id	sid	tid	token	lemma	pos
fcis-31608	1	1	frontiers	frontier	NOUN
fcis-31608	1	2	in	in	ADP
fcis-31608	1	3	computing	computing	NOUN
fcis-31608	1	4	and	and	CCONJ
fcis-31608	1	5	intelligent	intelligent	ADJ
fcis-31608	1	6	systems	system	NOUN
fcis-31608	1	7	issn	issn	VERB
fcis-31608	1	8	:	:	PUNCT
fcis-31608	1	9	2832	2832	NUM
fcis-31608	1	10	-	-	SYM
fcis-31608	1	11	6024	6024	NUM
fcis-31608	1	12	|	|	NOUN
fcis-31608	1	13	vol	vol	NOUN
fcis-31608	1	14	.	.	PROPN
fcis-31608	2	1	13	13	NUM
fcis-31608	2	2	,	,	PUNCT
fcis-31608	2	3	no	no	INTJ
fcis-31608	2	4	.	.	NOUN
fcis-31608	2	5	2	2	NUM
fcis-31608	2	6	,	,	PUNCT
fcis-31608	2	7	2025	2025	NUM
fcis-31608	2	8	41	41	NUM
fcis-31608	2	9	research	research	NOUN
fcis-31608	2	10	on	on	ADP
fcis-31608	2	11	a	a	DET
fcis-31608	2	12	non‐contact	non‐contact	PROPN
fcis-31608	2	13	cattle	cattle	NOUN
fcis-31608	2	14	weight	weight	NOUN
fcis-31608	2	15	measurement	measurement	NOUN
fcis-31608	2	16	system	system	NOUN
fcis-31608	2	17	based	base	VERB
fcis-31608	2	18	on	on	ADP
fcis-31608	2	19	deep	deep	ADJ
fcis-31608	2	20	learning	learn	VERB
fcis-31608	2	21	lihao	lihao	PROPN
fcis-31608	2	22	qin	qin	PROPN
fcis-31608	2	23	,	,	PUNCT
fcis-31608	2	24	zhongyu	zhongyu	PROPN
fcis-31608	2	25	ma	ma	PROPN
fcis-31608	2	26	,	,	PUNCT
fcis-31608	2	27	zhanshuo	zhanshuo	PROPN
fcis-31608	2	28	zhang	zhang	PROPN
fcis-31608	2	29	,	,	PUNCT
fcis-31608	2	30	yongfeng	yongfeng	PROPN
fcis-31608	2	31	zuo	zuo	PROPN
fcis-31608	2	32	,	,	PUNCT
fcis-31608	2	33	dan	dan	PROPN
fcis-31608	2	34	he	he	PROPN
fcis-31608	2	35	xinjiang	xinjiang	PROPN
fcis-31608	2	36	college	college	PROPN
fcis-31608	2	37	of	of	ADP
fcis-31608	2	38	science	science	PROPN
fcis-31608	2	39	&	&	CCONJ
fcis-31608	2	40	technology	technology	PROPN
fcis-31608	2	41	,	,	PUNCT
fcis-31608	2	42	kuerle	kuerle	PROPN
fcis-31608	2	43	xinjiang	xinjiang	PROPN
fcis-31608	2	44	,	,	PUNCT
fcis-31608	2	45	841000	841000	NUM
fcis-31608	2	46	,	,	PUNCT
fcis-31608	2	47	china	china	PROPN
fcis-31608	2	48	abstract	abstract	NOUN
fcis-31608	2	49	:	:	PUNCT
fcis-31608	2	50	as	as	SCONJ
fcis-31608	2	51	the	the	DET
fcis-31608	2	52	smart	smart	ADJ
fcis-31608	2	53	livestock	livestock	NOUN
fcis-31608	2	54	industry	industry	NOUN
fcis-31608	2	55	continues	continue	VERB
fcis-31608	2	56	to	to	PART
fcis-31608	2	57	evolve	evolve	VERB
fcis-31608	2	58	,	,	PUNCT
fcis-31608	2	59	traditional	traditional	ADJ
fcis-31608	2	60	methods	method	NOUN
fcis-31608	2	61	of	of	ADP
fcis-31608	2	62	measuring	measure	VERB
fcis-31608	2	63	cattle	cattle	NOUN
fcis-31608	2	64	weight	weight	NOUN
fcis-31608	2	65	are	be	AUX
fcis-31608	2	66	increasingly	increasingly	ADV
fcis-31608	2	67	inadequate	inadequate	ADJ
fcis-31608	2	68	for	for	ADP
fcis-31608	2	69	the	the	DET
fcis-31608	2	70	demands	demand	NOUN
fcis-31608	2	71	of	of	ADP
fcis-31608	2	72	large	large	ADJ
fcis-31608	2	73	-	-	PUNCT
fcis-31608	2	74	scale	scale	NOUN
fcis-31608	2	75	farms	farm	NOUN
fcis-31608	2	76	.	.	PUNCT
fcis-31608	3	1	conventional	conventional	ADJ
fcis-31608	3	2	approaches	approach	NOUN
fcis-31608	3	3	rely	rely	VERB
fcis-31608	3	4	on	on	ADP
fcis-31608	3	5	manual	manual	ADJ
fcis-31608	3	6	weighing	weigh	VERB
fcis-31608	3	7	or	or	CCONJ
fcis-31608	3	8	bulky	bulky	ADJ
fcis-31608	3	9	equipment	equipment	NOUN
fcis-31608	3	10	,	,	PUNCT
fcis-31608	3	11	which	which	PRON
fcis-31608	3	12	are	be	AUX
fcis-31608	3	13	inefficient	inefficient	ADJ
fcis-31608	3	14	and	and	CCONJ
fcis-31608	3	15	lack	lack	NOUN
fcis-31608	3	16	precision	precision	NOUN
fcis-31608	3	17	,	,	PUNCT
fcis-31608	3	18	failing	fail	VERB
fcis-31608	3	19	to	to	PART
fcis-31608	3	20	provide	provide	VERB
fcis-31608	3	21	real	real	ADJ
fcis-31608	3	22	-	-	PUNCT
fcis-31608	3	23	time	time	NOUN
fcis-31608	3	24	,	,	PUNCT
fcis-31608	3	25	accurate	accurate	ADJ
fcis-31608	3	26	weight	weight	NOUN
fcis-31608	3	27	measurements	measurement	NOUN
fcis-31608	3	28	required	require	VERB
fcis-31608	3	29	in	in	ADP
fcis-31608	3	30	modern	modern	ADJ
fcis-31608	3	31	breeding	breeding	NOUN
fcis-31608	3	32	facilities	facility	NOUN
fcis-31608	3	33	.	.	PUNCT
fcis-31608	4	1	to	to	PART
fcis-31608	4	2	address	address	VERB
fcis-31608	4	3	this	this	DET
fcis-31608	4	4	challenge	challenge	NOUN
fcis-31608	4	5	,	,	PUNCT
fcis-31608	4	6	this	this	DET
fcis-31608	4	7	paper	paper	NOUN
fcis-31608	4	8	proposes	propose	VERB
fcis-31608	4	9	an	an	DET
fcis-31608	4	10	automatic	automatic	ADJ
fcis-31608	4	11	cattle	cattle	NOUN
fcis-31608	4	12	weight	weight	NOUN
fcis-31608	4	13	measurement	measurement	NOUN
fcis-31608	4	14	system	system	NOUN
fcis-31608	4	15	based	base	VERB
fcis-31608	4	16	on	on	ADP
fcis-31608	4	17	deep	deep	ADJ
fcis-31608	4	18	learning	learning	NOUN
fcis-31608	4	19	.	.	PUNCT
fcis-31608	5	1	the	the	DET
fcis-31608	5	2	system	system	NOUN
fcis-31608	5	3	employs	employ	VERB
fcis-31608	5	4	deep	deep	ADJ
fcis-31608	5	5	learning	learning	NOUN
fcis-31608	5	6	technology	technology	NOUN
fcis-31608	5	7	for	for	ADP
fcis-31608	5	8	keypoint	keypoint	NOUN
fcis-31608	5	9	detection	detection	NOUN
fcis-31608	5	10	on	on	ADP
fcis-31608	5	11	cattle	cattle	NOUN
fcis-31608	5	12	and	and	CCONJ
fcis-31608	5	13	uses	use	VERB
fcis-31608	5	14	these	these	DET
fcis-31608	5	15	detection	detection	NOUN
fcis-31608	5	16	results	result	NOUN
fcis-31608	5	17	to	to	PART
fcis-31608	5	18	predict	predict	VERB
fcis-31608	5	19	weight	weight	NOUN
fcis-31608	5	20	,	,	PUNCT
fcis-31608	5	21	enabling	enable	VERB
fcis-31608	5	22	non	non	NOUN
fcis-31608	5	23	-	-	NOUN
fcis-31608	5	24	contact	contact	ADJ
fcis-31608	5	25	,	,	PUNCT
fcis-31608	5	26	high	high	ADJ
fcis-31608	5	27	-	-	PUNCT
fcis-31608	5	28	precision	precision	NOUN
fcis-31608	5	29	measurement	measurement	NOUN
fcis-31608	5	30	.	.	PUNCT
fcis-31608	6	1	for	for	ADP
fcis-31608	6	2	keypoint	keypoint	NOUN
fcis-31608	6	3	detection	detection	NOUN
fcis-31608	6	4	,	,	PUNCT
fcis-31608	6	5	mobilenetv3	mobilenetv3	PROPN
fcis-31608	6	6	is	be	AUX
fcis-31608	6	7	utilized	utilize	VERB
fcis-31608	6	8	as	as	ADP
fcis-31608	6	9	the	the	DET
fcis-31608	6	10	backbone	backbone	NOUN
fcis-31608	6	11	architecture	architecture	NOUN
fcis-31608	6	12	,	,	PUNCT
fcis-31608	6	13	while	while	SCONJ
fcis-31608	6	14	calibration	calibration	NOUN
fcis-31608	6	15	object	object	NOUN
fcis-31608	6	16	recognition	recognition	NOUN
fcis-31608	6	17	technology	technology	NOUN
fcis-31608	6	18	extracts	extract	VERB
fcis-31608	6	19	depth	depth	NOUN
fcis-31608	6	20	information	information	NOUN
fcis-31608	6	21	from	from	ADP
fcis-31608	6	22	images	image	NOUN
fcis-31608	6	23	to	to	PART
fcis-31608	6	24	perform	perform	VERB
fcis-31608	6	25	depth	depth	NOUN
fcis-31608	6	26	correction	correction	NOUN
fcis-31608	6	27	,	,	PUNCT
fcis-31608	6	28	thereby	thereby	ADV
fcis-31608	6	29	enhancing	enhance	VERB
fcis-31608	6	30	the	the	DET
fcis-31608	6	31	accuracy	accuracy	NOUN
fcis-31608	6	32	of	of	ADP
fcis-31608	6	33	image	image	NOUN
fcis-31608	6	34	scaling	scaling	NOUN
fcis-31608	6	35	.	.	PUNCT
fcis-31608	7	1	weight	weight	NOUN
fcis-31608	7	2	prediction	prediction	NOUN
fcis-31608	7	3	is	be	AUX
fcis-31608	7	4	conducted	conduct	VERB
fcis-31608	7	5	through	through	ADP
fcis-31608	7	6	a	a	DET
fcis-31608	7	7	regression	regression	NOUN
fcis-31608	7	8	model	model	NOUN
fcis-31608	7	9	that	that	PRON
fcis-31608	7	10	integrates	integrate	VERB
fcis-31608	7	11	keypoint	keypoint	NOUN
fcis-31608	7	12	coordinates	coordinate	NOUN
fcis-31608	7	13	with	with	ADP
fcis-31608	7	14	geometric	geometric	ADJ
fcis-31608	7	15	features	feature	NOUN
fcis-31608	7	16	such	such	ADJ
fcis-31608	7	17	as	as	ADP
fcis-31608	7	18	body	body	NOUN
fcis-31608	7	19	length	length	NOUN
fcis-31608	7	20	,	,	PUNCT
fcis-31608	7	21	shoulder	shoulder	NOUN
fcis-31608	7	22	height	height	NOUN
fcis-31608	7	23	,	,	PUNCT
fcis-31608	7	24	and	and	CCONJ
fcis-31608	7	25	chest	chest	NOUN
fcis-31608	7	26	girth	girth	NOUN
fcis-31608	7	27	to	to	PART
fcis-31608	7	28	estimate	estimate	VERB
fcis-31608	7	29	the	the	DET
fcis-31608	7	30	cattle	cattle	NOUN
fcis-31608	7	31	’s	’s	PART
fcis-31608	7	32	weight	weight	NOUN
fcis-31608	7	33	.	.	PUNCT
fcis-31608	8	1	experimental	experimental	ADJ
fcis-31608	8	2	results	result	NOUN
fcis-31608	8	3	demonstrate	demonstrate	VERB
fcis-31608	8	4	that	that	SCONJ
fcis-31608	8	5	the	the	DET
fcis-31608	8	6	proposed	propose	VERB
fcis-31608	8	7	system	system	NOUN
fcis-31608	8	8	achieves	achieve	VERB
fcis-31608	8	9	a	a	DET
fcis-31608	8	10	high	high	ADJ
fcis-31608	8	11	level	level	NOUN
fcis-31608	8	12	of	of	ADP
fcis-31608	8	13	accuracy	accuracy	NOUN
fcis-31608	8	14	in	in	ADP
fcis-31608	8	15	both	both	DET
fcis-31608	8	16	keypoint	keypoint	NOUN
fcis-31608	8	17	detection	detection	NOUN
fcis-31608	8	18	and	and	CCONJ
fcis-31608	8	19	weight	weight	NOUN
fcis-31608	8	20	prediction	prediction	NOUN
fcis-31608	8	21	tasks	task	NOUN
fcis-31608	8	22	,	,	PUNCT
fcis-31608	8	23	highlighting	highlight	VERB
fcis-31608	8	24	its	its	PRON
fcis-31608	8	25	potential	potential	NOUN
fcis-31608	8	26	for	for	ADP
fcis-31608	8	27	automated	automate	VERB
fcis-31608	8	28	weight	weight	NOUN
fcis-31608	8	29	estimation	estimation	NOUN
fcis-31608	8	30	in	in	ADP
fcis-31608	8	31	modern	modern	ADJ
fcis-31608	8	32	livestock	livestock	NOUN
fcis-31608	8	33	management	management	NOUN
fcis-31608	8	34	.	.	PUNCT
fcis-31608	9	1	keywords	keyword	NOUN
fcis-31608	9	2	:	:	PUNCT
fcis-31608	9	3	computer	computer	NOUN
fcis-31608	9	4	vision	vision	NOUN
fcis-31608	9	5	;	;	PUNCT
fcis-31608	9	6	cattle	cattle	NOUN
fcis-31608	9	7	body	body	NOUN
fcis-31608	9	8	weight	weight	NOUN
fcis-31608	9	9	measurement	measurement	NOUN
fcis-31608	9	10	;	;	PUNCT
fcis-31608	9	11	deep	deep	ADJ
fcis-31608	9	12	learning	learning	NOUN
fcis-31608	9	13	;	;	PUNCT
fcis-31608	9	14	lightweight	lightweight	ADJ
fcis-31608	9	15	network	network	NOUN
fcis-31608	9	16	.	.	PUNCT
fcis-31608	10	1	1	1	X
fcis-31608	10	2	.	.	X
fcis-31608	10	3	introduction	introduction	NOUN
fcis-31608	10	4	cattle	cattle	NOUN
fcis-31608	10	5	weight	weight	NOUN
fcis-31608	10	6	is	be	AUX
fcis-31608	10	7	a	a	DET
fcis-31608	10	8	crucial	crucial	ADJ
fcis-31608	10	9	indicator	indicator	NOUN
fcis-31608	10	10	in	in	ADP
fcis-31608	10	11	livestock	livestock	NOUN
fcis-31608	10	12	production	production	NOUN
fcis-31608	10	13	,	,	PUNCT
fcis-31608	10	14	used	use	VERB
fcis-31608	10	15	to	to	PART
fcis-31608	10	16	assess	assess	VERB
fcis-31608	10	17	growth	growth	NOUN
fcis-31608	10	18	and	and	CCONJ
fcis-31608	10	19	development	development	NOUN
fcis-31608	10	20	,	,	PUNCT
fcis-31608	10	21	feed	feed	NOUN
fcis-31608	10	22	conversion	conversion	NOUN
fcis-31608	10	23	efficiency	efficiency	NOUN
fcis-31608	10	24	,	,	PUNCT
fcis-31608	10	25	disease	disease	NOUN
fcis-31608	10	26	diagnosis	diagnosis	NOUN
fcis-31608	10	27	,	,	PUNCT
fcis-31608	10	28	and	and	CCONJ
fcis-31608	10	29	precision	precision	NOUN
fcis-31608	10	30	feeding	feeding	NOUN
fcis-31608	10	31	management	management	NOUN
fcis-31608	10	32	[	[	X
fcis-31608	10	33	1	1	NUM
fcis-31608	10	34	]	]	PUNCT
fcis-31608	10	35	.	.	PUNCT
fcis-31608	11	1	traditional	traditional	ADJ
fcis-31608	11	2	methods	method	NOUN
fcis-31608	11	3	for	for	ADP
fcis-31608	11	4	measuring	measure	VERB
fcis-31608	11	5	cattle	cattle	NOUN
fcis-31608	11	6	weight	weight	NOUN
fcis-31608	11	7	primarily	primarily	ADV
fcis-31608	11	8	include	include	VERB
fcis-31608	11	9	weighing	weigh	VERB
fcis-31608	11	10	and	and	CCONJ
fcis-31608	11	11	estimating	estimate	VERB
fcis-31608	11	12	body	body	NOUN
fcis-31608	11	13	size	size	NOUN
fcis-31608	11	14	.	.	PUNCT
fcis-31608	12	1	while	while	SCONJ
fcis-31608	12	2	weighing	weighing	NOUN
fcis-31608	12	3	methods	method	NOUN
fcis-31608	12	4	are	be	AUX
fcis-31608	12	5	highly	highly	ADV
fcis-31608	12	6	accurate	accurate	ADJ
fcis-31608	12	7	,	,	PUNCT
fcis-31608	12	8	they	they	PRON
fcis-31608	12	9	require	require	VERB
fcis-31608	12	10	specialized	specialized	ADJ
fcis-31608	12	11	equipment	equipment	NOUN
fcis-31608	12	12	,	,	PUNCT
fcis-31608	12	13	are	be	AUX
fcis-31608	12	14	cumbersome	cumbersome	ADJ
fcis-31608	12	15	to	to	PART
fcis-31608	12	16	operate	operate	VERB
fcis-31608	12	17	,	,	PUNCT
fcis-31608	12	18	and	and	CCONJ
fcis-31608	12	19	can	can	AUX
fcis-31608	12	20	easily	easily	ADV
fcis-31608	12	21	cause	cause	VERB
fcis-31608	12	22	stress	stress	NOUN
fcis-31608	12	23	in	in	ADP
fcis-31608	12	24	cattle	cattle	NOUN
fcis-31608	12	25	,	,	PUNCT
fcis-31608	12	26	making	make	VERB
fcis-31608	12	27	them	they	PRON
fcis-31608	12	28	unsuitable	unsuitable	ADJ
fcis-31608	12	29	for	for	ADP
fcis-31608	12	30	largescale	largescale	NOUN
fcis-31608	12	31	,	,	PUNCT
fcis-31608	12	32	high	high	ADJ
fcis-31608	12	33	-	-	PUNCT
fcis-31608	12	34	frequency	frequency	NOUN
fcis-31608	12	35	measurements	measurement	NOUN
fcis-31608	12	36	[	[	X
fcis-31608	12	37	2	2	NUM
fcis-31608	12	38	]	]	PUNCT
fcis-31608	12	39	.	.	PUNCT
fcis-31608	13	1	body	body	NOUN
fcis-31608	13	2	size	size	NOUN
fcis-31608	13	3	estimation	estimation	NOUN
fcis-31608	13	4	involves	involve	VERB
fcis-31608	13	5	measuring	measure	VERB
fcis-31608	13	6	parameters	parameter	NOUN
fcis-31608	13	7	such	such	ADJ
fcis-31608	13	8	as	as	ADP
fcis-31608	13	9	height	height	NOUN
fcis-31608	13	10	,	,	PUNCT
fcis-31608	13	11	diagonal	diagonal	ADJ
fcis-31608	13	12	length	length	NOUN
fcis-31608	13	13	,	,	PUNCT
fcis-31608	13	14	and	and	CCONJ
fcis-31608	13	15	chest	chest	NOUN
fcis-31608	13	16	circumference	circumference	NOUN
fcis-31608	13	17	,	,	PUNCT
fcis-31608	13	18	then	then	ADV
fcis-31608	13	19	applying	apply	VERB
fcis-31608	13	20	empirical	empirical	ADJ
fcis-31608	13	21	formulas	formula	NOUN
fcis-31608	13	22	to	to	PART
fcis-31608	13	23	estimate	estimate	VERB
fcis-31608	13	24	weight	weight	NOUN
fcis-31608	13	25	.	.	PUNCT
fcis-31608	14	1	however	however	ADV
fcis-31608	14	2	,	,	PUNCT
fcis-31608	14	3	this	this	DET
fcis-31608	14	4	method	method	NOUN
fcis-31608	14	5	typically	typically	ADV
fcis-31608	14	6	requires	require	VERB
fcis-31608	14	7	manual	manual	ADJ
fcis-31608	14	8	operation	operation	NOUN
fcis-31608	14	9	,	,	PUNCT
fcis-31608	14	10	which	which	PRON
fcis-31608	14	11	is	be	AUX
fcis-31608	14	12	inefficient	inefficient	ADJ
fcis-31608	14	13	and	and	CCONJ
fcis-31608	14	14	whose	whose	DET
fcis-31608	14	15	accuracy	accuracy	NOUN
fcis-31608	14	16	is	be	AUX
fcis-31608	14	17	heavily	heavily	ADV
fcis-31608	14	18	influenced	influence	VERB
fcis-31608	14	19	by	by	ADP
fcis-31608	14	20	the	the	DET
fcis-31608	14	21	operator	operator	NOUN
fcis-31608	14	22	’s	’s	PART
fcis-31608	14	23	experience	experience	NOUN
fcis-31608	14	24	and	and	CCONJ
fcis-31608	14	25	the	the	DET
fcis-31608	14	26	cattle	cattle	NOUN
fcis-31608	14	27	’s	’s	PART
fcis-31608	14	28	cooperation	cooperation	NOUN
fcis-31608	14	29	[	[	X
fcis-31608	14	30	3	3	NUM
fcis-31608	14	31	]	]	PUNCT
fcis-31608	14	32	.	.	PUNCT
fcis-31608	15	1	with	with	ADP
fcis-31608	15	2	the	the	DET
fcis-31608	15	3	rapid	rapid	ADJ
fcis-31608	15	4	advancement	advancement	NOUN
fcis-31608	15	5	of	of	ADP
fcis-31608	15	6	computer	computer	NOUN
fcis-31608	15	7	vision	vision	NOUN
fcis-31608	15	8	and	and	CCONJ
fcis-31608	15	9	deep	deep	ADJ
fcis-31608	15	10	learning	learning	NOUN
fcis-31608	15	11	technologies	technology	NOUN
fcis-31608	15	12	,	,	PUNCT
fcis-31608	15	13	non	non	ADJ
fcis-31608	15	14	-	-	ADJ
fcis-31608	15	15	contact	contact	ADJ
fcis-31608	15	16	measurement	measurement	NOUN
fcis-31608	15	17	methods	method	NOUN
fcis-31608	15	18	offer	offer	VERB
fcis-31608	15	19	innovative	innovative	ADJ
fcis-31608	15	20	solutions	solution	NOUN
fcis-31608	15	21	to	to	PART
fcis-31608	15	22	overcome	overcome	VERB
fcis-31608	15	23	the	the	DET
fcis-31608	15	24	limitations	limitation	NOUN
fcis-31608	15	25	of	of	ADP
fcis-31608	15	26	traditional	traditional	ADJ
fcis-31608	15	27	cattle	cattle	NOUN
fcis-31608	15	28	weight	weight	NOUN
fcis-31608	15	29	measurement	measurement	NOUN
fcis-31608	15	30	techniques	technique	NOUN
fcis-31608	15	31	.	.	PUNCT
fcis-31608	16	1	deep	deep	ADJ
fcis-31608	16	2	learning	learning	NOUN
fcis-31608	16	3	has	have	AUX
fcis-31608	16	4	demonstrated	demonstrate	VERB
fcis-31608	16	5	powerful	powerful	ADJ
fcis-31608	16	6	capabilities	capability	NOUN
fcis-31608	16	7	in	in	ADP
fcis-31608	16	8	image	image	NOUN
fcis-31608	16	9	recognition	recognition	NOUN
fcis-31608	16	10	,	,	PUNCT
fcis-31608	16	11	object	object	NOUN
fcis-31608	16	12	detection	detection	NOUN
fcis-31608	16	13	,	,	PUNCT
fcis-31608	16	14	and	and	CCONJ
fcis-31608	16	15	pose	pose	VERB
fcis-31608	16	16	estimation	estimation	NOUN
fcis-31608	16	17	,	,	PUNCT
fcis-31608	16	18	establishing	establish	VERB
fcis-31608	16	19	a	a	DET
fcis-31608	16	20	foundation	foundation	NOUN
fcis-31608	16	21	for	for	ADP
fcis-31608	16	22	automated	automate	VERB
fcis-31608	16	23	,	,	PUNCT
fcis-31608	16	24	high	high	ADJ
fcis-31608	16	25	-	-	PUNCT
fcis-31608	16	26	precision	precision	NOUN
fcis-31608	16	27	measurement	measurement	NOUN
fcis-31608	16	28	of	of	ADP
fcis-31608	16	29	cattle	cattle	NOUN
fcis-31608	16	30	size	size	NOUN
fcis-31608	16	31	and	and	CCONJ
fcis-31608	16	32	weight	weight	NOUN
fcis-31608	16	33	[	[	X
fcis-31608	16	34	4	4	NUM
fcis-31608	16	35	,	,	PUNCT
fcis-31608	16	36	5	5	NUM
fcis-31608	16	37	]	]	PUNCT
fcis-31608	16	38	.	.	PUNCT
fcis-31608	17	1	in	in	ADP
fcis-31608	17	2	recent	recent	ADJ
fcis-31608	17	3	years	year	NOUN
fcis-31608	17	4	,	,	PUNCT
fcis-31608	17	5	researchers	researcher	NOUN
fcis-31608	17	6	both	both	CCONJ
fcis-31608	17	7	domestically	domestically	ADV
fcis-31608	17	8	and	and	CCONJ
fcis-31608	17	9	internationally	internationally	ADV
fcis-31608	17	10	have	have	AUX
fcis-31608	17	11	conducted	conduct	VERB
fcis-31608	17	12	extensive	extensive	ADJ
fcis-31608	17	13	studies	study	NOUN
fcis-31608	17	14	on	on	ADP
fcis-31608	17	15	non	non	ADJ
fcis-31608	17	16	-	-	ADJ
fcis-31608	17	17	contact	contact	ADJ
fcis-31608	17	18	measurement	measurement	NOUN
fcis-31608	17	19	of	of	ADP
fcis-31608	17	20	cattle	cattle	NOUN
fcis-31608	17	21	size	size	NOUN
fcis-31608	17	22	and	and	CCONJ
fcis-31608	17	23	weight	weight	NOUN
fcis-31608	17	24	using	use	VERB
fcis-31608	17	25	deep	deep	ADJ
fcis-31608	17	26	learning	learning	NOUN
fcis-31608	17	27	.	.	PUNCT
fcis-31608	18	1	in	in	ADP
fcis-31608	18	2	the	the	DET
fcis-31608	18	3	field	field	NOUN
fcis-31608	18	4	of	of	ADP
fcis-31608	18	5	size	size	NOUN
fcis-31608	18	6	measurement	measurement	NOUN
fcis-31608	18	7	,	,	PUNCT
fcis-31608	18	8	chao	chao	PROPN
fcis-31608	18	9	haitian	haitian	PROPN
fcis-31608	19	1	[	[	X
fcis-31608	19	2	2	2	NUM
fcis-31608	19	3	]	]	PUNCT
fcis-31608	19	4	was	be	AUX
fcis-31608	19	5	an	an	DET
fcis-31608	19	6	early	early	ADJ
fcis-31608	19	7	pioneer	pioneer	NOUN
fcis-31608	19	8	in	in	ADP
fcis-31608	19	9	exploring	explore	VERB
fcis-31608	19	10	non	non	ADJ
fcis-31608	19	11	-	-	ADJ
fcis-31608	19	12	contact	contact	ADJ
fcis-31608	19	13	measurement	measurement	NOUN
fcis-31608	19	14	systems	system	NOUN
fcis-31608	19	15	for	for	ADP
fcis-31608	19	16	cattle	cattle	NOUN
fcis-31608	19	17	size	size	NOUN
fcis-31608	19	18	.	.	PUNCT
fcis-31608	20	1	liu	liu	PROPN
fcis-31608	20	2	wei	wei	PROPN
fcis-31608	21	1	[	[	X
fcis-31608	21	2	6	6	NUM
fcis-31608	21	3	]	]	PUNCT
fcis-31608	21	4	and	and	CCONJ
fcis-31608	21	5	guan	guan	PROPN
fcis-31608	21	6	xiaopeng	xiaopeng	PROPN
fcis-31608	22	1	[	[	X
fcis-31608	22	2	7	7	NUM
fcis-31608	22	3	]	]	PUNCT
fcis-31608	22	4	investigated	investigate	VERB
fcis-31608	22	5	cattle	cattle	NOUN
fcis-31608	22	6	size	size	NOUN
fcis-31608	22	7	measurement	measurement	NOUN
fcis-31608	22	8	methods	method	NOUN
fcis-31608	22	9	based	base	VERB
fcis-31608	22	10	on	on	ADP
fcis-31608	22	11	deep	deep	ADJ
fcis-31608	22	12	learning	learning	NOUN
fcis-31608	22	13	and	and	CCONJ
fcis-31608	22	14	depth	depth	NOUN
fcis-31608	22	15	estimation	estimation	NOUN
fcis-31608	22	16	,	,	PUNCT
fcis-31608	22	17	respectively	respectively	ADV
fcis-31608	22	18	.	.	PUNCT
fcis-31608	23	1	zhang	zhang	PROPN
fcis-31608	23	2	xianyu	xianyu	PROPN
fcis-31608	24	1	[	[	X
fcis-31608	24	2	8	8	NUM
fcis-31608	24	3	]	]	PUNCT
fcis-31608	24	4	further	far	ADV
fcis-31608	24	5	advanced	advance	VERB
fcis-31608	24	6	automatic	automatic	ADJ
fcis-31608	24	7	cattle	cattle	NOUN
fcis-31608	24	8	size	size	NOUN
fcis-31608	24	9	measurement	measurement	NOUN
fcis-31608	24	10	techniques	technique	NOUN
fcis-31608	24	11	using	use	VERB
fcis-31608	24	12	deep	deep	ADJ
fcis-31608	24	13	learning	learning	NOUN
fcis-31608	24	14	.	.	PUNCT
fcis-31608	25	1	deng	deng	PROPN
fcis-31608	25	2	hongxing	hongxe	VERB
fcis-31608	25	3	et	et	PROPN
fcis-31608	25	4	al	al	PROPN
fcis-31608	25	5	.	.	PUNCT
fcis-31608	26	1	[	[	X
fcis-31608	26	2	9	9	NUM
fcis-31608	26	3	]	]	PUNCT
fcis-31608	26	4	achieved	achieve	VERB
fcis-31608	26	5	precise	precise	ADJ
fcis-31608	26	6	measurement	measurement	NOUN
fcis-31608	26	7	of	of	ADP
fcis-31608	26	8	dairy	dairy	NOUN
fcis-31608	26	9	cattle	cattle	NOUN
fcis-31608	26	10	size	size	NOUN
fcis-31608	26	11	by	by	ADP
fcis-31608	26	12	combining	combine	VERB
fcis-31608	26	13	binocular	binocular	ADJ
fcis-31608	26	14	stereo	stereo	NOUN
fcis-31608	26	15	matching	matching	NOUN
fcis-31608	26	16	with	with	ADP
fcis-31608	26	17	an	an	DET
fcis-31608	26	18	improved	improved	ADJ
fcis-31608	26	19	yolov8n	yolov8n	NOUN
fcis-31608	26	20	-	-	PUNCT
fcis-31608	26	21	pose	pose	NOUN
fcis-31608	26	22	keypoint	keypoint	NOUN
fcis-31608	26	23	detection	detection	NOUN
fcis-31608	26	24	model	model	NOUN
fcis-31608	26	25	.	.	PUNCT
fcis-31608	27	1	li	li	PROPN
fcis-31608	27	2	et	et	PROPN
fcis-31608	27	3	al	al	PROPN
fcis-31608	27	4	.	.	PUNCT
fcis-31608	28	1	[	[	X
fcis-31608	28	2	10	10	NUM
fcis-31608	28	3	]	]	PUNCT
fcis-31608	28	4	also	also	ADV
fcis-31608	28	5	accomplished	accomplish	VERB
fcis-31608	28	6	automated	automate	VERB
fcis-31608	28	7	measurement	measurement	NOUN
fcis-31608	28	8	of	of	ADP
fcis-31608	28	9	beef	beef	NOUN
fcis-31608	28	10	cattle	cattle	NOUN
fcis-31608	28	11	size	size	VERB
fcis-31608	28	12	through	through	ADP
fcis-31608	28	13	keypoint	keypoint	NOUN
fcis-31608	28	14	detection	detection	NOUN
fcis-31608	28	15	and	and	CCONJ
fcis-31608	28	16	monocular	monocular	ADJ
fcis-31608	28	17	depth	depth	NOUN
fcis-31608	28	18	estimation	estimation	NOUN
fcis-31608	28	19	.	.	PUNCT
fcis-31608	29	1	these	these	DET
fcis-31608	29	2	studies	study	NOUN
fcis-31608	29	3	collectively	collectively	ADV
fcis-31608	29	4	demonstrate	demonstrate	VERB
fcis-31608	29	5	significant	significant	ADJ
fcis-31608	29	6	progress	progress	NOUN
fcis-31608	29	7	in	in	ADP
fcis-31608	29	8	the	the	DET
fcis-31608	29	9	non	non	ADJ
fcis-31608	29	10	-	-	ADJ
fcis-31608	29	11	contact	contact	ADJ
fcis-31608	29	12	acquisition	acquisition	NOUN
fcis-31608	29	13	of	of	ADP
fcis-31608	29	14	cattle	cattle	NOUN
fcis-31608	29	15	size	size	NOUN
fcis-31608	29	16	using	use	VERB
fcis-31608	29	17	deep	deep	ADJ
fcis-31608	29	18	learning	learning	NOUN
fcis-31608	29	19	.	.	PUNCT
fcis-31608	30	1	regarding	regard	VERB
fcis-31608	30	2	weight	weight	NOUN
fcis-31608	30	3	estimation	estimation	NOUN
fcis-31608	30	4	,	,	PUNCT
fcis-31608	30	5	zhang	zhang	PROPN
fcis-31608	30	6	shuai	shuai	PROPN
fcis-31608	31	1	[	[	X
fcis-31608	31	2	11	11	NUM
fcis-31608	31	3	]	]	PUNCT
fcis-31608	31	4	applied	apply	VERB
fcis-31608	31	5	deep	deep	ADJ
fcis-31608	31	6	learning	learning	NOUN
fcis-31608	31	7	methods	method	NOUN
fcis-31608	31	8	to	to	PART
fcis-31608	31	9	predict	predict	VERB
fcis-31608	31	10	the	the	DET
fcis-31608	31	11	size	size	NOUN
fcis-31608	31	12	and	and	CCONJ
fcis-31608	31	13	weight	weight	NOUN
fcis-31608	31	14	of	of	ADP
fcis-31608	31	15	jinnan	jinnan	PROPN
fcis-31608	31	16	cattle	cattle	NOUN
fcis-31608	31	17	.	.	PUNCT
fcis-31608	32	1	peng	peng	PROPN
fcis-31608	32	2	zhaoyuan	zhaoyuan	PROPN
fcis-31608	33	1	[	[	X
fcis-31608	33	2	12	12	NUM
fcis-31608	33	3	]	]	PUNCT
fcis-31608	33	4	developed	develop	VERB
fcis-31608	33	5	a	a	DET
fcis-31608	33	6	non	non	ADJ
fcis-31608	33	7	-	-	ADJ
fcis-31608	33	8	contact	contact	ADJ
fcis-31608	33	9	weight	weight	NOUN
fcis-31608	33	10	measurement	measurement	NOUN
fcis-31608	33	11	method	method	NOUN
fcis-31608	33	12	for	for	ADP
fcis-31608	33	13	yaks	yak	NOUN
fcis-31608	33	14	based	base	VERB
fcis-31608	33	15	on	on	ADP
fcis-31608	33	16	deep	deep	ADJ
fcis-31608	33	17	learning	learning	NOUN
fcis-31608	33	18	.	.	PUNCT
fcis-31608	34	1	lan	lan	PROPN
fcis-31608	34	2	leibin	leibin	PROPN
fcis-31608	35	1	[	[	X
fcis-31608	35	2	13	13	NUM
fcis-31608	35	3	]	]	PUNCT
fcis-31608	35	4	focused	focus	VERB
fcis-31608	35	5	on	on	ADP
fcis-31608	35	6	algorithms	algorithm	NOUN
fcis-31608	35	7	for	for	ADP
fcis-31608	35	8	size	size	NOUN
fcis-31608	35	9	and	and	CCONJ
fcis-31608	35	10	weight	weight	NOUN
fcis-31608	35	11	estimation	estimation	NOUN
fcis-31608	35	12	of	of	ADP
fcis-31608	35	13	cattle	cattle	NOUN
fcis-31608	35	14	using	use	VERB
fcis-31608	35	15	machine	machine	NOUN
fcis-31608	35	16	vision	vision	NOUN
fcis-31608	35	17	.	.	PUNCT
fcis-31608	36	1	additionally	additionally	ADV
fcis-31608	36	2	,	,	PUNCT
fcis-31608	36	3	elkhrachy	elkhrachy	NOUN
fcis-31608	36	4	’s	’s	PART
fcis-31608	36	5	research	research	NOUN
fcis-31608	36	6	[	[	X
fcis-31608	36	7	14	14	NUM
fcis-31608	36	8	]	]	PUNCT
fcis-31608	36	9	provided	provide	VERB
fcis-31608	36	10	a	a	DET
fcis-31608	36	11	theoretical	theoretical	ADJ
fcis-31608	36	12	foundation	foundation	NOUN
fcis-31608	36	13	for	for	ADP
fcis-31608	36	14	constructing	construct	VERB
fcis-31608	36	15	threedimensional	threedimensional	ADJ
fcis-31608	36	16	structures	structure	NOUN
fcis-31608	36	17	from	from	ADP
fcis-31608	36	18	two	two	NUM
fcis-31608	36	19	-	-	PUNCT
fcis-31608	36	20	dimensional	dimensional	ADJ
fcis-31608	36	21	images	image	NOUN
fcis-31608	36	22	,	,	PUNCT
fcis-31608	36	23	which	which	PRON
fcis-31608	36	24	is	be	AUX
fcis-31608	36	25	crucial	crucial	ADJ
fcis-31608	36	26	for	for	ADP
fcis-31608	36	27	estimating	estimate	VERB
fcis-31608	36	28	weight	weight	NOUN
fcis-31608	36	29	from	from	ADP
fcis-31608	36	30	size	size	NOUN
fcis-31608	36	31	data	datum	NOUN
fcis-31608	36	32	.	.	PUNCT
fcis-31608	37	1	despite	despite	SCONJ
fcis-31608	37	2	existing	exist	VERB
fcis-31608	37	3	research	research	NOUN
fcis-31608	37	4	achieving	achieve	VERB
fcis-31608	37	5	some	some	DET
fcis-31608	37	6	progress	progress	NOUN
fcis-31608	37	7	,	,	PUNCT
fcis-31608	37	8	challenges	challenge	NOUN
fcis-31608	37	9	remain	remain	VERB
fcis-31608	37	10	in	in	ADP
fcis-31608	37	11	enhancing	enhance	VERB
fcis-31608	37	12	the	the	DET
fcis-31608	37	13	robustness	robustness	NOUN
fcis-31608	37	14	,	,	PUNCT
fcis-31608	37	15	accuracy	accuracy	NOUN
fcis-31608	37	16	,	,	PUNCT
fcis-31608	37	17	and	and	CCONJ
fcis-31608	37	18	real	real	ADJ
fcis-31608	37	19	-	-	PUNCT
fcis-31608	37	20	time	time	NOUN
fcis-31608	37	21	performance	performance	NOUN
fcis-31608	37	22	of	of	ADP
fcis-31608	37	23	non	non	ADJ
fcis-31608	37	24	-	-	ADJ
fcis-31608	37	25	contact	contact	ADJ
fcis-31608	37	26	measurement	measurement	NOUN
fcis-31608	37	27	systems	system	NOUN
fcis-31608	37	28	within	within	ADP
fcis-31608	37	29	complex	complex	ADJ
fcis-31608	37	30	breeding	breeding	NOUN
fcis-31608	37	31	environments	environment	NOUN
fcis-31608	37	32	.	.	PUNCT
fcis-31608	38	1	additionally	additionally	ADV
fcis-31608	38	2	,	,	PUNCT
fcis-31608	38	3	effectively	effectively	ADV
fcis-31608	38	4	integrating	integrate	VERB
fcis-31608	38	5	multimodal	multimodal	ADJ
fcis-31608	38	6	data	datum	NOUN
fcis-31608	38	7	to	to	PART
fcis-31608	38	8	improve	improve	VERB
fcis-31608	38	9	weight	weight	NOUN
fcis-31608	38	10	estimation	estimation	NOUN
fcis-31608	38	11	accuracy	accuracy	NOUN
fcis-31608	38	12	continues	continue	VERB
fcis-31608	38	13	to	to	PART
fcis-31608	38	14	be	be	AUX
fcis-31608	38	15	a	a	DET
fcis-31608	38	16	significant	significant	ADJ
fcis-31608	38	17	hurdle	hurdle	NOUN
fcis-31608	38	18	.	.	PUNCT
fcis-31608	39	1	this	this	DET
fcis-31608	39	2	study	study	NOUN
fcis-31608	39	3	aims	aim	VERB
fcis-31608	39	4	to	to	PART
fcis-31608	39	5	thoroughly	thoroughly	ADV
fcis-31608	39	6	investigate	investigate	VERB
fcis-31608	39	7	a	a	DET
fcis-31608	39	8	non	non	ADJ
fcis-31608	39	9	-	-	ADJ
fcis-31608	39	10	contact	contact	ADJ
fcis-31608	39	11	cattle	cattle	NOUN
fcis-31608	39	12	weight	weight	NOUN
fcis-31608	39	13	measurement	measurement	NOUN
fcis-31608	39	14	system	system	NOUN
fcis-31608	39	15	based	base	VERB
fcis-31608	39	16	on	on	ADP
fcis-31608	39	17	deep	deep	ADJ
fcis-31608	39	18	learning	learning	NOUN
fcis-31608	39	19	,	,	PUNCT
fcis-31608	39	20	to	to	PART
fcis-31608	39	21	develop	develop	VERB
fcis-31608	39	22	an	an	DET
fcis-31608	39	23	efficient	efficient	ADJ
fcis-31608	39	24	,	,	PUNCT
fcis-31608	39	25	accurate	accurate	ADJ
fcis-31608	39	26	,	,	PUNCT
fcis-31608	39	27	and	and	CCONJ
fcis-31608	39	28	non	non	ADJ
fcis-31608	39	29	-	-	ADJ
fcis-31608	39	30	intrusive	intrusive	ADJ
fcis-31608	39	31	solution	solution	NOUN
fcis-31608	39	32	that	that	PRON
fcis-31608	39	33	supports	support	VERB
fcis-31608	39	34	intelligent	intelligent	ADJ
fcis-31608	39	35	management	management	NOUN
fcis-31608	39	36	in	in	ADP
fcis-31608	39	37	the	the	DET
fcis-31608	39	38	livestock	livestock	NOUN
fcis-31608	39	39	industry	industry	NOUN
fcis-31608	39	40	.	.	PUNCT
fcis-31608	40	1	2	2	X
fcis-31608	40	2	.	.	X
fcis-31608	40	3	keypoint	keypoint	NOUN
fcis-31608	40	4	detection	detection	NOUN
fcis-31608	40	5	of	of	ADP
fcis-31608	40	6	cattle	cattle	NOUN
fcis-31608	40	7	body	body	NOUN
fcis-31608	40	8	2.1	2.1	NUM
fcis-31608	40	9	.	.	PUNCT
fcis-31608	41	1	cattle	cattle	NOUN
fcis-31608	41	2	body	body	NOUN
fcis-31608	41	3	image	image	NOUN
fcis-31608	41	4	dataset	dataset	VERB
fcis-31608	41	5	the	the	DET
fcis-31608	41	6	cattle	cattle	NOUN
fcis-31608	41	7	image	image	NOUN
fcis-31608	41	8	dataset	dataset	VERB
fcis-31608	41	9	used	use	VERB
fcis-31608	41	10	in	in	ADP
fcis-31608	41	11	this	this	DET
fcis-31608	41	12	study	study	NOUN
fcis-31608	41	13	is	be	AUX
fcis-31608	41	14	derived	derive	VERB
fcis-31608	41	15	from	from	ADP
fcis-31608	41	16	a	a	DET
fcis-31608	41	17	competition	competition	NOUN
fcis-31608	41	18	dataset	dataset	VERB
fcis-31608	41	19	titled	title	VERB
fcis-31608	41	20	weight	weight	NOUN
fcis-31608	41	21	detection	detection	NOUN
fcis-31608	41	22	model	model	NOUN
fcis-31608	41	23	+	+	CCONJ
fcis-31608	41	24	dataset	dataset	NOUN
fcis-31608	41	25	(	(	PUNCT
fcis-31608	41	26	12k~	12k~	NUM
fcis-31608	41	27	)	)	PUNCT
fcis-31608	41	28	.	.	PUNCT
fcis-31608	42	1	side	side	NOUN
fcis-31608	42	2	-	-	PUNCT
fcis-31608	42	3	view	view	NOUN
fcis-31608	42	4	images	image	NOUN
fcis-31608	42	5	of	of	ADP
fcis-31608	42	6	cattle	cattle	NOUN
fcis-31608	42	7	were	be	AUX
fcis-31608	42	8	selected	select	VERB
fcis-31608	42	9	from	from	ADP
fcis-31608	42	10	this	this	DET
fcis-31608	42	11	dataset	dataset	NOUN
fcis-31608	42	12	,	,	PUNCT
fcis-31608	42	13	comprising	comprise	VERB
fcis-31608	42	14	1,556	1,556	NUM
fcis-31608	42	15	training	training	NOUN
fcis-31608	42	16	images	image	NOUN
fcis-31608	42	17	and	and	CCONJ
fcis-31608	42	18	389	389	NUM
fcis-31608	42	19	testing	testing	NOUN
fcis-31608	42	20	images	image	NOUN
fcis-31608	42	21	,	,	PUNCT
fcis-31608	42	22	for	for	ADP
fcis-31608	42	23	a	a	DET
fcis-31608	42	24	total	total	NOUN
fcis-31608	42	25	of	of	ADP
fcis-31608	42	26	1,945	1,945	NUM
fcis-31608	42	27	images	image	NOUN
fcis-31608	42	28	.	.	PUNCT
fcis-31608	43	1	the	the	DET
fcis-31608	43	2	dataset	dataset	NOUN
fcis-31608	43	3	includes	include	VERB
fcis-31608	43	4	images	image	NOUN
fcis-31608	43	5	of	of	ADP
fcis-31608	43	6	cattle	cattle	NOUN
fcis-31608	43	7	from	from	ADP
fcis-31608	43	8	various	various	ADJ
fcis-31608	43	9	breeds	breed	NOUN
fcis-31608	43	10	,	,	PUNCT
fcis-31608	43	11	poses	pose	NOUN
fcis-31608	43	12	,	,	PUNCT
fcis-31608	43	13	and	and	CCONJ
fcis-31608	43	14	lighting	lighting	NOUN
fcis-31608	43	15	conditions	condition	NOUN
fcis-31608	43	16	to	to	PART
fcis-31608	43	17	enhance	enhance	VERB
fcis-31608	43	18	the	the	DET
fcis-31608	43	19	model	model	NOUN
fcis-31608	43	20	's	's	PART
fcis-31608	43	21	generalization	generalization	NOUN
fcis-31608	43	22	ability	ability	NOUN
fcis-31608	43	23	and	and	CCONJ
fcis-31608	43	24	robustness	robustness	NOUN
fcis-31608	43	25	across	across	ADP
fcis-31608	43	26	diverse	diverse	ADJ
fcis-31608	43	27	environments	environment	NOUN
fcis-31608	43	28	.	.	PUNCT
fcis-31608	44	1	each	each	DET
fcis-31608	44	2	cattle	cattle	NOUN
fcis-31608	44	3	image	image	NOUN
fcis-31608	44	4	is	be	AUX
fcis-31608	44	5	annotated	annotate	VERB
fcis-31608	44	6	with	with	ADP
fcis-31608	44	7	nine	nine	NUM
fcis-31608	44	8	keypoints	keypoint	NOUN
fcis-31608	44	9	corresponding	correspond	VERB
fcis-31608	44	10	to	to	ADP
fcis-31608	44	11	critical	critical	ADJ
fcis-31608	44	12	parts	part	NOUN
fcis-31608	44	13	of	of	ADP
fcis-31608	44	14	the	the	DET
fcis-31608	44	15	animal	animal	NOUN
fcis-31608	44	16	's	's	PART
fcis-31608	44	17	body	body	NOUN
fcis-31608	44	18	,	,	PUNCT
fcis-31608	44	19	such	such	ADJ
fcis-31608	44	20	as	as	ADP
fcis-31608	44	21	the	the	DET
fcis-31608	44	22	shoulder	shoulder	NOUN
fcis-31608	44	23	,	,	PUNCT
fcis-31608	44	24	back	back	ADV
fcis-31608	44	25	,	,	PUNCT
fcis-31608	44	26	and	and	CCONJ
fcis-31608	44	27	legs	leg	NOUN
fcis-31608	44	28	.	.	PUNCT
fcis-31608	45	1	the	the	DET
fcis-31608	45	2	filename	filename	NOUN
fcis-31608	45	3	of	of	ADP
fcis-31608	45	4	each	each	DET
fcis-31608	45	5	image	image	NOUN
fcis-31608	45	6	contains	contain	VERB
fcis-31608	45	7	the	the	DET
fcis-31608	45	8	42	42	NUM
fcis-31608	45	9	weight	weight	NOUN
fcis-31608	45	10	information	information	NOUN
fcis-31608	45	11	for	for	ADP
fcis-31608	45	12	the	the	DET
fcis-31608	45	13	specific	specific	ADJ
fcis-31608	45	14	animal	animal	NOUN
fcis-31608	45	15	,	,	PUNCT
fcis-31608	45	16	and	and	CCONJ
fcis-31608	45	17	this	this	DET
fcis-31608	45	18	weight	weight	NOUN
fcis-31608	45	19	data	datum	NOUN
fcis-31608	45	20	,	,	PUNCT
fcis-31608	45	21	extracted	extract	VERB
fcis-31608	45	22	from	from	ADP
fcis-31608	45	23	the	the	DET
fcis-31608	45	24	filename	filename	NOUN
fcis-31608	45	25	,	,	PUNCT
fcis-31608	45	26	is	be	AUX
fcis-31608	45	27	directly	directly	ADV
fcis-31608	45	28	used	use	VERB
fcis-31608	45	29	as	as	ADP
fcis-31608	45	30	the	the	DET
fcis-31608	45	31	target	target	NOUN
fcis-31608	45	32	value	value	NOUN
fcis-31608	45	33	for	for	ADP
fcis-31608	45	34	the	the	DET
fcis-31608	45	35	regression	regression	NOUN
fcis-31608	45	36	task	task	NOUN
fcis-31608	45	37	.	.	PUNCT
fcis-31608	46	1	these	these	DET
fcis-31608	46	2	images	image	NOUN
fcis-31608	46	3	and	and	CCONJ
fcis-31608	46	4	their	their	PRON
fcis-31608	46	5	corresponding	corresponding	ADJ
fcis-31608	46	6	weight	weight	NOUN
fcis-31608	46	7	values	value	NOUN
fcis-31608	46	8	are	be	AUX
fcis-31608	46	9	then	then	ADV
fcis-31608	46	10	input	input	ADJ
fcis-31608	46	11	into	into	ADP
fcis-31608	46	12	the	the	DET
fcis-31608	46	13	model	model	NOUN
fcis-31608	46	14	for	for	ADP
fcis-31608	46	15	training	training	NOUN
fcis-31608	46	16	,	,	PUNCT
fcis-31608	46	17	as	as	SCONJ
fcis-31608	46	18	illustrated	illustrate	VERB
fcis-31608	46	19	in	in	ADP
fcis-31608	46	20	figure	figure	NOUN
fcis-31608	46	21	1	1	NUM
fcis-31608	46	22	.	.	PUNCT
fcis-31608	46	23	fig	fig	NOUN
fcis-31608	47	1	1	1	NUM
fcis-31608	47	2	.	.	PUNCT
fcis-31608	48	1	cattle	cattle	NOUN
fcis-31608	48	2	keypoint	keypoint	VERB
fcis-31608	48	3	image	image	NOUN
fcis-31608	48	4	2.2	2.2	NUM
fcis-31608	48	5	.	.	PUNCT
fcis-31608	49	1	keypoint	keypoint	NOUN
fcis-31608	49	2	detection	detection	NOUN
fcis-31608	49	3	based	base	VERB
fcis-31608	49	4	on	on	ADP
fcis-31608	49	5	deep	deep	ADJ
fcis-31608	49	6	learning	learning	NOUN
fcis-31608	49	7	to	to	PART
fcis-31608	49	8	achieve	achieve	VERB
fcis-31608	49	9	efficient	efficient	ADJ
fcis-31608	49	10	and	and	CCONJ
fcis-31608	49	11	accurate	accurate	ADJ
fcis-31608	49	12	detection	detection	NOUN
fcis-31608	49	13	of	of	ADP
fcis-31608	49	14	cattle	cattle	NOUN
fcis-31608	49	15	keypoints	keypoint	NOUN
fcis-31608	49	16	,	,	PUNCT
fcis-31608	49	17	this	this	DET
fcis-31608	49	18	study	study	NOUN
fcis-31608	49	19	employs	employ	VERB
fcis-31608	49	20	two	two	NUM
fcis-31608	49	21	convolutional	convolutional	ADJ
fcis-31608	49	22	neural	neural	ADJ
fcis-31608	49	23	network	network	NOUN
fcis-31608	49	24	models	model	NOUN
fcis-31608	49	25	:	:	PUNCT
fcis-31608	49	26	mobilenetv3	mobilenetv3	PROPN
fcis-31608	49	27	and	and	CCONJ
fcis-31608	49	28	resnet50	resnet50	PROPN
fcis-31608	49	29	,	,	PUNCT
fcis-31608	49	30	conducting	conduct	VERB
fcis-31608	49	31	a	a	DET
fcis-31608	49	32	comparative	comparative	ADJ
fcis-31608	49	33	analysis	analysis	NOUN
fcis-31608	49	34	.	.	PUNCT
fcis-31608	50	1	each	each	DET
fcis-31608	50	2	model	model	NOUN
fcis-31608	50	3	has	have	VERB
fcis-31608	50	4	distinct	distinct	ADJ
fcis-31608	50	5	architectural	architectural	ADJ
fcis-31608	50	6	characteristics	characteristic	NOUN
fcis-31608	50	7	and	and	CCONJ
fcis-31608	50	8	advantages	advantage	NOUN
fcis-31608	50	9	:	:	PUNCT
fcis-31608	50	10	mobilenetv3	mobilenetv3	PROPN
fcis-31608	50	11	is	be	AUX
fcis-31608	50	12	a	a	DET
fcis-31608	50	13	lightweight	lightweight	ADJ
fcis-31608	50	14	model	model	NOUN
fcis-31608	50	15	suitable	suitable	ADJ
fcis-31608	50	16	for	for	ADP
fcis-31608	50	17	environments	environment	NOUN
fcis-31608	50	18	with	with	ADP
fcis-31608	50	19	limited	limited	ADJ
fcis-31608	50	20	computational	computational	ADJ
fcis-31608	50	21	resources	resource	NOUN
fcis-31608	50	22	,	,	PUNCT
fcis-31608	50	23	while	while	SCONJ
fcis-31608	50	24	resnet50	resnet50	NOUN
fcis-31608	50	25	is	be	AUX
fcis-31608	50	26	a	a	DET
fcis-31608	50	27	deep	deep	ADJ
fcis-31608	50	28	network	network	NOUN
fcis-31608	50	29	that	that	PRON
fcis-31608	50	30	typically	typically	ADV
fcis-31608	50	31	offers	offer	VERB
fcis-31608	50	32	higher	high	ADJ
fcis-31608	50	33	accuracy	accuracy	NOUN
fcis-31608	50	34	.	.	PUNCT
fcis-31608	51	1	by	by	ADP
fcis-31608	51	2	comparing	compare	VERB
fcis-31608	51	3	the	the	DET
fcis-31608	51	4	performance	performance	NOUN
fcis-31608	51	5	of	of	ADP
fcis-31608	51	6	both	both	DET
fcis-31608	51	7	models	model	NOUN
fcis-31608	51	8	on	on	ADP
fcis-31608	51	9	cattle	cattle	NOUN
fcis-31608	51	10	images	image	NOUN
fcis-31608	51	11	for	for	ADP
fcis-31608	51	12	the	the	DET
fcis-31608	51	13	keypoint	keypoint	NOUN
fcis-31608	51	14	detection	detection	NOUN
fcis-31608	51	15	task	task	NOUN
fcis-31608	51	16	,	,	PUNCT
fcis-31608	51	17	we	we	PRON
fcis-31608	51	18	can	can	AUX
fcis-31608	51	19	comprehensively	comprehensively	ADV
fcis-31608	51	20	evaluate	evaluate	VERB
fcis-31608	51	21	their	their	PRON
fcis-31608	51	22	effectiveness	effectiveness	NOUN
fcis-31608	51	23	and	and	CCONJ
fcis-31608	51	24	select	select	VERB
fcis-31608	51	25	the	the	DET
fcis-31608	51	26	most	most	ADV
fcis-31608	51	27	suitable	suitable	ADJ
fcis-31608	51	28	model	model	NOUN
fcis-31608	51	29	.	.	PUNCT
fcis-31608	52	1	(	(	PUNCT
fcis-31608	52	2	1	1	X
fcis-31608	52	3	)	)	PUNCT
fcis-31608	52	4	mobilenetv3	mobilenetv3	PROPN
fcis-31608	52	5	mobilenetv3	mobilenetv3	PROPN
fcis-31608	52	6	utilizes	utilize	VERB
fcis-31608	52	7	an	an	DET
fcis-31608	52	8	optimized	optimize	VERB
fcis-31608	52	9	architecture	architecture	NOUN
fcis-31608	52	10	that	that	PRON
fcis-31608	52	11	incorporates	incorporate	VERB
fcis-31608	52	12	se	se	ADJ
fcis-31608	52	13	modules	module	NOUN
fcis-31608	52	14	and	and	CCONJ
fcis-31608	52	15	the	the	DET
fcis-31608	52	16	h	h	NOUN
fcis-31608	52	17	-	-	PUNCT
fcis-31608	52	18	swish	swish	ADJ
fcis-31608	52	19	activation	activation	NOUN
fcis-31608	52	20	function	function	NOUN
fcis-31608	52	21	.	.	PUNCT
fcis-31608	53	1	this	this	DET
fcis-31608	53	2	design	design	NOUN
fcis-31608	53	3	enables	enable	VERB
fcis-31608	53	4	mobilenetv3	mobilenetv3	NOUN
fcis-31608	53	5	to	to	PART
fcis-31608	53	6	achieve	achieve	VERB
fcis-31608	53	7	high	high	ADJ
fcis-31608	53	8	detection	detection	NOUN
fcis-31608	53	9	accuracy	accuracy	NOUN
fcis-31608	53	10	while	while	SCONJ
fcis-31608	53	11	maintaining	maintain	VERB
fcis-31608	53	12	low	low	ADJ
fcis-31608	53	13	computational	computational	ADJ
fcis-31608	53	14	resource	resource	NOUN
fcis-31608	53	15	consumption	consumption	NOUN
fcis-31608	53	16	.	.	PUNCT
fcis-31608	54	1	the	the	DET
fcis-31608	54	2	model	model	NOUN
fcis-31608	54	3	is	be	AUX
fcis-31608	54	4	adapted	adapt	VERB
fcis-31608	54	5	for	for	ADP
fcis-31608	54	6	the	the	DET
fcis-31608	54	7	cattle	cattle	NOUN
fcis-31608	54	8	keypoint	keypoint	VERB
fcis-31608	54	9	detection	detection	NOUN
fcis-31608	54	10	task	task	NOUN
fcis-31608	54	11	by	by	ADP
fcis-31608	54	12	modifying	modify	VERB
fcis-31608	54	13	its	its	PRON
fcis-31608	54	14	output	output	NOUN
fcis-31608	54	15	layer	layer	NOUN
fcis-31608	54	16	:	:	PUNCT
fcis-31608	54	17	the	the	DET
fcis-31608	54	18	original	original	ADJ
fcis-31608	54	19	classification	classification	NOUN
fcis-31608	54	20	layer	layer	NOUN
fcis-31608	54	21	at	at	ADP
fcis-31608	54	22	the	the	DET
fcis-31608	54	23	end	end	NOUN
fcis-31608	54	24	of	of	ADP
fcis-31608	54	25	mobilenetv3	mobilenetv3	PROPN
fcis-31608	54	26	-	-	PUNCT
fcis-31608	54	27	small	small	ADJ
fcis-31608	54	28	is	be	AUX
fcis-31608	54	29	replaced	replace	VERB
fcis-31608	54	30	with	with	ADP
fcis-31608	54	31	a	a	DET
fcis-31608	54	32	multi	multi	ADJ
fcis-31608	54	33	-	-	ADJ
fcis-31608	54	34	task	task	ADJ
fcis-31608	54	35	regression	regression	NOUN
fcis-31608	54	36	head	head	NOUN
fcis-31608	54	37	that	that	PRON
fcis-31608	54	38	outputs	output	VERB
fcis-31608	54	39	the	the	DET
fcis-31608	54	40	normalized	normalize	VERB
fcis-31608	54	41	coordinates	coordinate	NOUN
fcis-31608	54	42	(	(	PUNCT
fcis-31608	54	43	x	x	X
fcis-31608	54	44	,	,	PUNCT
fcis-31608	54	45	y	y	NOUN
fcis-31608	54	46	)	)	PUNCT
fcis-31608	54	47	of	of	ADP
fcis-31608	54	48	nine	nine	NUM
fcis-31608	54	49	keypoints	keypoint	NOUN
fcis-31608	54	50	along	along	ADV
fcis-31608	54	51	with	with	ADP
fcis-31608	54	52	their	their	PRON
fcis-31608	54	53	visibility	visibility	NOUN
fcis-31608	54	54	probabilities	probability	NOUN
fcis-31608	54	55	(	(	PUNCT
fcis-31608	54	56	v	v	NOUN
fcis-31608	54	57	)	)	PUNCT
fcis-31608	54	58	.	.	PUNCT
fcis-31608	55	1	the	the	DET
fcis-31608	55	2	overall	overall	ADJ
fcis-31608	55	3	network	network	NOUN
fcis-31608	55	4	architecture	architecture	NOUN
fcis-31608	55	5	is	be	AUX
fcis-31608	55	6	illustrated	illustrate	VERB
fcis-31608	55	7	in	in	ADP
fcis-31608	55	8	figure	figure	NOUN
fcis-31608	55	9	2	2	NUM
fcis-31608	55	10	.	.	PUNCT
fcis-31608	55	11	fig	fig	NOUN
fcis-31608	55	12	2	2	NUM
fcis-31608	55	13	.	.	PUNCT
fcis-31608	55	14	modified	modify	VERB
fcis-31608	55	15	mobilenetv3	mobilenetv3	PROPN
fcis-31608	55	16	structure	structure	NOUN
fcis-31608	55	17	(	(	PUNCT
fcis-31608	55	18	2)resnet50	2)resnet50	NUM
fcis-31608	55	19	the	the	DET
fcis-31608	55	20	deep	deep	ADJ
fcis-31608	55	21	architecture	architecture	NOUN
fcis-31608	55	22	of	of	ADP
fcis-31608	55	23	resnet50	resnet50	NOUN
fcis-31608	55	24	enables	enable	VERB
fcis-31608	55	25	it	it	PRON
fcis-31608	55	26	to	to	PART
fcis-31608	55	27	achieve	achieve	VERB
fcis-31608	55	28	notable	notable	ADJ
fcis-31608	55	29	accuracy	accuracy	NOUN
fcis-31608	55	30	in	in	ADP
fcis-31608	55	31	detection	detection	NOUN
fcis-31608	55	32	tasks	task	NOUN
fcis-31608	55	33	;	;	PUNCT
fcis-31608	55	34	however	however	ADV
fcis-31608	55	35	,	,	PUNCT
fcis-31608	55	36	its	its	PRON
fcis-31608	55	37	depth	depth	NOUN
fcis-31608	55	38	also	also	ADV
fcis-31608	55	39	results	result	VERB
fcis-31608	55	40	in	in	ADP
fcis-31608	55	41	increased	increase	VERB
fcis-31608	55	42	computational	computational	ADJ
fcis-31608	55	43	complexity	complexity	NOUN
fcis-31608	55	44	.	.	PUNCT
fcis-31608	56	1	to	to	PART
fcis-31608	56	2	adapt	adapt	VERB
fcis-31608	56	3	resnet50	resnet50	NOUN
fcis-31608	56	4	for	for	ADP
fcis-31608	56	5	keypoint	keypoint	NOUN
fcis-31608	56	6	detection	detection	NOUN
fcis-31608	56	7	,	,	PUNCT
fcis-31608	56	8	the	the	DET
fcis-31608	56	9	final	final	ADJ
fcis-31608	56	10	fully	fully	ADV
fcis-31608	56	11	connected	connect	VERB
fcis-31608	56	12	layer	layer	NOUN
fcis-31608	56	13	has	have	AUX
fcis-31608	56	14	been	be	AUX
fcis-31608	56	15	modified	modify	VERB
fcis-31608	56	16	to	to	PART
fcis-31608	56	17	output	output	VERB
fcis-31608	56	18	27	27	NUM
fcis-31608	56	19	dimensions	dimension	NOUN
fcis-31608	56	20	.	.	PUNCT
fcis-31608	57	1	the	the	DET
fcis-31608	57	2	overall	overall	ADJ
fcis-31608	57	3	network	network	NOUN
fcis-31608	57	4	architecture	architecture	NOUN
fcis-31608	57	5	is	be	AUX
fcis-31608	57	6	illustrated	illustrate	VERB
fcis-31608	57	7	in	in	ADP
fcis-31608	57	8	figure	figure	NOUN
fcis-31608	57	9	3	3	NUM
fcis-31608	57	10	.	.	PROPN
fcis-31608	57	11	2.3	2.3	NUM
fcis-31608	57	12	.	.	PUNCT
fcis-31608	58	1	model	model	NOUN
fcis-31608	58	2	training	training	NOUN
fcis-31608	58	3	during	during	ADP
fcis-31608	58	4	training	training	NOUN
fcis-31608	58	5	,	,	PUNCT
fcis-31608	58	6	the	the	DET
fcis-31608	58	7	adam	adam	PROPN
fcis-31608	58	8	optimizer	optimizer	NOUN
fcis-31608	58	9	was	be	AUX
fcis-31608	58	10	selected	select	VERB
fcis-31608	58	11	due	due	ADP
fcis-31608	58	12	to	to	ADP
fcis-31608	58	13	its	its	PRON
fcis-31608	58	14	effectiveness	effectiveness	NOUN
fcis-31608	58	15	in	in	ADP
fcis-31608	58	16	handling	handle	VERB
fcis-31608	58	17	large	large	ADJ
fcis-31608	58	18	-	-	PUNCT
fcis-31608	58	19	scale	scale	NOUN
fcis-31608	58	20	data	datum	NOUN
fcis-31608	58	21	and	and	CCONJ
fcis-31608	58	22	complex	complex	ADJ
fcis-31608	58	23	models	model	NOUN
fcis-31608	58	24	,	,	PUNCT
fcis-31608	58	25	making	make	VERB
fcis-31608	58	26	it	it	PRON
fcis-31608	58	27	a	a	DET
fcis-31608	58	28	popular	popular	ADJ
fcis-31608	58	29	choice	choice	NOUN
fcis-31608	58	30	in	in	ADP
fcis-31608	58	31	deep	deep	ADJ
fcis-31608	58	32	learning	learning	NOUN
fcis-31608	58	33	.	.	PUNCT
fcis-31608	59	1	the	the	DET
fcis-31608	59	2	batch	batch	NOUN
fcis-31608	59	3	size	size	NOUN
fcis-31608	59	4	was	be	AUX
fcis-31608	59	5	set	set	VERB
fcis-31608	59	6	to	to	ADP
fcis-31608	59	7	16	16	NUM
fcis-31608	59	8	;	;	PUNCT
fcis-31608	59	9	a	a	DET
fcis-31608	59	10	larger	large	ADJ
fcis-31608	59	11	batch	batch	NOUN
fcis-31608	59	12	size	size	NOUN
fcis-31608	59	13	improves	improve	VERB
fcis-31608	59	14	computational	computational	ADJ
fcis-31608	59	15	efficiency	efficiency	NOUN
fcis-31608	59	16	,	,	PUNCT
fcis-31608	59	17	reduces	reduce	VERB
fcis-31608	59	18	training	training	NOUN
fcis-31608	59	19	time	time	NOUN
fcis-31608	59	20	,	,	PUNCT
fcis-31608	59	21	and	and	CCONJ
fcis-31608	59	22	provides	provide	VERB
fcis-31608	59	23	the	the	DET
fcis-31608	59	24	model	model	NOUN
fcis-31608	59	25	with	with	ADP
fcis-31608	59	26	sufficient	sufficient	ADJ
fcis-31608	59	27	sample	sample	NOUN
fcis-31608	59	28	information	information	NOUN
fcis-31608	59	29	for	for	ADP
fcis-31608	59	30	effective	effective	ADJ
fcis-31608	59	31	learning	learning	NOUN
fcis-31608	59	32	.	.	PUNCT
fcis-31608	60	1	the	the	DET
fcis-31608	60	2	number	number	NOUN
fcis-31608	60	3	of	of	ADP
fcis-31608	60	4	epochs	epoch	NOUN
fcis-31608	60	5	was	be	AUX
fcis-31608	60	6	set	set	VERB
fcis-31608	60	7	to	to	ADP
fcis-31608	60	8	100	100	NUM
fcis-31608	60	9	,	,	PUNCT
fcis-31608	60	10	with	with	ADP
fcis-31608	60	11	early	early	ADJ
fcis-31608	60	12	stopping	stopping	NOUN
fcis-31608	60	13	implemented	implement	VERB
fcis-31608	60	14	to	to	PART
fcis-31608	60	15	prevent	prevent	VERB
fcis-31608	60	16	overfitting	overfitting	NOUN
fcis-31608	60	17	.	.	PUNCT
fcis-31608	61	1	this	this	PRON
fcis-31608	61	2	means	mean	VERB
fcis-31608	61	3	training	training	NOUN
fcis-31608	61	4	would	would	AUX
fcis-31608	61	5	halt	halt	VERB
fcis-31608	61	6	if	if	SCONJ
fcis-31608	61	7	there	there	PRON
fcis-31608	61	8	were	be	VERB
fcis-31608	61	9	no	no	DET
fcis-31608	61	10	significant	significant	ADJ
fcis-31608	61	11	improvements	improvement	NOUN
fcis-31608	61	12	in	in	ADP
fcis-31608	61	13	loss	loss	NOUN
fcis-31608	61	14	values	value	NOUN
fcis-31608	61	15	over	over	ADP
fcis-31608	61	16	several	several	ADJ
fcis-31608	61	17	consecutive	consecutive	ADJ
fcis-31608	61	18	epochs	epoch	NOUN
fcis-31608	61	19	.	.	PUNCT
fcis-31608	62	1	throughout	throughout	ADP
fcis-31608	62	2	the	the	DET
fcis-31608	62	3	training	training	NOUN
fcis-31608	62	4	process	process	NOUN
fcis-31608	62	5	,	,	PUNCT
fcis-31608	62	6	the	the	DET
fcis-31608	62	7	loss	loss	NOUN
fcis-31608	62	8	function	function	NOUN
fcis-31608	62	9	value	value	NOUN
fcis-31608	62	10	gradually	gradually	ADV
fcis-31608	62	11	decreases	decrease	VERB
fcis-31608	62	12	,	,	PUNCT
fcis-31608	62	13	indicating	indicate	VERB
fcis-31608	62	14	that	that	SCONJ
fcis-31608	62	15	the	the	DET
fcis-31608	62	16	model	model	NOUN
fcis-31608	62	17	is	be	AUX
fcis-31608	62	18	progressively	progressively	ADV
fcis-31608	62	19	improving	improve	VERB
fcis-31608	62	20	its	its	PRON
fcis-31608	62	21	ability	ability	NOUN
fcis-31608	62	22	to	to	PART
fcis-31608	62	23	predict	predict	VERB
fcis-31608	62	24	the	the	DET
fcis-31608	62	25	coordinates	coordinate	NOUN
fcis-31608	62	26	of	of	ADP
fcis-31608	62	27	the	the	DET
fcis-31608	62	28	keypoints	keypoint	NOUN
fcis-31608	62	29	.	.	PUNCT
fcis-31608	63	1	by	by	ADP
fcis-31608	63	2	tracking	track	VERB
fcis-31608	63	3	the	the	DET
fcis-31608	63	4	loss	loss	NOUN
fcis-31608	63	5	on	on	ADP
fcis-31608	63	6	both	both	CCONJ
fcis-31608	63	7	the	the	DET
fcis-31608	63	8	training	training	NOUN
fcis-31608	63	9	and	and	CCONJ
fcis-31608	63	10	validation	validation	NOUN
fcis-31608	63	11	sets	set	NOUN
fcis-31608	63	12	,	,	PUNCT
fcis-31608	63	13	we	we	PRON
fcis-31608	63	14	observe	observe	VERB
fcis-31608	63	15	that	that	SCONJ
fcis-31608	63	16	the	the	DET
fcis-31608	63	17	loss	loss	NOUN
fcis-31608	63	18	on	on	ADP
fcis-31608	63	19	the	the	DET
fcis-31608	63	20	validation	validation	NOUN
fcis-31608	63	21	set	set	NOUN
fcis-31608	63	22	eventually	eventually	ADV
fcis-31608	63	23	stabilizes	stabilize	VERB
fcis-31608	63	24	.	.	PUNCT
fcis-31608	64	1	figure	figure	NOUN
fcis-31608	64	2	4	4	NUM
fcis-31608	64	3	illustrates	illustrate	VERB
fcis-31608	64	4	the	the	DET
fcis-31608	64	5	changes	change	NOUN
fcis-31608	64	6	in	in	ADP
fcis-31608	64	7	the	the	DET
fcis-31608	64	8	loss	loss	NOUN
fcis-31608	64	9	functions	function	NOUN
fcis-31608	64	10	of	of	ADP
fcis-31608	64	11	both	both	DET
fcis-31608	64	12	models	model	NOUN
fcis-31608	64	13	over	over	ADP
fcis-31608	64	14	the	the	DET
fcis-31608	64	15	epochs	epoch	NOUN
fcis-31608	64	16	.	.	PUNCT
fcis-31608	65	1	43	43	NUM
fcis-31608	65	2	fig	fig	NOUN
fcis-31608	65	3	3	3	NUM
fcis-31608	65	4	.	.	PUNCT
fcis-31608	65	5	modified	modify	VERB
fcis-31608	65	6	resnet50	resnet50	NOUN
fcis-31608	65	7	structure	structure	NOUN
fcis-31608	65	8	fig	fig	NOUN
fcis-31608	65	9	4	4	NUM
fcis-31608	65	10	.	.	PUNCT
fcis-31608	65	11	loss	loss	NOUN
fcis-31608	65	12	variation	variation	NOUN
fcis-31608	65	13	graph	graph	NOUN
fcis-31608	65	14	3	3	NUM
fcis-31608	65	15	.	.	PUNCT
fcis-31608	65	16	body	body	NOUN
fcis-31608	65	17	measurement	measurement	NOUN
fcis-31608	65	18	-	-	PUNCT
fcis-31608	65	19	based	base	VERB
fcis-31608	65	20	weight	weight	NOUN
fcis-31608	65	21	prediction	prediction	NOUN
fcis-31608	65	22	system	system	NOUN
fcis-31608	65	23	3.1	3.1	NUM
fcis-31608	65	24	.	.	PUNCT
fcis-31608	65	25	extraction	extraction	NOUN
fcis-31608	65	26	of	of	ADP
fcis-31608	65	27	body	body	NOUN
fcis-31608	65	28	measurement	measurement	NOUN
fcis-31608	65	29	parameters	parameter	NOUN
fcis-31608	65	30	in	in	ADP
fcis-31608	65	31	the	the	DET
fcis-31608	65	32	task	task	NOUN
fcis-31608	65	33	of	of	ADP
fcis-31608	65	34	cattle	cattle	NOUN
fcis-31608	65	35	weight	weight	NOUN
fcis-31608	65	36	prediction	prediction	NOUN
fcis-31608	65	37	,	,	PUNCT
fcis-31608	65	38	body	body	NOUN
fcis-31608	65	39	measurement	measurement	NOUN
fcis-31608	65	40	parameters	parameter	NOUN
fcis-31608	65	41	serve	serve	VERB
fcis-31608	65	42	as	as	ADP
fcis-31608	65	43	crucial	crucial	ADJ
fcis-31608	65	44	spatial	spatial	ADJ
fcis-31608	65	45	features	feature	NOUN
fcis-31608	65	46	.	.	PUNCT
fcis-31608	66	1	they	they	PRON
fcis-31608	66	2	reflect	reflect	VERB
fcis-31608	66	3	the	the	DET
fcis-31608	66	4	geometric	geometric	ADJ
fcis-31608	66	5	shape	shape	NOUN
fcis-31608	66	6	and	and	CCONJ
fcis-31608	66	7	size	size	NOUN
fcis-31608	66	8	of	of	ADP
fcis-31608	66	9	the	the	DET
fcis-31608	66	10	cattle	cattle	NOUN
fcis-31608	66	11	’s	’s	PART
fcis-31608	66	12	body	body	NOUN
fcis-31608	66	13	,	,	PUNCT
fcis-31608	66	14	which	which	PRON
fcis-31608	66	15	are	be	AUX
fcis-31608	66	16	essential	essential	ADJ
fcis-31608	66	17	for	for	ADP
fcis-31608	66	18	accurate	accurate	ADJ
fcis-31608	66	19	weight	weight	NOUN
fcis-31608	66	20	estimation	estimation	NOUN
fcis-31608	66	21	..	..	PUNCT
fcis-31608	66	22	nine	nine	NUM
fcis-31608	66	23	key	key	ADJ
fcis-31608	66	24	points	point	NOUN
fcis-31608	66	25	on	on	ADP
fcis-31608	66	26	the	the	DET
fcis-31608	66	27	cattle	cattle	NOUN
fcis-31608	66	28	’s	’s	PART
fcis-31608	66	29	body	body	NOUN
fcis-31608	66	30	are	be	AUX
fcis-31608	66	31	identified	identify	VERB
fcis-31608	66	32	from	from	ADP
fcis-31608	66	33	the	the	DET
fcis-31608	66	34	images	image	NOUN
fcis-31608	66	35	,	,	PUNCT
fcis-31608	66	36	and	and	CCONJ
fcis-31608	66	37	body	body	NOUN
fcis-31608	66	38	measurement	measurement	NOUN
fcis-31608	66	39	parameters	parameter	NOUN
fcis-31608	66	40	are	be	AUX
fcis-31608	66	41	calculated	calculate	VERB
fcis-31608	66	42	based	base	VERB
fcis-31608	66	43	on	on	ADP
fcis-31608	66	44	these	these	DET
fcis-31608	66	45	points	point	NOUN
fcis-31608	66	46	.	.	PUNCT
fcis-31608	67	1	the	the	DET
fcis-31608	67	2	locations	location	NOUN
fcis-31608	67	3	of	of	ADP
fcis-31608	67	4	these	these	DET
fcis-31608	67	5	measurement	measurement	NOUN
fcis-31608	67	6	points	point	NOUN
fcis-31608	67	7	are	be	AUX
fcis-31608	67	8	shown	show	VERB
fcis-31608	67	9	in	in	ADP
fcis-31608	67	10	figure	figure	NOUN
fcis-31608	67	11	5	5	NUM
fcis-31608	67	12	.	.	PUNCT
fcis-31608	67	13	to	to	PART
fcis-31608	67	14	derive	derive	VERB
fcis-31608	67	15	the	the	DET
fcis-31608	67	16	body	body	NOUN
fcis-31608	67	17	measurement	measurement	NOUN
fcis-31608	67	18	parameters	parameter	NOUN
fcis-31608	67	19	,	,	PUNCT
fcis-31608	67	20	five	five	NUM
fcis-31608	67	21	pairs	pair	NOUN
fcis-31608	67	22	of	of	ADP
fcis-31608	67	23	key	key	ADJ
fcis-31608	67	24	points	point	NOUN
fcis-31608	67	25	are	be	AUX
fcis-31608	67	26	selected	select	VERB
fcis-31608	67	27	from	from	ADP
fcis-31608	67	28	the	the	DET
fcis-31608	67	29	cattle	cattle	NOUN
fcis-31608	67	30	images	image	NOUN
fcis-31608	67	31	,	,	PUNCT
fcis-31608	67	32	and	and	CCONJ
fcis-31608	67	33	the	the	DET
fcis-31608	67	34	euclidean	euclidean	ADJ
fcis-31608	67	35	distances	distance	NOUN
fcis-31608	67	36	between	between	ADP
fcis-31608	67	37	each	each	DET
fcis-31608	67	38	pair	pair	NOUN
fcis-31608	67	39	are	be	AUX
fcis-31608	67	40	calculated	calculate	VERB
fcis-31608	67	41	.	.	PUNCT
fcis-31608	68	1	these	these	DET
fcis-31608	68	2	distances	distance	NOUN
fcis-31608	68	3	represent	represent	VERB
fcis-31608	68	4	the	the	DET
fcis-31608	68	5	proportional	proportional	ADJ
fcis-31608	68	6	relationships	relationship	NOUN
fcis-31608	68	7	of	of	ADP
fcis-31608	68	8	different	different	ADJ
fcis-31608	68	9	parts	part	NOUN
fcis-31608	68	10	of	of	ADP
fcis-31608	68	11	the	the	DET
fcis-31608	68	12	cattle	cattle	NOUN
fcis-31608	68	13	’s	’s	PART
fcis-31608	68	14	body	body	NOUN
fcis-31608	68	15	,	,	PUNCT
fcis-31608	68	16	thereby	thereby	ADV
fcis-31608	68	17	enhancing	enhance	VERB
fcis-31608	68	18	the	the	DET
fcis-31608	68	19	accuracy	accuracy	NOUN
fcis-31608	68	20	of	of	ADP
fcis-31608	68	21	weight	weight	NOUN
fcis-31608	68	22	prediction	prediction	NOUN
fcis-31608	68	23	.	.	PUNCT
fcis-31608	69	1	the	the	DET
fcis-31608	69	2	specific	specific	ADJ
fcis-31608	69	3	body	body	NOUN
fcis-31608	69	4	measurement	measurement	NOUN
fcis-31608	69	5	parameters	parameter	NOUN
fcis-31608	69	6	are	be	AUX
fcis-31608	69	7	listed	list	VERB
fcis-31608	69	8	in	in	ADP
fcis-31608	69	9	table	table	NOUN
fcis-31608	69	10	1	1	NUM
fcis-31608	69	11	.	.	PUNCT
fcis-31608	69	12	fig	fig	NOUN
fcis-31608	69	13	5	5	NUM
fcis-31608	69	14	.	.	PUNCT
fcis-31608	69	15	body	body	NOUN
fcis-31608	69	16	measurement	measurement	NOUN
fcis-31608	69	17	information	information	NOUN
fcis-31608	69	18	for	for	ADP
fcis-31608	69	19	each	each	DET
fcis-31608	69	20	pair	pair	NOUN
fcis-31608	69	21	of	of	ADP
fcis-31608	69	22	key	key	ADJ
fcis-31608	69	23	points	point	NOUN
fcis-31608	69	24	,	,	PUNCT
fcis-31608	69	25	first	first	ADV
fcis-31608	69	26	obtain	obtain	VERB
fcis-31608	69	27	their	their	PRON
fcis-31608	69	28	pixel	pixel	NOUN
fcis-31608	69	29	coordinates	coordinate	NOUN
fcis-31608	69	30	in	in	ADP
fcis-31608	69	31	the	the	DET
fcis-31608	69	32	image	image	NOUN
fcis-31608	69	33	.	.	PUNCT
fcis-31608	70	1	then	then	ADV
fcis-31608	70	2	use	use	VERB
fcis-31608	70	3	the	the	DET
fcis-31608	70	4	euclidean	euclidean	ADJ
fcis-31608	70	5	distance	distance	NOUN
fcis-31608	70	6	formula	formula	NOUN
fcis-31608	70	7	to	to	PART
fcis-31608	70	8	calculate	calculate	VERB
fcis-31608	70	9	the	the	DET
fcis-31608	70	10	distance	distance	NOUN
fcis-31608	70	11	between	between	ADP
fcis-31608	70	12	the	the	DET
fcis-31608	70	13	two	two	NUM
fcis-31608	70	14	points	point	NOUN
fcis-31608	70	15	.	.	PUNCT
fcis-31608	71	1	the	the	DET
fcis-31608	71	2	formula	formula	NOUN
fcis-31608	71	3	for	for	ADP
fcis-31608	71	4	calculating	calculate	VERB
fcis-31608	71	5	the	the	DET
fcis-31608	71	6	euclidean	euclidean	ADJ
fcis-31608	71	7	distance	distance	NOUN
fcis-31608	71	8	is	be	AUX
fcis-31608	71	9	shown	show	VERB
fcis-31608	71	10	in	in	ADP
fcis-31608	71	11	equation	equation	NOUN
fcis-31608	71	12	(	(	PUNCT
fcis-31608	71	13	1	1	NUM
fcis-31608	71	14	):	):	PUNCT
fcis-31608	71	15	44	44	NUM
fcis-31608	71	16	d	d	NOUN
fcis-31608	71	17	x	x	SYM
fcis-31608	71	18	x	x	X
fcis-31608	71	19	y	y	PROPN
fcis-31608	71	20	y	y	PROPN
fcis-31608	71	21	(	(	PUNCT
fcis-31608	71	22	1	1	NUM
fcis-31608	71	23	)	)	PUNCT
fcis-31608	71	24	table	table	NOUN
fcis-31608	71	25	1	1	NUM
fcis-31608	71	26	.	.	PUNCT
fcis-31608	71	27	body	body	NOUN
fcis-31608	71	28	measurements	measurement	NOUN
fcis-31608	71	29	parameters	parameter	NOUN
fcis-31608	71	30	body	body	NOUN
fcis-31608	71	31	measurement	measurement	NOUN
fcis-31608	71	32	description	description	NOUN
fcis-31608	71	33	image	image	NOUN
fcis-31608	71	34	location	location	NOUN
fcis-31608	71	35	oblique	oblique	ADJ
fcis-31608	71	36	length	length	NOUN
fcis-31608	71	37	1	1	NUM
fcis-31608	71	38	distance	distance	NOUN
fcis-31608	71	39	from	from	ADP
fcis-31608	71	40	the	the	DET
fcis-31608	71	41	scapula	scapula	NOUN
fcis-31608	71	42	to	to	ADP
fcis-31608	71	43	the	the	DET
fcis-31608	71	44	tailbone	tailbone	NOUN
fcis-31608	71	45	1	1	NUM
fcis-31608	71	46	-	-	SYM
fcis-31608	71	47	2	2	NUM
fcis-31608	71	48	oblique	oblique	ADJ
fcis-31608	71	49	length	length	NOUN
fcis-31608	71	50	2	2	NUM
fcis-31608	71	51	distance	distance	NOUN
fcis-31608	71	52	from	from	ADP
fcis-31608	71	53	the	the	DET
fcis-31608	71	54	shoulder	shoulder	NOUN
fcis-31608	71	55	to	to	ADP
fcis-31608	71	56	the	the	DET
fcis-31608	71	57	tailbone	tailbone	NOUN
fcis-31608	71	58	2	2	NUM
fcis-31608	71	59	-	-	SYM
fcis-31608	71	60	3	3	NUM
fcis-31608	71	61	bust	bust	NOUN
fcis-31608	71	62	measurement	measurement	NOUN
fcis-31608	71	63	distance	distance	NOUN
fcis-31608	71	64	from	from	ADP
fcis-31608	71	65	the	the	DET
fcis-31608	71	66	posterior	posterior	ADJ
fcis-31608	71	67	edge	edge	NOUN
fcis-31608	71	68	of	of	ADP
fcis-31608	71	69	the	the	DET
fcis-31608	71	70	scapula	scapula	NOUN
fcis-31608	71	71	to	to	ADP
fcis-31608	71	72	the	the	DET
fcis-31608	71	73	abdomen	abdomen	NOUN
fcis-31608	71	74	4	4	NUM
fcis-31608	71	75	-	-	SYM
fcis-31608	71	76	5	5	NUM
fcis-31608	71	77	waist	waist	NOUN
fcis-31608	71	78	measurement	measurement	NOUN
fcis-31608	71	79	distance	distance	NOUN
fcis-31608	71	80	from	from	ADP
fcis-31608	71	81	the	the	DET
fcis-31608	71	82	posterior	posterior	ADJ
fcis-31608	71	83	aspect	aspect	NOUN
fcis-31608	71	84	of	of	ADP
fcis-31608	71	85	the	the	DET
fcis-31608	71	86	lumbar	lumbar	NOUN
fcis-31608	71	87	vertebrae	vertebrae	NOUN
fcis-31608	71	88	to	to	ADP
fcis-31608	71	89	the	the	DET
fcis-31608	71	90	abdomen	abdomen	NOUN
fcis-31608	71	91	6	6	NUM
fcis-31608	71	92	-	-	SYM
fcis-31608	71	93	7	7	NUM
fcis-31608	71	94	height	height	NOUN
fcis-31608	71	95	distance	distance	NOUN
fcis-31608	71	96	from	from	ADP
fcis-31608	71	97	the	the	DET
fcis-31608	71	98	sacrum	sacrum	NOUN
fcis-31608	71	99	to	to	ADP
fcis-31608	71	100	the	the	DET
fcis-31608	71	101	ground	ground	NOUN
fcis-31608	71	102	8	8	NUM
fcis-31608	71	103	-	-	SYM
fcis-31608	71	104	9	9	NUM
fcis-31608	71	105	in	in	ADP
fcis-31608	71	106	the	the	DET
fcis-31608	71	107	formula	formula	NOUN
fcis-31608	71	108	,	,	PUNCT
fcis-31608	71	109	(	(	PUNCT
fcis-31608	71	110	x1	x1	PROPN
fcis-31608	71	111	,	,	PUNCT
fcis-31608	71	112	y1	y1	PROPN
fcis-31608	71	113	)	)	PUNCT
fcis-31608	71	114	and	and	CCONJ
fcis-31608	71	115	(	(	PUNCT
fcis-31608	71	116	x2	x2	PROPN
fcis-31608	71	117	,	,	PUNCT
fcis-31608	71	118	y2	y2	PROPN
fcis-31608	71	119	)	)	PUNCT
fcis-31608	71	120	represent	represent	VERB
fcis-31608	71	121	the	the	DET
fcis-31608	71	122	pixel	pixel	PROPN
fcis-31608	71	123	coordinates	coordinate	NOUN
fcis-31608	71	124	of	of	ADP
fcis-31608	71	125	two	two	NUM
fcis-31608	71	126	key	key	ADJ
fcis-31608	71	127	points	point	NOUN
fcis-31608	71	128	in	in	ADP
fcis-31608	71	129	the	the	DET
fcis-31608	71	130	image	image	NOUN
fcis-31608	71	131	,	,	PUNCT
fcis-31608	71	132	and	and	CCONJ
fcis-31608	71	133	d	d	NOUN
fcis-31608	71	134	is	be	AUX
fcis-31608	71	135	the	the	DET
fcis-31608	71	136	euclidean	euclidean	ADJ
fcis-31608	71	137	distance	distance	NOUN
fcis-31608	71	138	between	between	ADP
fcis-31608	71	139	them	they	PRON
fcis-31608	71	140	.	.	PUNCT
fcis-31608	72	1	using	use	VERB
fcis-31608	72	2	this	this	DET
fcis-31608	72	3	method	method	NOUN
fcis-31608	72	4	,	,	PUNCT
fcis-31608	72	5	the	the	DET
fcis-31608	72	6	body	body	NOUN
fcis-31608	72	7	measurement	measurement	NOUN
fcis-31608	72	8	parameters	parameter	NOUN
fcis-31608	72	9	derived	derive	VERB
fcis-31608	72	10	from	from	ADP
fcis-31608	72	11	the	the	DET
fcis-31608	72	12	key	key	ADJ
fcis-31608	72	13	points	point	NOUN
fcis-31608	72	14	accurately	accurately	ADV
fcis-31608	72	15	reflect	reflect	VERB
fcis-31608	72	16	the	the	DET
fcis-31608	72	17	size	size	NOUN
fcis-31608	72	18	and	and	CCONJ
fcis-31608	72	19	proportions	proportion	NOUN
fcis-31608	72	20	of	of	ADP
fcis-31608	72	21	the	the	DET
fcis-31608	72	22	cow	cow	NOUN
fcis-31608	72	23	's	's	PART
fcis-31608	72	24	body	body	NOUN
fcis-31608	72	25	.	.	PUNCT
fcis-31608	73	1	these	these	DET
fcis-31608	73	2	parameters	parameter	NOUN
fcis-31608	73	3	,	,	PUNCT
fcis-31608	73	4	combined	combine	VERB
fcis-31608	73	5	with	with	ADP
fcis-31608	73	6	other	other	ADJ
fcis-31608	73	7	image	image	NOUN
fcis-31608	73	8	features	feature	NOUN
fcis-31608	73	9	,	,	PUNCT
fcis-31608	73	10	are	be	AUX
fcis-31608	73	11	then	then	ADV
fcis-31608	73	12	input	input	ADJ
fcis-31608	73	13	into	into	ADP
fcis-31608	73	14	the	the	DET
fcis-31608	73	15	weight	weight	NOUN
fcis-31608	73	16	prediction	prediction	NOUN
fcis-31608	73	17	model	model	NOUN
fcis-31608	73	18	.	.	PUNCT
fcis-31608	74	1	3.2	3.2	NUM
fcis-31608	74	2	.	.	PUNCT
fcis-31608	74	3	depth	depth	NOUN
fcis-31608	74	4	of	of	ADP
fcis-31608	74	5	field	field	NOUN
fcis-31608	74	6	feature	feature	NOUN
fcis-31608	74	7	extraction	extraction	NOUN
fcis-31608	74	8	and	and	CCONJ
fcis-31608	74	9	integration	integration	NOUN
fcis-31608	74	10	depth	depth	NOUN
fcis-31608	74	11	of	of	ADP
fcis-31608	74	12	field	field	NOUN
fcis-31608	74	13	correction	correction	NOUN
fcis-31608	74	14	is	be	AUX
fcis-31608	74	15	essential	essential	ADJ
fcis-31608	74	16	for	for	ADP
fcis-31608	74	17	mitigating	mitigate	VERB
fcis-31608	74	18	the	the	DET
fcis-31608	74	19	effects	effect	NOUN
fcis-31608	74	20	of	of	ADP
fcis-31608	74	21	variations	variation	NOUN
fcis-31608	74	22	in	in	ADP
fcis-31608	74	23	shooting	shoot	VERB
fcis-31608	74	24	angle	angle	NOUN
fcis-31608	74	25	and	and	CCONJ
fcis-31608	74	26	distance	distance	NOUN
fcis-31608	74	27	on	on	ADP
fcis-31608	74	28	the	the	DET
fcis-31608	74	29	cattle	cattle	NOUN
fcis-31608	74	30	weight	weight	NOUN
fcis-31608	74	31	prediction	prediction	NOUN
fcis-31608	74	32	model	model	NOUN
fcis-31608	74	33	.	.	PUNCT
fcis-31608	75	1	by	by	ADP
fcis-31608	75	2	identifying	identify	VERB
fcis-31608	75	3	the	the	DET
fcis-31608	75	4	calibration	calibration	NOUN
fcis-31608	75	5	object	object	NOUN
fcis-31608	75	6	within	within	ADP
fcis-31608	75	7	the	the	DET
fcis-31608	75	8	image	image	NOUN
fcis-31608	75	9	and	and	CCONJ
fcis-31608	75	10	measuring	measure	VERB
fcis-31608	75	11	its	its	PRON
fcis-31608	75	12	pixel	pixel	PROPN
fcis-31608	75	13	diameter	diameter	NOUN
fcis-31608	75	14	,	,	PUNCT
fcis-31608	75	15	depth	depth	NOUN
fcis-31608	75	16	of	of	ADP
fcis-31608	75	17	field	field	NOUN
fcis-31608	75	18	features	feature	NOUN
fcis-31608	75	19	can	can	AUX
fcis-31608	75	20	be	be	AUX
fcis-31608	75	21	extracted	extract	VERB
fcis-31608	75	22	.	.	PUNCT
fcis-31608	76	1	these	these	DET
fcis-31608	76	2	features	feature	NOUN
fcis-31608	76	3	are	be	AUX
fcis-31608	76	4	then	then	ADV
fcis-31608	76	5	incorporated	incorporate	VERB
fcis-31608	76	6	as	as	ADP
fcis-31608	76	7	input	input	NOUN
fcis-31608	76	8	variables	variable	NOUN
fcis-31608	76	9	alongside	alongside	ADP
fcis-31608	76	10	other	other	ADJ
fcis-31608	76	11	body	body	NOUN
fcis-31608	76	12	measurement	measurement	NOUN
fcis-31608	76	13	parameters	parameter	NOUN
fcis-31608	76	14	to	to	PART
fcis-31608	76	15	train	train	VERB
fcis-31608	76	16	the	the	DET
fcis-31608	76	17	weight	weight	NOUN
fcis-31608	76	18	prediction	prediction	NOUN
fcis-31608	76	19	model	model	NOUN
fcis-31608	76	20	.	.	PUNCT
fcis-31608	77	1	the	the	DET
fcis-31608	77	2	hough	hough	PROPN
fcis-31608	77	3	circle	circle	PROPN
fcis-31608	77	4	transform	transform	NOUN
fcis-31608	77	5	is	be	AUX
fcis-31608	77	6	employed	employ	VERB
fcis-31608	77	7	to	to	PART
fcis-31608	77	8	detect	detect	VERB
fcis-31608	77	9	the	the	DET
fcis-31608	77	10	calibration	calibration	NOUN
fcis-31608	77	11	disk	disk	NOUN
fcis-31608	77	12	,	,	PUNCT
fcis-31608	77	13	as	as	SCONJ
fcis-31608	77	14	illustrated	illustrate	VERB
fcis-31608	77	15	in	in	ADP
fcis-31608	77	16	figure	figure	NOUN
fcis-31608	77	17	5	5	NUM
fcis-31608	77	18	.	.	PUNCT
fcis-31608	78	1	this	this	DET
fcis-31608	78	2	algorithm	algorithm	NOUN
fcis-31608	78	3	scans	scan	VERB
fcis-31608	78	4	the	the	DET
fcis-31608	78	5	image	image	NOUN
fcis-31608	78	6	for	for	ADP
fcis-31608	78	7	regions	region	NOUN
fcis-31608	78	8	that	that	PRON
fcis-31608	78	9	are	be	AUX
fcis-31608	78	10	likely	likely	ADV
fcis-31608	78	11	circular	circular	ADJ
fcis-31608	78	12	,	,	PUNCT
fcis-31608	78	13	fitting	fitting	ADJ
fcis-31608	78	14	circles	circle	NOUN
fcis-31608	78	15	based	base	VERB
fcis-31608	78	16	on	on	ADP
fcis-31608	78	17	the	the	DET
fcis-31608	78	18	radius	radius	NOUN
fcis-31608	78	19	parameter	parameter	NOUN
fcis-31608	78	20	.	.	PUNCT
fcis-31608	79	1	ultimately	ultimately	ADV
fcis-31608	79	2	,	,	PUNCT
fcis-31608	79	3	the	the	DET
fcis-31608	79	4	center	center	NOUN
fcis-31608	79	5	coordinates	coordinate	VERB
fcis-31608	79	6	and	and	CCONJ
fcis-31608	79	7	pixel	pixel	PROPN
fcis-31608	79	8	radius	radius	NOUN
fcis-31608	79	9	of	of	ADP
fcis-31608	79	10	the	the	DET
fcis-31608	79	11	circular	circular	ADJ
fcis-31608	79	12	calibration	calibration	NOUN
fcis-31608	79	13	object	object	NOUN
fcis-31608	79	14	are	be	AUX
fcis-31608	79	15	determined	determine	VERB
fcis-31608	79	16	.	.	PUNCT
fcis-31608	80	1	these	these	DET
fcis-31608	80	2	detected	detect	VERB
fcis-31608	80	3	center	center	NOUN
fcis-31608	80	4	coordinates	coordinate	NOUN
fcis-31608	80	5	and	and	CCONJ
fcis-31608	80	6	pixel	pixel	PROPN
fcis-31608	80	7	radius	radius	PROPN
fcis-31608	80	8	serve	serve	VERB
fcis-31608	80	9	as	as	ADP
fcis-31608	80	10	the	the	DET
fcis-31608	80	11	basis	basis	NOUN
fcis-31608	80	12	for	for	ADP
fcis-31608	80	13	subsequent	subsequent	ADJ
fcis-31608	80	14	scale	scale	NOUN
fcis-31608	80	15	correction	correction	NOUN
fcis-31608	80	16	.	.	PUNCT
fcis-31608	81	1	fig	fig	NOUN
fcis-31608	81	2	6	6	NUM
fcis-31608	81	3	.	.	PUNCT
fcis-31608	82	1	neural	neural	ADJ
fcis-31608	82	2	network	network	NOUN
fcis-31608	82	3	architecture	architecture	NOUN
fcis-31608	82	4	diagram	diagram	NOUN
fcis-31608	82	5	a	a	DET
fcis-31608	82	6	multi	multi	ADJ
fcis-31608	82	7	-	-	ADJ
fcis-31608	82	8	layer	layer	NOUN
fcis-31608	82	9	fully	fully	ADV
fcis-31608	82	10	connected	connect	VERB
fcis-31608	82	11	neural	neural	ADJ
fcis-31608	82	12	network	network	NOUN
fcis-31608	82	13	is	be	AUX
fcis-31608	82	14	employed	employ	VERB
fcis-31608	82	15	to	to	PART
fcis-31608	82	16	predict	predict	VERB
fcis-31608	82	17	weight	weight	NOUN
fcis-31608	82	18	.	.	PUNCT
fcis-31608	83	1	the	the	DET
fcis-31608	83	2	input	input	NOUN
fcis-31608	83	3	features	feature	VERB
fcis-31608	83	4	consist	consist	VERB
fcis-31608	83	5	of	of	ADP
fcis-31608	83	6	the	the	DET
fcis-31608	83	7	euclidean	euclidean	ADJ
fcis-31608	83	8	distances	distance	NOUN
fcis-31608	83	9	between	between	ADP
fcis-31608	83	10	five	five	NUM
fcis-31608	83	11	pairs	pair	NOUN
fcis-31608	83	12	of	of	ADP
fcis-31608	83	13	key	key	ADJ
fcis-31608	83	14	points	point	NOUN
fcis-31608	83	15	,	,	PUNCT
fcis-31608	83	16	representing	represent	VERB
fcis-31608	83	17	body	body	NOUN
fcis-31608	83	18	measurement	measurement	NOUN
fcis-31608	83	19	parameters	parameter	NOUN
fcis-31608	83	20	,	,	PUNCT
fcis-31608	83	21	along	along	ADP
fcis-31608	83	22	with	with	ADP
fcis-31608	83	23	the	the	DET
fcis-31608	83	24	pixel	pixel	ADJ
fcis-31608	83	25	values	value	NOUN
fcis-31608	83	26	of	of	ADP
fcis-31608	83	27	the	the	DET
fcis-31608	83	28	circle	circle	NOUN
fcis-31608	83	29	diameter	diameter	NOUN
fcis-31608	83	30	obtained	obtain	VERB
fcis-31608	83	31	after	after	ADP
fcis-31608	83	32	depth	depth	NOUN
fcis-31608	83	33	correction	correction	NOUN
fcis-31608	83	34	.	.	PUNCT
fcis-31608	84	1	these	these	DET
fcis-31608	84	2	features	feature	NOUN
fcis-31608	84	3	are	be	AUX
fcis-31608	84	4	processed	process	VERB
fcis-31608	84	5	through	through	ADP
fcis-31608	84	6	multiple	multiple	ADJ
fcis-31608	84	7	fully	fully	ADV
fcis-31608	84	8	connected	connected	ADJ
fcis-31608	84	9	layers	layer	NOUN
fcis-31608	84	10	,	,	PUNCT
fcis-31608	84	11	ultimately	ultimately	ADV
fcis-31608	84	12	producing	produce	VERB
fcis-31608	84	13	the	the	DET
fcis-31608	84	14	predicted	predict	VERB
fcis-31608	84	15	weight	weight	NOUN
fcis-31608	84	16	of	of	ADP
fcis-31608	84	17	the	the	DET
fcis-31608	84	18	cow	cow	NOUN
fcis-31608	84	19	.	.	PUNCT
fcis-31608	85	1	the	the	DET
fcis-31608	85	2	architecture	architecture	NOUN
fcis-31608	85	3	of	of	ADP
fcis-31608	85	4	the	the	DET
fcis-31608	85	5	weight	weight	NOUN
fcis-31608	85	6	prediction	prediction	NOUN
fcis-31608	85	7	network	network	NOUN
fcis-31608	85	8	is	be	AUX
fcis-31608	85	9	illustrated	illustrate	VERB
fcis-31608	85	10	in	in	ADP
fcis-31608	85	11	figure	figure	NOUN
fcis-31608	85	12	6	6	NUM
fcis-31608	85	13	.	.	NOUN
fcis-31608	86	1	4	4	NUM
fcis-31608	86	2	.	.	X
fcis-31608	87	1	analysis	analysis	NOUN
fcis-31608	87	2	of	of	ADP
fcis-31608	87	3	experimental	experimental	ADJ
fcis-31608	87	4	results	result	NOUN
fcis-31608	87	5	4.1	4.1	NUM
fcis-31608	87	6	.	.	PUNCT
fcis-31608	88	1	evaluation	evaluation	NOUN
fcis-31608	88	2	of	of	ADP
fcis-31608	88	3	keypoint	keypoint	NOUN
fcis-31608	88	4	detection	detection	NOUN
fcis-31608	88	5	models	model	NOUN
fcis-31608	88	6	this	this	DET
fcis-31608	88	7	study	study	NOUN
fcis-31608	88	8	employs	employ	VERB
fcis-31608	88	9	the	the	DET
fcis-31608	88	10	pck	pck	NOUN
fcis-31608	88	11	(	(	PUNCT
fcis-31608	88	12	percentage	percentage	NOUN
fcis-31608	88	13	of	of	ADP
fcis-31608	88	14	correct	correct	ADJ
fcis-31608	88	15	keypoints	keypoint	NOUN
fcis-31608	88	16	)	)	PUNCT
fcis-31608	88	17	metric	metric	NOUN
fcis-31608	88	18	to	to	PART
fcis-31608	88	19	evaluate	evaluate	VERB
fcis-31608	88	20	the	the	DET
fcis-31608	88	21	performance	performance	NOUN
fcis-31608	88	22	of	of	ADP
fcis-31608	88	23	keypoint	keypoint	NOUN
fcis-31608	88	24	detection	detection	NOUN
fcis-31608	88	25	models	model	NOUN
fcis-31608	88	26	.	.	PUNCT
fcis-31608	89	1	pck	pck	NOUN
fcis-31608	89	2	primarily	primarily	ADV
fcis-31608	89	3	measures	measure	VERB
fcis-31608	89	4	a	a	DET
fcis-31608	89	5	model	model	NOUN
fcis-31608	89	6	’s	’s	PART
fcis-31608	89	7	ability	ability	NOUN
fcis-31608	89	8	to	to	PART
fcis-31608	89	9	accurately	accurately	ADV
fcis-31608	89	10	detect	detect	VERB
fcis-31608	89	11	keypoints	keypoint	NOUN
fcis-31608	89	12	within	within	ADP
fcis-31608	89	13	various	various	ADJ
fcis-31608	89	14	distance	distance	NOUN
fcis-31608	89	15	thresholds	threshold	NOUN
fcis-31608	89	16	,	,	PUNCT
fcis-31608	89	17	effectively	effectively	ADV
fcis-31608	89	18	reflecting	reflect	VERB
fcis-31608	89	19	performance	performance	NOUN
fcis-31608	89	20	under	under	ADP
fcis-31608	89	21	multiscale	multiscale	ADJ
fcis-31608	89	22	imaging	imaging	NOUN
fcis-31608	89	23	conditions	condition	NOUN
fcis-31608	89	24	.	.	PUNCT
fcis-31608	90	1	it	it	PRON
fcis-31608	90	2	calculates	calculate	VERB
fcis-31608	90	3	the	the	DET
fcis-31608	90	4	percentage	percentage	NOUN
fcis-31608	90	5	of	of	ADP
fcis-31608	90	6	correctly	correctly	ADV
fcis-31608	90	7	detected	detect	VERB
fcis-31608	90	8	keypoints	keypoint	NOUN
fcis-31608	90	9	by	by	ADP
fcis-31608	90	10	determining	determine	VERB
fcis-31608	90	11	whether	whether	SCONJ
fcis-31608	90	12	the	the	DET
fcis-31608	90	13	distance	distance	NOUN
fcis-31608	90	14	between	between	ADP
fcis-31608	90	15	predicted	predict	VERB
fcis-31608	90	16	keypoints	keypoint	NOUN
fcis-31608	90	17	and	and	CCONJ
fcis-31608	90	18	ground	ground	NOUN
fcis-31608	90	19	truth	truth	NOUN
fcis-31608	90	20	keypoints	keypoint	NOUN
fcis-31608	90	21	falls	fall	VERB
fcis-31608	90	22	within	within	ADP
fcis-31608	90	23	an	an	DET
fcis-31608	90	24	acceptable	acceptable	ADJ
fcis-31608	90	25	range	range	NOUN
fcis-31608	90	26	at	at	ADP
fcis-31608	90	27	each	each	DET
fcis-31608	90	28	threshold	threshold	NOUN
fcis-31608	90	29	.	.	PUNCT
fcis-31608	91	1	to	to	PART
fcis-31608	91	2	comprehensively	comprehensively	ADV
fcis-31608	91	3	assess	assess	VERB
fcis-31608	91	4	model	model	NOUN
fcis-31608	91	5	performance	performance	NOUN
fcis-31608	91	6	,	,	PUNCT
fcis-31608	91	7	pck	pck	NOUN
fcis-31608	91	8	values	value	NOUN
fcis-31608	91	9	are	be	AUX
fcis-31608	91	10	computed	compute	VERB
fcis-31608	91	11	on	on	ADP
fcis-31608	91	12	both	both	CCONJ
fcis-31608	91	13	the	the	DET
fcis-31608	91	14	training	training	NOUN
fcis-31608	91	15	and	and	CCONJ
fcis-31608	91	16	validation	validation	NOUN
fcis-31608	91	17	sets	set	NOUN
fcis-31608	91	18	.	.	PUNCT
fcis-31608	92	1	calculating	calculate	VERB
fcis-31608	92	2	pck	pck	NOUN
fcis-31608	92	3	on	on	ADP
fcis-31608	92	4	the	the	DET
fcis-31608	92	5	training	training	NOUN
fcis-31608	92	6	set	set	NOUN
fcis-31608	92	7	allows	allow	VERB
fcis-31608	92	8	real	real	ADJ
fcis-31608	92	9	-	-	PUNCT
fcis-31608	92	10	time	time	NOUN
fcis-31608	92	11	monitoring	monitoring	NOUN
fcis-31608	92	12	of	of	ADP
fcis-31608	92	13	the	the	DET
fcis-31608	92	14	model	model	NOUN
fcis-31608	92	15	’s	’s	PART
fcis-31608	92	16	learning	learn	VERB
fcis-31608	92	17	progress	progress	NOUN
fcis-31608	92	18	,	,	PUNCT
fcis-31608	92	19	while	while	SCONJ
fcis-31608	92	20	pck	pck	NOUN
fcis-31608	92	21	on	on	ADP
fcis-31608	92	22	the	the	DET
fcis-31608	92	23	validation	validation	NOUN
fcis-31608	92	24	set	set	NOUN
fcis-31608	92	25	serves	serve	VERB
fcis-31608	92	26	as	as	ADP
fcis-31608	92	27	a	a	DET
fcis-31608	92	28	key	key	ADJ
fcis-31608	92	29	indicator	indicator	NOUN
fcis-31608	92	30	of	of	ADP
fcis-31608	92	31	the	the	DET
fcis-31608	92	32	model	model	NOUN
fcis-31608	92	33	’s	’s	PART
fcis-31608	92	34	generalization	generalization	NOUN
fcis-31608	92	35	ability	ability	NOUN
fcis-31608	92	36	.	.	PUNCT
fcis-31608	93	1	higher	high	ADJ
fcis-31608	93	2	pck	pck	PROPN
fcis-31608	93	3	values	value	NOUN
fcis-31608	93	4	indicate	indicate	VERB
fcis-31608	93	5	that	that	SCONJ
fcis-31608	93	6	the	the	DET
fcis-31608	93	7	model	model	NOUN
fcis-31608	93	8	correctly	correctly	ADV
fcis-31608	93	9	recalls	recall	VERB
fcis-31608	93	10	more	more	ADJ
fcis-31608	93	11	keypoints	keypoint	NOUN
fcis-31608	93	12	,	,	PUNCT
fcis-31608	93	13	demonstrating	demonstrate	VERB
fcis-31608	93	14	greater	great	ADJ
fcis-31608	93	15	accuracy	accuracy	NOUN
fcis-31608	93	16	and	and	CCONJ
fcis-31608	93	17	robustness	robustness	NOUN
fcis-31608	93	18	.	.	PUNCT
fcis-31608	94	1	during	during	ADP
fcis-31608	94	2	keypoint	keypoint	NOUN
fcis-31608	94	3	detection	detection	NOUN
fcis-31608	94	4	using	use	VERB
fcis-31608	94	5	the	the	DET
fcis-31608	94	6	mobilenetv3	mobilenetv3	NOUN
fcis-31608	94	7	and	and	CCONJ
fcis-31608	94	8	resnet50	resnet50	NOUN
fcis-31608	94	9	models	model	NOUN
fcis-31608	94	10	,	,	PUNCT
fcis-31608	94	11	pck	pck	NOUN
fcis-31608	94	12	values	value	NOUN
fcis-31608	94	13	were	be	AUX
fcis-31608	94	14	calculated	calculate	VERB
fcis-31608	94	15	for	for	ADP
fcis-31608	94	16	both	both	DET
fcis-31608	94	17	models	model	NOUN
fcis-31608	94	18	on	on	ADP
fcis-31608	94	19	the	the	DET
fcis-31608	94	20	training	training	NOUN
fcis-31608	94	21	and	and	CCONJ
fcis-31608	94	22	validation	validation	NOUN
fcis-31608	94	23	sets	set	NOUN
fcis-31608	94	24	,	,	PUNCT
fcis-31608	94	25	enabling	enable	VERB
fcis-31608	94	26	a	a	DET
fcis-31608	94	27	comparative	comparative	ADJ
fcis-31608	94	28	analysis	analysis	NOUN
fcis-31608	94	29	.	.	PUNCT
fcis-31608	95	1	these	these	DET
fcis-31608	95	2	evaluations	evaluation	NOUN
fcis-31608	95	3	confirm	confirm	VERB
fcis-31608	95	4	the	the	DET
fcis-31608	95	5	models	model	NOUN
fcis-31608	95	6	’	’	PART
fcis-31608	95	7	stability	stability	NOUN
fcis-31608	95	8	and	and	CCONJ
fcis-31608	95	9	robustness	robustness	NOUN
fcis-31608	95	10	under	under	ADP
fcis-31608	95	11	varying	vary	VERB
fcis-31608	95	12	shooting	shooting	NOUN
fcis-31608	95	13	conditions	condition	NOUN
fcis-31608	95	14	.	.	PUNCT
fcis-31608	96	1	the	the	DET
fcis-31608	96	2	changes	change	NOUN
fcis-31608	96	3	in	in	ADP
fcis-31608	96	4	pck	pck	NOUN
fcis-31608	96	5	metrics	metric	NOUN
fcis-31608	96	6	for	for	ADP
fcis-31608	96	7	both	both	DET
fcis-31608	96	8	models	model	NOUN
fcis-31608	96	9	are	be	AUX
fcis-31608	96	10	illustrated	illustrate	VERB
fcis-31608	96	11	in	in	ADP
fcis-31608	96	12	figure	figure	NOUN
fcis-31608	96	13	7	7	NUM
fcis-31608	96	14	.	.	PUNCT
fcis-31608	97	1	the	the	DET
fcis-31608	97	2	experimental	experimental	ADJ
fcis-31608	97	3	results	result	NOUN
fcis-31608	97	4	demonstrate	demonstrate	VERB
fcis-31608	97	5	that	that	SCONJ
fcis-31608	97	6	both	both	DET
fcis-31608	97	7	models	model	NOUN
fcis-31608	97	8	achieved	achieve	VERB
fcis-31608	97	9	high	high	ADJ
fcis-31608	97	10	pck	pck	NOUN
fcis-31608	97	11	values	value	NOUN
fcis-31608	97	12	on	on	ADP
fcis-31608	97	13	the	the	DET
fcis-31608	97	14	training	training	NOUN
fcis-31608	97	15	and	and	CCONJ
fcis-31608	97	16	validation	validation	NOUN
fcis-31608	97	17	sets	set	NOUN
fcis-31608	97	18	,	,	PUNCT
fcis-31608	97	19	indicating	indicate	VERB
fcis-31608	97	20	strong	strong	ADJ
fcis-31608	97	21	recall	recall	NOUN
fcis-31608	97	22	capabilities	capability	NOUN
fcis-31608	97	23	,	,	PUNCT
fcis-31608	97	24	especially	especially	ADV
fcis-31608	97	25	under	under	ADP
fcis-31608	97	26	varying	vary	VERB
fcis-31608	97	27	shooting	shooting	NOUN
fcis-31608	97	28	angles	angle	NOUN
fcis-31608	97	29	and	and	CCONJ
fcis-31608	97	30	lighting	lighting	NOUN
fcis-31608	97	31	conditions	condition	NOUN
fcis-31608	97	32	.	.	PUNCT
fcis-31608	98	1	the	the	DET
fcis-31608	98	2	mobilenetv3	mobilenetv3	PROPN
fcis-31608	98	3	model	model	PROPN
fcis-31608	98	4	converged	converge	VERB
fcis-31608	98	5	rapidly	rapidly	ADV
fcis-31608	98	6	during	during	ADP
fcis-31608	98	7	training	training	NOUN
fcis-31608	98	8	,	,	PUNCT
fcis-31608	98	9	exhibiting	exhibit	VERB
fcis-31608	98	10	lower	low	ADJ
fcis-31608	98	11	computational	computational	ADJ
fcis-31608	98	12	complexity	complexity	NOUN
fcis-31608	98	13	and	and	CCONJ
fcis-31608	98	14	excellent	excellent	ADJ
fcis-31608	98	15	real	real	ADJ
fcis-31608	98	16	-	-	PUNCT
fcis-31608	98	17	time	time	NOUN
fcis-31608	98	18	performance	performance	NOUN
fcis-31608	98	19	,	,	PUNCT
fcis-31608	98	20	which	which	PRON
fcis-31608	98	21	enables	enable	VERB
fcis-31608	98	22	keypoint	keypoint	VERB
fcis-31608	98	23	detection	detection	NOUN
fcis-31608	98	24	to	to	PART
fcis-31608	98	25	be	be	AUX
fcis-31608	98	26	completed	complete	VERB
fcis-31608	98	27	quickly	quickly	ADV
fcis-31608	98	28	.	.	PUNCT
fcis-31608	99	1	this	this	PRON
fcis-31608	99	2	makes	make	VERB
fcis-31608	99	3	it	it	PRON
fcis-31608	99	4	well	well	ADV
fcis-31608	99	5	-	-	PUNCT
fcis-31608	99	6	suited	suit	VERB
fcis-31608	99	7	for	for	ADP
fcis-31608	99	8	applications	application	NOUN
fcis-31608	99	9	with	with	ADP
fcis-31608	99	10	stringent	stringent	ADJ
fcis-31608	99	11	real	real	ADJ
fcis-31608	99	12	-	-	PUNCT
fcis-31608	99	13	time	time	NOUN
fcis-31608	99	14	processing	processing	NOUN
fcis-31608	99	15	requirements	requirement	NOUN
fcis-31608	99	16	.	.	PUNCT
fcis-31608	100	1	based	base	VERB
fcis-31608	100	2	on	on	ADP
fcis-31608	100	3	these	these	DET
fcis-31608	100	4	evaluation	evaluation	NOUN
fcis-31608	100	5	metrics	metric	NOUN
fcis-31608	100	6	,	,	PUNCT
fcis-31608	100	7	the	the	DET
fcis-31608	100	8	mobilenetv3	mobilenetv3	PROPN
fcis-31608	100	9	model	model	NOUN
fcis-31608	100	10	proves	prove	VERB
fcis-31608	100	11	to	to	PART
fcis-31608	100	12	be	be	AUX
fcis-31608	100	13	more	more	ADV
fcis-31608	100	14	efficient	efficient	ADJ
fcis-31608	100	15	in	in	ADP
fcis-31608	100	16	practical	practical	ADJ
fcis-31608	100	17	scenarios	scenario	NOUN
fcis-31608	100	18	,	,	PUNCT
fcis-31608	100	19	particularly	particularly	ADV
fcis-31608	100	20	in	in	ADP
fcis-31608	100	21	realworld	realworld	PROPN
fcis-31608	100	22	environments	environment	NOUN
fcis-31608	100	23	that	that	PRON
fcis-31608	100	24	demand	demand	VERB
fcis-31608	100	25	both	both	PRON
fcis-31608	100	26	speed	speed	NOUN
fcis-31608	100	27	and	and	CCONJ
fcis-31608	100	28	accuracy	accuracy	NOUN
fcis-31608	100	29	,	,	PUNCT
fcis-31608	100	30	showcasing	showcase	VERB
fcis-31608	100	31	strong	strong	ADJ
fcis-31608	100	32	adaptability	adaptability	NOUN
fcis-31608	100	33	and	and	CCONJ
fcis-31608	100	34	robustness	robustness	NOUN
fcis-31608	100	35	.	.	PUNCT
fcis-31608	101	1	furthermore	furthermore	ADV
fcis-31608	101	2	,	,	PUNCT
fcis-31608	101	3	the	the	DET
fcis-31608	101	4	mobilenetv3	mobilenetv3	PROPN
fcis-31608	101	5	model	model	PROPN
fcis-31608	101	6	’s	’s	PART
fcis-31608	101	7	stability	stability	NOUN
fcis-31608	101	8	and	and	CCONJ
fcis-31608	101	9	high	high	ADJ
fcis-31608	101	10	recall	recall	NOUN
fcis-31608	101	11	rate	rate	NOUN
fcis-31608	101	12	across	across	ADP
fcis-31608	101	13	different	different	ADJ
fcis-31608	101	14	shooting	shooting	NOUN
fcis-31608	101	15	conditions	condition	NOUN
fcis-31608	101	16	provide	provide	VERB
fcis-31608	101	17	robust	robust	ADJ
fcis-31608	101	18	feature	feature	NOUN
fcis-31608	101	19	support	support	NOUN
fcis-31608	101	20	for	for	ADP
fcis-31608	101	21	subsequent	subsequent	ADJ
fcis-31608	101	22	weight	weight	NOUN
fcis-31608	101	23	prediction	prediction	NOUN
fcis-31608	101	24	models	model	NOUN
fcis-31608	101	25	,	,	PUNCT
fcis-31608	101	26	ensuring	ensure	VERB
fcis-31608	101	27	the	the	DET
fcis-31608	101	28	reliability	reliability	NOUN
fcis-31608	101	29	and	and	CCONJ
fcis-31608	101	30	accuracy	accuracy	NOUN
fcis-31608	101	31	of	of	ADP
fcis-31608	101	32	the	the	DET
fcis-31608	101	33	weight	weight	NOUN
fcis-31608	101	34	prediction	prediction	NOUN
fcis-31608	101	35	results	result	NOUN
fcis-31608	101	36	.	.	PUNCT
fcis-31608	102	1	4.2	4.2	NUM
fcis-31608	102	2	.	.	PUNCT
fcis-31608	102	3	evaluation	evaluation	NOUN
fcis-31608	102	4	of	of	ADP
fcis-31608	102	5	the	the	DET
fcis-31608	102	6	weight	weight	NOUN
fcis-31608	102	7	prediction	prediction	NOUN
fcis-31608	102	8	model	model	NOUN
fcis-31608	102	9	this	this	DET
fcis-31608	102	10	experiment	experiment	NOUN
fcis-31608	102	11	employs	employ	VERB
fcis-31608	102	12	a	a	DET
fcis-31608	102	13	common	common	ADJ
fcis-31608	102	14	regression	regression	NOUN
fcis-31608	102	15	evaluation	evaluation	NOUN
fcis-31608	102	16	metric	metric	NOUN
fcis-31608	102	17	,	,	PUNCT
fcis-31608	102	18	the	the	DET
fcis-31608	102	19	mean	mean	ADJ
fcis-31608	102	20	absolute	absolute	ADJ
fcis-31608	102	21	error	error	NOUN
fcis-31608	102	22	(	(	PUNCT
fcis-31608	102	23	mae	mae	PROPN
fcis-31608	102	24	)	)	PUNCT
fcis-31608	102	25	.	.	PUNCT
fcis-31608	103	1	mae	mae	PROPN
fcis-31608	103	2	measures	measure	VERB
fcis-31608	103	3	the	the	DET
fcis-31608	103	4	average	average	ADJ
fcis-31608	103	5	absolute	absolute	ADJ
fcis-31608	103	6	difference	difference	NOUN
fcis-31608	103	7	between	between	ADP
fcis-31608	103	8	predicted	predict	VERB
fcis-31608	103	9	and	and	CCONJ
fcis-31608	103	10	actual	actual	ADJ
fcis-31608	103	11	values	value	NOUN
fcis-31608	103	12	.	.	PUNCT
fcis-31608	104	1	a	a	DET
fcis-31608	104	2	smaller	small	ADJ
fcis-31608	104	3	mae	mae	PROPN
fcis-31608	104	4	indicates	indicate	VERB
fcis-31608	104	5	a	a	DET
fcis-31608	104	6	closer	close	ADJ
fcis-31608	104	7	match	match	NOUN
fcis-31608	104	8	between	between	ADP
fcis-31608	104	9	predictions	prediction	NOUN
fcis-31608	104	10	and	and	CCONJ
fcis-31608	104	11	actual	actual	ADJ
fcis-31608	104	12	values	value	NOUN
fcis-31608	104	13	,	,	PUNCT
fcis-31608	104	14	reflecting	reflect	VERB
fcis-31608	104	15	higher	high	ADJ
fcis-31608	104	16	model	model	NOUN
fcis-31608	104	17	accuracy	accuracy	NOUN
fcis-31608	104	18	.	.	PUNCT
fcis-31608	105	1	the	the	DET
fcis-31608	105	2	experiment	experiment	NOUN
fcis-31608	105	3	compares	compare	VERB
fcis-31608	105	4	two	two	NUM
fcis-31608	105	5	weight	weight	NOUN
fcis-31608	105	6	prediction	prediction	NOUN
fcis-31608	105	7	methods	method	NOUN
fcis-31608	105	8	:	:	PUNCT
fcis-31608	105	9	(	(	PUNCT
fcis-31608	105	10	1	1	X
fcis-31608	105	11	)	)	PUNCT
fcis-31608	105	12	deriving	derive	VERB
fcis-31608	105	13	body	body	NOUN
fcis-31608	105	14	measurement	measurement	NOUN
fcis-31608	105	15	parameters	parameter	NOUN
fcis-31608	105	16	from	from	ADP
fcis-31608	105	17	keypoint	keypoint	NOUN
fcis-31608	105	18	information	information	NOUN
fcis-31608	105	19	and	and	CCONJ
fcis-31608	105	20	applying	apply	VERB
fcis-31608	105	21	depth	depth	NOUN
fcis-31608	105	22	correction	correction	NOUN
fcis-31608	105	23	technology	technology	NOUN
fcis-31608	105	24	for	for	ADP
fcis-31608	105	25	weight	weight	NOUN
fcis-31608	105	26	prediction	prediction	NOUN
fcis-31608	105	27	,	,	PUNCT
fcis-31608	105	28	with	with	ADP
fcis-31608	105	29	results	result	NOUN
fcis-31608	105	30	shown	show	VERB
fcis-31608	105	31	in	in	ADP
fcis-31608	105	32	figure8(a	figure8(a	PROPN
fcis-31608	105	33	)	)	PUNCT
fcis-31608	105	34	;	;	PUNCT
fcis-31608	105	35	and	and	CCONJ
fcis-31608	105	36	(	(	PUNCT
fcis-31608	105	37	2	2	X
fcis-31608	105	38	)	)	PUNCT
fcis-31608	105	39	using	use	VERB
fcis-31608	105	40	a	a	DET
fcis-31608	105	41	model	model	NOUN
fcis-31608	105	42	trained	train	VERB
fcis-31608	105	43	on	on	ADP
fcis-31608	105	44	keypoints	keypoint	NOUN
fcis-31608	105	45	as	as	ADP
fcis-31608	105	46	a	a	DET
fcis-31608	105	47	feature	feature	NOUN
fcis-31608	105	48	extractor	extractor	NOUN
fcis-31608	105	49	to	to	PART
fcis-31608	105	50	directly	directly	ADV
fcis-31608	105	51	predict	predict	VERB
fcis-31608	105	52	weight	weight	NOUN
fcis-31608	105	53	,	,	PUNCT
fcis-31608	105	54	with	with	ADP
fcis-31608	105	55	results	result	NOUN
fcis-31608	105	56	shown	show	VERB
fcis-31608	105	57	in	in	ADP
fcis-31608	105	58	figure	figure	NOUN
fcis-31608	105	59	8(b	8(b	NUM
fcis-31608	105	60	)	)	PUNCT
fcis-31608	105	61	.	.	PUNCT
fcis-31608	106	1	the	the	DET
fcis-31608	106	2	impact	impact	NOUN
fcis-31608	106	3	of	of	ADP
fcis-31608	106	4	different	different	ADJ
fcis-31608	106	5	input	input	NOUN
fcis-31608	106	6	features	feature	NOUN
fcis-31608	106	7	on	on	ADP
fcis-31608	106	8	weight	weight	NOUN
fcis-31608	106	9	prediction	prediction	NOUN
fcis-31608	106	10	performance	performance	NOUN
fcis-31608	106	11	is	be	AUX
fcis-31608	106	12	analyzed	analyze	VERB
fcis-31608	106	13	.	.	PUNCT
fcis-31608	107	1	the	the	DET
fcis-31608	107	2	mae	mae	PROPN
fcis-31608	107	3	values	value	NOUN
fcis-31608	107	4	for	for	ADP
fcis-31608	107	5	both	both	DET
fcis-31608	107	6	approaches	approach	NOUN
fcis-31608	107	7	are	be	AUX
fcis-31608	107	8	presented	present	VERB
fcis-31608	107	9	in	in	ADP
fcis-31608	107	10	table	table	NOUN
fcis-31608	107	11	2	2	NUM
fcis-31608	107	12	.	.	X
fcis-31608	107	13	45	45	NUM
fcis-31608	107	14	fig	fig	NOUN
fcis-31608	107	15	7	7	NUM
fcis-31608	107	16	.	.	PUNCT
fcis-31608	108	1	changes	change	NOUN
fcis-31608	108	2	in	in	ADP
fcis-31608	108	3	different	different	ADJ
fcis-31608	108	4	pck	pck	NOUN
fcis-31608	108	5	metrics	metric	NOUN
fcis-31608	108	6	(	(	PUNCT
fcis-31608	108	7	a)plan	a)plan	VERB
fcis-31608	108	8	1	1	NUM
fcis-31608	108	9	weight	weight	NOUN
fcis-31608	108	10	prediction	prediction	NOUN
fcis-31608	108	11	results	result	NOUN
fcis-31608	108	12	(	(	PUNCT
fcis-31608	108	13	b)plan	b)plan	NOUN
fcis-31608	108	14	2	2	NUM
fcis-31608	108	15	weight	weight	NOUN
fcis-31608	108	16	prediction	prediction	NOUN
fcis-31608	108	17	performance	performance	NOUN
fcis-31608	108	18	fig	fig	NOUN
fcis-31608	108	19	8	8	NUM
fcis-31608	108	20	.	.	PUNCT
fcis-31608	109	1	model	model	NOUN
fcis-31608	109	2	performance	performance	NOUN
fcis-31608	109	3	evaluation	evaluation	NOUN
fcis-31608	109	4	table	table	NOUN
fcis-31608	109	5	2	2	NUM
fcis-31608	109	6	.	.	X
fcis-31608	109	7	mae	mae	PROPN
fcis-31608	109	8	of	of	ADP
fcis-31608	109	9	the	the	DET
fcis-31608	109	10	two	two	NUM
fcis-31608	109	11	schemes	scheme	NOUN
fcis-31608	109	12	number	number	NOUN
fcis-31608	109	13	mae	mae	PROPN
fcis-31608	109	14	1	1	NUM
fcis-31608	109	15	16	16	NUM
fcis-31608	109	16	2	2	NUM
fcis-31608	109	17	23	23	NUM
fcis-31608	109	18	the	the	DET
fcis-31608	109	19	experimental	experimental	ADJ
fcis-31608	109	20	results	result	NOUN
fcis-31608	109	21	indicate	indicate	VERB
fcis-31608	109	22	that	that	SCONJ
fcis-31608	109	23	the	the	DET
fcis-31608	109	24	mean	mean	ADJ
fcis-31608	109	25	absolute	absolute	ADJ
fcis-31608	109	26	error	error	NOUN
fcis-31608	109	27	(	(	PUNCT
fcis-31608	109	28	mae	mae	PROPN
fcis-31608	109	29	)	)	PUNCT
fcis-31608	109	30	of	of	ADP
fcis-31608	109	31	the	the	DET
fcis-31608	109	32	first	first	ADJ
fcis-31608	109	33	scheme	scheme	NOUN
fcis-31608	109	34	is	be	AUX
fcis-31608	109	35	relatively	relatively	ADV
fcis-31608	109	36	low	low	ADJ
fcis-31608	109	37	,	,	PUNCT
fcis-31608	109	38	demonstrating	demonstrate	VERB
fcis-31608	109	39	that	that	SCONJ
fcis-31608	109	40	the	the	DET
fcis-31608	109	41	model	model	NOUN
fcis-31608	109	42	achieves	achieve	VERB
fcis-31608	109	43	high	high	ADJ
fcis-31608	109	44	accuracy	accuracy	NOUN
fcis-31608	109	45	in	in	ADP
fcis-31608	109	46	predicting	predict	VERB
fcis-31608	109	47	cattle	cattle	NOUN
fcis-31608	109	48	weight	weight	NOUN
fcis-31608	109	49	.	.	PUNCT
fcis-31608	110	1	using	use	VERB
fcis-31608	110	2	this	this	DET
fcis-31608	110	3	scheme	scheme	NOUN
fcis-31608	110	4	,	,	PUNCT
fcis-31608	110	5	weight	weight	NOUN
fcis-31608	110	6	data	datum	NOUN
fcis-31608	110	7	were	be	AUX
fcis-31608	110	8	collected	collect	VERB
fcis-31608	110	9	for	for	ADP
fcis-31608	110	10	20	20	NUM
fcis-31608	110	11	cows	cow	NOUN
fcis-31608	110	12	.	.	PUNCT
fcis-31608	111	1	their	their	PRON
fcis-31608	111	2	actual	actual	ADJ
fcis-31608	111	3	weights	weight	NOUN
fcis-31608	111	4	,	,	PUNCT
fcis-31608	111	5	body	body	NOUN
fcis-31608	111	6	measurement	measurement	NOUN
fcis-31608	111	7	parameters	parameter	NOUN
fcis-31608	111	8	,	,	PUNCT
fcis-31608	111	9	calibration	calibration	NOUN
fcis-31608	111	10	object	object	NOUN
fcis-31608	111	11	diameters	diameter	NOUN
fcis-31608	111	12	,	,	PUNCT
fcis-31608	111	13	and	and	CCONJ
fcis-31608	111	14	predicted	predict	VERB
fcis-31608	111	15	weights	weight	NOUN
fcis-31608	111	16	are	be	AUX
fcis-31608	111	17	presented	present	VERB
fcis-31608	111	18	in	in	ADP
fcis-31608	111	19	table	table	NOUN
fcis-31608	111	20	3	3	NUM
fcis-31608	111	21	for	for	ADP
fcis-31608	111	22	comparison	comparison	NOUN
fcis-31608	111	23	.	.	PUNCT
fcis-31608	112	1	5	5	X
fcis-31608	112	2	.	.	X
fcis-31608	112	3	summary	summary	NOUN
fcis-31608	112	4	this	this	DET
fcis-31608	112	5	study	study	NOUN
fcis-31608	112	6	proposes	propose	VERB
fcis-31608	112	7	an	an	DET
fcis-31608	112	8	automatic	automatic	ADJ
fcis-31608	112	9	cattle	cattle	NOUN
fcis-31608	112	10	weight	weight	NOUN
fcis-31608	112	11	measurement	measurement	NOUN
fcis-31608	112	12	system	system	NOUN
fcis-31608	112	13	based	base	VERB
fcis-31608	112	14	on	on	ADP
fcis-31608	112	15	deep	deep	ADJ
fcis-31608	112	16	learning	learning	NOUN
fcis-31608	112	17	.	.	PUNCT
fcis-31608	113	1	the	the	DET
fcis-31608	113	2	system	system	NOUN
fcis-31608	113	3	integrates	integrate	VERB
fcis-31608	113	4	keypoint	keypoint	NOUN
fcis-31608	113	5	detection	detection	NOUN
fcis-31608	113	6	,	,	PUNCT
fcis-31608	113	7	body	body	NOUN
fcis-31608	113	8	measurement	measurement	NOUN
fcis-31608	113	9	parameter	parameter	NOUN
fcis-31608	113	10	extraction	extraction	NOUN
fcis-31608	113	11	,	,	PUNCT
fcis-31608	113	12	and	and	CCONJ
fcis-31608	113	13	depth	depth	NOUN
fcis-31608	113	14	correction	correction	NOUN
fcis-31608	113	15	techniques	technique	NOUN
fcis-31608	113	16	to	to	PART
fcis-31608	113	17	enable	enable	VERB
fcis-31608	113	18	automatic	automatic	ADJ
fcis-31608	113	19	weight	weight	NOUN
fcis-31608	113	20	estimation	estimation	NOUN
fcis-31608	113	21	from	from	ADP
fcis-31608	113	22	cattle	cattle	NOUN
fcis-31608	113	23	images	image	NOUN
fcis-31608	113	24	.	.	PUNCT
fcis-31608	114	1	for	for	ADP
fcis-31608	114	2	keypoint	keypoint	NOUN
fcis-31608	114	3	detection	detection	NOUN
fcis-31608	114	4	,	,	PUNCT
fcis-31608	114	5	the	the	DET
fcis-31608	114	6	system	system	NOUN
fcis-31608	114	7	is	be	AUX
fcis-31608	114	8	trained	train	VERB
fcis-31608	114	9	using	use	VERB
fcis-31608	114	10	the	the	DET
fcis-31608	114	11	mean	mean	ADJ
fcis-31608	114	12	squared	square	VERB
fcis-31608	114	13	error	error	NOUN
fcis-31608	114	14	(	(	PUNCT
fcis-31608	114	15	mse	mse	NOUN
fcis-31608	114	16	)	)	PUNCT
fcis-31608	114	17	loss	loss	NOUN
fcis-31608	114	18	function	function	NOUN
fcis-31608	114	19	and	and	CCONJ
fcis-31608	114	20	the	the	DET
fcis-31608	114	21	adam	adam	PROPN
fcis-31608	114	22	optimizer	optimizer	NOUN
fcis-31608	114	23	,	,	PUNCT
fcis-31608	114	24	employing	employ	VERB
fcis-31608	114	25	a	a	DET
fcis-31608	114	26	mobilenetv3	mobilenetv3	NOUN
fcis-31608	114	27	model	model	NOUN
fcis-31608	114	28	to	to	PART
fcis-31608	114	29	detect	detect	VERB
fcis-31608	114	30	key	key	ADJ
fcis-31608	114	31	points	point	NOUN
fcis-31608	114	32	on	on	ADP
fcis-31608	114	33	the	the	DET
fcis-31608	114	34	cattle	cattle	NOUN
fcis-31608	114	35	’s	’s	PART
fcis-31608	114	36	body	body	NOUN
fcis-31608	114	37	46	46	NUM
fcis-31608	114	38	and	and	CCONJ
fcis-31608	114	39	obtain	obtain	VERB
fcis-31608	114	40	their	their	PRON
fcis-31608	114	41	coordinates	coordinate	NOUN
fcis-31608	114	42	.	.	PUNCT
fcis-31608	115	1	these	these	DET
fcis-31608	115	2	coordinates	coordinate	NOUN
fcis-31608	115	3	are	be	AUX
fcis-31608	115	4	then	then	ADV
fcis-31608	115	5	used	use	VERB
fcis-31608	115	6	to	to	PART
fcis-31608	115	7	calculate	calculate	VERB
fcis-31608	115	8	body	body	NOUN
fcis-31608	115	9	measurement	measurement	NOUN
fcis-31608	115	10	parameters	parameter	NOUN
fcis-31608	115	11	related	relate	VERB
fcis-31608	115	12	to	to	ADP
fcis-31608	115	13	weight	weight	NOUN
fcis-31608	115	14	.	.	PUNCT
fcis-31608	116	1	subsequently	subsequently	ADV
fcis-31608	116	2	,	,	PUNCT
fcis-31608	116	3	depth	depth	NOUN
fcis-31608	116	4	correction	correction	NOUN
fcis-31608	116	5	technology	technology	NOUN
fcis-31608	116	6	is	be	AUX
fcis-31608	116	7	applied	apply	VERB
fcis-31608	116	8	to	to	PART
fcis-31608	116	9	mitigate	mitigate	VERB
fcis-31608	116	10	the	the	DET
fcis-31608	116	11	effects	effect	NOUN
fcis-31608	116	12	of	of	ADP
fcis-31608	116	13	variations	variation	NOUN
fcis-31608	116	14	in	in	ADP
fcis-31608	116	15	shooting	shoot	VERB
fcis-31608	116	16	angle	angle	NOUN
fcis-31608	116	17	and	and	CCONJ
fcis-31608	116	18	distance	distance	NOUN
fcis-31608	116	19	on	on	ADP
fcis-31608	116	20	image	image	NOUN
fcis-31608	116	21	scale	scale	NOUN
fcis-31608	116	22	.	.	PUNCT
fcis-31608	117	1	through	through	ADP
fcis-31608	117	2	these	these	DET
fcis-31608	117	3	methods	method	NOUN
fcis-31608	117	4	,	,	PUNCT
fcis-31608	117	5	the	the	DET
fcis-31608	117	6	system	system	NOUN
fcis-31608	117	7	acquires	acquire	VERB
fcis-31608	117	8	more	more	ADV
fcis-31608	117	9	accurate	accurate	ADJ
fcis-31608	117	10	image	image	NOUN
fcis-31608	117	11	features	feature	NOUN
fcis-31608	117	12	,	,	PUNCT
fcis-31608	117	13	providing	provide	VERB
fcis-31608	117	14	stable	stable	ADJ
fcis-31608	117	15	and	and	CCONJ
fcis-31608	117	16	high	high	ADJ
fcis-31608	117	17	-	-	PUNCT
fcis-31608	117	18	quality	quality	NOUN
fcis-31608	117	19	data	datum	NOUN
fcis-31608	117	20	input	input	NOUN
fcis-31608	117	21	for	for	ADP
fcis-31608	117	22	weight	weight	NOUN
fcis-31608	117	23	estimation	estimation	NOUN
fcis-31608	117	24	.	.	PUNCT
fcis-31608	118	1	in	in	ADP
fcis-31608	118	2	designing	design	VERB
fcis-31608	118	3	the	the	DET
fcis-31608	118	4	weight	weight	NOUN
fcis-31608	118	5	prediction	prediction	NOUN
fcis-31608	118	6	model	model	NOUN
fcis-31608	118	7	,	,	PUNCT
fcis-31608	118	8	a	a	DET
fcis-31608	118	9	regression	regression	NOUN
fcis-31608	118	10	neural	neural	ADJ
fcis-31608	118	11	network	network	NOUN
fcis-31608	118	12	based	base	VERB
fcis-31608	118	13	on	on	ADP
fcis-31608	118	14	fully	fully	ADV
fcis-31608	118	15	connected	connected	ADJ
fcis-31608	118	16	layers	layer	NOUN
fcis-31608	118	17	is	be	AUX
fcis-31608	118	18	utilized	utilize	VERB
fcis-31608	118	19	,	,	PUNCT
fcis-31608	118	20	trained	train	VERB
fcis-31608	118	21	with	with	ADP
fcis-31608	118	22	the	the	DET
fcis-31608	118	23	smooth	smooth	ADJ
fcis-31608	118	24	l1	l1	PROPN
fcis-31608	118	25	loss	loss	NOUN
fcis-31608	118	26	function	function	NOUN
fcis-31608	118	27	.	.	PUNCT
fcis-31608	119	1	by	by	ADP
fcis-31608	119	2	integrating	integrate	VERB
fcis-31608	119	3	body	body	NOUN
fcis-31608	119	4	measurement	measurement	NOUN
fcis-31608	119	5	parameters	parameter	NOUN
fcis-31608	119	6	and	and	CCONJ
fcis-31608	119	7	depth	depth	NOUN
fcis-31608	119	8	features	feature	NOUN
fcis-31608	119	9	,	,	PUNCT
fcis-31608	119	10	the	the	DET
fcis-31608	119	11	model	model	NOUN
fcis-31608	119	12	comprehensively	comprehensively	ADV
fcis-31608	119	13	captures	capture	VERB
fcis-31608	119	14	the	the	DET
fcis-31608	119	15	relationship	relationship	NOUN
fcis-31608	119	16	between	between	ADP
fcis-31608	119	17	cattle	cattle	NOUN
fcis-31608	119	18	body	body	NOUN
fcis-31608	119	19	shape	shape	NOUN
fcis-31608	119	20	and	and	CCONJ
fcis-31608	119	21	weight	weight	NOUN
fcis-31608	119	22	,	,	PUNCT
fcis-31608	119	23	thereby	thereby	ADV
fcis-31608	119	24	improving	improve	VERB
fcis-31608	119	25	prediction	prediction	NOUN
fcis-31608	119	26	accuracy	accuracy	NOUN
fcis-31608	119	27	.	.	PUNCT
fcis-31608	120	1	experimental	experimental	ADJ
fcis-31608	120	2	results	result	NOUN
fcis-31608	120	3	demonstrate	demonstrate	VERB
fcis-31608	120	4	that	that	SCONJ
fcis-31608	120	5	the	the	DET
fcis-31608	120	6	system	system	NOUN
fcis-31608	120	7	performs	perform	VERB
fcis-31608	120	8	well	well	ADV
fcis-31608	120	9	under	under	ADP
fcis-31608	120	10	various	various	ADJ
fcis-31608	120	11	shooting	shooting	NOUN
fcis-31608	120	12	angles	angle	NOUN
fcis-31608	120	13	and	and	CCONJ
fcis-31608	120	14	lighting	lighting	NOUN
fcis-31608	120	15	conditions	condition	NOUN
fcis-31608	120	16	.	.	PUNCT
fcis-31608	121	1	evaluation	evaluation	NOUN
fcis-31608	121	2	metrics	metric	NOUN
fcis-31608	121	3	such	such	ADJ
fcis-31608	121	4	as	as	ADP
fcis-31608	121	5	mean	mean	NOUN
fcis-31608	121	6	absolute	absolute	ADJ
fcis-31608	121	7	error	error	NOUN
fcis-31608	121	8	(	(	PUNCT
fcis-31608	121	9	mae	mae	PROPN
fcis-31608	121	10	)	)	PUNCT
fcis-31608	121	11	,	,	PUNCT
fcis-31608	121	12	root	root	NOUN
fcis-31608	121	13	mean	mean	VERB
fcis-31608	121	14	square	square	ADJ
fcis-31608	121	15	error	error	NOUN
fcis-31608	121	16	(	(	PUNCT
fcis-31608	121	17	rmse	rmse	NOUN
fcis-31608	121	18	)	)	PUNCT
fcis-31608	121	19	,	,	PUNCT
fcis-31608	121	20	and	and	CCONJ
fcis-31608	121	21	mean	mean	VERB
fcis-31608	121	22	absolute	absolute	ADJ
fcis-31608	121	23	percentage	percentage	NOUN
fcis-31608	121	24	error	error	NOUN
fcis-31608	121	25	(	(	PUNCT
fcis-31608	121	26	mape	mape	NOUN
fcis-31608	121	27	)	)	PUNCT
fcis-31608	121	28	indicate	indicate	VERB
fcis-31608	121	29	that	that	SCONJ
fcis-31608	121	30	the	the	DET
fcis-31608	121	31	system	system	NOUN
fcis-31608	121	32	achieves	achieve	VERB
fcis-31608	121	33	high	high	ADJ
fcis-31608	121	34	precision	precision	NOUN
fcis-31608	121	35	and	and	CCONJ
fcis-31608	121	36	strong	strong	ADJ
fcis-31608	121	37	stability	stability	NOUN
fcis-31608	121	38	.	.	PUNCT
fcis-31608	122	1	however	however	ADV
fcis-31608	122	2	,	,	PUNCT
fcis-31608	122	3	there	there	PRON
fcis-31608	122	4	remains	remain	VERB
fcis-31608	122	5	room	room	NOUN
fcis-31608	122	6	for	for	ADP
fcis-31608	122	7	improvement	improvement	NOUN
fcis-31608	122	8	,	,	PUNCT
fcis-31608	122	9	such	such	ADJ
fcis-31608	122	10	as	as	ADP
fcis-31608	122	11	enhancing	enhance	VERB
fcis-31608	122	12	dataset	dataset	ADJ
fcis-31608	122	13	diversity	diversity	NOUN
fcis-31608	122	14	and	and	CCONJ
fcis-31608	122	15	improving	improve	VERB
fcis-31608	122	16	model	model	ADJ
fcis-31608	122	17	computational	computational	ADJ
fcis-31608	122	18	efficiency	efficiency	NOUN
fcis-31608	122	19	,	,	PUNCT
fcis-31608	122	20	especially	especially	ADV
fcis-31608	122	21	in	in	ADP
fcis-31608	122	22	complex	complex	ADJ
fcis-31608	122	23	environments	environment	NOUN
fcis-31608	122	24	.	.	PUNCT
fcis-31608	123	1	table	table	NOUN
fcis-31608	123	2	3	3	NUM
fcis-31608	123	3	.	.	PUNCT
fcis-31608	123	4	comparison	comparison	NOUN
fcis-31608	123	5	of	of	ADP
fcis-31608	123	6	predicted	predict	VERB
fcis-31608	123	7	and	and	CCONJ
fcis-31608	123	8	actual	actual	ADJ
fcis-31608	123	9	body	body	NOUN
fcis-31608	123	10	weight	weight	NOUN
fcis-31608	123	11	results	result	VERB
fcis-31608	123	12	number	number	NOUN
fcis-31608	123	13	oblique	oblique	ADJ
fcis-31608	123	14	length	length	NOUN
fcis-31608	123	15	1	1	NUM
fcis-31608	123	16	oblique	oblique	ADJ
fcis-31608	123	17	length	length	NOUN
fcis-31608	123	18	2	2	NUM
fcis-31608	123	19	bust	bust	NOUN
fcis-31608	123	20	measurement	measurement	NOUN
fcis-31608	123	21	abdominal	abdominal	ADJ
fcis-31608	123	22	circumference	circumference	NOUN
fcis-31608	123	23	height	height	NOUN
fcis-31608	123	24	disk	disk	NOUN
fcis-31608	123	25	diameter	diameter	NOUN
fcis-31608	123	26	actual	actual	ADJ
fcis-31608	123	27	weight	weight	NOUN
fcis-31608	123	28	predict	predict	VERB
fcis-31608	123	29	weight	weight	NOUN
fcis-31608	123	30	1	1	NUM
fcis-31608	123	31	945.70	945.70	NUM
fcis-31608	123	32	920.22	920.22	NUM
fcis-31608	123	33	455.00	455.00	NUM
fcis-31608	123	34	405.39	405.39	NUM
fcis-31608	123	35	843.90	843.90	NUM
fcis-31608	123	36	100	100	NUM
fcis-31608	123	37	170	170	NUM
fcis-31608	123	38	176.94	176.94	NUM
fcis-31608	123	39	2	2	NUM
fcis-31608	123	40	1031.63	1031.63	NUM
fcis-31608	123	41	1042.67	1042.67	NUM
fcis-31608	123	42	479.87	479.87	NUM
fcis-31608	123	43	460.15	460.15	NUM
fcis-31608	123	44	1010.38	1010.38	NUM
fcis-31608	123	45	92	92	NUM
fcis-31608	123	46	204	204	NUM
fcis-31608	124	1	200.47	200.47	NUM
fcis-31608	124	2	3	3	NUM
fcis-31608	124	3	1042.35	1042.35	NUM
fcis-31608	124	4	1131.92	1131.92	NUM
fcis-31608	124	5	518.21	518.21	NUM
fcis-31608	124	6	481.03	481.03	NUM
fcis-31608	124	7	1106.04	1106.04	NUM
fcis-31608	124	8	108	108	NUM
fcis-31608	124	9	188	188	NUM
fcis-31608	124	10	193.49	193.49	NUM
fcis-31608	124	11	4	4	NUM
fcis-31608	124	12	989.10	989.10	NUM
fcis-31608	124	13	1014.06	1014.06	NUM
fcis-31608	124	14	494.38	494.38	NUM
fcis-31608	124	15	470.27	470.27	NUM
fcis-31608	124	16	1013.53	1013.53	NUM
fcis-31608	124	17	118	118	NUM
fcis-31608	124	18	192	192	NUM
fcis-31608	124	19	132.66	132.66	NUM
fcis-31608	124	20	5	5	NUM
fcis-31608	124	21	1049.19	1049.19	NUM
fcis-31608	124	22	1138.19	1138.19	NUM
fcis-31608	124	23	534.07	534.07	NUM
fcis-31608	124	24	519.02	519.02	NUM
fcis-31608	124	25	1170.03	1170.03	NUM
fcis-31608	124	26	114	114	NUM
fcis-31608	124	27	170	170	NUM
fcis-31608	124	28	159.61	159.61	NUM
fcis-31608	124	29	6	6	NUM
fcis-31608	124	30	949.12	949.12	NUM
fcis-31608	124	31	1021.41	1021.41	NUM
fcis-31608	124	32	444.09	444.09	NUM
fcis-31608	124	33	435.33	435.33	NUM
fcis-31608	124	34	914.26	914.26	NUM
fcis-31608	124	35	102	102	NUM
fcis-31608	124	36	183	183	NUM
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fcis-31608	124	38	7	7	NUM
fcis-31608	124	39	930.31	930.31	NUM
fcis-31608	124	40	924.11	924.11	NUM
fcis-31608	124	41	480.01	480.01	NUM
fcis-31608	124	42	483.26	483.26	NUM
fcis-31608	124	43	964.00	964.00	NUM
fcis-31608	124	44	102	102	NUM
fcis-31608	124	45	148	148	NUM
fcis-31608	124	46	133.64	133.64	NUM
fcis-31608	124	47	8	8	NUM
fcis-31608	124	48	936.23	936.23	NUM
fcis-31608	124	49	1045.01	1045.01	NUM
fcis-31608	124	50	500.68	500.68	NUM
fcis-31608	124	51	459.97	459.97	NUM
fcis-31608	124	52	979.37	979.37	NUM
fcis-31608	124	53	134	134	NUM
fcis-31608	124	54	156	156	NUM
fcis-31608	124	55	149.59	149.59	NUM
fcis-31608	124	56	9	9	NUM
fcis-31608	124	57	1117.40	1117.40	NUM
fcis-31608	124	58	1160.13	1160.13	NUM
fcis-31608	124	59	506.25	506.25	NUM
fcis-31608	124	60	532.01	532.01	NUM
fcis-31608	124	61	984.73	984.73	NUM
fcis-31608	124	62	120	120	NUM
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fcis-31608	124	65	10	10	NUM
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fcis-31608	124	69	432.02	432.02	NUM
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fcis-31608	124	71	112	112	NUM
fcis-31608	124	72	186	186	NUM
fcis-31608	124	73	192.27	192.27	NUM
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fcis-31608	124	84	project	project	NOUN
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fcis-31608	124	87	-	-	PUNCT
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fcis-31608	124	91	-	-	PUNCT
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fcis-31608	125	3	1	1	NUM
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fcis-31608	125	10	organization	organization	NOUN
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fcis-31608	125	20	.	.	PUNCT
fcis-31608	126	1	oecd	oecd	PROPN
fcis-31608	126	2	-	-	PUNCT
fcis-31608	126	3	fao	fao	ADJ
fcis-31608	126	4	agricultural	agricultural	ADJ
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fcis-31608	126	7	-	-	SYM
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fcis-31608	128	3	-	-	SYM
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fcis-31608	128	5	-	-	SYM
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fcis-31608	134	7	):	):	PUNCT
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fcis-31608	150	11	s	s	PROPN
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fcis-31608	150	13	et	et	PROPN
fcis-31608	150	14	al	al	PROPN
fcis-31608	150	15	.	.	PROPN
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fcis-31608	150	19	beef	beef	NOUN
fcis-31608	150	20	cattle	cattle	NOUN
fcis-31608	150	21	body	body	NOUN
fcis-31608	150	22	size	size	NOUN
fcis-31608	150	23	via	via	ADP
fcis-31608	150	24	key	key	ADJ
fcis-31608	150	25	point	point	NOUN
fcis-31608	150	26	detection	detection	NOUN
fcis-31608	150	27	and	and	CCONJ
fcis-31608	150	28	monocular	monocular	ADJ
fcis-31608	150	29	depth	depth	NOUN
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fcis-31608	150	31	[	[	X
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fcis-31608	150	34	.	.	PUNCT
fcis-31608	151	1	expert	expert	NOUN
fcis-31608	151	2	systems	system	NOUN
fcis-31608	151	3	with	with	ADP
fcis-31608	151	4	applications	application	NOUN
fcis-31608	151	5	,	,	PUNCT
fcis-31608	151	6	2024	2024	NUM
fcis-31608	151	7	,	,	PUNCT
fcis-31608	151	8	244	244	NUM
fcis-31608	151	9	:	:	PUNCT
fcis-31608	151	10	123042	123042	NUM
fcis-31608	151	11	.	.	PUNCT
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fcis-31608	152	2	11	11	NUM
fcis-31608	152	3	]	]	X
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fcis-31608	152	5	s.	s.	PROPN
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fcis-31608	152	8	body	body	NOUN
fcis-31608	152	9	size	size	NOUN
fcis-31608	152	10	and	and	CCONJ
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fcis-31608	152	12	prediction	prediction	NOUN
fcis-31608	152	13	methods	method	NOUN
fcis-31608	152	14	of	of	ADP
fcis-31608	152	15	jinan	jinan	PROPN
fcis-31608	152	16	cattle	cattle	NOUN
fcis-31608	152	17	based	base	VERB
fcis-31608	152	18	on	on	ADP
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fcis-31608	152	21	[	[	X
fcis-31608	152	22	d	d	X
fcis-31608	152	23	]	]	X
fcis-31608	152	24	.	.	PUNCT
fcis-31608	153	1	taiyuan	taiyuan	PROPN
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fcis-31608	153	4	agricultural	agricultural	PROPN
fcis-31608	153	5	university	university	PROPN
fcis-31608	153	6	,	,	PUNCT
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fcis-31608	153	8	.	.	PUNCT
fcis-31608	154	1	[	[	X
fcis-31608	154	2	12	12	NUM
fcis-31608	154	3	]	]	X
fcis-31608	154	4	peng	peng	PROPN
fcis-31608	154	5	z	z	PROPN
fcis-31608	154	6	y.	y.	PROPN
fcis-31608	154	7	research	research	PROPN
fcis-31608	154	8	on	on	ADP
fcis-31608	154	9	non	non	ADJ
fcis-31608	154	10	-	-	ADJ
fcis-31608	154	11	contact	contact	ADJ
fcis-31608	154	12	yak	yak	NOUN
fcis-31608	154	13	weight	weight	NOUN
fcis-31608	154	14	measurement	measurement	NOUN
fcis-31608	154	15	method	method	NOUN
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fcis-31608	154	17	on	on	ADP
fcis-31608	154	18	deep	deep	ADJ
fcis-31608	154	19	learning	learning	NOUN
fcis-31608	155	1	[	[	X
fcis-31608	155	2	d	d	X
fcis-31608	155	3	]	]	X
fcis-31608	155	4	.	.	PUNCT
fcis-31608	156	1	ya'an	ya'an	NOUN
fcis-31608	156	2	:	:	PUNCT
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fcis-31608	156	4	agricultural	agricultural	PROPN
fcis-31608	156	5	university	university	PROPN
fcis-31608	156	6	,	,	PUNCT
fcis-31608	156	7	2024	2024	NUM
fcis-31608	156	8	.	.	PUNCT
fcis-31608	157	1	[	[	X
fcis-31608	157	2	13	13	NUM
fcis-31608	157	3	]	]	PUNCT
fcis-31608	157	4	lan	lan	PROPN
fcis-31608	157	5	l	l	PROPN
fcis-31608	157	6	b.	b.	PROPN
fcis-31608	157	7	research	research	NOUN
fcis-31608	157	8	on	on	ADP
fcis-31608	157	9	cattle	cattle	NOUN
fcis-31608	157	10	body	body	NOUN
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fcis-31608	157	12	and	and	CCONJ
fcis-31608	157	13	weight	weight	NOUN
fcis-31608	157	14	estimation	estimation	NOUN
fcis-31608	157	15	algorithms	algorithm	NOUN
fcis-31608	157	16	based	base	VERB
fcis-31608	157	17	on	on	ADP
fcis-31608	157	18	machine	machine	NOUN
fcis-31608	157	19	vision	vision	NOUN
fcis-31608	157	20	[	[	X
fcis-31608	157	21	d	d	X
fcis-31608	157	22	]	]	X
fcis-31608	157	23	.	.	PUNCT
fcis-31608	158	1	hangzhou	hangzhou	PROPN
fcis-31608	158	2	:	:	PUNCT
fcis-31608	158	3	hangzhou	hangzhou	PROPN
fcis-31608	158	4	dianzi	dianzi	PROPN
fcis-31608	158	5	university	university	PROPN
fcis-31608	158	6	,	,	PUNCT
fcis-31608	158	7	2024	2024	NUM
fcis-31608	158	8	.	.	PUNCT
fcis-31608	159	1	[	[	X
fcis-31608	159	2	14	14	NUM
fcis-31608	159	3	]	]	PUNCT
fcis-31608	159	4	elkhrachy	elkhrachy	ADJ
fcis-31608	159	5	i.	i.	PROPN
fcis-31608	159	6	3d	3d	PROPN
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fcis-31608	159	8	from	from	ADP
fcis-31608	159	9	2d	2d	NUM
fcis-31608	159	10	dimensional	dimensional	ADJ
fcis-31608	159	11	images	image	NOUN
fcis-31608	159	12	using	use	VERB
fcis-31608	159	13	structure	structure	NOUN
fcis-31608	159	14	from	from	ADP
fcis-31608	159	15	motion	motion	NOUN
fcis-31608	159	16	algorithms	algorithm	NOUN
fcis-31608	159	17	[	[	X
fcis-31608	159	18	j	j	X
fcis-31608	159	19	]	]	X
fcis-31608	159	20	.	.	PUNCT
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fcis-31608	160	2	,	,	PUNCT
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fcis-31608	160	4	,	,	PUNCT
fcis-31608	160	5	14(9	14(9	NUM
fcis-31608	160	6	):	):	PUNCT
fcis-31608	160	7	5399	5399	NUM
fcis-31608	160	8	.	.	PUNCT