id	sid	tid	token	lemma	pos
fcis-30422	1	1	frontiers	frontier	NOUN
fcis-30422	1	2	in	in	ADP
fcis-30422	1	3	computing	computing	NOUN
fcis-30422	1	4	and	and	CCONJ
fcis-30422	1	5	intelligent	intelligent	ADJ
fcis-30422	1	6	systems	system	NOUN
fcis-30422	1	7	issn	issn	VERB
fcis-30422	1	8	:	:	PUNCT
fcis-30422	1	9	2832	2832	NUM
fcis-30422	1	10	-	-	SYM
fcis-30422	1	11	6024	6024	NUM
fcis-30422	1	12	|	|	NOUN
fcis-30422	1	13	vol	vol	NOUN
fcis-30422	1	14	.	.	PROPN
fcis-30422	2	1	12	12	NUM
fcis-30422	2	2	,	,	PUNCT
fcis-30422	2	3	no	no	INTJ
fcis-30422	2	4	.	.	NOUN
fcis-30422	2	5	1	1	NUM
fcis-30422	2	6	,	,	PUNCT
fcis-30422	2	7	2025	2025	NUM
fcis-30422	2	8	58	58	NUM
fcis-30422	2	9	application	application	NOUN
fcis-30422	2	10	of	of	ADP
fcis-30422	2	11	microbiological	microbiological	ADJ
fcis-30422	2	12	detection	detection	NOUN
fcis-30422	2	13	based	base	VERB
fcis-30422	2	14	on	on	ADP
fcis-30422	2	15	computer	computer	NOUN
fcis-30422	2	16	image	image	NOUN
fcis-30422	2	17	analysis	analysis	NOUN
fcis-30422	2	18	yaqin	yaqin	NOUN
fcis-30422	2	19	zhang	zhang	PROPN
fcis-30422	3	1	*	*	PROPN
fcis-30422	3	2	,	,	PUNCT
fcis-30422	3	3	yan	yan	PROPN
fcis-30422	3	4	zhao	zhao	PROPN
fcis-30422	3	5	,	,	PUNCT
fcis-30422	3	6	tuanjie	tuanjie	PROPN
fcis-30422	3	7	chu	chu	PROPN
fcis-30422	3	8	pharmaceutical	pharmaceutical	NOUN
fcis-30422	3	9	guoxin	guoxin	PROPN
fcis-30422	3	10	(	(	PUNCT
fcis-30422	3	11	zhejiang	zhejiang	PROPN
fcis-30422	3	12	)	)	PUNCT
fcis-30422	3	13	quality	quality	PROPN
fcis-30422	3	14	technology	technology	PROPN
fcis-30422	3	15	co.	co.	PROPN
fcis-30422	3	16	,	,	PUNCT
fcis-30422	3	17	ltd	ltd	PROPN
fcis-30422	3	18	.	.	PROPN
fcis-30422	4	1	hangzhou	hangzhou	PROPN
fcis-30422	4	2	zhejiang	zhejiang	PROPN
fcis-30422	4	3	,	,	PUNCT
fcis-30422	4	4	310018	310018	NUM
fcis-30422	4	5	,	,	PUNCT
fcis-30422	4	6	china	china	PROPN
fcis-30422	4	7	*	*	PUNCT
fcis-30422	4	8	corresponding	correspond	VERB
fcis-30422	4	9	author	author	NOUN
fcis-30422	4	10	:	:	PUNCT
fcis-30422	4	11	yaqin	yaqin	PROPN
fcis-30422	4	12	zhang	zhang	PROPN
fcis-30422	4	13	(	(	PUNCT
fcis-30422	4	14	email	email	NOUN
fcis-30422	4	15	:	:	PUNCT
fcis-30422	4	16	715521939@qq.com	715521939@qq.com	NUM
fcis-30422	4	17	)	)	PUNCT
fcis-30422	4	18	abstract	abstract	NOUN
fcis-30422	4	19	:	:	PUNCT
fcis-30422	4	20	microorganisms	microorganism	NOUN
fcis-30422	4	21	play	play	VERB
fcis-30422	4	22	an	an	DET
fcis-30422	4	23	important	important	ADJ
fcis-30422	4	24	role	role	NOUN
fcis-30422	4	25	in	in	ADP
fcis-30422	4	26	human	human	ADJ
fcis-30422	4	27	society	society	NOUN
fcis-30422	4	28	,	,	PUNCT
fcis-30422	4	29	and	and	CCONJ
fcis-30422	4	30	the	the	DET
fcis-30422	4	31	analysis	analysis	NOUN
fcis-30422	4	32	of	of	ADP
fcis-30422	4	33	microorganisms	microorganism	NOUN
fcis-30422	4	34	is	be	AUX
fcis-30422	4	35	of	of	ADP
fcis-30422	4	36	great	great	ADJ
fcis-30422	4	37	significance	significance	NOUN
fcis-30422	4	38	.	.	PUNCT
fcis-30422	5	1	traditional	traditional	ADJ
fcis-30422	5	2	microbial	microbial	ADJ
fcis-30422	5	3	detection	detection	NOUN
fcis-30422	5	4	methods	method	NOUN
fcis-30422	5	5	based	base	VERB
fcis-30422	5	6	on	on	ADP
fcis-30422	5	7	microscopes	microscope	NOUN
fcis-30422	5	8	have	have	VERB
fcis-30422	5	9	some	some	DET
fcis-30422	5	10	defects	defect	NOUN
fcis-30422	5	11	,	,	PUNCT
fcis-30422	5	12	and	and	CCONJ
fcis-30422	5	13	more	more	ADV
fcis-30422	5	14	effective	effective	ADJ
fcis-30422	5	15	methods	method	NOUN
fcis-30422	5	16	are	be	AUX
fcis-30422	5	17	needed	need	VERB
fcis-30422	5	18	to	to	PART
fcis-30422	5	19	achieve	achieve	VERB
fcis-30422	5	20	rapid	rapid	ADJ
fcis-30422	5	21	and	and	CCONJ
fcis-30422	5	22	accurate	accurate	ADJ
fcis-30422	5	23	analysis	analysis	NOUN
fcis-30422	5	24	.	.	PUNCT
fcis-30422	6	1	this	this	DET
fcis-30422	6	2	paper	paper	NOUN
fcis-30422	6	3	studies	study	VERB
fcis-30422	6	4	the	the	DET
fcis-30422	6	5	microbial	microbial	ADJ
fcis-30422	6	6	detection	detection	NOUN
fcis-30422	6	7	methods	method	NOUN
fcis-30422	6	8	based	base	VERB
fcis-30422	6	9	on	on	ADP
fcis-30422	6	10	computer	computer	NOUN
fcis-30422	6	11	image	image	NOUN
fcis-30422	6	12	analysis	analysis	NOUN
fcis-30422	6	13	technology	technology	NOUN
fcis-30422	6	14	,	,	PUNCT
fcis-30422	6	15	and	and	CCONJ
fcis-30422	6	16	introduces	introduce	VERB
fcis-30422	6	17	three	three	NUM
fcis-30422	6	18	main	main	ADJ
fcis-30422	6	19	methods	method	NOUN
fcis-30422	6	20	in	in	ADP
fcis-30422	6	21	detail	detail	NOUN
fcis-30422	6	22	,	,	PUNCT
fcis-30422	6	23	including	include	VERB
fcis-30422	6	24	methods	method	NOUN
fcis-30422	6	25	based	base	VERB
fcis-30422	6	26	on	on	ADP
fcis-30422	6	27	classical	classical	ADJ
fcis-30422	6	28	image	image	NOUN
fcis-30422	6	29	processing	processing	NOUN
fcis-30422	6	30	,	,	PUNCT
fcis-30422	6	31	traditional	traditional	ADJ
fcis-30422	6	32	machine	machine	NOUN
fcis-30422	6	33	learning	learning	NOUN
fcis-30422	6	34	,	,	PUNCT
fcis-30422	6	35	and	and	CCONJ
fcis-30422	6	36	deep	deep	ADJ
fcis-30422	6	37	learning	learning	NOUN
fcis-30422	6	38	.	.	PUNCT
fcis-30422	7	1	the	the	DET
fcis-30422	7	2	main	main	ADJ
fcis-30422	7	3	implementation	implementation	NOUN
fcis-30422	7	4	steps	step	NOUN
fcis-30422	7	5	and	and	CCONJ
fcis-30422	7	6	shortcomings	shortcoming	NOUN
fcis-30422	7	7	of	of	ADP
fcis-30422	7	8	various	various	ADJ
fcis-30422	7	9	methods	method	NOUN
fcis-30422	7	10	are	be	AUX
fcis-30422	7	11	analyzed	analyze	VERB
fcis-30422	7	12	.	.	PUNCT
fcis-30422	8	1	finally	finally	ADV
fcis-30422	8	2	,	,	PUNCT
fcis-30422	8	3	this	this	DET
fcis-30422	8	4	paper	paper	NOUN
fcis-30422	8	5	points	point	VERB
fcis-30422	8	6	out	out	ADP
fcis-30422	8	7	the	the	DET
fcis-30422	8	8	current	current	ADJ
fcis-30422	8	9	challenges	challenge	NOUN
fcis-30422	8	10	and	and	CCONJ
fcis-30422	8	11	research	research	NOUN
fcis-30422	8	12	directions	direction	NOUN
fcis-30422	8	13	of	of	ADP
fcis-30422	8	14	microbial	microbial	ADJ
fcis-30422	8	15	detection	detection	NOUN
fcis-30422	8	16	technology	technology	NOUN
fcis-30422	8	17	based	base	VERB
fcis-30422	8	18	on	on	ADP
fcis-30422	8	19	computer	computer	NOUN
fcis-30422	8	20	image	image	NOUN
fcis-30422	8	21	analysis	analysis	NOUN
fcis-30422	8	22	,	,	PUNCT
fcis-30422	8	23	and	and	CCONJ
fcis-30422	8	24	provides	provide	VERB
fcis-30422	8	25	a	a	DET
fcis-30422	8	26	theoretical	theoretical	ADJ
fcis-30422	8	27	basis	basis	NOUN
fcis-30422	8	28	for	for	ADP
fcis-30422	8	29	promoting	promote	VERB
fcis-30422	8	30	microbial	microbial	ADJ
fcis-30422	8	31	detection	detection	NOUN
fcis-30422	8	32	technology	technology	NOUN
fcis-30422	8	33	based	base	VERB
fcis-30422	8	34	on	on	ADP
fcis-30422	8	35	computer	computer	NOUN
fcis-30422	8	36	image	image	NOUN
fcis-30422	8	37	analysis	analysis	NOUN
fcis-30422	8	38	.	.	PUNCT
fcis-30422	9	1	keywords	keyword	NOUN
fcis-30422	9	2	:	:	PUNCT
fcis-30422	9	3	microbial	microbial	ADJ
fcis-30422	9	4	detection	detection	NOUN
fcis-30422	9	5	;	;	PUNCT
fcis-30422	9	6	computer	computer	NOUN
fcis-30422	9	7	image	image	NOUN
fcis-30422	9	8	analysis	analysis	NOUN
fcis-30422	9	9	;	;	PUNCT
fcis-30422	9	10	machine	machine	NOUN
fcis-30422	9	11	learning	learning	NOUN
fcis-30422	9	12	;	;	PUNCT
fcis-30422	9	13	deep	deep	ADJ
fcis-30422	9	14	learning	learning	NOUN
fcis-30422	9	15	;	;	PUNCT
fcis-30422	9	16	image	image	NOUN
fcis-30422	9	17	processing	processing	NOUN
fcis-30422	9	18	.	.	PUNCT
fcis-30422	10	1	1	1	X
fcis-30422	10	2	.	.	X
fcis-30422	10	3	introduction	introduction	NOUN
fcis-30422	10	4	microorganisms	microorganism	NOUN
fcis-30422	10	5	are	be	AUX
fcis-30422	10	6	tiny	tiny	ADJ
fcis-30422	10	7	organisms	organism	NOUN
fcis-30422	10	8	with	with	ADP
fcis-30422	10	9	independent	independent	ADJ
fcis-30422	10	10	life	life	NOUN
fcis-30422	10	11	functions	function	NOUN
fcis-30422	10	12	that	that	PRON
fcis-30422	10	13	can	can	AUX
fcis-30422	10	14	absorb	absorb	VERB
fcis-30422	10	15	energy	energy	NOUN
fcis-30422	10	16	,	,	PUNCT
fcis-30422	10	17	grow	grow	VERB
fcis-30422	10	18	and	and	CCONJ
fcis-30422	10	19	reproduce	reproduce	VERB
fcis-30422	10	20	on	on	ADP
fcis-30422	10	21	their	their	PRON
fcis-30422	10	22	own	own	ADJ
fcis-30422	10	23	,	,	PUNCT
fcis-30422	10	24	and	and	CCONJ
fcis-30422	10	25	can	can	AUX
fcis-30422	10	26	exist	exist	VERB
fcis-30422	10	27	in	in	ADP
fcis-30422	10	28	various	various	ADJ
fcis-30422	10	29	ecosystems	ecosystem	NOUN
fcis-30422	10	30	[	[	X
fcis-30422	10	31	1	1	NUM
fcis-30422	10	32	]	]	PUNCT
fcis-30422	10	33	.	.	PUNCT
fcis-30422	11	1	microorganisms	microorganism	NOUN
fcis-30422	11	2	play	play	VERB
fcis-30422	11	3	an	an	DET
fcis-30422	11	4	important	important	ADJ
fcis-30422	11	5	role	role	NOUN
fcis-30422	11	6	in	in	ADP
fcis-30422	11	7	human	human	ADJ
fcis-30422	11	8	society	society	NOUN
fcis-30422	11	9	.	.	PUNCT
fcis-30422	12	1	for	for	ADP
fcis-30422	12	2	example	example	NOUN
fcis-30422	12	3	,	,	PUNCT
fcis-30422	12	4	some	some	DET
fcis-30422	12	5	rhizobia	rhizobia	NOUN
fcis-30422	12	6	can	can	AUX
fcis-30422	12	7	have	have	VERB
fcis-30422	12	8	a	a	DET
fcis-30422	12	9	beneficial	beneficial	ADJ
fcis-30422	12	10	effect	effect	NOUN
fcis-30422	12	11	on	on	ADP
fcis-30422	12	12	plant	plant	NOUN
fcis-30422	12	13	health	health	NOUN
fcis-30422	12	14	and	and	CCONJ
fcis-30422	12	15	growth	growth	NOUN
fcis-30422	12	16	,	,	PUNCT
fcis-30422	12	17	and	and	CCONJ
fcis-30422	12	18	can	can	AUX
fcis-30422	12	19	also	also	ADV
fcis-30422	12	20	inhibit	inhibit	VERB
fcis-30422	12	21	pathogenic	pathogenic	ADJ
fcis-30422	12	22	microorganisms	microorganism	NOUN
fcis-30422	12	23	[	[	X
fcis-30422	12	24	2	2	NUM
fcis-30422	12	25	]	]	PUNCT
fcis-30422	12	26	.	.	PUNCT
fcis-30422	13	1	lactic	lactic	ADJ
fcis-30422	13	2	acid	acid	NOUN
fcis-30422	13	3	bacteria	bacteria	NOUN
fcis-30422	13	4	can	can	AUX
fcis-30422	13	5	affect	affect	VERB
fcis-30422	13	6	humans	human	NOUN
fcis-30422	13	7	in	in	ADP
fcis-30422	13	8	many	many	ADJ
fcis-30422	13	9	ways	way	NOUN
fcis-30422	13	10	,	,	PUNCT
fcis-30422	13	11	such	such	ADJ
fcis-30422	13	12	as	as	ADP
fcis-30422	13	13	regulating	regulate	VERB
fcis-30422	13	14	gastrointestinal	gastrointestinal	ADJ
fcis-30422	13	15	flora	flora	NOUN
fcis-30422	13	16	,	,	PUNCT
fcis-30422	13	17	the	the	DET
fcis-30422	13	18	normal	normal	ADJ
fcis-30422	13	19	operation	operation	NOUN
fcis-30422	13	20	of	of	ADP
fcis-30422	13	21	human	human	ADJ
fcis-30422	13	22	metabolism	metabolism	NOUN
fcis-30422	13	23	,	,	PUNCT
fcis-30422	13	24	and	and	CCONJ
fcis-30422	13	25	inhibiting	inhibit	VERB
fcis-30422	13	26	the	the	DET
fcis-30422	13	27	reproduction	reproduction	NOUN
fcis-30422	13	28	of	of	ADP
fcis-30422	13	29	harmful	harmful	ADJ
fcis-30422	13	30	bacteria	bacteria	NOUN
fcis-30422	14	1	[	[	X
fcis-30422	14	2	3	3	NUM
fcis-30422	14	3	]	]	PUNCT
fcis-30422	14	4	.	.	PUNCT
fcis-30422	15	1	severe	severe	ADJ
fcis-30422	15	2	acute	acute	ADJ
fcis-30422	15	3	respiratory	respiratory	ADJ
fcis-30422	15	4	syndrome	syndrome	NOUN
fcis-30422	15	5	coronavirus	coronavirus	NOUN
fcis-30422	15	6	2	2	NUM
fcis-30422	15	7	(	(	PUNCT
fcis-30422	15	8	sars	sar	NOUN
fcis-30422	15	9	-	-	PUNCT
fcis-30422	15	10	cov-2	cov-2	NOUN
fcis-30422	15	11	)	)	PUNCT
fcis-30422	15	12	can	can	AUX
fcis-30422	15	13	cause	cause	VERB
fcis-30422	15	14	fever	fever	NOUN
fcis-30422	15	15	,	,	PUNCT
fcis-30422	15	16	malaise	malaise	NOUN
fcis-30422	15	17	,	,	PUNCT
fcis-30422	15	18	dry	dry	ADJ
fcis-30422	15	19	cough	cough	NOUN
fcis-30422	15	20	,	,	PUNCT
fcis-30422	15	21	shortness	shortness	NOUN
fcis-30422	15	22	of	of	ADP
fcis-30422	15	23	breath	breath	NOUN
fcis-30422	15	24	,	,	PUNCT
fcis-30422	15	25	and	and	CCONJ
fcis-30422	15	26	even	even	ADV
fcis-30422	15	27	death	death	NOUN
fcis-30422	15	28	in	in	ADP
fcis-30422	15	29	severe	severe	ADJ
fcis-30422	15	30	cases	case	NOUN
fcis-30422	15	31	[	[	X
fcis-30422	15	32	4	4	NUM
fcis-30422	15	33	]	]	PUNCT
fcis-30422	15	34	.	.	PUNCT
fcis-30422	16	1	it	it	PRON
fcis-30422	16	2	can	can	AUX
fcis-30422	16	3	be	be	AUX
fcis-30422	16	4	seen	see	VERB
fcis-30422	16	5	that	that	SCONJ
fcis-30422	16	6	the	the	DET
fcis-30422	16	7	analysis	analysis	NOUN
fcis-30422	16	8	of	of	ADP
fcis-30422	16	9	microorganisms	microorganism	NOUN
fcis-30422	16	10	is	be	AUX
fcis-30422	16	11	of	of	ADP
fcis-30422	16	12	great	great	ADJ
fcis-30422	16	13	significance	significance	NOUN
fcis-30422	16	14	to	to	ADP
fcis-30422	16	15	humans	human	NOUN
fcis-30422	16	16	.	.	PUNCT
fcis-30422	17	1	microscopic	microscopic	ADJ
fcis-30422	17	2	observation	observation	NOUN
fcis-30422	17	3	is	be	AUX
fcis-30422	17	4	a	a	DET
fcis-30422	17	5	common	common	ADJ
fcis-30422	17	6	and	and	CCONJ
fcis-30422	17	7	important	important	ADJ
fcis-30422	17	8	method	method	NOUN
fcis-30422	17	9	in	in	ADP
fcis-30422	17	10	microbial	microbial	ADJ
fcis-30422	17	11	analysis	analysis	NOUN
fcis-30422	17	12	.	.	PUNCT
fcis-30422	18	1	for	for	ADP
fcis-30422	18	2	example	example	NOUN
fcis-30422	18	3	,	,	PUNCT
fcis-30422	18	4	stereo	stereo	NOUN
fcis-30422	18	5	scanning	scanning	NOUN
fcis-30422	18	6	electron	electron	NOUN
fcis-30422	18	7	microscopy	microscopy	NOUN
fcis-30422	18	8	is	be	AUX
fcis-30422	18	9	used	use	VERB
fcis-30422	18	10	to	to	PART
fcis-30422	18	11	analyze	analyze	VERB
fcis-30422	18	12	microorganisms	microorganism	NOUN
fcis-30422	18	13	in	in	ADP
fcis-30422	18	14	soil	soil	NOUN
fcis-30422	18	15	[	[	X
fcis-30422	18	16	5	5	NUM
fcis-30422	18	17	]	]	PUNCT
fcis-30422	18	18	,	,	PUNCT
fcis-30422	18	19	aquatic	aquatic	ADJ
fcis-30422	18	20	bacteria	bacteria	NOUN
fcis-30422	18	21	are	be	AUX
fcis-30422	18	22	counted	count	VERB
fcis-30422	18	23	using	use	VERB
fcis-30422	18	24	improved	improve	VERB
fcis-30422	18	25	epifluorescence	epifluorescence	NOUN
fcis-30422	18	26	technology	technology	NOUN
fcis-30422	18	27	based	base	VERB
fcis-30422	18	28	on	on	ADP
fcis-30422	18	29	microscopes	microscope	NOUN
fcis-30422	18	30	[	[	X
fcis-30422	18	31	6	6	NUM
fcis-30422	18	32	]	]	PUNCT
fcis-30422	18	33	,	,	PUNCT
fcis-30422	18	34	and	and	CCONJ
fcis-30422	18	35	microbial	microbial	ADJ
fcis-30422	18	36	analysis	analysis	NOUN
fcis-30422	18	37	is	be	AUX
fcis-30422	18	38	performed	perform	VERB
fcis-30422	18	39	using	use	VERB
fcis-30422	18	40	environmental	environmental	ADJ
fcis-30422	18	41	scanning	scanning	NOUN
fcis-30422	18	42	electron	electron	NOUN
fcis-30422	18	43	microscopy	microscopy	NOUN
fcis-30422	19	1	[	[	X
fcis-30422	19	2	7	7	NUM
fcis-30422	19	3	]	]	PUNCT
fcis-30422	19	4	.	.	PUNCT
fcis-30422	20	1	however	however	ADV
fcis-30422	20	2	,	,	PUNCT
fcis-30422	20	3	these	these	DET
fcis-30422	20	4	microscopic	microscopic	ADJ
fcis-30422	20	5	methods	method	NOUN
fcis-30422	20	6	have	have	VERB
fcis-30422	20	7	some	some	DET
fcis-30422	20	8	disadvantages	disadvantage	NOUN
fcis-30422	20	9	.	.	PUNCT
fcis-30422	21	1	according	accord	VERB
fcis-30422	21	2	to	to	ADP
fcis-30422	21	3	locey	locey	PROPN
fcis-30422	21	4	et	et	PROPN
fcis-30422	21	5	al	al	PROPN
fcis-30422	21	6	.	.	PROPN
fcis-30422	21	7	,	,	PUNCT
fcis-30422	21	8	there	there	PRON
fcis-30422	21	9	are	be	VERB
fcis-30422	21	10	1011	1011	NUM
fcis-30422	21	11	to	to	ADP
fcis-30422	21	12	1012	1012	NUM
fcis-30422	21	13	species	specie	NOUN
fcis-30422	21	14	of	of	ADP
fcis-30422	21	15	microorganisms	microorganism	NOUN
fcis-30422	21	16	living	live	VERB
fcis-30422	21	17	on	on	ADP
fcis-30422	21	18	the	the	DET
fcis-30422	21	19	earth	earth	NOUN
fcis-30422	21	20	[	[	X
fcis-30422	21	21	8	8	NUM
fcis-30422	21	22	]	]	PUNCT
fcis-30422	21	23	.	.	PUNCT
fcis-30422	22	1	therefore	therefore	ADV
fcis-30422	22	2	,	,	PUNCT
fcis-30422	22	3	when	when	SCONJ
fcis-30422	22	4	researchers	researcher	NOUN
fcis-30422	22	5	use	use	VERB
fcis-30422	22	6	this	this	DET
fcis-30422	22	7	method	method	NOUN
fcis-30422	22	8	for	for	ADP
fcis-30422	22	9	microbial	microbial	ADJ
fcis-30422	22	10	analysis	analysis	NOUN
fcis-30422	22	11	,	,	PUNCT
fcis-30422	22	12	they	they	PRON
fcis-30422	22	13	often	often	ADV
fcis-30422	22	14	have	have	VERB
fcis-30422	22	15	to	to	PART
fcis-30422	22	16	consult	consult	VERB
fcis-30422	22	17	a	a	DET
fcis-30422	22	18	large	large	ADJ
fcis-30422	22	19	amount	amount	NOUN
fcis-30422	22	20	of	of	ADP
fcis-30422	22	21	literature	literature	NOUN
fcis-30422	22	22	.	.	PUNCT
fcis-30422	23	1	secondly	secondly	ADV
fcis-30422	23	2	,	,	PUNCT
fcis-30422	23	3	this	this	DET
fcis-30422	23	4	type	type	NOUN
fcis-30422	23	5	of	of	ADP
fcis-30422	23	6	professional	professional	ADJ
fcis-30422	23	7	method	method	NOUN
fcis-30422	23	8	requires	require	VERB
fcis-30422	23	9	researchers	researcher	NOUN
fcis-30422	23	10	to	to	PART
fcis-30422	23	11	undergo	undergo	VERB
fcis-30422	23	12	long	long	ADJ
fcis-30422	23	13	-	-	PUNCT
fcis-30422	23	14	term	term	NOUN
fcis-30422	23	15	professional	professional	ADJ
fcis-30422	23	16	training	training	NOUN
fcis-30422	23	17	,	,	PUNCT
fcis-30422	23	18	and	and	CCONJ
fcis-30422	23	19	the	the	DET
fcis-30422	23	20	detection	detection	NOUN
fcis-30422	23	21	process	process	NOUN
fcis-30422	23	22	takes	take	VERB
fcis-30422	23	23	a	a	DET
fcis-30422	23	24	long	long	ADJ
fcis-30422	23	25	time	time	NOUN
fcis-30422	23	26	.	.	PUNCT
fcis-30422	24	1	for	for	ADP
fcis-30422	24	2	example	example	NOUN
fcis-30422	24	3	,	,	PUNCT
fcis-30422	24	4	using	use	VERB
fcis-30422	24	5	traditional	traditional	ADJ
fcis-30422	24	6	microscopy	microscopy	NOUN
fcis-30422	24	7	methods	method	NOUN
fcis-30422	24	8	to	to	PART
fcis-30422	24	9	count	count	VERB
fcis-30422	24	10	phytoplankton	phytoplankton	NOUN
fcis-30422	24	11	takes	take	VERB
fcis-30422	24	12	a	a	DET
fcis-30422	24	13	very	very	ADV
fcis-30422	24	14	long	long	ADJ
fcis-30422	24	15	time	time	NOUN
fcis-30422	24	16	,	,	PUNCT
fcis-30422	24	17	and	and	CCONJ
fcis-30422	24	18	the	the	DET
fcis-30422	24	19	work	work	NOUN
fcis-30422	24	20	is	be	AUX
fcis-30422	24	21	boring	boring	ADJ
fcis-30422	24	22	and	and	CCONJ
fcis-30422	24	23	labor	labor	NOUN
fcis-30422	24	24	-	-	PUNCT
fcis-30422	24	25	intensive	intensive	ADJ
fcis-30422	24	26	.	.	PUNCT
fcis-30422	25	1	in	in	ADP
fcis-30422	25	2	addition	addition	NOUN
fcis-30422	25	3	,	,	PUNCT
fcis-30422	25	4	the	the	DET
fcis-30422	25	5	microorganisms	microorganism	NOUN
fcis-30422	25	6	to	to	PART
fcis-30422	25	7	be	be	AUX
fcis-30422	25	8	analyzed	analyze	VERB
fcis-30422	25	9	are	be	AUX
fcis-30422	25	10	often	often	ADV
fcis-30422	25	11	large	large	ADJ
fcis-30422	25	12	in	in	ADP
fcis-30422	25	13	magnitude	magnitude	NOUN
fcis-30422	25	14	.	.	PUNCT
fcis-30422	26	1	microscopic	microscopic	ADJ
fcis-30422	26	2	methods	method	NOUN
fcis-30422	26	3	are	be	AUX
fcis-30422	26	4	difficult	difficult	ADJ
fcis-30422	26	5	to	to	PART
fcis-30422	26	6	handle	handle	VERB
fcis-30422	26	7	analytical	analytical	ADJ
fcis-30422	26	8	problems	problem	NOUN
fcis-30422	26	9	with	with	ADP
fcis-30422	26	10	large	large	ADJ
fcis-30422	26	11	data	datum	NOUN
fcis-30422	26	12	volumes	volume	NOUN
fcis-30422	26	13	,	,	PUNCT
fcis-30422	26	14	and	and	CCONJ
fcis-30422	26	15	large	large	ADJ
fcis-30422	26	16	sample	sample	NOUN
fcis-30422	26	17	sizes	size	NOUN
fcis-30422	26	18	will	will	AUX
fcis-30422	26	19	affect	affect	VERB
fcis-30422	26	20	the	the	DET
fcis-30422	26	21	accuracy	accuracy	NOUN
fcis-30422	26	22	of	of	ADP
fcis-30422	26	23	the	the	DET
fcis-30422	26	24	operator	operator	NOUN
fcis-30422	26	25	's	's	PART
fcis-30422	26	26	analysis	analysis	NOUN
fcis-30422	26	27	[	[	X
fcis-30422	26	28	9	9	NUM
fcis-30422	26	29	]	]	PUNCT
fcis-30422	26	30	.	.	PUNCT
fcis-30422	27	1	in	in	ADP
fcis-30422	27	2	view	view	NOUN
fcis-30422	27	3	of	of	ADP
fcis-30422	27	4	the	the	DET
fcis-30422	27	5	shortcomings	shortcoming	NOUN
fcis-30422	27	6	of	of	ADP
fcis-30422	27	7	the	the	DET
fcis-30422	27	8	above	above	ADJ
fcis-30422	27	9	microscopy	microscopy	NOUN
fcis-30422	27	10	method	method	NOUN
fcis-30422	27	11	,	,	PUNCT
fcis-30422	27	12	a	a	DET
fcis-30422	27	13	more	more	ADV
fcis-30422	27	14	effective	effective	ADJ
fcis-30422	27	15	method	method	NOUN
fcis-30422	27	16	is	be	AUX
fcis-30422	27	17	needed	need	VERB
fcis-30422	27	18	to	to	PART
fcis-30422	27	19	achieve	achieve	VERB
fcis-30422	27	20	fast	fast	ADJ
fcis-30422	27	21	and	and	CCONJ
fcis-30422	27	22	accurate	accurate	ADJ
fcis-30422	27	23	microbial	microbial	ADJ
fcis-30422	27	24	analysis	analysis	NOUN
fcis-30422	27	25	.	.	PUNCT
fcis-30422	28	1	with	with	ADP
fcis-30422	28	2	the	the	DET
fcis-30422	28	3	continuous	continuous	ADJ
fcis-30422	28	4	development	development	NOUN
fcis-30422	28	5	of	of	ADP
fcis-30422	28	6	science	science	NOUN
fcis-30422	28	7	and	and	CCONJ
fcis-30422	28	8	technology	technology	NOUN
fcis-30422	28	9	,	,	PUNCT
fcis-30422	28	10	researchers	researcher	NOUN
fcis-30422	28	11	have	have	AUX
fcis-30422	28	12	tried	try	VERB
fcis-30422	28	13	to	to	PART
fcis-30422	28	14	apply	apply	VERB
fcis-30422	28	15	computer	computer	NOUN
fcis-30422	28	16	image	image	NOUN
fcis-30422	28	17	analysis	analysis	NOUN
fcis-30422	28	18	technology	technology	NOUN
fcis-30422	28	19	to	to	ADP
fcis-30422	28	20	microbial	microbial	ADJ
fcis-30422	28	21	detection	detection	NOUN
fcis-30422	28	22	and	and	CCONJ
fcis-30422	28	23	achieved	achieve	VERB
fcis-30422	28	24	good	good	ADJ
fcis-30422	28	25	results	result	NOUN
fcis-30422	28	26	.	.	PUNCT
fcis-30422	29	1	this	this	DET
fcis-30422	29	2	paper	paper	NOUN
fcis-30422	29	3	studies	study	VERB
fcis-30422	29	4	the	the	DET
fcis-30422	29	5	detection	detection	NOUN
fcis-30422	29	6	method	method	NOUN
fcis-30422	29	7	of	of	ADP
fcis-30422	29	8	microorganisms	microorganism	NOUN
fcis-30422	29	9	,	,	PUNCT
fcis-30422	29	10	studies	study	VERB
fcis-30422	29	11	the	the	DET
fcis-30422	29	12	principles	principle	NOUN
fcis-30422	29	13	of	of	ADP
fcis-30422	29	14	microbial	microbial	ADJ
fcis-30422	29	15	detection	detection	NOUN
fcis-30422	29	16	methods	method	NOUN
fcis-30422	29	17	based	base	VERB
fcis-30422	29	18	on	on	ADP
fcis-30422	29	19	computer	computer	NOUN
fcis-30422	29	20	image	image	NOUN
fcis-30422	29	21	analysis	analysis	NOUN
fcis-30422	29	22	technology	technology	NOUN
fcis-30422	29	23	,	,	PUNCT
fcis-30422	29	24	and	and	CCONJ
fcis-30422	29	25	introduces	introduce	VERB
fcis-30422	29	26	methods	method	NOUN
fcis-30422	29	27	based	base	VERB
fcis-30422	29	28	on	on	ADP
fcis-30422	29	29	classical	classical	ADJ
fcis-30422	29	30	image	image	NOUN
fcis-30422	29	31	processing	processing	NOUN
fcis-30422	29	32	,	,	PUNCT
fcis-30422	29	33	methods	method	NOUN
fcis-30422	29	34	based	base	VERB
fcis-30422	29	35	on	on	ADP
fcis-30422	29	36	traditional	traditional	ADJ
fcis-30422	29	37	machine	machine	NOUN
fcis-30422	29	38	learning	learning	NOUN
fcis-30422	29	39	,	,	PUNCT
fcis-30422	29	40	and	and	CCONJ
fcis-30422	29	41	methods	method	NOUN
fcis-30422	29	42	based	base	VERB
fcis-30422	29	43	on	on	ADP
fcis-30422	29	44	deep	deep	ADJ
fcis-30422	29	45	learning	learning	NOUN
fcis-30422	29	46	,	,	PUNCT
fcis-30422	29	47	respectively	respectively	ADV
fcis-30422	29	48	,	,	PUNCT
fcis-30422	29	49	providing	provide	VERB
fcis-30422	29	50	a	a	DET
fcis-30422	29	51	reference	reference	NOUN
fcis-30422	29	52	for	for	ADP
fcis-30422	29	53	future	future	ADJ
fcis-30422	29	54	research	research	NOUN
fcis-30422	29	55	on	on	ADP
fcis-30422	29	56	microbial	microbial	ADJ
fcis-30422	29	57	detection	detection	NOUN
fcis-30422	29	58	.	.	PUNCT
fcis-30422	30	1	2	2	X
fcis-30422	30	2	.	.	X
fcis-30422	30	3	microbial	microbial	ADJ
fcis-30422	30	4	detection	detection	NOUN
fcis-30422	30	5	based	base	VERB
fcis-30422	30	6	on	on	ADP
fcis-30422	30	7	classical	classical	ADJ
fcis-30422	30	8	image	image	NOUN
fcis-30422	30	9	processing	process	VERB
fcis-30422	30	10	the	the	DET
fcis-30422	30	11	microbial	microbial	ADJ
fcis-30422	30	12	detection	detection	NOUN
fcis-30422	30	13	method	method	NOUN
fcis-30422	30	14	based	base	VERB
fcis-30422	30	15	on	on	ADP
fcis-30422	30	16	classical	classical	ADJ
fcis-30422	30	17	image	image	NOUN
fcis-30422	30	18	processing	processing	NOUN
fcis-30422	30	19	mainly	mainly	ADV
fcis-30422	30	20	includes	include	VERB
fcis-30422	30	21	four	four	NUM
fcis-30422	30	22	steps	step	NOUN
fcis-30422	30	23	:	:	PUNCT
fcis-30422	30	24	preprocessing	preprocessing	NOUN
fcis-30422	30	25	,	,	PUNCT
fcis-30422	30	26	segmentation	segmentation	NOUN
fcis-30422	30	27	,	,	PUNCT
fcis-30422	30	28	postprocessing	postprocessing	NOUN
fcis-30422	30	29	and	and	CCONJ
fcis-30422	30	30	classification	classification	NOUN
fcis-30422	30	31	.	.	PUNCT
fcis-30422	31	1	its	its	PRON
fcis-30422	31	2	main	main	ADJ
fcis-30422	31	3	processing	processing	NOUN
fcis-30422	31	4	flow	flow	NOUN
fcis-30422	31	5	and	and	CCONJ
fcis-30422	31	6	common	common	ADJ
fcis-30422	31	7	algorithms	algorithm	NOUN
fcis-30422	31	8	are	be	AUX
fcis-30422	31	9	shown	show	VERB
fcis-30422	31	10	in	in	ADP
fcis-30422	31	11	figure	figure	NOUN
fcis-30422	31	12	1	1	NUM
fcis-30422	31	13	.	.	PUNCT
fcis-30422	31	14	figure	figure	NOUN
fcis-30422	31	15	1	1	NUM
fcis-30422	31	16	.	.	PUNCT
fcis-30422	31	17	processing	processing	NOUN
fcis-30422	31	18	flow	flow	NOUN
fcis-30422	31	19	and	and	CCONJ
fcis-30422	31	20	common	common	ADJ
fcis-30422	31	21	algorithms	algorithm	NOUN
fcis-30422	31	22	of	of	ADP
fcis-30422	31	23	classical	classical	ADJ
fcis-30422	31	24	image	image	NOUN
fcis-30422	31	25	processing	processing	NOUN
fcis-30422	31	26	preprocessing	preprocessing	NOUN
fcis-30422	31	27	aims	aim	NOUN
fcis-30422	31	28	to	to	PART
fcis-30422	31	29	improve	improve	VERB
fcis-30422	31	30	image	image	NOUN
fcis-30422	31	31	quality	quality	NOUN
fcis-30422	31	32	,	,	PUNCT
fcis-30422	31	33	reduce	reduce	VERB
fcis-30422	31	34	noise	noise	NOUN
fcis-30422	31	35	,	,	PUNCT
fcis-30422	31	36	and	and	CCONJ
fcis-30422	31	37	make	make	VERB
fcis-30422	31	38	the	the	DET
fcis-30422	31	39	area	area	NOUN
fcis-30422	31	40	of	of	ADP
fcis-30422	31	41	interest	interest	NOUN
fcis-30422	31	42	or	or	CCONJ
fcis-30422	31	43	target	target	NOUN
fcis-30422	31	44	in	in	ADP
fcis-30422	31	45	the	the	DET
fcis-30422	31	46	image	image	NOUN
fcis-30422	31	47	clearer	clear	ADJ
fcis-30422	31	48	by	by	ADP
fcis-30422	31	49	adjusting	adjust	VERB
fcis-30422	31	50	parameters	parameter	NOUN
fcis-30422	31	51	such	such	ADJ
fcis-30422	31	52	as	as	ADP
fcis-30422	31	53	image	image	NOUN
fcis-30422	31	54	contrast	contrast	NOUN
fcis-30422	31	55	and	and	CCONJ
fcis-30422	31	56	brightness	brightness	NOUN
fcis-30422	31	57	,	,	PUNCT
fcis-30422	31	58	thereby	thereby	ADV
fcis-30422	31	59	improving	improve	VERB
fcis-30422	31	60	the	the	DET
fcis-30422	31	61	effect	effect	NOUN
fcis-30422	31	62	of	of	ADP
fcis-30422	31	63	subsequent	subsequent	ADJ
fcis-30422	31	64	processing	processing	NOUN
fcis-30422	31	65	.	.	PUNCT
fcis-30422	32	1	image	image	NOUN
fcis-30422	32	2	segmentation	segmentation	NOUN
fcis-30422	32	3	is	be	AUX
fcis-30422	32	4	the	the	DET
fcis-30422	32	5	process	process	NOUN
fcis-30422	32	6	of	of	ADP
fcis-30422	32	7	dividing	divide	VERB
fcis-30422	32	8	an	an	DET
fcis-30422	32	9	image	image	NOUN
fcis-30422	32	10	into	into	ADP
fcis-30422	32	11	multiple	multiple	ADJ
fcis-30422	32	12	independent	independent	ADJ
fcis-30422	32	13	regions	region	NOUN
fcis-30422	32	14	,	,	PUNCT
fcis-30422	32	15	aiming	aim	VERB
fcis-30422	32	16	to	to	PART
fcis-30422	32	17	distinguish	distinguish	VERB
fcis-30422	32	18	the	the	DET
fcis-30422	32	19	target	target	NOUN
fcis-30422	32	20	of	of	ADP
fcis-30422	32	21	interest	interest	NOUN
fcis-30422	32	22	from	from	ADP
fcis-30422	32	23	the	the	DET
fcis-30422	32	24	background	background	NOUN
fcis-30422	32	25	.	.	PUNCT
fcis-30422	33	1	threshold	threshold	NOUN
fcis-30422	33	2	segmentation	segmentation	NOUN
fcis-30422	33	3	is	be	AUX
fcis-30422	33	4	the	the	DET
fcis-30422	33	5	most	most	ADV
fcis-30422	33	6	widely	widely	ADV
fcis-30422	33	7	used	use	VERB
fcis-30422	33	8	detection	detection	NOUN
fcis-30422	33	9	segmentation	segmentation	NOUN
fcis-30422	33	10	algorithm	algorithm	NOUN
fcis-30422	33	11	at	at	ADP
fcis-30422	33	12	present	present	ADJ
fcis-30422	33	13	.	.	PUNCT
fcis-30422	34	1	the	the	DET
fcis-30422	34	2	algorithm	algorithm	NOUN
fcis-30422	34	3	is	be	AUX
fcis-30422	34	4	simple	simple	ADJ
fcis-30422	34	5	to	to	PART
fcis-30422	34	6	calculate	calculate	VERB
fcis-30422	34	7	and	and	CCONJ
fcis-30422	34	8	has	have	VERB
fcis-30422	34	9	high	high	ADJ
fcis-30422	34	10	computational	computational	ADJ
fcis-30422	34	11	efficiency	efficiency	NOUN
fcis-30422	34	12	.	.	PUNCT
fcis-30422	35	1	threshold	threshold	NOUN
fcis-30422	35	2	segmentation	segmentation	NOUN
fcis-30422	35	3	sets	set	VERB
fcis-30422	35	4	one	one	NUM
fcis-30422	35	5	or	or	CCONJ
fcis-30422	35	6	more	more	ADJ
fcis-30422	35	7	thresholds	threshold	NOUN
fcis-30422	35	8	and	and	CCONJ
fcis-30422	35	9	intercepts	intercept	NOUN
fcis-30422	35	10	pixels	pixel	NOUN
fcis-30422	35	11	whose	whose	DET
fcis-30422	35	12	grayscale	grayscale	NOUN
fcis-30422	35	13	values	value	NOUN
fcis-30422	35	14	59	59	NUM
fcis-30422	35	15	are	be	AUX
fcis-30422	35	16	within	within	ADP
fcis-30422	35	17	the	the	DET
fcis-30422	35	18	threshold	threshold	NOUN
fcis-30422	35	19	range	range	NOUN
fcis-30422	35	20	in	in	ADP
fcis-30422	35	21	the	the	DET
fcis-30422	35	22	image	image	NOUN
fcis-30422	35	23	to	to	PART
fcis-30422	35	24	obtain	obtain	VERB
fcis-30422	35	25	the	the	DET
fcis-30422	35	26	target	target	NOUN
fcis-30422	35	27	in	in	ADP
fcis-30422	35	28	the	the	DET
fcis-30422	35	29	image	image	NOUN
fcis-30422	35	30	.	.	PUNCT
fcis-30422	36	1	the	the	DET
fcis-30422	36	2	calculation	calculation	NOUN
fcis-30422	36	3	process	process	NOUN
fcis-30422	36	4	of	of	ADP
fcis-30422	36	5	the	the	DET
fcis-30422	36	6	otsu	otsu	NOUN
fcis-30422	36	7	threshold	threshold	NOUN
fcis-30422	36	8	is	be	AUX
fcis-30422	36	9	simple	simple	ADJ
fcis-30422	36	10	and	and	CCONJ
fcis-30422	36	11	has	have	VERB
fcis-30422	36	12	strong	strong	ADJ
fcis-30422	36	13	versatility	versatility	NOUN
fcis-30422	36	14	[	[	X
fcis-30422	36	15	10	10	NUM
fcis-30422	36	16	]	]	PUNCT
fcis-30422	36	17	.	.	PUNCT
fcis-30422	37	1	however	however	ADV
fcis-30422	37	2	,	,	PUNCT
fcis-30422	37	3	when	when	SCONJ
fcis-30422	37	4	the	the	DET
fcis-30422	37	5	target	target	NOUN
fcis-30422	37	6	area	area	NOUN
fcis-30422	37	7	is	be	AUX
fcis-30422	37	8	much	much	ADV
fcis-30422	37	9	smaller	small	ADJ
fcis-30422	37	10	than	than	ADP
fcis-30422	37	11	the	the	DET
fcis-30422	37	12	background	background	NOUN
fcis-30422	37	13	area	area	NOUN
fcis-30422	37	14	,	,	PUNCT
fcis-30422	37	15	the	the	DET
fcis-30422	37	16	otsu	otsu	NOUN
fcis-30422	37	17	threshold	threshold	NOUN
fcis-30422	37	18	can	can	AUX
fcis-30422	37	19	not	not	PART
fcis-30422	37	20	provide	provide	VERB
fcis-30422	37	21	good	good	ADJ
fcis-30422	37	22	segmentation	segmentation	NOUN
fcis-30422	37	23	results	result	NOUN
fcis-30422	37	24	[	[	X
fcis-30422	37	25	11	11	NUM
fcis-30422	37	26	]	]	PUNCT
fcis-30422	37	27	.	.	PUNCT
fcis-30422	38	1	post	post	ADJ
fcis-30422	38	2	-	-	ADJ
fcis-30422	38	3	processing	processing	ADJ
fcis-30422	38	4	steps	step	NOUN
fcis-30422	38	5	can	can	AUX
fcis-30422	38	6	be	be	AUX
fcis-30422	38	7	used	use	VERB
fcis-30422	38	8	to	to	PART
fcis-30422	38	9	remove	remove	VERB
fcis-30422	38	10	noise	noise	NOUN
fcis-30422	38	11	caused	cause	VERB
fcis-30422	38	12	by	by	ADP
fcis-30422	38	13	segmentation	segmentation	NOUN
fcis-30422	38	14	errors	error	NOUN
fcis-30422	38	15	,	,	PUNCT
fcis-30422	38	16	refine	refine	VERB
fcis-30422	38	17	segmentation	segmentation	NOUN
fcis-30422	38	18	results	result	NOUN
fcis-30422	38	19	,	,	PUNCT
fcis-30422	38	20	repair	repair	NOUN
fcis-30422	38	21	breaks	break	NOUN
fcis-30422	38	22	,	,	PUNCT
fcis-30422	38	23	etc	etc	X
fcis-30422	38	24	.	.	X
fcis-30422	39	1	classification	classification	NOUN
fcis-30422	39	2	extracts	extract	NOUN
fcis-30422	39	3	feature	feature	NOUN
fcis-30422	39	4	values	value	NOUN
fcis-30422	39	5	that	that	PRON
fcis-30422	39	6	can	can	AUX
fcis-30422	39	7	represent	represent	VERB
fcis-30422	39	8	the	the	DET
fcis-30422	39	9	essential	essential	ADJ
fcis-30422	39	10	attributes	attribute	NOUN
fcis-30422	39	11	of	of	ADP
fcis-30422	39	12	the	the	DET
fcis-30422	39	13	target	target	NOUN
fcis-30422	39	14	object	object	NOUN
fcis-30422	39	15	from	from	ADP
fcis-30422	39	16	the	the	DET
fcis-30422	39	17	image	image	NOUN
fcis-30422	39	18	,	,	PUNCT
fcis-30422	39	19	matches	match	VERB
fcis-30422	39	20	the	the	DET
fcis-30422	39	21	target	target	NOUN
fcis-30422	39	22	object	object	NOUN
fcis-30422	39	23	in	in	ADP
fcis-30422	39	24	the	the	DET
fcis-30422	39	25	image	image	NOUN
fcis-30422	39	26	with	with	ADP
fcis-30422	39	27	the	the	DET
fcis-30422	39	28	reference	reference	NOUN
fcis-30422	39	29	pattern	pattern	NOUN
fcis-30422	39	30	,	,	PUNCT
fcis-30422	39	31	and	and	CCONJ
fcis-30422	39	32	thus	thus	ADV
fcis-30422	39	33	identifies	identify	VERB
fcis-30422	39	34	and	and	CCONJ
fcis-30422	39	35	classifies	classify	VERB
fcis-30422	39	36	the	the	DET
fcis-30422	39	37	target	target	NOUN
fcis-30422	39	38	object	object	NOUN
fcis-30422	39	39	.	.	PUNCT
fcis-30422	40	1	the	the	DET
fcis-30422	40	2	main	main	ADJ
fcis-30422	40	3	classification	classification	NOUN
fcis-30422	40	4	methods	method	NOUN
fcis-30422	40	5	currently	currently	ADV
fcis-30422	40	6	include	include	VERB
fcis-30422	40	7	pattern	pattern	NOUN
fcis-30422	40	8	recognition	recognition	NOUN
fcis-30422	40	9	and	and	CCONJ
fcis-30422	40	10	angle	angle	NOUN
fcis-30422	40	11	threshold	threshold	NOUN
fcis-30422	40	12	recognition	recognition	PROPN
fcis-30422	40	13	.	.	PUNCT
fcis-30422	41	1	however	however	ADV
fcis-30422	41	2	,	,	PUNCT
fcis-30422	41	3	such	such	ADJ
fcis-30422	41	4	methods	method	NOUN
fcis-30422	41	5	are	be	AUX
fcis-30422	41	6	usually	usually	ADV
fcis-30422	41	7	generally	generally	ADV
fcis-30422	41	8	not	not	PART
fcis-30422	41	9	robust	robust	ADJ
fcis-30422	41	10	,	,	PUNCT
fcis-30422	41	11	have	have	AUX
fcis-30422	41	12	high	high	ADJ
fcis-30422	41	13	requirements	requirement	NOUN
fcis-30422	41	14	for	for	ADP
fcis-30422	41	15	the	the	DET
fcis-30422	41	16	accuracy	accuracy	NOUN
fcis-30422	41	17	of	of	ADP
fcis-30422	41	18	the	the	DET
fcis-30422	41	19	segmentation	segmentation	NOUN
fcis-30422	41	20	step	step	NOUN
fcis-30422	41	21	,	,	PUNCT
fcis-30422	41	22	and	and	CCONJ
fcis-30422	41	23	often	often	ADV
fcis-30422	41	24	can	can	AUX
fcis-30422	41	25	not	not	PART
fcis-30422	41	26	achieve	achieve	VERB
fcis-30422	41	27	practical	practical	ADJ
fcis-30422	41	28	application	application	NOUN
fcis-30422	41	29	effects	effect	NOUN
fcis-30422	41	30	.	.	PUNCT
fcis-30422	42	1	methods	method	NOUN
fcis-30422	42	2	based	base	VERB
fcis-30422	42	3	on	on	ADP
fcis-30422	42	4	classical	classical	ADJ
fcis-30422	42	5	image	image	NOUN
fcis-30422	42	6	processing	processing	NOUN
fcis-30422	42	7	have	have	VERB
fcis-30422	42	8	certain	certain	ADJ
fcis-30422	42	9	limitations	limitation	NOUN
fcis-30422	42	10	.	.	PUNCT
fcis-30422	43	1	such	such	ADJ
fcis-30422	43	2	methods	method	NOUN
fcis-30422	43	3	are	be	AUX
fcis-30422	43	4	highly	highly	ADV
fcis-30422	43	5	dependent	dependent	ADJ
fcis-30422	43	6	on	on	ADP
fcis-30422	43	7	expert	expert	ADJ
fcis-30422	43	8	knowledge	knowledge	NOUN
fcis-30422	43	9	and	and	CCONJ
fcis-30422	43	10	manually	manually	ADV
fcis-30422	43	11	designed	design	VERB
fcis-30422	43	12	features	feature	NOUN
fcis-30422	43	13	,	,	PUNCT
fcis-30422	43	14	and	and	CCONJ
fcis-30422	43	15	have	have	VERB
fcis-30422	43	16	limited	limit	VERB
fcis-30422	43	17	robustness	robustness	NOUN
fcis-30422	43	18	.	.	PUNCT
fcis-30422	44	1	moreover	moreover	ADV
fcis-30422	44	2	,	,	PUNCT
fcis-30422	44	3	as	as	ADP
fcis-30422	44	4	the	the	DET
fcis-30422	44	5	amount	amount	NOUN
fcis-30422	44	6	of	of	ADP
fcis-30422	44	7	image	image	NOUN
fcis-30422	44	8	data	data	NOUN
fcis-30422	44	9	increases	increase	NOUN
fcis-30422	44	10	,	,	PUNCT
fcis-30422	44	11	the	the	DET
fcis-30422	44	12	process	process	NOUN
fcis-30422	44	13	of	of	ADP
fcis-30422	44	14	manually	manually	ADV
fcis-30422	44	15	adjusting	adjust	VERB
fcis-30422	44	16	parameters	parameter	NOUN
fcis-30422	44	17	and	and	CCONJ
fcis-30422	44	18	designing	design	VERB
fcis-30422	44	19	features	feature	NOUN
fcis-30422	44	20	becomes	become	VERB
fcis-30422	44	21	increasingly	increasingly	ADV
fcis-30422	44	22	difficult	difficult	ADJ
fcis-30422	44	23	.	.	PUNCT
fcis-30422	45	1	in	in	ADP
fcis-30422	45	2	addition	addition	NOUN
fcis-30422	45	3	,	,	PUNCT
fcis-30422	45	4	classical	classical	ADJ
fcis-30422	45	5	methods	method	NOUN
fcis-30422	45	6	are	be	AUX
fcis-30422	45	7	difficult	difficult	ADJ
fcis-30422	45	8	to	to	PART
fcis-30422	45	9	capture	capture	VERB
fcis-30422	45	10	high	high	ADJ
fcis-30422	45	11	-	-	PUNCT
fcis-30422	45	12	level	level	NOUN
fcis-30422	45	13	abstract	abstract	ADJ
fcis-30422	45	14	features	feature	NOUN
fcis-30422	45	15	and	and	CCONJ
fcis-30422	45	16	can	can	AUX
fcis-30422	45	17	not	not	PART
fcis-30422	45	18	effectively	effectively	ADV
fcis-30422	45	19	mine	mine	VERB
fcis-30422	45	20	the	the	DET
fcis-30422	45	21	rich	rich	ADJ
fcis-30422	45	22	information	information	NOUN
fcis-30422	45	23	contained	contain	VERB
fcis-30422	45	24	in	in	ADP
fcis-30422	45	25	the	the	DET
fcis-30422	45	26	data	datum	NOUN
fcis-30422	45	27	.	.	PUNCT
fcis-30422	46	1	therefore	therefore	ADV
fcis-30422	46	2	,	,	PUNCT
fcis-30422	46	3	researchers	researcher	NOUN
fcis-30422	46	4	have	have	AUX
fcis-30422	46	5	begun	begin	VERB
fcis-30422	46	6	to	to	PART
fcis-30422	46	7	try	try	VERB
fcis-30422	46	8	microbial	microbial	ADJ
fcis-30422	46	9	detection	detection	NOUN
fcis-30422	46	10	methods	method	NOUN
fcis-30422	46	11	based	base	VERB
fcis-30422	46	12	on	on	ADP
fcis-30422	46	13	machine	machine	NOUN
fcis-30422	46	14	learning	learning	NOUN
fcis-30422	46	15	and	and	CCONJ
fcis-30422	46	16	deep	deep	ADJ
fcis-30422	46	17	learning	learning	NOUN
fcis-30422	46	18	.	.	PUNCT
fcis-30422	47	1	3	3	X
fcis-30422	47	2	.	.	X
fcis-30422	47	3	microbial	microbial	ADJ
fcis-30422	47	4	detection	detection	NOUN
fcis-30422	47	5	based	base	VERB
fcis-30422	47	6	on	on	ADP
fcis-30422	47	7	machine	machine	NOUN
fcis-30422	47	8	learning	learn	VERB
fcis-30422	47	9	the	the	DET
fcis-30422	47	10	traditional	traditional	ADJ
fcis-30422	47	11	machine	machine	NOUN
fcis-30422	47	12	learning	learning	NOUN
fcis-30422	47	13	method	method	PROPN
fcis-30422	47	14	introduces	introduce	NOUN
fcis-30422	47	15	machine	machine	NOUN
fcis-30422	47	16	learning	learn	VERB
fcis-30422	47	17	technology	technology	NOUN
fcis-30422	47	18	into	into	ADP
fcis-30422	47	19	microbial	microbial	ADJ
fcis-30422	47	20	detection	detection	NOUN
fcis-30422	47	21	.	.	PUNCT
fcis-30422	48	1	compared	compare	VERB
fcis-30422	48	2	with	with	ADP
fcis-30422	48	3	the	the	DET
fcis-30422	48	4	method	method	NOUN
fcis-30422	48	5	based	base	VERB
fcis-30422	48	6	on	on	ADP
fcis-30422	48	7	classical	classical	ADJ
fcis-30422	48	8	image	image	NOUN
fcis-30422	48	9	processing	processing	NOUN
fcis-30422	48	10	,	,	PUNCT
fcis-30422	48	11	this	this	DET
fcis-30422	48	12	type	type	NOUN
fcis-30422	48	13	of	of	ADP
fcis-30422	48	14	method	method	NOUN
fcis-30422	48	15	can	can	AUX
fcis-30422	48	16	automatically	automatically	ADV
fcis-30422	48	17	learn	learn	VERB
fcis-30422	48	18	feature	feature	NOUN
fcis-30422	48	19	representation	representation	NOUN
fcis-30422	48	20	and	and	CCONJ
fcis-30422	48	21	mine	mine	PRON
fcis-30422	48	22	useful	useful	ADJ
fcis-30422	48	23	patterns	pattern	NOUN
fcis-30422	48	24	from	from	ADP
fcis-30422	48	25	training	train	VERB
fcis-30422	48	26	data	datum	NOUN
fcis-30422	48	27	without	without	ADP
fcis-30422	48	28	manually	manually	ADV
fcis-30422	48	29	designing	design	VERB
fcis-30422	48	30	features	feature	NOUN
fcis-30422	48	31	.	.	PUNCT
fcis-30422	49	1	common	common	ADJ
fcis-30422	49	2	traditional	traditional	ADJ
fcis-30422	49	3	machine	machine	NOUN
fcis-30422	49	4	learning	learn	VERB
fcis-30422	49	5	algorithms	algorithm	NOUN
fcis-30422	49	6	include	include	VERB
fcis-30422	49	7	support	support	NOUN
fcis-30422	49	8	vector	vector	NOUN
fcis-30422	49	9	machine	machine	NOUN
fcis-30422	49	10	(	(	PUNCT
fcis-30422	49	11	svm	svm	PROPN
fcis-30422	49	12	)	)	PUNCT
fcis-30422	49	13	,	,	PUNCT
fcis-30422	49	14	decision	decision	NOUN
fcis-30422	49	15	tree	tree	NOUN
fcis-30422	49	16	,	,	PUNCT
fcis-30422	49	17	random	random	ADJ
fcis-30422	49	18	forest	forest	NOUN
fcis-30422	49	19	,	,	PUNCT
fcis-30422	49	20	naive	naive	ADJ
fcis-30422	49	21	bayes	bayes	NOUN
fcis-30422	49	22	,	,	PUNCT
fcis-30422	49	23	etc	etc	X
fcis-30422	49	24	.	.	X
fcis-30422	49	25	microbial	microbial	ADJ
fcis-30422	49	26	detection	detection	NOUN
fcis-30422	49	27	based	base	VERB
fcis-30422	49	28	on	on	ADP
fcis-30422	49	29	machine	machine	NOUN
fcis-30422	49	30	learning	learning	NOUN
fcis-30422	49	31	is	be	AUX
fcis-30422	49	32	similar	similar	ADJ
fcis-30422	49	33	to	to	ADP
fcis-30422	49	34	the	the	DET
fcis-30422	49	35	method	method	NOUN
fcis-30422	49	36	based	base	VERB
fcis-30422	49	37	on	on	ADP
fcis-30422	49	38	classical	classical	ADJ
fcis-30422	49	39	image	image	NOUN
fcis-30422	49	40	processing	processing	NOUN
fcis-30422	49	41	.	.	PUNCT
fcis-30422	50	1	first	first	ADV
fcis-30422	50	2	,	,	PUNCT
fcis-30422	50	3	the	the	DET
fcis-30422	50	4	image	image	NOUN
fcis-30422	50	5	needs	need	VERB
fcis-30422	50	6	to	to	PART
fcis-30422	50	7	be	be	AUX
fcis-30422	50	8	preprocessed	preprocesse	VERB
fcis-30422	50	9	and	and	CCONJ
fcis-30422	50	10	features	feature	NOUN
fcis-30422	50	11	such	such	ADJ
fcis-30422	50	12	as	as	ADP
fcis-30422	50	13	color	color	NOUN
fcis-30422	50	14	,	,	PUNCT
fcis-30422	50	15	texture	texture	NOUN
fcis-30422	50	16	,	,	PUNCT
fcis-30422	50	17	shape	shape	NOUN
fcis-30422	50	18	,	,	PUNCT
fcis-30422	50	19	etc	etc	X
fcis-30422	50	20	.	.	X
fcis-30422	50	21	need	need	VERB
fcis-30422	50	22	to	to	PART
fcis-30422	50	23	be	be	AUX
fcis-30422	50	24	manually	manually	ADV
fcis-30422	50	25	extracted	extract	VERB
fcis-30422	50	26	from	from	ADP
fcis-30422	50	27	the	the	DET
fcis-30422	50	28	preprocessed	preprocesse	VERB
fcis-30422	50	29	image	image	NOUN
fcis-30422	50	30	.	.	PUNCT
fcis-30422	51	1	the	the	DET
fcis-30422	51	2	second	second	ADJ
fcis-30422	51	3	step	step	NOUN
fcis-30422	51	4	is	be	AUX
fcis-30422	51	5	to	to	PART
fcis-30422	51	6	train	train	VERB
fcis-30422	51	7	the	the	DET
fcis-30422	51	8	classifier	classifier	NOUN
fcis-30422	51	9	.	.	PUNCT
fcis-30422	52	1	using	use	VERB
fcis-30422	52	2	the	the	DET
fcis-30422	52	3	labeled	label	VERB
fcis-30422	52	4	training	training	NOUN
fcis-30422	52	5	data	datum	NOUN
fcis-30422	52	6	set	set	VERB
fcis-30422	52	7	,	,	PUNCT
fcis-30422	52	8	the	the	DET
fcis-30422	52	9	extracted	extract	VERB
fcis-30422	52	10	features	feature	NOUN
fcis-30422	52	11	are	be	AUX
fcis-30422	52	12	input	input	NOUN
fcis-30422	52	13	into	into	ADP
fcis-30422	52	14	the	the	DET
fcis-30422	52	15	machine	machine	NOUN
fcis-30422	52	16	learning	learn	VERB
fcis-30422	52	17	algorithm	algorithm	NOUN
fcis-30422	52	18	to	to	PART
fcis-30422	52	19	train	train	VERB
fcis-30422	52	20	the	the	DET
fcis-30422	52	21	model	model	NOUN
fcis-30422	52	22	.	.	PUNCT
fcis-30422	53	1	the	the	DET
fcis-30422	53	2	trained	train	VERB
fcis-30422	53	3	model	model	NOUN
fcis-30422	53	4	can	can	AUX
fcis-30422	53	5	be	be	AUX
fcis-30422	53	6	used	use	VERB
fcis-30422	53	7	in	in	ADP
fcis-30422	53	8	the	the	DET
fcis-30422	53	9	classification	classification	NOUN
fcis-30422	53	10	and	and	CCONJ
fcis-30422	53	11	detection	detection	NOUN
fcis-30422	53	12	tasks	task	NOUN
fcis-30422	53	13	of	of	ADP
fcis-30422	53	14	new	new	ADJ
fcis-30422	53	15	microbial	microbial	ADJ
fcis-30422	53	16	images	image	NOUN
fcis-30422	53	17	.	.	PUNCT
fcis-30422	54	1	among	among	ADP
fcis-30422	54	2	them	they	PRON
fcis-30422	54	3	,	,	PUNCT
fcis-30422	54	4	the	the	DET
fcis-30422	54	5	most	most	ADV
fcis-30422	54	6	widely	widely	ADV
fcis-30422	54	7	used	use	VERB
fcis-30422	54	8	classification	classification	NOUN
fcis-30422	54	9	model	model	NOUN
fcis-30422	54	10	in	in	ADP
fcis-30422	54	11	microbial	microbial	ADJ
fcis-30422	54	12	detection	detection	NOUN
fcis-30422	54	13	is	be	AUX
fcis-30422	54	14	svm	svm	ADJ
fcis-30422	54	15	and	and	CCONJ
fcis-30422	54	16	its	its	PRON
fcis-30422	54	17	variants	variant	NOUN
fcis-30422	54	18	.	.	PUNCT
fcis-30422	55	1	svm	svm	PROPN
fcis-30422	55	2	can	can	AUX
fcis-30422	55	3	effectively	effectively	ADV
fcis-30422	55	4	use	use	VERB
fcis-30422	55	5	smaller	small	ADJ
fcis-30422	55	6	training	training	NOUN
fcis-30422	55	7	samples	sample	NOUN
fcis-30422	55	8	,	,	PUNCT
fcis-30422	55	9	so	so	SCONJ
fcis-30422	55	10	that	that	SCONJ
fcis-30422	55	11	svm	svm	PROPN
fcis-30422	55	12	can	can	AUX
fcis-30422	55	13	obtain	obtain	VERB
fcis-30422	55	14	higher	high	ADJ
fcis-30422	55	15	classification	classification	NOUN
fcis-30422	55	16	accuracy	accuracy	NOUN
fcis-30422	55	17	on	on	ADP
fcis-30422	55	18	a	a	DET
fcis-30422	55	19	smaller	small	ADJ
fcis-30422	55	20	training	training	NOUN
fcis-30422	55	21	set	set	NOUN
fcis-30422	55	22	[	[	X
fcis-30422	55	23	12	12	NUM
fcis-30422	55	24	]	]	PUNCT
fcis-30422	55	25	.	.	PUNCT
fcis-30422	56	1	however	however	ADV
fcis-30422	56	2	,	,	PUNCT
fcis-30422	56	3	support	support	NOUN
fcis-30422	56	4	vector	vector	NOUN
fcis-30422	56	5	machines	machine	NOUN
fcis-30422	56	6	are	be	AUX
fcis-30422	56	7	not	not	PART
fcis-30422	56	8	suitable	suitable	ADJ
fcis-30422	56	9	for	for	ADP
fcis-30422	56	10	solving	solve	VERB
fcis-30422	56	11	multi	multi	ADJ
fcis-30422	56	12	-	-	ADJ
fcis-30422	56	13	classification	classification	ADJ
fcis-30422	56	14	tasks	task	NOUN
fcis-30422	56	15	[	[	X
fcis-30422	56	16	13	13	NUM
fcis-30422	56	17	]	]	PUNCT
fcis-30422	56	18	.	.	PUNCT
fcis-30422	57	1	in	in	ADP
fcis-30422	57	2	addition	addition	NOUN
fcis-30422	57	3	,	,	PUNCT
fcis-30422	57	4	support	support	NOUN
fcis-30422	57	5	vector	vector	NOUN
fcis-30422	57	6	machines	machine	NOUN
fcis-30422	57	7	are	be	AUX
fcis-30422	57	8	sensitive	sensitive	ADJ
fcis-30422	57	9	to	to	ADP
fcis-30422	57	10	the	the	DET
fcis-30422	57	11	choice	choice	NOUN
fcis-30422	57	12	of	of	ADP
fcis-30422	57	13	parameters	parameter	NOUN
fcis-30422	57	14	and	and	CCONJ
fcis-30422	57	15	kernel	kernel	PROPN
fcis-30422	57	16	functions	function	NOUN
fcis-30422	57	17	,	,	PUNCT
fcis-30422	57	18	which	which	PRON
fcis-30422	57	19	means	mean	VERB
fcis-30422	57	20	that	that	SCONJ
fcis-30422	57	21	different	different	ADJ
fcis-30422	57	22	choices	choice	NOUN
fcis-30422	57	23	will	will	AUX
fcis-30422	57	24	have	have	VERB
fcis-30422	57	25	a	a	DET
fcis-30422	57	26	great	great	ADJ
fcis-30422	57	27	impact	impact	NOUN
fcis-30422	57	28	on	on	ADP
fcis-30422	57	29	the	the	DET
fcis-30422	57	30	final	final	ADJ
fcis-30422	57	31	classification	classification	NOUN
fcis-30422	57	32	accuracy	accuracy	NOUN
fcis-30422	57	33	of	of	ADP
fcis-30422	57	34	svm	svm	PROPN
fcis-30422	57	35	[	[	X
fcis-30422	57	36	14	14	NUM
fcis-30422	57	37	]	]	PUNCT
fcis-30422	57	38	.	.	PUNCT
fcis-30422	58	1	methods	method	NOUN
fcis-30422	58	2	based	base	VERB
fcis-30422	58	3	on	on	ADP
fcis-30422	58	4	traditional	traditional	ADJ
fcis-30422	58	5	machine	machine	NOUN
fcis-30422	58	6	learning	learning	NOUN
fcis-30422	58	7	can	can	AUX
fcis-30422	58	8	automatically	automatically	ADV
fcis-30422	58	9	learn	learn	VERB
fcis-30422	58	10	feature	feature	NOUN
fcis-30422	58	11	patterns	pattern	NOUN
fcis-30422	58	12	to	to	PART
fcis-30422	58	13	improve	improve	VERB
fcis-30422	58	14	detection	detection	NOUN
fcis-30422	58	15	performance	performance	NOUN
fcis-30422	58	16	.	.	PUNCT
fcis-30422	59	1	however	however	ADV
fcis-30422	59	2	,	,	PUNCT
fcis-30422	59	3	such	such	ADJ
fcis-30422	59	4	methods	method	NOUN
fcis-30422	59	5	still	still	ADV
fcis-30422	59	6	require	require	VERB
fcis-30422	59	7	manual	manual	ADJ
fcis-30422	59	8	design	design	NOUN
fcis-30422	59	9	of	of	ADP
fcis-30422	59	10	low	low	ADJ
fcis-30422	59	11	-	-	PUNCT
fcis-30422	59	12	level	level	NOUN
fcis-30422	59	13	features	feature	NOUN
fcis-30422	59	14	and	and	CCONJ
fcis-30422	59	15	can	can	AUX
fcis-30422	59	16	not	not	PART
fcis-30422	59	17	directly	directly	ADV
fcis-30422	59	18	learn	learn	VERB
fcis-30422	59	19	feature	feature	NOUN
fcis-30422	59	20	representations	representation	NOUN
fcis-30422	59	21	end	end	NOUN
fcis-30422	59	22	-	-	PUNCT
fcis-30422	59	23	to	to	ADP
fcis-30422	59	24	-	-	PUNCT
fcis-30422	59	25	end	end	NOUN
fcis-30422	59	26	from	from	ADP
fcis-30422	59	27	the	the	DET
fcis-30422	59	28	original	original	ADJ
fcis-30422	59	29	image	image	NOUN
fcis-30422	59	30	,	,	PUNCT
fcis-30422	59	31	which	which	PRON
fcis-30422	59	32	has	have	VERB
fcis-30422	59	33	certain	certain	ADJ
fcis-30422	59	34	limitations	limitation	NOUN
fcis-30422	59	35	.	.	PUNCT
fcis-30422	60	1	4	4	X
fcis-30422	60	2	.	.	X
fcis-30422	60	3	microbial	microbial	ADJ
fcis-30422	60	4	detection	detection	NOUN
fcis-30422	60	5	based	base	VERB
fcis-30422	60	6	on	on	ADP
fcis-30422	60	7	deep	deep	ADJ
fcis-30422	60	8	learning	learning	NOUN
fcis-30422	60	9	deep	deep	ADJ
fcis-30422	60	10	learning	learning	NOUN
fcis-30422	60	11	is	be	AUX
fcis-30422	60	12	a	a	DET
fcis-30422	60	13	data	data	NOUN
fcis-30422	60	14	-	-	PUNCT
fcis-30422	60	15	based	base	VERB
fcis-30422	60	16	representation	representation	NOUN
fcis-30422	60	17	learning	learning	NOUN
fcis-30422	60	18	method	method	NOUN
fcis-30422	60	19	that	that	PRON
fcis-30422	60	20	can	can	AUX
fcis-30422	60	21	automatically	automatically	ADV
fcis-30422	60	22	learn	learn	VERB
fcis-30422	60	23	multi	multi	ADJ
fcis-30422	60	24	-	-	ADJ
fcis-30422	60	25	level	level	ADJ
fcis-30422	60	26	feature	feature	NOUN
fcis-30422	60	27	representations	representation	NOUN
fcis-30422	60	28	directly	directly	ADV
fcis-30422	60	29	from	from	ADP
fcis-30422	60	30	raw	raw	ADJ
fcis-30422	60	31	data	datum	NOUN
fcis-30422	60	32	without	without	ADP
fcis-30422	60	33	the	the	DET
fcis-30422	60	34	need	need	NOUN
fcis-30422	60	35	for	for	ADP
fcis-30422	60	36	manual	manual	ADJ
fcis-30422	60	37	feature	feature	NOUN
fcis-30422	60	38	design	design	NOUN
fcis-30422	60	39	.	.	PUNCT
fcis-30422	61	1	in	in	ADP
fcis-30422	61	2	recent	recent	ADJ
fcis-30422	61	3	years	year	NOUN
fcis-30422	61	4	,	,	PUNCT
fcis-30422	61	5	microbial	microbial	ADJ
fcis-30422	61	6	detection	detection	NOUN
fcis-30422	61	7	methods	method	NOUN
fcis-30422	61	8	based	base	VERB
fcis-30422	61	9	on	on	ADP
fcis-30422	61	10	deep	deep	ADJ
fcis-30422	61	11	learning	learning	NOUN
fcis-30422	61	12	have	have	AUX
fcis-30422	61	13	achieved	achieve	VERB
fcis-30422	61	14	outstanding	outstanding	ADJ
fcis-30422	61	15	results	result	NOUN
fcis-30422	61	16	.	.	PUNCT
fcis-30422	62	1	convolutional	convolutional	ADJ
fcis-30422	62	2	neural	neural	ADJ
fcis-30422	62	3	network	network	NOUN
fcis-30422	62	4	(	(	PUNCT
fcis-30422	62	5	cnn	cnn	PROPN
fcis-30422	62	6	)	)	PUNCT
fcis-30422	62	7	is	be	AUX
fcis-30422	62	8	a	a	DET
fcis-30422	62	9	classic	classic	ADJ
fcis-30422	62	10	deep	deep	ADJ
fcis-30422	62	11	learning	learning	NOUN
fcis-30422	62	12	model	model	NOUN
fcis-30422	62	13	that	that	PRON
fcis-30422	62	14	performs	perform	VERB
fcis-30422	62	15	well	well	ADV
fcis-30422	62	16	in	in	ADP
fcis-30422	62	17	the	the	DET
fcis-30422	62	18	field	field	NOUN
fcis-30422	62	19	of	of	ADP
fcis-30422	62	20	computer	computer	NOUN
fcis-30422	62	21	vision	vision	NOUN
fcis-30422	62	22	.	.	PUNCT
fcis-30422	63	1	researchers	researcher	NOUN
fcis-30422	63	2	apply	apply	VERB
fcis-30422	63	3	cnn	cnn	PROPN
fcis-30422	63	4	to	to	ADP
fcis-30422	63	5	microbial	microbial	ADJ
fcis-30422	63	6	image	image	NOUN
fcis-30422	63	7	detection	detection	NOUN
fcis-30422	63	8	to	to	PART
fcis-30422	63	9	automatically	automatically	ADV
fcis-30422	63	10	learn	learn	VERB
fcis-30422	63	11	features	feature	NOUN
fcis-30422	63	12	from	from	ADP
fcis-30422	63	13	images	image	NOUN
fcis-30422	63	14	and	and	CCONJ
fcis-30422	63	15	classify	classify	VERB
fcis-30422	63	16	them	they	PRON
fcis-30422	63	17	.	.	PUNCT
fcis-30422	64	1	for	for	ADP
fcis-30422	64	2	example	example	NOUN
fcis-30422	64	3	,	,	PUNCT
fcis-30422	64	4	tahir	tahir	PROPN
fcis-30422	64	5	et	et	PROPN
fcis-30422	64	6	al	al	PROPN
fcis-30422	64	7	.	.	PROPN
fcis-30422	64	8	proposed	propose	VERB
fcis-30422	64	9	a	a	DET
fcis-30422	64	10	cnn	cnn	PROPN
fcis-30422	64	11	-	-	PUNCT
fcis-30422	64	12	based	base	VERB
fcis-30422	64	13	method	method	NOUN
fcis-30422	64	14	for	for	ADP
fcis-30422	64	15	fungal	fungal	ADJ
fcis-30422	64	16	detection	detection	NOUN
fcis-30422	64	17	and	and	CCONJ
fcis-30422	64	18	differentiation	differentiation	NOUN
fcis-30422	64	19	of	of	ADP
fcis-30422	64	20	different	different	ADJ
fcis-30422	64	21	types	type	NOUN
fcis-30422	64	22	of	of	ADP
fcis-30422	64	23	fungi	fungi	NOUN
fcis-30422	64	24	[	[	X
fcis-30422	64	25	15	15	NUM
fcis-30422	64	26	]	]	PUNCT
fcis-30422	64	27	.	.	PUNCT
fcis-30422	65	1	in	in	ADP
fcis-30422	65	2	addition	addition	NOUN
fcis-30422	65	3	,	,	PUNCT
fcis-30422	65	4	they	they	PRON
fcis-30422	65	5	developed	develop	VERB
fcis-30422	65	6	a	a	DET
fcis-30422	65	7	new	new	ADJ
fcis-30422	65	8	fungal	fungal	ADJ
fcis-30422	65	9	dataset	dataset	NOUN
fcis-30422	65	10	consisting	consist	VERB
fcis-30422	65	11	of	of	ADP
fcis-30422	65	12	five	five	NUM
fcis-30422	65	13	different	different	ADJ
fcis-30422	65	14	types	type	NOUN
fcis-30422	65	15	of	of	ADP
fcis-30422	65	16	fungal	fungal	ADJ
fcis-30422	65	17	spores	spore	NOUN
fcis-30422	65	18	and	and	CCONJ
fcis-30422	65	19	dirt	dirt	NOUN
fcis-30422	65	20	.	.	PUNCT
fcis-30422	66	1	the	the	DET
fcis-30422	66	2	results	result	NOUN
fcis-30422	66	3	showed	show	VERB
fcis-30422	66	4	that	that	SCONJ
fcis-30422	66	5	the	the	DET
fcis-30422	66	6	accuracy	accuracy	NOUN
fcis-30422	66	7	of	of	ADP
fcis-30422	66	8	this	this	DET
fcis-30422	66	9	method	method	NOUN
fcis-30422	66	10	was	be	AUX
fcis-30422	66	11	94.8	94.8	NUM
fcis-30422	66	12	%	%	NOUN
fcis-30422	66	13	.	.	PUNCT
fcis-30422	67	1	panicker	panicker	PROPN
fcis-30422	67	2	et	et	PROPN
fcis-30422	67	3	al	al	PROPN
fcis-30422	67	4	.	.	PROPN
fcis-30422	67	5	proposed	propose	VERB
fcis-30422	67	6	a	a	DET
fcis-30422	67	7	cnn	cnn	PROPN
fcis-30422	67	8	-	-	PUNCT
fcis-30422	67	9	based	base	VERB
fcis-30422	67	10	method	method	NOUN
fcis-30422	67	11	for	for	ADP
fcis-30422	67	12	detecting	detect	VERB
fcis-30422	67	13	tuberculosis	tuberculosis	NOUN
fcis-30422	67	14	in	in	ADP
fcis-30422	67	15	sputum	sputum	PROPN
fcis-30422	67	16	smear	smear	NOUN
fcis-30422	67	17	microscopic	microscopic	ADJ
fcis-30422	67	18	images	image	NOUN
fcis-30422	67	19	[	[	X
fcis-30422	67	20	16	16	NUM
fcis-30422	67	21	]	]	PUNCT
fcis-30422	67	22	.	.	PUNCT
fcis-30422	68	1	this	this	DET
fcis-30422	68	2	method	method	NOUN
fcis-30422	68	3	uses	use	VERB
fcis-30422	68	4	the	the	DET
fcis-30422	68	5	otsu	otsu	ADJ
fcis-30422	68	6	threshold	threshold	NOUN
fcis-30422	68	7	algorithm	algorithm	NOUN
fcis-30422	68	8	to	to	PART
fcis-30422	68	9	binarize	binarize	VERB
fcis-30422	68	10	the	the	DET
fcis-30422	68	11	image	image	NOUN
fcis-30422	68	12	and	and	CCONJ
fcis-30422	68	13	applies	apply	VERB
fcis-30422	68	14	cnn	cnn	PROPN
fcis-30422	68	15	to	to	PART
fcis-30422	68	16	determine	determine	VERB
fcis-30422	68	17	the	the	DET
fcis-30422	68	18	category	category	NOUN
fcis-30422	68	19	of	of	ADP
fcis-30422	68	20	the	the	DET
fcis-30422	68	21	region	region	NOUN
fcis-30422	68	22	extracted	extract	VERB
fcis-30422	68	23	from	from	ADP
fcis-30422	68	24	the	the	DET
fcis-30422	68	25	first	first	ADJ
fcis-30422	68	26	stage	stage	NOUN
fcis-30422	68	27	.	.	PUNCT
fcis-30422	69	1	the	the	DET
fcis-30422	69	2	classification	classification	NOUN
fcis-30422	69	3	results	result	NOUN
fcis-30422	69	4	show	show	VERB
fcis-30422	69	5	that	that	SCONJ
fcis-30422	69	6	the	the	DET
fcis-30422	69	7	recall	recall	NOUN
fcis-30422	69	8	rate	rate	NOUN
fcis-30422	69	9	of	of	ADP
fcis-30422	69	10	this	this	DET
fcis-30422	69	11	method	method	NOUN
fcis-30422	69	12	is	be	AUX
fcis-30422	69	13	97.13	97.13	NUM
fcis-30422	69	14	%	%	NOUN
fcis-30422	69	15	,	,	PUNCT
fcis-30422	69	16	the	the	DET
fcis-30422	69	17	accuracy	accuracy	NOUN
fcis-30422	69	18	rate	rate	NOUN
fcis-30422	69	19	is	be	AUX
fcis-30422	69	20	78.4	78.4	NUM
fcis-30422	69	21	%	%	NOUN
fcis-30422	69	22	,	,	PUNCT
fcis-30422	69	23	and	and	CCONJ
fcis-30422	69	24	the	the	DET
fcis-30422	69	25	f	f	NOUN
fcis-30422	69	26	-	-	PUNCT
fcis-30422	69	27	score	score	NOUN
fcis-30422	69	28	is	be	AUX
fcis-30422	69	29	86.76	86.76	NUM
fcis-30422	69	30	%	%	NOUN
fcis-30422	69	31	.	.	PUNCT
fcis-30422	70	1	methods	method	NOUN
fcis-30422	70	2	based	base	VERB
fcis-30422	70	3	on	on	ADP
fcis-30422	70	4	deep	deep	ADJ
fcis-30422	70	5	learning	learning	NOUN
fcis-30422	70	6	can	can	AUX
fcis-30422	70	7	automatically	automatically	ADV
fcis-30422	70	8	learn	learn	VERB
fcis-30422	70	9	feature	feature	NOUN
fcis-30422	70	10	representation	representation	NOUN
fcis-30422	70	11	directly	directly	ADV
fcis-30422	70	12	from	from	ADP
fcis-30422	70	13	raw	raw	ADJ
fcis-30422	70	14	image	image	NOUN
fcis-30422	70	15	data	datum	NOUN
fcis-30422	70	16	without	without	ADP
fcis-30422	70	17	the	the	DET
fcis-30422	70	18	need	need	NOUN
fcis-30422	70	19	for	for	ADP
fcis-30422	70	20	manual	manual	ADJ
fcis-30422	70	21	feature	feature	NOUN
fcis-30422	70	22	design	design	NOUN
fcis-30422	70	23	,	,	PUNCT
fcis-30422	70	24	and	and	CCONJ
fcis-30422	70	25	have	have	VERB
fcis-30422	70	26	stronger	strong	ADJ
fcis-30422	70	27	expressive	expressive	ADJ
fcis-30422	70	28	power	power	NOUN
fcis-30422	70	29	.	.	PUNCT
fcis-30422	71	1	these	these	DET
fcis-30422	71	2	methods	method	NOUN
fcis-30422	71	3	have	have	AUX
fcis-30422	71	4	shown	show	VERB
fcis-30422	71	5	superiority	superiority	NOUN
fcis-30422	71	6	over	over	ADP
fcis-30422	71	7	methods	method	NOUN
fcis-30422	71	8	based	base	VERB
fcis-30422	71	9	on	on	ADP
fcis-30422	71	10	classical	classical	ADJ
fcis-30422	71	11	image	image	NOUN
fcis-30422	71	12	processing	processing	NOUN
fcis-30422	71	13	and	and	CCONJ
fcis-30422	71	14	traditional	traditional	ADJ
fcis-30422	71	15	machine	machine	NOUN
fcis-30422	71	16	learning	learning	NOUN
fcis-30422	71	17	in	in	ADP
fcis-30422	71	18	multiple	multiple	ADJ
fcis-30422	71	19	microbial	microbial	ADJ
fcis-30422	71	20	detection	detection	NOUN
fcis-30422	71	21	tasks	task	NOUN
fcis-30422	71	22	and	and	CCONJ
fcis-30422	71	23	have	have	AUX
fcis-30422	71	24	become	become	VERB
fcis-30422	71	25	the	the	DET
fcis-30422	71	26	mainstream	mainstream	NOUN
fcis-30422	71	27	methods	method	NOUN
fcis-30422	71	28	in	in	ADP
fcis-30422	71	29	this	this	DET
fcis-30422	71	30	field	field	NOUN
fcis-30422	71	31	.	.	PUNCT
fcis-30422	72	1	however	however	ADV
fcis-30422	72	2	,	,	PUNCT
fcis-30422	72	3	since	since	SCONJ
fcis-30422	72	4	deep	deep	ADJ
fcis-30422	72	5	models	model	NOUN
fcis-30422	72	6	usually	usually	ADV
fcis-30422	72	7	require	require	VERB
fcis-30422	72	8	a	a	DET
fcis-30422	72	9	large	large	ADJ
fcis-30422	72	10	amount	amount	NOUN
fcis-30422	72	11	of	of	ADP
fcis-30422	72	12	labeled	label	VERB
fcis-30422	72	13	data	datum	NOUN
fcis-30422	72	14	for	for	ADP
fcis-30422	72	15	training	training	NOUN
fcis-30422	72	16	,	,	PUNCT
fcis-30422	72	17	the	the	DET
fcis-30422	72	18	difficulty	difficulty	NOUN
fcis-30422	72	19	and	and	CCONJ
fcis-30422	72	20	time	time	NOUN
fcis-30422	72	21	-	-	PUNCT
fcis-30422	72	22	consuming	consuming	NOUN
fcis-30422	72	23	of	of	ADP
fcis-30422	72	24	data	datum	NOUN
fcis-30422	72	25	labeling	labeling	NOUN
fcis-30422	72	26	have	have	AUX
fcis-30422	72	27	also	also	ADV
fcis-30422	72	28	become	become	VERB
fcis-30422	72	29	one	one	NUM
fcis-30422	72	30	of	of	ADP
fcis-30422	72	31	the	the	DET
fcis-30422	72	32	constraints	constraint	NOUN
fcis-30422	72	33	.	.	PUNCT
fcis-30422	73	1	5	5	X
fcis-30422	73	2	.	.	X
fcis-30422	73	3	conclusion	conclusion	NOUN
fcis-30422	73	4	this	this	DET
fcis-30422	73	5	paper	paper	NOUN
fcis-30422	73	6	reviews	review	VERB
fcis-30422	73	7	microbial	microbial	ADJ
fcis-30422	73	8	detection	detection	NOUN
fcis-30422	73	9	methods	method	NOUN
fcis-30422	73	10	based	base	VERB
fcis-30422	73	11	on	on	ADP
fcis-30422	73	12	computer	computer	NOUN
fcis-30422	73	13	image	image	NOUN
fcis-30422	73	14	analysis	analysis	NOUN
fcis-30422	73	15	technology	technology	NOUN
fcis-30422	73	16	,	,	PUNCT
fcis-30422	73	17	mainly	mainly	ADV
fcis-30422	73	18	including	include	VERB
fcis-30422	73	19	three	three	NUM
fcis-30422	73	20	types	type	NOUN
fcis-30422	73	21	of	of	ADP
fcis-30422	73	22	methods	method	NOUN
fcis-30422	73	23	based	base	VERB
fcis-30422	73	24	on	on	ADP
fcis-30422	73	25	classical	classical	ADJ
fcis-30422	73	26	image	image	NOUN
fcis-30422	73	27	processing	processing	NOUN
fcis-30422	73	28	,	,	PUNCT
fcis-30422	73	29	machine	machine	NOUN
fcis-30422	73	30	learning	learning	NOUN
fcis-30422	73	31	,	,	PUNCT
fcis-30422	73	32	and	and	CCONJ
fcis-30422	73	33	deep	deep	ADJ
fcis-30422	73	34	learning	learning	NOUN
fcis-30422	73	35	.	.	PUNCT
fcis-30422	74	1	these	these	DET
fcis-30422	74	2	methods	method	NOUN
fcis-30422	74	3	have	have	AUX
fcis-30422	74	4	significantly	significantly	ADV
fcis-30422	74	5	improved	improve	VERB
fcis-30422	74	6	the	the	DET
fcis-30422	74	7	performance	performance	NOUN
fcis-30422	74	8	of	of	ADP
fcis-30422	74	9	microbial	microbial	ADJ
fcis-30422	74	10	detection	detection	NOUN
fcis-30422	74	11	and	and	CCONJ
fcis-30422	74	12	have	have	AUX
fcis-30422	74	13	become	become	VERB
fcis-30422	74	14	the	the	DET
fcis-30422	74	15	mainstream	mainstream	NOUN
fcis-30422	74	16	technology	technology	NOUN
fcis-30422	74	17	in	in	ADP
fcis-30422	74	18	this	this	DET
fcis-30422	74	19	field	field	NOUN
fcis-30422	74	20	.	.	PUNCT
fcis-30422	75	1	although	although	SCONJ
fcis-30422	75	2	deep	deep	ADJ
fcis-30422	75	3	learning	learning	NOUN
fcis-30422	75	4	-	-	PUNCT
fcis-30422	75	5	based	base	VERB
fcis-30422	75	6	microbial	microbial	ADJ
fcis-30422	75	7	detection	detection	NOUN
fcis-30422	75	8	methods	method	NOUN
fcis-30422	75	9	have	have	AUX
fcis-30422	75	10	achieved	achieve	VERB
fcis-30422	75	11	remarkable	remarkable	ADJ
fcis-30422	75	12	results	result	NOUN
fcis-30422	75	13	,	,	PUNCT
fcis-30422	75	14	they	they	PRON
fcis-30422	75	15	still	still	ADV
fcis-30422	75	16	face	face	VERB
fcis-30422	75	17	problems	problem	NOUN
fcis-30422	75	18	such	such	ADJ
fcis-30422	75	19	as	as	ADP
fcis-30422	75	20	difficulty	difficulty	NOUN
fcis-30422	75	21	in	in	ADP
fcis-30422	75	22	data	datum	NOUN
fcis-30422	75	23	labeling	labeling	NOUN
fcis-30422	75	24	,	,	PUNCT
fcis-30422	75	25	scarcity	scarcity	NOUN
fcis-30422	75	26	of	of	ADP
fcis-30422	75	27	data	datum	NOUN
fcis-30422	75	28	,	,	PUNCT
fcis-30422	75	29	and	and	CCONJ
fcis-30422	75	30	lack	lack	NOUN
fcis-30422	75	31	of	of	ADP
fcis-30422	75	32	interpretability	interpretability	NOUN
fcis-30422	75	33	,	,	PUNCT
fcis-30422	75	34	which	which	PRON
fcis-30422	75	35	still	still	ADV
fcis-30422	75	36	require	require	VERB
fcis-30422	75	37	further	further	ADJ
fcis-30422	75	38	research	research	NOUN
fcis-30422	75	39	.	.	PUNCT
fcis-30422	76	1	in	in	ADP
fcis-30422	76	2	the	the	DET
fcis-30422	76	3	future	future	NOUN
fcis-30422	76	4	,	,	PUNCT
fcis-30422	76	5	research	research	NOUN
fcis-30422	76	6	on	on	ADP
fcis-30422	76	7	deep	deep	ADJ
fcis-30422	76	8	learning	learning	NOUN
fcis-30422	76	9	-	-	PUNCT
fcis-30422	76	10	based	base	VERB
fcis-30422	76	11	microbial	microbial	ADJ
fcis-30422	76	12	monitoring	monitoring	NOUN
fcis-30422	76	13	technology	technology	NOUN
fcis-30422	76	14	will	will	AUX
fcis-30422	76	15	develop	develop	VERB
fcis-30422	76	16	in	in	ADP
fcis-30422	76	17	the	the	DET
fcis-30422	76	18	direction	direction	NOUN
fcis-30422	76	19	of	of	ADP
fcis-30422	76	20	designing	design	VERB
fcis-30422	76	21	more	more	ADV
fcis-30422	76	22	efficient	efficient	ADJ
fcis-30422	76	23	network	network	NOUN
fcis-30422	76	24	models	model	NOUN
fcis-30422	76	25	,	,	PUNCT
fcis-30422	76	26	data	datum	NOUN
fcis-30422	76	27	enhancement	enhancement	NOUN
fcis-30422	76	28	strategies	strategy	NOUN
fcis-30422	76	29	,	,	PUNCT
fcis-30422	76	30	and	and	CCONJ
fcis-30422	76	31	transfer	transfer	VERB
fcis-30422	76	32	learning	learning	NOUN
fcis-30422	76	33	with	with	ADP
fcis-30422	76	34	strong	strong	ADJ
fcis-30422	76	35	generalization	generalization	NOUN
fcis-30422	76	36	capabilities	capability	NOUN
fcis-30422	76	37	to	to	PART
fcis-30422	76	38	further	far	ADV
fcis-30422	76	39	improve	improve	VERB
fcis-30422	76	40	detection	detection	NOUN
fcis-30422	76	41	performance	performance	NOUN
fcis-30422	76	42	.	.	PUNCT
fcis-30422	77	1	in	in	ADP
fcis-30422	77	2	summary	summary	NOUN
fcis-30422	77	3	,	,	PUNCT
fcis-30422	77	4	deep	deep	ADJ
fcis-30422	77	5	learning	learning	NOUN
fcis-30422	77	6	-	-	PUNCT
fcis-30422	77	7	based	base	VERB
fcis-30422	77	8	microbial	microbial	ADJ
fcis-30422	77	9	detection	detection	NOUN
fcis-30422	77	10	technology	technology	NOUN
fcis-30422	77	11	is	be	AUX
fcis-30422	77	12	constantly	constantly	ADV
fcis-30422	77	13	developing	develop	VERB
fcis-30422	77	14	and	and	CCONJ
fcis-30422	77	15	improving	improve	VERB
fcis-30422	77	16	.	.	PUNCT
fcis-30422	78	1	through	through	ADP
fcis-30422	78	2	continuous	continuous	ADJ
fcis-30422	78	3	innovation	innovation	NOUN
fcis-30422	78	4	and	and	CCONJ
fcis-30422	78	5	development	development	NOUN
fcis-30422	78	6	,	,	PUNCT
fcis-30422	78	7	it	it	PRON
fcis-30422	78	8	is	be	AUX
fcis-30422	78	9	believed	believe	VERB
fcis-30422	78	10	that	that	SCONJ
fcis-30422	78	11	this	this	DET
fcis-30422	78	12	technology	technology	NOUN
fcis-30422	78	13	will	will	AUX
fcis-30422	78	14	bring	bring	VERB
fcis-30422	78	15	more	more	ADJ
fcis-30422	78	16	breakthroughs	breakthrough	NOUN
fcis-30422	78	17	to	to	ADP
fcis-30422	78	18	the	the	DET
fcis-30422	78	19	field	field	NOUN
fcis-30422	78	20	of	of	ADP
fcis-30422	78	21	microbial	microbial	ADJ
fcis-30422	78	22	analysis	analysis	NOUN
fcis-30422	78	23	and	and	CCONJ
fcis-30422	78	24	make	make	VERB
fcis-30422	78	25	important	important	ADJ
fcis-30422	78	26	contributions	contribution	NOUN
fcis-30422	78	27	to	to	ADP
fcis-30422	78	28	promoting	promote	VERB
fcis-30422	78	29	the	the	DET
fcis-30422	78	30	sustainable	sustainable	ADJ
fcis-30422	78	31	development	development	NOUN
fcis-30422	78	32	of	of	ADP
fcis-30422	78	33	human	human	ADJ
fcis-30422	78	34	society	society	NOUN
fcis-30422	78	35	.	.	PUNCT
fcis-30422	79	1	references	reference	NOUN
fcis-30422	79	2	[	[	X
fcis-30422	79	3	1	1	X
fcis-30422	79	4	]	]	X
fcis-30422	79	5	ma	ma	PROPN
fcis-30422	79	6	p	p	PROPN
fcis-30422	79	7	,	,	PUNCT
fcis-30422	79	8	li	li	PROPN
fcis-30422	79	9	c	c	PROPN
fcis-30422	79	10	,	,	PUNCT
fcis-30422	79	11	rahaman	rahaman	NOUN
fcis-30422	79	12	m	m	NOUN
fcis-30422	79	13	m	m	PROPN
fcis-30422	79	14	,	,	PUNCT
fcis-30422	79	15	et	et	PROPN
fcis-30422	79	16	al	al	PROPN
fcis-30422	79	17	.	.	PUNCT
fcis-30422	80	1	a	a	DET
fcis-30422	80	2	state	state	NOUN
fcis-30422	80	3	-	-	PUNCT
fcis-30422	80	4	of	of	ADP
fcis-30422	80	5	-	-	PUNCT
fcis-30422	80	6	the	the	DET
fcis-30422	80	7	-	-	PUNCT
fcis-30422	80	8	art	art	NOUN
fcis-30422	80	9	survey	survey	NOUN
fcis-30422	80	10	of	of	ADP
fcis-30422	80	11	object	object	NOUN
fcis-30422	80	12	detection	detection	NOUN
fcis-30422	80	13	techniques	technique	NOUN
fcis-30422	80	14	in	in	ADP
fcis-30422	80	15	microorganism	microorganism	NOUN
fcis-30422	80	16	image	image	NOUN
fcis-30422	80	17	analysis	analysis	NOUN
fcis-30422	80	18	:	:	PUNCT
fcis-30422	80	19	from	from	ADP
fcis-30422	80	20	classical	classical	ADJ
fcis-30422	80	21	methods	method	NOUN
fcis-30422	80	22	to	to	ADP
fcis-30422	80	23	deep	deep	ADJ
fcis-30422	80	24	learning	learn	VERB
fcis-30422	80	25	approaches[j	approaches[j	PROPN
fcis-30422	80	26	]	]	PUNCT
fcis-30422	80	27	.	.	PUNCT
fcis-30422	81	1	artificial	artificial	ADJ
fcis-30422	81	2	intelligence	intelligence	NOUN
fcis-30422	81	3	review	review	NOUN
fcis-30422	81	4	,	,	PUNCT
fcis-30422	81	5	2023	2023	NUM
fcis-30422	81	6	,	,	PUNCT
fcis-30422	81	7	56(2	56(2	NUM
fcis-30422	81	8	):	):	PUNCT
fcis-30422	81	9	1627	1627	NUM
fcis-30422	81	10	-	-	SYM
fcis-30422	81	11	1698	1698	NUM
fcis-30422	81	12	.	.	PUNCT
fcis-30422	82	1	60	60	NUM
fcis-30422	83	1	[	[	SYM
fcis-30422	83	2	2	2	NUM
fcis-30422	83	3	]	]	PUNCT
fcis-30422	83	4	babalola	babalola	NOUN
fcis-30422	83	5	o	o	NOUN
fcis-30422	83	6	o.	o.	PROPN
fcis-30422	83	7	beneficial	beneficial	ADJ
fcis-30422	83	8	bacteria	bacteria	NOUN
fcis-30422	83	9	of	of	ADP
fcis-30422	83	10	agricultural	agricultural	ADJ
fcis-30422	83	11	importance[j	importance[j	NOUN
fcis-30422	83	12	]	]	PUNCT
fcis-30422	83	13	.	.	PUNCT
fcis-30422	84	1	biotechnology	biotechnology	NOUN
fcis-30422	84	2	letters	letter	NOUN
fcis-30422	84	3	,	,	PUNCT
fcis-30422	84	4	2010	2010	NUM
fcis-30422	84	5	,	,	PUNCT
fcis-30422	84	6	32	32	NUM
fcis-30422	84	7	:	:	SYM
fcis-30422	84	8	1559	1559	NUM
fcis-30422	84	9	-	-	SYM
fcis-30422	84	10	1570	1570	NUM
fcis-30422	84	11	.	.	PUNCT
fcis-30422	85	1	[	[	X
fcis-30422	85	2	3	3	X
fcis-30422	85	3	]	]	X
fcis-30422	85	4	masood	masood	PROPN
fcis-30422	85	5	m	m	VERB
fcis-30422	85	6	i	i	PROPN
fcis-30422	85	7	,	,	PUNCT
fcis-30422	85	8	qadir	qadir	PROPN
fcis-30422	85	9	m	m	VERB
fcis-30422	85	10	i	i	PRON
fcis-30422	85	11	,	,	PUNCT
fcis-30422	85	12	shirazi	shirazi	PROPN
fcis-30422	85	13	j	j	PROPN
fcis-30422	85	14	h	h	PROPN
fcis-30422	85	15	,	,	PUNCT
fcis-30422	85	16	et	et	PROPN
fcis-30422	85	17	al	al	PROPN
fcis-30422	85	18	.	.	PROPN
fcis-30422	85	19	beneficial	beneficial	ADJ
fcis-30422	85	20	effects	effect	NOUN
fcis-30422	85	21	of	of	ADP
fcis-30422	85	22	lactic	lactic	ADJ
fcis-30422	85	23	acid	acid	NOUN
fcis-30422	85	24	bacteria	bacteria	NOUN
fcis-30422	85	25	on	on	ADP
fcis-30422	85	26	human	human	ADJ
fcis-30422	85	27	beings[j	beings[j	PROPN
fcis-30422	85	28	]	]	PUNCT
fcis-30422	85	29	.	.	PUNCT
fcis-30422	86	1	critical	critical	ADJ
fcis-30422	86	2	reviews	review	NOUN
fcis-30422	86	3	in	in	ADP
fcis-30422	86	4	microbiology	microbiology	NOUN
fcis-30422	86	5	,	,	PUNCT
fcis-30422	86	6	2011	2011	NUM
fcis-30422	86	7	,	,	PUNCT
fcis-30422	86	8	37(1	37(1	NUM
fcis-30422	86	9	):	):	PUNCT
fcis-30422	86	10	91	91	NUM
fcis-30422	86	11	-	-	SYM
fcis-30422	86	12	98	98	NUM
fcis-30422	86	13	.	.	PUNCT
fcis-30422	87	1	[	[	X
fcis-30422	87	2	4	4	X
fcis-30422	87	3	]	]	PUNCT
fcis-30422	87	4	hui	hui	PROPN
fcis-30422	87	5	d	d	PROPN
fcis-30422	87	6	s	s	PROPN
fcis-30422	87	7	,	,	PUNCT
fcis-30422	87	8	azhar	azhar	PROPN
fcis-30422	87	9	e	e	PROPN
fcis-30422	87	10	i	i	PROPN
fcis-30422	87	11	,	,	PUNCT
fcis-30422	87	12	madani	madani	PROPN
fcis-30422	87	13	t	t	PROPN
fcis-30422	87	14	a	a	PROPN
fcis-30422	87	15	,	,	PUNCT
fcis-30422	87	16	et	et	PROPN
fcis-30422	87	17	al	al	PROPN
fcis-30422	87	18	.	.	PUNCT
fcis-30422	88	1	the	the	DET
fcis-30422	88	2	continuing	continue	VERB
fcis-30422	88	3	2019ncov	2019ncov	NUM
fcis-30422	88	4	epidemic	epidemic	NOUN
fcis-30422	88	5	threat	threat	NOUN
fcis-30422	88	6	of	of	ADP
fcis-30422	88	7	novel	novel	ADJ
fcis-30422	88	8	coronaviruses	coronaviruse	NOUN
fcis-30422	88	9	to	to	ADP
fcis-30422	88	10	global	global	ADJ
fcis-30422	88	11	health	health	NOUN
fcis-30422	88	12	—	—	PUNCT
fcis-30422	88	13	the	the	DET
fcis-30422	88	14	latest	late	ADJ
fcis-30422	88	15	2019	2019	NUM
fcis-30422	88	16	novel	novel	ADJ
fcis-30422	88	17	coronavirus	coronavirus	NOUN
fcis-30422	88	18	outbreak	outbreak	NOUN
fcis-30422	88	19	in	in	ADP
fcis-30422	88	20	wuhan	wuhan	PROPN
fcis-30422	88	21	,	,	PUNCT
fcis-30422	88	22	china[j	china[j	PROPN
fcis-30422	88	23	]	]	PUNCT
fcis-30422	88	24	.	.	PUNCT
fcis-30422	89	1	international	international	ADJ
fcis-30422	89	2	journal	journal	PROPN
fcis-30422	89	3	of	of	ADP
fcis-30422	89	4	infectious	infectious	ADJ
fcis-30422	89	5	diseases	disease	NOUN
fcis-30422	89	6	,	,	PUNCT
fcis-30422	89	7	2020	2020	NUM
fcis-30422	89	8	,	,	PUNCT
fcis-30422	89	9	91	91	NUM
fcis-30422	89	10	:	:	SYM
fcis-30422	89	11	264	264	NUM
fcis-30422	89	12	-	-	SYM
fcis-30422	89	13	266	266	NUM
fcis-30422	89	14	.	.	PUNCT
fcis-30422	90	1	[	[	X
fcis-30422	90	2	5	5	NUM
fcis-30422	90	3	]	]	X
fcis-30422	90	4	gray	gray	ADJ
fcis-30422	90	5	t	t	PROPN
fcis-30422	90	6	r	r	NOUN
fcis-30422	90	7	g.	g.	PROPN
fcis-30422	90	8	stereoscan	stereoscan	PROPN
fcis-30422	90	9	electron	electron	PROPN
fcis-30422	90	10	microscopy	microscopy	NOUN
fcis-30422	90	11	of	of	ADP
fcis-30422	90	12	soil	soil	NOUN
fcis-30422	90	13	microorganisms[j	microorganisms[j	PROPN
fcis-30422	90	14	]	]	PUNCT
fcis-30422	90	15	.	.	PUNCT
fcis-30422	91	1	science	science	NOUN
fcis-30422	91	2	,	,	PUNCT
fcis-30422	91	3	1967	1967	NUM
fcis-30422	91	4	,	,	PUNCT
fcis-30422	91	5	155(3770	155(3770	NUM
fcis-30422	91	6	):	):	PUNCT
fcis-30422	91	7	1668	1668	NUM
fcis-30422	91	8	-	-	SYM
fcis-30422	91	9	1670	1670	NUM
fcis-30422	91	10	.	.	PUNCT
fcis-30422	92	1	[	[	X
fcis-30422	92	2	6	6	NUM
fcis-30422	92	3	]	]	PUNCT
fcis-30422	92	4	daley	daley	PROPN
fcis-30422	92	5	r	r	PROPN
fcis-30422	92	6	j	j	PROPN
fcis-30422	92	7	,	,	PUNCT
fcis-30422	92	8	hobbie	hobbie	PROPN
fcis-30422	92	9	j	j	PROPN
fcis-30422	92	10	e.	e.	PROPN
fcis-30422	92	11	direct	direct	PROPN
fcis-30422	92	12	counts	count	NOUN
fcis-30422	92	13	of	of	ADP
fcis-30422	92	14	aquatic	aquatic	ADJ
fcis-30422	92	15	bacteria	bacteria	NOUN
fcis-30422	92	16	by	by	ADP
fcis-30422	92	17	a	a	DET
fcis-30422	92	18	modified	modify	VERB
fcis-30422	92	19	epifluorescence	epifluorescence	NOUN
fcis-30422	92	20	technique	technique	NOUN
fcis-30422	92	21	1[j	1[j	NUM
fcis-30422	92	22	]	]	PUNCT
fcis-30422	92	23	.	.	PUNCT
fcis-30422	92	24	limnology	limnology	NOUN
fcis-30422	92	25	and	and	CCONJ
fcis-30422	92	26	oceanography	oceanography	NOUN
fcis-30422	92	27	,	,	PUNCT
fcis-30422	92	28	1975	1975	NUM
fcis-30422	92	29	,	,	PUNCT
fcis-30422	92	30	20(5	20(5	NUM
fcis-30422	92	31	):	):	PUNCT
fcis-30422	92	32	875	875	NUM
fcis-30422	92	33	-	-	SYM
fcis-30422	92	34	882	882	NUM
fcis-30422	92	35	.	.	PUNCT
fcis-30422	93	1	[	[	X
fcis-30422	93	2	7	7	X
fcis-30422	93	3	]	]	X
fcis-30422	93	4	daneshpanah	daneshpanah	PROPN
fcis-30422	93	5	m	m	PROPN
fcis-30422	93	6	,	,	PUNCT
fcis-30422	93	7	zwick	zwick	PROPN
fcis-30422	93	8	s	s	PROPN
fcis-30422	93	9	,	,	PUNCT
fcis-30422	93	10	schaal	schaal	PROPN
fcis-30422	93	11	f	f	PROPN
fcis-30422	93	12	,	,	PUNCT
fcis-30422	93	13	et	et	PROPN
fcis-30422	93	14	al	al	PROPN
fcis-30422	93	15	.	.	PROPN
fcis-30422	93	16	3d	3d	PROPN
fcis-30422	93	17	holographic	holographic	ADJ
fcis-30422	93	18	imaging	imaging	NOUN
fcis-30422	93	19	and	and	CCONJ
fcis-30422	93	20	trapping	trap	VERB
fcis-30422	93	21	for	for	ADP
fcis-30422	93	22	non	non	ADJ
fcis-30422	93	23	-	-	ADJ
fcis-30422	93	24	invasive	invasive	ADJ
fcis-30422	93	25	cell	cell	NOUN
fcis-30422	93	26	identification	identification	NOUN
fcis-30422	93	27	and	and	CCONJ
fcis-30422	93	28	tracking[j	tracking[j	NOUN
fcis-30422	93	29	]	]	PUNCT
fcis-30422	93	30	.	.	PUNCT
fcis-30422	94	1	journal	journal	PROPN
fcis-30422	94	2	of	of	ADP
fcis-30422	94	3	display	display	NOUN
fcis-30422	94	4	technology	technology	NOUN
fcis-30422	94	5	,	,	PUNCT
fcis-30422	94	6	2010	2010	NUM
fcis-30422	94	7	,	,	PUNCT
fcis-30422	94	8	6(10	6(10	NUM
fcis-30422	94	9	):	):	PUNCT
fcis-30422	94	10	490499	490499	NUM
fcis-30422	94	11	.	.	PUNCT
fcis-30422	95	1	[	[	X
fcis-30422	95	2	8	8	NUM
fcis-30422	95	3	]	]	X
fcis-30422	95	4	locey	locey	PROPN
fcis-30422	95	5	k	k	PROPN
fcis-30422	95	6	j	j	PROPN
fcis-30422	95	7	,	,	PUNCT
fcis-30422	95	8	lennon	lennon	PROPN
fcis-30422	95	9	j	j	PROPN
fcis-30422	95	10	t.	t.	PROPN
fcis-30422	95	11	scaling	scale	VERB
fcis-30422	95	12	laws	law	NOUN
fcis-30422	95	13	predict	predict	VERB
fcis-30422	95	14	global	global	ADJ
fcis-30422	95	15	microbial	microbial	ADJ
fcis-30422	95	16	diversity[j	diversity[j	PROPN
fcis-30422	95	17	]	]	PUNCT
fcis-30422	95	18	.	.	PUNCT
fcis-30422	96	1	proceedings	proceeding	NOUN
fcis-30422	96	2	of	of	ADP
fcis-30422	96	3	the	the	DET
fcis-30422	96	4	national	national	PROPN
fcis-30422	96	5	academy	academy	PROPN
fcis-30422	96	6	of	of	ADP
fcis-30422	96	7	sciences	sciences	PROPN
fcis-30422	96	8	,	,	PUNCT
fcis-30422	96	9	2016	2016	NUM
fcis-30422	96	10	,	,	PUNCT
fcis-30422	96	11	113(21	113(21	NUM
fcis-30422	96	12	):	):	PUNCT
fcis-30422	96	13	5970	5970	NUM
fcis-30422	96	14	-	-	SYM
fcis-30422	96	15	5975	5975	NUM
fcis-30422	96	16	.	.	PUNCT
fcis-30422	97	1	[	[	X
fcis-30422	97	2	9	9	NUM
fcis-30422	97	3	]	]	PUNCT
fcis-30422	97	4	van	van	PROPN
fcis-30422	97	5	deun	deun	PROPN
fcis-30422	97	6	a	a	X
fcis-30422	97	7	,	,	PUNCT
fcis-30422	97	8	salim	salim	PROPN
fcis-30422	97	9	a	a	DET
fcis-30422	97	10	h	h	NOUN
fcis-30422	97	11	,	,	PUNCT
fcis-30422	97	12	cooreman	cooreman	NOUN
fcis-30422	97	13	e	e	NOUN
fcis-30422	97	14	,	,	PUNCT
fcis-30422	97	15	et	et	PROPN
fcis-30422	97	16	al	al	PROPN
fcis-30422	97	17	.	.	PUNCT
fcis-30422	97	18	optimal	optimal	ADJ
fcis-30422	97	19	tuberculosis	tuberculosis	NOUN
fcis-30422	97	20	case	case	NOUN
fcis-30422	97	21	detection	detection	NOUN
fcis-30422	97	22	by	by	ADP
fcis-30422	97	23	direct	direct	ADJ
fcis-30422	97	24	sputum	sputum	PROPN
fcis-30422	97	25	smear	smear	NOUN
fcis-30422	97	26	microscopy	microscopy	PROPN
fcis-30422	97	27	:	:	PUNCT
fcis-30422	97	28	how	how	SCONJ
fcis-30422	97	29	much	much	ADV
fcis-30422	97	30	better	well	ADJ
fcis-30422	97	31	is	be	AUX
fcis-30422	97	32	more?[j	more?[j	NOUN
fcis-30422	97	33	]	]	PUNCT
fcis-30422	97	34	.	.	PUNCT
fcis-30422	98	1	the	the	DET
fcis-30422	98	2	international	international	ADJ
fcis-30422	98	3	journal	journal	NOUN
fcis-30422	98	4	of	of	ADP
fcis-30422	98	5	tuberculosis	tuberculosis	NOUN
fcis-30422	98	6	and	and	CCONJ
fcis-30422	98	7	lung	lung	NOUN
fcis-30422	98	8	disease	disease	NOUN
fcis-30422	98	9	,	,	PUNCT
fcis-30422	98	10	2002	2002	NUM
fcis-30422	98	11	,	,	PUNCT
fcis-30422	98	12	6(3	6(3	NUM
fcis-30422	98	13	):	):	PUNCT
fcis-30422	98	14	222	222	NUM
fcis-30422	98	15	-	-	SYM
fcis-30422	98	16	230	230	NUM
fcis-30422	98	17	.	.	PUNCT
fcis-30422	99	1	[	[	X
fcis-30422	99	2	10	10	NUM
fcis-30422	99	3	]	]	X
fcis-30422	99	4	otsu	otsu	NOUN
fcis-30422	99	5	n.	n.	NOUN
fcis-30422	99	6	a	a	DET
fcis-30422	99	7	threshold	threshold	NOUN
fcis-30422	99	8	selection	selection	NOUN
fcis-30422	99	9	method	method	NOUN
fcis-30422	99	10	from	from	ADP
fcis-30422	99	11	gray	gray	ADJ
fcis-30422	99	12	-	-	PUNCT
fcis-30422	99	13	level	level	NOUN
fcis-30422	99	14	histograms[j	histograms[j	NOUN
fcis-30422	99	15	]	]	PUNCT
fcis-30422	99	16	.	.	PUNCT
fcis-30422	100	1	ieee	ieee	NOUN
fcis-30422	100	2	transactions	transaction	NOUN
fcis-30422	100	3	on	on	ADP
fcis-30422	100	4	systems	system	NOUN
fcis-30422	100	5	,	,	PUNCT
fcis-30422	100	6	man	man	NOUN
fcis-30422	100	7	,	,	PUNCT
fcis-30422	100	8	and	and	CCONJ
fcis-30422	100	9	cybernetics	cybernetic	NOUN
fcis-30422	100	10	,	,	PUNCT
fcis-30422	100	11	1979	1979	NUM
fcis-30422	100	12	,	,	PUNCT
fcis-30422	100	13	9(1	9(1	NUM
fcis-30422	100	14	):	):	PUNCT
fcis-30422	100	15	62	62	NUM
fcis-30422	100	16	-	-	SYM
fcis-30422	100	17	66	66	NUM
fcis-30422	100	18	.	.	PUNCT
fcis-30422	101	1	[	[	X
fcis-30422	101	2	11	11	NUM
fcis-30422	101	3	]	]	PUNCT
fcis-30422	101	4	sezgin	sezgin	PROPN
fcis-30422	101	5	m	m	PROPN
fcis-30422	101	6	,	,	PUNCT
fcis-30422	101	7	sankur	sankur	PROPN
fcis-30422	101	8	b.	b.	PROPN
fcis-30422	101	9	survey	survey	PROPN
fcis-30422	101	10	over	over	ADP
fcis-30422	101	11	image	image	NOUN
fcis-30422	101	12	thresholding	thresholde	VERB
fcis-30422	101	13	techniques	technique	NOUN
fcis-30422	101	14	and	and	CCONJ
fcis-30422	101	15	quantitative	quantitative	ADJ
fcis-30422	101	16	performance	performance	NOUN
fcis-30422	101	17	evaluation[j	evaluation[j	NUM
fcis-30422	101	18	]	]	PUNCT
fcis-30422	101	19	.	.	PUNCT
fcis-30422	102	1	journal	journal	PROPN
fcis-30422	102	2	of	of	ADP
fcis-30422	102	3	electronic	electronic	ADJ
fcis-30422	102	4	imaging	imaging	NOUN
fcis-30422	102	5	,	,	PUNCT
fcis-30422	102	6	2004	2004	NUM
fcis-30422	102	7	,	,	PUNCT
fcis-30422	102	8	13(1	13(1	NUM
fcis-30422	102	9	):	):	PUNCT
fcis-30422	102	10	146	146	NUM
fcis-30422	102	11	-	-	SYM
fcis-30422	102	12	168	168	NUM
fcis-30422	102	13	.	.	PUNCT
fcis-30422	103	1	[	[	X
fcis-30422	103	2	12	12	NUM
fcis-30422	103	3	]	]	X
fcis-30422	103	4	mercier	merci	ADJ
fcis-30422	103	5	g	g	PROPN
fcis-30422	103	6	,	,	PUNCT
fcis-30422	103	7	lennon	lennon	PROPN
fcis-30422	103	8	m.	m.	PROPN
fcis-30422	103	9	support	support	PROPN
fcis-30422	103	10	vector	vector	NOUN
fcis-30422	103	11	machines	machine	NOUN
fcis-30422	103	12	for	for	ADP
fcis-30422	103	13	hyperspectral	hyperspectral	ADJ
fcis-30422	103	14	image	image	NOUN
fcis-30422	103	15	classification	classification	NOUN
fcis-30422	103	16	with	with	ADP
fcis-30422	103	17	spectral	spectral	ADJ
fcis-30422	103	18	-	-	PUNCT
fcis-30422	103	19	based	base	VERB
fcis-30422	103	20	kernels	kernel	NOUN
fcis-30422	103	21	[	[	X
fcis-30422	103	22	c	c	X
fcis-30422	103	23	]	]	X
fcis-30422	103	24	//	//	X
fcis-30422	103	25	igarss	igarss	PROPN
fcis-30422	103	26	2003	2003	NUM
fcis-30422	103	27	.	.	PUNCT
fcis-30422	104	1	2003	2003	NUM
fcis-30422	104	2	ieee	ieee	PROPN
fcis-30422	104	3	international	international	PROPN
fcis-30422	104	4	geoscience	geoscience	PROPN
fcis-30422	104	5	and	and	CCONJ
fcis-30422	104	6	remote	remote	ADJ
fcis-30422	104	7	sensing	sense	VERB
fcis-30422	104	8	symposium	symposium	NOUN
fcis-30422	104	9	.	.	PUNCT
fcis-30422	105	1	proceedings	proceeding	NOUN
fcis-30422	105	2	(	(	PUNCT
fcis-30422	105	3	ieee	ieee	NOUN
fcis-30422	105	4	cat	cat	NOUN
fcis-30422	105	5	.	.	PUNCT
fcis-30422	106	1	no	no	INTJ
fcis-30422	106	2	.	.	NOUN
fcis-30422	107	1	03ch37477	03ch37477	NUM
fcis-30422	107	2	)	)	PUNCT
fcis-30422	107	3	.	.	PUNCT
fcis-30422	108	1	ieee	ieee	PROPN
fcis-30422	108	2	,	,	PUNCT
fcis-30422	108	3	2003	2003	NUM
fcis-30422	108	4	,	,	PUNCT
fcis-30422	108	5	1	1	NUM
fcis-30422	108	6	:	:	PUNCT
fcis-30422	108	7	288	288	NUM
fcis-30422	108	8	-	-	SYM
fcis-30422	108	9	290	290	NUM
fcis-30422	108	10	.	.	PUNCT
fcis-30422	109	1	[	[	X
fcis-30422	109	2	13	13	NUM
fcis-30422	109	3	]	]	X
fcis-30422	109	4	noble	noble	ADJ
fcis-30422	109	5	w	w	PROPN
fcis-30422	109	6	s.	s.	PROPN
fcis-30422	109	7	what	what	PRON
fcis-30422	109	8	is	be	AUX
fcis-30422	109	9	a	a	DET
fcis-30422	109	10	support	support	NOUN
fcis-30422	109	11	vector	vector	NOUN
fcis-30422	109	12	machine	machine	NOUN
fcis-30422	109	13	?	?	PUNCT
fcis-30422	110	1	[	[	X
fcis-30422	110	2	j	j	X
fcis-30422	110	3	]	]	X
fcis-30422	110	4	.	.	PUNCT
fcis-30422	111	1	nature	nature	PROPN
fcis-30422	111	2	biotechnology	biotechnology	NOUN
fcis-30422	111	3	,	,	PUNCT
fcis-30422	111	4	2006	2006	NUM
fcis-30422	111	5	,	,	PUNCT
fcis-30422	111	6	24(12	24(12	NUM
fcis-30422	111	7	):	):	PUNCT
fcis-30422	111	8	1565	1565	NUM
fcis-30422	111	9	-	-	SYM
fcis-30422	111	10	1567	1567	NUM
fcis-30422	111	11	.	.	PUNCT
fcis-30422	112	1	[	[	X
fcis-30422	112	2	14	14	NUM
fcis-30422	112	3	]	]	X
fcis-30422	112	4	chang	chang	PROPN
fcis-30422	112	5	c	c	PROPN
fcis-30422	112	6	c	c	PROPN
fcis-30422	112	7	,	,	PUNCT
fcis-30422	112	8	lin	lin	PROPN
fcis-30422	112	9	c	c	PROPN
fcis-30422	112	10	j.	j.	PROPN
fcis-30422	112	11	libsvm	libsvm	PROPN
fcis-30422	112	12	:	:	PUNCT
fcis-30422	112	13	a	a	DET
fcis-30422	112	14	library	library	NOUN
fcis-30422	112	15	for	for	ADP
fcis-30422	112	16	support	support	NOUN
fcis-30422	112	17	vector	vector	NOUN
fcis-30422	112	18	machines[j	machines[j	PROPN
fcis-30422	112	19	]	]	PUNCT
fcis-30422	112	20	.	.	PUNCT
fcis-30422	113	1	acm	acm	PROPN
fcis-30422	113	2	transactions	transaction	NOUN
fcis-30422	113	3	on	on	ADP
fcis-30422	113	4	intelligent	intelligent	ADJ
fcis-30422	113	5	systems	system	NOUN
fcis-30422	113	6	and	and	CCONJ
fcis-30422	113	7	technology	technology	NOUN
fcis-30422	113	8	(	(	PUNCT
fcis-30422	113	9	tist	tist	NOUN
fcis-30422	113	10	)	)	PUNCT
fcis-30422	113	11	,	,	PUNCT
fcis-30422	113	12	2011	2011	NUM
fcis-30422	113	13	,	,	PUNCT
fcis-30422	113	14	2(3	2(3	NUM
fcis-30422	113	15	):	):	PUNCT
fcis-30422	113	16	1	1	NUM
fcis-30422	113	17	-	-	SYM
fcis-30422	113	18	27	27	NUM
fcis-30422	113	19	.	.	PUNCT
fcis-30422	114	1	[	[	X
fcis-30422	114	2	15	15	NUM
fcis-30422	114	3	]	]	X
fcis-30422	114	4	tahir	tahir	PROPN
fcis-30422	114	5	m	m	PROPN
fcis-30422	114	6	w	w	PROPN
fcis-30422	114	7	,	,	PUNCT
fcis-30422	114	8	zaidi	zaidi	PROPN
fcis-30422	114	9	n	n	PROPN
fcis-30422	114	10	a	a	PROPN
fcis-30422	114	11	,	,	PUNCT
fcis-30422	114	12	rao	rao	PROPN
fcis-30422	114	13	a	a	DET
fcis-30422	114	14	a	a	NOUN
fcis-30422	114	15	,	,	PUNCT
fcis-30422	114	16	et	et	PROPN
fcis-30422	114	17	al	al	PROPN
fcis-30422	114	18	.	.	PUNCT
fcis-30422	115	1	a	a	DET
fcis-30422	115	2	fungus	fungus	NOUN
fcis-30422	115	3	spores	spore	NOUN
fcis-30422	115	4	dataset	dataset	VERB
fcis-30422	115	5	and	and	CCONJ
fcis-30422	115	6	a	a	DET
fcis-30422	115	7	convolutional	convolutional	ADJ
fcis-30422	115	8	neural	neural	ADJ
fcis-30422	115	9	network	network	NOUN
fcis-30422	115	10	based	base	VERB
fcis-30422	115	11	approach	approach	NOUN
fcis-30422	115	12	for	for	ADP
fcis-30422	115	13	fungus	fungus	PROPN
fcis-30422	115	14	detection[j	detection[j	PROPN
fcis-30422	115	15	]	]	PUNCT
fcis-30422	115	16	.	.	PUNCT
fcis-30422	116	1	ieee	ieee	NOUN
fcis-30422	116	2	transactions	transaction	NOUN
fcis-30422	116	3	on	on	ADP
fcis-30422	116	4	nanobioscience	nanobioscience	NOUN
fcis-30422	116	5	,	,	PUNCT
fcis-30422	116	6	2018	2018	NUM
fcis-30422	116	7	,	,	PUNCT
fcis-30422	116	8	17(3	17(3	NUM
fcis-30422	116	9	):	):	PUNCT
fcis-30422	116	10	281	281	NUM
fcis-30422	116	11	-	-	SYM
fcis-30422	116	12	290	290	NUM
fcis-30422	116	13	.	.	PUNCT
fcis-30422	117	1	[	[	X
fcis-30422	117	2	16	16	NUM
fcis-30422	117	3	]	]	X
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fcis-30422	117	6	o	o	PROPN
fcis-30422	117	7	,	,	PUNCT
fcis-30422	117	8	kalmady	kalmady	PROPN
fcis-30422	117	9	k	k	PROPN
fcis-30422	117	10	s	s	PROPN
fcis-30422	117	11	,	,	PUNCT
fcis-30422	117	12	rajan	rajan	PROPN
fcis-30422	117	13	j	j	PROPN
fcis-30422	117	14	,	,	PUNCT
fcis-30422	117	15	et	et	PROPN
fcis-30422	117	16	al	al	PROPN
fcis-30422	117	17	.	.	PROPN
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fcis-30422	117	19	detection	detection	NOUN
fcis-30422	117	20	of	of	ADP
fcis-30422	117	21	tuberculosis	tuberculosis	NOUN
fcis-30422	117	22	bacilli	bacilli	NOUN
fcis-30422	117	23	from	from	ADP
fcis-30422	117	24	microscopic	microscopic	ADJ
fcis-30422	117	25	sputum	sputum	NOUN
fcis-30422	117	26	smear	smear	NOUN
fcis-30422	117	27	images	image	NOUN
fcis-30422	117	28	using	use	VERB
fcis-30422	117	29	deep	deep	ADJ
fcis-30422	117	30	learning	learn	VERB
fcis-30422	117	31	methods[j	methods[j	PROPN
fcis-30422	117	32	]	]	PUNCT
fcis-30422	117	33	.	.	PUNCT
fcis-30422	118	1	biocybernetics	biocybernetic	NOUN
fcis-30422	118	2	and	and	CCONJ
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fcis-30422	118	4	engineering	engineering	NOUN
fcis-30422	118	5	,	,	PUNCT
fcis-30422	118	6	2018	2018	NUM
fcis-30422	118	7	,	,	PUNCT
fcis-30422	118	8	38(3	38(3	NUM
fcis-30422	118	9	):	):	PUNCT
fcis-30422	118	10	691	691	NUM
fcis-30422	118	11	-	-	SYM
fcis-30422	118	12	699	699	NUM
fcis-30422	118	13	.	.	PUNCT