13	.	.	PUNCT
app01-10214	46	1	the	the	DET
app01-10214	46	2	reconstruction	reconstruction	NOUN
app01-10214	46	3	algorithm	algorithm	NOUN
app01-10214	46	4	terminates	terminate	VERB
app01-10214	46	5	in	in	ADP
app01-10214	46	6	the	the	DET
app01-10214	46	7	lower	low	ADJ
app01-10214	46	8	right	right	ADJ
app01-10214	46	9	corner	corner	NOUN
app01-10214	46	10	of	of	ADP
app01-10214	46	11	the	the	DET
app01-10214	46	12	image	image	NOUN
app01-10214	46	13	.	.	PUNCT
app01-10214	47	1	subsequently	subsequently	ADV
app01-10214	47	2	,	,	PUNCT
app01-10214	47	3	the	the	DET
app01-10214	47	4	metrics	metric	NOUN
app01-10214	47	5	of	of	ADP
app01-10214	47	6	the	the	DET
app01-10214	47	7	statistical	statistical	ADJ
app01-10214	47	8	and	and	CCONJ
app01-10214	47	9	physical	physical	ADJ
app01-10214	47	10	descriptors	descriptor	NOUN
app01-10214	47	11	are	be	AUX
app01-10214	47	12	evaluated	evaluate	VERB
app01-10214	47	13	.	.	PUNCT
app01-10214	48	1	2.1	2.1	NUM
app01-10214	48	2	.	.	PUNCT
app01-10214	48	3	architecture	architecture	NOUN
app01-10214	48	4	of	of	ADP
app01-10214	48	5	dnn	dnn	PROPN
app01-10214	48	6	deep	deep	ADJ
app01-10214	48	7	neural	neural	ADJ
app01-10214	48	8	learning	learning	NOUN
app01-10214	48	9	is	be	AUX
app01-10214	48	10	the	the	DET
app01-10214	48	11	subclass	subclass	NOUN
app01-10214	48	12	of	of	ADP
app01-10214	48	13	machine	machine	NOUN
app01-10214	48	14	learning	learning	NOUN
app01-10214	48	15	using	use	VERB
app01-10214	48	16	dnn	dnn	PROPN
app01-10214	48	17	as	as	ADP
app01-10214	48	18	a	a	DET
app01-10214	48	19	tool	tool	NOUN
app01-10214	48	20	for	for	ADP
app01-10214	48	21	solving	solve	VERB
app01-10214	48	22	complex	complex	ADJ
app01-10214	48	23	problems	problem	NOUN
app01-10214	48	24	.	.	PUNCT
app01-10214	49	1	each	each	DET
app01-10214	49	2	dnn	dnn	PROPN
app01-10214	49	3	has	have	VERB
app01-10214	49	4	multiple	multiple	ADJ
app01-10214	49	5	layers	layer	NOUN
app01-10214	49	6	of	of	ADP
app01-10214	49	7	interconnected	interconnected	ADJ
app01-10214	49	8	nodes	node	NOUN
app01-10214	49	9	enabling	enable	VERB
app01-10214	49	10	one	one	NUM
app01-10214	49	11	to	to	PART
app01-10214	49	12	learn	learn	VERB
app01-10214	49	13	complex	complex	ADJ
app01-10214	49	14	representations	representation	NOUN
app01-10214	49	15	of	of	ADP
app01-10214	49	16	data	datum	NOUN
app01-10214	49	17	by	by	ADP
app01-10214	49	18	discovering	discover	VERB
app01-10214	49	19	hierarchical	hierarchical	ADJ
app01-10214	49	20	patterns	pattern	NOUN
app01-10214	49	21	and	and	CCONJ
app01-10214	49	22	features	feature	NOUN
app01-10214	49	23	,	,	PUNCT
app01-10214	49	24	see	see	VERB
app01-10214	49	25	[	[	X
app01-10214	49	26	15	15	NUM
app01-10214	49	27	]	]	PUNCT
app01-10214	49	28	.	.	PUNCT
app01-10214	50	1	the	the	DET
app01-10214	50	2	regular	regular	ADJ
app01-10214	50	3	dnn	dnn	PROPN
app01-10214	50	4	is	be	AUX
app01-10214	50	5	composed	compose	VERB
app01-10214	50	6	of	of	ADP
app01-10214	50	7	three	three	NUM
app01-10214	50	8	types	type	NOUN
app01-10214	50	9	of	of	ADP
app01-10214	50	10	layers	layer	NOUN
app01-10214	50	11	:	:	PUNCT
app01-10214	50	12	(	(	PUNCT
app01-10214	50	13	1	1	NUM
app01-10214	50	14	.	.	PUNCT
app01-10214	50	15	)	)	PUNCT
app01-10214	50	16	input	input	NOUN
app01-10214	50	17	layer	layer	NOUN
app01-10214	50	18	processing	processing	NOUN
app01-10214	50	19	input	input	NOUN
app01-10214	50	20	data	datum	NOUN
app01-10214	50	21	into	into	ADP
app01-10214	50	22	the	the	DET
app01-10214	50	23	model	model	NOUN
app01-10214	50	24	,	,	PUNCT
app01-10214	50	25	(	(	PUNCT
app01-10214	50	26	2	2	NUM
app01-10214	50	27	.	.	PUNCT
app01-10214	50	28	)	)	PUNCT
app01-10214	51	1	hidden	hide	VERB
app01-10214	51	2	layers	layer	NOUN
app01-10214	51	3	representing	represent	VERB
app01-10214	51	4	the	the	DET
app01-10214	51	5	key	key	ADJ
app01-10214	51	6	part	part	NOUN
app01-10214	51	7	of	of	ADP
app01-10214	51	8	dnn	dnn	PROPN
app01-10214	51	9	and	and	CCONJ
app01-10214	51	10	applying	apply	VERB
app01-10214	51	11	weights	weight	NOUN
app01-10214	51	12	to	to	ADP
app01-10214	51	13	the	the	DET
app01-10214	51	14	inputs	input	NOUN
app01-10214	51	15	and	and	CCONJ
app01-10214	51	16	directing	direct	VERB
app01-10214	51	17	them	they	PRON
app01-10214	51	18	through	through	ADP
app01-10214	51	19	an	an	DET
app01-10214	51	20	activation	activation	NOUN
app01-10214	51	21	function	function	NOUN
app01-10214	51	22	as	as	ADP
app01-10214	51	23	the	the	DET
app01-10214	51	24	outputs	output	NOUN
app01-10214	51	25	,	,	PUNCT
app01-10214	51	26	(	(	PUNCT
app01-10214	51	27	3	3	NUM
app01-10214	51	28	.	.	PUNCT
app01-10214	51	29	)	)	PUNCT
app01-10214	52	1	output	output	NOUN
app01-10214	52	2	layer	layer	NOUN
app01-10214	52	3	is	be	AUX
app01-10214	52	4	the	the	DET
app01-10214	52	5	last	last	ADJ
app01-10214	52	6	layer	layer	NOUN
app01-10214	52	7	in	in	ADP
app01-10214	52	8	the	the	DET
app01-10214	52	9	neural	neural	ADJ
app01-10214	52	10	network	network	NOUN
app01-10214	52	11	calculating	calculate	VERB
app01-10214	52	12	the	the	DET
app01-10214	52	13	final	final	ADJ
app01-10214	52	14	probability	probability	NOUN
app01-10214	52	15	scores	score	NOUN
app01-10214	52	16	of	of	ADP
app01-10214	52	17	desired	desire	VERB
app01-10214	52	18	outputs	output	NOUN
app01-10214	52	19	.	.	PUNCT
app01-10214	53	1	the	the	DET
app01-10214	53	2	special	special	ADJ
app01-10214	53	3	case	case	NOUN
app01-10214	53	4	of	of	ADP
app01-10214	53	5	dnn	dnn	PROPN
app01-10214	53	6	is	be	AUX
app01-10214	53	7	the	the	DET
app01-10214	53	8	convolutional	convolutional	ADJ
app01-10214	53	9	neural	neural	ADJ
app01-10214	53	10	network	network	NOUN
app01-10214	53	11	(	(	PUNCT
app01-10214	53	12	cnn	cnn	PROPN
app01-10214	53	13	)	)	PUNCT
app01-10214	53	14	developed	develop	VERB
app01-10214	53	15	for	for	ADP
app01-10214	53	16	image	image	NOUN
app01-10214	53	17	classification	classification	NOUN
app01-10214	53	18	and	and	CCONJ
app01-10214	53	19	data	datum	NOUN
app01-10214	53	20	visual	visual	ADJ
app01-10214	53	21	interpretation	interpretation	NOUN
app01-10214	53	22	,	,	PUNCT
app01-10214	53	23	see	see	VERB
app01-10214	53	24	[	[	X
app01-10214	53	25	16	16	NUM
app01-10214	53	26	]	]	PUNCT
app01-10214	53	27	.	.	PUNCT
app01-10214	54	1	it	it	PRON
app01-10214	54	2	is	be	AUX
app01-10214	54	3	based	base	VERB
app01-10214	54	4	on	on	ADP
app01-10214	54	5	the	the	DET
app01-10214	54	6	principles	principle	NOUN
app01-10214	54	7	of	of	ADP
app01-10214	54	8	mathematical	mathematical	ADJ
app01-10214	54	9	convolution	convolution	NOUN
app01-10214	54	10	extracting	extract	VERB
app01-10214	54	11	the	the	DET
app01-10214	54	12	important	important	ADJ
app01-10214	54	13	features	feature	NOUN
app01-10214	54	14	from	from	ADP
app01-10214	54	15	the	the	DET
app01-10214	54	16	image	image	NOUN
app01-10214	54	17	with	with	ADP
app01-10214	54	18	the	the	DET
app01-10214	54	19	help	help	NOUN
app01-10214	54	20	of	of	ADP
app01-10214	54	21	learnable	learnable	ADJ
app01-10214	54	22	filters	filter	NOUN
app01-10214	54	23	.	.	PUNCT
app01-10214	55	1	the	the	DET
app01-10214	55	2	cnn	cnn	PROPN
app01-10214	55	3	is	be	AUX
app01-10214	55	4	primarily	primarily	ADV
app01-10214	55	5	composed	compose	VERB
app01-10214	55	6	of	of	ADP
app01-10214	55	7	86	86	NUM
app01-10214	55	8	vol	vol	NOUN
app01-10214	55	9	.	.	PUNCT
app01-10214	56	1	49/2024	49/2024	NUM
app01-10214	56	2	reconstruction	reconstruction	NOUN
app01-10214	56	3	of	of	ADP
app01-10214	56	4	concrete	concrete	ADJ
app01-10214	56	5	morphology	morphology	NOUN
app01-10214	56	6	using	use	VERB
app01-10214	56	7	deep	deep	ADJ
app01-10214	56	8	learning	learning	NOUN
app01-10214	56	9	(	(	PUNCT
app01-10214	56	10	a	a	NOUN
app01-10214	56	11	)	)	PUNCT
app01-10214	56	12	.	.	PUNCT
app01-10214	57	1	original	original	ADJ
app01-10214	57	2	segmented	segment	VERB
app01-10214	57	3	image	image	NOUN
app01-10214	57	4	–	–	PUNCT
app01-10214	57	5	1	1	NUM
app01-10214	57	6	200	200	NUM
app01-10214	57	7	×	×	NOUN
app01-10214	57	8	1	1	NUM
app01-10214	57	9	225	225	NUM
app01-10214	57	10	px	px	NOUN
app01-10214	57	11	.	.	PUNCT
app01-10214	57	12	(	(	PUNCT
app01-10214	57	13	b	b	NOUN
app01-10214	57	14	)	)	PUNCT
app01-10214	57	15	.	.	PUNCT
app01-10214	58	1	the	the	DET
app01-10214	58	2	largest	large	ADJ
app01-10214	58	3	possible	possible	ADJ
app01-10214	58	4	square	square	ADJ
app01-10214	58	5	image	image	NOUN
app01-10214	58	6	cut	cut	VERB
app01-10214	58	7	from	from	ADP
app01-10214	58	8	the	the	DET
app01-10214	58	9	original	original	ADJ
app01-10214	58	10	segmented	segment	VERB
app01-10214	58	11	image	image	NOUN
app01-10214	58	12	–	–	PUNCT
app01-10214	58	13	816	816	NUM
app01-10214	58	14	×	×	NOUN
app01-10214	58	15	816	816	NUM
app01-10214	58	16	px	px	NOUN
app01-10214	58	17	.	.	PUNCT
app01-10214	58	18	(	(	PUNCT
app01-10214	58	19	c	c	NOUN
app01-10214	58	20	)	)	PUNCT
app01-10214	58	21	.	.	PUNCT
app01-10214	59	1	the	the	DET
app01-10214	59	2	final	final	ADJ
app01-10214	59	3	image	image	NOUN
app01-10214	59	4	adjusted	adjust	VERB
app01-10214	59	5	for	for	ADP
app01-10214	59	6	redundant	redundant	ADJ
app01-10214	59	7	pores	pore	NOUN
app01-10214	59	8	–	–	PUNCT
app01-10214	59	9	400	400	NUM
app01-10214	59	10	×	×	NOUN
app01-10214	59	11	400	400	NUM
app01-10214	59	12	px	px	PROPN
app01-10214	59	13	.	.	PROPN
app01-10214	59	14	figure	figure	NOUN
app01-10214	59	15	3	3	NUM
app01-10214	59	16	.	.	PUNCT
app01-10214	59	17	input	input	NOUN
app01-10214	59	18	image	image	NOUN
app01-10214	59	19	preparation	preparation	NOUN
app01-10214	59	20	.	.	PUNCT
app01-10214	60	1	convolutional	convolutional	ADJ
app01-10214	60	2	layers	layer	NOUN
app01-10214	60	3	and	and	CCONJ
app01-10214	60	4	max	max	PROPN
app01-10214	60	5	pooling	pool	VERB
app01-10214	60	6	layers	layer	NOUN
app01-10214	60	7	reducing	reduce	VERB
app01-10214	60	8	the	the	DET
app01-10214	60	9	number	number	NOUN
app01-10214	60	10	of	of	ADP
app01-10214	60	11	weights	weight	NOUN
app01-10214	60	12	in	in	ADP
app01-10214	60	13	the	the	DET
app01-10214	60	14	neural	neural	ADJ
app01-10214	60	15	network	network	NOUN
app01-10214	60	16	.	.	PUNCT
app01-10214	61	1	our	our	PRON
app01-10214	61	2	designed	design	VERB
app01-10214	61	3	classifiers	classifier	NOUN
app01-10214	61	4	are	be	AUX
app01-10214	61	5	built	build	VERB
app01-10214	61	6	upon	upon	SCONJ
app01-10214	61	7	the	the	DET
app01-10214	61	8	standards	standard	NOUN
app01-10214	61	9	of	of	ADP
app01-10214	61	10	dnn	dnn	PROPN
app01-10214	61	11	and	and	CCONJ
app01-10214	61	12	cnn	cnn	PROPN
app01-10214	61	13	architectures	architecture	NOUN
app01-10214	61	14	.	.	PUNCT
app01-10214	62	1	3	3	X
app01-10214	62	2	.	.	X
app01-10214	62	3	example	example	NOUN
app01-10214	62	4	the	the	DET
app01-10214	62	5	example	example	NOUN
app01-10214	62	6	devoted	devote	VERB
app01-10214	62	7	to	to	ADP
app01-10214	62	8	the	the	DET
app01-10214	62	9	reconstruction	reconstruction	NOUN
app01-10214	62	10	of	of	ADP
app01-10214	62	11	the	the	DET
app01-10214	62	12	concrete	concrete	ADJ
app01-10214	62	13	structure	structure	NOUN
app01-10214	62	14	using	use	VERB
app01-10214	62	15	deep	deep	ADJ
app01-10214	62	16	learning	learning	NOUN
app01-10214	62	17	techniques	technique	NOUN
app01-10214	62	18	is	be	AUX
app01-10214	62	19	illustrated	illustrate	VERB
app01-10214	62	20	in	in	ADP
app01-10214	62	21	this	this	DET
app01-10214	62	22	section	section	NOUN
app01-10214	62	23	.	.	PUNCT
app01-10214	63	1	the	the	DET
app01-10214	63	2	sample	sample	NOUN
app01-10214	63	3	of	of	ADP
app01-10214	63	4	concrete	concrete	ADJ
app01-10214	63	5	morphology	morphology	NOUN
app01-10214	63	6	that	that	PRON
app01-10214	63	7	is	be	AUX
app01-10214	63	8	being	be	AUX
app01-10214	63	9	reconstructed	reconstruct	VERB
app01-10214	63	10	is	be	AUX
app01-10214	63	11	depicted	depict	VERB
app01-10214	63	12	in	in	ADP
app01-10214	63	13	figure	figure	NOUN
app01-10214	63	14	3a	3a	NUM
app01-10214	63	15	.	.	PUNCT
app01-10214	64	1	it	it	PRON
app01-10214	64	2	is	be	AUX
app01-10214	64	3	a	a	DET
app01-10214	64	4	ct	ct	NOUN
app01-10214	64	5	scan	scan	NOUN
app01-10214	64	6	of	of	ADP
app01-10214	64	7	the	the	DET
app01-10214	64	8	concrete	concrete	NOUN
app01-10214	64	9	transformed	transform	VERB
app01-10214	64	10	by	by	ADP
app01-10214	64	11	a	a	DET
app01-10214	64	12	segmentation	segmentation	NOUN
app01-10214	64	13	algorithm	algorithm	NOUN
app01-10214	64	14	into	into	ADP
app01-10214	64	15	a	a	DET
app01-10214	64	16	monochrome	monochrome	NOUN
app01-10214	64	17	image	image	NOUN
app01-10214	64	18	.	.	PUNCT
app01-10214	65	1	the	the	DET
app01-10214	65	2	white	white	ADJ
app01-10214	65	3	pixels	pixel	NOUN
app01-10214	65	4	indicate	indicate	VERB
app01-10214	65	5	the	the	DET
app01-10214	65	6	aggregates	aggregate	NOUN
app01-10214	65	7	and	and	CCONJ
app01-10214	65	8	the	the	DET
app01-10214	65	9	pores	pore	NOUN
app01-10214	65	10	,	,	PUNCT
app01-10214	65	11	while	while	SCONJ
app01-10214	65	12	the	the	DET
app01-10214	65	13	cementitious	cementitious	ADJ
app01-10214	65	14	binder	binder	NOUN
app01-10214	65	15	in	in	ADP
app01-10214	65	16	between	between	ADP
app01-10214	65	17	is	be	AUX
app01-10214	65	18	represented	represent	VERB
app01-10214	65	19	by	by	ADP
app01-10214	65	20	black	black	ADJ
app01-10214	65	21	pixels	pixel	NOUN
app01-10214	65	22	.	.	PUNCT
app01-10214	66	1	the	the	DET
app01-10214	66	2	sample	sample	NOUN
app01-10214	66	3	image	image	NOUN
app01-10214	66	4	was	be	AUX
app01-10214	66	5	captured	capture	VERB
app01-10214	66	6	on	on	ADP
app01-10214	66	7	a	a	DET
app01-10214	66	8	74	74	NUM
app01-10214	66	9	mm	mm	NOUN
app01-10214	66	10	diameter	diameter	NOUN
app01-10214	66	11	concrete	concrete	ADJ
app01-10214	66	12	cylinder	cylinder	NOUN
app01-10214	66	13	.	.	PUNCT
app01-10214	67	1	for	for	ADP
app01-10214	67	2	algorithmic	algorithmic	ADJ
app01-10214	67	3	simplicity	simplicity	NOUN
app01-10214	67	4	,	,	PUNCT
app01-10214	67	5	the	the	DET
app01-10214	67	6	largest	large	ADJ
app01-10214	67	7	possible	possible	ADJ
app01-10214	67	8	square	square	ADJ
app01-10214	67	9	image	image	NOUN
app01-10214	67	10	with	with	ADP
app01-10214	67	11	dimensions	dimension	NOUN
app01-10214	67	12	of	of	ADP
app01-10214	67	13	816×816	816×816	NUM
app01-10214	67	14	px	px	PROPN
app01-10214	67	15	is	be	AUX
app01-10214	67	16	selected	select	VERB
app01-10214	67	17	from	from	ADP
app01-10214	67	18	the	the	DET
app01-10214	67	19	original	original	ADJ
app01-10214	67	20	segmented	segment	VERB
app01-10214	67	21	image	image	NOUN
app01-10214	67	22	,	,	PUNCT
app01-10214	67	23	see	see	VERB
app01-10214	67	24	figure	figure	NOUN
app01-10214	67	25	3b	3b	NOUN
app01-10214	67	26	.	.	PUNCT
app01-10214	68	1	although	although	SCONJ
app01-10214	68	2	the	the	DET
app01-10214	68	3	training	training	NOUN
app01-10214	68	4	process	process	NOUN
app01-10214	68	5	of	of	ADP
app01-10214	68	6	our	our	PRON
app01-10214	68	7	computational	computational	ADJ
app01-10214	68	8	model	model	NOUN
app01-10214	68	9	is	be	AUX
app01-10214	68	10	accelerated	accelerate	VERB
app01-10214	68	11	on	on	ADP
app01-10214	68	12	a	a	DET
app01-10214	68	13	graphics	graphics	NOUN
app01-10214	68	14	card	card	NOUN
app01-10214	68	15	(	(	PUNCT
app01-10214	68	16	nvidia	nvidia	PROPN
app01-10214	68	17	geforce	geforce	NOUN
app01-10214	68	18	rtx	rtx	PROPN
app01-10214	68	19	2060	2060	NUM
app01-10214	68	20	)	)	PUNCT
app01-10214	68	21	,	,	PUNCT
app01-10214	68	22	it	it	PRON
app01-10214	68	23	turns	turn	VERB
app01-10214	68	24	out	out	ADP
app01-10214	68	25	that	that	SCONJ
app01-10214	68	26	it	it	PRON
app01-10214	68	27	is	be	AUX
app01-10214	68	28	not	not	PART
app01-10214	68	29	possible	possible	ADJ
app01-10214	68	30	to	to	PART
app01-10214	68	31	work	work	VERB
app01-10214	68	32	with	with	ADP
app01-10214	68	33	such	such	DET
app01-10214	68	34	a	a	DET
app01-10214	68	35	huge	huge	ADJ
app01-10214	68	36	dataset	dataset	NOUN
app01-10214	68	37	collected	collect	VERB
app01-10214	68	38	from	from	ADP
app01-10214	68	39	the	the	DET
app01-10214	68	40	largest	large	ADJ
app01-10214	68	41	possible	possible	ADJ
app01-10214	68	42	square	square	ADJ
app01-10214	68	43	image	image	NOUN
app01-10214	68	44	.	.	PUNCT
app01-10214	69	1	therefore	therefore	ADV
app01-10214	69	2	,	,	PUNCT
app01-10214	69	3	we	we	PRON
app01-10214	69	4	reduced	reduce	VERB
app01-10214	69	5	the	the	DET
app01-10214	69	6	image	image	NOUN
app01-10214	69	7	to	to	ADP
app01-10214	69	8	a	a	DET
app01-10214	69	9	final	final	ADJ
app01-10214	69	10	resolution	resolution	NOUN
app01-10214	69	11	of	of	ADP
app01-10214	69	12	400	400	NUM
app01-10214	69	13	×	×	NOUN
app01-10214	69	14	400	400	NUM
app01-10214	69	15	px	px	NOUN
app01-10214	69	16	minimizing	minimize	VERB
app01-10214	69	17	the	the	DET
app01-10214	69	18	work	work	NOUN
app01-10214	69	19	with	with	ADP
app01-10214	69	20	large	large	ADJ
app01-10214	69	21	data	datum	NOUN
app01-10214	69	22	files	file	NOUN
app01-10214	69	23	.	.	PUNCT
app01-10214	70	1	unfortunately	unfortunately	ADV
app01-10214	70	2	,	,	PUNCT
app01-10214	70	3	the	the	DET
app01-10214	70	4	segmentation	segmentation	NOUN
app01-10214	70	5	algorithm	algorithm	NOUN
app01-10214	70	6	does	do	AUX
app01-10214	70	7	not	not	PART
app01-10214	70	8	allow	allow	VERB
app01-10214	70	9	to	to	PART
app01-10214	70	10	identify	identify	VERB
app01-10214	70	11	between	between	ADP
app01-10214	70	12	the	the	DET
app01-10214	70	13	pore	pore	NOUN
app01-10214	70	14	and	and	CCONJ
app01-10214	70	15	the	the	DET
app01-10214	70	16	aggregate	aggregate	NOUN
app01-10214	70	17	and	and	CCONJ
app01-10214	70	18	labels	label	NOUN
app01-10214	70	19	both	both	DET
app01-10214	70	20	phases	phase	NOUN
app01-10214	70	21	identically	identically	ADV
app01-10214	70	22	as	as	ADP
app01-10214	70	23	white	white	ADJ
app01-10214	70	24	pixels	pixel	NOUN
app01-10214	70	25	.	.	PUNCT
app01-10214	71	1	since	since	SCONJ
app01-10214	71	2	the	the	DET
app01-10214	71	3	original	original	ADJ
app01-10214	71	4	grain	grain	NOUN
app01-10214	71	5	size	size	NOUN
app01-10214	71	6	distribution	distribution	NOUN
app01-10214	71	7	curve	curve	NOUN
app01-10214	71	8	is	be	AUX
app01-10214	71	9	known	know	VERB
app01-10214	71	10	,	,	PUNCT
app01-10214	71	11	a	a	DET
app01-10214	71	12	portion	portion	NOUN
app01-10214	71	13	of	of	ADP
app01-10214	71	14	the	the	DET
app01-10214	71	15	small	small	ADJ
app01-10214	71	16	white	white	ADJ
app01-10214	71	17	pixels	pixel	NOUN
app01-10214	71	18	has	have	AUX
app01-10214	71	19	been	be	AUX
app01-10214	71	20	removed	remove	VERB
app01-10214	71	21	so	so	SCONJ
app01-10214	71	22	that	that	SCONJ
app01-10214	71	23	the	the	DET
app01-10214	71	24	grain	grain	NOUN
app01-10214	71	25	size	size	NOUN
app01-10214	71	26	distribution	distribution	NOUN
app01-10214	71	27	curve	curve	NOUN
app01-10214	71	28	is	be	AUX
app01-10214	71	29	as	as	ADV
app01-10214	71	30	close	close	ADJ
app01-10214	71	31	as	as	ADP
app01-10214	71	32	possible	possible	ADJ
app01-10214	71	33	to	to	ADP
app01-10214	71	34	the	the	DET
app01-10214	71	35	original	original	ADJ
app01-10214	71	36	mixture	mixture	NOUN
app01-10214	71	37	curve	curve	NOUN
app01-10214	71	38	of	of	ADP
app01-10214	71	39	the	the	DET
app01-10214	71	40	concrete	concrete	ADJ
app01-10214	71	41	sample	sample	NOUN
app01-10214	71	42	.	.	PUNCT
app01-10214	72	1	the	the	DET
app01-10214	72	2	histogram	histogram	NOUN
app01-10214	72	3	shows	show	VERB
app01-10214	72	4	the	the	DET
app01-10214	72	5	grain	grain	NOUN
app01-10214	72	6	size	size	NOUN
app01-10214	72	7	distribution	distribution	NOUN
app01-10214	72	8	curve	curve	NOUN
app01-10214	72	9	of	of	ADP
app01-10214	72	10	the	the	DET
app01-10214	72	11	final	final	ADJ
app01-10214	72	12	image	image	NOUN
app01-10214	72	13	determined	determine	VERB
app01-10214	72	14	by	by	ADP
app01-10214	72	15	the	the	DET
app01-10214	72	16	principal	principal	ADJ
app01-10214	72	17	component	component	NOUN
app01-10214	72	18	analysis	analysis	NOUN
app01-10214	72	19	(	(	PUNCT
app01-10214	72	20	pca	pca	NOUN
app01-10214	72	21	)	)	PUNCT
app01-10214	72	22	and	and	CCONJ
app01-10214	72	23	feret	feret	PROPN
app01-10214	72	24	’s	’s	PART
app01-10214	72	25	characteristics	characteristic	NOUN
app01-10214	72	26	(	(	PUNCT
app01-10214	72	27	feret	feret	ADJ
app01-10214	72	28	)	)	PUNCT
app01-10214	72	29	,	,	PUNCT
app01-10214	72	30	and	and	CCONJ
app01-10214	72	31	the	the	DET
app01-10214	72	32	real	real	ADJ
app01-10214	72	33	volume	volume	NOUN
app01-10214	72	34	distributions	distribution	NOUN
app01-10214	72	35	of	of	ADP
app01-10214	72	36	aggregates	aggregate	NOUN
app01-10214	72	37	in	in	ADP
app01-10214	72	38	the	the	DET
app01-10214	72	39	investigated	investigate	VERB
app01-10214	72	40	concrete	concrete	NOUN
app01-10214	72	41	,	,	PUNCT
app01-10214	72	42	see	see	VERB
app01-10214	72	43	figure	figure	NOUN
app01-10214	72	44	4	4	NUM
app01-10214	72	45	.	.	PUNCT
app01-10214	73	1	the	the	DET
app01-10214	73	2	imperceptible	imperceptible	ADJ
app01-10214	73	3	differences	difference	NOUN
app01-10214	73	4	in	in	ADP
app01-10214	73	5	the	the	DET
app01-10214	73	6	histogram	histogram	NOUN
app01-10214	73	7	are	be	AUX
app01-10214	73	8	probably	probably	ADV
app01-10214	73	9	mainly	mainly	ADV
app01-10214	73	10	caused	cause	VERB
app01-10214	73	11	by	by	ADP
app01-10214	73	12	the	the	DET
app01-10214	73	13	absence	absence	NOUN
app01-10214	73	14	of	of	ADP
app01-10214	73	15	the	the	DET
app01-10214	73	16	third	third	ADJ
app01-10214	73	17	grain	grain	NOUN
app01-10214	73	18	dimension	dimension	NOUN
app01-10214	73	19	in	in	ADP
app01-10214	73	20	the	the	DET
app01-10214	73	21	calculafigure	calculafigure	NOUN
app01-10214	73	22	4	4	NUM
app01-10214	73	23	.	.	PUNCT
app01-10214	73	24	grain	grain	NOUN
app01-10214	73	25	size	size	NOUN
app01-10214	73	26	distribution	distribution	NOUN
app01-10214	73	27	curve	curve	NOUN
app01-10214	73	28	of	of	ADP
app01-10214	73	29	final	final	ADJ
app01-10214	73	30	image	image	NOUN
app01-10214	73	31	utilized	utilize	VERB
app01-10214	73	32	for	for	ADP
app01-10214	73	33	the	the	DET
app01-10214	73	34	reconstruction	reconstruction	NOUN
app01-10214	73	35	process	process	NOUN
app01-10214	73	36	.	.	PUNCT
app01-10214	74	1	the	the	DET
app01-10214	74	2	original	original	ADJ
app01-10214	74	3	data	datum	NOUN
app01-10214	74	4	(	(	PUNCT
app01-10214	74	5	blue	blue	ADV
app01-10214	74	6	-	-	PUNCT
app01-10214	74	7	labeled	label	VERB
app01-10214	74	8	)	)	PUNCT
app01-10214	74	9	represents	represent	VERB
app01-10214	74	10	the	the	DET
app01-10214	74	11	concrete	concrete	ADJ
app01-10214	74	12	mixture	mixture	NOUN
app01-10214	74	13	used	use	VERB
app01-10214	74	14	for	for	ADP
app01-10214	74	15	the	the	DET
app01-10214	74	16	ct	ct	PROPN
app01-10214	74	17	scanning	scanning	NOUN
app01-10214	74	18	.	.	PUNCT
app01-10214	75	1	the	the	DET
app01-10214	75	2	red	red	NOUN
app01-10214	75	3	-	-	PUNCT
app01-10214	75	4	labeled	label	VERB
app01-10214	75	5	and	and	CCONJ
app01-10214	75	6	orangelabeled	orangelabele	VERB
app01-10214	75	7	grain	grain	NOUN
app01-10214	75	8	size	size	NOUN
app01-10214	75	9	distribution	distribution	NOUN
app01-10214	75	10	curves	curve	NOUN
app01-10214	75	11	display	display	VERB
app01-10214	75	12	the	the	DET
app01-10214	75	13	results	result	NOUN
app01-10214	75	14	computed	compute	VERB
app01-10214	75	15	for	for	ADP
app01-10214	75	16	the	the	DET
app01-10214	75	17	pca	pca	PROPN
app01-10214	75	18	and	and	CCONJ
app01-10214	75	19	feret	feret	PROPN
app01-10214	75	20	’s	’s	PART
app01-10214	75	21	algorithm	algorithm	NOUN
app01-10214	75	22	,	,	PUNCT
app01-10214	75	23	respectively	respectively	ADV
app01-10214	75	24	.	.	PUNCT
app01-10214	76	1	tion	tion	NOUN
app01-10214	76	2	of	of	ADP
app01-10214	76	3	the	the	DET
app01-10214	76	4	grain	grain	NOUN
app01-10214	76	5	size	size	NOUN
app01-10214	76	6	distribution	distribution	NOUN
app01-10214	76	7	curves	curve	NOUN
app01-10214	76	8	.	.	PUNCT
app01-10214	77	1	the	the	DET
app01-10214	77	2	final	final	ADJ
app01-10214	77	3	400	400	NUM
app01-10214	77	4	×	×	NOUN
app01-10214	77	5	400	400	NUM
app01-10214	77	6	px	px	NOUN
app01-10214	77	7	image	image	NOUN
app01-10214	77	8	,	,	PUNCT
app01-10214	77	9	adjusted	adjust	VERB
app01-10214	77	10	for	for	ADP
app01-10214	77	11	redundant	redundant	ADJ
app01-10214	77	12	pores	pore	NOUN
app01-10214	77	13	,	,	PUNCT
app01-10214	77	14	is	be	AUX
app01-10214	77	15	shown	show	VERB
app01-10214	77	16	in	in	ADP
app01-10214	77	17	figure	figure	NOUN
app01-10214	77	18	3c	3c	NUM
app01-10214	77	19	.	.	PUNCT
app01-10214	78	1	the	the	DET
app01-10214	78	2	computational	computational	ADJ
app01-10214	78	3	image	image	NOUN
app01-10214	78	4	reconstruction	reconstruction	NOUN
app01-10214	78	5	algorithm	algorithm	NOUN
app01-10214	78	6	offers	offer	VERB
app01-10214	78	7	various	various	ADJ
app01-10214	78	8	solutions	solution	NOUN
app01-10214	78	9	with	with	ADP
app01-10214	78	10	different	different	ADJ
app01-10214	78	11	success	success	NOUN
app01-10214	78	12	rates	rate	NOUN
app01-10214	78	13	influenced	influence	VERB
app01-10214	78	14	by	by	ADP
app01-10214	78	15	several	several	ADJ
app01-10214	78	16	variables	variable	NOUN
app01-10214	78	17	.	.	PUNCT
app01-10214	79	1	the	the	DET
app01-10214	79	2	variables	variable	NOUN
app01-10214	79	3	affecting	affect	VERB
app01-10214	79	4	the	the	DET
app01-10214	79	5	reconstruction	reconstruction	NOUN
app01-10214	79	6	process	process	NOUN
app01-10214	79	7	are	be	AUX
app01-10214	79	8	mainly	mainly	ADV
app01-10214	79	9	:	:	PUNCT
app01-10214	79	10	(	(	PUNCT
app01-10214	79	11	1	1	NUM
app01-10214	79	12	.	.	NUM
app01-10214	79	13	)	)	PUNCT
app01-10214	79	14	hyper	hyper	NOUN
app01-10214	79	15	-	-	NOUN
app01-10214	79	16	parameters	parameter	NOUN
app01-10214	79	17	of	of	ADP
app01-10214	79	18	the	the	DET
app01-10214	79	19	model	model	NOUN
app01-10214	79	20	.	.	PUNCT
app01-10214	80	1	these	these	PRON
app01-10214	80	2	are	be	AUX
app01-10214	80	3	the	the	DET
app01-10214	80	4	parameters	parameter	NOUN
app01-10214	80	5	controlling	control	VERB
app01-10214	80	6	the	the	DET
app01-10214	80	7	neural	neural	ADJ
app01-10214	80	8	network	network	NOUN
app01-10214	80	9	architecture	architecture	NOUN
app01-10214	80	10	,	,	PUNCT
app01-10214	80	11	and	and	CCONJ
app01-10214	80	12	some	some	PRON
app01-10214	80	13	of	of	ADP
app01-10214	80	14	their	their	PRON
app01-10214	80	15	aspects	aspect	NOUN
app01-10214	80	16	are	be	AUX
app01-10214	80	17	examined	examine	VERB
app01-10214	80	18	here	here	ADV
app01-10214	80	19	in	in	ADP
app01-10214	80	20	detail	detail	NOUN
app01-10214	80	21	.	.	PUNCT
app01-10214	81	1	in	in	ADP
app01-10214	81	2	particular	particular	ADJ
app01-10214	81	3	,	,	PUNCT
app01-10214	81	4	the	the	DET
app01-10214	81	5	type	type	NOUN
app01-10214	81	6	of	of	ADP
app01-10214	81	7	neural	neural	ADJ
app01-10214	81	8	network	network	NOUN
app01-10214	81	9	layer	layer	NOUN
app01-10214	81	10	and	and	CCONJ
app01-10214	81	11	its	its	PRON
app01-10214	81	12	input	input	NOUN
app01-10214	81	13	parameters	parameter	NOUN
app01-10214	81	14	such	such	ADJ
app01-10214	81	15	as	as	ADP
app01-10214	81	16	the	the	DET
app01-10214	81	17	number	number	NOUN
app01-10214	81	18	of	of	ADP
app01-10214	81	19	neurons	neuron	NOUN
app01-10214	81	20	,	,	PUNCT
app01-10214	81	21	the	the	DET
app01-10214	81	22	composition	composition	NOUN
app01-10214	81	23	of	of	ADP
app01-10214	81	24	the	the	DET
app01-10214	81	25	layers	layer	NOUN
app01-10214	81	26	in	in	ADP
app01-10214	81	27	a	a	DET
app01-10214	81	28	sequence	sequence	NOUN
app01-10214	81	29	,	,	PUNCT
app01-10214	81	30	or	or	CCONJ
app01-10214	81	31	the	the	DET
app01-10214	81	32	total	total	ADJ
app01-10214	81	33	number	number	NOUN
app01-10214	81	34	of	of	ADP
app01-10214	81	35	layers	layer	NOUN
app01-10214	81	36	.	.	PUNCT
app01-10214	82	1	(	(	PUNCT
app01-10214	82	2	2	2	NUM
app01-10214	82	3	.	.	PUNCT
app01-10214	82	4	)	)	PUNCT
app01-10214	83	1	the	the	DET
app01-10214	83	2	size	size	NOUN
app01-10214	83	3	of	of	ADP
app01-10214	83	4	the	the	DET
app01-10214	83	5	pixel	pixel	PROPN
app01-10214	83	6	neighborhood	neighborhood	NOUN
app01-10214	83	7	is	be	AUX
app01-10214	83	8	the	the	DET
app01-10214	83	9	second	second	ADJ
app01-10214	83	10	essential	essential	ADJ
app01-10214	83	11	parameter	parameter	NOUN
app01-10214	83	12	that	that	PRON
app01-10214	83	13	significantly	significantly	ADV
app01-10214	83	14	affects	affect	VERB
app01-10214	83	15	87	87	NUM
app01-10214	83	16	ondřej	ondřej	NOUN
app01-10214	83	17	šperl	šperl	NOUN
app01-10214	83	18	,	,	PUNCT
app01-10214	83	19	jan	jan	PROPN
app01-10214	83	20	sýkora	sýkora	PROPN
app01-10214	83	21	acta	acta	PROPN
app01-10214	83	22	polytechnica	polytechnica	PROPN
app01-10214	83	23	ctu	ctu	PROPN
app01-10214	83	24	proceedings	proceeding	NOUN
app01-10214	83	25	original	original	ADJ
app01-10214	83	26	medium	medium	NOUN
app01-10214	83	27	#	#	SYM
app01-10214	83	28	1	1	NUM
app01-10214	83	29	#	#	SYM
app01-10214	83	30	2	2	NUM
app01-10214	83	31	#	#	SYM
app01-10214	83	32	3	3	NUM
app01-10214	83	33	#	#	SYM
app01-10214	83	34	4	4	NUM
app01-10214	83	35	#	#	SYM
app01-10214	83	36	5	5	NUM
app01-10214	83	37	#	#	SYM
app01-10214	83	38	6	6	NUM
app01-10214	83	39	#	#	SYM
app01-10214	83	40	7	7	NUM
app01-10214	83	41	#	#	SYM
app01-10214	83	42	8	8	NUM
app01-10214	83	43	#	#	SYM
app01-10214	83	44	9	9	NUM
app01-10214	83	45	#	#	SYM
app01-10214	83	46	10	10	NUM
app01-10214	83	47	figure	figure	NOUN
app01-10214	83	48	5	5	NUM
app01-10214	83	49	.	.	PUNCT
app01-10214	84	1	the	the	DET
app01-10214	84	2	original	original	ADJ
app01-10214	84	3	and	and	CCONJ
app01-10214	84	4	resulting	result	VERB
app01-10214	84	5	reconstructed	reconstructed	ADJ
app01-10214	84	6	images	image	NOUN
app01-10214	84	7	(	(	PUNCT
app01-10214	84	8	#	#	SYM
app01-10214	84	9	1–#10	1–#10	NUM
app01-10214	84	10	)	)	PUNCT
app01-10214	84	11	.	.	PUNCT
app01-10214	85	1	model	model	NOUN
app01-10214	85	2	i	i	PROPN
app01-10214	85	3	d	d	PROPN
app01-10214	85	4	architecture	architecture	NOUN
app01-10214	85	5	of	of	ADP
app01-10214	85	6	dnn	dnn	PROPN
app01-10214	85	7	#	#	SYM
app01-10214	85	8	1	1	NUM
app01-10214	85	9	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(64)_d(64)_d(64	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(64)_d(64)_d(64	NOUN
app01-10214	85	10	)	)	PUNCT
app01-10214	85	11	#	#	SYM
app01-10214	85	12	2	2	NUM
app01-10214	85	13	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(128)_d(128)_d(128	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(128)_d(128)_d(128	NUM
app01-10214	85	14	)	)	PUNCT
app01-10214	85	15	#	#	SYM
app01-10214	85	16	3	3	NUM
app01-10214	85	17	15x15_c(32,3x3)_c(32,3x3)_m(2x2)_d(64,l1_0.01)_d(64)_d(64	15x15_c(32,3x3)_c(32,3x3)_m(2x2)_d(64,l1_0.01)_d(64)_d(64	NUM
app01-10214	85	18	)	)	PUNCT
app01-10214	85	19	#	#	SYM
app01-10214	85	20	4	4	NUM
app01-10214	85	21	15x15_d(128)_d(128)_d(128	15x15_d(128)_d(128)_d(128	NUM
app01-10214	85	22	)	)	PUNCT
app01-10214	85	23	#	#	SYM
app01-10214	85	24	5	5	NUM
app01-10214	85	25	15x15_d(128)_d(128	15x15_d(128)_d(128	NUM
app01-10214	85	26	)	)	PUNCT
app01-10214	85	27	#	#	SYM
app01-10214	85	28	6	6	NUM
app01-10214	85	29	15x15_d(64)_d(64)_d(64	15x15_d(64)_d(64)_d(64	NOUN
app01-10214	85	30	)	)	PUNCT
app01-10214	85	31	#	#	SYM
app01-10214	85	32	7	7	NUM
app01-10214	85	33	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(128)_d(128)_d(128	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(128)_d(128)_d(128	NUM
app01-10214	85	34	)	)	PUNCT
app01-10214	85	35	#	#	SYM
app01-10214	85	36	8	8	NUM
app01-10214	85	37	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(128)_d(128	15x15_c(16,3x3)_c(16,3x3)_m(2x2)_d(128)_d(128	NUM
app01-10214	85	38	)	)	PUNCT
app01-10214	85	39	#	#	SYM
app01-10214	85	40	9	9	NUM
app01-10214	85	41	15x15_c(8,3x3)_c(8,3x3)_m(2x2)_d(128)_d(128)_d(128	15x15_c(8,3x3)_c(8,3x3)_m(2x2)_d(128)_d(128)_d(128	NUM
app01-10214	85	42	)	)	PUNCT
app01-10214	85	43	#	#	SYM
app01-10214	85	44	10	10	NUM
app01-10214	85	45	15x15_c(8,3x3)_c(8,3x3)_m(2x2)_d(64)_d(64)_d(64	15x15_c(8,3x3)_c(8,3x3)_m(2x2)_d(64)_d(64)_d(64	NUM
app01-10214	85	46	)	)	PUNCT
app01-10214	85	47	table	table	NOUN
app01-10214	85	48	1	1	NUM
app01-10214	85	49	.	.	PUNCT
app01-10214	85	50	model	model	PROPN
app01-10214	85	51	i	i	PROPN
app01-10214	85	52	d	d	PROPN
app01-10214	85	53	’s	’s	PART
app01-10214	85	54	and	and	CCONJ
app01-10214	85	55	abbreviated	abbreviate	VERB
app01-10214	85	56	names	name	NOUN
app01-10214	85	57	of	of	ADP
app01-10214	85	58	dnn	dnn	PROPN
app01-10214	85	59	architecture	architecture	NOUN
app01-10214	85	60	:	:	PUNCT
app01-10214	85	61	for	for	ADP
app01-10214	85	62	illustration	illustration	NOUN
app01-10214	85	63	,	,	PUNCT
app01-10214	85	64	15	15	NUM
app01-10214	85	65	×	×	NOUN
app01-10214	85	66	15	15	NUM
app01-10214	85	67	stands	stand	VERB
app01-10214	85	68	for	for	ADP
app01-10214	85	69	the	the	DET
app01-10214	85	70	pixel	pixel	PROPN
app01-10214	85	71	neighborhood	neighborhood	NOUN
app01-10214	85	72	,	,	PUNCT
app01-10214	85	73	i.e.	i.e.	X
app01-10214	85	74	the	the	DET
app01-10214	85	75	dimensions	dimension	NOUN
app01-10214	85	76	of	of	ADP
app01-10214	85	77	w	w	PROPN
app01-10214	85	78	and	and	CCONJ
app01-10214	85	79	h	h	NOUN
app01-10214	85	80	in	in	ADP
app01-10214	85	81	pixels	pixel	NOUN
app01-10214	85	82	,	,	PUNCT
app01-10214	85	83	c(16,3x3	c(16,3x3	PROPN
app01-10214	85	84	)	)	PUNCT
app01-10214	85	85	is	be	AUX
app01-10214	85	86	the	the	DET
app01-10214	85	87	convolutional	convolutional	ADJ
app01-10214	85	88	layer	layer	NOUN
app01-10214	85	89	with	with	ADP
app01-10214	85	90	16	16	NUM
app01-10214	85	91	filters	filter	NOUN
app01-10214	85	92	of	of	ADP
app01-10214	85	93	spatial	spatial	ADJ
app01-10214	85	94	size	size	NOUN
app01-10214	85	95	3x3	3x3	NUM
app01-10214	85	96	,	,	PUNCT
app01-10214	85	97	m(2x2	m(2x2	NOUN
app01-10214	85	98	)	)	PUNCT
app01-10214	85	99	is	be	AUX
app01-10214	85	100	the	the	DET
app01-10214	85	101	max	max	PROPN
app01-10214	85	102	pooling	pool	VERB
app01-10214	85	103	layer	layer	NOUN
app01-10214	85	104	with	with	ADP
app01-10214	85	105	2x2	2x2	NUM
app01-10214	85	106	filter	filter	NOUN
app01-10214	85	107	,	,	PUNCT
app01-10214	85	108	and	and	CCONJ
app01-10214	85	109	d(64	d(64	NOUN
app01-10214	85	110	)	)	PUNCT
app01-10214	85	111	is	be	AUX
app01-10214	85	112	the	the	DET
app01-10214	85	113	dense	dense	ADJ
app01-10214	85	114	layer	layer	NOUN
app01-10214	85	115	with	with	ADP
app01-10214	85	116	64	64	NUM
app01-10214	85	117	neurons	neuron	NOUN
app01-10214	85	118	.	.	PUNCT
app01-10214	86	1	the	the	DET
app01-10214	86	2	success	success	NOUN
app01-10214	86	3	rate	rate	NOUN
app01-10214	86	4	of	of	ADP
app01-10214	86	5	the	the	DET
app01-10214	86	6	entire	entire	ADJ
app01-10214	86	7	model	model	NOUN
app01-10214	86	8	.	.	PUNCT
app01-10214	87	1	this	this	DET
app01-10214	87	2	parameter	parameter	NOUN
app01-10214	87	3	has	have	AUX
app01-10214	87	4	also	also	ADV
app01-10214	87	5	been	be	AUX
app01-10214	87	6	investigated	investigate	VERB
app01-10214	87	7	;	;	PUNCT
app01-10214	87	8	however	however	ADV
app01-10214	87	9	,	,	PUNCT
app01-10214	87	10	due	due	ADP
app01-10214	87	11	to	to	ADP
app01-10214	87	12	the	the	DET
app01-10214	87	13	limited	limited	ADJ
app01-10214	87	14	space	space	NOUN
app01-10214	87	15	of	of	ADP
app01-10214	87	16	the	the	DET
app01-10214	87	17	paper	paper	NOUN
app01-10214	87	18	,	,	PUNCT
app01-10214	87	19	we	we	PRON
app01-10214	87	20	limit	limit	VERB
app01-10214	87	21	ourselves	ourselves	PRON
app01-10214	87	22	to	to	ADP
app01-10214	87	23	claiming	claim	VERB
app01-10214	87	24	that	that	PRON
app01-10214	87	25	for	for	ADP
app01-10214	87	26	the	the	DET
app01-10214	87	27	problem	problem	NOUN
app01-10214	87	28	illustrated	illustrate	VERB
app01-10214	87	29	here	here	ADV
app01-10214	87	30	,	,	PUNCT
app01-10214	87	31	a	a	DET
app01-10214	87	32	pixel	pixel	ADJ
app01-10214	87	33	neighborhood	neighborhood	NOUN
app01-10214	87	34	of	of	ADP
app01-10214	87	35	15	15	NUM
app01-10214	87	36	×	×	NOUN
app01-10214	87	37	15	15	NUM
app01-10214	87	38	px	px	NOUN
app01-10214	87	39	seems	seem	VERB
app01-10214	87	40	optimal	optimal	ADJ
app01-10214	87	41	.	.	PUNCT
app01-10214	88	1	the	the	DET
app01-10214	88	2	hyper	hyper	NOUN
app01-10214	88	3	-	-	NOUN
app01-10214	88	4	parameters	parameter	NOUN
app01-10214	88	5	of	of	ADP
app01-10214	88	6	the	the	DET
app01-10214	88	7	model	model	NOUN
app01-10214	88	8	are	be	AUX
app01-10214	88	9	investigated	investigate	VERB
app01-10214	88	10	on	on	ADP
app01-10214	88	11	the	the	DET
app01-10214	88	12	image	image	NOUN
app01-10214	88	13	with	with	ADP
app01-10214	88	14	dimensions	dimension	NOUN
app01-10214	88	15	of	of	ADP
app01-10214	88	16	300	300	NUM
app01-10214	88	17	×	×	NOUN
app01-10214	88	18	300	300	NUM
app01-10214	88	19	px	px	NOUN
app01-10214	88	20	,	,	PUNCT
app01-10214	88	21	see	see	VERB
app01-10214	88	22	figure	figure	NOUN
app01-10214	88	23	5	5	NUM
app01-10214	88	24	.	.	PUNCT
app01-10214	89	1	the	the	DET
app01-10214	89	2	reason	reason	NOUN
app01-10214	89	3	for	for	ADP
app01-10214	89	4	reducing	reduce	VERB
app01-10214	89	5	the	the	DET
app01-10214	89	6	image	image	NOUN
app01-10214	89	7	to	to	ADP
app01-10214	89	8	acceptable	acceptable	ADJ
app01-10214	89	9	dimensions	dimension	NOUN
app01-10214	89	10	is	be	AUX
app01-10214	89	11	again	again	ADV
app01-10214	89	12	the	the	DET
app01-10214	89	13	higher	high	ADJ
app01-10214	89	14	computational	computational	ADJ
app01-10214	89	15	effort	effort	NOUN
app01-10214	89	16	of	of	ADP
app01-10214	89	17	the	the	DET
app01-10214	89	18	entire	entire	ADJ
app01-10214	89	19	study	study	NOUN
app01-10214	89	20	,	,	PUNCT
app01-10214	89	21	which	which	PRON
app01-10214	89	22	is	be	AUX
app01-10214	89	23	performed	perform	VERB
app01-10214	89	24	on	on	ADP
app01-10214	89	25	a	a	DET
app01-10214	89	26	series	series	NOUN
app01-10214	89	27	of	of	ADP
app01-10214	89	28	10	10	NUM
app01-10214	89	29	architectures	architecture	NOUN
app01-10214	89	30	of	of	ADP
app01-10214	89	31	the	the	DET
app01-10214	89	32	neural	neural	ADJ
app01-10214	89	33	network	network	NOUN
app01-10214	89	34	with	with	ADP
app01-10214	89	35	differently	differently	ADV
app01-10214	89	36	composed	compose	VERB
app01-10214	89	37	convolutional	convolutional	ADJ
app01-10214	89	38	,	,	PUNCT
app01-10214	89	39	dense	dense	ADJ
app01-10214	89	40	,	,	PUNCT
app01-10214	89	41	and	and	CCONJ
app01-10214	89	42	max	max	PROPN
app01-10214	89	43	pooling	pool	VERB
app01-10214	89	44	layers	layer	NOUN
app01-10214	89	45	.	.	PUNCT
app01-10214	90	1	the	the	DET
app01-10214	90	2	model	model	NOUN
app01-10214	90	3	i	i	PROPN
app01-10214	90	4	d	d	PROPN
app01-10214	90	5	’s	’s	PART
app01-10214	90	6	and	and	CCONJ
app01-10214	90	7	abbreviated	abbreviate	VERB
app01-10214	90	8	names	name	NOUN
app01-10214	90	9	of	of	ADP
app01-10214	90	10	dnn	dnn	PROPN
app01-10214	90	11	architecture	architecture	NOUN
app01-10214	90	12	are	be	AUX
app01-10214	90	13	summarized	summarize	VERB
app01-10214	90	14	in	in	ADP
app01-10214	90	15	table	table	NOUN
app01-10214	90	16	1	1	NUM
app01-10214	90	17	.	.	PUNCT
app01-10214	91	1	it	it	PRON
app01-10214	91	2	is	be	AUX
app01-10214	91	3	obvious	obvious	ADJ
app01-10214	91	4	that	that	SCONJ
app01-10214	91	5	the	the	DET
app01-10214	91	6	possibility	possibility	NOUN
app01-10214	91	7	of	of	ADP
app01-10214	91	8	designing	design	VERB
app01-10214	91	9	the	the	DET
app01-10214	91	10	dnn	dnn	PROPN
app01-10214	91	11	architecture	architecture	NOUN
app01-10214	91	12	is	be	AUX
app01-10214	91	13	enormous	enormous	ADJ
app01-10214	91	14	,	,	PUNCT
app01-10214	91	15	especially	especially	ADV
app01-10214	91	16	in	in	ADP
app01-10214	91	17	terms	term	NOUN
app01-10214	91	18	of	of	ADP
app01-10214	91	19	filter	filter	NOUN
app01-10214	91	20	size	size	NOUN
app01-10214	91	21	or	or	CCONJ
app01-10214	91	22	number	number	NOUN
app01-10214	91	23	of	of	ADP
app01-10214	91	24	neurons	neuron	NOUN
app01-10214	91	25	;	;	PUNCT
app01-10214	91	26	thus	thus	ADV
app01-10214	91	27	this	this	DET
app01-10214	91	28	study	study	NOUN
app01-10214	91	29	is	be	AUX
app01-10214	91	30	limited	limit	VERB
app01-10214	91	31	more	more	ADV
app01-10214	91	32	to	to	ADP
app01-10214	91	33	the	the	DET
app01-10214	91	34	comparison	comparison	NOUN
app01-10214	91	35	between	between	ADP
app01-10214	91	36	the	the	DET
app01-10214	91	37	cnn	cnn	PROPN
app01-10214	91	38	and	and	CCONJ
app01-10214	91	39	dnn	dnn	PROPN
app01-10214	91	40	architectures	architecture	NOUN
app01-10214	91	41	.	.	PUNCT
app01-10214	92	1	the	the	DET
app01-10214	92	2	resulting	result	VERB
app01-10214	92	3	reconstructed	reconstruct	VERB
app01-10214	92	4	images	image	NOUN
app01-10214	92	5	for	for	ADP
app01-10214	92	6	ten	ten	NUM
app01-10214	92	7	different	different	ADJ
app01-10214	92	8	dnn	dnn	PROPN
app01-10214	92	9	architectures	architecture	NOUN
app01-10214	92	10	are	be	AUX
app01-10214	92	11	depicted	depict	VERB
app01-10214	92	12	in	in	ADP
app01-10214	92	13	figure	figure	NOUN
app01-10214	92	14	5	5	NUM
app01-10214	92	15	.	.	PUNCT
app01-10214	93	1	besides	besides	SCONJ
app01-10214	93	2	the	the	DET
app01-10214	93	3	visual	visual	ADJ
app01-10214	93	4	comparison	comparison	NOUN
app01-10214	93	5	,	,	PUNCT
app01-10214	93	6	the	the	DET
app01-10214	93	7	following	follow	VERB
app01-10214	93	8	table	table	NOUN
app01-10214	93	9	(	(	PUNCT
app01-10214	93	10	table	table	NOUN
app01-10214	93	11	2	2	NUM
app01-10214	93	12	)	)	PUNCT
app01-10214	93	13	displays	display	VERB
app01-10214	93	14	the	the	DET
app01-10214	93	15	values	value	NOUN
app01-10214	93	16	of	of	ADP
app01-10214	93	17	errors	error	NOUN
app01-10214	93	18	in	in	ADP
app01-10214	93	19	the	the	DET
app01-10214	93	20	statistical	statistical	ADJ
app01-10214	93	21	descriptors	descriptor	NOUN
app01-10214	93	22	computed	compute	VERB
app01-10214	93	23	for	for	ADP
app01-10214	93	24	the	the	DET
app01-10214	93	25	original	original	ADJ
app01-10214	93	26	and	and	CCONJ
app01-10214	93	27	reconstructed	reconstructed	ADJ
app01-10214	93	28	structures	structure	NOUN
app01-10214	93	29	.	.	PUNCT
app01-10214	94	1	from	from	ADP
app01-10214	94	2	the	the	DET
app01-10214	94	3	wide	wide	ADJ
app01-10214	94	4	range	range	NOUN
app01-10214	94	5	of	of	ADP
app01-10214	94	6	statistical	statistical	ADJ
app01-10214	94	7	descriptors	descriptor	NOUN
app01-10214	94	8	,	,	PUNCT
app01-10214	94	9	three	three	NUM
app01-10214	94	10	fundamental	fundamental	ADJ
app01-10214	94	11	metrics	metric	NOUN
app01-10214	94	12	are	be	AUX
app01-10214	94	13	selected	select	VERB
app01-10214	94	14	for	for	ADP
app01-10214	94	15	our	our	PRON
app01-10214	94	16	study	study	NOUN
app01-10214	94	17	–	–	PUNCT
app01-10214	94	18	the	the	DET
app01-10214	94	19	volume	volume	NOUN
app01-10214	94	20	fraction	fraction	NOUN
app01-10214	94	21	(	(	PUNCT
app01-10214	94	22	ϕ	ϕ	NOUN
app01-10214	94	23	)	)	PUNCT
app01-10214	94	24	,	,	PUNCT
app01-10214	94	25	the	the	DET
app01-10214	94	26	two	two	NUM
app01-10214	94	27	-	-	PUNCT
app01-10214	94	28	point	point	NOUN
app01-10214	94	29	proba88	proba88	NOUN
app01-10214	94	30	vol	vol	NOUN
app01-10214	94	31	.	.	PUNCT
app01-10214	95	1	49/2024	49/2024	NUM
app01-10214	95	2	reconstruction	reconstruction	NOUN
app01-10214	95	3	of	of	ADP
app01-10214	95	4	concrete	concrete	ADJ
app01-10214	95	5	morphology	morphology	NOUN
app01-10214	95	6	using	use	VERB
app01-10214	95	7	deep	deep	ADJ
app01-10214	95	8	learning	learning	NOUN
app01-10214	95	9	model	model	NOUN
app01-10214	96	1	i	i	PROPN
app01-10214	96	2	d	d	PROPN
app01-10214	96	3	ϵwhite	ϵwhite	PROPN
app01-10214	96	4	ϕ	ϕ	PROPN
app01-10214	97	1	ϵwhite	ϵwhite	PROPN
app01-10214	97	2	s2	s2	PROPN
app01-10214	97	3	ϵblack	ϵblack	NOUN
app01-10214	97	4	s2	s2	PROPN
app01-10214	97	5	ϵwhite	ϵwhite	ADJ
app01-10214	97	6	l2	l2	NOUN
app01-10214	97	7	ϵblack	ϵblack	NOUN
app01-10214	97	8	l2	l2	VERB
app01-10214	97	9	#	#	SYM
app01-10214	97	10	1	1	NUM
app01-10214	97	11	0.001797	0.001797	NUM
app01-10214	97	12	0.000157	0.000157	NUM
app01-10214	97	13	0.000158	0.000158	NUM
app01-10214	98	1	0.000171	0.000171	NUM
app01-10214	98	2	0.000106	0.000106	NUM
app01-10214	98	3	#	#	SYM
app01-10214	98	4	2	2	NUM
app01-10214	98	5	0.009209	0.009209	NUM
app01-10214	98	6	0.000185	0.000185	NUM
app01-10214	98	7	0.000220	0.000220	NUM
app01-10214	98	8	0.000205	0.000205	NUM
app01-10214	98	9	0.000117	0.000117	NUM
app01-10214	98	10	#	#	SYM
app01-10214	98	11	3	3	NUM
app01-10214	98	12	0.010342	0.010342	NUM
app01-10214	98	13	0.000238	0.000238	NUM
app01-10214	98	14	0.000284	0.000284	NUM
app01-10214	98	15	0.000202	0.000202	NUM
app01-10214	98	16	0.000148	0.000148	NUM
app01-10214	98	17	#	#	SYM
app01-10214	98	18	4	4	NUM
app01-10214	98	19	0.011240	0.011240	NUM
app01-10214	98	20	0.000247	0.000247	NUM
app01-10214	98	21	0.000303	0.000303	NUM
app01-10214	98	22	0.000213	0.000213	NUM
app01-10214	98	23	0.000153	0.000153	NUM
app01-10214	98	24	#	#	SYM
app01-10214	98	25	5	5	NUM
app01-10214	98	26	0.054454	0.054454	NUM
app01-10214	98	27	0.002175	0.002175	NUM
app01-10214	98	28	0.002939	0.002939	NUM
app01-10214	98	29	0.000796	0.000796	NUM
app01-10214	98	30	0.000557	0.000557	NUM
app01-10214	98	31	#	#	SYM
app01-10214	98	32	6	6	NUM
app01-10214	98	33	0.055820	0.055820	NUM
app01-10214	98	34	0.001978	0.001978	NUM
app01-10214	98	35	0.003782	0.003782	NUM
app01-10214	98	36	0.000727	0.000727	NUM
app01-10214	98	37	0.000627	0.000627	NUM
app01-10214	98	38	#	#	SYM
app01-10214	98	39	7	7	NUM
app01-10214	98	40	0.060252	0.060252	NUM
app01-10214	98	41	0.002672	0.002672	NUM
app01-10214	98	42	0.003554	0.003554	NUM
app01-10214	98	43	0.000884	0.000884	NUM
app01-10214	98	44	0.000614	0.000614	NUM
app01-10214	98	45	#	#	SYM
app01-10214	98	46	8	8	NUM
app01-10214	98	47	0.092767	0.092767	NUM
app01-10214	98	48	0.006558	0.006558	NUM
app01-10214	98	49	0.007819	0.007819	NUM
app01-10214	98	50	0.001403	0.001403	NUM
app01-10214	98	51	0.000919	0.000919	NUM
app01-10214	98	52	#	#	SYM
app01-10214	98	53	9	9	NUM
app01-10214	98	54	0.094060	0.094060	NUM
app01-10214	98	55	0.004631	0.004631	NUM
app01-10214	98	56	0.010755	0.010755	NUM
app01-10214	98	57	0.001173	0.001173	NUM
app01-10214	98	58	0.001081	0.001081	NUM
app01-10214	98	59	#	#	SYM
app01-10214	98	60	10	10	NUM
app01-10214	98	61	0.113770	0.113770	NUM
app01-10214	98	62	0.010151	0.010151	NUM
app01-10214	98	63	0.011235	0.011235	NUM
app01-10214	98	64	0.001756	0.001756	NUM
app01-10214	98	65	0.001106	0.001106	NUM
app01-10214	98	66	table	table	NOUN
app01-10214	98	67	2	2	NUM
app01-10214	98	68	.	.	PUNCT
app01-10214	99	1	the	the	DET
app01-10214	99	2	resulting	result	VERB
app01-10214	99	3	values	value	NOUN
app01-10214	99	4	of	of	ADP
app01-10214	99	5	errors	error	NOUN
app01-10214	99	6	calculated	calculate	VERB
app01-10214	99	7	for	for	ADP
app01-10214	99	8	the	the	DET
app01-10214	99	9	volume	volume	NOUN
app01-10214	99	10	fraction	fraction	NOUN
app01-10214	99	11	,	,	PUNCT
app01-10214	99	12	the	the	DET
app01-10214	99	13	two	two	NUM
app01-10214	99	14	-	-	PUNCT
app01-10214	99	15	point	point	NOUN
app01-10214	99	16	probability	probability	NOUN
app01-10214	99	17	function	function	NOUN
app01-10214	99	18	,	,	PUNCT
app01-10214	99	19	and	and	CCONJ
app01-10214	99	20	the	the	DET
app01-10214	99	21	lineal	lineal	ADJ
app01-10214	99	22	path	path	NOUN
app01-10214	99	23	function	function	NOUN
app01-10214	99	24	.	.	PUNCT
app01-10214	100	1	bility	bility	NOUN
app01-10214	100	2	function	function	NOUN
app01-10214	100	3	(	(	PUNCT
app01-10214	100	4	s2	s2	PROPN
app01-10214	100	5	)	)	PUNCT
app01-10214	100	6	,	,	PUNCT
app01-10214	100	7	and	and	CCONJ
app01-10214	100	8	the	the	DET
app01-10214	100	9	lineal	lineal	ADJ
app01-10214	100	10	path	path	NOUN
app01-10214	100	11	function	function	NOUN
app01-10214	100	12	(	(	PUNCT
app01-10214	100	13	l2	l2	NOUN
app01-10214	100	14	)	)	PUNCT
app01-10214	100	15	.	.	PUNCT
app01-10214	101	1	these	these	DET
app01-10214	101	2	statistical	statistical	ADJ
app01-10214	101	3	descriptors	descriptor	NOUN
app01-10214	101	4	have	have	AUX
app01-10214	101	5	been	be	AUX
app01-10214	101	6	used	use	VERB
app01-10214	101	7	in	in	ADP
app01-10214	101	8	reconstruction	reconstruction	NOUN
app01-10214	101	9	problems	problem	NOUN
app01-10214	101	10	for	for	ADP
app01-10214	101	11	a	a	DET
app01-10214	101	12	significant	significant	ADJ
app01-10214	101	13	period	period	NOUN
app01-10214	101	14	and	and	CCONJ
app01-10214	101	15	have	have	AUX
app01-10214	101	16	become	become	VERB
app01-10214	101	17	an	an	DET
app01-10214	101	18	essential	essential	ADJ
app01-10214	101	19	part	part	NOUN
app01-10214	101	20	of	of	ADP
app01-10214	101	21	numerical	numerical	ADJ
app01-10214	101	22	studies	study	NOUN
app01-10214	101	23	devoted	devote	VERB
app01-10214	101	24	to	to	ADP
app01-10214	101	25	material	material	NOUN
app01-10214	101	26	morphology	morphology	NOUN
app01-10214	101	27	.	.	PUNCT
app01-10214	102	1	their	their	PRON
app01-10214	102	2	particular	particular	ADJ
app01-10214	102	3	formulations	formulation	NOUN
app01-10214	102	4	are	be	AUX
app01-10214	102	5	skipped	skip	VERB
app01-10214	102	6	here	here	ADV
app01-10214	102	7	,	,	PUNCT
app01-10214	102	8	and	and	CCONJ
app01-10214	102	9	the	the	DET
app01-10214	102	10	interested	interested	ADJ
app01-10214	102	11	reader	reader	NOUN
app01-10214	102	12	referred	refer	VERB
app01-10214	102	13	to	to	ADP
app01-10214	102	14	,	,	PUNCT
app01-10214	102	15	e.g.	e.g.	ADV
app01-10214	102	16	,	,	PUNCT
app01-10214	102	17	[	[	X
app01-10214	102	18	17	17	NUM
app01-10214	102	19	]	]	PUNCT
app01-10214	102	20	or	or	CCONJ
app01-10214	102	21	[	[	X
app01-10214	102	22	2	2	X
app01-10214	102	23	]	]	PUNCT
app01-10214	102	24	providing	provide	VERB
app01-10214	102	25	basic	basic	ADJ
app01-10214	102	26	characteristics	characteristic	NOUN
app01-10214	102	27	,	,	PUNCT
app01-10214	102	28	illustrative	illustrative	ADJ
app01-10214	102	29	examples	example	NOUN
app01-10214	102	30	,	,	PUNCT
app01-10214	102	31	and	and	CCONJ
app01-10214	102	32	implementation	implementation	NOUN
app01-10214	102	33	strategies	strategy	NOUN
app01-10214	102	34	.	.	PUNCT
app01-10214	103	1	the	the	DET
app01-10214	103	2	values	value	NOUN
app01-10214	103	3	of	of	ADP
app01-10214	103	4	errors	error	NOUN
app01-10214	103	5	are	be	AUX
app01-10214	103	6	calculated	calculate	VERB
app01-10214	103	7	according	accord	VERB
app01-10214	103	8	to	to	ADP
app01-10214	103	9	the	the	DET
app01-10214	103	10	following	follow	VERB
app01-10214	103	11	formulas	formula	NOUN
app01-10214	103	12	expressing	express	VERB
app01-10214	103	13	the	the	DET
app01-10214	103	14	differences	difference	NOUN
app01-10214	103	15	between	between	ADP
app01-10214	103	16	values	value	NOUN
app01-10214	103	17	of	of	ADP
app01-10214	103	18	selected	select	VERB
app01-10214	103	19	statistical	statistical	ADJ
app01-10214	103	20	descriptors	descriptor	NOUN
app01-10214	103	21	calculated	calculate	VERB
app01-10214	103	22	for	for	ADP
app01-10214	103	23	the	the	DET
app01-10214	103	24	original	original	ADJ
app01-10214	103	25	and	and	CCONJ
app01-10214	103	26	reconstructed	reconstructed	ADJ
app01-10214	103	27	image	image	NOUN
app01-10214	103	28	:	:	PUNCT
app01-10214	103	29	ϵphase	ϵphase	PROPN
app01-10214	103	30	ϕ	ϕ	X
app01-10214	103	31	=	=	PUNCT
app01-10214	103	32	ϕphase	ϕphase	NOUN
app01-10214	103	33	orig	orig	NOUN
app01-10214	103	34	−	−	PROPN
app01-10214	103	35	ϕphase	ϕphase	PROPN
app01-10214	103	36	rec	rec	X
app01-10214	103	37	,	,	PUNCT
app01-10214	103	38	(	(	PUNCT
app01-10214	103	39	1	1	X
app01-10214	103	40	)	)	PUNCT
app01-10214	103	41	where	where	SCONJ
app01-10214	103	42	ϕphase	ϕphase	NOUN
app01-10214	103	43	orig	orig	NOUN
app01-10214	103	44	is	be	AUX
app01-10214	103	45	the	the	DET
app01-10214	103	46	volume	volume	NOUN
app01-10214	103	47	fractions	fraction	NOUN
app01-10214	103	48	of	of	ADP
app01-10214	103	49	a	a	DET
app01-10214	103	50	given	give	VERB
app01-10214	103	51	phase	phase	NOUN
app01-10214	103	52	corresponding	correspond	VERB
app01-10214	103	53	to	to	ADP
app01-10214	103	54	the	the	DET
app01-10214	103	55	original	original	ADJ
app01-10214	103	56	image	image	NOUN
app01-10214	103	57	,	,	PUNCT
app01-10214	103	58	ϕphase	ϕphase	PROPN
app01-10214	103	59	rec	rec	PROPN
app01-10214	103	60	is	be	AUX
app01-10214	103	61	the	the	DET
app01-10214	103	62	volume	volume	NOUN
app01-10214	103	63	fractions	fraction	NOUN
app01-10214	103	64	of	of	ADP
app01-10214	103	65	a	a	DET
app01-10214	103	66	given	give	VERB
app01-10214	103	67	phase	phase	NOUN
app01-10214	103	68	corresponding	correspond	VERB
app01-10214	103	69	to	to	ADP
app01-10214	103	70	the	the	DET
app01-10214	103	71	reconstructed	reconstructed	ADJ
app01-10214	103	72	image	image	NOUN
app01-10214	103	73	.	.	PUNCT
app01-10214	104	1	the	the	DET
app01-10214	104	2	values	value	NOUN
app01-10214	104	3	of	of	ADP
app01-10214	104	4	errors	error	NOUN
app01-10214	104	5	for	for	ADP
app01-10214	104	6	complex	complex	ADJ
app01-10214	104	7	statistical	statistical	ADJ
app01-10214	104	8	descriptors	descriptor	NOUN
app01-10214	104	9	are	be	AUX
app01-10214	104	10	evaluated	evaluate	VERB
app01-10214	104	11	as	as	ADP
app01-10214	104	12	:	:	PUNCT
app01-10214	104	13	ϵphase	ϵphase	PROPN
app01-10214	104	14	p	p	NOUN
app01-10214	104	15	=	=	PUNCT
app01-10214	104	16	r∑	r∑	NOUN
app01-10214	104	17	r=1	r=1	NOUN
app01-10214	104	18	s∑	s∑	PROPN
app01-10214	104	19	s=1	s=1	X
app01-10214	104	20	(	(	PUNCT
app01-10214	104	21	pphase	pphase	NOUN
app01-10214	104	22	rs	rs	NOUN
app01-10214	104	23	,	,	PUNCT
app01-10214	104	24	orig	orig	NOUN
app01-10214	104	25	−	−	NOUN
app01-10214	104	26	pphase	pphase	NOUN
app01-10214	104	27	rs	rs	NOUN
app01-10214	104	28	,	,	PUNCT
app01-10214	104	29	rec)2	rec)2	PROPN
app01-10214	104	30	sr	sr	PROPN
app01-10214	104	31	,	,	PUNCT
app01-10214	104	32	(	(	PUNCT
app01-10214	104	33	2	2	X
app01-10214	104	34	)	)	PUNCT
app01-10214	104	35	where	where	SCONJ
app01-10214	104	36	r	r	NOUN
app01-10214	104	37	and	and	CCONJ
app01-10214	104	38	s	s	NOUN
app01-10214	104	39	are	be	AUX
app01-10214	104	40	the	the	DET
app01-10214	104	41	image	image	NOUN
app01-10214	104	42	dimensions	dimension	NOUN
app01-10214	104	43	,	,	PUNCT
app01-10214	104	44	p	p	PROPN
app01-10214	104	45	is	be	AUX
app01-10214	104	46	the	the	DET
app01-10214	104	47	chosen	choose	VERB
app01-10214	104	48	statistical	statistical	ADJ
app01-10214	104	49	descriptor	descriptor	NOUN
app01-10214	104	50	,	,	PUNCT
app01-10214	104	51	here	here	ADV
app01-10214	104	52	p	p	NOUN
app01-10214	104	53	=	=	SYM
app01-10214	104	54	{	{	PUNCT
app01-10214	104	55	s2	s2	PROPN
app01-10214	104	56	,	,	PUNCT
app01-10214	104	57	l2	l2	NOUN
app01-10214	104	58	}	}	PUNCT
app01-10214	104	59	.	.	PUNCT
app01-10214	105	1	from	from	ADP
app01-10214	105	2	the	the	DET
app01-10214	105	3	resulting	result	VERB
app01-10214	105	4	values	value	NOUN
app01-10214	105	5	of	of	ADP
app01-10214	105	6	errors	error	NOUN
app01-10214	105	7	and	and	CCONJ
app01-10214	105	8	comparison	comparison	NOUN
app01-10214	105	9	of	of	ADP
app01-10214	105	10	the	the	DET
app01-10214	105	11	reconstructed	reconstruct	VERB
app01-10214	105	12	images	image	NOUN
app01-10214	105	13	,	,	PUNCT
app01-10214	105	14	two	two	NUM
app01-10214	105	15	models	model	NOUN
app01-10214	105	16	#	#	SYM
app01-10214	105	17	1	1	NUM
app01-10214	105	18	and	and	CCONJ
app01-10214	105	19	#	#	SYM
app01-10214	105	20	2	2	NUM
app01-10214	105	21	have	have	AUX
app01-10214	105	22	been	be	AUX
app01-10214	105	23	studied	study	VERB
app01-10214	105	24	in	in	ADP
app01-10214	105	25	detail	detail	NOUN
app01-10214	105	26	and	and	CCONJ
app01-10214	105	27	more	more	ADJ
app01-10214	105	28	runs	run	NOUN
app01-10214	105	29	of	of	ADP
app01-10214	105	30	reconstruction	reconstruction	NOUN
app01-10214	105	31	algorithm	algorithm	NOUN
app01-10214	105	32	have	have	AUX
app01-10214	105	33	been	be	AUX
app01-10214	105	34	performed	perform	VERB
app01-10214	105	35	focusing	focus	VERB
app01-10214	105	36	on	on	ADP
app01-10214	105	37	the	the	DET
app01-10214	105	38	statistical	statistical	ADJ
app01-10214	105	39	moments	moment	NOUN
app01-10214	105	40	of	of	ADP
app01-10214	105	41	error	error	NOUN
app01-10214	105	42	analysis	analysis	NOUN
app01-10214	105	43	.	.	PUNCT
app01-10214	106	1	the	the	DET
app01-10214	106	2	most	most	ADV
app01-10214	106	3	stable	stable	ADJ
app01-10214	106	4	classifier	classifier	NOUN
app01-10214	106	5	is	be	AUX
app01-10214	106	6	model	model	NOUN
app01-10214	106	7	#	#	SYM
app01-10214	106	8	2	2	NUM
app01-10214	106	9	,	,	PUNCT
app01-10214	106	10	which	which	PRON
app01-10214	106	11	is	be	AUX
app01-10214	106	12	further	far	ADV
app01-10214	106	13	utilized	utilize	VERB
app01-10214	106	14	for	for	ADP
app01-10214	106	15	reconstructing	reconstruct	VERB
app01-10214	106	16	the	the	DET
app01-10214	106	17	larger	large	ADJ
app01-10214	106	18	image	image	NOUN
app01-10214	106	19	of	of	ADP
app01-10214	106	20	the	the	DET
app01-10214	106	21	concrete	concrete	ADJ
app01-10214	106	22	cross	cross	NOUN
app01-10214	106	23	-	-	NOUN
app01-10214	106	24	section	section	NOUN
app01-10214	106	25	in	in	ADP
app01-10214	106	26	the	the	DET
app01-10214	106	27	following	follow	VERB
app01-10214	106	28	paragraph	paragraph	NOUN
app01-10214	106	29	.	.	PUNCT
app01-10214	107	1	3.1	3.1	NUM
app01-10214	107	2	.	.	PUNCT
app01-10214	108	1	large	large	ADJ
app01-10214	108	2	image	image	NOUN
app01-10214	108	3	evaluation	evaluation	NOUN
app01-10214	108	4	the	the	DET
app01-10214	108	5	final	final	ADJ
app01-10214	108	6	reconstruction	reconstruction	NOUN
app01-10214	108	7	is	be	AUX
app01-10214	108	8	carried	carry	VERB
app01-10214	108	9	out	out	ADP
app01-10214	108	10	on	on	ADP
app01-10214	108	11	an	an	DET
app01-10214	108	12	image	image	NOUN
app01-10214	108	13	of	of	ADP
app01-10214	108	14	dimensions	dimension	NOUN
app01-10214	108	15	400×400	400×400	PRON
app01-10214	108	16	px	px	NOUN
app01-10214	108	17	,	,	PUNCT
app01-10214	108	18	the	the	DET
app01-10214	108	19	original	original	ADJ
app01-10214	108	20	image	image	NOUN
app01-10214	108	21	is	be	AUX
app01-10214	108	22	shown	show	VERB
app01-10214	108	23	in	in	ADP
app01-10214	108	24	(	(	PUNCT
app01-10214	108	25	a	a	NOUN
app01-10214	108	26	)	)	PUNCT
app01-10214	108	27	.	.	PUNCT
app01-10214	109	1	original	original	ADJ
app01-10214	109	2	image	image	NOUN
app01-10214	109	3	–	–	PUNCT
app01-10214	109	4	400	400	NUM
app01-10214	109	5	×	×	NOUN
app01-10214	109	6	400	400	NUM
app01-10214	109	7	px	px	NOUN
app01-10214	109	8	.	.	PUNCT
app01-10214	109	9	(	(	PUNCT
app01-10214	109	10	b	b	NOUN
app01-10214	109	11	)	)	PUNCT
app01-10214	109	12	.	.	PUNCT
app01-10214	110	1	reconstructed	reconstructed	ADJ
app01-10214	110	2	image	image	NOUN
app01-10214	110	3	obtained	obtain	VERB
app01-10214	110	4	with	with	ADP
app01-10214	110	5	the	the	DET
app01-10214	110	6	model	model	NOUN
app01-10214	110	7	#	#	SYM
app01-10214	110	8	2	2	NUM
app01-10214	110	9	–	–	PUNCT
app01-10214	110	10	400	400	NUM
app01-10214	110	11	×	×	NOUN
app01-10214	110	12	400	400	NUM
app01-10214	110	13	px	px	PROPN
app01-10214	110	14	.	.	PROPN
app01-10214	110	15	figure	figure	NOUN
app01-10214	110	16	6	6	NUM
app01-10214	110	17	.	.	PUNCT
app01-10214	110	18	final	final	ADJ
app01-10214	110	19	image	image	NOUN
app01-10214	110	20	reconstruction	reconstruction	NOUN
app01-10214	110	21	.	.	PUNCT
app01-10214	111	1	figure	figure	VERB
app01-10214	111	2	6a	6a	NOUN
app01-10214	111	3	,	,	PUNCT
app01-10214	111	4	and	and	CCONJ
app01-10214	111	5	the	the	DET
app01-10214	111	6	reconstructed	reconstructed	ADJ
app01-10214	111	7	result	result	NOUN
app01-10214	111	8	is	be	AUX
app01-10214	111	9	in	in	ADP
app01-10214	111	10	figure	figure	NOUN
app01-10214	111	11	6b	6b	NOUN
app01-10214	111	12	.	.	PUNCT
app01-10214	112	1	it	it	PRON
app01-10214	112	2	is	be	AUX
app01-10214	112	3	apparent	apparent	ADJ
app01-10214	112	4	that	that	SCONJ
app01-10214	112	5	the	the	DET
app01-10214	112	6	reconstruction	reconstruction	NOUN
app01-10214	112	7	algorithm	algorithm	NOUN
app01-10214	112	8	is	be	AUX
app01-10214	112	9	quite	quite	ADV
app01-10214	112	10	successful	successful	ADJ
app01-10214	112	11	from	from	ADP
app01-10214	112	12	the	the	DET
app01-10214	112	13	visual	visual	ADJ
app01-10214	112	14	comparison	comparison	NOUN
app01-10214	112	15	of	of	ADP
app01-10214	112	16	these	these	DET
app01-10214	112	17	two	two	NUM
app01-10214	112	18	images	image	NOUN
app01-10214	112	19	.	.	PUNCT
app01-10214	113	1	however	however	ADV
app01-10214	113	2	,	,	PUNCT
app01-10214	113	3	some	some	DET
app01-10214	113	4	irregularities	irregularity	NOUN
app01-10214	113	5	are	be	AUX
app01-10214	113	6	observed	observe	VERB
app01-10214	113	7	in	in	ADP
app01-10214	113	8	the	the	DET
app01-10214	113	9	shape	shape	NOUN
app01-10214	113	10	of	of	ADP
app01-10214	113	11	the	the	DET
app01-10214	113	12	grains	grain	NOUN
app01-10214	113	13	compared	compare	VERB
app01-10214	113	14	to	to	ADP
app01-10214	113	15	the	the	DET
app01-10214	113	16	original	original	ADJ
app01-10214	113	17	image	image	NOUN
app01-10214	113	18	.	.	PUNCT
app01-10214	114	1	from	from	ADP
app01-10214	114	2	the	the	DET
app01-10214	114	3	perspective	perspective	NOUN
app01-10214	114	4	of	of	ADP
app01-10214	114	5	statistical	statistical	ADJ
app01-10214	114	6	descriptors	descriptor	NOUN
app01-10214	114	7	,	,	PUNCT
app01-10214	114	8	the	the	DET
app01-10214	114	9	following	follow	VERB
app01-10214	114	10	values	value	NOUN
app01-10214	114	11	of	of	ADP
app01-10214	114	12	errors	error	NOUN
app01-10214	114	13	–	–	PUNCT
app01-10214	114	14	ϵwhite	ϵwhite	PROPN
app01-10214	114	15	ϕ	ϕ	X
app01-10214	114	16	=	=	SYM
app01-10214	114	17	0.001046	0.001046	NUM
app01-10214	114	18	,	,	PUNCT
app01-10214	114	19	ϵwhite	ϵwhite	ADJ
app01-10214	114	20	s2	s2	NOUN
app01-10214	114	21	=	=	PUNCT
app01-10214	114	22	0.000171	0.000171	NUM
app01-10214	114	23	,	,	PUNCT
app01-10214	114	24	and	and	CCONJ
app01-10214	114	25	ϵwhite	ϵwhite	ADJ
app01-10214	114	26	l2	l2	NOUN
app01-10214	114	27	=	=	SYM
app01-10214	114	28	0.000069	0.000069	NUM
app01-10214	114	29	–	–	PUNCT
app01-10214	114	30	indicate	indicate	VERB
app01-10214	114	31	89	89	NUM
app01-10214	114	32	ondřej	ondřej	NOUN
app01-10214	114	33	šperl	šperl	NOUN
app01-10214	114	34	,	,	PUNCT
app01-10214	114	35	jan	jan	PROPN
app01-10214	114	36	sýkora	sýkora	PROPN
app01-10214	114	37	acta	acta	PROPN
app01-10214	114	38	polytechnica	polytechnica	PROPN
app01-10214	114	39	ctu	ctu	PROPN
app01-10214	114	40	proceedings	proceeding	NOUN
app01-10214	114	41	figure	figure	VERB
app01-10214	114	42	7	7	NUM
app01-10214	114	43	.	.	PUNCT
app01-10214	114	44	comparison	comparison	NOUN
app01-10214	114	45	of	of	ADP
app01-10214	114	46	grain	grain	NOUN
app01-10214	114	47	size	size	NOUN
app01-10214	114	48	distribution	distribution	NOUN
app01-10214	114	49	curves	curve	NOUN
app01-10214	114	50	obtained	obtain	VERB
app01-10214	114	51	for	for	ADP
app01-10214	114	52	the	the	DET
app01-10214	114	53	original	original	ADJ
app01-10214	114	54	and	and	CCONJ
app01-10214	114	55	reconstructed	reconstructed	ADJ
app01-10214	114	56	concrete	concrete	ADJ
app01-10214	114	57	cross	cross	NOUN
app01-10214	114	58	-	-	NOUN
app01-10214	114	59	sections	section	NOUN
app01-10214	114	60	.	.	PUNCT
app01-10214	115	1	again	again	ADV
app01-10214	115	2	good	good	ADJ
app01-10214	115	3	performance	performance	NOUN
app01-10214	115	4	of	of	ADP
app01-10214	115	5	proposed	propose	VERB
app01-10214	115	6	strategy	strategy	NOUN
app01-10214	115	7	.	.	PUNCT
app01-10214	116	1	the	the	DET
app01-10214	116	2	last	last	ADJ
app01-10214	116	3	comparison	comparison	NOUN
app01-10214	116	4	(	(	PUNCT
app01-10214	116	5	see	see	VERB
app01-10214	116	6	figure	figure	NOUN
app01-10214	116	7	7	7	NUM
app01-10214	116	8	)	)	PUNCT
app01-10214	116	9	shows	show	VERB
app01-10214	116	10	the	the	DET
app01-10214	116	11	grain	grain	NOUN
app01-10214	116	12	size	size	NOUN
app01-10214	116	13	distribution	distribution	NOUN
app01-10214	116	14	curves	curve	NOUN
app01-10214	116	15	of	of	ADP
app01-10214	116	16	original	original	ADJ
app01-10214	116	17	and	and	CCONJ
app01-10214	116	18	reconstructed	reconstructed	ADJ
app01-10214	116	19	images	image	NOUN
app01-10214	116	20	computed	compute	VERB
app01-10214	116	21	for	for	ADP
app01-10214	116	22	the	the	DET
app01-10214	116	23	algorithm	algorithm	NOUN
app01-10214	116	24	using	use	VERB
app01-10214	116	25	feret	feret	ADJ
app01-10214	116	26	diameters	diameter	NOUN
app01-10214	116	27	(	(	PUNCT
app01-10214	116	28	feret	feret	ADJ
app01-10214	116	29	)	)	PUNCT
app01-10214	116	30	and	and	CCONJ
app01-10214	116	31	principal	principal	ADJ
app01-10214	116	32	component	component	NOUN
app01-10214	116	33	analysis	analysis	NOUN
app01-10214	116	34	(	(	PUNCT
app01-10214	116	35	pca	pca	NOUN
app01-10214	116	36	)	)	PUNCT
app01-10214	116	37	.	.	PUNCT
app01-10214	117	1	in	in	ADP
app01-10214	117	2	the	the	DET
app01-10214	117	3	case	case	NOUN
app01-10214	117	4	of	of	ADP
app01-10214	117	5	the	the	DET
app01-10214	117	6	pca	pca	PROPN
app01-10214	117	7	evaluation	evaluation	NOUN
app01-10214	117	8	,	,	PUNCT
app01-10214	117	9	the	the	DET
app01-10214	117	10	original	original	ADJ
app01-10214	117	11	and	and	CCONJ
app01-10214	117	12	reconstructed	reconstructed	ADJ
app01-10214	117	13	images	image	NOUN
app01-10214	117	14	differ	differ	VERB
app01-10214	117	15	in	in	ADP
app01-10214	117	16	the	the	DET
app01-10214	117	17	representation	representation	NOUN
app01-10214	117	18	of	of	ADP
app01-10214	117	19	the	the	DET
app01-10214	117	20	individual	individual	ADJ
app01-10214	117	21	grain	grain	NOUN
app01-10214	117	22	size	size	NOUN
app01-10214	117	23	as	as	SCONJ
app01-10214	117	24	follows	follow	VERB
app01-10214	117	25	:	:	PUNCT
app01-10214	117	26	size	size	NOUN
app01-10214	117	27	range	range	NOUN
app01-10214	117	28	of	of	ADP
app01-10214	117	29	0–4	0–4	NUM
app01-10214	117	30	mm	mm	PROPN
app01-10214	117	31	–	–	PUNCT
app01-10214	117	32	17.7	17.7	NUM
app01-10214	117	33	%	%	NOUN
app01-10214	117	34	,	,	PUNCT
app01-10214	117	35	4–8	4–8	NUM
app01-10214	117	36	mm	mm	NOUN
app01-10214	117	37	–	–	PUNCT
app01-10214	117	38	8.6	8.6	NUM
app01-10214	117	39	%	%	NOUN
app01-10214	117	40	,	,	PUNCT
app01-10214	117	41	and	and	CCONJ
app01-10214	117	42	8–16	8–16	PROPN
app01-10214	117	43	mm	mm	PROPN
app01-10214	117	44	–	–	PUNCT
app01-10214	117	45	9.1	9.1	NUM
app01-10214	117	46	%	%	NOUN
app01-10214	117	47	.	.	PUNCT
app01-10214	118	1	in	in	ADP
app01-10214	118	2	the	the	DET
app01-10214	118	3	case	case	NOUN
app01-10214	118	4	of	of	ADP
app01-10214	118	5	the	the	DET
app01-10214	118	6	feret	feret	ADJ
app01-10214	118	7	diameters	diameter	NOUN
app01-10214	118	8	,	,	PUNCT
app01-10214	118	9	the	the	DET
app01-10214	118	10	grain	grain	NOUN
app01-10214	118	11	size	size	NOUN
app01-10214	118	12	distribution	distribution	NOUN
app01-10214	118	13	differs	differ	VERB
app01-10214	118	14	as	as	SCONJ
app01-10214	118	15	follows	follow	VERB
app01-10214	118	16	:	:	PUNCT
app01-10214	118	17	size	size	NOUN
app01-10214	118	18	range	range	NOUN
app01-10214	118	19	of	of	ADP
app01-10214	118	20	0–4	0–4	NUM
app01-10214	118	21	mm	mm	PROPN
app01-10214	118	22	–	–	PUNCT
app01-10214	118	23	8.6	8.6	NUM
app01-10214	118	24	%	%	NOUN
app01-10214	118	25	,	,	PUNCT
app01-10214	118	26	4–8	4–8	NUM
app01-10214	118	27	mm	mm	NOUN
app01-10214	118	28	–	–	PUNCT
app01-10214	118	29	3.9	3.9	NUM
app01-10214	118	30	%	%	NOUN
app01-10214	118	31	,	,	PUNCT
app01-10214	118	32	and	and	CCONJ
app01-10214	118	33	8–16	8–16	PROPN
app01-10214	118	34	mm	mm	PROPN
app01-10214	118	35	–	–	PUNCT
app01-10214	118	36	4.7	4.7	NUM
app01-10214	118	37	%	%	NOUN
app01-10214	118	38	.	.	PUNCT
app01-10214	119	1	thus	thus	ADV
app01-10214	119	2	,	,	PUNCT
app01-10214	119	3	the	the	DET
app01-10214	119	4	reconstructed	reconstructed	ADJ
app01-10214	119	5	image	image	NOUN
app01-10214	119	6	contains	contain	VERB
app01-10214	119	7	more	more	ADJ
app01-10214	119	8	aggregates	aggregate	NOUN
app01-10214	119	9	of	of	ADP
app01-10214	119	10	0–4	0–4	NUM
app01-10214	119	11	mm	mm	NOUN
app01-10214	119	12	since	since	SCONJ
app01-10214	119	13	both	both	DET
app01-10214	119	14	methods	method	NOUN
app01-10214	119	15	result	result	VERB
app01-10214	119	16	in	in	ADP
app01-10214	119	17	a	a	DET
app01-10214	119	18	higher	high	ADJ
app01-10214	119	19	volume	volume	NOUN
app01-10214	119	20	percentage	percentage	NOUN
app01-10214	119	21	,	,	PUNCT
app01-10214	119	22	and	and	CCONJ
app01-10214	119	23	conversely	conversely	ADV
app01-10214	119	24	,	,	PUNCT
app01-10214	119	25	size	size	NOUN
app01-10214	119	26	ranges	range	NOUN
app01-10214	119	27	of	of	ADP
app01-10214	119	28	4–8	4–8	NUM
app01-10214	119	29	mm	mm	NOUN
app01-10214	119	30	and	and	CCONJ
app01-10214	119	31	8–16	8–16	PROPN
app01-10214	119	32	mm	mm	PROPN
app01-10214	119	33	are	be	AUX
app01-10214	119	34	less	less	ADV
app01-10214	119	35	observed	observed	ADJ
app01-10214	119	36	in	in	ADP
app01-10214	119	37	the	the	DET
app01-10214	119	38	reconstructed	reconstructed	ADJ
app01-10214	119	39	image	image	NOUN
app01-10214	119	40	.	.	PUNCT
app01-10214	120	1	from	from	ADP
app01-10214	120	2	the	the	DET
app01-10214	120	3	perspective	perspective	NOUN
app01-10214	120	4	of	of	ADP
app01-10214	120	5	the	the	DET
app01-10214	120	6	grain	grain	NOUN
app01-10214	120	7	size	size	NOUN
app01-10214	120	8	distribution	distribution	NOUN
app01-10214	120	9	curve	curve	NOUN
app01-10214	120	10	,	,	PUNCT
app01-10214	120	11	the	the	DET
app01-10214	120	12	reconstruction	reconstruction	NOUN
app01-10214	120	13	process	process	NOUN
app01-10214	120	14	of	of	ADP
app01-10214	120	15	concrete	concrete	ADJ
app01-10214	120	16	morphology	morphology	NOUN
app01-10214	120	17	is	be	AUX
app01-10214	120	18	less	less	ADV
app01-10214	120	19	effective	effective	ADJ
app01-10214	120	20	.	.	PUNCT
app01-10214	121	1	4	4	X
app01-10214	121	2	.	.	X
app01-10214	121	3	conclusion	conclusion	VERB
app01-10214	121	4	the	the	DET
app01-10214	121	5	reconstruction	reconstruction	NOUN
app01-10214	121	6	of	of	ADP
app01-10214	121	7	the	the	DET
app01-10214	121	8	concrete	concrete	ADJ
app01-10214	121	9	cross	cross	ADJ
app01-10214	121	10	-	-	ADJ
app01-10214	121	11	section	section	ADJ
app01-10214	121	12	area	area	NOUN
app01-10214	121	13	using	use	VERB
app01-10214	121	14	deep	deep	ADJ
app01-10214	121	15	learning	learning	NOUN
app01-10214	121	16	techniques	technique	NOUN
app01-10214	121	17	is	be	AUX
app01-10214	121	18	illustrated	illustrate	VERB
app01-10214	121	19	in	in	ADP
app01-10214	121	20	this	this	DET
app01-10214	121	21	paper	paper	NOUN
app01-10214	121	22	.	.	PUNCT
app01-10214	122	1	the	the	DET
app01-10214	122	2	proposed	propose	VERB
app01-10214	122	3	model	model	NOUN
app01-10214	122	4	can	can	AUX
app01-10214	122	5	generate	generate	VERB
app01-10214	122	6	reasonably	reasonably	ADV
app01-10214	122	7	accurate	accurate	ADJ
app01-10214	122	8	samples	sample	NOUN
app01-10214	122	9	of	of	ADP
app01-10214	122	10	concrete	concrete	ADJ
app01-10214	122	11	morphology	morphology	NOUN
app01-10214	122	12	in	in	ADP
app01-10214	122	13	terms	term	NOUN
app01-10214	122	14	of	of	ADP
app01-10214	122	15	the	the	DET
app01-10214	122	16	selected	select	VERB
app01-10214	122	17	statistical	statistical	ADJ
app01-10214	122	18	descriptors	descriptor	NOUN
app01-10214	122	19	.	.	PUNCT
app01-10214	123	1	some	some	DET
app01-10214	123	2	limitations	limitation	NOUN
app01-10214	123	3	are	be	AUX
app01-10214	123	4	observed	observe	VERB
app01-10214	123	5	in	in	ADP
app01-10214	123	6	the	the	DET
app01-10214	123	7	results	result	NOUN
app01-10214	123	8	of	of	ADP
app01-10214	123	9	the	the	DET
app01-10214	123	10	grain	grain	NOUN
app01-10214	123	11	size	size	NOUN
app01-10214	123	12	distribution	distribution	NOUN
app01-10214	123	13	curve	curve	NOUN
app01-10214	123	14	,	,	PUNCT
app01-10214	123	15	and	and	CCONJ
app01-10214	123	16	the	the	DET
app01-10214	123	17	shapes	shape	NOUN
app01-10214	123	18	of	of	ADP
app01-10214	123	19	the	the	DET
app01-10214	123	20	aggregates	aggregate	NOUN
app01-10214	123	21	which	which	PRON
app01-10214	123	22	appear	appear	VERB
app01-10214	123	23	to	to	PART
app01-10214	123	24	be	be	AUX
app01-10214	123	25	more	more	ADV
app01-10214	123	26	irregular	irregular	ADJ
app01-10214	123	27	.	.	PUNCT
app01-10214	124	1	taking	take	VERB
app01-10214	124	2	into	into	ADP
app01-10214	124	3	account	account	NOUN
app01-10214	124	4	that	that	SCONJ
app01-10214	124	5	the	the	DET
app01-10214	124	6	computational	computational	ADJ
app01-10214	124	7	hardware	hardware	NOUN
app01-10214	124	8	has	have	VERB
app01-10214	124	9	some	some	DET
app01-10214	124	10	limitations	limitation	NOUN
app01-10214	124	11	and	and	CCONJ
app01-10214	124	12	also	also	ADV
app01-10214	124	13	the	the	DET
app01-10214	124	14	fact	fact	NOUN
app01-10214	124	15	that	that	SCONJ
app01-10214	124	16	we	we	PRON
app01-10214	124	17	only	only	ADV
app01-10214	124	18	handled	handle	VERB
app01-10214	124	19	one	one	NUM
app01-10214	124	20	image	image	NOUN
app01-10214	124	21	,	,	PUNCT
app01-10214	124	22	the	the	DET
app01-10214	124	23	obtained	obtain	VERB
app01-10214	124	24	result	result	NOUN
app01-10214	124	25	can	can	AUX
app01-10214	124	26	be	be	AUX
app01-10214	124	27	evaluated	evaluate	VERB
app01-10214	124	28	positively	positively	ADV
app01-10214	124	29	.	.	PUNCT
app01-10214	125	1	acknowledgements	acknowledgement	NOUN
app01-10214	125	2	the	the	DET
app01-10214	125	3	authors	author	NOUN
app01-10214	125	4	are	be	AUX
app01-10214	125	5	thankful	thankful	ADJ
app01-10214	125	6	for	for	ADP
app01-10214	125	7	financial	financial	ADJ
app01-10214	125	8	support	support	NOUN
app01-10214	125	9	from	from	ADP
app01-10214	125	10	the	the	DET
app01-10214	125	11	student	student	NOUN
app01-10214	125	12	grant	grant	NOUN
app01-10214	125	13	competition	competition	NOUN
app01-10214	125	14	of	of	ADP
app01-10214	125	15	ctu	ctu	NOUN
app01-10214	125	16	,	,	PUNCT
app01-10214	125	17	project	project	NOUN
app01-10214	125	18	no	no	NOUN
app01-10214	125	19	.	.	PUNCT
app01-10214	126	1	sgs23/152	sgs23/152	PROPN
app01-10214	126	2	/	/	SYM
app01-10214	127	1	ohk1/3t/11	ohk1/3t/11	PROPN
app01-10214	127	2	and	and	CCONJ
app01-10214	127	3	the	the	DET
app01-10214	127	4	czech	czech	PROPN
app01-10214	127	5	science	science	PROPN
app01-10214	127	6	foundation	foundation	PROPN
app01-10214	127	7	,	,	PUNCT
app01-10214	127	8	project	project	VERB
app01-10214	127	9	no	no	NOUN
app01-10214	127	10	.	.	NOUN
app01-10214	128	1	22	22	NUM
app01-10214	128	2	-	-	PUNCT
app01-10214	128	3	35755k	35755k	NUM
app01-10214	128	4	.	.	PUNCT
app01-10214	129	1	references	reference	NOUN
app01-10214	129	2	[	[	X
app01-10214	129	3	1	1	NUM
app01-10214	129	4	]	]	PUNCT
app01-10214	129	5	c.	c.	PROPN
app01-10214	129	6	l.	l.	PROPN
app01-10214	129	7	y.	y.	PROPN
app01-10214	129	8	yeong	yeong	PROPN
app01-10214	129	9	,	,	PUNCT
app01-10214	129	10	s.	s.	PROPN
app01-10214	129	11	torquato	torquato	PROPN
app01-10214	129	12	.	.	PUNCT
app01-10214	129	13	reconstructing	reconstruct	VERB
app01-10214	129	14	random	random	ADJ
app01-10214	129	15	media	medium	NOUN
app01-10214	129	16	.	.	PUNCT
app01-10214	130	1	physical	physical	ADJ
app01-10214	130	2	review	review	NOUN
app01-10214	130	3	e	e	PROPN
app01-10214	130	4	57(1):495	57(1):495	NUM
app01-10214	130	5	,	,	PUNCT
app01-10214	130	6	1998	1998	NUM
app01-10214	130	7	.	.	PUNCT
app01-10214	131	1	https://doi.org/10.1103/physreve.57.495	https://doi.org/10.1103/physreve.57.495	PROPN
app01-10214	131	2	[	[	X
app01-10214	131	3	2	2	X
app01-10214	131	4	]	]	PUNCT
app01-10214	131	5	j.	j.	PROPN
app01-10214	131	6	havelka	havelka	PROPN
app01-10214	131	7	,	,	PUNCT
app01-10214	131	8	a.	a.	PROPN
app01-10214	131	9	kučerová	kučerová	PROPN
app01-10214	131	10	,	,	PUNCT
app01-10214	131	11	j.	j.	PROPN
app01-10214	131	12	sýkora	sýkora	PROPN
app01-10214	131	13	.	.	PUNCT
app01-10214	132	1	compression	compression	NOUN
app01-10214	132	2	and	and	CCONJ
app01-10214	132	3	reconstruction	reconstruction	NOUN
app01-10214	132	4	of	of	ADP
app01-10214	132	5	random	random	ADJ
app01-10214	132	6	microstructures	microstructure	NOUN
app01-10214	132	7	using	use	VERB
app01-10214	132	8	accelerated	accelerate	VERB
app01-10214	132	9	lineal	lineal	ADJ
app01-10214	132	10	path	path	NOUN
app01-10214	132	11	function	function	NOUN
app01-10214	132	12	.	.	PUNCT
app01-10214	133	1	computational	computational	ADJ
app01-10214	133	2	materials	material	NOUN
app01-10214	133	3	science	science	NOUN
app01-10214	133	4	122:102–117	122:102–117	NUM
app01-10214	133	5	,	,	PUNCT
app01-10214	133	6	2016	2016	NUM
app01-10214	133	7	.	.	PUNCT
app01-10214	134	1	https://doi.org/10.1016/j.commatsci.2016.04.044	https://doi.org/10.1016/j.commatsci.2016.04.044	PROPN
app01-10214	134	2	[	[	X
app01-10214	134	3	3	3	NUM
app01-10214	134	4	]	]	X
app01-10214	134	5	r.	r.	PROPN
app01-10214	134	6	bostanabad	bostanabad	PROPN
app01-10214	134	7	,	,	PUNCT
app01-10214	134	8	y.	y.	PROPN
app01-10214	134	9	zhang	zhang	PROPN
app01-10214	134	10	,	,	PUNCT
app01-10214	134	11	x.	x.	PROPN
app01-10214	134	12	li	li	PROPN
app01-10214	134	13	,	,	PUNCT
app01-10214	134	14	et	et	PROPN
app01-10214	135	1	al	al	PROPN
app01-10214	135	2	.	.	PUNCT
app01-10214	135	3	computational	computational	ADJ
app01-10214	135	4	microstructure	microstructure	ADJ
app01-10214	135	5	characterization	characterization	NOUN
app01-10214	135	6	and	and	CCONJ
app01-10214	135	7	reconstruction	reconstruction	NOUN
app01-10214	135	8	:	:	PUNCT
app01-10214	135	9	review	review	NOUN
app01-10214	135	10	of	of	ADP
app01-10214	135	11	the	the	DET
app01-10214	135	12	state	state	NOUN
app01-10214	135	13	-	-	PUNCT
app01-10214	135	14	of	of	ADP
app01-10214	135	15	-	-	PUNCT
app01-10214	135	16	the	the	DET
app01-10214	135	17	-	-	PUNCT
app01-10214	135	18	art	art	NOUN
app01-10214	135	19	techniques	technique	NOUN
app01-10214	135	20	.	.	PUNCT
app01-10214	136	1	progress	progress	NOUN
app01-10214	136	2	in	in	ADP
app01-10214	136	3	materials	material	NOUN
app01-10214	136	4	science	science	NOUN
app01-10214	136	5	95:1–41	95:1–41	NUM
app01-10214	136	6	,	,	PUNCT
app01-10214	136	7	2018	2018	NUM
app01-10214	136	8	.	.	PUNCT
app01-10214	137	1	https://doi.org/10.1016/j.pmatsci.2018.01.005	https://doi.org/10.1016/j.pmatsci.2018.01.005	NUM
app01-10214	138	1	[	[	X
app01-10214	138	2	4	4	NUM
app01-10214	138	3	]	]	X
app01-10214	138	4	m.	m.	NOUN
app01-10214	138	5	v.	v.	ADP
app01-10214	138	6	karsanina	karsanina	PROPN
app01-10214	138	7	,	,	PUNCT
app01-10214	138	8	k.	k.	PROPN
app01-10214	138	9	m.	m.	PROPN
app01-10214	138	10	gerke	gerke	PROPN
app01-10214	138	11	.	.	PUNCT
app01-10214	139	1	stochastic	stochastic	NOUN
app01-10214	139	2	(	(	PUNCT
app01-10214	139	3	re)constructions	re)construction	NOUN
app01-10214	139	4	of	of	ADP
app01-10214	139	5	non	non	ADJ
app01-10214	139	6	-	-	ADJ
app01-10214	139	7	stationary	stationary	ADJ
app01-10214	139	8	material	material	NOUN
app01-10214	139	9	structures	structure	NOUN
app01-10214	139	10	:	:	PUNCT
app01-10214	139	11	using	use	VERB
app01-10214	139	12	ensemble	ensemble	ADJ
app01-10214	139	13	averaged	average	VERB
app01-10214	139	14	correlation	correlation	NOUN
app01-10214	139	15	functions	function	NOUN
app01-10214	139	16	and	and	CCONJ
app01-10214	139	17	non	non	ADJ
app01-10214	139	18	-	-	ADJ
app01-10214	139	19	uniform	uniform	ADJ
app01-10214	139	20	phase	phase	NOUN
app01-10214	139	21	distributions	distribution	NOUN
app01-10214	139	22	.	.	PUNCT
app01-10214	140	1	physica	physica	VERB
app01-10214	140	2	a	a	DET
app01-10214	140	3	:	:	PUNCT
app01-10214	140	4	statistical	statistical	ADJ
app01-10214	140	5	mechanics	mechanic	NOUN
app01-10214	140	6	and	and	CCONJ
app01-10214	140	7	its	its	PRON
app01-10214	140	8	applications	application	NOUN
app01-10214	140	9	611:128417	611:128417	NUM
app01-10214	140	10	,	,	PUNCT
app01-10214	140	11	2023	2023	NUM
app01-10214	140	12	.	.	PUNCT
app01-10214	141	1	https://doi.org/10.1016/j.physa.2022.128417	https://doi.org/10.1016/j.physa.2022.128417	PROPN
app01-10214	141	2	[	[	X
app01-10214	141	3	5	5	NUM
app01-10214	141	4	]	]	PUNCT
app01-10214	141	5	m.	m.	NOUN
app01-10214	141	6	lombardo	lombardo	PROPN
app01-10214	141	7	,	,	PUNCT
app01-10214	141	8	j.	j.	PROPN
app01-10214	141	9	zeman	zeman	PROPN
app01-10214	141	10	,	,	PUNCT
app01-10214	141	11	m.	m.	NOUN
app01-10214	141	12	sejnoha	sejnoha	PROPN
app01-10214	141	13	,	,	PUNCT
app01-10214	141	14	g.	g.	PROPN
app01-10214	141	15	falsone	falsone	PROPN
app01-10214	141	16	.	.	PUNCT
app01-10214	142	1	stochastic	stochastic	ADJ
app01-10214	142	2	modeling	modeling	NOUN
app01-10214	142	3	of	of	ADP
app01-10214	142	4	chaotic	chaotic	ADJ
app01-10214	142	5	masonry	masonry	NOUN
app01-10214	142	6	via	via	ADP
app01-10214	142	7	mesostructural	mesostructural	ADJ
app01-10214	142	8	characterization	characterization	NOUN
app01-10214	142	9	.	.	PUNCT
app01-10214	143	1	international	international	ADJ
app01-10214	143	2	journal	journal	PROPN
app01-10214	143	3	for	for	ADP
app01-10214	143	4	multiscale	multiscale	ADJ
app01-10214	143	5	computational	computational	ADJ
app01-10214	143	6	engineering	engineering	NOUN
app01-10214	143	7	7(2):171–185	7(2):171–185	NOUN
app01-10214	143	8	,	,	PUNCT
app01-10214	143	9	2009	2009	NUM
app01-10214	143	10	.	.	PUNCT
app01-10214	144	1	https	https	NOUN
app01-10214	144	2	:	:	PUNCT
app01-10214	145	1	//doi.org/10.1615	//doi.org/10.1615	ADJ
app01-10214	145	2	/	/	SYM
app01-10214	145	3	intjmultcompeng.v7.i2.70	intjmultcompeng.v7.i2.70	X
app01-10214	145	4	[	[	X
app01-10214	145	5	6	6	NUM
app01-10214	145	6	]	]	PUNCT
app01-10214	145	7	j.	j.	PROPN
app01-10214	145	8	havelka	havelka	PROPN
app01-10214	145	9	,	,	PUNCT
app01-10214	145	10	a.	a.	PROPN
app01-10214	145	11	kučerová	kučerová	PROPN
app01-10214	145	12	,	,	PUNCT
app01-10214	145	13	j.	j.	PROPN
app01-10214	145	14	sýkora	sýkora	PROPN
app01-10214	145	15	.	.	PUNCT
app01-10214	146	1	dimensionality	dimensionality	NOUN
app01-10214	146	2	reduction	reduction	NOUN
app01-10214	146	3	in	in	ADP
app01-10214	146	4	thermal	thermal	ADJ
app01-10214	146	5	tomography	tomography	NOUN
app01-10214	146	6	.	.	PUNCT
app01-10214	147	1	computers	computer	NOUN
app01-10214	147	2	&	&	CCONJ
app01-10214	147	3	mathematics	mathematics	PROPN
app01-10214	147	4	with	with	ADP
app01-10214	147	5	applications	application	NOUN
app01-10214	147	6	78(9):3077–3089	78(9):3077–3089	NUM
app01-10214	147	7	,	,	PUNCT
app01-10214	147	8	2019	2019	NUM
app01-10214	147	9	.	.	PUNCT
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app01-10214	148	9	t.	t.	PROPN
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app01-10214	148	12	w.	w.	PROPN
app01-10214	148	13	xie	xie	PROPN
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app01-10214	148	16	al	al	PROPN
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app01-10214	149	2	microstructure	microstructure	ADJ
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app01-10214	149	5	reconstruction	reconstruction	NOUN
app01-10214	149	6	via	via	ADP
app01-10214	149	7	supervised	supervised	ADJ
app01-10214	149	8	learning	learning	NOUN
app01-10214	149	9	.	.	PUNCT
app01-10214	150	1	acta	acta	PROPN
app01-10214	150	2	materialia	materialia	PROPN
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app01-10214	150	4	,	,	PUNCT
app01-10214	150	5	2016	2016	NUM
app01-10214	150	6	.	.	PUNCT
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app01-10214	151	2	[	[	X
app01-10214	151	3	8	8	NUM
app01-10214	151	4	]	]	X
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app01-10214	151	6	fu	fu	PROPN
app01-10214	151	7	,	,	PUNCT
app01-10214	151	8	s.	s.	PROPN
app01-10214	151	9	cui	cui	PROPN
app01-10214	151	10	,	,	PUNCT
app01-10214	151	11	s.	s.	PROPN
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app01-10214	151	13	,	,	PUNCT
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app01-10214	151	15	li	li	PROPN
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app01-10214	151	18	characterization	characterization	NOUN
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app01-10214	151	22	heterogeneous	heterogeneous	ADJ
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app01-10214	151	26	neural	neural	ADJ
app01-10214	151	27	network	network	NOUN
app01-10214	151	28	.	.	PUNCT
app01-10214	152	1	computer	computer	NOUN
app01-10214	152	2	methods	method	NOUN
app01-10214	152	3	in	in	ADP
app01-10214	152	4	applied	applied	ADJ
app01-10214	152	5	mechanics	mechanic	NOUN
app01-10214	152	6	and	and	CCONJ
app01-10214	152	7	engineering	engineering	NOUN
app01-10214	152	8	373:113516	373:113516	NUM
app01-10214	152	9	,	,	PUNCT
app01-10214	152	10	2021	2021	NUM
app01-10214	152	11	.	.	PUNCT
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app01-10214	154	2	9	9	X
app01-10214	154	3	]	]	PUNCT
app01-10214	154	4	k.	k.	PROPN
app01-10214	154	5	latka	latka	PROPN
app01-10214	154	6	,	,	PUNCT
app01-10214	154	7	m.	m.	PROPN
app01-10214	154	8	doškář	doškář	PROPN
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app01-10214	155	2	reconstruction	reconstruction	NOUN
app01-10214	155	3	via	via	ADP
app01-10214	155	4	artificial	artificial	ADJ
app01-10214	155	5	neural	neural	ADJ
app01-10214	155	6	networks	network	NOUN
app01-10214	155	7	:	:	PUNCT
app01-10214	155	8	a	a	DET
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app01-10214	155	11	causal	causal	ADJ
app01-10214	155	12	and	and	CCONJ
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app01-10214	155	14	-	-	ADJ
app01-10214	155	15	causal	causal	ADJ
app01-10214	155	16	approach	approach	NOUN
app01-10214	155	17	.	.	PUNCT
app01-10214	156	1	acta	acta	PROPN
app01-10214	156	2	polytechnica	polytechnica	PROPN
app01-10214	156	3	ctu	ctu	NOUN
app01-10214	156	4	proceedings	proceeding	NOUN
app01-10214	156	5	34:32–37	34:32–37	NUM
app01-10214	156	6	,	,	PUNCT
app01-10214	156	7	2022	2022	NUM
app01-10214	156	8	.	.	PUNCT
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app01-10214	158	1	[	[	X
app01-10214	158	2	10	10	NUM
app01-10214	158	3	]	]	PUNCT
app01-10214	158	4	l.-y	l.-y	NOUN
app01-10214	158	5	.	.	PUNCT
app01-10214	159	1	wei	wei	PROPN
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app01-10214	160	5	tree	tree	NOUN
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app01-10214	160	8	vector	vector	NOUN
app01-10214	160	9	quantization	quantization	NOUN
app01-10214	160	10	.	.	PUNCT
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app01-10214	161	5	27th	27th	ADJ
app01-10214	161	6	annual	annual	ADJ
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app01-10214	161	8	on	on	ADP
app01-10214	161	9	computer	computer	NOUN
app01-10214	161	10	graphics	graphic	NOUN
app01-10214	161	11	and	and	CCONJ
app01-10214	161	12	interactive	interactive	ADJ
app01-10214	161	13	techniques	technique	NOUN
app01-10214	161	14	,	,	PUNCT
app01-10214	161	15	pp	pp	ADJ
app01-10214	161	16	.	.	PUNCT
app01-10214	162	1	479–488	479–488	NUM
app01-10214	162	2	.	.	PUNCT
app01-10214	162	3	2000	2000	NUM
app01-10214	162	4	.	.	PUNCT
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app01-10214	164	1	[	[	X
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app01-10214	164	3	]	]	X
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app01-10214	164	5	sze	sze	PROPN
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app01-10214	164	7	y.-h	y.-h	PROPN
app01-10214	164	8	.	.	PUNCT
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app01-10214	165	2	,	,	PUNCT
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app01-10214	165	4	.	.	PUNCT
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app01-10214	166	3	j.	j.	PROPN
app01-10214	166	4	s.	s.	PROPN
app01-10214	166	5	emer	emer	PROPN
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app01-10214	167	2	processing	processing	NOUN
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app01-10214	167	4	deep	deep	ADJ
app01-10214	167	5	neural	neural	ADJ
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app01-10214	167	12	.	.	PUNCT
app01-10214	168	1	proceedings	proceeding	NOUN
app01-10214	168	2	of	of	ADP
app01-10214	168	3	the	the	DET
app01-10214	168	4	ieee	ieee	NOUN
app01-10214	168	5	105(12):2295–2329	105(12):2295–2329	NUM
app01-10214	168	6	,	,	PUNCT
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app01-10214	168	8	.	.	PUNCT
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app01-10214	170	2	12	12	NUM
app01-10214	170	3	]	]	PUNCT
app01-10214	170	4	k.-h	k.-h	NOUN
app01-10214	170	5	.	.	PUNCT
app01-10214	171	1	lee	lee	PROPN
app01-10214	171	2	,	,	PUNCT
app01-10214	171	3	g.	g.	PROPN
app01-10214	171	4	j.	j.	PROPN
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app01-10214	172	2	reconstruction	reconstruction	NOUN
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app01-10214	172	4	diffusion	diffusion	NOUN
app01-10214	172	5	-	-	PUNCT
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app01-10214	173	1	mechanics	mechanic	NOUN
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app01-10214	173	3	advanced	advanced	ADJ
app01-10214	173	4	materials	material	NOUN
app01-10214	173	5	and	and	CCONJ
app01-10214	173	6	structures	structure	NOUN
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app01-10214	173	8	,	,	PUNCT
app01-10214	173	9	2024	2024	NUM
app01-10214	173	10	.	.	PUNCT
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app01-10214	175	1	https://doi.org/10.1109/jproc.2017.2761740	https://doi.org/10.1109/jproc.2017.2761740	PROPN
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app01-10214	176	1	49/2024	49/2024	NUM
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app01-10214	176	4	concrete	concrete	ADJ
app01-10214	176	5	morphology	morphology	NOUN
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app01-10214	176	13	düreth	düreth	PROPN
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app01-10214	176	15	p.	p.	PROPN
app01-10214	176	16	seibert	seibert	PROPN
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app01-10214	176	20	,	,	PUNCT
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app01-10214	176	23	.	.	PUNCT
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app01-10214	177	3	-	-	PUNCT
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app01-10214	177	5	microstructure	microstructure	ADJ
app01-10214	177	6	reconstruction	reconstruction	NOUN
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app01-10214	178	2	today	today	NOUN
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app01-10214	178	5	,	,	PUNCT
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app01-10214	180	2	reconstruction	reconstruction	NOUN
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app01-10214	180	4	2d/3d	2d/3d	NUM
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app01-10214	180	6	materials	material	NOUN
app01-10214	180	7	via	via	ADP
app01-10214	180	8	diffusion	diffusion	NOUN
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app01-10214	180	14	.	.	PUNCT
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app01-10214	188	9	,	,	PUNCT
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app01-10214	189	5	networks	network	NOUN
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app01-10214	189	10	,	,	PUNCT
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app01-10214	192	4	materials	material	NOUN
app01-10214	192	5	with	with	ADP
app01-10214	192	6	random	random	ADJ
app01-10214	192	7	microstructure	microstructure	NOUN
app01-10214	192	8	.	.	PUNCT
app01-10214	193	1	ph.d	ph.d	PROPN
app01-10214	193	2	.	.	PUNCT
app01-10214	194	1	thesis	thesis	NOUN
app01-10214	194	2	,	,	PUNCT
app01-10214	194	3	czech	czech	PROPN
app01-10214	194	4	technical	technical	PROPN
app01-10214	194	5	university	university	PROPN
app01-10214	194	6	,	,	PUNCT
app01-10214	194	7	2003	2003	NUM
app01-10214	194	8	.	.	PUNCT
app01-10214	195	1	https://doi.org/10.13140/rg.2.1.2399.0004	https://doi.org/10.13140/rg.2.1.2399.0004	VERB
app01-10214	195	2	91	91	NUM
app01-10214	195	3	https://doi.org/10.1016/j.mtcomm.2023.105608	https://doi.org/10.1016/j.mtcomm.2023.105608	NOUN
app01-10214	195	4	https://doi.org/10.1038/s41598-024-54861-9	https://doi.org/10.1038/s41598-024-54861-9	PROPN
app01-10214	195	5	https://doi.org/10.1109/tnnls.2021.3084827	https://doi.org/10.1109/tnnls.2021.3084827	PROPN
app01-10214	195	6	https://doi.org/10.13140/rg.2.1.2399.0004	https://doi.org/10.13140/rg.2.1.2399.0004	NOUN
app01-10214	195	7	acta	acta	PROPN
app01-10214	195	8	polytechnica	polytechnica	PROPN
app01-10214	195	9	ctu	ctu	NOUN
app01-10214	195	10	proceedings	proceeding	NOUN
app01-10214	195	11	49:85–91	49:85–91	NUM
app01-10214	195	12	,	,	PUNCT
app01-10214	195	13	2024	2024	NUM
app01-10214	195	14	1	1	NUM
app01-10214	195	15	introduction	introduction	NOUN
app01-10214	195	16	2	2	NUM
app01-10214	195	17	methodology	methodology	NOUN
app01-10214	195	18	2.1	2.1	NUM
app01-10214	195	19	architecture	architecture	NOUN
app01-10214	195	20	of	of	ADP
app01-10214	195	21	dnn	dnn	PROPN
app01-10214	195	22	3	3	NUM
app01-10214	195	23	example	example	NOUN
app01-10214	195	24	3.1	3.1	NUM
app01-10214	195	25	large	large	ADJ
app01-10214	195	26	image	image	NOUN
app01-10214	195	27	evaluation	evaluation	NOUN
app01-10214	195	28	4	4	NUM
app01-10214	195	29	conclusion	conclusion	NOUN
app01-10214	195	30	acknowledgements	acknowledgement	NOUN
app01-10214	195	31	references	reference	NOUN