id	sid	tid	token	lemma	pos
fcis-26112	1	1	frontiers	frontier	NOUN
fcis-26112	1	2	in	in	ADP
fcis-26112	1	3	computing	computing	NOUN
fcis-26112	1	4	and	and	CCONJ
fcis-26112	1	5	intelligent	intelligent	ADJ
fcis-26112	1	6	systems	system	NOUN
fcis-26112	1	7	issn	issn	VERB
fcis-26112	1	8	:	:	PUNCT
fcis-26112	1	9	2832	2832	NUM
fcis-26112	1	10	-	-	SYM
fcis-26112	1	11	6024	6024	NUM
fcis-26112	1	12	|	|	NOUN
fcis-26112	1	13	vol	vol	NOUN
fcis-26112	1	14	.	.	PROPN
fcis-26112	2	1	10	10	NUM
fcis-26112	2	2	,	,	PUNCT
fcis-26112	2	3	no	no	INTJ
fcis-26112	2	4	.	.	NOUN
fcis-26112	2	5	1	1	NUM
fcis-26112	2	6	,	,	PUNCT
fcis-26112	2	7	2024	2024	NUM
fcis-26112	2	8	9	9	NUM
fcis-26112	2	9	transfer	transfer	NOUN
fcis-26112	2	10	learning	learning	NOUN
fcis-26112	2	11	with	with	ADP
fcis-26112	2	12	pre‐trained	pre‐traine	VERB
fcis-26112	2	13	resnet‐50	resnet‐50	NOUN
fcis-26112	2	14	:	:	PUNCT
fcis-26112	2	15	predicting	predict	VERB
fcis-26112	2	16	spx	spx	PROPN
fcis-26112	2	17	option	option	NOUN
fcis-26112	2	18	prices	price	NOUN
fcis-26112	2	19	zihao	zihao	PROPN
fcis-26112	2	20	lin	lin	PROPN
fcis-26112	2	21	school	school	PROPN
fcis-26112	2	22	of	of	ADP
fcis-26112	2	23	computer	computer	NOUN
fcis-26112	2	24	science	science	NOUN
fcis-26112	2	25	and	and	CCONJ
fcis-26112	2	26	engineering	engineering	NOUN
fcis-26112	2	27	,	,	PUNCT
fcis-26112	2	28	south	south	PROPN
fcis-26112	2	29	china	china	PROPN
fcis-26112	2	30	university	university	PROPN
fcis-26112	2	31	of	of	ADP
fcis-26112	2	32	technology	technology	PROPN
fcis-26112	2	33	,	,	PUNCT
fcis-26112	2	34	guangzhou	guangzhou	PROPN
fcis-26112	2	35	,	,	PUNCT
fcis-26112	2	36	guangdong	guangdong	PROPN
fcis-26112	2	37	510006	510006	NUM
fcis-26112	2	38	,	,	PUNCT
fcis-26112	2	39	china	china	PROPN
fcis-26112	2	40	abstract	abstract	NOUN
fcis-26112	2	41	:	:	PUNCT
fcis-26112	2	42	due	due	ADP
fcis-26112	2	43	to	to	ADP
fcis-26112	2	44	the	the	DET
fcis-26112	2	45	volatility	volatility	NOUN
fcis-26112	2	46	and	and	CCONJ
fcis-26112	2	47	complexity	complexity	NOUN
fcis-26112	2	48	of	of	ADP
fcis-26112	2	49	the	the	DET
fcis-26112	2	50	options	option	NOUN
fcis-26112	2	51	market	market	NOUN
fcis-26112	2	52	,	,	PUNCT
fcis-26112	2	53	it	it	PRON
fcis-26112	2	54	has	have	AUX
fcis-26112	2	55	exacerbated	exacerbate	VERB
fcis-26112	2	56	the	the	DET
fcis-26112	2	57	difficulty	difficulty	NOUN
fcis-26112	2	58	of	of	ADP
fcis-26112	2	59	predicting	predict	VERB
fcis-26112	2	60	option	option	NOUN
fcis-26112	2	61	prices	price	NOUN
fcis-26112	2	62	and	and	CCONJ
fcis-26112	2	63	attracted	attract	VERB
fcis-26112	2	64	widespread	widespread	ADJ
fcis-26112	2	65	attention	attention	NOUN
fcis-26112	2	66	.	.	PUNCT
fcis-26112	3	1	in	in	ADP
fcis-26112	3	2	recent	recent	ADJ
fcis-26112	3	3	years	year	NOUN
fcis-26112	3	4	,	,	PUNCT
fcis-26112	3	5	many	many	ADJ
fcis-26112	3	6	machine	machine	NOUN
fcis-26112	3	7	learning	learning	NOUN
fcis-26112	3	8	(	(	PUNCT
fcis-26112	3	9	ml	ml	NOUN
fcis-26112	3	10	)	)	PUNCT
fcis-26112	3	11	techniques	technique	NOUN
fcis-26112	3	12	have	have	AUX
fcis-26112	3	13	been	be	AUX
fcis-26112	3	14	explored	explore	VERB
fcis-26112	3	15	for	for	ADP
fcis-26112	3	16	this	this	DET
fcis-26112	3	17	purpose	purpose	NOUN
fcis-26112	3	18	.	.	PUNCT
fcis-26112	4	1	this	this	DET
fcis-26112	4	2	paper	paper	NOUN
fcis-26112	4	3	implements	implement	VERB
fcis-26112	4	4	the	the	DET
fcis-26112	4	5	advanced	advanced	ADJ
fcis-26112	4	6	ml	ml	NOUN
fcis-26112	4	7	models	model	NOUN
fcis-26112	4	8	to	to	PART
fcis-26112	4	9	boost	boost	VERB
fcis-26112	4	10	the	the	DET
fcis-26112	4	11	accurate	accurate	ADJ
fcis-26112	4	12	prediction	prediction	NOUN
fcis-26112	4	13	of	of	ADP
fcis-26112	4	14	the	the	DET
fcis-26112	4	15	option	option	NOUN
fcis-26112	4	16	price	price	NOUN
fcis-26112	4	17	,	,	PUNCT
fcis-26112	4	18	which	which	PRON
fcis-26112	4	19	includes	include	VERB
fcis-26112	4	20	the	the	DET
fcis-26112	4	21	comparison	comparison	NOUN
fcis-26112	4	22	between	between	ADP
fcis-26112	4	23	traditional	traditional	ADJ
fcis-26112	4	24	ml	ml	NOUN
fcis-26112	4	25	techniques	technique	NOUN
fcis-26112	4	26	random	random	ADJ
fcis-26112	4	27	forest	forest	NOUN
fcis-26112	4	28	and	and	CCONJ
fcis-26112	4	29	support	support	VERB
fcis-26112	4	30	vector	vector	NOUN
fcis-26112	4	31	regression	regression	NOUN
fcis-26112	4	32	(	(	PUNCT
fcis-26112	4	33	svr	svr	PROPN
fcis-26112	4	34	)	)	PUNCT
fcis-26112	4	35	,	,	PUNCT
fcis-26112	4	36	as	as	ADV
fcis-26112	4	37	well	well	ADV
fcis-26112	4	38	as	as	ADP
fcis-26112	4	39	the	the	DET
fcis-26112	4	40	convolutional	convolutional	ADJ
fcis-26112	4	41	neural	neural	ADJ
fcis-26112	4	42	network	network	NOUN
fcis-26112	4	43	(	(	PUNCT
fcis-26112	4	44	cnn	cnn	PROPN
fcis-26112	4	45	)	)	PUNCT
fcis-26112	4	46	resnet-50	resnet-50	PROPN
fcis-26112	4	47	.	.	PROPN
fcis-26112	5	1	additionally	additionally	ADV
fcis-26112	5	2	,	,	PUNCT
fcis-26112	5	3	we	we	PRON
fcis-26112	5	4	further	far	ADV
fcis-26112	5	5	compare	compare	VERB
fcis-26112	5	6	the	the	DET
fcis-26112	5	7	performance	performance	NOUN
fcis-26112	5	8	of	of	ADP
fcis-26112	5	9	resnet-50	resnet-50	PROPN
fcis-26112	5	10	pre	pre	ADJ
fcis-26112	5	11	-	-	VERB
fcis-26112	5	12	trained	train	VERB
fcis-26112	5	13	on	on	ADP
fcis-26112	5	14	imagenet	imagenet	NOUN
fcis-26112	5	15	through	through	ADP
fcis-26112	5	16	transfer	transfer	NOUN
fcis-26112	5	17	learning	learning	NOUN
fcis-26112	5	18	.	.	PUNCT
fcis-26112	6	1	these	these	DET
fcis-26112	6	2	methods	method	NOUN
fcis-26112	6	3	are	be	AUX
fcis-26112	6	4	used	use	VERB
fcis-26112	6	5	to	to	PART
fcis-26112	6	6	predict	predict	VERB
fcis-26112	6	7	the	the	DET
fcis-26112	6	8	implied	imply	VERB
fcis-26112	6	9	volatility	volatility	NOUN
fcis-26112	6	10	,	,	PUNCT
fcis-26112	6	11	which	which	PRON
fcis-26112	6	12	is	be	AUX
fcis-26112	6	13	then	then	ADV
fcis-26112	6	14	transformed	transform	VERB
fcis-26112	6	15	into	into	ADP
fcis-26112	6	16	option	option	NOUN
fcis-26112	6	17	pricing	pricing	NOUN
fcis-26112	6	18	using	use	VERB
fcis-26112	6	19	the	the	DET
fcis-26112	6	20	black	black	ADJ
fcis-26112	6	21	–	–	PUNCT
fcis-26112	6	22	scholes	schole	NOUN
fcis-26112	6	23	option	option	NOUN
fcis-26112	6	24	pricing	pricing	NOUN
fcis-26112	6	25	model	model	NOUN
fcis-26112	6	26	(	(	PUNCT
fcis-26112	6	27	bsopm	bsopm	NOUN
fcis-26112	6	28	)	)	PUNCT
fcis-26112	6	29	.	.	PUNCT
fcis-26112	7	1	finally	finally	ADV
fcis-26112	7	2	,	,	PUNCT
fcis-26112	7	3	we	we	PRON
fcis-26112	7	4	compare	compare	VERB
fcis-26112	7	5	the	the	DET
fcis-26112	7	6	performance	performance	NOUN
fcis-26112	7	7	of	of	ADP
fcis-26112	7	8	these	these	DET
fcis-26112	7	9	models	model	NOUN
fcis-26112	7	10	based	base	VERB
fcis-26112	7	11	on	on	ADP
fcis-26112	7	12	error	error	NOUN
fcis-26112	7	13	analysis	analysis	NOUN
fcis-26112	7	14	using	use	VERB
fcis-26112	7	15	rmse	rmse	NOUN
fcis-26112	7	16	and	and	CCONJ
fcis-26112	7	17	r²	r²	NOUN
fcis-26112	7	18	.	.	PUNCT
fcis-26112	8	1	the	the	DET
fcis-26112	8	2	experimental	experimental	ADJ
fcis-26112	8	3	results	result	NOUN
fcis-26112	8	4	show	show	VERB
fcis-26112	8	5	that	that	SCONJ
fcis-26112	8	6	the	the	DET
fcis-26112	8	7	pre	pre	ADJ
fcis-26112	8	8	-	-	ADJ
fcis-26112	8	9	trained	train	VERB
fcis-26112	8	10	resnet-50	resnet-50	PROPN
fcis-26112	8	11	reduces	reduce	VERB
fcis-26112	8	12	the	the	DET
fcis-26112	8	13	error	error	NOUN
fcis-26112	8	14	by	by	ADP
fcis-26112	8	15	6	6	NUM
fcis-26112	8	16	%	%	NOUN
fcis-26112	8	17	compared	compare	VERB
fcis-26112	8	18	to	to	ADP
fcis-26112	8	19	the	the	DET
fcis-26112	8	20	un	un	PROPN
fcis-26112	8	21	-	-	ADJ
fcis-26112	8	22	pretrained	pretrained	ADJ
fcis-26112	8	23	resnet-50	resnet-50	PROPN
fcis-26112	8	24	,	,	PUNCT
fcis-26112	8	25	by	by	ADP
fcis-26112	8	26	51.2	51.2	NUM
fcis-26112	8	27	%	%	NOUN
fcis-26112	8	28	compared	compare	VERB
fcis-26112	8	29	to	to	ADP
fcis-26112	8	30	decision	decision	NOUN
fcis-26112	8	31	trees	tree	NOUN
fcis-26112	8	32	,	,	PUNCT
fcis-26112	8	33	and	and	CCONJ
fcis-26112	8	34	by	by	ADP
fcis-26112	8	35	51.1	51.1	NUM
fcis-26112	8	36	%	%	NOUN
fcis-26112	8	37	compared	compare	VERB
fcis-26112	8	38	to	to	AUX
fcis-26112	8	39	svr	svr	PROPN
fcis-26112	8	40	.	.	PUNCT
fcis-26112	9	1	the	the	DET
fcis-26112	9	2	predicted	predict	VERB
fcis-26112	9	3	option	option	NOUN
fcis-26112	9	4	prices	price	NOUN
fcis-26112	9	5	align	align	VERB
fcis-26112	9	6	well	well	ADV
fcis-26112	9	7	with	with	ADP
fcis-26112	9	8	the	the	DET
fcis-26112	9	9	actual	actual	ADJ
fcis-26112	9	10	values	value	NOUN
fcis-26112	9	11	,	,	PUNCT
fcis-26112	9	12	demonstrating	demonstrate	VERB
fcis-26112	9	13	the	the	DET
fcis-26112	9	14	feasibility	feasibility	NOUN
fcis-26112	9	15	of	of	ADP
fcis-26112	9	16	applying	apply	VERB
fcis-26112	9	17	pre	pre	ADJ
fcis-26112	9	18	-	-	ADJ
fcis-26112	9	19	trained	train	VERB
fcis-26112	9	20	resnet-50	resnet-50	PROPN
fcis-26112	9	21	on	on	ADP
fcis-26112	9	22	option	option	NOUN
fcis-26112	9	23	price	price	NOUN
fcis-26112	9	24	prediction	prediction	NOUN
fcis-26112	9	25	.	.	PUNCT
fcis-26112	10	1	keywords	keyword	NOUN
fcis-26112	10	2	:	:	PUNCT
fcis-26112	10	3	resnet-50	resnet-50	NUM
fcis-26112	10	4	;	;	PUNCT
fcis-26112	10	5	cnn	cnn	PROPN
fcis-26112	10	6	;	;	PUNCT
fcis-26112	10	7	option	option	NOUN
fcis-26112	10	8	price	price	NOUN
fcis-26112	10	9	;	;	PUNCT
fcis-26112	10	10	transfer	transfer	NOUN
fcis-26112	10	11	learning	learning	NOUN
fcis-26112	10	12	.	.	PUNCT
fcis-26112	11	1	1	1	X
fcis-26112	11	2	.	.	X
fcis-26112	11	3	introduction	introduction	NOUN
fcis-26112	11	4	options	option	NOUN
fcis-26112	11	5	are	be	AUX
fcis-26112	11	6	derivatives	derivative	NOUN
fcis-26112	11	7	of	of	ADP
fcis-26112	11	8	underlying	underlie	VERB
fcis-26112	11	9	assets	asset	NOUN
fcis-26112	11	10	and	and	CCONJ
fcis-26112	11	11	are	be	AUX
fcis-26112	11	12	financial	financial	ADJ
fcis-26112	11	13	products	product	NOUN
fcis-26112	11	14	that	that	PRON
fcis-26112	11	15	allow	allow	VERB
fcis-26112	11	16	trading	trading	NOUN
fcis-26112	11	17	on	on	ADP
fcis-26112	11	18	future	future	ADJ
fcis-26112	11	19	market	market	NOUN
fcis-26112	11	20	prices	price	NOUN
fcis-26112	11	21	.	.	PUNCT
fcis-26112	12	1	there	there	PRON
fcis-26112	12	2	are	be	VERB
fcis-26112	12	3	two	two	NUM
fcis-26112	12	4	types	type	NOUN
fcis-26112	12	5	of	of	ADP
fcis-26112	12	6	options	option	NOUN
fcis-26112	12	7	:	:	PUNCT
fcis-26112	12	8	call	call	VERB
fcis-26112	12	9	options	option	NOUN
fcis-26112	12	10	and	and	CCONJ
fcis-26112	12	11	put	put	VERB
fcis-26112	12	12	options	option	NOUN
fcis-26112	12	13	.	.	PUNCT
fcis-26112	13	1	a	a	DET
fcis-26112	13	2	call	call	NOUN
fcis-26112	13	3	option	option	NOUN
fcis-26112	13	4	is	be	AUX
fcis-26112	13	5	a	a	DET
fcis-26112	13	6	financial	financial	ADJ
fcis-26112	13	7	contract	contract	NOUN
fcis-26112	13	8	that	that	PRON
fcis-26112	13	9	allows	allow	VERB
fcis-26112	13	10	the	the	DET
fcis-26112	13	11	buyer	buyer	NOUN
fcis-26112	13	12	to	to	PART
fcis-26112	13	13	purchase	purchase	VERB
fcis-26112	13	14	the	the	DET
fcis-26112	13	15	underlying	underlie	VERB
fcis-26112	13	16	asset	asset	NOUN
fcis-26112	13	17	from	from	ADP
fcis-26112	13	18	the	the	DET
fcis-26112	13	19	issuer	issuer	NOUN
fcis-26112	13	20	at	at	ADP
fcis-26112	13	21	a	a	DET
fcis-26112	13	22	specified	specified	ADJ
fcis-26112	13	23	price	price	NOUN
fcis-26112	13	24	in	in	ADP
fcis-26112	13	25	the	the	DET
fcis-26112	13	26	future	future	NOUN
fcis-26112	13	27	,	,	PUNCT
fcis-26112	13	28	while	while	SCONJ
fcis-26112	13	29	a	a	DET
fcis-26112	13	30	put	put	NOUN
fcis-26112	13	31	option	option	NOUN
fcis-26112	13	32	allows	allow	VERB
fcis-26112	13	33	the	the	DET
fcis-26112	13	34	buyer	buyer	NOUN
fcis-26112	13	35	to	to	PART
fcis-26112	13	36	sell	sell	VERB
fcis-26112	13	37	the	the	DET
fcis-26112	13	38	underlying	underlie	VERB
fcis-26112	13	39	asset	asset	NOUN
fcis-26112	13	40	to	to	ADP
fcis-26112	13	41	the	the	DET
fcis-26112	13	42	issuer	issuer	NOUN
fcis-26112	13	43	at	at	ADP
fcis-26112	13	44	a	a	DET
fcis-26112	13	45	specified	specified	ADJ
fcis-26112	13	46	price	price	NOUN
fcis-26112	13	47	in	in	ADP
fcis-26112	13	48	the	the	DET
fcis-26112	13	49	future	future	NOUN
fcis-26112	13	50	.	.	PUNCT
fcis-26112	14	1	options	option	NOUN
fcis-26112	14	2	play	play	VERB
fcis-26112	14	3	a	a	DET
fcis-26112	14	4	crucial	crucial	ADJ
fcis-26112	14	5	role	role	NOUN
fcis-26112	14	6	in	in	ADP
fcis-26112	14	7	both	both	CCONJ
fcis-26112	14	8	the	the	DET
fcis-26112	14	9	financial	financial	ADJ
fcis-26112	14	10	sector	sector	NOUN
fcis-26112	14	11	and	and	CCONJ
fcis-26112	14	12	everyday	everyday	ADJ
fcis-26112	14	13	life	life	NOUN
fcis-26112	14	14	.	.	PUNCT
fcis-26112	15	1	companies	company	NOUN
fcis-26112	15	2	may	may	AUX
fcis-26112	15	3	issue	issue	VERB
fcis-26112	15	4	stock	stock	NOUN
fcis-26112	15	5	options	option	NOUN
fcis-26112	15	6	to	to	ADP
fcis-26112	15	7	employees	employee	NOUN
fcis-26112	15	8	as	as	ADP
fcis-26112	15	9	part	part	NOUN
fcis-26112	15	10	of	of	ADP
fcis-26112	15	11	incentive	incentive	NOUN
fcis-26112	15	12	plans	plan	NOUN
fcis-26112	15	13	,	,	PUNCT
fcis-26112	15	14	enabling	enable	VERB
fcis-26112	15	15	employees	employee	NOUN
fcis-26112	15	16	to	to	PART
fcis-26112	15	17	buy	buy	VERB
fcis-26112	15	18	company	company	NOUN
fcis-26112	15	19	stock	stock	NOUN
fcis-26112	15	20	at	at	ADP
fcis-26112	15	21	a	a	DET
fcis-26112	15	22	predetermined	predetermine	VERB
fcis-26112	15	23	price	price	NOUN
fcis-26112	15	24	in	in	ADP
fcis-26112	15	25	the	the	DET
fcis-26112	15	26	future	future	NOUN
fcis-26112	15	27	and	and	CCONJ
fcis-26112	15	28	thus	thus	ADV
fcis-26112	15	29	share	share	VERB
fcis-26112	15	30	in	in	ADP
fcis-26112	15	31	the	the	DET
fcis-26112	15	32	company	company	NOUN
fcis-26112	15	33	's	's	PART
fcis-26112	15	34	future	future	ADJ
fcis-26112	15	35	growth	growth	NOUN
fcis-26112	15	36	[	[	X
fcis-26112	15	37	1	1	NUM
fcis-26112	15	38	]	]	PUNCT
fcis-26112	15	39	.	.	PUNCT
fcis-26112	16	1	exchanges	exchange	NOUN
fcis-26112	16	2	also	also	ADV
fcis-26112	16	3	issue	issue	VERB
fcis-26112	16	4	options	option	NOUN
fcis-26112	16	5	,	,	PUNCT
fcis-26112	16	6	providing	provide	VERB
fcis-26112	16	7	standardized	standardized	ADJ
fcis-26112	16	8	option	option	NOUN
fcis-26112	16	9	contracts	contract	NOUN
fcis-26112	16	10	that	that	PRON
fcis-26112	16	11	allow	allow	VERB
fcis-26112	16	12	investors	investor	NOUN
fcis-26112	16	13	to	to	PART
fcis-26112	16	14	buy	buy	VERB
fcis-26112	16	15	and	and	CCONJ
fcis-26112	16	16	sell	sell	VERB
fcis-26112	16	17	in	in	ADP
fcis-26112	16	18	the	the	DET
fcis-26112	16	19	secondary	secondary	ADJ
fcis-26112	16	20	market	market	NOUN
fcis-26112	16	21	.	.	PUNCT
fcis-26112	17	1	these	these	DET
fcis-26112	17	2	option	option	NOUN
fcis-26112	17	3	contracts	contract	NOUN
fcis-26112	17	4	typically	typically	ADV
fcis-26112	17	5	have	have	VERB
fcis-26112	17	6	stocks	stock	NOUN
fcis-26112	17	7	as	as	ADP
fcis-26112	17	8	the	the	DET
fcis-26112	17	9	underlying	underlie	VERB
fcis-26112	17	10	assets	asset	NOUN
fcis-26112	17	11	and	and	CCONJ
fcis-26112	17	12	come	come	VERB
fcis-26112	17	13	with	with	ADP
fcis-26112	17	14	preset	preset	ADJ
fcis-26112	17	15	prices	price	NOUN
fcis-26112	17	16	and	and	CCONJ
fcis-26112	17	17	expiration	expiration	NOUN
fcis-26112	17	18	dates	date	NOUN
fcis-26112	17	19	.	.	PUNCT
fcis-26112	18	1	through	through	ADP
fcis-26112	18	2	this	this	DET
fcis-26112	18	3	mechanism	mechanism	NOUN
fcis-26112	18	4	,	,	PUNCT
fcis-26112	18	5	investors	investor	NOUN
fcis-26112	18	6	can	can	AUX
fcis-26112	18	7	purchase	purchase	VERB
fcis-26112	18	8	option	option	NOUN
fcis-26112	18	9	contracts	contract	NOUN
fcis-26112	18	10	,	,	PUNCT
fcis-26112	18	11	aiming	aim	VERB
fcis-26112	18	12	to	to	PART
fcis-26112	18	13	profit	profit	VERB
fcis-26112	18	14	from	from	ADP
fcis-26112	18	15	future	future	ADJ
fcis-26112	18	16	fluctuations	fluctuation	NOUN
fcis-26112	18	17	in	in	ADP
fcis-26112	18	18	stock	stock	NOUN
fcis-26112	18	19	prices	price	NOUN
fcis-26112	18	20	[	[	X
fcis-26112	18	21	2	2	NUM
fcis-26112	18	22	]	]	PUNCT
fcis-26112	18	23	.	.	PUNCT
fcis-26112	19	1	the	the	DET
fcis-26112	19	2	trading	trading	NOUN
fcis-26112	19	3	volume	volume	NOUN
fcis-26112	19	4	in	in	ADP
fcis-26112	19	5	the	the	DET
fcis-26112	19	6	options	option	NOUN
fcis-26112	19	7	market	market	NOUN
fcis-26112	19	8	increased	increase	VERB
fcis-26112	19	9	from	from	ADP
fcis-26112	19	10	9.42	9.42	NUM
fcis-26112	19	11	billion	billion	NUM
fcis-26112	19	12	contracts	contract	NOUN
fcis-26112	19	13	in	in	ADP
fcis-26112	19	14	2013	2013	NUM
fcis-26112	19	15	to	to	ADP
fcis-26112	19	16	54.53	54.53	NUM
fcis-26112	19	17	billion	billion	NUM
fcis-26112	19	18	contracts	contract	NOUN
fcis-26112	19	19	in	in	ADP
fcis-26112	19	20	2022	2022	NUM
fcis-26112	19	21	,	,	PUNCT
fcis-26112	19	22	far	far	ADV
fcis-26112	19	23	surpassing	surpass	VERB
fcis-26112	19	24	the	the	DET
fcis-26112	19	25	growth	growth	NOUN
fcis-26112	19	26	of	of	ADP
fcis-26112	19	27	the	the	DET
fcis-26112	19	28	futures	future	NOUN
fcis-26112	19	29	market	market	NOUN
fcis-26112	19	30	during	during	ADP
fcis-26112	19	31	the	the	DET
fcis-26112	19	32	same	same	ADJ
fcis-26112	19	33	period	period	NOUN
fcis-26112	19	34	.	.	PUNCT
fcis-26112	20	1	this	this	PRON
fcis-26112	20	2	demonstrates	demonstrate	VERB
fcis-26112	20	3	that	that	SCONJ
fcis-26112	20	4	options	option	NOUN
fcis-26112	20	5	have	have	AUX
fcis-26112	20	6	become	become	VERB
fcis-26112	20	7	a	a	DET
fcis-26112	20	8	highly	highly	ADV
fcis-26112	20	9	liquid	liquid	ADJ
fcis-26112	20	10	financial	financial	ADJ
fcis-26112	20	11	product	product	NOUN
fcis-26112	20	12	with	with	ADP
fcis-26112	20	13	significant	significant	ADJ
fcis-26112	20	14	investment	investment	NOUN
fcis-26112	20	15	opportunities	opportunity	NOUN
fcis-26112	20	16	.	.	PUNCT
fcis-26112	21	1	however	however	ADV
fcis-26112	21	2	,	,	PUNCT
fcis-26112	21	3	the	the	DET
fcis-26112	21	4	vast	vast	ADJ
fcis-26112	21	5	majority	majority	NOUN
fcis-26112	21	6	of	of	ADP
fcis-26112	21	7	options	option	NOUN
fcis-26112	21	8	traders	trader	NOUN
fcis-26112	21	9	incur	incur	VERB
fcis-26112	21	10	losses	loss	NOUN
fcis-26112	21	11	due	due	ADP
fcis-26112	21	12	to	to	ADP
fcis-26112	21	13	their	their	PRON
fcis-26112	21	14	lack	lack	NOUN
fcis-26112	21	15	of	of	ADP
fcis-26112	21	16	sufficient	sufficient	ADJ
fcis-26112	21	17	knowledge	knowledge	NOUN
fcis-26112	21	18	and	and	CCONJ
fcis-26112	21	19	tools	tool	NOUN
fcis-26112	21	20	.	.	PUNCT
fcis-26112	22	1	therefore	therefore	ADV
fcis-26112	22	2	,	,	PUNCT
fcis-26112	22	3	an	an	DET
fcis-26112	22	4	accurate	accurate	ADJ
fcis-26112	22	5	prediction	prediction	NOUN
fcis-26112	22	6	model	model	NOUN
fcis-26112	22	7	is	be	AUX
fcis-26112	22	8	crucial	crucial	ADJ
fcis-26112	22	9	as	as	SCONJ
fcis-26112	22	10	it	it	PRON
fcis-26112	22	11	can	can	AUX
fcis-26112	22	12	significantly	significantly	ADV
fcis-26112	22	13	enhance	enhance	VERB
fcis-26112	22	14	investors	investor	NOUN
fcis-26112	22	15	'	'	PART
fcis-26112	22	16	success	success	NOUN
fcis-26112	22	17	rates	rate	NOUN
fcis-26112	22	18	in	in	ADP
fcis-26112	22	19	various	various	ADJ
fcis-26112	22	20	aspects	aspect	NOUN
fcis-26112	22	21	.	.	PUNCT
fcis-26112	23	1	our	our	PRON
fcis-26112	23	2	research	research	NOUN
fcis-26112	23	3	focuses	focus	VERB
fcis-26112	23	4	on	on	ADP
fcis-26112	23	5	options	option	NOUN
fcis-26112	23	6	prediction	prediction	NOUN
fcis-26112	23	7	and	and	CCONJ
fcis-26112	23	8	aims	aim	VERB
fcis-26112	23	9	to	to	PART
fcis-26112	23	10	evaluate	evaluate	VERB
fcis-26112	23	11	the	the	DET
fcis-26112	23	12	performance	performance	NOUN
fcis-26112	23	13	of	of	ADP
fcis-26112	23	14	different	different	ADJ
fcis-26112	23	15	machine	machine	NOUN
fcis-26112	23	16	learning	learning	NOUN
fcis-26112	23	17	models	model	NOUN
fcis-26112	23	18	in	in	ADP
fcis-26112	23	19	addressing	address	VERB
fcis-26112	23	20	this	this	DET
fcis-26112	23	21	issue	issue	NOUN
fcis-26112	23	22	.	.	PUNCT
fcis-26112	24	1	currently	currently	ADV
fcis-26112	24	2	,	,	PUNCT
fcis-26112	24	3	many	many	ADJ
fcis-26112	24	4	researchers	researcher	NOUN
fcis-26112	24	5	have	have	AUX
fcis-26112	24	6	made	make	VERB
fcis-26112	24	7	progress	progress	NOUN
fcis-26112	24	8	using	use	VERB
fcis-26112	24	9	pretrained	pretraine	VERB
fcis-26112	24	10	cnn	cnn	PROPN
fcis-26112	24	11	networks	network	NOUN
fcis-26112	24	12	for	for	ADP
fcis-26112	24	13	transfer	transfer	NOUN
fcis-26112	24	14	learning	learning	NOUN
fcis-26112	24	15	in	in	ADP
fcis-26112	24	16	various	various	ADJ
fcis-26112	24	17	fields	field	NOUN
fcis-26112	24	18	.	.	PUNCT
fcis-26112	25	1	hoo	hoo	PROPN
fcis-26112	25	2	-	-	PUNCT
fcis-26112	25	3	chang	chang	PROPN
fcis-26112	25	4	shin	shin	PROPN
fcis-26112	25	5	et	et	PROPN
fcis-26112	25	6	al	al	PROPN
fcis-26112	25	7	.	.	PUNCT
fcis-26112	26	1	[	[	X
fcis-26112	26	2	3	3	NUM
fcis-26112	26	3	]	]	X
fcis-26112	26	4	utilized	utilize	VERB
fcis-26112	26	5	a	a	DET
fcis-26112	26	6	cnn	cnn	PROPN
fcis-26112	26	7	model	model	NOUN
fcis-26112	26	8	pre	pre	VERB
fcis-26112	26	9	-	-	VERB
fcis-26112	26	10	trained	train	VERB
fcis-26112	26	11	on	on	ADP
fcis-26112	26	12	imagenet	imagenet	NOUN
fcis-26112	26	13	for	for	ADP
fcis-26112	26	14	transfer	transfer	NOUN
fcis-26112	26	15	learning	learning	NOUN
fcis-26112	26	16	,	,	PUNCT
fcis-26112	26	17	applying	apply	VERB
fcis-26112	26	18	it	it	PRON
fcis-26112	26	19	to	to	ADP
fcis-26112	26	20	computeraided	computeraide	VERB
fcis-26112	26	21	detection	detection	NOUN
fcis-26112	26	22	problems	problem	NOUN
fcis-26112	26	23	with	with	ADP
fcis-26112	26	24	good	good	ADJ
fcis-26112	26	25	results	result	NOUN
fcis-26112	26	26	,	,	PUNCT
fcis-26112	26	27	which	which	PRON
fcis-26112	26	28	outperforms	outperform	VERB
fcis-26112	26	29	other	other	ADJ
fcis-26112	26	30	machine	machine	NOUN
fcis-26112	26	31	learning	learning	NOUN
fcis-26112	26	32	models	model	NOUN
fcis-26112	26	33	.	.	PUNCT
fcis-26112	27	1	ali	ali	PROPN
fcis-26112	27	2	et	et	PROPN
fcis-26112	27	3	al	al	PROPN
fcis-26112	27	4	.	.	PUNCT
fcis-26112	28	1	[	[	X
fcis-26112	28	2	4	4	X
fcis-26112	28	3	]	]	PUNCT
fcis-26112	28	4	studied	study	VERB
fcis-26112	28	5	the	the	DET
fcis-26112	28	6	performance	performance	NOUN
fcis-26112	28	7	of	of	ADP
fcis-26112	28	8	pre	pre	ADJ
fcis-26112	28	9	-	-	ADJ
fcis-26112	28	10	trained	train	VERB
fcis-26112	28	11	cnn	cnn	PROPN
fcis-26112	28	12	models	model	NOUN
fcis-26112	28	13	on	on	ADP
fcis-26112	28	14	tasks	task	NOUN
fcis-26112	28	15	far	far	ADV
fcis-26112	28	16	removed	remove	VERB
fcis-26112	28	17	from	from	ADP
fcis-26112	28	18	the	the	DET
fcis-26112	28	19	original	original	ADJ
fcis-26112	28	20	training	training	NOUN
fcis-26112	28	21	set	set	NOUN
fcis-26112	28	22	,	,	PUNCT
fcis-26112	28	23	reporting	report	VERB
fcis-26112	28	24	consistently	consistently	ADV
fcis-26112	28	25	superior	superior	ADJ
fcis-26112	28	26	results	result	NOUN
fcis-26112	28	27	,	,	PUNCT
fcis-26112	28	28	and	and	CCONJ
fcis-26112	28	29	highlighting	highlight	VERB
fcis-26112	28	30	the	the	DET
fcis-26112	28	31	universality	universality	NOUN
fcis-26112	28	32	of	of	ADP
fcis-26112	28	33	learned	learn	VERB
fcis-26112	28	34	representations	representation	NOUN
fcis-26112	28	35	.	.	PUNCT
fcis-26112	29	1	minyoung	minyoung	VERB
fcis-26112	29	2	et	et	PROPN
fcis-26112	29	3	al	al	PROPN
fcis-26112	29	4	.	.	PUNCT
fcis-26112	30	1	[	[	X
fcis-26112	30	2	5	5	NUM
fcis-26112	30	3	]	]	X
fcis-26112	30	4	pre	pre	ADJ
fcis-26112	30	5	-	-	ADJ
fcis-26112	30	6	trained	train	VERB
fcis-26112	30	7	models	model	NOUN
fcis-26112	30	8	on	on	ADP
fcis-26112	30	9	subsets	subset	NOUN
fcis-26112	30	10	of	of	ADP
fcis-26112	30	11	imagenet	imagenet	NOUN
fcis-26112	30	12	and	and	CCONJ
fcis-26112	30	13	evaluated	evaluate	VERB
fcis-26112	30	14	their	their	PRON
fcis-26112	30	15	transfer	transfer	NOUN
fcis-26112	30	16	performance	performance	NOUN
fcis-26112	30	17	across	across	ADP
fcis-26112	30	18	various	various	ADJ
fcis-26112	30	19	standard	standard	ADJ
fcis-26112	30	20	visual	visual	ADJ
fcis-26112	30	21	tasks	task	NOUN
fcis-26112	30	22	,	,	PUNCT
fcis-26112	30	23	finding	find	VERB
fcis-26112	30	24	that	that	SCONJ
fcis-26112	30	25	most	most	ADJ
fcis-26112	30	26	changes	change	NOUN
fcis-26112	30	27	in	in	ADP
fcis-26112	30	28	pre	pre	ADJ
fcis-26112	30	29	-	-	ADJ
fcis-26112	30	30	trained	train	VERB
fcis-26112	30	31	data	datum	NOUN
fcis-26112	30	32	selection	selection	NOUN
fcis-26112	30	33	did	do	AUX
fcis-26112	30	34	not	not	PART
fcis-26112	30	35	significantly	significantly	ADV
fcis-26112	30	36	affect	affect	VERB
fcis-26112	30	37	transfer	transfer	NOUN
fcis-26112	30	38	performance	performance	NOUN
fcis-26112	30	39	.	.	PUNCT
fcis-26112	31	1	they	they	PRON
fcis-26112	31	2	even	even	ADV
fcis-26112	31	3	argued	argue	VERB
fcis-26112	31	4	that	that	SCONJ
fcis-26112	31	5	cnn	cnn	PROPN
fcis-26112	31	6	training	training	NOUN
fcis-26112	31	7	is	be	AUX
fcis-26112	31	8	not	not	PART
fcis-26112	31	9	as	as	SCONJ
fcis-26112	31	10	data	datum	NOUN
fcis-26112	31	11	-	-	PUNCT
fcis-26112	31	12	hungry	hungry	ADJ
fcis-26112	31	13	as	as	SCONJ
fcis-26112	31	14	previously	previously	ADV
fcis-26112	31	15	thought	think	VERB
fcis-26112	31	16	,	,	PUNCT
fcis-26112	31	17	reaffirming	reaffirm	VERB
fcis-26112	31	18	its	its	PRON
fcis-26112	31	19	generalization	generalization	NOUN
fcis-26112	31	20	ability	ability	NOUN
fcis-26112	31	21	.	.	PUNCT
fcis-26112	32	1	all	all	DET
fcis-26112	32	2	the	the	DET
fcis-26112	32	3	above	above	ADJ
fcis-26112	32	4	studies	study	NOUN
fcis-26112	32	5	have	have	AUX
fcis-26112	32	6	confirmed	confirm	VERB
fcis-26112	32	7	the	the	DET
fcis-26112	32	8	good	good	ADJ
fcis-26112	32	9	transferability	transferability	NOUN
fcis-26112	32	10	and	and	CCONJ
fcis-26112	32	11	excellent	excellent	ADJ
fcis-26112	32	12	performance	performance	NOUN
fcis-26112	32	13	of	of	ADP
fcis-26112	32	14	pre	pre	ADJ
fcis-26112	32	15	-	-	ADJ
fcis-26112	32	16	trained	train	VERB
fcis-26112	32	17	cnn	cnn	PROPN
fcis-26112	32	18	models	model	NOUN
fcis-26112	32	19	.	.	PUNCT
fcis-26112	33	1	in	in	ADP
fcis-26112	33	2	the	the	DET
fcis-26112	33	3	context	context	NOUN
fcis-26112	33	4	of	of	ADP
fcis-26112	33	5	option	option	NOUN
fcis-26112	33	6	price	price	NOUN
fcis-26112	33	7	prediction	prediction	NOUN
fcis-26112	33	8	,	,	PUNCT
fcis-26112	33	9	there	there	PRON
fcis-26112	33	10	are	be	VERB
fcis-26112	33	11	also	also	ADV
fcis-26112	33	12	several	several	ADJ
fcis-26112	33	13	precedents	precedent	NOUN
fcis-26112	33	14	for	for	ADP
fcis-26112	33	15	using	use	VERB
fcis-26112	33	16	machine	machine	NOUN
fcis-26112	33	17	learning	learning	NOUN
fcis-26112	33	18	methods	method	NOUN
fcis-26112	33	19	.	.	PUNCT
fcis-26112	34	1	omer	omer	PROPN
fcis-26112	34	2	et	et	PROPN
fcis-26112	34	3	al	al	PROPN
fcis-26112	34	4	.	.	PROPN
fcis-26112	34	5	's	's	PART
fcis-26112	35	1	[	[	X
fcis-26112	35	2	6	6	NUM
fcis-26112	35	3	]	]	PUNCT
fcis-26112	35	4	literature	literature	NOUN
fcis-26112	35	5	review	review	NOUN
fcis-26112	35	6	reported	report	VERB
fcis-26112	35	7	various	various	ADJ
fcis-26112	35	8	neural	neural	ADJ
fcis-26112	35	9	network	network	NOUN
fcis-26112	35	10	applications	application	NOUN
fcis-26112	35	11	in	in	ADP
fcis-26112	35	12	financial	financial	ADJ
fcis-26112	35	13	forecasting	forecasting	NOUN
fcis-26112	35	14	,	,	PUNCT
fcis-26112	35	15	including	include	VERB
fcis-26112	35	16	jonathan	jonathan	PROPN
fcis-26112	35	17	et	et	PROPN
fcis-26112	35	18	al	al	PROPN
fcis-26112	35	19	.	.	PROPN
fcis-26112	35	20	's	's	PART
fcis-26112	35	21	[	[	X
fcis-26112	35	22	7	7	NUM
fcis-26112	35	23	]	]	SYM
fcis-26112	35	24	use	use	NOUN
fcis-26112	35	25	of	of	ADP
fcis-26112	35	26	cnn	cnn	PROPN
fcis-26112	35	27	models	model	NOUN
fcis-26112	35	28	to	to	PART
fcis-26112	35	29	predict	predict	VERB
fcis-26112	35	30	price	price	NOUN
fcis-26112	35	31	fluctuations	fluctuation	NOUN
fcis-26112	35	32	,	,	PUNCT
fcis-26112	35	33	finding	find	VERB
fcis-26112	35	34	excellent	excellent	ADJ
fcis-26112	35	35	performance	performance	NOUN
fcis-26112	35	36	.	.	PUNCT
fcis-26112	36	1	however	however	ADV
fcis-26112	36	2	,	,	PUNCT
fcis-26112	36	3	there	there	PRON
fcis-26112	36	4	have	have	AUX
fcis-26112	36	5	been	be	AUX
fcis-26112	36	6	no	no	DET
fcis-26112	36	7	reports	report	NOUN
fcis-26112	36	8	on	on	ADP
fcis-26112	36	9	using	use	VERB
fcis-26112	36	10	imagenet	imagenet	NOUN
fcis-26112	36	11	pre	pre	ADJ
fcis-26112	36	12	-	-	ADJ
fcis-26112	36	13	trained	train	VERB
fcis-26112	36	14	cnns	cnn	NOUN
fcis-26112	36	15	for	for	ADP
fcis-26112	36	16	transfer	transfer	NOUN
fcis-26112	36	17	learning	learning	NOUN
fcis-26112	36	18	in	in	ADP
fcis-26112	36	19	volatility	volatility	NOUN
fcis-26112	36	20	prediction	prediction	NOUN
fcis-26112	36	21	.	.	PUNCT
fcis-26112	37	1	boris	boris	PROPN
fcis-26112	37	2	et	et	PROPN
fcis-26112	37	3	al	al	PROPN
fcis-26112	37	4	.	.	PUNCT
fcis-26112	38	1	[	[	X
fcis-26112	38	2	8	8	NUM
fcis-26112	38	3	]	]	PUNCT
fcis-26112	38	4	proposed	propose	VERB
fcis-26112	38	5	a	a	DET
fcis-26112	38	6	method	method	NOUN
fcis-26112	38	7	to	to	PART
fcis-26112	38	8	visualize	visualize	VERB
fcis-26112	38	9	non	non	ADJ
fcis-26112	38	10	-	-	ADJ
fcis-26112	38	11	image	image	ADJ
fcis-26112	38	12	data	datum	NOUN
fcis-26112	38	13	and	and	CCONJ
fcis-26112	38	14	then	then	ADV
fcis-26112	38	15	use	use	VERB
fcis-26112	38	16	cnn	cnn	PROPN
fcis-26112	38	17	algorithms	algorithm	NOUN
fcis-26112	38	18	to	to	PART
fcis-26112	38	19	solve	solve	VERB
fcis-26112	38	20	learning	learn	VERB
fcis-26112	38	21	problems	problem	NOUN
fcis-26112	38	22	.	.	PUNCT
fcis-26112	39	1	ivascu	ivascu	NOUN
fcis-26112	40	1	[	[	X
fcis-26112	40	2	9	9	NUM
fcis-26112	40	3	]	]	PUNCT
fcis-26112	40	4	used	use	VERB
fcis-26112	40	5	machine	machine	NOUN
fcis-26112	40	6	learning	learning	NOUN
fcis-26112	40	7	methods	method	NOUN
fcis-26112	40	8	for	for	ADP
fcis-26112	40	9	option	option	NOUN
fcis-26112	40	10	pricing	pricing	NOUN
fcis-26112	40	11	,	,	PUNCT
fcis-26112	40	12	showing	show	VERB
fcis-26112	40	13	better	well	ADJ
fcis-26112	40	14	results	result	NOUN
fcis-26112	40	15	than	than	ADP
fcis-26112	40	16	traditional	traditional	ADJ
fcis-26112	40	17	methods	method	NOUN
fcis-26112	40	18	,	,	PUNCT
fcis-26112	40	19	but	but	CCONJ
fcis-26112	40	20	did	do	AUX
fcis-26112	40	21	not	not	PART
fcis-26112	40	22	mention	mention	VERB
fcis-26112	40	23	pre	pre	ADJ
fcis-26112	40	24	-	-	ADJ
fcis-26112	40	25	trained	train	VERB
fcis-26112	40	26	cnn	cnn	PROPN
fcis-26112	40	27	methods	method	NOUN
fcis-26112	40	28	.	.	PUNCT
fcis-26112	41	1	overall	overall	ADV
fcis-26112	41	2	,	,	PUNCT
fcis-26112	41	3	the	the	DET
fcis-26112	41	4	aforementioned	aforementioned	ADJ
fcis-26112	41	5	research	research	NOUN
fcis-26112	41	6	on	on	ADP
fcis-26112	41	7	applying	apply	VERB
fcis-26112	41	8	neural	neural	ADJ
fcis-26112	41	9	networks	network	NOUN
fcis-26112	41	10	to	to	PART
fcis-26112	41	11	option	option	NOUN
fcis-26112	41	12	price	price	NOUN
fcis-26112	41	13	prediction	prediction	NOUN
fcis-26112	41	14	has	have	AUX
fcis-26112	41	15	achieved	achieve	VERB
fcis-26112	41	16	significant	significant	ADJ
fcis-26112	41	17	results	result	NOUN
fcis-26112	41	18	,	,	PUNCT
fcis-26112	41	19	and	and	CCONJ
fcis-26112	41	20	the	the	DET
fcis-26112	41	21	use	use	NOUN
fcis-26112	41	22	of	of	ADP
fcis-26112	41	23	pre	pre	ADJ
fcis-26112	41	24	-	-	ADJ
fcis-26112	41	25	trained	train	VERB
fcis-26112	41	26	cnns	cnn	NOUN
fcis-26112	41	27	for	for	ADP
fcis-26112	41	28	transfer	transfer	NOUN
fcis-26112	41	29	learning	learning	NOUN
fcis-26112	41	30	has	have	AUX
fcis-26112	41	31	also	also	ADV
fcis-26112	41	32	been	be	AUX
fcis-26112	41	33	proven	prove	VERB
fcis-26112	41	34	feasible	feasible	ADJ
fcis-26112	41	35	.	.	PUNCT
fcis-26112	42	1	however	however	ADV
fcis-26112	42	2	,	,	PUNCT
fcis-26112	42	3	the	the	DET
fcis-26112	42	4	required	require	VERB
fcis-26112	42	5	dataset	dataset	NOUN
fcis-26112	42	6	dimensions	dimension	NOUN
fcis-26112	42	7	for	for	ADP
fcis-26112	42	8	different	different	ADJ
fcis-26112	42	9	research	research	NOUN
fcis-26112	42	10	subjects	subject	NOUN
fcis-26112	42	11	are	be	AUX
fcis-26112	42	12	diverse	diverse	ADJ
fcis-26112	42	13	and	and	CCONJ
fcis-26112	42	14	extensive	extensive	ADJ
fcis-26112	42	15	,	,	PUNCT
fcis-26112	42	16	and	and	CCONJ
fcis-26112	42	17	there	there	PRON
fcis-26112	42	18	have	have	AUX
fcis-26112	42	19	been	be	AUX
fcis-26112	42	20	no	no	DET
fcis-26112	42	21	reports	report	NOUN
fcis-26112	42	22	on	on	ADP
fcis-26112	42	23	using	use	VERB
fcis-26112	42	24	pre	pre	ADJ
fcis-26112	42	25	-	-	ADJ
fcis-26112	42	26	trained	train	VERB
fcis-26112	42	27	cnn	cnn	PROPN
fcis-26112	42	28	networks	network	NOUN
fcis-26112	42	29	for	for	ADP
fcis-26112	42	30	option	option	NOUN
fcis-26112	42	31	price	price	NOUN
fcis-26112	42	32	prediction	prediction	NOUN
fcis-26112	42	33	.	.	PUNCT
fcis-26112	43	1	this	this	PRON
fcis-26112	43	2	inspires	inspire	VERB
fcis-26112	43	3	and	and	CCONJ
fcis-26112	43	4	necessitates	necessitate	VERB
fcis-26112	43	5	the	the	DET
fcis-26112	43	6	exploration	exploration	NOUN
fcis-26112	43	7	of	of	ADP
fcis-26112	43	8	transferring	transfer	VERB
fcis-26112	43	9	pre	pre	ADJ
fcis-26112	43	10	-	-	ADJ
fcis-26112	43	11	trained	train	VERB
fcis-26112	43	12	cnn	cnn	PROPN
fcis-26112	43	13	models	model	NOUN
fcis-26112	43	14	to	to	ADP
fcis-26112	43	15	the	the	DET
fcis-26112	43	16	problem	problem	NOUN
fcis-26112	43	17	of	of	ADP
fcis-26112	43	18	option	option	NOUN
fcis-26112	43	19	price	price	NOUN
fcis-26112	43	20	prediction	prediction	NOUN
fcis-26112	43	21	,	,	PUNCT
fcis-26112	43	22	as	as	SCONJ
fcis-26112	43	23	better	well	ADJ
fcis-26112	43	24	predictions	prediction	NOUN
fcis-26112	43	25	can	can	AUX
fcis-26112	43	26	reduce	reduce	VERB
fcis-26112	43	27	investors	investor	NOUN
fcis-26112	43	28	'	'	PART
fcis-26112	43	29	losses	loss	NOUN
fcis-26112	43	30	and	and	CCONJ
fcis-26112	43	31	help	help	VERB
fcis-26112	43	32	them	they	PRON
fcis-26112	43	33	achieve	achieve	VERB
fcis-26112	43	34	higher	high	ADJ
fcis-26112	43	35	returns	return	NOUN
fcis-26112	43	36	.	.	PUNCT
fcis-26112	44	1	the	the	DET
fcis-26112	44	2	contribution	contribution	NOUN
fcis-26112	44	3	of	of	ADP
fcis-26112	44	4	this	this	DET
fcis-26112	44	5	study	study	NOUN
fcis-26112	44	6	lies	lie	VERB
fcis-26112	44	7	in	in	ADP
fcis-26112	44	8	proposing	propose	VERB
fcis-26112	44	9	a	a	DET
fcis-26112	44	10	method	method	NOUN
fcis-26112	44	11	to	to	PART
fcis-26112	44	12	transform	transform	VERB
fcis-26112	44	13	vector	vector	NOUN
fcis-26112	44	14	data	datum	NOUN
fcis-26112	44	15	into	into	ADP
fcis-26112	44	16	images	image	NOUN
fcis-26112	44	17	during	during	ADP
fcis-26112	44	18	data	datum	NOUN
fcis-26112	44	19	preprocessing	preprocessing	NOUN
fcis-26112	44	20	and	and	CCONJ
fcis-26112	44	21	comparing	compare	VERB
fcis-26112	44	22	the	the	DET
fcis-26112	44	23	performance	performance	NOUN
fcis-26112	44	24	of	of	ADP
fcis-26112	44	25	different	different	ADJ
fcis-26112	44	26	algorithms	algorithm	NOUN
fcis-26112	44	27	in	in	ADP
fcis-26112	44	28	10	10	NUM
fcis-26112	44	29	option	option	NOUN
fcis-26112	44	30	prediction	prediction	NOUN
fcis-26112	44	31	.	.	PUNCT
fcis-26112	45	1	the	the	DET
fcis-26112	45	2	results	result	NOUN
fcis-26112	45	3	indicate	indicate	VERB
fcis-26112	45	4	that	that	SCONJ
fcis-26112	45	5	on	on	ADP
fcis-26112	45	6	a	a	DET
fcis-26112	45	7	limited	limited	ADJ
fcis-26112	45	8	historical	historical	ADJ
fcis-26112	45	9	trading	trading	NOUN
fcis-26112	45	10	dataset	dataset	NOUN
fcis-26112	45	11	,	,	PUNCT
fcis-26112	45	12	the	the	DET
fcis-26112	45	13	pre	pre	ADJ
fcis-26112	45	14	-	-	ADJ
fcis-26112	45	15	trained	train	VERB
fcis-26112	45	16	resnet-50	resnet-50	PROPN
fcis-26112	45	17	outperforms	outperform	VERB
fcis-26112	45	18	the	the	DET
fcis-26112	45	19	random	random	ADJ
fcis-26112	45	20	forest	forest	NOUN
fcis-26112	45	21	and	and	CCONJ
fcis-26112	45	22	svr	svr	VERB
fcis-26112	45	23	algorithms	algorithm	NOUN
fcis-26112	45	24	by	by	ADP
fcis-26112	45	25	about	about	ADV
fcis-26112	45	26	51	51	NUM
fcis-26112	45	27	%	%	NOUN
fcis-26112	45	28	and	and	CCONJ
fcis-26112	45	29	the	the	DET
fcis-26112	45	30	un	un	ADJ
fcis-26112	45	31	-	-	ADJ
fcis-26112	45	32	pretrained	pretraine	VERB
fcis-26112	45	33	resnet-50	resnet-50	PROPN
fcis-26112	45	34	by	by	ADP
fcis-26112	45	35	6	6	NUM
fcis-26112	45	36	%	%	NOUN
fcis-26112	45	37	.	.	PUNCT
fcis-26112	46	1	the	the	DET
fcis-26112	46	2	structure	structure	NOUN
fcis-26112	46	3	of	of	ADP
fcis-26112	46	4	the	the	DET
fcis-26112	46	5	paper	paper	NOUN
fcis-26112	46	6	is	be	AUX
fcis-26112	46	7	as	as	SCONJ
fcis-26112	46	8	follows	follow	VERB
fcis-26112	46	9	:	:	PUNCT
fcis-26112	46	10	section	section	NOUN
fcis-26112	46	11	2	2	NUM
fcis-26112	46	12	,	,	PUNCT
fcis-26112	46	13	models	model	NOUN
fcis-26112	46	14	and	and	CCONJ
fcis-26112	46	15	methods	method	NOUN
fcis-26112	46	16	,	,	PUNCT
fcis-26112	46	17	briefly	briefly	ADV
fcis-26112	46	18	explains	explain	VERB
fcis-26112	46	19	the	the	DET
fcis-26112	46	20	models	model	NOUN
fcis-26112	46	21	used	use	VERB
fcis-26112	46	22	and	and	CCONJ
fcis-26112	46	23	the	the	DET
fcis-26112	46	24	resnet-50	resnet-50	PROPN
fcis-26112	46	25	transfer	transfer	NOUN
fcis-26112	46	26	learning	learning	NOUN
fcis-26112	46	27	method	method	NOUN
fcis-26112	46	28	;	;	PUNCT
fcis-26112	46	29	section	section	NOUN
fcis-26112	46	30	3	3	NUM
fcis-26112	46	31	,	,	PUNCT
fcis-26112	46	32	experiments	experiment	NOUN
fcis-26112	46	33	and	and	CCONJ
fcis-26112	46	34	discussion	discussion	NOUN
fcis-26112	46	35	;	;	PUNCT
fcis-26112	46	36	and	and	CCONJ
fcis-26112	46	37	section	section	NOUN
fcis-26112	46	38	4	4	NUM
fcis-26112	46	39	,	,	PUNCT
fcis-26112	46	40	conclusion	conclusion	NOUN
fcis-26112	46	41	,	,	PUNCT
fcis-26112	46	42	which	which	PRON
fcis-26112	46	43	discusses	discuss	VERB
fcis-26112	46	44	the	the	DET
fcis-26112	46	45	limitations	limitation	NOUN
fcis-26112	46	46	of	of	ADP
fcis-26112	46	47	the	the	DET
fcis-26112	46	48	study	study	NOUN
fcis-26112	46	49	and	and	CCONJ
fcis-26112	46	50	suggests	suggest	VERB
fcis-26112	46	51	directions	direction	NOUN
fcis-26112	46	52	for	for	ADP
fcis-26112	46	53	future	future	ADJ
fcis-26112	46	54	work	work	NOUN
fcis-26112	46	55	.	.	PUNCT
fcis-26112	47	1	2	2	X
fcis-26112	47	2	.	.	NUM
fcis-26112	47	3	models	model	NOUN
fcis-26112	47	4	and	and	CCONJ
fcis-26112	47	5	methods	method	NOUN
fcis-26112	47	6	2.1	2.1	NUM
fcis-26112	47	7	.	.	PUNCT
fcis-26112	48	1	the	the	DET
fcis-26112	48	2	black	black	ADJ
fcis-26112	48	3	–	–	PUNCT
fcis-26112	48	4	scholes	schole	NOUN
fcis-26112	48	5	option	option	NOUN
fcis-26112	48	6	pricing	pricing	NOUN
fcis-26112	48	7	model	model	NOUN
fcis-26112	48	8	(	(	PUNCT
fcis-26112	48	9	bsopm	bsopm	NOUN
fcis-26112	48	10	)	)	PUNCT
fcis-26112	48	11	in	in	ADP
fcis-26112	48	12	this	this	DET
fcis-26112	48	13	paper	paper	NOUN
fcis-26112	48	14	,	,	PUNCT
fcis-26112	48	15	we	we	PRON
fcis-26112	48	16	use	use	VERB
fcis-26112	48	17	the	the	DET
fcis-26112	48	18	black	black	ADJ
fcis-26112	48	19	–	–	PUNCT
fcis-26112	48	20	scholes	schole	NOUN
fcis-26112	48	21	option	option	NOUN
fcis-26112	48	22	pricing	pricing	NOUN
fcis-26112	48	23	model	model	NOUN
fcis-26112	48	24	(	(	PUNCT
fcis-26112	48	25	bsopm	bsopm	NOUN
fcis-26112	48	26	)	)	PUNCT
fcis-26112	48	27	to	to	PART
fcis-26112	48	28	convert	convert	VERB
fcis-26112	48	29	the	the	DET
fcis-26112	48	30	predicted	predict	VERB
fcis-26112	48	31	implied	imply	VERB
fcis-26112	48	32	volatility	volatility	NOUN
fcis-26112	48	33	for	for	ADP
fcis-26112	48	34	the	the	DET
fcis-26112	48	35	target	target	NOUN
fcis-26112	48	36	date	date	NOUN
fcis-26112	48	37	into	into	ADP
fcis-26112	48	38	option	option	NOUN
fcis-26112	48	39	prices	price	NOUN
fcis-26112	48	40	.	.	PUNCT
fcis-26112	49	1	for	for	ADP
fcis-26112	49	2	call	call	NOUN
fcis-26112	49	3	options	option	NOUN
fcis-26112	49	4	,	,	PUNCT
fcis-26112	49	5	the	the	DET
fcis-26112	49	6	following	follow	VERB
fcis-26112	49	7	equation	equation	NOUN
fcis-26112	49	8	(	(	PUNCT
fcis-26112	49	9	1	1	X
fcis-26112	49	10	)	)	PUNCT
fcis-26112	49	11	applies	apply	VERB
fcis-26112	49	12	:	:	PUNCT
fcis-26112	49	13	c	c	PROPN
fcis-26112	49	14	s	s	PROPN
fcis-26112	49	15	,	,	PUNCT
fcis-26112	49	16	t	t	PROPN
fcis-26112	49	17	s	s	PART
fcis-26112	49	18	n	n	PROPN
fcis-26112	49	19	d	d	NOUN
fcis-26112	49	20	e	e	NOUN
fcis-26112	49	21	kn	kn	PROPN
fcis-26112	49	22	d	d	X
fcis-26112	49	23	(	(	PUNCT
fcis-26112	49	24	1	1	NUM
fcis-26112	49	25	)	)	PUNCT
fcis-26112	49	26	in	in	ADP
fcis-26112	49	27	this	this	DET
fcis-26112	49	28	formula	formula	NOUN
fcis-26112	49	29	,	,	PUNCT
fcis-26112	49	30	c	c	PROPN
fcis-26112	49	31	is	be	AUX
fcis-26112	49	32	the	the	DET
fcis-26112	49	33	call	call	NOUN
fcis-26112	49	34	option	option	NOUN
fcis-26112	49	35	price	price	NOUN
fcis-26112	49	36	,	,	PUNCT
fcis-26112	49	37	s	s	VERB
fcis-26112	49	38	is	be	AUX
fcis-26112	49	39	the	the	DET
fcis-26112	49	40	current	current	ADJ
fcis-26112	49	41	stock	stock	NOUN
fcis-26112	49	42	price	price	NOUN
fcis-26112	49	43	,	,	PUNCT
fcis-26112	49	44	k	k	PROPN
fcis-26112	49	45	is	be	AUX
fcis-26112	49	46	the	the	DET
fcis-26112	49	47	strike	strike	NOUN
fcis-26112	49	48	price	price	NOUN
fcis-26112	49	49	,	,	PUNCT
fcis-26112	49	50	r	r	NOUN
fcis-26112	49	51	is	be	AUX
fcis-26112	49	52	the	the	DET
fcis-26112	49	53	risk	risk	NOUN
fcis-26112	49	54	-	-	PUNCT
fcis-26112	49	55	free	free	ADJ
fcis-26112	49	56	interest	interest	NOUN
fcis-26112	49	57	rate	rate	NOUN
fcis-26112	49	58	,	,	PUNCT
fcis-26112	49	59	t	t	PROPN
fcis-26112	49	60	is	be	AUX
fcis-26112	49	61	the	the	DET
fcis-26112	49	62	time	time	NOUN
fcis-26112	49	63	to	to	ADP
fcis-26112	49	64	maturity	maturity	NOUN
fcis-26112	49	65	,	,	PUNCT
fcis-26112	49	66	and	and	CCONJ
fcis-26112	49	67	σ	σ	PROPN
fcis-26112	49	68	is	be	AUX
fcis-26112	49	69	the	the	DET
fcis-26112	49	70	implied	imply	VERB
fcis-26112	49	71	volatility	volatility	NOUN
fcis-26112	49	72	.	.	PUNCT
fcis-26112	50	1	n	n	PRON
fcis-26112	50	2	is	be	AUX
fcis-26112	50	3	the	the	DET
fcis-26112	50	4	cumulative	cumulative	ADJ
fcis-26112	50	5	distribution	distribution	NOUN
fcis-26112	50	6	function	function	NOUN
fcis-26112	50	7	of	of	ADP
fcis-26112	50	8	the	the	DET
fcis-26112	50	9	standard	standard	ADJ
fcis-26112	50	10	normal	normal	ADJ
fcis-26112	50	11	distribution	distribution	NOUN
fcis-26112	50	12	,	,	PUNCT
fcis-26112	50	13	and	and	CCONJ
fcis-26112	50	14	d1	d1	PROPN
fcis-26112	50	15	,	,	PUNCT
fcis-26112	50	16	d2	d2	PROPN
fcis-26112	50	17	are	be	AUX
fcis-26112	50	18	calculated	calculate	VERB
fcis-26112	50	19	as	as	ADP
fcis-26112	50	20	(	(	PUNCT
fcis-26112	50	21	2)(3	2)(3	NUM
fcis-26112	50	22	):	):	PUNCT
fcis-26112	50	23	√	√	NOUN
fcis-26112	50	24	√	√	NUM
fcis-26112	50	25	√	√	INTJ
fcis-26112	50	26	(	(	PUNCT
fcis-26112	50	27	2)(3	2)(3	NUM
fcis-26112	50	28	)	)	PUNCT
fcis-26112	50	29	2.2	2.2	NUM
fcis-26112	50	30	.	.	PUNCT
fcis-26112	51	1	random	random	ADJ
fcis-26112	51	2	forest	forest	NOUN
fcis-26112	51	3	and	and	CCONJ
fcis-26112	51	4	support	support	VERB
fcis-26112	51	5	vector	vector	NOUN
fcis-26112	51	6	regression	regression	NOUN
fcis-26112	51	7	random	random	ADJ
fcis-26112	51	8	forest	forest	NOUN
fcis-26112	51	9	is	be	AUX
fcis-26112	51	10	an	an	DET
fcis-26112	51	11	ensemble	ensemble	ADJ
fcis-26112	51	12	learning	learning	NOUN
fcis-26112	51	13	method	method	NOUN
fcis-26112	51	14	[	[	X
fcis-26112	51	15	10	10	NUM
fcis-26112	51	16	]	]	PUNCT
fcis-26112	51	17	that	that	PRON
fcis-26112	51	18	constructs	construct	VERB
fcis-26112	51	19	multiple	multiple	ADJ
fcis-26112	51	20	decision	decision	NOUN
fcis-26112	51	21	trees	tree	NOUN
fcis-26112	51	22	and	and	CCONJ
fcis-26112	51	23	averages	average	NOUN
fcis-26112	51	24	their	their	PRON
fcis-26112	51	25	predictions	prediction	NOUN
fcis-26112	51	26	as	as	ADP
fcis-26112	51	27	the	the	DET
fcis-26112	51	28	output	output	NOUN
fcis-26112	51	29	.	.	PUNCT
fcis-26112	52	1	its	its	PRON
fcis-26112	52	2	key	key	ADJ
fcis-26112	52	3	concepts	concept	NOUN
fcis-26112	52	4	include	include	VERB
fcis-26112	52	5	:	:	PUNCT
fcis-26112	52	6	bagging	bag	VERB
fcis-26112	52	7	:	:	PUNCT
fcis-26112	52	8	random	random	ADJ
fcis-26112	52	9	forest	forest	NOUN
fcis-26112	52	10	independently	independently	ADV
fcis-26112	52	11	trains	train	VERB
fcis-26112	52	12	decision	decision	NOUN
fcis-26112	52	13	trees	tree	NOUN
fcis-26112	52	14	by	by	ADP
fcis-26112	52	15	drawing	draw	VERB
fcis-26112	52	16	bootstrap	bootstrap	NOUN
fcis-26112	52	17	samples	sample	NOUN
fcis-26112	52	18	from	from	ADP
fcis-26112	52	19	the	the	DET
fcis-26112	52	20	training	training	NOUN
fcis-26112	52	21	set	set	NOUN
fcis-26112	52	22	.	.	PUNCT
fcis-26112	53	1	random	random	ADJ
fcis-26112	53	2	feature	feature	NOUN
fcis-26112	53	3	selection	selection	NOUN
fcis-26112	53	4	:	:	PUNCT
fcis-26112	53	5	random	random	ADJ
fcis-26112	53	6	forest	forest	NOUN
fcis-26112	53	7	splits	split	VERB
fcis-26112	53	8	nodes	node	NOUN
fcis-26112	53	9	based	base	VERB
fcis-26112	53	10	on	on	ADP
fcis-26112	53	11	subsets	subset	NOUN
fcis-26112	53	12	of	of	ADP
fcis-26112	53	13	features	feature	NOUN
fcis-26112	53	14	to	to	PART
fcis-26112	53	15	reduce	reduce	VERB
fcis-26112	53	16	the	the	DET
fcis-26112	53	17	correlation	correlation	NOUN
fcis-26112	53	18	between	between	ADP
fcis-26112	53	19	trees	tree	NOUN
fcis-26112	53	20	.	.	PUNCT
fcis-26112	54	1	ensemble	ensemble	ADJ
fcis-26112	54	2	averaging	averaging	NOUN
fcis-26112	54	3	:	:	PUNCT
fcis-26112	54	4	the	the	DET
fcis-26112	54	5	final	final	ADJ
fcis-26112	54	6	prediction	prediction	NOUN
fcis-26112	54	7	is	be	AUX
fcis-26112	54	8	the	the	DET
fcis-26112	54	9	mean	mean	NOUN
fcis-26112	54	10	of	of	ADP
fcis-26112	54	11	all	all	DET
fcis-26112	54	12	the	the	DET
fcis-26112	54	13	trees	tree	NOUN
fcis-26112	54	14	'	'	PART
fcis-26112	54	15	predictions	prediction	NOUN
fcis-26112	54	16	.	.	PUNCT
fcis-26112	55	1	the	the	DET
fcis-26112	55	2	formula	formula	NOUN
fcis-26112	55	3	is	be	AUX
fcis-26112	55	4	as	as	SCONJ
fcis-26112	55	5	follows	follow	VERB
fcis-26112	55	6	:	:	PUNCT
fcis-26112	55	7	f	f	PROPN
fcis-26112	55	8	∑	∑	PROPN
fcis-26112	55	9	f	f	PROPN
fcis-26112	55	10	x	x	X
fcis-26112	55	11	(	(	PUNCT
fcis-26112	55	12	4	4	NUM
fcis-26112	55	13	)	)	PUNCT
fcis-26112	55	14	out	out	ADV
fcis-26112	55	15	-	-	PUNCT
fcis-26112	55	16	of	of	ADP
fcis-26112	55	17	-	-	PUNCT
fcis-26112	55	18	bag	bag	NOUN
fcis-26112	55	19	(	(	PUNCT
fcis-26112	55	20	oob	oob	NOUN
fcis-26112	55	21	):	):	PUNCT
fcis-26112	55	22	each	each	DET
fcis-26112	55	23	tree	tree	NOUN
fcis-26112	55	24	leaves	leave	VERB
fcis-26112	55	25	out	out	ADP
fcis-26112	55	26	a	a	DET
fcis-26112	55	27	subset	subset	NOUN
fcis-26112	55	28	of	of	ADP
fcis-26112	55	29	the	the	DET
fcis-26112	55	30	training	training	NOUN
fcis-26112	55	31	data	datum	NOUN
fcis-26112	55	32	,	,	PUNCT
fcis-26112	55	33	called	call	VERB
fcis-26112	55	34	out	out	ADV
fcis-26112	55	35	-	-	PUNCT
fcis-26112	55	36	of	of	ADP
fcis-26112	55	37	-	-	PUNCT
fcis-26112	55	38	bag	bag	NOUN
fcis-26112	55	39	samples	sample	NOUN
fcis-26112	55	40	,	,	PUNCT
fcis-26112	55	41	which	which	PRON
fcis-26112	55	42	are	be	AUX
fcis-26112	55	43	used	use	VERB
fcis-26112	55	44	to	to	PART
fcis-26112	55	45	estimate	estimate	VERB
fcis-26112	55	46	the	the	DET
fcis-26112	55	47	generalization	generalization	NOUN
fcis-26112	55	48	error	error	NOUN
fcis-26112	55	49	and	and	CCONJ
fcis-26112	55	50	adjust	adjust	VERB
fcis-26112	55	51	the	the	DET
fcis-26112	55	52	number	number	NOUN
fcis-26112	55	53	of	of	ADP
fcis-26112	55	54	trees	tree	NOUN
fcis-26112	55	55	accordingly	accordingly	ADV
fcis-26112	55	56	.	.	PUNCT
fcis-26112	56	1	support	support	NOUN
fcis-26112	56	2	vector	vector	NOUN
fcis-26112	56	3	regression	regression	NOUN
fcis-26112	56	4	(	(	PUNCT
fcis-26112	56	5	svr	svr	PROPN
fcis-26112	56	6	)	)	PUNCT
fcis-26112	56	7	is	be	AUX
fcis-26112	56	8	a	a	DET
fcis-26112	56	9	supervised	supervised	ADJ
fcis-26112	56	10	learning	learning	NOUN
fcis-26112	56	11	algorithm	algorithm	NOUN
fcis-26112	56	12	adapted	adapt	VERB
fcis-26112	56	13	from	from	ADP
fcis-26112	56	14	support	support	NOUN
fcis-26112	56	15	vector	vector	NOUN
fcis-26112	56	16	machines	machine	NOUN
fcis-26112	56	17	(	(	PUNCT
fcis-26112	56	18	svm	svm	PROPN
fcis-26112	56	19	)	)	PUNCT
fcis-26112	56	20	for	for	ADP
fcis-26112	56	21	regression	regression	NOUN
fcis-26112	56	22	tasks	task	NOUN
fcis-26112	56	23	[	[	X
fcis-26112	56	24	11	11	NUM
fcis-26112	56	25	]	]	PUNCT
fcis-26112	56	26	.	.	PUNCT
fcis-26112	57	1	svr	svr	PROPN
fcis-26112	57	2	introduces	introduce	VERB
fcis-26112	57	3	an	an	DET
fcis-26112	57	4	ε	ε	NOUN
fcis-26112	57	5	-	-	PUNCT
fcis-26112	57	6	insensitive	insensitive	ADJ
fcis-26112	57	7	loss	loss	NOUN
fcis-26112	57	8	function	function	NOUN
fcis-26112	57	9	that	that	PRON
fcis-26112	57	10	defines	define	VERB
fcis-26112	57	11	a	a	DET
fcis-26112	57	12	tolerance	tolerance	NOUN
fcis-26112	57	13	margin	margin	NOUN
fcis-26112	57	14	,	,	PUNCT
fcis-26112	57	15	within	within	ADP
fcis-26112	57	16	which	which	PRON
fcis-26112	57	17	errors	error	NOUN
fcis-26112	57	18	are	be	AUX
fcis-26112	57	19	not	not	PART
fcis-26112	57	20	penalized	penalize	VERB
fcis-26112	57	21	.	.	PUNCT
fcis-26112	58	1	only	only	ADV
fcis-26112	58	2	errors	error	NOUN
fcis-26112	58	3	beyond	beyond	ADP
fcis-26112	58	4	the	the	DET
fcis-26112	58	5	ε	ε	PROPN
fcis-26112	58	6	margin	margin	NOUN
fcis-26112	58	7	incur	incur	VERB
fcis-26112	58	8	a	a	DET
fcis-26112	58	9	loss	loss	NOUN
fcis-26112	58	10	.	.	PUNCT
fcis-26112	59	1	svr	svr	PROPN
fcis-26112	59	2	aims	aim	VERB
fcis-26112	59	3	to	to	PART
fcis-26112	59	4	find	find	VERB
fcis-26112	59	5	the	the	DET
fcis-26112	59	6	optimal	optimal	ADJ
fcis-26112	59	7	hyperplane	hyperplane	NOUN
fcis-26112	59	8	.	.	PUNCT
fcis-26112	60	1	in	in	ADP
fcis-26112	60	2	regression	regression	NOUN
fcis-26112	60	3	,	,	PUNCT
fcis-26112	60	4	this	this	DET
fcis-26112	60	5	hyperplane	hyperplane	NOUN
fcis-26112	60	6	is	be	AUX
fcis-26112	60	7	a	a	DET
fcis-26112	60	8	function	function	NOUN
fcis-26112	60	9	that	that	PRON
fcis-26112	60	10	best	well	ADV
fcis-26112	60	11	fits	fit	VERB
fcis-26112	60	12	the	the	DET
fcis-26112	60	13	data	datum	NOUN
fcis-26112	60	14	(	(	PUNCT
fcis-26112	60	15	support	support	NOUN
fcis-26112	60	16	vectors	vector	NOUN
fcis-26112	60	17	)	)	PUNCT
fcis-26112	60	18	while	while	SCONJ
fcis-26112	60	19	maintaining	maintain	VERB
fcis-26112	60	20	a	a	DET
fcis-26112	60	21	margin	margin	NOUN
fcis-26112	60	22	of	of	ADP
fcis-26112	60	23	ε	ε	PROPN
fcis-26112	60	24	around	around	ADP
fcis-26112	60	25	it	it	PRON
fcis-26112	60	26	.	.	PUNCT
fcis-26112	61	1	svr	svr	PROPN
fcis-26112	61	2	also	also	ADV
fcis-26112	61	3	employs	employ	VERB
fcis-26112	61	4	the	the	DET
fcis-26112	61	5	kernel	kernel	NOUN
fcis-26112	61	6	trick	trick	NOUN
fcis-26112	61	7	to	to	PART
fcis-26112	61	8	transform	transform	VERB
fcis-26112	61	9	the	the	DET
fcis-26112	61	10	input	input	NOUN
fcis-26112	61	11	space	space	NOUN
fcis-26112	61	12	into	into	ADP
fcis-26112	61	13	a	a	DET
fcis-26112	61	14	higher	higher	ADV
fcis-26112	61	15	-	-	PUNCT
fcis-26112	61	16	dimensional	dimensional	ADJ
fcis-26112	61	17	space	space	NOUN
fcis-26112	61	18	.	.	PUNCT
fcis-26112	62	1	this	this	PRON
fcis-26112	62	2	allows	allow	VERB
fcis-26112	62	3	svr	svr	PROPN
fcis-26112	62	4	to	to	PART
fcis-26112	62	5	find	find	VERB
fcis-26112	62	6	a	a	DET
fcis-26112	62	7	linear	linear	ADJ
fcis-26112	62	8	fit	fit	NOUN
fcis-26112	62	9	in	in	ADP
fcis-26112	62	10	the	the	DET
fcis-26112	62	11	transformed	transform	VERB
fcis-26112	62	12	space	space	NOUN
fcis-26112	62	13	,	,	PUNCT
fcis-26112	62	14	which	which	PRON
fcis-26112	62	15	corresponds	correspond	VERB
fcis-26112	62	16	to	to	ADP
fcis-26112	62	17	a	a	DET
fcis-26112	62	18	nonlinear	nonlinear	ADJ
fcis-26112	62	19	fit	fit	NOUN
fcis-26112	62	20	in	in	ADP
fcis-26112	62	21	the	the	DET
fcis-26112	62	22	original	original	ADJ
fcis-26112	62	23	space	space	NOUN
fcis-26112	62	24	.	.	PUNCT
fcis-26112	63	1	its	its	PRON
fcis-26112	63	2	regularization	regularization	NOUN
fcis-26112	63	3	parameter	parameter	NOUN
fcis-26112	63	4	(	(	PUNCT
fcis-26112	63	5	c	c	NOUN
fcis-26112	63	6	)	)	PUNCT
fcis-26112	63	7	controls	control	VERB
fcis-26112	63	8	the	the	DET
fcis-26112	63	9	trade	trade	NOUN
fcis-26112	63	10	-	-	PUNCT
fcis-26112	63	11	off	off	NOUN
fcis-26112	63	12	between	between	ADP
fcis-26112	63	13	a	a	DET
fcis-26112	63	14	low	low	ADJ
fcis-26112	63	15	error	error	NOUN
fcis-26112	63	16	margin	margin	NOUN
fcis-26112	63	17	and	and	CCONJ
fcis-26112	63	18	a	a	DET
fcis-26112	63	19	smooth	smooth	ADJ
fcis-26112	63	20	regression	regression	NOUN
fcis-26112	63	21	function	function	NOUN
fcis-26112	63	22	.	.	PUNCT
fcis-26112	64	1	a	a	DET
fcis-26112	64	2	higher	high	ADJ
fcis-26112	64	3	c	c	NOUN
fcis-26112	64	4	value	value	NOUN
fcis-26112	64	5	penalizes	penalize	VERB
fcis-26112	64	6	large	large	ADJ
fcis-26112	64	7	errors	error	NOUN
fcis-26112	64	8	more	more	ADV
fcis-26112	64	9	,	,	PUNCT
fcis-26112	64	10	resulting	result	VERB
fcis-26112	64	11	in	in	ADP
fcis-26112	64	12	a	a	DET
fcis-26112	64	13	tighter	tight	ADJ
fcis-26112	64	14	fit	fit	NOUN
fcis-26112	64	15	,	,	PUNCT
fcis-26112	64	16	while	while	SCONJ
fcis-26112	64	17	a	a	DET
fcis-26112	64	18	lower	low	ADJ
fcis-26112	64	19	c	c	NOUN
fcis-26112	64	20	value	value	NOUN
fcis-26112	64	21	allows	allow	VERB
fcis-26112	64	22	more	more	ADJ
fcis-26112	64	23	error	error	NOUN
fcis-26112	64	24	tolerance	tolerance	NOUN
fcis-26112	64	25	and	and	CCONJ
fcis-26112	64	26	results	result	NOUN
fcis-26112	64	27	in	in	ADP
fcis-26112	64	28	a	a	DET
fcis-26112	64	29	smoother	smooth	ADJ
fcis-26112	64	30	function	function	NOUN
fcis-26112	64	31	.	.	PUNCT
fcis-26112	65	1	figure	figure	NOUN
fcis-26112	65	2	1	1	NUM
fcis-26112	65	3	.	.	PUNCT
fcis-26112	66	1	support	support	NOUN
fcis-26112	66	2	vector	vector	NOUN
fcis-26112	66	3	regression	regression	NOUN
fcis-26112	66	4	schematic	schematic	ADJ
fcis-26112	66	5	diagram	diagram	NOUN
fcis-26112	66	6	,	,	PUNCT
fcis-26112	66	7	red	red	PROPN
fcis-26112	66	8	indicates	indicate	VERB
fcis-26112	66	9	the	the	DET
fcis-26112	66	10	ε	ε	PROPN
fcis-26112	66	11	-	-	PUNCT
fcis-26112	66	12	margin	margin	NOUN
fcis-26112	66	13	band	band	NOUN
fcis-26112	66	14	,	,	PUNCT
fcis-26112	66	15	samples	sample	NOUN
fcis-26112	66	16	falling	fall	VERB
fcis-26112	66	17	into	into	ADP
fcis-26112	66	18	it	it	PRON
fcis-26112	66	19	do	do	AUX
fcis-26112	66	20	not	not	PART
fcis-26112	66	21	calculate	calculate	VERB
fcis-26112	66	22	loss	loss	NOUN
fcis-26112	66	23	.	.	PUNCT
fcis-26112	67	1	[	[	X
fcis-26112	67	2	12	12	NUM
fcis-26112	67	3	]	]	SYM
fcis-26112	67	4	2.3	2.3	NUM
fcis-26112	67	5	.	.	PUNCT
fcis-26112	68	1	resnet-50	resnet-50	NOUN
fcis-26112	68	2	and	and	CCONJ
fcis-26112	68	3	transfer	transfer	NOUN
fcis-26112	68	4	learning	learn	VERB
fcis-26112	68	5	resnet-50	resnet-50	PROPN
fcis-26112	68	6	is	be	AUX
fcis-26112	68	7	a	a	DET
fcis-26112	68	8	classical	classical	ADJ
fcis-26112	68	9	convolutional	convolutional	ADJ
fcis-26112	68	10	neural	neural	ADJ
fcis-26112	68	11	network	network	NOUN
fcis-26112	68	12	(	(	PUNCT
fcis-26112	68	13	cnn	cnn	PROPN
fcis-26112	68	14	)	)	PUNCT
fcis-26112	68	15	commonly	commonly	ADV
fcis-26112	68	16	used	use	VERB
fcis-26112	68	17	for	for	ADP
fcis-26112	68	18	image	image	NOUN
fcis-26112	68	19	classification	classification	NOUN
fcis-26112	68	20	and	and	CCONJ
fcis-26112	68	21	recognition	recognition	NOUN
fcis-26112	68	22	.	.	PUNCT
fcis-26112	69	1	figure	figure	NOUN
fcis-26112	69	2	2	2	NUM
fcis-26112	69	3	shows	show	VERB
fcis-26112	69	4	its	its	PRON
fcis-26112	69	5	network	network	NOUN
fcis-26112	69	6	architecture	architecture	NOUN
fcis-26112	69	7	.	.	PUNCT
fcis-26112	70	1	what	what	PRON
fcis-26112	70	2	sets	set	VERB
fcis-26112	70	3	resnet-50	resnet-50	NOUN
fcis-26112	70	4	apart	apart	ADV
fcis-26112	70	5	from	from	ADP
fcis-26112	70	6	other	other	ADJ
fcis-26112	70	7	cnns	cnn	NOUN
fcis-26112	70	8	is	be	AUX
fcis-26112	70	9	its	its	PRON
fcis-26112	70	10	use	use	NOUN
fcis-26112	70	11	of	of	ADP
fcis-26112	70	12	a	a	DET
fcis-26112	70	13	residual	residual	ADJ
fcis-26112	70	14	structure	structure	NOUN
fcis-26112	70	15	introduced	introduce	VERB
fcis-26112	70	16	by	by	ADP
fcis-26112	70	17	the	the	DET
fcis-26112	70	18	designers	designer	NOUN
fcis-26112	70	19	[	[	X
fcis-26112	70	20	13	13	NUM
fcis-26112	70	21	]	]	PUNCT
fcis-26112	70	22	.	.	PUNCT
fcis-26112	71	1	this	this	DET
fcis-26112	71	2	structure	structure	NOUN
fcis-26112	71	3	allows	allow	VERB
fcis-26112	71	4	some	some	DET
fcis-26112	71	5	intermediate	intermediate	ADJ
fcis-26112	71	6	layers	layer	NOUN
fcis-26112	71	7	of	of	ADP
fcis-26112	71	8	the	the	DET
fcis-26112	71	9	neural	neural	ADJ
fcis-26112	71	10	network	network	NOUN
fcis-26112	71	11	to	to	PART
fcis-26112	71	12	adapt	adapt	VERB
fcis-26112	71	13	to	to	ADP
fcis-26112	71	14	a	a	DET
fcis-26112	71	15	residual	residual	ADJ
fcis-26112	71	16	mapping	mapping	NOUN
fcis-26112	71	17	instead	instead	ADV
fcis-26112	71	18	of	of	ADP
fcis-26112	71	19	directly	directly	ADV
fcis-26112	71	20	fitting	fit	VERB
fcis-26112	71	21	the	the	DET
fcis-26112	71	22	desired	desire	VERB
fcis-26112	71	23	underlying	underlie	VERB
fcis-26112	71	24	mapping	mapping	NOUN
fcis-26112	71	25	.	.	PUNCT
fcis-26112	72	1	assume	assume	VERB
fcis-26112	72	2	the	the	DET
fcis-26112	72	3	underlying	underlie	VERB
fcis-26112	72	4	mapping	mapping	NOUN
fcis-26112	72	5	is	be	AUX
fcis-26112	72	6	h(x	h(x	PROPN
fcis-26112	72	7	)	)	PUNCT
fcis-26112	72	8	,	,	PUNCT
fcis-26112	72	9	and	and	CCONJ
fcis-26112	72	10	the	the	DET
fcis-26112	72	11	stacked	stack	VERB
fcis-26112	72	12	nonlinear	nonlinear	ADJ
fcis-26112	72	13	layers	layer	NOUN
fcis-26112	72	14	adapt	adapt	VERB
fcis-26112	72	15	to	to	ADP
fcis-26112	72	16	the	the	DET
fcis-26112	72	17	residual	residual	ADJ
fcis-26112	72	18	mapping	mapping	NOUN
fcis-26112	72	19	:	:	PUNCT
fcis-26112	73	1	f(x)=h(x)-x	f(x)=h(x)-x	PROPN
fcis-26112	73	2	,	,	PUNCT
fcis-26112	73	3	the	the	DET
fcis-26112	73	4	output	output	NOUN
fcis-26112	73	5	of	of	ADP
fcis-26112	73	6	the	the	DET
fcis-26112	73	7	convolutional	convolutional	ADJ
fcis-26112	73	8	layers	layer	NOUN
fcis-26112	73	9	is	be	AUX
fcis-26112	73	10	then	then	ADV
fcis-26112	73	11	added	add	VERB
fcis-26112	73	12	directly	directly	ADV
fcis-26112	73	13	to	to	ADP
fcis-26112	73	14	the	the	DET
fcis-26112	73	15	input	input	NOUN
fcis-26112	73	16	,	,	PUNCT
fcis-26112	73	17	reformulating	reformulate	VERB
fcis-26112	73	18	the	the	DET
fcis-26112	73	19	original	original	ADJ
fcis-26112	73	20	mapping	mapping	NOUN
fcis-26112	73	21	as	as	ADP
fcis-26112	73	22	f(x)+x	f(x)+x	NOUN
fcis-26112	73	23	.	.	PUNCT
fcis-26112	74	1	this	this	PRON
fcis-26112	74	2	is	be	AUX
fcis-26112	74	3	achieved	achieve	VERB
fcis-26112	74	4	by	by	ADP
fcis-26112	74	5	adding	add	VERB
fcis-26112	74	6	a	a	DET
fcis-26112	74	7	"	"	PUNCT
fcis-26112	74	8	shortcut	shortcut	NOUN
fcis-26112	74	9	connection	connection	NOUN
fcis-26112	74	10	"	"	PUNCT
fcis-26112	74	11	that	that	PRON
fcis-26112	74	12	skips	skip	VERB
fcis-26112	74	13	one	one	NUM
fcis-26112	74	14	or	or	CCONJ
fcis-26112	74	15	more	more	ADJ
fcis-26112	74	16	layers	layer	NOUN
fcis-26112	74	17	and	and	CCONJ
fcis-26112	74	18	directly	directly	ADV
fcis-26112	74	19	adds	add	VERB
fcis-26112	74	20	the	the	DET
fcis-26112	74	21	input	input	NOUN
fcis-26112	74	22	to	to	ADP
fcis-26112	74	23	the	the	DET
fcis-26112	74	24	output	output	NOUN
fcis-26112	74	25	of	of	ADP
fcis-26112	74	26	the	the	DET
fcis-26112	74	27	stacked	stack	VERB
fcis-26112	74	28	convolutional	convolutional	ADJ
fcis-26112	74	29	layers	layer	NOUN
fcis-26112	74	30	.	.	PUNCT
fcis-26112	75	1	figure	figure	NOUN
fcis-26112	75	2	3	3	NUM
fcis-26112	75	3	illustrates	illustrate	VERB
fcis-26112	75	4	the	the	DET
fcis-26112	75	5	structure	structure	NOUN
fcis-26112	75	6	of	of	ADP
fcis-26112	75	7	a	a	DET
fcis-26112	75	8	residual	residual	ADJ
fcis-26112	75	9	block	block	NOUN
fcis-26112	75	10	in	in	ADP
fcis-26112	75	11	resnet-50	resnet-50	NUM
fcis-26112	75	12	,	,	PUNCT
fcis-26112	75	13	and	and	CCONJ
fcis-26112	75	14	figure	figure	VERB
fcis-26112	75	15	4	4	NUM
fcis-26112	75	16	provides	provide	VERB
fcis-26112	75	17	a	a	DET
fcis-26112	75	18	detailed	detailed	ADJ
fcis-26112	75	19	breakdown	breakdown	NOUN
fcis-26112	75	20	of	of	ADP
fcis-26112	75	21	resnet-50	resnet-50	PROPN
fcis-26112	75	22	's	's	PART
fcis-26112	75	23	composition	composition	NOUN
fcis-26112	75	24	.	.	PUNCT
fcis-26112	76	1	figure	figure	NOUN
fcis-26112	76	2	2	2	NUM
fcis-26112	76	3	.	.	PUNCT
fcis-26112	77	1	there	there	PRON
fcis-26112	77	2	are	be	VERB
fcis-26112	77	3	five	five	NUM
fcis-26112	77	4	main	main	ADJ
fcis-26112	77	5	stages	stage	NOUN
fcis-26112	77	6	between	between	ADP
fcis-26112	77	7	the	the	DET
fcis-26112	77	8	input	input	NOUN
fcis-26112	77	9	and	and	CCONJ
fcis-26112	77	10	output	output	NOUN
fcis-26112	77	11	11	11	NUM
fcis-26112	77	12	stage0	stage0	NOUN
fcis-26112	77	13	is	be	AUX
fcis-26112	77	14	the	the	DET
fcis-26112	77	15	input	input	NOUN
fcis-26112	77	16	layer	layer	NOUN
fcis-26112	77	17	,	,	PUNCT
fcis-26112	77	18	and	and	CCONJ
fcis-26112	77	19	each	each	DET
fcis-26112	77	20	subsequent	subsequent	ADJ
fcis-26112	77	21	stage	stage	NOUN
fcis-26112	77	22	consists	consist	VERB
fcis-26112	77	23	of	of	ADP
fcis-26112	77	24	two	two	NUM
fcis-26112	77	25	types	type	NOUN
fcis-26112	77	26	of	of	ADP
fcis-26112	77	27	bottleneck	bottleneck	NOUN
fcis-26112	77	28	blocks	block	NOUN
fcis-26112	77	29	(	(	PUNCT
fcis-26112	77	30	special	special	ADJ
fcis-26112	77	31	residual	residual	ADJ
fcis-26112	77	32	blocks	block	NOUN
fcis-26112	77	33	):	):	PUNCT
fcis-26112	77	34	btnk1	btnk1	NOUN
fcis-26112	77	35	,	,	PUNCT
fcis-26112	77	36	where	where	SCONJ
fcis-26112	77	37	the	the	DET
fcis-26112	77	38	number	number	NOUN
fcis-26112	77	39	of	of	ADP
fcis-26112	77	40	input	input	NOUN
fcis-26112	77	41	and	and	CCONJ
fcis-26112	77	42	output	output	NOUN
fcis-26112	77	43	channels	channel	NOUN
fcis-26112	77	44	differs	differ	NOUN
fcis-26112	77	45	,	,	PUNCT
fcis-26112	77	46	and	and	CCONJ
fcis-26112	77	47	btnk2	btnk2	NOUN
fcis-26112	77	48	,	,	PUNCT
fcis-26112	77	49	where	where	SCONJ
fcis-26112	77	50	the	the	DET
fcis-26112	77	51	number	number	NOUN
fcis-26112	77	52	of	of	ADP
fcis-26112	77	53	input	input	NOUN
fcis-26112	77	54	and	and	CCONJ
fcis-26112	77	55	output	output	NOUN
fcis-26112	77	56	channels	channel	NOUN
fcis-26112	77	57	is	be	AUX
fcis-26112	77	58	the	the	DET
fcis-26112	77	59	same	same	ADJ
fcis-26112	77	60	.	.	PUNCT
fcis-26112	78	1	figure	figure	NOUN
fcis-26112	78	2	3	3	NUM
fcis-26112	78	3	.	.	PUNCT
fcis-26112	79	1	resnet-50	resnet-50	ADJ
fcis-26112	79	2	residual	residual	ADJ
fcis-26112	79	3	block	block	NOUN
fcis-26112	79	4	and	and	CCONJ
fcis-26112	79	5	shortcut	shortcut	NOUN
fcis-26112	79	6	connection	connection	NOUN
fcis-26112	79	7	diagram	diagram	NOUN
fcis-26112	79	8	figure	figure	NOUN
fcis-26112	79	9	4	4	NUM
fcis-26112	79	10	.	.	PUNCT
fcis-26112	80	1	composition	composition	NOUN
fcis-26112	80	2	of	of	ADP
fcis-26112	80	3	convolutional	convolutional	ADJ
fcis-26112	80	4	layer	layer	NOUN
fcis-26112	80	5	to	to	PART
fcis-26112	80	6	address	address	VERB
fcis-26112	80	7	potential	potential	ADJ
fcis-26112	80	8	discrepancies	discrepancy	NOUN
fcis-26112	80	9	between	between	ADP
fcis-26112	80	10	the	the	DET
fcis-26112	80	11	input	input	NOUN
fcis-26112	80	12	and	and	CCONJ
fcis-26112	80	13	output	output	NOUN
fcis-26112	80	14	sizes	size	NOUN
fcis-26112	80	15	of	of	ADP
fcis-26112	80	16	residual	residual	ADJ
fcis-26112	80	17	blocks	block	NOUN
fcis-26112	80	18	,	,	PUNCT
fcis-26112	80	19	resnet-50	resnet-50	PROPN
fcis-26112	80	20	employs	employ	VERB
fcis-26112	80	21	zeropadding	zeropadde	VERB
fcis-26112	80	22	.	.	PUNCT
fcis-26112	81	1	for	for	ADP
fcis-26112	81	2	issues	issue	NOUN
fcis-26112	81	3	where	where	SCONJ
fcis-26112	81	4	the	the	DET
fcis-26112	81	5	number	number	NOUN
fcis-26112	81	6	of	of	ADP
fcis-26112	81	7	channels	channel	NOUN
fcis-26112	81	8	in	in	ADP
fcis-26112	81	9	the	the	DET
fcis-26112	81	10	feature	feature	NOUN
fcis-26112	81	11	maps	map	NOUN
fcis-26112	81	12	might	might	AUX
fcis-26112	81	13	be	be	AUX
fcis-26112	81	14	inconsistent	inconsistent	ADJ
fcis-26112	81	15	,	,	PUNCT
fcis-26112	81	16	a	a	DET
fcis-26112	81	17	1×1	1×1	NUM
fcis-26112	81	18	convolution	convolution	NOUN
fcis-26112	81	19	kernel	kernel	NOUN
fcis-26112	81	20	is	be	AUX
fcis-26112	81	21	used	use	VERB
fcis-26112	81	22	to	to	PART
fcis-26112	81	23	adjust	adjust	VERB
fcis-26112	81	24	them	they	PRON
fcis-26112	81	25	.	.	PUNCT
fcis-26112	82	1	this	this	DET
fcis-26112	82	2	structure	structure	NOUN
fcis-26112	82	3	has	have	VERB
fcis-26112	82	4	a	a	DET
fcis-26112	82	5	notable	notable	ADJ
fcis-26112	82	6	advantage	advantage	NOUN
fcis-26112	82	7	in	in	ADP
fcis-26112	82	8	solving	solve	VERB
fcis-26112	82	9	the	the	DET
fcis-26112	82	10	vanishing	vanish	VERB
fcis-26112	82	11	gradient	gradient	NOUN
fcis-26112	82	12	problem	problem	NOUN
fcis-26112	82	13	.	.	PUNCT
fcis-26112	83	1	during	during	ADP
fcis-26112	83	2	backpropagation	backpropagation	NOUN
fcis-26112	83	3	of	of	ADP
fcis-26112	83	4	errors	error	NOUN
fcis-26112	83	5	in	in	ADP
fcis-26112	83	6	the	the	DET
fcis-26112	83	7	neural	neural	ADJ
fcis-26112	83	8	network	network	NOUN
fcis-26112	83	9	,	,	PUNCT
fcis-26112	83	10	the	the	DET
fcis-26112	83	11	presence	presence	NOUN
fcis-26112	83	12	of	of	ADP
fcis-26112	83	13	shortcut	shortcut	NOUN
fcis-26112	83	14	connections	connection	NOUN
fcis-26112	83	15	ensures	ensure	VERB
fcis-26112	83	16	that	that	SCONJ
fcis-26112	83	17	even	even	ADV
fcis-26112	83	18	very	very	ADV
fcis-26112	83	19	small	small	ADJ
fcis-26112	83	20	errors	error	NOUN
fcis-26112	83	21	can	can	AUX
fcis-26112	83	22	be	be	AUX
fcis-26112	83	23	effectively	effectively	ADV
fcis-26112	83	24	propagated	propagate	VERB
fcis-26112	83	25	back	back	ADV
fcis-26112	83	26	,	,	PUNCT
fcis-26112	83	27	thereby	thereby	ADV
fcis-26112	83	28	preventing	prevent	VERB
fcis-26112	83	29	the	the	DET
fcis-26112	83	30	vanishing	vanish	VERB
fcis-26112	83	31	gradient	gradient	NOUN
fcis-26112	83	32	issue	issue	NOUN
fcis-26112	83	33	.	.	PUNCT
fcis-26112	84	1	2.4	2.4	NUM
fcis-26112	84	2	.	.	PUNCT
fcis-26112	84	3	data	datum	NOUN
fcis-26112	84	4	preprocessing	preprocesse	VERB
fcis-26112	84	5	next	next	ADV
fcis-26112	84	6	,	,	PUNCT
fcis-26112	84	7	we	we	PRON
fcis-26112	84	8	will	will	AUX
fcis-26112	84	9	explain	explain	VERB
fcis-26112	84	10	how	how	SCONJ
fcis-26112	84	11	to	to	PART
fcis-26112	84	12	preprocess	preprocess	VERB
fcis-26112	84	13	the	the	DET
fcis-26112	84	14	original	original	ADJ
fcis-26112	84	15	vector	vector	NOUN
fcis-26112	84	16	data	datum	NOUN
fcis-26112	84	17	to	to	PART
fcis-26112	84	18	fit	fit	VERB
fcis-26112	84	19	the	the	DET
fcis-26112	84	20	input	input	NOUN
fcis-26112	84	21	of	of	ADP
fcis-26112	84	22	the	the	DET
fcis-26112	84	23	pre	pre	ADJ
fcis-26112	84	24	-	-	ADJ
fcis-26112	84	25	trained	train	VERB
fcis-26112	84	26	resnet-50	resnet-50	NOUN
fcis-26112	84	27	,	,	PUNCT
fcis-26112	84	28	enabling	enable	VERB
fcis-26112	84	29	transfer	transfer	NOUN
fcis-26112	84	30	learning	learning	NOUN
fcis-26112	84	31	.	.	PUNCT
fcis-26112	85	1	in	in	ADP
fcis-26112	85	2	the	the	DET
fcis-26112	85	3	past	past	NOUN
fcis-26112	85	4	,	,	PUNCT
fcis-26112	85	5	there	there	PRON
fcis-26112	85	6	have	have	AUX
fcis-26112	85	7	been	be	AUX
fcis-26112	85	8	related	relate	VERB
fcis-26112	85	9	studies	study	NOUN
fcis-26112	85	10	on	on	ADP
fcis-26112	85	11	solving	solve	VERB
fcis-26112	85	12	non	non	ADJ
fcis-26112	85	13	-	-	ADJ
fcis-26112	85	14	image	image	ADJ
fcis-26112	85	15	learning	learning	NOUN
fcis-26112	85	16	problems	problem	NOUN
fcis-26112	85	17	by	by	ADP
fcis-26112	85	18	mapping	map	VERB
fcis-26112	85	19	to	to	ADP
fcis-26112	85	20	images	image	NOUN
fcis-26112	85	21	,	,	PUNCT
fcis-26112	85	22	such	such	ADJ
fcis-26112	85	23	as	as	ADP
fcis-26112	85	24	[	[	X
fcis-26112	85	25	15	15	NUM
fcis-26112	85	26	]	]	PUNCT
fcis-26112	85	27	.	.	PUNCT
fcis-26112	86	1	similarly	similarly	ADV
fcis-26112	86	2	,	,	PUNCT
fcis-26112	86	3	we	we	PRON
fcis-26112	86	4	use	use	VERB
fcis-26112	86	5	the	the	DET
fcis-26112	86	6	following	follow	VERB
fcis-26112	86	7	operations	operation	NOUN
fcis-26112	86	8	to	to	ADP
fcis-26112	86	9	preprocess	preprocess	NOUN
fcis-26112	86	10	data	datum	NOUN
fcis-26112	86	11	.	.	PUNCT
fcis-26112	87	1	our	our	PRON
fcis-26112	87	2	design	design	NOUN
fcis-26112	87	3	treats	treat	VERB
fcis-26112	87	4	the	the	DET
fcis-26112	87	5	resnet50	resnet50	NOUN
fcis-26112	87	6	pre	pre	VERB
fcis-26112	87	7	-	-	VERB
fcis-26112	87	8	trained	train	VERB
fcis-26112	87	9	on	on	ADP
fcis-26112	87	10	imagenet	imagenet	NOUN
fcis-26112	87	11	as	as	ADP
fcis-26112	87	12	an	an	DET
fcis-26112	87	13	effective	effective	ADJ
fcis-26112	87	14	feature	feature	NOUN
fcis-26112	87	15	extractor	extractor	NOUN
fcis-26112	87	16	,	,	PUNCT
fcis-26112	87	17	then	then	ADV
fcis-26112	87	18	customizes	customize	VERB
fcis-26112	87	19	the	the	DET
fcis-26112	87	20	top	top	ADJ
fcis-26112	87	21	layer	layer	NOUN
fcis-26112	87	22	:	:	PUNCT
fcis-26112	87	23	a	a	DET
fcis-26112	87	24	global	global	ADJ
fcis-26112	87	25	average	average	ADJ
fcis-26112	87	26	pooling	pooling	NOUN
fcis-26112	87	27	layer	layer	NOUN
fcis-26112	87	28	and	and	CCONJ
fcis-26112	87	29	two	two	NUM
fcis-26112	87	30	fully	fully	ADV
fcis-26112	87	31	connected	connected	ADJ
fcis-26112	87	32	layers	layer	NOUN
fcis-26112	87	33	for	for	ADP
fcis-26112	87	34	this	this	DET
fcis-26112	87	35	task	task	NOUN
fcis-26112	87	36	's	's	PART
fcis-26112	87	37	transfer	transfer	NOUN
fcis-26112	87	38	learning	learning	NOUN
fcis-26112	87	39	.	.	PUNCT
fcis-26112	88	1	to	to	PART
fcis-26112	88	2	train	train	VERB
fcis-26112	88	3	these	these	DET
fcis-26112	88	4	top	top	ADJ
fcis-26112	88	5	layers	layer	NOUN
fcis-26112	88	6	,	,	PUNCT
fcis-26112	88	7	we	we	PRON
fcis-26112	88	8	convert	convert	VERB
fcis-26112	88	9	the	the	DET
fcis-26112	88	10	four	four	NUM
fcis-26112	88	11	feature	feature	NOUN
fcis-26112	88	12	dimensions	dimension	NOUN
fcis-26112	88	13	of	of	ADP
fcis-26112	88	14	the	the	DET
fcis-26112	88	15	input	input	NOUN
fcis-26112	88	16	into	into	ADP
fcis-26112	88	17	rgb	rgb	PROPN
fcis-26112	88	18	three	three	NUM
fcis-26112	88	19	-	-	PUNCT
fcis-26112	88	20	channel	channel	NOUN
fcis-26112	88	21	images	image	NOUN
fcis-26112	88	22	.	.	PUNCT
fcis-26112	89	1	specifically	specifically	ADV
fcis-26112	89	2	,	,	PUNCT
fcis-26112	89	3	the	the	DET
fcis-26112	89	4	normalized	normalize	VERB
fcis-26112	89	5	values	value	NOUN
fcis-26112	89	6	of	of	ADP
fcis-26112	89	7	the	the	DET
fcis-26112	89	8	four	four	NUM
fcis-26112	89	9	dimensions	dimension	NOUN
fcis-26112	89	10	are	be	AUX
fcis-26112	89	11	projected	project	VERB
fcis-26112	89	12	onto	onto	ADP
fcis-26112	89	13	the	the	DET
fcis-26112	89	14	range	range	NOUN
fcis-26112	89	15	[	[	X
fcis-26112	89	16	0	0	NUM
fcis-26112	89	17	,	,	PUNCT
fcis-26112	89	18	255	255	NUM
fcis-26112	89	19	]	]	PUNCT
fcis-26112	89	20	as	as	ADP
fcis-26112	89	21	grayscale	grayscale	NOUN
fcis-26112	89	22	,	,	PUNCT
fcis-26112	89	23	forming	form	VERB
fcis-26112	89	24	a	a	DET
fcis-26112	89	25	2×2	2×2	NUM
fcis-26112	89	26	image	image	NOUN
fcis-26112	89	27	.	.	PUNCT
fcis-26112	90	1	the	the	DET
fcis-26112	90	2	standard	standard	ADJ
fcis-26112	90	3	input	input	NOUN
fcis-26112	90	4	size	size	NOUN
fcis-26112	90	5	for	for	ADP
fcis-26112	90	6	resnet-50	resnet-50	PROPN
fcis-26112	90	7	is	be	AUX
fcis-26112	90	8	an	an	DET
fcis-26112	90	9	rgb	rgb	PROPN
fcis-26112	90	10	image	image	NOUN
fcis-26112	90	11	with	with	ADP
fcis-26112	90	12	a	a	DET
fcis-26112	90	13	height	height	NOUN
fcis-26112	90	14	and	and	CCONJ
fcis-26112	90	15	width	width	NOUN
fcis-26112	90	16	of	of	ADP
fcis-26112	90	17	224	224	NUM
fcis-26112	90	18	(	(	PUNCT
fcis-26112	90	19	224×224×3	224×224×3	NUM
fcis-26112	90	20	)	)	PUNCT
fcis-26112	90	21	,	,	PUNCT
fcis-26112	90	22	but	but	CCONJ
fcis-26112	90	23	an	an	DET
fcis-26112	90	24	input	input	NOUN
fcis-26112	90	25	size	size	NOUN
fcis-26112	90	26	of	of	ADP
fcis-26112	90	27	56×56×3	56×56×3	NUM
fcis-26112	90	28	is	be	AUX
fcis-26112	90	29	sufficient	sufficient	ADJ
fcis-26112	90	30	for	for	ADP
fcis-26112	90	31	this	this	DET
fcis-26112	90	32	transfer	transfer	NOUN
fcis-26112	90	33	learning	learning	NOUN
fcis-26112	90	34	task	task	NOUN
fcis-26112	90	35	,	,	PUNCT
fcis-26112	90	36	greatly	greatly	ADV
fcis-26112	90	37	reducing	reduce	VERB
fcis-26112	90	38	computation	computation	NOUN
fcis-26112	90	39	while	while	SCONJ
fcis-26112	90	40	maintaining	maintain	VERB
fcis-26112	90	41	balanced	balanced	ADJ
fcis-26112	90	42	scaling	scaling	NOUN
fcis-26112	90	43	to	to	PART
fcis-26112	90	44	avoid	avoid	VERB
fcis-26112	90	45	distortion	distortion	NOUN
fcis-26112	90	46	.	.	PUNCT
fcis-26112	91	1	therefore	therefore	ADV
fcis-26112	91	2	,	,	PUNCT
fcis-26112	91	3	we	we	PRON
fcis-26112	91	4	proportionally	proportionally	ADV
fcis-26112	91	5	enlarge	enlarge	VERB
fcis-26112	91	6	the	the	DET
fcis-26112	91	7	2×2	2×2	NUM
fcis-26112	91	8	image	image	NOUN
fcis-26112	91	9	,	,	PUNCT
fcis-26112	91	10	transforming	transform	VERB
fcis-26112	91	11	each	each	DET
fcis-26112	91	12	pixel	pixel	NOUN
fcis-26112	91	13	into	into	ADP
fcis-26112	91	14	a	a	DET
fcis-26112	91	15	28×28	28×28	NUM
fcis-26112	91	16	pixel	pixel	NOUN
fcis-26112	91	17	block	block	NOUN
fcis-26112	91	18	,	,	PUNCT
fcis-26112	91	19	and	and	CCONJ
fcis-26112	91	20	expand	expand	VERB
fcis-26112	91	21	the	the	DET
fcis-26112	91	22	grayscale	grayscale	NOUN
fcis-26112	91	23	x	x	PUNCT
fcis-26112	91	24	to	to	ADP
fcis-26112	91	25	an	an	DET
fcis-26112	91	26	rgb	rgb	PROPN
fcis-26112	91	27	three	three	NUM
fcis-26112	91	28	-	-	PUNCT
fcis-26112	91	29	channel	channel	NOUN
fcis-26112	91	30	(	(	PUNCT
fcis-26112	91	31	x	x	NOUN
fcis-26112	91	32	,	,	PUNCT
fcis-26112	91	33	x	x	X
fcis-26112	91	34	,	,	PUNCT
fcis-26112	91	35	x	x	NOUN
fcis-26112	91	36	)	)	PUNCT
fcis-26112	91	37	.	.	PUNCT
fcis-26112	92	1	finally	finally	ADV
fcis-26112	92	2	,	,	PUNCT
fcis-26112	92	3	each	each	DET
fcis-26112	92	4	sample	sample	NOUN
fcis-26112	92	5	is	be	AUX
fcis-26112	92	6	processed	process	VERB
fcis-26112	92	7	into	into	ADP
fcis-26112	92	8	an	an	DET
fcis-26112	92	9	image	image	NOUN
fcis-26112	92	10	as	as	SCONJ
fcis-26112	92	11	shown	show	VERB
fcis-26112	92	12	in	in	ADP
fcis-26112	92	13	fig	fig	NOUN
fcis-26112	92	14	.	.	PUNCT
fcis-26112	93	1	5	5	X
fcis-26112	93	2	.	.	X
fcis-26112	93	3	figure	figure	NOUN
fcis-26112	93	4	5	5	NUM
fcis-26112	93	5	.	.	PUNCT
fcis-26112	93	6	convert	convert	VERB
fcis-26112	93	7	the	the	DET
fcis-26112	93	8	four	four	NUM
fcis-26112	93	9	-	-	PUNCT
fcis-26112	93	10	dimensional	dimensional	ADJ
fcis-26112	93	11	vector	vector	NOUN
fcis-26112	93	12	into	into	ADP
fcis-26112	93	13	an	an	DET
fcis-26112	93	14	rgb	rgb	PROPN
fcis-26112	93	15	threechannel	threechannel	NOUN
fcis-26112	93	16	image	image	NOUN
fcis-26112	93	17	after	after	ADP
fcis-26112	93	18	training	train	VERB
fcis-26112	93	19	the	the	DET
fcis-26112	93	20	custom	custom	NOUN
fcis-26112	93	21	top	top	ADJ
fcis-26112	93	22	layers	layer	NOUN
fcis-26112	93	23	with	with	ADP
fcis-26112	93	24	these	these	DET
fcis-26112	93	25	images	image	NOUN
fcis-26112	93	26	,	,	PUNCT
fcis-26112	93	27	the	the	DET
fcis-26112	93	28	model	model	NOUN
fcis-26112	93	29	can	can	AUX
fcis-26112	93	30	learn	learn	VERB
fcis-26112	93	31	how	how	SCONJ
fcis-26112	93	32	to	to	PART
fcis-26112	93	33	apply	apply	VERB
fcis-26112	93	34	the	the	DET
fcis-26112	93	35	high	high	ADJ
fcis-26112	93	36	-	-	PUNCT
fcis-26112	93	37	level	level	NOUN
fcis-26112	93	38	features	feature	NOUN
fcis-26112	93	39	extracted	extract	VERB
fcis-26112	93	40	by	by	ADP
fcis-26112	93	41	the	the	DET
fcis-26112	93	42	pre	pre	ADJ
fcis-26112	93	43	-	-	ADJ
fcis-26112	93	44	trained	train	VERB
fcis-26112	93	45	model	model	NOUN
fcis-26112	93	46	to	to	PART
fcis-26112	93	47	predict	predict	VERB
fcis-26112	93	48	option	option	NOUN
fcis-26112	93	49	prices	price	NOUN
fcis-26112	93	50	.	.	PUNCT
fcis-26112	94	1	2.5	2.5	NUM
fcis-26112	94	2	.	.	PUNCT
fcis-26112	95	1	error	error	NOUN
fcis-26112	95	2	assessment	assessment	NOUN
fcis-26112	95	3	based	base	VERB
fcis-26112	95	4	on	on	ADP
fcis-26112	95	5	rmse	rmse	NOUN
fcis-26112	95	6	and	and	CCONJ
fcis-26112	95	7	r²	r²	VERB
fcis-26112	95	8	∑	∑	PUNCT
fcis-26112	95	9	(	(	PUNCT
fcis-26112	95	10	5	5	NUM
fcis-26112	95	11	)	)	PUNCT
fcis-26112	95	12	1	1	NUM
fcis-26112	95	13	∑	∑	PROPN
fcis-26112	95	14	∑	∑	PROPN
fcis-26112	95	15	(	(	PUNCT
fcis-26112	95	16	6	6	NUM
fcis-26112	95	17	)	)	PUNCT
fcis-26112	95	18	in	in	ADP
fcis-26112	95	19	formulas	formula	NOUN
fcis-26112	95	20	(	(	PUNCT
fcis-26112	95	21	5	5	NUM
fcis-26112	95	22	)	)	PUNCT
fcis-26112	95	23	and	and	CCONJ
fcis-26112	95	24	(	(	PUNCT
fcis-26112	95	25	6	6	NUM
fcis-26112	95	26	)	)	PUNCT
fcis-26112	95	27	,	,	PUNCT
fcis-26112	95	28	represents	represent	VERB
fcis-26112	95	29	the	the	DET
fcis-26112	95	30	number	number	NOUN
fcis-26112	95	31	of	of	ADP
fcis-26112	95	32	samples	sample	NOUN
fcis-26112	95	33	.	.	PUNCT
fcis-26112	96	1	rmse	rmse	PROPN
fcis-26112	96	2	is	be	AUX
fcis-26112	96	3	a	a	DET
fcis-26112	96	4	common	common	ADJ
fcis-26112	96	5	metric	metric	NOUN
fcis-26112	96	6	used	use	VERB
fcis-26112	96	7	to	to	PART
fcis-26112	96	8	evaluate	evaluate	VERB
fcis-26112	96	9	regression	regression	NOUN
fcis-26112	96	10	,	,	PUNCT
fcis-26112	96	11	characterized	characterize	VERB
fcis-26112	96	12	by	by	ADP
fcis-26112	96	13	maintaining	maintain	VERB
fcis-26112	96	14	the	the	DET
fcis-26112	96	15	same	same	ADJ
fcis-26112	96	16	unit	unit	NOUN
fcis-26112	96	17	as	as	ADP
fcis-26112	96	18	the	the	DET
fcis-26112	96	19	original	original	ADJ
fcis-26112	96	20	data	datum	NOUN
fcis-26112	96	21	.	.	PUNCT
fcis-26112	97	1	this	this	DET
fcis-26112	97	2	characteristic	characteristic	NOUN
fcis-26112	97	3	makes	make	VERB
fcis-26112	97	4	it	it	PRON
fcis-26112	97	5	very	very	ADV
fcis-26112	97	6	suitable	suitable	ADJ
fcis-26112	97	7	for	for	ADP
fcis-26112	97	8	measuring	measure	VERB
fcis-26112	97	9	price	price	NOUN
fcis-26112	97	10	errors	error	NOUN
fcis-26112	97	11	,	,	PUNCT
fcis-26112	97	12	as	as	SCONJ
fcis-26112	97	13	it	it	PRON
fcis-26112	97	14	brings	bring	VERB
fcis-26112	97	15	the	the	DET
fcis-26112	97	16	error	error	NOUN
fcis-26112	97	17	metric	metric	ADJ
fcis-26112	97	18	back	back	ADV
fcis-26112	97	19	to	to	ADP
fcis-26112	97	20	the	the	DET
fcis-26112	97	21	price	price	NOUN
fcis-26112	97	22	scale	scale	NOUN
fcis-26112	97	23	[	[	X
fcis-26112	97	24	16	16	NUM
fcis-26112	97	25	]	]	PUNCT
fcis-26112	97	26	.	.	PUNCT
fcis-26112	98	1	r²	r²	NOUN
fcis-26112	98	2	is	be	AUX
fcis-26112	98	3	a	a	DET
fcis-26112	98	4	metric	metric	NOUN
fcis-26112	98	5	used	use	VERB
fcis-26112	98	6	only	only	ADV
fcis-26112	98	7	in	in	ADP
fcis-26112	98	8	regression	regression	NOUN
fcis-26112	98	9	problems	problem	NOUN
fcis-26112	98	10	[	[	X
fcis-26112	98	11	16	16	NUM
fcis-26112	98	12	]	]	PUNCT
fcis-26112	98	13	to	to	PART
fcis-26112	98	14	measure	measure	VERB
fcis-26112	98	15	the	the	DET
fcis-26112	98	16	amount	amount	NOUN
fcis-26112	98	17	of	of	ADP
fcis-26112	98	18	variation	variation	NOUN
fcis-26112	98	19	explained	explain	VERB
fcis-26112	98	20	by	by	ADP
fcis-26112	98	21	the	the	DET
fcis-26112	98	22	model	model	NOUN
fcis-26112	98	23	as	as	ADP
fcis-26112	98	24	a	a	DET
fcis-26112	98	25	proportion	proportion	NOUN
fcis-26112	98	26	of	of	ADP
fcis-26112	98	27	the	the	DET
fcis-26112	98	28	total	total	ADJ
fcis-26112	98	29	variation	variation	NOUN
fcis-26112	98	30	,	,	PUNCT
fcis-26112	98	31	reflecting	reflect	VERB
fcis-26112	98	32	the	the	DET
fcis-26112	98	33	model	model	NOUN
fcis-26112	98	34	's	's	PART
fcis-26112	98	35	ability	ability	NOUN
fcis-26112	98	36	to	to	PART
fcis-26112	98	37	interpret	interpret	VERB
fcis-26112	98	38	fluctuations	fluctuation	NOUN
fcis-26112	98	39	.	.	PUNCT
fcis-26112	99	1	therefore	therefore	ADV
fcis-26112	99	2	,	,	PUNCT
fcis-26112	99	3	this	this	DET
fcis-26112	99	4	paper	paper	NOUN
fcis-26112	99	5	uses	use	VERB
fcis-26112	99	6	these	these	DET
fcis-26112	99	7	two	two	NUM
fcis-26112	99	8	indicators	indicator	NOUN
fcis-26112	99	9	to	to	PART
fcis-26112	99	10	measure	measure	VERB
fcis-26112	99	11	errors	error	NOUN
fcis-26112	99	12	.	.	PUNCT
fcis-26112	100	1	the	the	PRON
fcis-26112	100	2	smaller	small	ADJ
fcis-26112	100	3	the	the	DET
fcis-26112	100	4	rmse	rmse	NOUN
fcis-26112	100	5	and	and	CCONJ
fcis-26112	100	6	the	the	PRON
fcis-26112	100	7	closer	close	ADV
fcis-26112	100	8	the	the	DET
fcis-26112	100	9	r²	r²	NOUN
fcis-26112	100	10	is	be	AUX
fcis-26112	100	11	to	to	ADP
fcis-26112	100	12	1	1	NUM
fcis-26112	100	13	,	,	PUNCT
fcis-26112	100	14	the	the	PRON
fcis-26112	100	15	better	well	ADJ
fcis-26112	100	16	the	the	DET
fcis-26112	100	17	accuracy	accuracy	NOUN
fcis-26112	100	18	of	of	ADP
fcis-26112	100	19	the	the	DET
fcis-26112	100	20	model	model	NOUN
fcis-26112	100	21	.	.	PUNCT
fcis-26112	101	1	the	the	DET
fcis-26112	101	2	error	error	NOUN
fcis-26112	101	3	handling	handling	NOUN
fcis-26112	101	4	in	in	ADP
fcis-26112	101	5	this	this	DET
fcis-26112	101	6	study	study	NOUN
fcis-26112	101	7	is	be	AUX
fcis-26112	101	8	used	use	VERB
fcis-26112	101	9	in	in	ADP
fcis-26112	101	10	two	two	NUM
fcis-26112	101	11	ways	way	NOUN
fcis-26112	101	12	:	:	PUNCT
fcis-26112	101	13	first	first	ADV
fcis-26112	101	14	,	,	PUNCT
fcis-26112	101	15	to	to	PART
fcis-26112	101	16	measure	measure	VERB
fcis-26112	101	17	the	the	DET
fcis-26112	101	18	prediction	prediction	NOUN
fcis-26112	101	19	accuracy	accuracy	NOUN
fcis-26112	101	20	of	of	ADP
fcis-26112	101	21	different	different	ADJ
fcis-26112	101	22	models	model	NOUN
fcis-26112	101	23	to	to	PART
fcis-26112	101	24	determine	determine	VERB
fcis-26112	101	25	the	the	DET
fcis-26112	101	26	best	well	ADV
fcis-26112	101	27	-	-	PUNCT
fcis-26112	101	28	performing	perform	VERB
fcis-26112	101	29	model	model	NOUN
fcis-26112	101	30	;	;	PUNCT
fcis-26112	101	31	second	second	ADJ
fcis-26112	101	32	,	,	PUNCT
fcis-26112	101	33	to	to	PART
fcis-26112	101	34	adjust	adjust	VERB
fcis-26112	101	35	the	the	DET
fcis-26112	101	36	internal	internal	ADJ
fcis-26112	101	37	parameters	parameter	NOUN
fcis-26112	101	38	of	of	ADP
fcis-26112	101	39	the	the	DET
fcis-26112	101	40	model	model	NOUN
fcis-26112	101	41	(	(	PUNCT
fcis-26112	101	42	such	such	ADJ
fcis-26112	101	43	as	as	ADP
fcis-26112	101	44	epoch	epoch	NOUN
fcis-26112	101	45	,	,	PUNCT
fcis-26112	101	46	learning	learn	VERB
fcis-26112	101	47	rate	rate	NOUN
fcis-26112	101	48	,	,	PUNCT
fcis-26112	101	49	etc	etc	X
fcis-26112	101	50	.	.	X
fcis-26112	101	51	)	)	PUNCT
fcis-26112	101	52	.	.	PUNCT
fcis-26112	102	1	12	12	NUM
fcis-26112	102	2	3	3	NUM
fcis-26112	102	3	.	.	PUNCT
fcis-26112	102	4	experiments	experiment	NOUN
fcis-26112	102	5	and	and	CCONJ
fcis-26112	102	6	discussion	discussion	NOUN
fcis-26112	102	7	3.1	3.1	NUM
fcis-26112	102	8	.	.	PUNCT
fcis-26112	103	1	data	datum	NOUN
fcis-26112	103	2	description	description	NOUN
fcis-26112	103	3	the	the	DET
fcis-26112	103	4	dataset	dataset	NOUN
fcis-26112	103	5	used	use	VERB
fcis-26112	103	6	in	in	ADP
fcis-26112	103	7	the	the	DET
fcis-26112	103	8	experiment	experiment	NOUN
fcis-26112	103	9	is	be	AUX
fcis-26112	103	10	from	from	ADP
fcis-26112	103	11	the	the	DET
fcis-26112	103	12	website	website	NOUN
fcis-26112	103	13	www.discountoptiondata.com	www.discountoptiondata.com	NOUN
fcis-26112	103	14	.	.	PUNCT
fcis-26112	104	1	this	this	DET
fcis-26112	104	2	website	website	NOUN
fcis-26112	104	3	has	have	AUX
fcis-26112	104	4	recorded	record	VERB
fcis-26112	104	5	daily	daily	ADJ
fcis-26112	104	6	options	option	NOUN
fcis-26112	104	7	data	datum	NOUN
fcis-26112	104	8	since	since	SCONJ
fcis-26112	104	9	2005	2005	NUM
fcis-26112	104	10	.	.	PUNCT
fcis-26112	105	1	we	we	PRON
fcis-26112	105	2	selected	select	VERB
fcis-26112	105	3	spx	spx	NUM
fcis-26112	105	4	call	call	NOUN
fcis-26112	105	5	option	option	NOUN
fcis-26112	105	6	contracts	contract	NOUN
fcis-26112	105	7	from	from	ADP
fcis-26112	105	8	december	december	PROPN
fcis-26112	105	9	1	1	NUM
fcis-26112	105	10	,	,	PUNCT
fcis-26112	105	11	2023	2023	NUM
fcis-26112	105	12	,	,	PUNCT
fcis-26112	105	13	to	to	ADP
fcis-26112	105	14	december	december	PROPN
fcis-26112	105	15	28	28	NUM
fcis-26112	105	16	,	,	PUNCT
fcis-26112	105	17	2023	2023	NUM
fcis-26112	105	18	,	,	PUNCT
fcis-26112	105	19	with	with	ADP
fcis-26112	105	20	strike	strike	NOUN
fcis-26112	105	21	prices	price	NOUN
fcis-26112	105	22	within	within	ADP
fcis-26112	105	23	±30	±30	NUM
fcis-26112	105	24	%	%	NOUN
fcis-26112	105	25	of	of	ADP
fcis-26112	105	26	the	the	DET
fcis-26112	105	27	underlying	underlie	VERB
fcis-26112	105	28	price	price	NOUN
fcis-26112	105	29	as	as	ADP
fcis-26112	105	30	the	the	DET
fcis-26112	105	31	dataset	dataset	NOUN
fcis-26112	105	32	.	.	PUNCT
fcis-26112	106	1	of	of	ADP
fcis-26112	106	2	these	these	PRON
fcis-26112	106	3	,	,	PUNCT
fcis-26112	106	4	80	80	NUM
fcis-26112	106	5	%	%	NOUN
fcis-26112	106	6	were	be	AUX
fcis-26112	106	7	used	use	VERB
fcis-26112	106	8	as	as	ADP
fcis-26112	106	9	the	the	DET
fcis-26112	106	10	training	training	NOUN
fcis-26112	106	11	set	set	NOUN
fcis-26112	106	12	and	and	CCONJ
fcis-26112	106	13	20	20	NUM
fcis-26112	106	14	%	%	NOUN
fcis-26112	106	15	as	as	ADP
fcis-26112	106	16	the	the	DET
fcis-26112	106	17	validation	validation	NOUN
fcis-26112	106	18	set	set	NOUN
fcis-26112	106	19	.	.	PUNCT
fcis-26112	107	1	the	the	DET
fcis-26112	107	2	data	datum	NOUN
fcis-26112	107	3	from	from	ADP
fcis-26112	107	4	december	december	PROPN
fcis-26112	107	5	29	29	NUM
fcis-26112	107	6	,	,	PUNCT
fcis-26112	107	7	2023	2023	NUM
fcis-26112	107	8	(	(	PUNCT
fcis-26112	107	9	with	with	ADP
fcis-26112	107	10	strike	strike	NOUN
fcis-26112	107	11	prices	price	NOUN
fcis-26112	107	12	within	within	ADP
fcis-26112	107	13	±30	±30	NUM
fcis-26112	107	14	%	%	NOUN
fcis-26112	107	15	of	of	ADP
fcis-26112	107	16	the	the	DET
fcis-26112	107	17	underlying	underlie	VERB
fcis-26112	107	18	price	price	NOUN
fcis-26112	107	19	and	and	CCONJ
fcis-26112	107	20	with	with	ADP
fcis-26112	107	21	maturity	maturity	NOUN
fcis-26112	107	22	between	between	ADP
fcis-26112	107	23	100	100	NUM
fcis-26112	107	24	and	and	CCONJ
fcis-26112	107	25	500	500	NUM
fcis-26112	107	26	days	day	NOUN
fcis-26112	107	27	)	)	PUNCT
fcis-26112	107	28	,	,	PUNCT
fcis-26112	107	29	was	be	AUX
fcis-26112	107	30	used	use	VERB
fcis-26112	107	31	as	as	ADP
fcis-26112	107	32	the	the	DET
fcis-26112	107	33	prediction	prediction	NOUN
fcis-26112	107	34	target	target	NOUN
fcis-26112	107	35	.	.	PUNCT
fcis-26112	108	1	an	an	DET
fcis-26112	108	2	example	example	NOUN
fcis-26112	108	3	of	of	ADP
fcis-26112	108	4	the	the	DET
fcis-26112	108	5	dataset	dataset	NOUN
fcis-26112	108	6	information	information	NOUN
fcis-26112	108	7	is	be	AUX
fcis-26112	108	8	as	as	SCONJ
fcis-26112	108	9	follows	follow	VERB
fcis-26112	108	10	:	:	PUNCT
fcis-26112	108	11	table	table	NOUN
fcis-26112	108	12	1	1	NUM
fcis-26112	108	13	.	.	PUNCT
fcis-26112	108	14	example	example	NOUN
fcis-26112	108	15	of	of	ADP
fcis-26112	108	16	the	the	DET
fcis-26112	108	17	raw	raw	ADJ
fcis-26112	108	18	dataset	dataset	NOUN
fcis-26112	108	19	.	.	PUNCT
fcis-26112	109	1	note	note	NOUN
fcis-26112	109	2	:	:	PUNCT
fcis-26112	109	3	the	the	DET
fcis-26112	109	4	implied	imply	VERB
fcis-26112	109	5	volatility	volatility	NOUN
fcis-26112	109	6	of	of	ADP
fcis-26112	109	7	some	some	DET
fcis-26112	109	8	data	datum	NOUN
fcis-26112	109	9	points	point	NOUN
fcis-26112	109	10	is	be	AUX
fcis-26112	109	11	very	very	ADV
fcis-26112	109	12	low	low	ADJ
fcis-26112	109	13	,	,	PUNCT
fcis-26112	109	14	not	not	PART
fcis-26112	109	15	missing	miss	VERB
fcis-26112	109	16	.	.	PUNCT
fcis-26112	110	1	index	index	NOUN
fcis-26112	110	2	symbol	symbol	NOUN
fcis-26112	110	3	date	date	NOUN
fcis-26112	110	4	maturity	maturity	NOUN
fcis-26112	110	5	strikeprice	strikeprice	NOUN
fcis-26112	110	6	underlyingprice	underlyingprice	NOUN
fcis-26112	110	7	putcall	putcall	NOUN
fcis-26112	110	8	askprice	askprice	PROPN
fcis-26112	110	9	asksize	asksize	PROPN
fcis-26112	110	10	bidprice	bidprice	NOUN
fcis-26112	110	11	bidsize	bidsize	PROPN
fcis-26112	110	12	lastprice	lastprice	NOUN
fcis-26112	110	13	impliedvolatility	impliedvolatility	NOUN
fcis-26112	110	14	1	1	NUM
fcis-26112	110	15	spx	spx	NOUN
fcis-26112	110	16	2023/12/4	2023/12/4	NUM
fcis-26112	110	17	0.030136986	0.030136986	NUM
fcis-26112	110	18	100	100	NUM
fcis-26112	110	19	4569.78	4569.78	NUM
fcis-26112	110	20	call	call	NOUN
fcis-26112	110	21	4470.1	4470.1	NUM
fcis-26112	110	22	77	77	NUM
fcis-26112	110	23	4460.2	4460.2	NUM
fcis-26112	110	24	77	77	NUM
fcis-26112	110	25	4449.6	4449.6	NUM
fcis-26112	110	26	0	0	NUM
fcis-26112	110	27	2	2	NUM
fcis-26112	110	28	spx	spx	NOUN
fcis-26112	110	29	2023/12/4	2023/12/4	NUM
fcis-26112	110	30	0.030136986	0.030136986	NUM
fcis-26112	110	31	1000	1000	NUM
fcis-26112	110	32	4569.78	4569.78	NUM
fcis-26112	110	33	call	call	VERB
fcis-26112	110	34	3571.7	3571.7	NUM
fcis-26112	110	35	77	77	NUM
fcis-26112	110	36	3561.6	3561.6	NUM
fcis-26112	110	37	77	77	NUM
fcis-26112	110	38	3546.85	3546.85	NUM
fcis-26112	110	39	0	0	NUM
fcis-26112	110	40	3	3	NUM
fcis-26112	110	41	spx	spx	PROPN
fcis-26112	110	42	2023/12/4	2023/12/4	NUM
fcis-26112	110	43	0.030136986	0.030136986	NUM
fcis-26112	110	44	1100	1100	NUM
fcis-26112	110	45	4569.78	4569.78	NUM
fcis-26112	110	46	call	call	VERB
fcis-26112	110	47	3471.9	3471.9	NUM
fcis-26112	110	48	77	77	NUM
fcis-26112	110	49	3461.8	3461.8	NUM
fcis-26112	110	50	77	77	NUM
fcis-26112	110	51	3457.18	3457.18	NUM
fcis-26112	110	52	0	0	NUM
fcis-26112	110	53	4	4	NUM
fcis-26112	110	54	spx	spx	NOUN
fcis-26112	110	55	2023/12/4	2023/12/4	NUM
fcis-26112	110	56	0.030136986	0.030136986	NUM
fcis-26112	110	57	1200	1200	NUM
fcis-26112	110	58	4569.78	4569.78	NUM
fcis-26112	110	59	call	call	VERB
fcis-26112	110	60	3372.2	3372.2	NUM
fcis-26112	110	61	77	77	NUM
fcis-26112	110	62	3360.3	3360.3	NUM
fcis-26112	110	63	30	30	NUM
fcis-26112	110	64	3366.65	3366.65	NUM
fcis-26112	110	65	0	0	NUM
fcis-26112	110	66	5	5	NUM
fcis-26112	110	67	spx	spx	NOUN
fcis-26112	110	68	2023/12/4	2023/12/4	NUM
fcis-26112	110	69	0.030136986	0.030136986	NUM
fcis-26112	110	70	1300	1300	NUM
fcis-26112	110	71	4569.78	4569.78	NUM
fcis-26112	110	72	call	call	VERB
fcis-26112	110	73	3272.2	3272.2	NUM
fcis-26112	110	74	77	77	NUM
fcis-26112	110	75	3262.5	3262.5	NUM
fcis-26112	110	76	77	77	NUM
fcis-26112	110	77	3249.85	3249.85	NUM
fcis-26112	110	78	0	0	NUM
fcis-26112	110	79	6	6	NUM
fcis-26112	110	80	spx	spx	NOUN
fcis-26112	110	81	2023/12/4	2023/12/4	NUM
fcis-26112	110	82	0.030136986	0.030136986	NUM
fcis-26112	110	83	200	200	NUM
fcis-26112	110	84	4569.78	4569.78	NUM
fcis-26112	110	85	call	call	VERB
fcis-26112	110	86	4369.9	4369.9	NUM
fcis-26112	110	87	77	77	NUM
fcis-26112	111	1	4360.7	4360.7	NUM
fcis-26112	111	2	77	77	NUM
fcis-26112	111	3	4353.7	4353.7	NUM
fcis-26112	111	4	0	0	NUM
fcis-26112	111	5	7	7	NUM
fcis-26112	111	6	spx	spx	NOUN
fcis-26112	111	7	2023/12/4	2023/12/4	NUM
fcis-26112	111	8	0.030136986	0.030136986	NUM
fcis-26112	111	9	300	300	NUM
fcis-26112	111	10	4569.78	4569.78	NUM
fcis-26112	111	11	call	call	VERB
fcis-26112	111	12	4270.3	4270.3	NUM
fcis-26112	111	13	77	77	NUM
fcis-26112	111	14	4260.3	4260.3	NUM
fcis-26112	111	15	77	77	NUM
fcis-26112	111	16	4254	4254	NUM
fcis-26112	111	17	0	0	NUM
fcis-26112	111	18	8	8	NUM
fcis-26112	111	19	spx	spx	NOUN
fcis-26112	111	20	2023/12/4	2023/12/4	NUM
fcis-26112	111	21	0.030136986	0.030136986	NUM
fcis-26112	111	22	400	400	NUM
fcis-26112	111	23	4569.78	4569.78	NUM
fcis-26112	111	24	call	call	NOUN
fcis-26112	111	25	4170.5	4170.5	NUM
fcis-26112	111	26	77	77	NUM
fcis-26112	111	27	4160.4	4160.4	NUM
fcis-26112	111	28	77	77	NUM
fcis-26112	111	29	4157.1	4157.1	NUM
fcis-26112	111	30	0	0	NUM
fcis-26112	111	31	9	9	NUM
fcis-26112	111	32	spx	spx	NUM
fcis-26112	111	33	2023/12/4	2023/12/4	NUM
fcis-26112	111	34	0.030136986	0.030136986	NUM
fcis-26112	111	35	500	500	NUM
fcis-26112	111	36	4569.78	4569.78	NUM
fcis-26112	111	37	call	call	VERB
fcis-26112	112	1	4070.7	4070.7	NUM
fcis-26112	112	2	77	77	NUM
fcis-26112	112	3	4060.6	4060.6	NUM
fcis-26112	112	4	77	77	NUM
fcis-26112	112	5	4050.35	4050.35	NUM
fcis-26112	112	6	0	0	NUM
fcis-26112	112	7	…	…	SYM
fcis-26112	112	8	93550	93550	NUM
fcis-26112	112	9	spx	spx	NOUN
fcis-26112	112	10	2023/12/28	2023/12/28	NUM
fcis-26112	112	11	5.98630137	5.98630137	NUM
fcis-26112	112	12	6200	6200	NUM
fcis-26112	112	13	4783.35	4783.35	NUM
fcis-26112	112	14	put	put	VERB
fcis-26112	112	15	1108.3	1108.3	NUM
fcis-26112	112	16	5	5	NUM
fcis-26112	112	17	1028.3	1028.3	NUM
fcis-26112	112	18	5	5	NUM
fcis-26112	112	19	0	0	NUM
fcis-26112	112	20	0	0	NUM
fcis-26112	113	1	this	this	DET
fcis-26112	113	2	study	study	NOUN
fcis-26112	113	3	selected	select	VERB
fcis-26112	113	4	'	'	PUNCT
fcis-26112	113	5	maturity	maturity	NOUN
fcis-26112	113	6	'	'	PUNCT
fcis-26112	113	7	,	,	PUNCT
fcis-26112	113	8	'	'	PUNCT
fcis-26112	113	9	strikeprice	strikeprice	NOUN
fcis-26112	113	10	'	'	PUNCT
fcis-26112	113	11	,	,	PUNCT
fcis-26112	113	12	'	'	PUNCT
fcis-26112	113	13	underlyingprice	underlyingprice	NOUN
fcis-26112	113	14	'	'	PUNCT
fcis-26112	113	15	,	,	PUNCT
fcis-26112	113	16	and	and	CCONJ
fcis-26112	113	17	'	'	PUNCT
fcis-26112	113	18	putcall	putcall	NOUN
fcis-26112	113	19	'	'	PUNCT
fcis-26112	113	20	as	as	ADP
fcis-26112	113	21	the	the	DET
fcis-26112	113	22	four	four	NUM
fcis-26112	113	23	input	input	NOUN
fcis-26112	113	24	features	feature	NOUN
fcis-26112	113	25	based	base	VERB
fcis-26112	113	26	on	on	ADP
fcis-26112	113	27	the	the	DET
fcis-26112	113	28	following	follow	VERB
fcis-26112	113	29	considerations	consideration	NOUN
fcis-26112	113	30	:	:	PUNCT
fcis-26112	113	31	firstly	firstly	ADV
fcis-26112	113	32	,	,	PUNCT
fcis-26112	113	33	these	these	DET
fcis-26112	113	34	features	feature	NOUN
fcis-26112	113	35	are	be	AUX
fcis-26112	113	36	core	core	NOUN
fcis-26112	113	37	variables	variable	NOUN
fcis-26112	113	38	in	in	ADP
fcis-26112	113	39	bsopm	bsopm	NOUN
fcis-26112	113	40	and	and	CCONJ
fcis-26112	113	41	theoretically	theoretically	ADV
fcis-26112	113	42	have	have	VERB
fcis-26112	113	43	a	a	DET
fcis-26112	113	44	direct	direct	ADJ
fcis-26112	113	45	impact	impact	NOUN
fcis-26112	113	46	on	on	ADP
fcis-26112	113	47	option	option	NOUN
fcis-26112	113	48	prices	price	NOUN
fcis-26112	113	49	and	and	CCONJ
fcis-26112	113	50	implied	imply	VERB
fcis-26112	113	51	volatility	volatility	NOUN
fcis-26112	113	52	.	.	PUNCT
fcis-26112	114	1	secondly	secondly	ADV
fcis-26112	114	2	,	,	PUNCT
fcis-26112	114	3	related	related	ADJ
fcis-26112	114	4	studies	study	NOUN
fcis-26112	114	5	on	on	ADP
fcis-26112	114	6	the	the	DET
fcis-26112	114	7	implied	imply	VERB
fcis-26112	114	8	volatility	volatility	NOUN
fcis-26112	114	9	surface	surface	NOUN
fcis-26112	114	10	show	show	VERB
fcis-26112	114	11	that	that	SCONJ
fcis-26112	114	12	maturity	maturity	NOUN
fcis-26112	114	13	and	and	CCONJ
fcis-26112	114	14	strikeprice	strikeprice	NOUN
fcis-26112	114	15	significantly	significantly	ADV
fcis-26112	114	16	affect	affect	VERB
fcis-26112	114	17	it	it	PRON
fcis-26112	114	18	,	,	PUNCT
fcis-26112	114	19	for	for	ADP
fcis-26112	114	20	example	example	NOUN
fcis-26112	115	1	[	[	X
fcis-26112	115	2	17	17	NUM
fcis-26112	115	3	]	]	PUNCT
fcis-26112	115	4	.	.	PUNCT
fcis-26112	116	1	additionally	additionally	ADV
fcis-26112	116	2	,	,	PUNCT
fcis-26112	116	3	preliminary	preliminary	ADJ
fcis-26112	116	4	analysis	analysis	NOUN
fcis-26112	116	5	of	of	ADP
fcis-26112	116	6	historical	historical	ADJ
fcis-26112	116	7	data	datum	NOUN
fcis-26112	116	8	revealed	reveal	VERB
fcis-26112	116	9	that	that	SCONJ
fcis-26112	116	10	these	these	DET
fcis-26112	116	11	features	feature	NOUN
fcis-26112	116	12	are	be	AUX
fcis-26112	116	13	highly	highly	ADV
fcis-26112	116	14	correlated	correlate	VERB
fcis-26112	116	15	with	with	ADP
fcis-26112	116	16	implied	imply	VERB
fcis-26112	116	17	volatility	volatility	NOUN
fcis-26112	116	18	.	.	PUNCT
fcis-26112	117	1	when	when	SCONJ
fcis-26112	117	2	using	use	VERB
fcis-26112	117	3	these	these	DET
fcis-26112	117	4	features	feature	NOUN
fcis-26112	117	5	for	for	ADP
fcis-26112	117	6	training	training	NOUN
fcis-26112	117	7	regression	regression	NOUN
fcis-26112	117	8	models	model	NOUN
fcis-26112	117	9	,	,	PUNCT
fcis-26112	117	10	the	the	DET
fcis-26112	117	11	model	model	NOUN
fcis-26112	117	12	performance	performance	NOUN
fcis-26112	117	13	significantly	significantly	ADV
fcis-26112	117	14	outperforms	outperform	VERB
fcis-26112	117	15	the	the	DET
fcis-26112	117	16	cases	case	NOUN
fcis-26112	117	17	without	without	ADP
fcis-26112	117	18	these	these	DET
fcis-26112	117	19	features	feature	NOUN
fcis-26112	117	20	.	.	PUNCT
fcis-26112	118	1	therefore	therefore	ADV
fcis-26112	118	2	,	,	PUNCT
fcis-26112	118	3	selecting	select	VERB
fcis-26112	118	4	these	these	DET
fcis-26112	118	5	features	feature	NOUN
fcis-26112	118	6	is	be	AUX
fcis-26112	118	7	not	not	PART
fcis-26112	118	8	only	only	ADV
fcis-26112	118	9	theoretically	theoretically	ADV
fcis-26112	118	10	sound	sound	ADJ
fcis-26112	118	11	but	but	CCONJ
fcis-26112	118	12	also	also	ADV
fcis-26112	118	13	empirically	empirically	ADV
fcis-26112	118	14	validated	validate	VERB
fcis-26112	118	15	.	.	PUNCT
fcis-26112	119	1	even	even	ADV
fcis-26112	119	2	for	for	ADP
fcis-26112	119	3	the	the	DET
fcis-26112	119	4	same	same	ADJ
fcis-26112	119	5	option	option	NOUN
fcis-26112	119	6	contract	contract	NOUN
fcis-26112	119	7	,	,	PUNCT
fcis-26112	119	8	trading	trading	NOUN
fcis-26112	119	9	prices	price	NOUN
fcis-26112	119	10	on	on	ADP
fcis-26112	119	11	the	the	DET
fcis-26112	119	12	same	same	ADJ
fcis-26112	119	13	day	day	NOUN
fcis-26112	119	14	can	can	AUX
fcis-26112	119	15	vary	vary	VERB
fcis-26112	119	16	.	.	PUNCT
fcis-26112	120	1	therefore	therefore	ADV
fcis-26112	120	2	,	,	PUNCT
fcis-26112	120	3	we	we	PRON
fcis-26112	120	4	define	define	VERB
fcis-26112	120	5	the	the	DET
fcis-26112	120	6	weighted	weighted	ADJ
fcis-26112	120	7	midprice	midprice	NOUN
fcis-26112	120	8	(	(	PUNCT
fcis-26112	120	9	also	also	ADV
fcis-26112	120	10	known	know	VERB
fcis-26112	120	11	as	as	ADP
fcis-26112	120	12	micro	micro	NOUN
fcis-26112	120	13	-	-	NOUN
fcis-26112	120	14	price	price	NOUN
fcis-26112	120	15	)	)	PUNCT
fcis-26112	120	16	to	to	PART
fcis-26112	120	17	describe	describe	VERB
fcis-26112	120	18	the	the	DET
fcis-26112	120	19	actual	actual	ADJ
fcis-26112	120	20	value	value	NOUN
fcis-26112	120	21	of	of	ADP
fcis-26112	120	22	the	the	DET
fcis-26112	120	23	option	option	NOUN
fcis-26112	120	24	on	on	ADP
fcis-26112	120	25	that	that	DET
fcis-26112	120	26	day	day	NOUN
fcis-26112	120	27	,	,	PUNCT
fcis-26112	120	28	∗	∗	NOUN
fcis-26112	120	29	∗	∗	NOUN
fcis-26112	120	30	(	(	PUNCT
fcis-26112	120	31	7	7	NUM
fcis-26112	120	32	)	)	PUNCT
fcis-26112	120	33	the	the	DET
fcis-26112	120	34	typical	typical	ADJ
fcis-26112	120	35	interpretation	interpretation	NOUN
fcis-26112	120	36	of	of	ADP
fcis-26112	120	37	formula	formula	NOUN
fcis-26112	120	38	(	(	PUNCT
fcis-26112	120	39	7	7	X
fcis-26112	120	40	)	)	PUNCT
fcis-26112	120	41	is	be	AUX
fcis-26112	120	42	that	that	SCONJ
fcis-26112	120	43	if	if	SCONJ
fcis-26112	120	44	the	the	DET
fcis-26112	120	45	number	number	NOUN
fcis-26112	120	46	of	of	ADP
fcis-26112	120	47	bids	bid	NOUN
fcis-26112	120	48	for	for	ADP
fcis-26112	120	49	an	an	DET
fcis-26112	120	50	option	option	NOUN
fcis-26112	120	51	exceeds	exceed	VERB
fcis-26112	120	52	the	the	DET
fcis-26112	120	53	number	number	NOUN
fcis-26112	120	54	of	of	ADP
fcis-26112	120	55	asks	ask	NOUN
fcis-26112	120	56	,	,	PUNCT
fcis-26112	120	57	it	it	PRON
fcis-26112	120	58	indicates	indicate	VERB
fcis-26112	120	59	greater	great	ADJ
fcis-26112	120	60	buying	buying	NOUN
fcis-26112	120	61	pressure	pressure	NOUN
fcis-26112	120	62	,	,	PUNCT
fcis-26112	120	63	thus	thus	ADV
fcis-26112	120	64	the	the	DET
fcis-26112	120	65	"	"	PUNCT
fcis-26112	120	66	true	true	ADJ
fcis-26112	120	67	"	"	PUNCT
fcis-26112	120	68	price	price	NOUN
fcis-26112	120	69	is	be	AUX
fcis-26112	120	70	closer	close	ADJ
fcis-26112	120	71	to	to	ADP
fcis-26112	120	72	the	the	DET
fcis-26112	120	73	ask	ask	NOUN
fcis-26112	120	74	price	price	NOUN
fcis-26112	120	75	rather	rather	ADV
fcis-26112	120	76	than	than	ADP
fcis-26112	120	77	the	the	DET
fcis-26112	120	78	bid	bid	NOUN
fcis-26112	120	79	price	price	NOUN
fcis-26112	120	80	.	.	PUNCT
fcis-26112	121	1	the	the	DET
fcis-26112	121	2	weighted	weight	VERB
fcis-26112	121	3	midprice	midprice	NOUN
fcis-26112	121	4	not	not	PART
fcis-26112	121	5	only	only	ADV
fcis-26112	121	6	takes	take	VERB
fcis-26112	121	7	into	into	ADP
fcis-26112	121	8	account	account	NOUN
fcis-26112	121	9	the	the	DET
fcis-26112	121	10	prices	price	NOUN
fcis-26112	121	11	of	of	ADP
fcis-26112	121	12	the	the	DET
fcis-26112	121	13	bid	bid	NOUN
fcis-26112	121	14	and	and	CCONJ
fcis-26112	121	15	ask	ask	VERB
fcis-26112	121	16	but	but	CCONJ
fcis-26112	121	17	also	also	ADV
fcis-26112	121	18	considers	consider	VERB
fcis-26112	121	19	the	the	DET
fcis-26112	121	20	imbalance	imbalance	NOUN
fcis-26112	121	21	in	in	ADP
fcis-26112	121	22	the	the	DET
fcis-26112	121	23	number	number	NOUN
fcis-26112	121	24	of	of	ADP
fcis-26112	121	25	bids	bid	NOUN
fcis-26112	121	26	and	and	CCONJ
fcis-26112	121	27	asks	ask	VERB
fcis-26112	121	28	,	,	PUNCT
fcis-26112	121	29	providing	provide	VERB
fcis-26112	121	30	a	a	DET
fcis-26112	121	31	more	more	ADV
fcis-26112	121	32	accurate	accurate	ADJ
fcis-26112	121	33	market	market	NOUN
fcis-26112	121	34	price	price	NOUN
fcis-26112	121	35	than	than	ADP
fcis-26112	121	36	the	the	DET
fcis-26112	121	37	mid	mid	NOUN
fcis-26112	121	38	-	-	NOUN
fcis-26112	121	39	price	price	NOUN
fcis-26112	121	40	.	.	PUNCT
fcis-26112	122	1	this	this	DET
fcis-26112	122	2	method	method	NOUN
fcis-26112	122	3	has	have	AUX
fcis-26112	122	4	been	be	AUX
fcis-26112	122	5	widely	widely	ADV
fcis-26112	122	6	applied	apply	VERB
fcis-26112	122	7	[	[	PUNCT
fcis-26112	122	8	18	18	NUM
fcis-26112	122	9	]	]	PUNCT
fcis-26112	122	10	.	.	PUNCT
fcis-26112	123	1	for	for	ADP
fcis-26112	123	2	options	option	NOUN
fcis-26112	123	3	that	that	PRON
fcis-26112	123	4	are	be	AUX
fcis-26112	123	5	not	not	PART
fcis-26112	123	6	bidded	bidde	VERB
fcis-26112	123	7	or	or	CCONJ
fcis-26112	123	8	asked	ask	VERB
fcis-26112	123	9	that	that	DET
fcis-26112	123	10	day	day	NOUN
fcis-26112	123	11	,	,	PUNCT
fcis-26112	123	12	we	we	PRON
fcis-26112	123	13	use	use	VERB
fcis-26112	123	14	lastprice	lastprice	NOUN
fcis-26112	123	15	for	for	ADP
fcis-26112	123	16	valuation	valuation	NOUN
fcis-26112	123	17	:	:	PUNCT
fcis-26112	123	18	,	,	PUNCT
fcis-26112	123	19	0	0	NUM
fcis-26112	123	20	(	(	PUNCT
fcis-26112	123	21	8)	8)	NUM
fcis-26112	123	22	,	,	PUNCT
fcis-26112	123	23	0	0	NUM
fcis-26112	123	24	(	(	PUNCT
fcis-26112	123	25	9	9	NUM
fcis-26112	123	26	)	)	PUNCT
fcis-26112	123	27	,	,	PUNCT
fcis-26112	123	28	0	0	NUM
fcis-26112	123	29	0	0	NUM
fcis-26112	123	30	(	(	PUNCT
fcis-26112	123	31	10	10	NUM
fcis-26112	123	32	)	)	PUNCT
fcis-26112	123	33	3.2	3.2	NUM
fcis-26112	123	34	.	.	PUNCT
fcis-26112	124	1	experiment	experiment	NOUN
fcis-26112	124	2	setting	set	VERB
fcis-26112	124	3	we	we	PRON
fcis-26112	124	4	used	use	VERB
fcis-26112	124	5	spx	spx	PROPN
fcis-26112	124	6	information	information	NOUN
fcis-26112	124	7	from	from	ADP
fcis-26112	124	8	november	november	PROPN
fcis-26112	124	9	1	1	NUM
fcis-26112	124	10	,	,	PUNCT
fcis-26112	124	11	2023	2023	NUM
fcis-26112	124	12	,	,	PUNCT
fcis-26112	124	13	to	to	ADP
fcis-26112	124	14	december	december	PROPN
fcis-26112	124	15	28	28	NUM
fcis-26112	124	16	,	,	PUNCT
fcis-26112	124	17	2023	2023	NUM
fcis-26112	124	18	,	,	PUNCT
fcis-26112	124	19	as	as	ADP
fcis-26112	124	20	the	the	DET
fcis-26112	124	21	dataset	dataset	NOUN
fcis-26112	124	22	,	,	PUNCT
fcis-26112	124	23	with	with	ADP
fcis-26112	124	24	80	80	NUM
fcis-26112	124	25	%	%	NOUN
fcis-26112	124	26	of	of	ADP
fcis-26112	124	27	it	it	PRON
fcis-26112	124	28	used	use	VERB
fcis-26112	124	29	as	as	ADP
fcis-26112	124	30	the	the	DET
fcis-26112	124	31	training	training	NOUN
fcis-26112	124	32	set	set	NOUN
fcis-26112	124	33	and	and	CCONJ
fcis-26112	124	34	20	20	NUM
fcis-26112	124	35	%	%	NOUN
fcis-26112	124	36	as	as	ADP
fcis-26112	124	37	the	the	DET
fcis-26112	124	38	validation	validation	NOUN
fcis-26112	124	39	set	set	NOUN
fcis-26112	124	40	,	,	PUNCT
fcis-26112	124	41	and	and	CCONJ
fcis-26112	124	42	the	the	DET
fcis-26112	124	43	data	datum	NOUN
fcis-26112	124	44	from	from	ADP
fcis-26112	124	45	december	december	PROPN
fcis-26112	124	46	29	29	NUM
fcis-26112	124	47	,	,	PUNCT
fcis-26112	124	48	2023	2023	NUM
fcis-26112	124	49	,	,	PUNCT
fcis-26112	124	50	as	as	ADP
fcis-26112	124	51	the	the	DET
fcis-26112	124	52	final	final	ADJ
fcis-26112	124	53	test	test	NOUN
fcis-26112	124	54	set	set	NOUN
fcis-26112	124	55	.	.	PUNCT
fcis-26112	125	1	figure	figure	NOUN
fcis-26112	125	2	7	7	NUM
fcis-26112	125	3	shows	show	VERB
fcis-26112	125	4	the	the	DET
fcis-26112	125	5	oob	oob	NOUN
fcis-26112	125	6	error	error	NOUN
fcis-26112	125	7	of	of	ADP
fcis-26112	125	8	the	the	DET
fcis-26112	125	9	random	random	ADJ
fcis-26112	125	10	forest	forest	NOUN
fcis-26112	125	11	algorithm	algorithm	NOUN
fcis-26112	125	12	as	as	ADP
fcis-26112	125	13	the	the	DET
fcis-26112	125	14	number	number	NOUN
fcis-26112	125	15	of	of	ADP
fcis-26112	125	16	trees	tree	NOUN
fcis-26112	125	17	changes	change	NOUN
fcis-26112	125	18	.	.	PUNCT
fcis-26112	126	1	figure	figure	NOUN
fcis-26112	126	2	8	8	NUM
fcis-26112	126	3	is	be	AUX
fcis-26112	126	4	a	a	DET
fcis-26112	126	5	heatmap	heatmap	NOUN
fcis-26112	126	6	of	of	ADP
fcis-26112	126	7	the	the	DET
fcis-26112	126	8	svr	svr	PROPN
fcis-26112	126	9	algorithm	algorithm	PROPN
fcis-26112	126	10	's	's	PART
fcis-26112	126	11	cross	cross	ADJ
fcis-26112	126	12	-	-	ADJ
fcis-26112	126	13	validation	validation	ADJ
fcis-26112	126	14	loss	loss	NOUN
fcis-26112	126	15	versus	versus	X
fcis-26112	126	16	(	(	PUNCT
fcis-26112	126	17	c	c	NOUN
fcis-26112	126	18	,	,	PUNCT
fcis-26112	126	19	epsilon	epsilon	PROPN
fcis-26112	126	20	)	)	PUNCT
fcis-26112	126	21	parameter	parameter	NOUN
fcis-26112	126	22	pairs	pair	NOUN
fcis-26112	126	23	.	.	PUNCT
fcis-26112	127	1	the	the	DET
fcis-26112	127	2	optimal	optimal	ADJ
fcis-26112	127	3	parameters	parameter	NOUN
fcis-26112	127	4	determined	determine	VERB
fcis-26112	127	5	from	from	ADP
fcis-26112	127	6	the	the	DET
fcis-26112	127	7	images	image	NOUN
fcis-26112	127	8	are	be	AUX
fcis-26112	127	9	shown	show	VERB
fcis-26112	127	10	in	in	ADP
fcis-26112	127	11	table	table	NOUN
fcis-26112	127	12	2	2	NUM
fcis-26112	127	13	.	.	PUNCT
fcis-26112	127	14	figures	figure	NOUN
fcis-26112	127	15	9	9	NUM
fcis-26112	127	16	and	and	CCONJ
fcis-26112	127	17	10	10	NUM
fcis-26112	127	18	show	show	VERB
fcis-26112	127	19	the	the	DET
fcis-26112	127	20	loss	loss	NOUN
fcis-26112	127	21	changes	change	NOUN
fcis-26112	127	22	with	with	ADP
fcis-26112	127	23	epochs	epoch	NOUN
fcis-26112	127	24	during	during	ADP
fcis-26112	127	25	cross	cross	NOUN
fcis-26112	127	26	-	-	NOUN
fcis-26112	127	27	validation	validation	NOUN
fcis-26112	127	28	for	for	ADP
fcis-26112	127	29	un	un	ADJ
fcis-26112	127	30	-	-	ADJ
fcis-26112	127	31	pre	pre	ADJ
fcis-26112	127	32	-	-	ADJ
fcis-26112	127	33	trained	train	VERB
fcis-26112	127	34	resnet-50	resnet-50	PROPN
fcis-26112	127	35	and	and	CCONJ
fcis-26112	127	36	pre	pre	ADJ
fcis-26112	127	37	-	-	ADJ
fcis-26112	127	38	trained	train	VERB
fcis-26112	127	39	resnet-50	resnet-50	PROPN
fcis-26112	127	40	(	(	PUNCT
fcis-26112	127	41	learning	learn	VERB
fcis-26112	127	42	rate=0.001	rate=0.001	NOUN
fcis-26112	127	43	)	)	PUNCT
fcis-26112	127	44	.	.	PUNCT
fcis-26112	128	1	it	it	PRON
fcis-26112	128	2	can	can	AUX
fcis-26112	128	3	be	be	AUX
fcis-26112	128	4	seen	see	VERB
fcis-26112	128	5	that	that	SCONJ
fcis-26112	128	6	the	the	DET
fcis-26112	128	7	loss	loss	NOUN
fcis-26112	128	8	for	for	ADP
fcis-26112	128	9	un	un	ADJ
fcis-26112	128	10	-	-	ADJ
fcis-26112	128	11	pre	pre	ADJ
fcis-26112	128	12	-	-	ADJ
fcis-26112	128	13	trained	train	VERB
fcis-26112	128	14	resnet-50	resnet-50	PROPN
fcis-26112	128	15	almost	almost	ADV
fcis-26112	128	16	stops	stop	VERB
fcis-26112	128	17	decreasing	decrease	VERB
fcis-26112	128	18	at	at	ADP
fcis-26112	128	19	epoch	epoch	NOUN
fcis-26112	128	20	10	10	NUM
fcis-26112	128	21	,	,	PUNCT
fcis-26112	128	22	while	while	SCONJ
fcis-26112	128	23	pre	pre	ADJ
fcis-26112	128	24	-	-	ADJ
fcis-26112	128	25	trained	train	VERB
fcis-26112	128	26	resnet-50	resnet-50	PROPN
fcis-26112	128	27	requires	require	VERB
fcis-26112	128	28	epoch	epoch	NOUN
fcis-26112	128	29	50	50	NUM
fcis-26112	128	30	.	.	PUNCT
fcis-26112	129	1	the	the	DET
fcis-26112	129	2	final	final	ADJ
fcis-26112	129	3	optimal	optimal	ADJ
fcis-26112	129	4	parameters	parameter	NOUN
fcis-26112	129	5	are	be	AUX
fcis-26112	129	6	shown	show	VERB
fcis-26112	129	7	in	in	ADP
fcis-26112	129	8	table	table	NOUN
fcis-26112	129	9	3	3	NUM
fcis-26112	129	10	.	.	NOUN
fcis-26112	129	11	3.3	3.3	NUM
fcis-26112	129	12	.	.	PUNCT
fcis-26112	130	1	results	result	NOUN
fcis-26112	130	2	after	after	ADP
fcis-26112	130	3	training	train	VERB
fcis-26112	130	4	the	the	DET
fcis-26112	130	5	model	model	NOUN
fcis-26112	130	6	with	with	ADP
fcis-26112	130	7	the	the	DET
fcis-26112	130	8	optimized	optimize	VERB
fcis-26112	130	9	parameters	parameter	NOUN
fcis-26112	130	10	from	from	ADP
fcis-26112	130	11	the	the	DET
fcis-26112	130	12	previous	previous	ADJ
fcis-26112	130	13	section	section	NOUN
fcis-26112	130	14	,	,	PUNCT
fcis-26112	130	15	we	we	PRON
fcis-26112	130	16	make	make	VERB
fcis-26112	130	17	predictions	prediction	NOUN
fcis-26112	130	18	on	on	ADP
fcis-26112	130	19	the	the	DET
fcis-26112	130	20	final	final	ADJ
fcis-26112	130	21	test	test	NOUN
fcis-26112	130	22	set	set	NOUN
fcis-26112	130	23	.	.	PUNCT
fcis-26112	131	1	by	by	ADP
fcis-26112	131	2	substituting	substitute	VERB
fcis-26112	131	3	the	the	DET
fcis-26112	131	4	predicted	predict	VERB
fcis-26112	131	5	implied	imply	VERB
fcis-26112	131	6	volatility	volatility	NOUN
fcis-26112	131	7	into	into	ADP
fcis-26112	131	8	the	the	DET
fcis-26112	131	9	bsopm	bsopm	NOUN
fcis-26112	131	10	formula	formula	NOUN
fcis-26112	131	11	(	(	PUNCT
fcis-26112	131	12	1	1	NUM
fcis-26112	131	13	)	)	PUNCT
fcis-26112	131	14	,	,	PUNCT
fcis-26112	131	15	we	we	PRON
fcis-26112	131	16	obtain	obtain	VERB
fcis-26112	131	17	the	the	DET
fcis-26112	131	18	final	final	ADJ
fcis-26112	131	19	option	option	NOUN
fcis-26112	131	20	price	price	NOUN
fcis-26112	131	21	prediction	prediction	NOUN
fcis-26112	131	22	.	.	PUNCT
fcis-26112	132	1	the	the	DET
fcis-26112	132	2	comparison	comparison	NOUN
fcis-26112	132	3	of	of	ADP
fcis-26112	132	4	prediction	prediction	NOUN
fcis-26112	132	5	errors	error	NOUN
fcis-26112	132	6	among	among	ADP
fcis-26112	132	7	different	different	ADJ
fcis-26112	132	8	models	model	NOUN
fcis-26112	132	9	is	be	AUX
fcis-26112	132	10	shown	show	VERB
fcis-26112	132	11	in	in	ADP
fcis-26112	132	12	table	table	NOUN
fcis-26112	132	13	4	4	NUM
fcis-26112	132	14	.	.	PUNCT
fcis-26112	133	1	it	it	PRON
fcis-26112	133	2	is	be	AUX
fcis-26112	133	3	evident	evident	ADJ
fcis-26112	133	4	that	that	SCONJ
fcis-26112	133	5	the	the	DET
fcis-26112	133	6	pre	pre	ADJ
fcis-26112	133	7	-	-	ADJ
fcis-26112	133	8	trained	train	VERB
fcis-26112	133	9	resnet-50	resnet-50	PROPN
fcis-26112	133	10	has	have	VERB
fcis-26112	133	11	the	the	DET
fcis-26112	133	12	smallest	small	ADJ
fcis-26112	133	13	rmse	rmse	NOUN
fcis-26112	133	14	and	and	CCONJ
fcis-26112	133	15	r²	r²	NOUN
fcis-26112	133	16	,	,	PUNCT
fcis-26112	133	17	indicating	indicate	VERB
fcis-26112	133	18	the	the	DET
fcis-26112	133	19	best	good	ADJ
fcis-26112	133	20	performance	performance	NOUN
fcis-26112	133	21	.	.	PUNCT
fcis-26112	134	1	the	the	DET
fcis-26112	134	2	scatter	scatter	NOUN
fcis-26112	134	3	plot	plot	NOUN
fcis-26112	134	4	of	of	ADP
fcis-26112	134	5	the	the	DET
fcis-26112	134	6	prediction	prediction	NOUN
fcis-26112	134	7	results	result	VERB
fcis-26112	134	8	from	from	ADP
fcis-26112	134	9	the	the	DET
fcis-26112	134	10	pre	pre	ADJ
fcis-26112	134	11	-	-	ADJ
fcis-26112	134	12	trained	train	VERB
fcis-26112	134	13	resnet-50	resnet-50	PROPN
fcis-26112	134	14	is	be	AUX
fcis-26112	134	15	shown	show	VERB
fcis-26112	134	16	in	in	ADP
fcis-26112	134	17	fig	fig	NOUN
fcis-26112	134	18	.	.	PUNCT
fcis-26112	135	1	11	11	NUM
fcis-26112	135	2	,	,	PUNCT
fcis-26112	135	3	where	where	SCONJ
fcis-26112	135	4	the	the	DET
fcis-26112	135	5	scatter	scatter	NOUN
fcis-26112	135	6	distribution	distribution	NOUN
fcis-26112	135	7	close	close	ADV
fcis-26112	135	8	to	to	ADP
fcis-26112	135	9	y	y	PROPN
fcis-26112	135	10	=	=	PUNCT
fcis-26112	135	11	x	x	NOUN
fcis-26112	135	12	indicates	indicate	VERB
fcis-26112	135	13	that	that	SCONJ
fcis-26112	135	14	the	the	DET
fcis-26112	135	15	predicted	predict	VERB
fcis-26112	135	16	values	value	NOUN
fcis-26112	135	17	are	be	AUX
fcis-26112	135	18	close	close	ADJ
fcis-26112	135	19	to	to	ADP
fcis-26112	135	20	the	the	DET
fcis-26112	135	21	actual	actual	ADJ
fcis-26112	135	22	values	value	NOUN
fcis-26112	135	23	.	.	PUNCT
fcis-26112	136	1	the	the	DET
fcis-26112	136	2	prediction	prediction	NOUN
fcis-26112	136	3	result	result	NOUN
fcis-26112	136	4	data	datum	NOUN
fcis-26112	136	5	is	be	AUX
fcis-26112	136	6	presented	present	VERB
fcis-26112	136	7	in	in	ADP
fcis-26112	136	8	the	the	DET
fcis-26112	136	9	table	table	NOUN
fcis-26112	136	10	5	5	NUM
fcis-26112	136	11	.	.	SYM
fcis-26112	136	12	13	13	NUM
fcis-26112	136	13	figure	figure	NOUN
fcis-26112	136	14	6	6	NUM
fcis-26112	136	15	.	.	PUNCT
fcis-26112	136	16	architecture	architecture	NOUN
fcis-26112	136	17	of	of	ADP
fcis-26112	136	18	predicting	predict	VERB
fcis-26112	136	19	option	option	NOUN
fcis-26112	136	20	price	price	NOUN
fcis-26112	136	21	and	and	CCONJ
fcis-26112	136	22	comparing	compare	VERB
fcis-26112	136	23	the	the	DET
fcis-26112	136	24	models	model	NOUN
fcis-26112	136	25	figure	figure	VERB
fcis-26112	136	26	7	7	NUM
fcis-26112	136	27	.	.	PUNCT
fcis-26112	136	28	oob	oob	NOUN
fcis-26112	136	29	errorn_estimators	errorn_estimator	NOUN
fcis-26112	136	30	line	line	NOUN
fcis-26112	136	31	chart	chart	NOUN
fcis-26112	136	32	for	for	ADP
fcis-26112	136	33	random	random	ADJ
fcis-26112	136	34	forest	forest	NOUN
fcis-26112	136	35	figure	figure	NOUN
fcis-26112	136	36	8	8	NUM
fcis-26112	136	37	.	.	PUNCT
fcis-26112	137	1	heatmap	heatmap	NOUN
fcis-26112	137	2	of	of	ADP
fcis-26112	137	3	cross	cross	ADJ
fcis-26112	137	4	-	-	ADJ
fcis-26112	137	5	validation	validation	ADJ
fcis-26112	137	6	loss	loss	NOUN
fcis-26112	137	7	with	with	ADP
fcis-26112	137	8	(	(	PUNCT
fcis-26112	137	9	c	c	NOUN
fcis-26112	137	10	,	,	PUNCT
fcis-26112	137	11	epsilon	epsilon	PROPN
fcis-26112	137	12	)	)	PUNCT
fcis-26112	137	13	parameter	parameter	NOUN
fcis-26112	137	14	combinations	combination	NOUN
fcis-26112	137	15	for	for	ADP
fcis-26112	137	16	svr	svr	PROPN
fcis-26112	137	17	table	table	NOUN
fcis-26112	137	18	2	2	NUM
fcis-26112	137	19	.	.	PUNCT
fcis-26112	137	20	optimized	optimize	VERB
fcis-26112	137	21	parameters	parameter	NOUN
fcis-26112	137	22	of	of	ADP
fcis-26112	137	23	random	random	ADJ
fcis-26112	137	24	forest	forest	NOUN
fcis-26112	137	25	and	and	CCONJ
fcis-26112	137	26	svr	svr	PROPN
fcis-26112	137	27	optimized	optimize	VERB
fcis-26112	137	28	parameters	parameter	NOUN
fcis-26112	137	29	of	of	ADP
fcis-26112	137	30	random	random	ADJ
fcis-26112	137	31	forest	forest	NOUN
fcis-26112	137	32	optimized	optimize	VERB
fcis-26112	137	33	parameters	parameter	NOUN
fcis-26112	137	34	of	of	ADP
fcis-26112	137	35	svr	svr	PROPN
fcis-26112	137	36	n_estimators	n_estimator	NOUN
fcis-26112	137	37	800	800	NUM
fcis-26112	137	38	c	c	NOUN
fcis-26112	137	39	100	100	NUM
fcis-26112	137	40	max_depth	max_depth	NOUN
fcis-26112	137	41	1000	1000	NUM
fcis-26112	137	42	epsilon	epsilon	PROPN
fcis-26112	137	43	0.001	0.001	NUM
fcis-26112	137	44	min_samples_split	min_samples_split	ADJ
fcis-26112	137	45	50	50	NUM
fcis-26112	137	46	gamma	gamma	NOUN
fcis-26112	137	47	scale	scale	NOUN
fcis-26112	137	48	min_samples_leaf	min_samples_leaf	ADJ
fcis-26112	137	49	20	20	NUM
fcis-26112	137	50	kernel	kernel	PROPN
fcis-26112	137	51	rbf	rbf	PROPN
fcis-26112	137	52	figure	figure	NOUN
fcis-26112	137	53	9	9	NUM
fcis-26112	137	54	.	.	PUNCT
fcis-26112	138	1	line	line	NOUN
fcis-26112	138	2	chart	chart	NOUN
fcis-26112	138	3	of	of	ADP
fcis-26112	138	4	loss	loss	NOUN
fcis-26112	138	5	-	-	PUNCT
fcis-26112	138	6	epochs	epoch	NOUN
fcis-26112	138	7	for	for	ADP
fcis-26112	138	8	un	un	ADJ
fcis-26112	138	9	-	-	ADJ
fcis-26112	138	10	pre	pre	ADJ
fcis-26112	138	11	-	-	ADJ
fcis-26112	138	12	trained	train	VERB
fcis-26112	138	13	resnet-50	resnet-50	PROPN
fcis-26112	138	14	figure	figure	NOUN
fcis-26112	138	15	10	10	NUM
fcis-26112	138	16	.	.	PUNCT
fcis-26112	139	1	line	line	NOUN
fcis-26112	139	2	chart	chart	NOUN
fcis-26112	139	3	of	of	ADP
fcis-26112	139	4	loss	loss	NOUN
fcis-26112	139	5	-	-	PUNCT
fcis-26112	139	6	epochs	epoch	NOUN
fcis-26112	139	7	for	for	ADP
fcis-26112	139	8	pre	pre	ADJ
fcis-26112	139	9	-	-	ADJ
fcis-26112	139	10	trained	train	VERB
fcis-26112	139	11	resnet-50	resnet-50	PROPN
fcis-26112	139	12	table	table	NOUN
fcis-26112	139	13	3	3	NUM
fcis-26112	139	14	.	.	PUNCT
fcis-26112	139	15	optimized	optimize	VERB
fcis-26112	139	16	parameters	parameter	NOUN
fcis-26112	139	17	of	of	ADP
fcis-26112	139	18	un	un	ADJ
fcis-26112	139	19	-	-	ADJ
fcis-26112	139	20	pre	pre	ADJ
fcis-26112	139	21	-	-	ADJ
fcis-26112	139	22	trained/	trained/	NUM
fcis-26112	139	23	pre	pre	ADJ
fcis-26112	139	24	-	-	ADJ
fcis-26112	139	25	trained	train	VERB
fcis-26112	139	26	resnet-50	resnet-50	PROPN
fcis-26112	139	27	optimized	optimize	VERB
fcis-26112	139	28	parameters	parameter	NOUN
fcis-26112	139	29	un	un	ADJ
fcis-26112	139	30	-	-	ADJ
fcis-26112	139	31	pre	pre	ADJ
fcis-26112	139	32	-	-	ADJ
fcis-26112	139	33	trained	train	VERB
fcis-26112	139	34	resnet-50	resnet-50	PROPN
fcis-26112	139	35	pre	pre	ADJ
fcis-26112	139	36	-	-	ADJ
fcis-26112	139	37	training	training	ADJ
fcis-26112	139	38	resnet-50	resnet-50	PROPN
fcis-26112	139	39	epoch	epoch	NOUN
fcis-26112	139	40	10	10	NUM
fcis-26112	139	41	50	50	NUM
fcis-26112	139	42	learning	learning	NOUN
fcis-26112	139	43	rate	rate	NOUN
fcis-26112	139	44	0.001	0.001	NUM
fcis-26112	139	45	0.001	0.001	NUM
fcis-26112	139	46	rmse	rmse	NOUN
fcis-26112	139	47	in	in	ADP
fcis-26112	139	48	crossvalidation	crossvalidation	NOUN
fcis-26112	139	49	0.0130	0.0130	NUM
fcis-26112	139	50	0.0071	0.0071	NUM
fcis-26112	139	51	table	table	NOUN
fcis-26112	139	52	4	4	NUM
fcis-26112	139	53	.	.	PUNCT
fcis-26112	139	54	error	error	NOUN
fcis-26112	139	55	in	in	ADP
fcis-26112	139	56	the	the	DET
fcis-26112	139	57	prediction	prediction	NOUN
fcis-26112	139	58	results	result	NOUN
fcis-26112	139	59	of	of	ADP
fcis-26112	139	60	four	four	NUM
fcis-26112	139	61	models	model	NOUN
fcis-26112	139	62	.	.	PUNCT
fcis-26112	140	1	model	model	NOUN
fcis-26112	140	2	rmse	rmse	PROPN
fcis-26112	140	3	r2	r2	PROPN
fcis-26112	140	4	random	random	PROPN
fcis-26112	140	5	forest	forest	NOUN
fcis-26112	140	6	126.83811132344044	126.83811132344044	NUM
fcis-26112	140	7	0.9191872682241727	0.9191872682241727	NUM
fcis-26112	140	8	svr	svr	PROPN
fcis-26112	140	9	126.57465092687552	126.57465092687552	NUM
fcis-26112	140	10	0.9195226381221107	0.9195226381221107	NUM
fcis-26112	140	11	un	un	ADJ
fcis-26112	140	12	-	-	ADJ
fcis-26112	140	13	pretrained	pretraine	VERB
fcis-26112	140	14	resnet-50	resnet-50	PROPN
fcis-26112	140	15	66.26175925800771	66.26175925800771	NUM
fcis-26112	140	16	0.9779325065386534	0.9779325065386534	NUM
fcis-26112	140	17	pre	pre	ADJ
fcis-26112	140	18	-	-	ADJ
fcis-26112	140	19	trained	train	VERB
fcis-26112	140	20	resnet-50	resnet-50	PROPN
fcis-26112	140	21	61.878718575051955	61.878718575051955	NUM
fcis-26112	140	22	0.9807662982367042	0.9807662982367042	NUM
fcis-26112	140	23	4	4	NUM
fcis-26112	140	24	.	.	PUNCT
fcis-26112	140	25	discussion	discussion	NOUN
fcis-26112	140	26	and	and	CCONJ
fcis-26112	140	27	future	future	ADJ
fcis-26112	140	28	work	work	NOUN
fcis-26112	140	29	from	from	ADP
fcis-26112	140	30	the	the	DET
fcis-26112	140	31	comparison	comparison	NOUN
fcis-26112	140	32	of	of	ADP
fcis-26112	140	33	rmse	rmse	NOUN
fcis-26112	140	34	,	,	PUNCT
fcis-26112	140	35	pre	pre	ADJ
fcis-26112	140	36	-	-	ADJ
fcis-26112	140	37	trained	train	VERB
fcis-26112	140	38	resnet-50	resnet-50	PROPN
fcis-26112	140	39	improved	improve	VERB
fcis-26112	140	40	by	by	ADP
fcis-26112	140	41	51.2	51.2	NUM
fcis-26112	140	42	%	%	NOUN
fcis-26112	140	43	compared	compare	VERB
fcis-26112	140	44	to	to	ADP
fcis-26112	140	45	random	random	ADJ
fcis-26112	140	46	forest	forest	NOUN
fcis-26112	140	47	,	,	PUNCT
fcis-26112	140	48	by	by	ADP
fcis-26112	140	49	51.1	51.1	NUM
fcis-26112	140	50	%	%	NOUN
fcis-26112	140	51	compared	compare	VERB
fcis-26112	140	52	to	to	ADP
fcis-26112	140	53	svr	svr	PROPN
fcis-26112	140	54	,	,	PUNCT
fcis-26112	140	55	and	and	CCONJ
fcis-26112	140	56	by	by	ADP
fcis-26112	140	57	6	6	NUM
fcis-26112	140	58	%	%	NOUN
fcis-26112	140	59	compared	compare	VERB
fcis-26112	140	60	to	to	ADP
fcis-26112	140	61	un	un	ADJ
fcis-26112	140	62	-	-	ADJ
fcis-26112	140	63	pre	pre	ADJ
fcis-26112	140	64	-	-	ADJ
fcis-26112	140	65	trained	train	VERB
fcis-26112	140	66	resnet-50	resnet-50	PROPN
fcis-26112	140	67	.	.	PUNCT
fcis-26112	141	1	this	this	PRON
fcis-26112	141	2	demonstrates	demonstrate	VERB
fcis-26112	141	3	that	that	SCONJ
fcis-26112	141	4	transferring	transfer	VERB
fcis-26112	141	5	the	the	DET
fcis-26112	141	6	pretrained	pretraine	VERB
fcis-26112	141	7	resnet-50	resnet-50	PROPN
fcis-26112	141	8	to	to	ADP
fcis-26112	141	9	the	the	DET
fcis-26112	141	10	problem	problem	NOUN
fcis-26112	141	11	of	of	ADP
fcis-26112	141	12	option	option	NOUN
fcis-26112	141	13	price	price	NOUN
fcis-26112	141	14	prediction	prediction	NOUN
fcis-26112	141	15	is	be	AUX
fcis-26112	141	16	valuable	valuable	ADJ
fcis-26112	141	17	,	,	PUNCT
fcis-26112	141	18	and	and	CCONJ
fcis-26112	141	19	it	it	PRON
fcis-26112	141	20	yielded	yield	VERB
fcis-26112	141	21	a	a	DET
fcis-26112	141	22	neural	neural	ADJ
fcis-26112	141	23	network	network	NOUN
fcis-26112	141	24	to	to	ADP
fcis-26112	141	25	price	price	NOUN
fcis-26112	141	26	options	option	NOUN
fcis-26112	141	27	that	that	PRON
fcis-26112	141	28	14	14	NUM
fcis-26112	141	29	was	be	AUX
fcis-26112	141	30	quite	quite	ADV
fcis-26112	141	31	accurate	accurate	ADJ
fcis-26112	141	32	in	in	ADP
fcis-26112	141	33	terms	term	NOUN
fcis-26112	141	34	of	of	ADP
fcis-26112	141	35	rmse	rmse	NOUN
fcis-26112	141	36	and	and	CCONJ
fcis-26112	141	37	r2	r2	PROPN
fcis-26112	141	38	.	.	PUNCT
fcis-26112	142	1	figure	figure	NOUN
fcis-26112	142	2	11	11	NUM
fcis-26112	142	3	.	.	PUNCT
fcis-26112	143	1	distribution	distribution	NOUN
fcis-26112	143	2	chart	chart	NOUN
fcis-26112	143	3	of	of	ADP
fcis-26112	143	4	the	the	DET
fcis-26112	143	5	prediction	prediction	NOUN
fcis-26112	143	6	results	result	NOUN
fcis-26112	143	7	of	of	ADP
fcis-26112	143	8	pre	pre	ADJ
fcis-26112	143	9	-	-	ADJ
fcis-26112	143	10	trained	train	VERB
fcis-26112	143	11	resnet-50	resnet-50	PROPN
fcis-26112	143	12	,	,	PUNCT
fcis-26112	143	13	where	where	SCONJ
fcis-26112	143	14	the	the	DET
fcis-26112	143	15	red	red	NOUN
fcis-26112	143	16	dashed	dash	VERB
fcis-26112	143	17	line	line	NOUN
fcis-26112	143	18	represents	represent	VERB
fcis-26112	143	19	predicted	predict	VERB
fcis-26112	143	20	values	value	NOUN
fcis-26112	143	21	equal	equal	ADJ
fcis-26112	143	22	to	to	ADP
fcis-26112	143	23	actual	actual	ADJ
fcis-26112	143	24	values	value	NOUN
fcis-26112	143	25	.	.	PUNCT
fcis-26112	144	1	table	table	NOUN
fcis-26112	144	2	5	5	NUM
fcis-26112	144	3	.	.	PUNCT
fcis-26112	144	4	example	example	NOUN
fcis-26112	144	5	of	of	ADP
fcis-26112	144	6	prediction	prediction	NOUN
fcis-26112	144	7	results	result	NOUN
fcis-26112	144	8	from	from	ADP
fcis-26112	144	9	pre	pre	ADJ
fcis-26112	144	10	-	-	ADJ
fcis-26112	144	11	trained	train	VERB
fcis-26112	144	12	resnet-50	resnet-50	PROPN
fcis-26112	144	13	prediction	prediction	NOUN
fcis-26112	144	14	results	result	NOUN
fcis-26112	144	15	of	of	ADP
fcis-26112	144	16	pre	pre	ADJ
fcis-26112	144	17	-	-	ADJ
fcis-26112	144	18	trained	train	VERB
fcis-26112	144	19	resnet-50	resnet-50	PROPN
fcis-26112	144	20	s	s	PROPN
fcis-26112	144	21	/	/	SYM
fcis-26112	144	22	n	n	PROPN
fcis-26112	144	23	predicted	predict	VERB
fcis-26112	144	24	price	price	NOUN
fcis-26112	144	25	actual	actual	ADJ
fcis-26112	144	26	price	price	NOUN
fcis-26112	144	27	1	1	NUM
fcis-26112	144	28	1553.904	1553.904	NUM
fcis-26112	144	29	1585.25	1585.25	NUM
fcis-26112	144	30	2	2	NUM
fcis-26112	144	31	1533.067	1533.067	NUM
fcis-26112	144	32	1567.05	1567.05	NUM
fcis-26112	144	33	3	3	NUM
fcis-26112	144	34	1523.566	1523.566	NUM
fcis-26112	144	35	1556.05	1556.05	NUM
fcis-26112	144	36	4	4	NUM
fcis-26112	144	37	1511.956	1511.956	NUM
fcis-26112	144	38	1544.7	1544.7	NUM
fcis-26112	144	39	5	5	NUM
fcis-26112	144	40	1510.514	1510.514	NUM
fcis-26112	144	41	1544.45	1544.45	NUM
fcis-26112	144	42	6	6	NUM
fcis-26112	144	43	1509.968	1509.968	NUM
fcis-26112	144	44	1540.8	1540.8	NUM
fcis-26112	144	45	7	7	NUM
fcis-26112	144	46	1502.915	1502.915	NUM
fcis-26112	144	47	1534.05	1534.05	NUM
fcis-26112	144	48	8	8	NUM
fcis-26112	144	49	1500.734	1500.734	NUM
fcis-26112	144	50	1533.3	1533.3	NUM
fcis-26112	144	51	9	9	NUM
fcis-26112	144	52	1494.189	1494.189	NUM
fcis-26112	144	53	1524.957	1524.957	NUM
fcis-26112	144	54	10	10	NUM
fcis-26112	144	55	1488.82	1488.82	NUM
fcis-26112	144	56	1522.35	1522.35	NUM
fcis-26112	144	57	11	11	NUM
fcis-26112	144	58	1488.031	1488.031	NUM
fcis-26112	144	59	1521.9	1521.9	NUM
fcis-26112	144	60	12	12	NUM
fcis-26112	144	61	1483.714	1483.714	NUM
fcis-26112	144	62	1515.075	1515.075	NUM
fcis-26112	144	63	13	13	NUM
fcis-26112	144	64	1479.518	1479.518	NUM
fcis-26112	144	65	1510.8	1510.8	NUM
fcis-26112	144	66	14	14	NUM
fcis-26112	144	67	1477.987	1477.987	NUM
fcis-26112	144	68	1510.55	1510.55	NUM
fcis-26112	144	69	15	15	NUM
fcis-26112	144	70	1475.617	1475.617	NUM
fcis-26112	144	71	1501	1501	NUM
fcis-26112	144	72	…	…	PUNCT
fcis-26112	144	73	…	…	PUNCT
fcis-26112	144	74	…	…	PUNCT
fcis-26112	144	75	1310	1310	NUM
fcis-26112	145	1	2.142062	2.142062	NUM
fcis-26112	145	2	0.140649	0.140649	NUM
fcis-26112	145	3	however	however	ADV
fcis-26112	145	4	,	,	PUNCT
fcis-26112	145	5	there	there	PRON
fcis-26112	145	6	may	may	AUX
fcis-26112	145	7	be	be	AUX
fcis-26112	145	8	some	some	DET
fcis-26112	145	9	possible	possible	ADJ
fcis-26112	145	10	limitations	limitation	NOUN
fcis-26112	145	11	in	in	ADP
fcis-26112	145	12	this	this	DET
fcis-26112	145	13	study	study	NOUN
fcis-26112	145	14	.	.	PUNCT
fcis-26112	146	1	due	due	ADP
fcis-26112	146	2	to	to	ADP
fcis-26112	146	3	the	the	DET
fcis-26112	146	4	constraints	constraint	NOUN
fcis-26112	146	5	of	of	ADP
fcis-26112	146	6	computational	computational	ADJ
fcis-26112	146	7	resources	resource	NOUN
fcis-26112	146	8	and	and	CCONJ
fcis-26112	146	9	time	time	NOUN
fcis-26112	146	10	,	,	PUNCT
fcis-26112	146	11	this	this	DET
fcis-26112	146	12	paper	paper	NOUN
fcis-26112	146	13	focused	focus	VERB
fcis-26112	146	14	only	only	ADV
fcis-26112	146	15	on	on	ADP
fcis-26112	146	16	the	the	DET
fcis-26112	146	17	transfer	transfer	NOUN
fcis-26112	146	18	learning	learning	NOUN
fcis-26112	146	19	of	of	ADP
fcis-26112	146	20	the	the	DET
fcis-26112	146	21	resnet-50	resnet-50	PROPN
fcis-26112	146	22	cnn	cnn	PROPN
fcis-26112	146	23	model	model	NOUN
fcis-26112	146	24	,	,	PUNCT
fcis-26112	146	25	and	and	CCONJ
fcis-26112	146	26	there	there	PRON
fcis-26112	146	27	may	may	AUX
fcis-26112	146	28	be	be	AUX
fcis-26112	146	29	other	other	ADJ
fcis-26112	146	30	more	more	ADV
fcis-26112	146	31	promising	promising	ADJ
fcis-26112	146	32	models	model	NOUN
fcis-26112	146	33	yet	yet	ADV
fcis-26112	146	34	to	to	PART
fcis-26112	146	35	be	be	AUX
fcis-26112	146	36	explored	explore	VERB
fcis-26112	146	37	.	.	PUNCT
fcis-26112	147	1	additionally	additionally	ADV
fcis-26112	147	2	,	,	PUNCT
fcis-26112	147	3	the	the	DET
fcis-26112	147	4	dataset	dataset	NOUN
fcis-26112	147	5	has	have	VERB
fcis-26112	147	6	a	a	DET
fcis-26112	147	7	small	small	ADJ
fcis-26112	147	8	-	-	PUNCT
fcis-26112	147	9	time	time	NOUN
fcis-26112	147	10	span	span	NOUN
fcis-26112	147	11	,	,	PUNCT
fcis-26112	147	12	which	which	PRON
fcis-26112	147	13	might	might	AUX
fcis-26112	147	14	introduce	introduce	VERB
fcis-26112	147	15	bias	bias	NOUN
fcis-26112	147	16	due	due	ADP
fcis-26112	147	17	to	to	ADP
fcis-26112	147	18	market	market	NOUN
fcis-26112	147	19	uncertainties	uncertainty	NOUN
fcis-26112	147	20	during	during	ADP
fcis-26112	147	21	that	that	DET
fcis-26112	147	22	period	period	NOUN
fcis-26112	147	23	.	.	PUNCT
fcis-26112	148	1	in	in	ADP
fcis-26112	148	2	future	future	ADJ
fcis-26112	148	3	work	work	NOUN
fcis-26112	148	4	,	,	PUNCT
fcis-26112	148	5	investigating	investigate	VERB
fcis-26112	148	6	more	more	ADJ
fcis-26112	148	7	pre	pre	ADJ
fcis-26112	148	8	-	-	ADJ
fcis-26112	148	9	trained	train	VERB
fcis-26112	148	10	cnn	cnn	PROPN
fcis-26112	148	11	models	model	NOUN
fcis-26112	148	12	and	and	CCONJ
fcis-26112	148	13	finding	find	VERB
fcis-26112	148	14	more	more	ADV
fcis-26112	148	15	reasonable	reasonable	ADJ
fcis-26112	148	16	data	datum	NOUN
fcis-26112	148	17	sampling	sample	VERB
fcis-26112	148	18	methods	method	NOUN
fcis-26112	148	19	are	be	AUX
fcis-26112	148	20	needed	need	VERB
fcis-26112	148	21	.	.	PUNCT
fcis-26112	149	1	exploring	explore	VERB
fcis-26112	149	2	how	how	SCONJ
fcis-26112	149	3	to	to	PART
fcis-26112	149	4	transfer	transfer	VERB
fcis-26112	149	5	pre	pre	ADJ
fcis-26112	149	6	-	-	VERB
fcis-26112	149	7	trained	train	VERB
fcis-26112	149	8	cnn	cnn	PROPN
fcis-26112	149	9	networks	network	NOUN
fcis-26112	149	10	to	to	ADP
fcis-26112	149	11	more	more	ADJ
fcis-26112	149	12	non	non	ADJ
fcis-26112	149	13	-	-	ADJ
fcis-26112	149	14	image	image	ADJ
fcis-26112	149	15	problems	problem	NOUN
fcis-26112	149	16	is	be	AUX
fcis-26112	149	17	also	also	ADV
fcis-26112	149	18	a	a	DET
fcis-26112	149	19	promising	promising	ADJ
fcis-26112	149	20	direction	direction	NOUN
fcis-26112	149	21	for	for	ADP
fcis-26112	149	22	future	future	ADJ
fcis-26112	149	23	research	research	NOUN
fcis-26112	149	24	.	.	PUNCT
fcis-26112	150	1	5	5	X
fcis-26112	150	2	.	.	X
fcis-26112	150	3	conclusion	conclusion	NOUN
fcis-26112	150	4	this	this	DET
fcis-26112	150	5	paper	paper	NOUN
fcis-26112	150	6	designed	design	VERB
fcis-26112	150	7	a	a	DET
fcis-26112	150	8	method	method	NOUN
fcis-26112	150	9	to	to	PART
fcis-26112	150	10	transfer	transfer	VERB
fcis-26112	150	11	pre	pre	ADJ
fcis-26112	150	12	-	-	ADJ
fcis-26112	150	13	trained	train	VERB
fcis-26112	150	14	resnet-50	resnet-50	PROPN
fcis-26112	150	15	to	to	ADP
fcis-26112	150	16	the	the	DET
fcis-26112	150	17	option	option	NOUN
fcis-26112	150	18	pricing	pricing	NOUN
fcis-26112	150	19	problem	problem	NOUN
fcis-26112	150	20	.	.	PUNCT
fcis-26112	151	1	treating	treat	VERB
fcis-26112	151	2	the	the	DET
fcis-26112	151	3	pretrained	pretraine	VERB
fcis-26112	151	4	resnet-50	resnet-50	PROPN
fcis-26112	151	5	as	as	ADP
fcis-26112	151	6	a	a	DET
fcis-26112	151	7	high	high	ADJ
fcis-26112	151	8	-	-	PUNCT
fcis-26112	151	9	level	level	NOUN
fcis-26112	151	10	feature	feature	NOUN
fcis-26112	151	11	extractor	extractor	NOUN
fcis-26112	151	12	,	,	PUNCT
fcis-26112	151	13	we	we	PRON
fcis-26112	151	14	trained	train	VERB
fcis-26112	151	15	custom	custom	NOUN
fcis-26112	151	16	top	top	ADJ
fcis-26112	151	17	layers	layer	NOUN
fcis-26112	151	18	to	to	PART
fcis-26112	151	19	fit	fit	VERB
fcis-26112	151	20	the	the	DET
fcis-26112	151	21	input	input	NOUN
fcis-26112	151	22	by	by	ADP
fcis-26112	151	23	converting	convert	VERB
fcis-26112	151	24	vector	vector	NOUN
fcis-26112	151	25	data	datum	NOUN
fcis-26112	151	26	into	into	ADP
fcis-26112	151	27	images	image	NOUN
fcis-26112	151	28	.	.	PUNCT
fcis-26112	152	1	the	the	DET
fcis-26112	152	2	final	final	ADJ
fcis-26112	152	3	option	option	NOUN
fcis-26112	152	4	price	price	NOUN
fcis-26112	152	5	prediction	prediction	NOUN
fcis-26112	152	6	was	be	AUX
fcis-26112	152	7	achieved	achieve	VERB
fcis-26112	152	8	with	with	ADP
fcis-26112	152	9	an	an	DET
fcis-26112	152	10	error	error	NOUN
fcis-26112	152	11	of	of	ADP
fcis-26112	152	12	rmse	rmse	NOUN
fcis-26112	152	13	=	=	SYM
fcis-26112	152	14	61.879	61.879	NUM
fcis-26112	152	15	and	and	CCONJ
fcis-26112	152	16	r²	r²	VERB
fcis-26112	152	17	=	=	SYM
fcis-26112	152	18	0.981	0.981	NUM
fcis-26112	152	19	,	,	PUNCT
fcis-26112	152	20	improving	improve	VERB
fcis-26112	152	21	by	by	ADP
fcis-26112	152	22	51.2	51.2	NUM
fcis-26112	152	23	%	%	NOUN
fcis-26112	152	24	over	over	ADP
fcis-26112	152	25	random	random	ADJ
fcis-26112	152	26	forest	forest	NOUN
fcis-26112	152	27	(	(	PUNCT
fcis-26112	152	28	rmse	rmse	NOUN
fcis-26112	152	29	=	=	SYM
fcis-26112	152	30	126.838	126.838	NUM
fcis-26112	152	31	,	,	PUNCT
fcis-26112	152	32	r²	r²	NOUN
fcis-26112	152	33	=	=	NOUN
fcis-26112	152	34	0.919	0.919	NUM
fcis-26112	152	35	)	)	PUNCT
fcis-26112	152	36	,	,	PUNCT
fcis-26112	152	37	by	by	ADP
fcis-26112	152	38	51.1	51.1	NUM
fcis-26112	152	39	%	%	NOUN
fcis-26112	152	40	over	over	ADP
fcis-26112	152	41	svr	svr	PROPN
fcis-26112	152	42	(	(	PUNCT
fcis-26112	152	43	rmse	rmse	PROPN
fcis-26112	152	44	=	=	PROPN
fcis-26112	152	45	126.575	126.575	NUM
fcis-26112	152	46	,	,	PUNCT
fcis-26112	152	47	r²	r²	NOUN
fcis-26112	152	48	=	=	NOUN
fcis-26112	152	49	0.920	0.920	NUM
fcis-26112	152	50	)	)	PUNCT
fcis-26112	152	51	,	,	PUNCT
fcis-26112	152	52	and	and	CCONJ
fcis-26112	152	53	by	by	ADP
fcis-26112	152	54	6	6	NUM
fcis-26112	152	55	%	%	NOUN
fcis-26112	152	56	over	over	ADP
fcis-26112	152	57	un	un	ADJ
fcis-26112	152	58	-	-	ADJ
fcis-26112	152	59	pre	pre	ADJ
fcis-26112	152	60	-	-	ADJ
fcis-26112	152	61	trained	train	VERB
fcis-26112	152	62	resnet-50	resnet-50	PROPN
fcis-26112	152	63	(	(	PUNCT
fcis-26112	152	64	rmse	rmse	NOUN
fcis-26112	152	65	=	=	SYM
fcis-26112	152	66	66.262	66.262	NUM
fcis-26112	152	67	,	,	PUNCT
fcis-26112	152	68	r²	r²	NOUN
fcis-26112	152	69	=	=	NOUN
fcis-26112	152	70	0.978	0.978	NUM
fcis-26112	152	71	)	)	PUNCT
fcis-26112	152	72	.	.	PUNCT
fcis-26112	153	1	this	this	PRON
fcis-26112	153	2	demonstrates	demonstrate	VERB
fcis-26112	153	3	the	the	DET
fcis-26112	153	4	effectiveness	effectiveness	NOUN
fcis-26112	153	5	of	of	ADP
fcis-26112	153	6	transferring	transfer	VERB
fcis-26112	153	7	pre	pre	ADJ
fcis-26112	153	8	-	-	ADJ
fcis-26112	153	9	trained	train	VERB
fcis-26112	153	10	cnn	cnn	PROPN
fcis-26112	153	11	networks	network	NOUN
fcis-26112	153	12	to	to	ADP
fcis-26112	153	13	the	the	DET
fcis-26112	153	14	option	option	NOUN
fcis-26112	153	15	pricing	pricing	NOUN
fcis-26112	153	16	problem	problem	NOUN
fcis-26112	153	17	.	.	PUNCT
fcis-26112	154	1	acknowledgments	acknowledgment	NOUN
fcis-26112	154	2	i	i	PRON
fcis-26112	154	3	sincerely	sincerely	ADV
fcis-26112	154	4	thank	thank	VERB
fcis-26112	154	5	my	my	PRON
fcis-26112	154	6	advisor	advisor	NOUN
fcis-26112	154	7	vipul	vipul	PROPN
fcis-26112	154	8	goyal	goyal	PROPN
fcis-26112	154	9	for	for	ADP
fcis-26112	154	10	his	his	PRON
fcis-26112	154	11	guidance	guidance	NOUN
fcis-26112	154	12	,	,	PUNCT
fcis-26112	154	13	support	support	NOUN
fcis-26112	154	14	,	,	PUNCT
fcis-26112	154	15	encouragement	encouragement	NOUN
fcis-26112	154	16	,	,	PUNCT
fcis-26112	154	17	and	and	CCONJ
fcis-26112	154	18	assistance	assistance	NOUN
fcis-26112	154	19	during	during	ADP
fcis-26112	154	20	the	the	DET
fcis-26112	154	21	research	research	NOUN
fcis-26112	154	22	period	period	NOUN
fcis-26112	154	23	.	.	PUNCT
fcis-26112	155	1	his	his	PRON
fcis-26112	155	2	expertise	expertise	NOUN
fcis-26112	155	3	and	and	CCONJ
fcis-26112	155	4	insights	insight	NOUN
fcis-26112	155	5	have	have	AUX
fcis-26112	155	6	been	be	AUX
fcis-26112	155	7	instrumental	instrumental	ADJ
fcis-26112	155	8	in	in	ADP
fcis-26112	155	9	shaping	shape	VERB
fcis-26112	155	10	this	this	DET
fcis-26112	155	11	work	work	NOUN
fcis-26112	155	12	.	.	PUNCT
fcis-26112	156	1	i	i	PRON
fcis-26112	156	2	also	also	ADV
fcis-26112	156	3	want	want	VERB
fcis-26112	156	4	to	to	PART
fcis-26112	156	5	thank	thank	VERB
fcis-26112	156	6	my	my	PRON
fcis-26112	156	7	mentor	mentor	NOUN
fcis-26112	156	8	yuru	yuru	PROPN
fcis-26112	156	9	jing	jing	PROPN
fcis-26112	156	10	for	for	ADP
fcis-26112	156	11	the	the	DET
fcis-26112	156	12	advice	advice	NOUN
fcis-26112	156	13	and	and	CCONJ
fcis-26112	156	14	help	help	NOUN
fcis-26112	156	15	provided	provide	VERB
fcis-26112	156	16	during	during	ADP
fcis-26112	156	17	the	the	DET
fcis-26112	156	18	writing	writing	NOUN
fcis-26112	156	19	process	process	NOUN
fcis-26112	156	20	.	.	PUNCT
fcis-26112	157	1	lastly	lastly	ADV
fcis-26112	157	2	,	,	PUNCT
fcis-26112	157	3	i	i	PRON
fcis-26112	157	4	am	be	AUX
fcis-26112	157	5	grateful	grateful	ADJ
fcis-26112	157	6	to	to	ADP
fcis-26112	157	7	all	all	DET
fcis-26112	157	8	those	those	PRON
fcis-26112	157	9	who	who	PRON
fcis-26112	157	10	have	have	AUX
fcis-26112	157	11	indirectly	indirectly	ADV
fcis-26112	157	12	contributed	contribute	VERB
fcis-26112	157	13	to	to	ADP
fcis-26112	157	14	this	this	DET
fcis-26112	157	15	research	research	NOUN
fcis-26112	157	16	.	.	PUNCT
fcis-26112	158	1	thank	thank	VERB
fcis-26112	158	2	you	you	PRON
fcis-26112	158	3	for	for	ADP
fcis-26112	158	4	your	your	PRON
fcis-26112	158	5	support	support	NOUN
fcis-26112	158	6	and	and	CCONJ
fcis-26112	158	7	understanding	understanding	NOUN
fcis-26112	158	8	.	.	PUNCT
fcis-26112	159	1	references	reference	NOUN
fcis-26112	159	2	[	[	X
fcis-26112	159	3	1	1	NUM
fcis-26112	159	4	]	]	PUNCT
fcis-26112	159	5	business	business	NOUN
fcis-26112	159	6	development	development	PROPN
fcis-26112	159	7	bank	bank	PROPN
fcis-26112	159	8	of	of	ADP
fcis-26112	159	9	canada	canada	PROPN
fcis-26112	159	10	.	.	PUNCT
fcis-26112	160	1	(	(	PUNCT
fcis-26112	160	2	n.d	n.d	PROPN
fcis-26112	160	3	.	.	PROPN
fcis-26112	160	4	)	)	PUNCT
fcis-26112	160	5	.	.	PUNCT
fcis-26112	161	1	how	how	SCONJ
fcis-26112	161	2	to	to	PART
fcis-26112	161	3	use	use	VERB
fcis-26112	161	4	stock	stock	NOUN
fcis-26112	161	5	options	option	NOUN
fcis-26112	161	6	to	to	PART
fcis-26112	161	7	recruit	recruit	VERB
fcis-26112	161	8	,	,	PUNCT
fcis-26112	161	9	retain	retain	VERB
fcis-26112	161	10	and	and	CCONJ
fcis-26112	161	11	motivate	motivate	VERB
fcis-26112	161	12	start	start	VERB
fcis-26112	161	13	-	-	PUNCT
fcis-26112	161	14	up	up	ADP
fcis-26112	161	15	employees	employee	NOUN
fcis-26112	161	16	.	.	PUNCT
fcis-26112	162	1	bdc.ca	bdc.ca	NOUN
fcis-26112	162	2	.	.	PUNCT
fcis-26112	163	1	retrieved	retrieve	VERB
fcis-26112	163	2	from	from	ADP
fcis-26112	163	3	https://www.bdc.ca/en/articlestools/employees/manage/how-to-use-stock-options-to-recruitretain-motivate-start-up-employees\.	https://www.bdc.ca/en/articlestools/employees/manage/how-to-use-stock-options-to-recruitretain-motivate-start-up-employees\.	NOUN
fcis-26112	164	1	[	[	X
fcis-26112	164	2	2	2	NUM
fcis-26112	164	3	]	]	PUNCT
fcis-26112	164	4	bullish	bullish	ADJ
fcis-26112	164	5	bears	bear	NOUN
fcis-26112	164	6	.	.	PUNCT
fcis-26112	165	1	(	(	PUNCT
fcis-26112	165	2	n.d	n.d	PROPN
fcis-26112	165	3	.	.	PROPN
fcis-26112	165	4	)	)	PUNCT
fcis-26112	165	5	.	.	PUNCT
fcis-26112	166	1	trading	trading	NOUN
fcis-26112	166	2	options	option	NOUN
fcis-26112	166	3	for	for	ADP
fcis-26112	166	4	a	a	DET
fcis-26112	166	5	living	living	NOUN
fcis-26112	166	6	.	.	PUNCT
fcis-26112	167	1	*	*	PUNCT
fcis-26112	167	2	bullish	bullish	ADJ
fcis-26112	167	3	bears	bear	NOUN
fcis-26112	167	4	*	*	PUNCT
fcis-26112	167	5	.	.	PUNCT
fcis-26112	167	6	retrieved	retrieve	VERB
fcis-26112	167	7	from	from	ADP
fcis-26112	167	8	https://bullishbears.com/tradingoptions-for-a-living/.	https://bullishbears.com/tradingoptions-for-a-living/.	PROPN
fcis-26112	168	1	[	[	X
fcis-26112	168	2	3	3	NUM
fcis-26112	168	3	]	]	PUNCT
fcis-26112	168	4	shin	shin	NOUN
fcis-26112	168	5	,	,	PUNCT
fcis-26112	168	6	hoo	hoo	PROPN
fcis-26112	168	7	-	-	PUNCT
fcis-26112	168	8	chang	chang	PROPN
fcis-26112	168	9	,	,	PUNCT
fcis-26112	168	10	et	et	PROPN
fcis-26112	168	11	al	al	PROPN
fcis-26112	168	12	.	.	PUNCT
fcis-26112	169	1	"	"	PUNCT
fcis-26112	169	2	deep	deep	ADJ
fcis-26112	169	3	convolutional	convolutional	ADJ
fcis-26112	169	4	neural	neural	ADJ
fcis-26112	169	5	networks	network	NOUN
fcis-26112	169	6	for	for	ADP
fcis-26112	169	7	computer	computer	NOUN
fcis-26112	169	8	-	-	PUNCT
fcis-26112	169	9	aided	aid	VERB
fcis-26112	169	10	detection	detection	NOUN
fcis-26112	169	11	:	:	PUNCT
fcis-26112	169	12	cnn	cnn	PROPN
fcis-26112	169	13	architectures	architecture	NOUN
fcis-26112	169	14	,	,	PUNCT
fcis-26112	169	15	dataset	dataset	ADJ
fcis-26112	169	16	characteristics	characteristic	NOUN
fcis-26112	169	17	and	and	CCONJ
fcis-26112	169	18	transfer	transfer	NOUN
fcis-26112	169	19	learning	learning	NOUN
fcis-26112	169	20	.	.	PUNCT
fcis-26112	169	21	"	"	PUNCT
fcis-26112	170	1	ieee	ieee	NOUN
fcis-26112	170	2	transactions	transaction	NOUN
fcis-26112	170	3	on	on	ADP
fcis-26112	170	4	medical	medical	ADJ
fcis-26112	170	5	imaging	imaging	NOUN
fcis-26112	170	6	35.5	35.5	NUM
fcis-26112	170	7	(	(	PUNCT
fcis-26112	170	8	2016	2016	NUM
fcis-26112	170	9	):	):	PUNCT
fcis-26112	170	10	1285	1285	NUM
fcis-26112	170	11	-	-	SYM
fcis-26112	170	12	1298	1298	NUM
fcis-26112	170	13	.	.	PUNCT
fcis-26112	171	1	[	[	X
fcis-26112	171	2	4	4	X
fcis-26112	171	3	]	]	X
fcis-26112	171	4	sharif	sharif	PROPN
fcis-26112	171	5	razavian	razavian	PROPN
fcis-26112	171	6	,	,	PUNCT
fcis-26112	171	7	ali	ali	PROPN
fcis-26112	171	8	,	,	PUNCT
fcis-26112	171	9	et	et	PROPN
fcis-26112	171	10	al	al	PROPN
fcis-26112	171	11	.	.	PUNCT
fcis-26112	172	1	"	"	PUNCT
fcis-26112	172	2	cnn	cnn	PROPN
fcis-26112	172	3	features	feature	VERB
fcis-26112	172	4	off	off	ADP
fcis-26112	172	5	-	-	PUNCT
fcis-26112	172	6	the	the	DET
fcis-26112	172	7	-	-	PUNCT
fcis-26112	172	8	shelf	shelf	NOUN
fcis-26112	172	9	:	:	PUNCT
fcis-26112	172	10	an	an	DET
fcis-26112	172	11	astounding	astounding	ADJ
fcis-26112	172	12	baseline	baseline	NOUN
fcis-26112	172	13	for	for	ADP
fcis-26112	172	14	recognition	recognition	NOUN
fcis-26112	172	15	.	.	PUNCT
fcis-26112	172	16	"	"	PUNCT
fcis-26112	173	1	proceedings	proceeding	NOUN
fcis-26112	173	2	of	of	ADP
fcis-26112	173	3	the	the	DET
fcis-26112	173	4	ieee	ieee	NOUN
fcis-26112	173	5	conference	conference	NOUN
fcis-26112	173	6	on	on	ADP
fcis-26112	173	7	computer	computer	NOUN
fcis-26112	173	8	vision	vision	NOUN
fcis-26112	173	9	and	and	CCONJ
fcis-26112	173	10	pattern	pattern	NOUN
fcis-26112	173	11	recognition	recognition	NOUN
fcis-26112	173	12	workshops	workshop	NOUN
fcis-26112	173	13	.	.	PUNCT
fcis-26112	174	1	2014	2014	NUM
fcis-26112	174	2	.	.	PUNCT
fcis-26112	175	1	[	[	X
fcis-26112	175	2	5	5	NUM
fcis-26112	175	3	]	]	PUNCT
fcis-26112	175	4	huh	huh	PROPN
fcis-26112	175	5	,	,	PUNCT
fcis-26112	175	6	minyoung	minyoung	PROPN
fcis-26112	175	7	,	,	PUNCT
fcis-26112	175	8	pulkit	pulkit	NOUN
fcis-26112	175	9	agrawal	agrawal	PROPN
fcis-26112	175	10	,	,	PUNCT
fcis-26112	175	11	and	and	CCONJ
fcis-26112	175	12	alexei	alexei	PROPN
fcis-26112	175	13	a.	a.	PROPN
fcis-26112	175	14	efros	efros	PROPN
fcis-26112	175	15	.	.	PUNCT
fcis-26112	176	1	"	"	PUNCT
fcis-26112	176	2	what	what	PRON
fcis-26112	176	3	makes	make	VERB
fcis-26112	176	4	imagenet	imagenet	NOUN
fcis-26112	176	5	good	good	ADJ
fcis-26112	176	6	for	for	ADP
fcis-26112	176	7	transfer	transfer	NOUN
fcis-26112	176	8	learning	learning	NOUN
fcis-26112	176	9	?	?	PUNCT
fcis-26112	176	10	.	.	PUNCT
fcis-26112	176	11	"	"	PUNCT
fcis-26112	177	1	arxiv	arxiv	PROPN
fcis-26112	177	2	preprint	preprint	NOUN
fcis-26112	177	3	arxiv:1608.08614	arxiv:1608.08614	NOUN
fcis-26112	177	4	(	(	PUNCT
fcis-26112	177	5	2016	2016	NUM
fcis-26112	177	6	)	)	PUNCT
fcis-26112	177	7	.	.	PUNCT
fcis-26112	178	1	[	[	X
fcis-26112	178	2	6	6	NUM
fcis-26112	178	3	]	]	PUNCT
fcis-26112	178	4	sezer	sezer	NOUN
fcis-26112	178	5	,	,	PUNCT
fcis-26112	178	6	omer	omer	PROPN
fcis-26112	178	7	berat	berat	PROPN
fcis-26112	178	8	,	,	PUNCT
fcis-26112	178	9	mehmet	mehmet	PROPN
fcis-26112	178	10	ugur	ugur	PROPN
fcis-26112	178	11	gudelek	gudelek	VERB
fcis-26112	178	12	,	,	PUNCT
fcis-26112	178	13	and	and	CCONJ
fcis-26112	178	14	ahmet	ahmet	PROPN
fcis-26112	178	15	murat	murat	PROPN
fcis-26112	178	16	ozbayoglu	ozbayoglu	NOUN
fcis-26112	178	17	.	.	PUNCT
fcis-26112	179	1	"	"	PUNCT
fcis-26112	179	2	financial	financial	ADJ
fcis-26112	179	3	time	time	NOUN
fcis-26112	179	4	series	series	PROPN
fcis-26112	179	5	forecasting	forecasting	NOUN
fcis-26112	179	6	with	with	ADP
fcis-26112	179	7	deep	deep	ADJ
fcis-26112	179	8	learning	learning	NOUN
fcis-26112	179	9	:	:	PUNCT
fcis-26112	179	10	a	a	DET
fcis-26112	179	11	systematic	systematic	ADJ
fcis-26112	179	12	literature	literature	NOUN
fcis-26112	179	13	review	review	NOUN
fcis-26112	179	14	:	:	PUNCT
fcis-26112	179	15	2005–2019	2005–2019	NUM
fcis-26112	179	16	.	.	PUNCT
fcis-26112	179	17	"	"	PUNCT
fcis-26112	179	18	applied	apply	VERB
fcis-26112	179	19	soft	soft	ADJ
fcis-26112	179	20	computing	compute	VERB
fcis-26112	179	21	90	90	NUM
fcis-26112	179	22	(	(	PUNCT
fcis-26112	179	23	2020	2020	NUM
fcis-26112	179	24	):	):	PUNCT
fcis-26112	179	25	106181	106181	NUM
fcis-26112	179	26	.	.	PUNCT
fcis-26112	180	1	[	[	X
fcis-26112	180	2	7	7	NUM
fcis-26112	180	3	]	]	X
fcis-26112	180	4	doering	doering	NOUN
fcis-26112	180	5	,	,	PUNCT
fcis-26112	180	6	jonathan	jonathan	PROPN
fcis-26112	180	7	,	,	PUNCT
fcis-26112	180	8	michael	michael	PROPN
fcis-26112	180	9	fairbank	fairbank	PROPN
fcis-26112	180	10	,	,	PUNCT
fcis-26112	180	11	and	and	CCONJ
fcis-26112	180	12	sheri	sheri	PROPN
fcis-26112	180	13	markose	markose	PROPN
fcis-26112	180	14	.	.	PUNCT
fcis-26112	181	1	"	"	PUNCT
fcis-26112	181	2	convolutional	convolutional	ADJ
fcis-26112	181	3	neural	neural	ADJ
fcis-26112	181	4	networks	network	NOUN
fcis-26112	181	5	applied	apply	VERB
fcis-26112	181	6	to	to	ADP
fcis-26112	181	7	high	high	ADJ
fcis-26112	181	8	-	-	PUNCT
fcis-26112	181	9	frequency	frequency	NOUN
fcis-26112	181	10	market	market	NOUN
fcis-26112	181	11	microstructure	microstructure	NOUN
fcis-26112	181	12	forecasting	forecasting	NOUN
fcis-26112	181	13	.	.	PUNCT
fcis-26112	181	14	"	"	PUNCT
fcis-26112	182	1	2017	2017	NUM
fcis-26112	182	2	9th	9th	ADJ
fcis-26112	182	3	computer	computer	NOUN
fcis-26112	182	4	science	science	NOUN
fcis-26112	182	5	and	and	CCONJ
fcis-26112	182	6	electronic	electronic	ADJ
fcis-26112	182	7	engineering	engineering	NOUN
fcis-26112	182	8	(	(	PUNCT
fcis-26112	182	9	ceec	ceec	ADJ
fcis-26112	182	10	)	)	PUNCT
fcis-26112	182	11	.	.	PUNCT
fcis-26112	183	1	ieee	ieee	PROPN
fcis-26112	183	2	,	,	PUNCT
fcis-26112	183	3	2017	2017	NUM
fcis-26112	183	4	.	.	PUNCT
fcis-26112	184	1	[	[	X
fcis-26112	184	2	8	8	NUM
fcis-26112	184	3	]	]	X
fcis-26112	184	4	kovalerchuk	kovalerchuk	NOUN
fcis-26112	184	5	,	,	PUNCT
fcis-26112	184	6	boris	boris	PROPN
fcis-26112	184	7	,	,	PUNCT
fcis-26112	184	8	bedant	bedant	PROPN
fcis-26112	184	9	agarwal	agarwal	PROPN
fcis-26112	184	10	,	,	PUNCT
fcis-26112	184	11	and	and	CCONJ
fcis-26112	184	12	divya	divya	PROPN
fcis-26112	184	13	chandrika	chandrika	PROPN
fcis-26112	184	14	kall	kall	PROPN
fcis-26112	184	15	.	.	PUNCT
fcis-26112	185	1	"	"	PUNCT
fcis-26112	185	2	solving	solve	VERB
fcis-26112	185	3	non	non	ADJ
fcis-26112	185	4	-	-	ADJ
fcis-26112	185	5	image	image	ADJ
fcis-26112	185	6	learning	learning	NOUN
fcis-26112	185	7	problems	problem	NOUN
fcis-26112	185	8	by	by	ADP
fcis-26112	185	9	mapping	map	VERB
fcis-26112	185	10	to	to	ADP
fcis-26112	185	11	images	image	NOUN
fcis-26112	185	12	.	.	PUNCT
fcis-26112	185	13	"	"	PUNCT
fcis-26112	186	1	2020	2020	NUM
fcis-26112	186	2	24th	24th	ADJ
fcis-26112	186	3	international	international	ADJ
fcis-26112	186	4	conference	conference	NOUN
fcis-26112	186	5	information	information	NOUN
fcis-26112	186	6	visualisation	visualisation	NOUN
fcis-26112	186	7	(	(	PUNCT
fcis-26112	186	8	iv	iv	NOUN
fcis-26112	186	9	)	)	PUNCT
fcis-26112	186	10	.	.	PUNCT
fcis-26112	187	1	ieee	ieee	PROPN
fcis-26112	187	2	,	,	PUNCT
fcis-26112	187	3	2020	2020	NUM
fcis-26112	187	4	.	.	PUNCT
fcis-26112	188	1	[	[	X
fcis-26112	188	2	9	9	NUM
fcis-26112	188	3	]	]	SYM
fcis-26112	188	4	ivașcu	ivașcu	NOUN
fcis-26112	188	5	,	,	PUNCT
fcis-26112	188	6	codruț	codruț	NOUN
fcis-26112	188	7	-	-	PUNCT
fcis-26112	188	8	florin	florin	PROPN
fcis-26112	188	9	.	.	PUNCT
fcis-26112	189	1	"	"	PUNCT
fcis-26112	189	2	option	option	NOUN
fcis-26112	189	3	pricing	pricing	NOUN
fcis-26112	189	4	using	use	VERB
fcis-26112	189	5	machine	machine	NOUN
fcis-26112	189	6	learning	learning	NOUN
fcis-26112	189	7	.	.	PUNCT
fcis-26112	189	8	"	"	PUNCT
fcis-26112	190	1	expert	expert	NOUN
fcis-26112	190	2	systems	system	NOUN
fcis-26112	190	3	with	with	ADP
fcis-26112	190	4	applications	application	NOUN
fcis-26112	190	5	163	163	NUM
fcis-26112	190	6	(	(	PUNCT
fcis-26112	190	7	2021	2021	NUM
fcis-26112	190	8	):	):	PUNCT
fcis-26112	190	9	113799	113799	NUM
fcis-26112	190	10	.	.	PUNCT
fcis-26112	191	1	[	[	X
fcis-26112	191	2	10	10	NUM
fcis-26112	191	3	]	]	X
fcis-26112	191	4	breiman	breiman	NOUN
fcis-26112	191	5	,	,	PUNCT
fcis-26112	191	6	leo	leo	PROPN
fcis-26112	191	7	.	.	PUNCT
fcis-26112	192	1	"	"	PUNCT
fcis-26112	192	2	random	random	ADJ
fcis-26112	192	3	forests	forest	NOUN
fcis-26112	192	4	.	.	PUNCT
fcis-26112	192	5	"	"	PUNCT
fcis-26112	193	1	machine	machine	NOUN
fcis-26112	193	2	learning	learn	VERB
fcis-26112	193	3	45	45	NUM
fcis-26112	193	4	(	(	PUNCT
fcis-26112	193	5	2001	2001	NUM
fcis-26112	193	6	):	):	PUNCT
fcis-26112	193	7	5	5	NUM
fcis-26112	193	8	-	-	SYM
fcis-26112	193	9	32	32	NUM
fcis-26112	193	10	.	.	PUNCT
fcis-26112	194	1	[	[	X
fcis-26112	194	2	11	11	NUM
fcis-26112	194	3	]	]	X
fcis-26112	194	4	pedregosa	pedregosa	PROPN
fcis-26112	194	5	,	,	PUNCT
fcis-26112	194	6	fabian	fabian	NOUN
fcis-26112	194	7	,	,	PUNCT
fcis-26112	194	8	et	et	PROPN
fcis-26112	194	9	al	al	PROPN
fcis-26112	194	10	.	.	PUNCT
fcis-26112	194	11	"	"	PUNCT
fcis-26112	194	12	scikit	scikit	NOUN
fcis-26112	194	13	-	-	PUNCT
fcis-26112	194	14	learn	learn	VERB
fcis-26112	194	15	:	:	PUNCT
fcis-26112	194	16	machine	machine	NOUN
fcis-26112	194	17	learning	learning	NOUN
fcis-26112	194	18	in	in	ADP
fcis-26112	194	19	python	python	NOUN
fcis-26112	194	20	.	.	PUNCT
fcis-26112	194	21	"	"	PUNCT
fcis-26112	194	22	journal	journal	NOUN
fcis-26112	194	23	of	of	ADP
fcis-26112	194	24	machine	machine	NOUN
fcis-26112	194	25	learning	learn	VERB
fcis-26112	194	26	research	research	NOUN
fcis-26112	194	27	,	,	PUNCT
fcis-26112	194	28	vol	vol	NOUN
fcis-26112	194	29	.	.	PROPN
fcis-26112	194	30	12	12	NUM
fcis-26112	194	31	,	,	PUNCT
fcis-26112	194	32	2011	2011	NUM
fcis-26112	194	33	,	,	PUNCT
fcis-26112	194	34	pp	pp	ADJ
fcis-26112	194	35	.	.	PUNCT
fcis-26112	195	1	2825	2825	NUM
fcis-26112	195	2	-	-	SYM
fcis-26112	195	3	2830	2830	NUM
fcis-26112	195	4	.	.	PUNCT
fcis-26112	196	1	scikit	scikit	NOUN
fcis-26112	196	2	-	-	PUNCT
fcis-26112	196	3	learn	learn	VERB
fcis-26112	196	4	,	,	PUNCT
fcis-26112	196	5	https://scikit-learn.org/	https://scikit-learn.org/	PROPN
fcis-26112	196	6	stable/	stable/	PROPN
fcis-26112	196	7	modules/	modules/	NUM
fcis-26112	196	8	svm.html	svm.html	NOUN
fcis-26112	196	9	.	.	PUNCT
fcis-26112	197	1	[	[	X
fcis-26112	197	2	12	12	NUM
fcis-26112	197	3	]	]	X
fcis-26112	197	4	zhou	zhou	PROPN
fcis-26112	197	5	zhihua	zhihua	PROPN
fcis-26112	197	6	.	.	PUNCT
fcis-26112	198	1	csdn	csdn	PROPN
fcis-26112	198	2	.	.	PUNCT
fcis-26112	199	1	(	(	PUNCT
fcis-26112	199	2	2018	2018	NUM
fcis-26112	199	3	)	)	PUNCT
fcis-26112	199	4	.	.	PUNCT
fcis-26112	200	1	retrieved	retrieve	VERB
fcis-26112	200	2	from	from	ADP
fcis-26112	200	3	https://	https://	PROPN
fcis-26112	200	4	blog.csdn.net/weixin_37160123/article/details/80963892	blog.csdn.net/weixin_37160123/article/details/80963892	PROPN
fcis-26112	200	5	.	.	PUNCT
fcis-26112	201	1	[	[	X
fcis-26112	201	2	13	13	NUM
fcis-26112	201	3	]	]	PUNCT
fcis-26112	201	4	he	he	PRON
fcis-26112	201	5	,	,	PUNCT
fcis-26112	201	6	kaiming	kaiming	NOUN
fcis-26112	201	7	,	,	PUNCT
fcis-26112	201	8	et	et	PROPN
fcis-26112	201	9	al	al	PROPN
fcis-26112	201	10	.	.	PUNCT
fcis-26112	202	1	"	"	PUNCT
fcis-26112	202	2	deep	deep	ADJ
fcis-26112	202	3	residual	residual	ADJ
fcis-26112	202	4	learning	learning	NOUN
fcis-26112	202	5	for	for	ADP
fcis-26112	202	6	image	image	NOUN
fcis-26112	202	7	recognition	recognition	NOUN
fcis-26112	202	8	.	.	PUNCT
fcis-26112	202	9	"	"	PUNCT
fcis-26112	203	1	proceedings	proceeding	NOUN
fcis-26112	203	2	of	of	ADP
fcis-26112	203	3	the	the	DET
fcis-26112	203	4	ieee	ieee	NOUN
fcis-26112	203	5	conference	conference	NOUN
fcis-26112	203	6	on	on	ADP
fcis-26112	203	7	computer	computer	NOUN
fcis-26112	203	8	vision	vision	NOUN
fcis-26112	203	9	and	and	CCONJ
fcis-26112	203	10	pattern	pattern	NOUN
fcis-26112	203	11	recognition	recognition	NOUN
fcis-26112	203	12	.	.	PUNCT
fcis-26112	204	1	2016	2016	NUM
fcis-26112	204	2	.	.	PUNCT
fcis-26112	205	1	[	[	X
fcis-26112	205	2	14	14	NUM
fcis-26112	205	3	]	]	PUNCT
fcis-26112	205	4	bing.resnet50	bing.resnet50	NOUN
fcis-26112	205	5	network	network	NOUN
fcis-26112	205	6	architecture	architecture	NOUN
fcis-26112	205	7	diagram	diagram	NOUN
fcis-26112	205	8	and	and	CCONJ
fcis-26112	205	9	detailed	detailed	ADJ
fcis-26112	205	10	structure	structure	NOUN
fcis-26112	205	11	explanation	explanation	NOUN
fcis-26112	205	12	[	[	X
fcis-26112	205	13	eb	eb	PROPN
fcis-26112	205	14	/	/	SYM
fcis-26112	205	15	ol].(2021	ol].(2021	NOUN
fcis-26112	205	16	-	-	PUNCT
fcis-26112	205	17	02	02	NUM
fcis-26112	205	18	-	-	PUNCT
fcis-26112	205	19	26)[2022	26)[2022	NUM
fcis-26112	205	20	-	-	PUNCT
fcis-26112	205	21	05	05	NUM
fcis-26112	205	22	-	-	SYM
fcis-26112	205	23	31	31	NUM
fcis-26112	205	24	]	]	PUNCT
fcis-26112	205	25	.	.	PUNCT
fcis-26112	206	1	zhuanlan	zhuanlan	PROPN
fcis-26112	206	2	.	.	PUNCT
fcis-26112	207	1	zhihu.com/p/353235794	zhihu.com/p/353235794	PROPN
fcis-26112	207	2	.	.	PUNCT
fcis-26112	208	1	[	[	X
fcis-26112	208	2	15	15	NUM
fcis-26112	208	3	]	]	X
fcis-26112	208	4	kovalerchuk	kovalerchuk	NOUN
fcis-26112	208	5	b	b	PROPN
fcis-26112	208	6	,	,	PUNCT
fcis-26112	208	7	agarwal	agarwal	PROPN
fcis-26112	208	8	b	b	PROPN
fcis-26112	208	9	,	,	PUNCT
fcis-26112	208	10	kall	kall	PROPN
fcis-26112	208	11	d	d	PROPN
fcis-26112	208	12	c.	c.	PROPN
fcis-26112	208	13	solving	solve	VERB
fcis-26112	208	14	non	non	ADJ
fcis-26112	208	15	-	-	ADJ
fcis-26112	208	16	image	image	ADJ
fcis-26112	208	17	learning	learning	NOUN
fcis-26112	208	18	problems	problem	NOUN
fcis-26112	208	19	by	by	ADP
fcis-26112	208	20	mapping	map	VERB
fcis-26112	208	21	to	to	ADP
fcis-26112	208	22	images[c]//2020	images[c]//2020	ADP
fcis-26112	208	23	24th	24th	ADJ
fcis-26112	208	24	15	15	NUM
fcis-26112	208	25	international	international	ADJ
fcis-26112	208	26	conference	conference	NOUN
fcis-26112	208	27	information	information	NOUN
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fcis-26112	208	29	(	(	PUNCT
fcis-26112	208	30	iv	iv	NOUN
fcis-26112	208	31	)	)	PUNCT
fcis-26112	208	32	.	.	PUNCT
fcis-26112	209	1	ieee	ieee	PROPN
fcis-26112	209	2	,	,	PUNCT
fcis-26112	209	3	2020	2020	NUM
fcis-26112	209	4	:	:	PUNCT
fcis-26112	209	5	264	264	NUM
fcis-26112	209	6	-	-	SYM
fcis-26112	209	7	269	269	NUM
fcis-26112	209	8	.	.	PUNCT
fcis-26112	210	1	[	[	X
fcis-26112	210	2	16	16	NUM
fcis-26112	210	3	]	]	X
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fcis-26112	210	5	.	.	PUNCT
fcis-26112	211	1	(	(	PUNCT
fcis-26112	211	2	2023	2023	NUM
fcis-26112	211	3	)	)	PUNCT
fcis-26112	211	4	.	.	PUNCT
fcis-26112	212	1	mse	mse	PROPN
fcis-26112	212	2	vs	vs	ADP
fcis-26112	212	3	rmse	rmse	PROPN
fcis-26112	212	4	vs	vs	ADP
fcis-26112	212	5	mae	mae	PROPN
fcis-26112	212	6	vs	vs	ADP
fcis-26112	212	7	mape	mape	NOUN
fcis-26112	212	8	vs	vs	ADP
fcis-26112	212	9	rsquared	rsquared	ADJ
fcis-26112	212	10	:	:	PUNCT
fcis-26112	212	11	when	when	SCONJ
fcis-26112	212	12	to	to	PART
fcis-26112	212	13	use	use	VERB
fcis-26112	212	14	?	?	PUNCT
fcis-26112	212	15	.	.	PUNCT
fcis-26112	213	1	*	*	PUNCT
fcis-26112	213	2	vitalflux	vitalflux	X
fcis-26112	213	3	*	*	PUNCT
fcis-26112	213	4	.	.	PUNCT
fcis-26112	214	1	retrieved	retrieve	VERB
fcis-26112	214	2	from	from	ADP
fcis-26112	214	3	https://	https://	PROPN
fcis-26112	214	4	vitalflux.com/mse-vs-rmse-vs-mae-vs-mape-vs-r-squaredwhen-to-use/.	vitalflux.com/mse-vs-rmse-vs-mae-vs-mape-vs-r-squaredwhen-to-use/.	PROPN
fcis-26112	214	5	[	[	X
fcis-26112	214	6	17	17	NUM
fcis-26112	214	7	]	]	X
fcis-26112	214	8	homescu	homescu	PROPN
fcis-26112	214	9	,	,	PUNCT
fcis-26112	214	10	cristian	cristian	PROPN
fcis-26112	214	11	.	.	PUNCT
fcis-26112	215	1	"	"	PUNCT
fcis-26112	215	2	implied	imply	VERB
fcis-26112	215	3	volatility	volatility	NOUN
fcis-26112	215	4	surface	surface	NOUN
fcis-26112	215	5	:	:	PUNCT
fcis-26112	215	6	construction	construction	NOUN
fcis-26112	215	7	methodologies	methodology	NOUN
fcis-26112	215	8	and	and	CCONJ
fcis-26112	215	9	characteristics	characteristic	NOUN
fcis-26112	215	10	.	.	PUNCT
fcis-26112	215	11	"	"	PUNCT
fcis-26112	216	1	arxiv	arxiv	PROPN
fcis-26112	216	2	preprint	preprint	NOUN
fcis-26112	216	3	arxiv:1107	arxiv:1107	PROPN
fcis-26112	216	4	.	.	PROPN
fcis-26112	217	1	1834	1834	NUM
fcis-26112	217	2	(	(	PUNCT
fcis-26112	217	3	2011	2011	NUM
fcis-26112	217	4	)	)	PUNCT
fcis-26112	217	5	.	.	PUNCT
fcis-26112	218	1	[	[	X
fcis-26112	218	2	18	18	NUM
fcis-26112	218	3	]	]	X
fcis-26112	218	4	kumar	kumar	PROPN
fcis-26112	218	5	,	,	PUNCT
fcis-26112	218	6	santosh	santosh	PROPN
fcis-26112	218	7	,	,	PUNCT
fcis-26112	218	8	et	et	PROPN
fcis-26112	218	9	al	al	PROPN
fcis-26112	218	10	.	.	PUNCT
fcis-26112	219	1	"	"	PUNCT
fcis-26112	219	2	the	the	DET
fcis-26112	219	3	six	six	NUM
fcis-26112	219	4	decades	decade	NOUN
fcis-26112	219	5	of	of	ADP
fcis-26112	219	6	the	the	DET
fcis-26112	219	7	capital	capital	NOUN
fcis-26112	219	8	asset	asset	NOUN
fcis-26112	219	9	pricing	pricing	NOUN
fcis-26112	219	10	model	model	NOUN
fcis-26112	219	11	:	:	PUNCT
fcis-26112	219	12	a	a	DET
fcis-26112	219	13	research	research	NOUN
fcis-26112	219	14	agenda	agenda	NOUN
fcis-26112	219	15	.	.	PUNCT
fcis-26112	219	16	"	"	PUNCT
fcis-26112	220	1	journal	journal	NOUN
fcis-26112	220	2	of	of	ADP
fcis-26112	220	3	risk	risk	NOUN
fcis-26112	220	4	and	and	CCONJ
fcis-26112	220	5	financial	financial	ADJ
fcis-26112	220	6	management	management	NOUN
fcis-26112	220	7	16.8	16.8	NUM
fcis-26112	220	8	(	(	PUNCT
fcis-26112	220	9	2023	2023	NUM
fcis-26112	220	10	):	):	PUNCT
fcis-26112	220	11	356	356	NUM
fcis-26112	220	12	.	.	PUNCT