id	sid	tid	token	lemma	pos
cana-5088	1	1	communications	communication	NOUN
cana-5088	1	2	on	on	ADP
cana-5088	1	3	applied	apply	VERB
cana-5088	1	4	nonlinear	nonlinear	ADJ
cana-5088	1	5	analysis	analysis	NOUN
cana-5088	1	6	issn	issn	NOUN
cana-5088	1	7	:	:	PUNCT
cana-5088	1	8	1074	1074	NUM
cana-5088	1	9	-	-	PUNCT
cana-5088	1	10	133x	133x	NUM
cana-5088	1	11	vol	vol	NOUN
cana-5088	1	12	32	32	NUM
cana-5088	1	13	no	no	NOUN
cana-5088	1	14	.	.	PUNCT
cana-5088	2	1	icmasd	icmasd	NOUN
cana-5088	2	2	(	(	PUNCT
cana-5088	2	3	2025	2025	NUM
cana-5088	2	4	)	)	PUNCT
cana-5088	2	5	587	587	NUM
cana-5088	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	2	7	optimizing	optimize	VERB
cana-5088	2	8	solid	solid	ADJ
cana-5088	2	9	waste	waste	NOUN
cana-5088	2	10	classification	classification	NOUN
cana-5088	2	11	with	with	ADP
cana-5088	2	12	deep	deep	ADJ
cana-5088	2	13	learning	learning	NOUN
cana-5088	2	14	:	:	PUNCT
cana-5088	2	15	a	a	DET
cana-5088	2	16	study	study	NOUN
cana-5088	2	17	on	on	ADP
cana-5088	2	18	the	the	DET
cana-5088	2	19	effectiveness	effectiveness	NOUN
cana-5088	2	20	of	of	ADP
cana-5088	2	21	pretrained	pretraine	VERB
cana-5088	2	22	models	model	NOUN
cana-5088	2	23	shruti	shruti	PROPN
cana-5088	2	24	handa1	handa1	PROPN
cana-5088	2	25	,	,	PUNCT
cana-5088	2	26	mandeep	mandeep	PROPN
cana-5088	2	27	kaur1	kaur1	PROPN
cana-5088	3	1	1department	1department	NUM
cana-5088	3	2	of	of	ADP
cana-5088	3	3	computer	computer	NOUN
cana-5088	3	4	applications	application	NOUN
cana-5088	3	5	,	,	PUNCT
cana-5088	4	1	ct	ct	PROPN
cana-5088	4	2	university	university	NOUN
cana-5088	4	3	,	,	PUNCT
cana-5088	4	4	ferozepur	ferozepur	NOUN
cana-5088	4	5	road	road	NOUN
cana-5088	4	6	,	,	PUNCT
cana-5088	4	7	sidhwan	sidhwan	NOUN
cana-5088	4	8	khurd	khurd	NOUN
cana-5088	4	9	,	,	PUNCT
cana-5088	4	10	ludhiana	ludhiana	PROPN
cana-5088	4	11	,	,	PUNCT
cana-5088	4	12	punjab	punjab	PROPN
cana-5088	4	13	142024	142024	NUM
cana-5088	4	14	,	,	PUNCT
cana-5088	4	15	india	india	PROPN
cana-5088	4	16	corresponding	corresponding	PROPN
cana-5088	4	17	author	author	PROPN
cana-5088	4	18	’s	’s	PART
cana-5088	4	19	email	email	NOUN
cana-5088	5	1	i	i	PROPN
cana-5088	5	2	d	d	PROPN
cana-5088	5	3	:	:	PUNCT
cana-5088	5	4	shruti133h@gmail.com	shruti133h@gmail.com	X
cana-5088	5	5	article	article	NOUN
cana-5088	5	6	history	history	NOUN
cana-5088	5	7	:	:	PUNCT
cana-5088	5	8	received	receive	VERB
cana-5088	5	9	:	:	PUNCT
cana-5088	5	10	12	12	NUM
cana-5088	5	11	-	-	SYM
cana-5088	5	12	12	12	NUM
cana-5088	5	13	-	-	PUNCT
cana-5088	5	14	2024	2024	NUM
cana-5088	5	15	revised	revise	VERB
cana-5088	5	16	:	:	PUNCT
cana-5088	5	17	25	25	NUM
cana-5088	5	18	-	-	PUNCT
cana-5088	5	19	01	01	NUM
cana-5088	5	20	-	-	PUNCT
cana-5088	5	21	2025	2025	NUM
cana-5088	5	22	accepted	accept	VERB
cana-5088	5	23	:	:	PUNCT
cana-5088	5	24	05	05	NUM
cana-5088	5	25	-	-	PUNCT
cana-5088	5	26	02	02	NUM
cana-5088	5	27	-	-	PUNCT
cana-5088	5	28	2025	2025	NUM
cana-5088	5	29	abstract	abstract	NOUN
cana-5088	5	30	:	:	PUNCT
cana-5088	5	31	the	the	DET
cana-5088	5	32	rapid	rapid	ADJ
cana-5088	5	33	growth	growth	NOUN
cana-5088	5	34	in	in	ADP
cana-5088	5	35	population	population	NOUN
cana-5088	5	36	,	,	PUNCT
cana-5088	5	37	urbanization	urbanization	NOUN
cana-5088	5	38	,	,	PUNCT
cana-5088	5	39	and	and	CCONJ
cana-5088	5	40	economic	economic	ADJ
cana-5088	5	41	activities	activity	NOUN
cana-5088	5	42	has	have	AUX
cana-5088	5	43	led	lead	VERB
cana-5088	5	44	to	to	ADP
cana-5088	5	45	a	a	DET
cana-5088	5	46	significant	significant	ADJ
cana-5088	5	47	increase	increase	NOUN
cana-5088	5	48	in	in	ADP
cana-5088	5	49	solid	solid	ADJ
cana-5088	5	50	waste	waste	NOUN
cana-5088	5	51	generation	generation	NOUN
cana-5088	5	52	,	,	PUNCT
cana-5088	5	53	raising	raise	VERB
cana-5088	5	54	critical	critical	ADJ
cana-5088	5	55	environmental	environmental	ADJ
cana-5088	5	56	concerns	concern	NOUN
cana-5088	5	57	.	.	PUNCT
cana-5088	6	1	proper	proper	ADJ
cana-5088	6	2	disposal	disposal	NOUN
cana-5088	6	3	and	and	CCONJ
cana-5088	6	4	recycling	recycling	NOUN
cana-5088	6	5	of	of	ADP
cana-5088	6	6	municipal	municipal	ADJ
cana-5088	6	7	solid	solid	ADJ
cana-5088	6	8	waste	waste	NOUN
cana-5088	6	9	are	be	AUX
cana-5088	6	10	vital	vital	ADJ
cana-5088	6	11	for	for	ADP
cana-5088	6	12	sustainable	sustainable	ADJ
cana-5088	6	13	development	development	NOUN
cana-5088	6	14	,	,	PUNCT
cana-5088	6	15	aligning	align	VERB
cana-5088	6	16	with	with	ADP
cana-5088	6	17	the	the	DET
cana-5088	6	18	united	united	PROPN
cana-5088	6	19	nations	nations	PROPN
cana-5088	6	20	sustainable	sustainable	ADJ
cana-5088	6	21	development	development	NOUN
cana-5088	6	22	goals	goal	NOUN
cana-5088	6	23	.	.	PUNCT
cana-5088	7	1	previous	previous	ADJ
cana-5088	7	2	studies	study	NOUN
cana-5088	7	3	in	in	ADP
cana-5088	7	4	this	this	DET
cana-5088	7	5	domain	domain	NOUN
cana-5088	7	6	faced	face	VERB
cana-5088	7	7	challenges	challenge	NOUN
cana-5088	7	8	such	such	ADJ
cana-5088	7	9	as	as	ADP
cana-5088	7	10	the	the	DET
cana-5088	7	11	unavailability	unavailability	NOUN
cana-5088	7	12	of	of	ADP
cana-5088	7	13	real	real	ADJ
cana-5088	7	14	-	-	PUNCT
cana-5088	7	15	world	world	NOUN
cana-5088	7	16	waste	waste	NOUN
cana-5088	7	17	data	datum	NOUN
cana-5088	7	18	and	and	CCONJ
cana-5088	7	19	insufficient	insufficient	ADJ
cana-5088	7	20	model	model	NOUN
cana-5088	7	21	generalization	generalization	NOUN
cana-5088	7	22	for	for	ADP
cana-5088	7	23	diverse	diverse	ADJ
cana-5088	7	24	waste	waste	NOUN
cana-5088	7	25	categories	category	NOUN
cana-5088	7	26	.	.	PUNCT
cana-5088	8	1	this	this	DET
cana-5088	8	2	study	study	NOUN
cana-5088	8	3	explores	explore	VERB
cana-5088	8	4	the	the	DET
cana-5088	8	5	optimization	optimization	NOUN
cana-5088	8	6	of	of	ADP
cana-5088	8	7	solid	solid	ADJ
cana-5088	8	8	waste	waste	NOUN
cana-5088	8	9	classification	classification	NOUN
cana-5088	8	10	by	by	ADP
cana-5088	8	11	employing	employ	VERB
cana-5088	8	12	transfer	transfer	NOUN
cana-5088	8	13	learning	learning	NOUN
cana-5088	8	14	with	with	ADP
cana-5088	8	15	pretrained	pretraine	VERB
cana-5088	8	16	convolutional	convolutional	ADJ
cana-5088	8	17	neural	neural	ADJ
cana-5088	8	18	network	network	NOUN
cana-5088	8	19	models	model	NOUN
cana-5088	8	20	to	to	PART
cana-5088	8	21	address	address	VERB
cana-5088	8	22	these	these	DET
cana-5088	8	23	limitations	limitation	NOUN
cana-5088	8	24	.	.	PUNCT
cana-5088	9	1	the	the	DET
cana-5088	9	2	study	study	NOUN
cana-5088	9	3	utilizes	utilize	VERB
cana-5088	9	4	the	the	DET
cana-5088	9	5	realwaste	realwaste	ADJ
cana-5088	9	6	dataset	dataset	NOUN
cana-5088	9	7	,	,	PUNCT
cana-5088	9	8	consisting	consist	VERB
cana-5088	9	9	of	of	ADP
cana-5088	9	10	4,752	4,752	NUM
cana-5088	9	11	images	image	NOUN
cana-5088	9	12	categorized	categorize	VERB
cana-5088	9	13	into	into	ADP
cana-5088	9	14	nine	nine	NUM
cana-5088	9	15	waste	waste	NOUN
cana-5088	9	16	classes	class	NOUN
cana-5088	9	17	(	(	PUNCT
cana-5088	9	18	paper	paper	NOUN
cana-5088	9	19	,	,	PUNCT
cana-5088	9	20	plastic	plastic	NOUN
cana-5088	9	21	,	,	PUNCT
cana-5088	9	22	glass	glass	NOUN
cana-5088	9	23	,	,	PUNCT
cana-5088	9	24	vegetation	vegetation	NOUN
cana-5088	9	25	,	,	PUNCT
cana-5088	9	26	food	food	NOUN
cana-5088	9	27	organics	organic	NOUN
cana-5088	9	28	,	,	PUNCT
cana-5088	9	29	cardboard	cardboard	NOUN
cana-5088	9	30	,	,	PUNCT
cana-5088	9	31	textile	textile	NOUN
cana-5088	9	32	trash	trash	NOUN
cana-5088	9	33	,	,	PUNCT
cana-5088	9	34	metal	metal	NOUN
cana-5088	9	35	,	,	PUNCT
cana-5088	9	36	and	and	CCONJ
cana-5088	9	37	miscellaneous	miscellaneous	ADJ
cana-5088	9	38	trash	trash	NOUN
cana-5088	9	39	)	)	PUNCT
cana-5088	9	40	,	,	PUNCT
cana-5088	9	41	to	to	PART
cana-5088	9	42	assess	assess	VERB
cana-5088	9	43	the	the	DET
cana-5088	9	44	performance	performance	NOUN
cana-5088	9	45	of	of	ADP
cana-5088	9	46	three	three	NUM
cana-5088	9	47	pre	pre	ADJ
cana-5088	9	48	-	-	ADJ
cana-5088	9	49	trained	train	VERB
cana-5088	9	50	convolutional	convolutional	ADJ
cana-5088	9	51	neural	neural	ADJ
cana-5088	9	52	network	network	NOUN
cana-5088	9	53	models	model	NOUN
cana-5088	9	54	:	:	PUNCT
cana-5088	9	55	resnet50	resnet50	NOUN
cana-5088	9	56	,	,	PUNCT
cana-5088	9	57	densenet121	densenet121	PROPN
cana-5088	9	58	,	,	PUNCT
cana-5088	9	59	and	and	CCONJ
cana-5088	9	60	efficientnet	efficientnet	NOUN
cana-5088	9	61	-	-	PUNCT
cana-5088	9	62	b0	b0	NOUN
cana-5088	9	63	.	.	PUNCT
cana-5088	10	1	originally	originally	ADV
cana-5088	10	2	trained	train	VERB
cana-5088	10	3	on	on	ADP
cana-5088	10	4	the	the	DET
cana-5088	10	5	imagenet	imagenet	NOUN
cana-5088	10	6	dataset	dataset	NOUN
cana-5088	10	7	,	,	PUNCT
cana-5088	10	8	these	these	DET
cana-5088	10	9	models	model	NOUN
cana-5088	10	10	were	be	AUX
cana-5088	10	11	fine	fine	ADV
cana-5088	10	12	-	-	PUNCT
cana-5088	10	13	tuned	tune	VERB
cana-5088	10	14	to	to	PART
cana-5088	10	15	classify	classify	VERB
cana-5088	10	16	waste	waste	NOUN
cana-5088	10	17	materials	material	NOUN
cana-5088	10	18	.	.	PUNCT
cana-5088	11	1	the	the	DET
cana-5088	11	2	resnet50	resnet50	NOUN
cana-5088	11	3	model	model	NOUN
cana-5088	11	4	achieved	achieve	VERB
cana-5088	11	5	an	an	DET
cana-5088	11	6	impressive	impressive	ADJ
cana-5088	11	7	training	training	NOUN
cana-5088	11	8	accuracy	accuracy	NOUN
cana-5088	11	9	of	of	ADP
cana-5088	11	10	100	100	NUM
cana-5088	11	11	%	%	NOUN
cana-5088	11	12	and	and	CCONJ
cana-5088	11	13	a	a	DET
cana-5088	11	14	validation	validation	NOUN
cana-5088	11	15	accuracy	accuracy	NOUN
cana-5088	11	16	of	of	ADP
cana-5088	11	17	92.24	92.24	NUM
cana-5088	11	18	%	%	NOUN
cana-5088	11	19	,	,	PUNCT
cana-5088	11	20	followed	follow	VERB
cana-5088	11	21	by	by	ADP
cana-5088	11	22	densenet121	densenet121	PROPN
cana-5088	11	23	with	with	ADP
cana-5088	11	24	a	a	DET
cana-5088	11	25	training	training	NOUN
cana-5088	11	26	accuracy	accuracy	NOUN
cana-5088	11	27	of	of	ADP
cana-5088	11	28	99.99	99.99	NUM
cana-5088	11	29	%	%	NOUN
cana-5088	11	30	and	and	CCONJ
cana-5088	11	31	a	a	DET
cana-5088	11	32	validation	validation	NOUN
cana-5088	11	33	accuracy	accuracy	NOUN
cana-5088	11	34	of	of	ADP
cana-5088	11	35	91.82	91.82	NUM
cana-5088	11	36	%	%	NOUN
cana-5088	11	37	,	,	PUNCT
cana-5088	11	38	and	and	CCONJ
cana-5088	11	39	efficientnet	efficientnet	NOUN
cana-5088	11	40	-	-	PUNCT
cana-5088	11	41	b0	b0	NOUN
cana-5088	11	42	with	with	ADP
cana-5088	11	43	a	a	DET
cana-5088	11	44	training	training	NOUN
cana-5088	11	45	accuracy	accuracy	NOUN
cana-5088	11	46	of	of	ADP
cana-5088	11	47	99.83	99.83	NUM
cana-5088	11	48	%	%	NOUN
cana-5088	11	49	and	and	CCONJ
cana-5088	11	50	a	a	DET
cana-5088	11	51	validation	validation	NOUN
cana-5088	11	52	accuracy	accuracy	NOUN
cana-5088	11	53	of	of	ADP
cana-5088	11	54	91.19	91.19	NUM
cana-5088	11	55	%	%	NOUN
cana-5088	11	56	.	.	PUNCT
cana-5088	12	1	among	among	ADP
cana-5088	12	2	the	the	DET
cana-5088	12	3	evaluated	evaluate	VERB
cana-5088	12	4	models	model	NOUN
cana-5088	12	5	,	,	PUNCT
cana-5088	12	6	densenet121	densenet121	PROPN
cana-5088	12	7	achieved	achieve	VERB
cana-5088	12	8	the	the	DET
cana-5088	12	9	highest	high	ADJ
cana-5088	12	10	test	test	NOUN
cana-5088	12	11	accuracy	accuracy	NOUN
cana-5088	12	12	of	of	ADP
cana-5088	12	13	94.33	94.33	NUM
cana-5088	12	14	%	%	NOUN
cana-5088	12	15	,	,	PUNCT
cana-5088	12	16	followed	follow	VERB
cana-5088	12	17	by	by	ADP
cana-5088	12	18	resnet50	resnet50	NOUN
cana-5088	12	19	at	at	ADP
cana-5088	12	20	91.82	91.82	NUM
cana-5088	12	21	%	%	NOUN
cana-5088	12	22	and	and	CCONJ
cana-5088	12	23	efficientnet	efficientnet	NOUN
cana-5088	12	24	-	-	PUNCT
cana-5088	12	25	b0	b0	NOUN
cana-5088	12	26	at	at	ADP
cana-5088	12	27	91.4	91.4	NUM
cana-5088	12	28	%	%	NOUN
cana-5088	12	29	,	,	PUNCT
cana-5088	12	30	demonstrating	demonstrate	VERB
cana-5088	12	31	the	the	DET
cana-5088	12	32	superior	superior	ADJ
cana-5088	12	33	performance	performance	NOUN
cana-5088	12	34	of	of	ADP
cana-5088	12	35	densenet121	densenet121	PROPN
cana-5088	12	36	in	in	ADP
cana-5088	12	37	the	the	DET
cana-5088	12	38	waste	waste	NOUN
cana-5088	12	39	classification	classification	NOUN
cana-5088	12	40	task	task	NOUN
cana-5088	12	41	.	.	PUNCT
cana-5088	13	1	these	these	DET
cana-5088	13	2	results	result	NOUN
cana-5088	13	3	underscore	underscore	VERB
cana-5088	13	4	the	the	DET
cana-5088	13	5	capability	capability	NOUN
cana-5088	13	6	of	of	ADP
cana-5088	13	7	deep	deep	ADJ
cana-5088	13	8	learning	learning	NOUN
cana-5088	13	9	to	to	PART
cana-5088	13	10	automate	automate	VERB
cana-5088	13	11	waste	waste	NOUN
cana-5088	13	12	categorization	categorization	NOUN
cana-5088	13	13	with	with	ADP
cana-5088	13	14	high	high	ADJ
cana-5088	13	15	precision	precision	NOUN
cana-5088	13	16	.	.	PUNCT
cana-5088	14	1	the	the	DET
cana-5088	14	2	research	research	NOUN
cana-5088	14	3	findings	finding	NOUN
cana-5088	14	4	highlight	highlight	VERB
cana-5088	14	5	the	the	DET
cana-5088	14	6	potential	potential	NOUN
cana-5088	14	7	of	of	ADP
cana-5088	14	8	transfer	transfer	NOUN
cana-5088	14	9	learning	learning	NOUN
cana-5088	14	10	with	with	ADP
cana-5088	14	11	pre	pre	ADJ
cana-5088	14	12	-	-	ADJ
cana-5088	14	13	trained	train	VERB
cana-5088	14	14	convolutional	convolutional	ADJ
cana-5088	14	15	neural	neural	ADJ
cana-5088	14	16	networks	network	NOUN
cana-5088	14	17	for	for	ADP
cana-5088	14	18	reliable	reliable	ADJ
cana-5088	14	19	waste	waste	NOUN
cana-5088	14	20	classification	classification	NOUN
cana-5088	14	21	across	across	ADP
cana-5088	14	22	multiple	multiple	ADJ
cana-5088	14	23	categories	category	NOUN
cana-5088	14	24	,	,	PUNCT
cana-5088	14	25	fostering	foster	VERB
cana-5088	14	26	efficient	efficient	ADJ
cana-5088	14	27	recycling	recycling	NOUN
cana-5088	14	28	systems	system	NOUN
cana-5088	14	29	and	and	CCONJ
cana-5088	14	30	contributing	contribute	VERB
cana-5088	14	31	to	to	ADP
cana-5088	14	32	a	a	DET
cana-5088	14	33	circular	circular	ADJ
cana-5088	14	34	economy	economy	NOUN
cana-5088	14	35	,	,	PUNCT
cana-5088	14	36	thereby	thereby	ADV
cana-5088	14	37	supporting	support	VERB
cana-5088	14	38	global	global	ADJ
cana-5088	14	39	sustainability	sustainability	NOUN
cana-5088	14	40	efforts	effort	NOUN
cana-5088	14	41	.	.	PUNCT
cana-5088	15	1	keywords	keyword	NOUN
cana-5088	15	2	:	:	PUNCT
cana-5088	15	3	convolutional	convolutional	ADJ
cana-5088	15	4	neural	neural	ADJ
cana-5088	15	5	network	network	NOUN
cana-5088	15	6	,	,	PUNCT
cana-5088	15	7	transfer	transfer	NOUN
cana-5088	15	8	learning	learning	NOUN
cana-5088	15	9	,	,	PUNCT
cana-5088	15	10	solid	solid	ADJ
cana-5088	15	11	waste	waste	NOUN
cana-5088	15	12	classification	classification	NOUN
cana-5088	15	13	,	,	PUNCT
cana-5088	15	14	deep	deep	ADJ
cana-5088	15	15	learning	learning	NOUN
cana-5088	15	16	.	.	PUNCT
cana-5088	16	1	1	1	X
cana-5088	16	2	.	.	X
cana-5088	16	3	introduction	introduction	NOUN
cana-5088	16	4	solid	solid	ADJ
cana-5088	16	5	waste	waste	NOUN
cana-5088	16	6	encompasses	encompass	VERB
cana-5088	16	7	a	a	DET
cana-5088	16	8	wide	wide	ADJ
cana-5088	16	9	variety	variety	NOUN
cana-5088	16	10	of	of	ADP
cana-5088	16	11	waste	waste	NOUN
cana-5088	16	12	types	type	NOUN
cana-5088	16	13	,	,	PUNCT
cana-5088	16	14	including	include	VERB
cana-5088	16	15	household	household	NOUN
cana-5088	16	16	waste	waste	NOUN
cana-5088	16	17	,	,	PUNCT
cana-5088	16	18	industrial	industrial	ADJ
cana-5088	16	19	waste	waste	NOUN
cana-5088	16	20	,	,	PUNCT
cana-5088	16	21	biomedical	biomedical	ADJ
cana-5088	16	22	waste	waste	NOUN
cana-5088	16	23	,	,	PUNCT
cana-5088	16	24	agricultural	agricultural	ADJ
cana-5088	16	25	waste	waste	NOUN
cana-5088	16	26	,	,	PUNCT
cana-5088	16	27	and	and	CCONJ
cana-5088	16	28	electronic	electronic	ADJ
cana-5088	16	29	waste	waste	NOUN
cana-5088	16	30	.	.	PUNCT
cana-5088	17	1	municipal	municipal	ADJ
cana-5088	17	2	solid	solid	ADJ
cana-5088	17	3	waste	waste	NOUN
cana-5088	17	4	(	(	PUNCT
cana-5088	17	5	msw	msw	NOUN
cana-5088	17	6	)	)	PUNCT
cana-5088	17	7	,	,	PUNCT
cana-5088	17	8	in	in	ADP
cana-5088	17	9	particular	particular	ADJ
cana-5088	17	10	,	,	PUNCT
cana-5088	17	11	consists	consist	VERB
cana-5088	17	12	of	of	ADP
cana-5088	17	13	everyday	everyday	ADJ
cana-5088	17	14	items	item	NOUN
cana-5088	17	15	such	such	ADJ
cana-5088	17	16	as	as	ADP
cana-5088	17	17	paper	paper	NOUN
cana-5088	17	18	,	,	PUNCT
cana-5088	17	19	plastic	plastic	NOUN
cana-5088	17	20	,	,	PUNCT
cana-5088	17	21	glass	glass	NOUN
cana-5088	17	22	,	,	PUNCT
cana-5088	17	23	vegetation	vegetation	NOUN
cana-5088	17	24	,	,	PUNCT
cana-5088	17	25	food	food	NOUN
cana-5088	17	26	organics	organic	NOUN
cana-5088	17	27	,	,	PUNCT
cana-5088	17	28	cardboard	cardboard	NOUN
cana-5088	17	29	,	,	PUNCT
cana-5088	17	30	metals	metal	NOUN
cana-5088	17	31	,	,	PUNCT
cana-5088	17	32	textiles	textile	NOUN
cana-5088	17	33	,	,	PUNCT
cana-5088	17	34	and	and	CCONJ
cana-5088	17	35	miscellaneous	miscellaneous	ADJ
cana-5088	17	36	trash	trash	NOUN
cana-5088	17	37	.	.	PUNCT
cana-5088	18	1	with	with	ADP
cana-5088	18	2	the	the	DET
cana-5088	18	3	increasing	increase	VERB
cana-5088	18	4	urbanization	urbanization	NOUN
cana-5088	18	5	and	and	CCONJ
cana-5088	18	6	industrialization	industrialization	NOUN
cana-5088	18	7	rate	rate	NOUN
cana-5088	18	8	,	,	PUNCT
cana-5088	18	9	solid	solid	ADJ
cana-5088	18	10	waste	waste	NOUN
cana-5088	18	11	generation	generation	NOUN
cana-5088	18	12	has	have	AUX
cana-5088	18	13	reached	reach	VERB
cana-5088	18	14	alarming	alarming	ADJ
cana-5088	18	15	levels	level	NOUN
cana-5088	18	16	,	,	PUNCT
cana-5088	18	17	posing	pose	VERB
cana-5088	18	18	significant	significant	ADJ
cana-5088	18	19	environmental	environmental	ADJ
cana-5088	18	20	and	and	CCONJ
cana-5088	18	21	societal	societal	ADJ
cana-5088	18	22	communications	communication	NOUN
cana-5088	18	23	on	on	ADP
cana-5088	18	24	applied	apply	VERB
cana-5088	18	25	nonlinear	nonlinear	ADJ
cana-5088	18	26	analysis	analysis	NOUN
cana-5088	18	27	issn	issn	NOUN
cana-5088	18	28	:	:	PUNCT
cana-5088	18	29	1074	1074	NUM
cana-5088	18	30	-	-	PUNCT
cana-5088	18	31	133x	133x	NUM
cana-5088	18	32	vol	vol	NOUN
cana-5088	18	33	32	32	NUM
cana-5088	18	34	no	no	NOUN
cana-5088	18	35	.	.	PUNCT
cana-5088	19	1	icmasd	icmasd	NOUN
cana-5088	19	2	(	(	PUNCT
cana-5088	19	3	2025	2025	NUM
cana-5088	19	4	)	)	PUNCT
cana-5088	19	5	588	588	NUM
cana-5088	19	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	19	7	challenges	challenge	NOUN
cana-5088	19	8	(	(	PUNCT
cana-5088	19	9	malik	malik	PROPN
cana-5088	19	10	et	et	PROPN
cana-5088	19	11	al	al	PROPN
cana-5088	19	12	.	.	PROPN
cana-5088	19	13	,	,	PUNCT
cana-5088	19	14	2022).msw	2022).msw	NUM
cana-5088	19	15	generation	generation	NOUN
cana-5088	19	16	is	be	AUX
cana-5088	19	17	projected	project	VERB
cana-5088	19	18	to	to	PART
cana-5088	19	19	increase	increase	VERB
cana-5088	19	20	dramatically	dramatically	ADV
cana-5088	19	21	from	from	ADP
cana-5088	19	22	2.3	2.3	NUM
cana-5088	19	23	billion	billion	NUM
cana-5088	19	24	tonnes	tonne	NOUN
cana-5088	19	25	in	in	ADP
cana-5088	19	26	2023	2023	NUM
cana-5088	19	27	to	to	ADP
cana-5088	19	28	3.8	3.8	NUM
cana-5088	19	29	billion	billion	NUM
cana-5088	19	30	tonnes	tonne	NOUN
cana-5088	19	31	by	by	ADP
cana-5088	19	32	2050	2050	NUM
cana-5088	19	33	,	,	PUNCT
cana-5088	19	34	highlighting	highlight	VERB
cana-5088	19	35	a	a	DET
cana-5088	19	36	pressing	press	VERB
cana-5088	19	37	global	global	ADJ
cana-5088	19	38	challenge	challenge	NOUN
cana-5088	19	39	.	.	PUNCT
cana-5088	20	1	despite	despite	SCONJ
cana-5088	20	2	this	this	DET
cana-5088	20	3	surge	surge	NOUN
cana-5088	20	4	,	,	PUNCT
cana-5088	20	5	only	only	ADV
cana-5088	20	6	19	19	NUM
cana-5088	20	7	%	%	NOUN
cana-5088	20	8	of	of	ADP
cana-5088	20	9	msw	msw	NOUN
cana-5088	20	10	is	be	AUX
cana-5088	20	11	recycled	recycle	VERB
cana-5088	20	12	worldwide	worldwide	ADV
cana-5088	20	13	,	,	PUNCT
cana-5088	20	14	reflecting	reflect	VERB
cana-5088	20	15	a	a	DET
cana-5088	20	16	critical	critical	ADJ
cana-5088	20	17	gap	gap	NOUN
cana-5088	20	18	in	in	ADP
cana-5088	20	19	effective	effective	ADJ
cana-5088	20	20	waste	waste	NOUN
cana-5088	20	21	management	management	NOUN
cana-5088	20	22	practices	practice	NOUN
cana-5088	20	23	(	(	PUNCT
cana-5088	20	24	iván	iván	NOUN
cana-5088	20	25	,	,	PUNCT
cana-5088	20	26	2024	2024	NUM
cana-5088	20	27	)	)	PUNCT
cana-5088	20	28	.	.	PUNCT
cana-5088	21	1	solid	solid	ADJ
cana-5088	21	2	waste	waste	NOUN
cana-5088	21	3	management	management	NOUN
cana-5088	21	4	is	be	AUX
cana-5088	21	5	a	a	DET
cana-5088	21	6	multifaceted	multifaceted	ADJ
cana-5088	21	7	problem	problem	NOUN
cana-5088	21	8	involving	involve	VERB
cana-5088	21	9	collection	collection	NOUN
cana-5088	21	10	,	,	PUNCT
cana-5088	21	11	segregation	segregation	NOUN
cana-5088	21	12	,	,	PUNCT
cana-5088	21	13	recycling	recycling	NOUN
cana-5088	21	14	,	,	PUNCT
cana-5088	21	15	and	and	CCONJ
cana-5088	21	16	disposal	disposal	NOUN
cana-5088	21	17	.	.	PUNCT
cana-5088	22	1	proper	proper	ADJ
cana-5088	22	2	management	management	NOUN
cana-5088	22	3	of	of	ADP
cana-5088	22	4	msw	msw	NOUN
cana-5088	22	5	has	have	AUX
cana-5088	22	6	become	become	VERB
cana-5088	22	7	a	a	DET
cana-5088	22	8	critical	critical	ADJ
cana-5088	22	9	challenge	challenge	NOUN
cana-5088	22	10	,	,	PUNCT
cana-5088	22	11	with	with	ADP
cana-5088	22	12	improper	improper	ADJ
cana-5088	22	13	waste	waste	NOUN
cana-5088	22	14	disposal	disposal	NOUN
cana-5088	22	15	leading	lead	VERB
cana-5088	22	16	to	to	ADP
cana-5088	22	17	environmental	environmental	ADJ
cana-5088	22	18	degradation	degradation	NOUN
cana-5088	22	19	,	,	PUNCT
cana-5088	22	20	resource	resource	NOUN
cana-5088	22	21	wastage	wastage	NOUN
cana-5088	22	22	,	,	PUNCT
cana-5088	22	23	and	and	CCONJ
cana-5088	22	24	health	health	NOUN
cana-5088	22	25	hazards	hazard	NOUN
cana-5088	22	26	.	.	PUNCT
cana-5088	23	1	unsustainable	unsustainable	ADJ
cana-5088	23	2	waste	waste	NOUN
cana-5088	23	3	management	management	NOUN
cana-5088	23	4	practices	practice	NOUN
cana-5088	23	5	like	like	ADP
cana-5088	23	6	open	open	ADJ
cana-5088	23	7	dumping	dumping	NOUN
cana-5088	23	8	and	and	CCONJ
cana-5088	23	9	incineration	incineration	NOUN
cana-5088	23	10	often	often	ADV
cana-5088	23	11	exacerbate	exacerbate	VERB
cana-5088	23	12	these	these	DET
cana-5088	23	13	effects	effect	NOUN
cana-5088	23	14	by	by	ADP
cana-5088	23	15	releasing	release	VERB
cana-5088	23	16	harmful	harmful	ADJ
cana-5088	23	17	pollutants	pollutant	NOUN
cana-5088	23	18	into	into	ADP
cana-5088	23	19	the	the	DET
cana-5088	23	20	environment	environment	NOUN
cana-5088	23	21	.	.	PUNCT
cana-5088	24	1	traditional	traditional	ADJ
cana-5088	24	2	waste	waste	NOUN
cana-5088	24	3	treatment	treatment	NOUN
cana-5088	24	4	methods	method	NOUN
cana-5088	24	5	,	,	PUNCT
cana-5088	24	6	including	include	VERB
cana-5088	24	7	landfilling	landfilling	NOUN
cana-5088	24	8	and	and	CCONJ
cana-5088	24	9	combustion	combustion	NOUN
cana-5088	24	10	,	,	PUNCT
cana-5088	24	11	while	while	SCONJ
cana-5088	24	12	reducing	reduce	VERB
cana-5088	24	13	visible	visible	ADJ
cana-5088	24	14	waste	waste	NOUN
cana-5088	24	15	,	,	PUNCT
cana-5088	24	16	often	often	ADV
cana-5088	24	17	contribute	contribute	VERB
cana-5088	24	18	to	to	ADP
cana-5088	24	19	greenhouse	greenhouse	NOUN
cana-5088	24	20	gas	gas	NOUN
cana-5088	24	21	emissions	emission	NOUN
cana-5088	24	22	and	and	CCONJ
cana-5088	24	23	leachate	leachate	NOUN
cana-5088	24	24	formation	formation	NOUN
cana-5088	24	25	,	,	PUNCT
cana-5088	24	26	undermining	undermine	VERB
cana-5088	24	27	efforts	effort	NOUN
cana-5088	24	28	to	to	PART
cana-5088	24	29	achieve	achieve	VERB
cana-5088	24	30	global	global	ADJ
cana-5088	24	31	sustainability	sustainability	NOUN
cana-5088	24	32	.	.	PUNCT
cana-5088	25	1	moreover	moreover	ADV
cana-5088	25	2	,	,	PUNCT
cana-5088	25	3	handling	handle	VERB
cana-5088	25	4	solid	solid	ADJ
cana-5088	25	5	waste	waste	NOUN
cana-5088	25	6	exposes	expose	VERB
cana-5088	25	7	workers	worker	NOUN
cana-5088	25	8	and	and	CCONJ
cana-5088	25	9	nearby	nearby	ADJ
cana-5088	25	10	populations	population	NOUN
cana-5088	25	11	to	to	ADP
cana-5088	25	12	various	various	ADJ
cana-5088	25	13	health	health	NOUN
cana-5088	25	14	risks	risk	NOUN
cana-5088	25	15	,	,	PUNCT
cana-5088	25	16	including	include	VERB
cana-5088	25	17	respiratory	respiratory	ADJ
cana-5088	25	18	diseases	disease	NOUN
cana-5088	25	19	from	from	ADP
cana-5088	25	20	inhaling	inhale	VERB
cana-5088	25	21	toxic	toxic	ADJ
cana-5088	25	22	fumes	fume	NOUN
cana-5088	25	23	,	,	PUNCT
cana-5088	25	24	skin	skin	NOUN
cana-5088	25	25	infections	infection	NOUN
cana-5088	25	26	from	from	ADP
cana-5088	25	27	direct	direct	ADJ
cana-5088	25	28	contact	contact	NOUN
cana-5088	25	29	,	,	PUNCT
cana-5088	25	30	and	and	CCONJ
cana-5088	25	31	vector	vector	NOUN
cana-5088	25	32	-	-	PUNCT
cana-5088	25	33	borne	bear	VERB
cana-5088	25	34	diseases	disease	NOUN
cana-5088	25	35	caused	cause	VERB
cana-5088	25	36	by	by	ADP
cana-5088	25	37	pests	pest	NOUN
cana-5088	25	38	breeding	breed	VERB
cana-5088	25	39	in	in	ADP
cana-5088	25	40	waste	waste	NOUN
cana-5088	25	41	(	(	PUNCT
cana-5088	25	42	vinti	vinti	NOUN
cana-5088	25	43	et	et	PROPN
cana-5088	25	44	al	al	PROPN
cana-5088	25	45	.	.	PROPN
cana-5088	25	46	,	,	PUNCT
cana-5088	25	47	2021	2021	NUM
cana-5088	25	48	)	)	PUNCT
cana-5088	25	49	.	.	PUNCT
cana-5088	26	1	effective	effective	ADJ
cana-5088	26	2	waste	waste	NOUN
cana-5088	26	3	management	management	NOUN
cana-5088	26	4	strategies	strategy	NOUN
cana-5088	26	5	,	,	PUNCT
cana-5088	26	6	such	such	ADJ
cana-5088	26	7	as	as	ADP
cana-5088	26	8	recycling	recycling	NOUN
cana-5088	26	9	and	and	CCONJ
cana-5088	26	10	composting	composting	NOUN
cana-5088	26	11	,	,	PUNCT
cana-5088	26	12	are	be	AUX
cana-5088	26	13	essential	essential	ADJ
cana-5088	26	14	to	to	PART
cana-5088	26	15	minimize	minimize	VERB
cana-5088	26	16	these	these	DET
cana-5088	26	17	adverse	adverse	ADJ
cana-5088	26	18	impacts	impact	NOUN
cana-5088	26	19	.	.	PUNCT
cana-5088	27	1	recycling	recycling	NOUN
cana-5088	27	2	,	,	PUNCT
cana-5088	27	3	in	in	ADP
cana-5088	27	4	particular	particular	ADJ
cana-5088	27	5	,	,	PUNCT
cana-5088	27	6	aligns	align	VERB
cana-5088	27	7	with	with	ADP
cana-5088	27	8	several	several	ADJ
cana-5088	27	9	united	united	ADJ
cana-5088	27	10	nations	nation	NOUN
cana-5088	27	11	sustainable	sustainable	ADJ
cana-5088	27	12	development	development	NOUN
cana-5088	27	13	goals	goal	NOUN
cana-5088	27	14	(	(	PUNCT
cana-5088	27	15	sdgs	sdgs	ADJ
cana-5088	27	16	)	)	PUNCT
cana-5088	27	17	,	,	PUNCT
cana-5088	27	18	including	include	VERB
cana-5088	27	19	sdg	sdg	NOUN
cana-5088	27	20	12	12	NUM
cana-5088	27	21	(	(	PUNCT
cana-5088	27	22	responsible	responsible	ADJ
cana-5088	27	23	consumption	consumption	NOUN
cana-5088	27	24	and	and	CCONJ
cana-5088	27	25	production	production	NOUN
cana-5088	27	26	)	)	PUNCT
cana-5088	27	27	and	and	CCONJ
cana-5088	27	28	sdg	sdg	NOUN
cana-5088	27	29	13	13	NUM
cana-5088	27	30	(	(	PUNCT
cana-5088	27	31	climate	climate	NOUN
cana-5088	27	32	action	action	NOUN
cana-5088	27	33	)	)	PUNCT
cana-5088	27	34	,	,	PUNCT
cana-5088	27	35	by	by	ADP
cana-5088	27	36	promoting	promote	VERB
cana-5088	27	37	resource	resource	NOUN
cana-5088	27	38	efficiency	efficiency	NOUN
cana-5088	27	39	,	,	PUNCT
cana-5088	27	40	reducing	reduce	VERB
cana-5088	27	41	landfill	landfill	NOUN
cana-5088	27	42	dependency	dependency	NOUN
cana-5088	27	43	,	,	PUNCT
cana-5088	27	44	and	and	CCONJ
cana-5088	27	45	curbing	curb	VERB
cana-5088	27	46	environmental	environmental	ADJ
cana-5088	27	47	contamination	contamination	NOUN
cana-5088	27	48	(	(	PUNCT
cana-5088	27	49	lenkiewicz	lenkiewicz	NOUN
cana-5088	27	50	,	,	PUNCT
cana-5088	27	51	2016	2016	NUM
cana-5088	27	52	)	)	PUNCT
cana-5088	27	53	.	.	PUNCT
cana-5088	28	1	furthermore	furthermore	ADV
cana-5088	28	2	,	,	PUNCT
cana-5088	28	3	by	by	ADP
cana-5088	28	4	reducing	reduce	VERB
cana-5088	28	5	waste	waste	NOUN
cana-5088	28	6	accumulation	accumulation	NOUN
cana-5088	28	7	and	and	CCONJ
cana-5088	28	8	pollution	pollution	NOUN
cana-5088	28	9	,	,	PUNCT
cana-5088	28	10	recycling	recycling	NOUN
cana-5088	28	11	helps	helps	AUX
cana-5088	28	12	mitigate	mitigate	VERB
cana-5088	28	13	the	the	DET
cana-5088	28	14	adverse	adverse	ADJ
cana-5088	28	15	effects	effect	NOUN
cana-5088	28	16	of	of	ADP
cana-5088	28	17	solid	solid	ADJ
cana-5088	28	18	waste	waste	NOUN
cana-5088	28	19	disposal	disposal	NOUN
cana-5088	28	20	on	on	ADP
cana-5088	28	21	public	public	ADJ
cana-5088	28	22	health	health	NOUN
cana-5088	28	23	and	and	CCONJ
cana-5088	28	24	fosters	foster	VERB
cana-5088	28	25	a	a	DET
cana-5088	28	26	cleaner	clean	ADJ
cana-5088	28	27	,	,	PUNCT
cana-5088	28	28	healthier	healthy	ADJ
cana-5088	28	29	society	society	NOUN
cana-5088	28	30	.	.	PUNCT
cana-5088	29	1	effective	effective	ADJ
cana-5088	29	2	waste	waste	NOUN
cana-5088	29	3	classification	classification	NOUN
cana-5088	29	4	is	be	AUX
cana-5088	29	5	a	a	DET
cana-5088	29	6	pivotal	pivotal	ADJ
cana-5088	29	7	step	step	NOUN
cana-5088	29	8	in	in	ADP
cana-5088	29	9	sustainable	sustainable	ADJ
cana-5088	29	10	waste	waste	NOUN
cana-5088	29	11	management	management	NOUN
cana-5088	29	12	as	as	SCONJ
cana-5088	29	13	it	it	PRON
cana-5088	29	14	enables	enable	VERB
cana-5088	29	15	targeted	targeted	ADJ
cana-5088	29	16	recycling	recycling	NOUN
cana-5088	29	17	processes	process	NOUN
cana-5088	29	18	,	,	PUNCT
cana-5088	29	19	reduces	reduce	VERB
cana-5088	29	20	contamination	contamination	NOUN
cana-5088	29	21	,	,	PUNCT
cana-5088	29	22	and	and	CCONJ
cana-5088	29	23	minimizes	minimize	VERB
cana-5088	29	24	the	the	DET
cana-5088	29	25	volume	volume	NOUN
cana-5088	29	26	of	of	ADP
cana-5088	29	27	waste	waste	NOUN
cana-5088	29	28	sent	send	VERB
cana-5088	29	29	to	to	ADP
cana-5088	29	30	landfills	landfill	NOUN
cana-5088	29	31	.	.	PUNCT
cana-5088	30	1	traditional	traditional	ADJ
cana-5088	30	2	methods	method	NOUN
cana-5088	30	3	of	of	ADP
cana-5088	30	4	waste	waste	NOUN
cana-5088	30	5	sorting	sorting	NOUN
cana-5088	30	6	are	be	AUX
cana-5088	30	7	often	often	ADV
cana-5088	30	8	labor	labor	NOUN
cana-5088	30	9	-	-	PUNCT
cana-5088	30	10	intensive	intensive	ADJ
cana-5088	30	11	,	,	PUNCT
cana-5088	30	12	error	error	NOUN
cana-5088	30	13	-	-	PUNCT
cana-5088	30	14	prone	prone	ADJ
cana-5088	30	15	,	,	PUNCT
cana-5088	30	16	and	and	CCONJ
cana-5088	30	17	inefficient	inefficient	ADJ
cana-5088	30	18	,	,	PUNCT
cana-5088	30	19	especially	especially	ADV
cana-5088	30	20	given	give	VERB
cana-5088	30	21	the	the	DET
cana-5088	30	22	sheer	sheer	ADJ
cana-5088	30	23	volume	volume	NOUN
cana-5088	30	24	and	and	CCONJ
cana-5088	30	25	diversity	diversity	NOUN
cana-5088	30	26	of	of	ADP
cana-5088	30	27	waste	waste	NOUN
cana-5088	30	28	materials	material	NOUN
cana-5088	30	29	.	.	PUNCT
cana-5088	31	1	artificial	artificial	ADJ
cana-5088	31	2	intelligence	intelligence	NOUN
cana-5088	31	3	(	(	PUNCT
cana-5088	31	4	ai	ai	NOUN
cana-5088	31	5	)	)	PUNCT
cana-5088	31	6	,	,	PUNCT
cana-5088	31	7	machine	machine	NOUN
cana-5088	31	8	learning	learning	NOUN
cana-5088	31	9	(	(	PUNCT
cana-5088	31	10	ml	ml	NOUN
cana-5088	31	11	)	)	PUNCT
cana-5088	31	12	,	,	PUNCT
cana-5088	31	13	and	and	CCONJ
cana-5088	31	14	deep	deep	ADJ
cana-5088	31	15	learning	learning	NOUN
cana-5088	31	16	(	(	PUNCT
cana-5088	31	17	dl	dl	INTJ
cana-5088	31	18	)	)	PUNCT
cana-5088	31	19	have	have	AUX
cana-5088	31	20	emerged	emerge	VERB
cana-5088	31	21	as	as	ADP
cana-5088	31	22	transformative	transformative	ADJ
cana-5088	31	23	technologies	technology	NOUN
cana-5088	31	24	for	for	ADP
cana-5088	31	25	automating	automate	VERB
cana-5088	31	26	and	and	CCONJ
cana-5088	31	27	optimizing	optimize	VERB
cana-5088	31	28	various	various	ADJ
cana-5088	31	29	aspects	aspect	NOUN
cana-5088	31	30	of	of	ADP
cana-5088	31	31	waste	waste	NOUN
cana-5088	31	32	management	management	NOUN
cana-5088	31	33	(	(	PUNCT
cana-5088	31	34	majchrowska	majchrowska	NOUN
cana-5088	31	35	et	et	PROPN
cana-5088	31	36	al	al	PROPN
cana-5088	31	37	.	.	PROPN
cana-5088	31	38	,	,	PUNCT
cana-5088	31	39	2022	2022	NUM
cana-5088	31	40	)	)	PUNCT
cana-5088	31	41	.	.	PUNCT
cana-5088	32	1	image	image	NOUN
cana-5088	32	2	classification	classification	NOUN
cana-5088	32	3	is	be	AUX
cana-5088	32	4	a	a	DET
cana-5088	32	5	fundamental	fundamental	ADJ
cana-5088	32	6	task	task	NOUN
cana-5088	32	7	in	in	ADP
cana-5088	32	8	computer	computer	NOUN
cana-5088	32	9	vision	vision	NOUN
cana-5088	32	10	,	,	PUNCT
cana-5088	32	11	involving	involve	VERB
cana-5088	32	12	automatically	automatically	ADV
cana-5088	32	13	categorizing	categorize	VERB
cana-5088	32	14	images	image	NOUN
cana-5088	32	15	into	into	ADP
cana-5088	32	16	predefined	predefined	ADJ
cana-5088	32	17	classes	class	NOUN
cana-5088	32	18	.	.	PUNCT
cana-5088	33	1	in	in	ADP
cana-5088	33	2	the	the	DET
cana-5088	33	3	context	context	NOUN
cana-5088	33	4	of	of	ADP
cana-5088	33	5	waste	waste	NOUN
cana-5088	33	6	management	management	NOUN
cana-5088	33	7	,	,	PUNCT
cana-5088	33	8	image	image	NOUN
cana-5088	33	9	classification	classification	NOUN
cana-5088	33	10	plays	play	VERB
cana-5088	33	11	a	a	DET
cana-5088	33	12	pivotal	pivotal	ADJ
cana-5088	33	13	role	role	NOUN
cana-5088	33	14	in	in	ADP
cana-5088	33	15	identifying	identify	VERB
cana-5088	33	16	and	and	CCONJ
cana-5088	33	17	sorting	sort	VERB
cana-5088	33	18	various	various	ADJ
cana-5088	33	19	types	type	NOUN
cana-5088	33	20	of	of	ADP
cana-5088	33	21	waste	waste	NOUN
cana-5088	33	22	materials	material	NOUN
cana-5088	33	23	,	,	PUNCT
cana-5088	33	24	such	such	ADJ
cana-5088	33	25	as	as	ADP
cana-5088	33	26	paper	paper	NOUN
cana-5088	33	27	,	,	PUNCT
cana-5088	33	28	plastic	plastic	NOUN
cana-5088	33	29	,	,	PUNCT
cana-5088	33	30	glass	glass	NOUN
cana-5088	33	31	,	,	PUNCT
cana-5088	33	32	and	and	CCONJ
cana-5088	33	33	organic	organic	ADJ
cana-5088	33	34	matter	matter	NOUN
cana-5088	33	35	.	.	PUNCT
cana-5088	34	1	deep	deep	ADJ
cana-5088	34	2	learning	learning	NOUN
cana-5088	34	3	,	,	PUNCT
cana-5088	34	4	a	a	DET
cana-5088	34	5	subset	subset	NOUN
cana-5088	34	6	of	of	ADP
cana-5088	34	7	ml	ml	NOUN
cana-5088	34	8	,	,	PUNCT
cana-5088	34	9	uses	use	VERB
cana-5088	34	10	neural	neural	ADJ
cana-5088	34	11	networks	network	NOUN
cana-5088	34	12	with	with	ADP
cana-5088	34	13	multiple	multiple	ADJ
cana-5088	34	14	layers	layer	NOUN
cana-5088	34	15	to	to	PART
cana-5088	34	16	automatically	automatically	ADV
cana-5088	34	17	learn	learn	VERB
cana-5088	34	18	features	feature	NOUN
cana-5088	34	19	from	from	ADP
cana-5088	34	20	data	datum	NOUN
cana-5088	34	21	,	,	PUNCT
cana-5088	34	22	mimicking	mimic	VERB
cana-5088	34	23	the	the	DET
cana-5088	34	24	human	human	ADJ
cana-5088	34	25	brain	brain	NOUN
cana-5088	34	26	's	's	PART
cana-5088	34	27	ability	ability	NOUN
cana-5088	34	28	to	to	PART
cana-5088	34	29	recognize	recognize	VERB
cana-5088	34	30	patterns	pattern	NOUN
cana-5088	34	31	(	(	PUNCT
cana-5088	34	32	yu	yu	PROPN
cana-5088	34	33	,	,	PUNCT
cana-5088	34	34	2023	2023	NUM
cana-5088	34	35	)	)	PUNCT
cana-5088	34	36	.	.	PUNCT
cana-5088	35	1	convolutional	convolutional	ADJ
cana-5088	35	2	neural	neural	ADJ
cana-5088	35	3	networks	network	NOUN
cana-5088	35	4	(	(	PUNCT
cana-5088	35	5	cnns	cnns	PROPN
cana-5088	35	6	)	)	PUNCT
cana-5088	35	7	,	,	PUNCT
cana-5088	35	8	a	a	DET
cana-5088	35	9	specialized	specialized	ADJ
cana-5088	35	10	class	class	NOUN
cana-5088	35	11	of	of	ADP
cana-5088	35	12	deep	deep	ADJ
cana-5088	35	13	learning	learning	NOUN
cana-5088	35	14	models	model	NOUN
cana-5088	35	15	,	,	PUNCT
cana-5088	35	16	excel	excel	VERB
cana-5088	35	17	in	in	ADP
cana-5088	35	18	processing	processing	NOUN
cana-5088	35	19	image	image	NOUN
cana-5088	35	20	data	datum	NOUN
cana-5088	35	21	,	,	PUNCT
cana-5088	35	22	making	make	VERB
cana-5088	35	23	them	they	PRON
cana-5088	35	24	ideal	ideal	ADJ
cana-5088	35	25	for	for	ADP
cana-5088	35	26	tasks	task	NOUN
cana-5088	35	27	like	like	ADP
cana-5088	35	28	waste	waste	NOUN
cana-5088	35	29	classification	classification	NOUN
cana-5088	35	30	(	(	PUNCT
cana-5088	35	31	chen	chen	PROPN
cana-5088	35	32	et	et	PROPN
cana-5088	35	33	al	al	PROPN
cana-5088	35	34	.	.	PROPN
cana-5088	35	35	,	,	PUNCT
cana-5088	35	36	2021	2021	NUM
cana-5088	35	37	)	)	PUNCT
cana-5088	35	38	.	.	PUNCT
cana-5088	36	1	employing	employ	VERB
cana-5088	36	2	machines	machine	NOUN
cana-5088	36	3	powered	power	VERB
cana-5088	36	4	by	by	ADP
cana-5088	36	5	deep	deep	ADJ
cana-5088	36	6	learning	learning	NOUN
cana-5088	36	7	not	not	PART
cana-5088	36	8	only	only	ADV
cana-5088	36	9	reduces	reduce	VERB
cana-5088	36	10	the	the	DET
cana-5088	36	11	dependency	dependency	NOUN
cana-5088	36	12	on	on	ADP
cana-5088	36	13	manual	manual	ADJ
cana-5088	36	14	labor	labor	NOUN
cana-5088	36	15	but	but	CCONJ
cana-5088	36	16	also	also	ADV
cana-5088	36	17	ensures	ensure	VERB
cana-5088	36	18	consistent	consistent	ADJ
cana-5088	36	19	,	,	PUNCT
cana-5088	36	20	scalable	scalable	ADJ
cana-5088	36	21	,	,	PUNCT
cana-5088	36	22	and	and	CCONJ
cana-5088	36	23	high	high	ADJ
cana-5088	36	24	-	-	PUNCT
cana-5088	36	25	accuracy	accuracy	NOUN
cana-5088	36	26	performance	performance	NOUN
cana-5088	36	27	.	.	PUNCT
cana-5088	37	1	this	this	DET
cana-5088	37	2	transformative	transformative	ADJ
cana-5088	37	3	approach	approach	NOUN
cana-5088	37	4	is	be	AUX
cana-5088	37	5	a	a	DET
cana-5088	37	6	critical	critical	ADJ
cana-5088	37	7	step	step	NOUN
cana-5088	37	8	toward	toward	ADP
cana-5088	37	9	efficient	efficient	ADJ
cana-5088	37	10	waste	waste	NOUN
cana-5088	37	11	management	management	NOUN
cana-5088	37	12	systems	system	NOUN
cana-5088	37	13	,	,	PUNCT
cana-5088	37	14	enabling	enable	VERB
cana-5088	37	15	real	real	ADJ
cana-5088	37	16	-	-	PUNCT
cana-5088	37	17	time	time	NOUN
cana-5088	37	18	sorting	sorting	NOUN
cana-5088	37	19	and	and	CCONJ
cana-5088	37	20	recycling	recycling	NOUN
cana-5088	37	21	while	while	SCONJ
cana-5088	37	22	minimizing	minimize	VERB
cana-5088	37	23	human	human	ADJ
cana-5088	37	24	error	error	NOUN
cana-5088	37	25	and	and	CCONJ
cana-5088	37	26	health	health	NOUN
cana-5088	37	27	risks	risk	NOUN
cana-5088	37	28	.	.	PUNCT
cana-5088	38	1	however	however	ADV
cana-5088	38	2	,	,	PUNCT
cana-5088	38	3	prior	prior	ADJ
cana-5088	38	4	research	research	NOUN
cana-5088	38	5	in	in	ADP
cana-5088	38	6	waste	waste	NOUN
cana-5088	38	7	classification	classification	NOUN
cana-5088	38	8	has	have	AUX
cana-5088	38	9	encountered	encounter	VERB
cana-5088	38	10	notable	notable	ADJ
cana-5088	38	11	challenges	challenge	NOUN
cana-5088	38	12	,	,	PUNCT
cana-5088	38	13	such	such	ADJ
cana-5088	38	14	as	as	ADP
cana-5088	38	15	the	the	DET
cana-5088	38	16	lack	lack	NOUN
cana-5088	38	17	of	of	ADP
cana-5088	38	18	real	real	ADJ
cana-5088	38	19	-	-	PUNCT
cana-5088	38	20	world	world	NOUN
cana-5088	38	21	waste	waste	NOUN
cana-5088	38	22	datasets	dataset	NOUN
cana-5088	38	23	,	,	PUNCT
cana-5088	38	24	and	and	CCONJ
cana-5088	38	25	inadequate	inadequate	ADJ
cana-5088	38	26	model	model	NOUN
cana-5088	38	27	generalization	generalization	NOUN
cana-5088	38	28	across	across	ADP
cana-5088	38	29	diverse	diverse	ADJ
cana-5088	38	30	waste	waste	NOUN
cana-5088	38	31	categories	category	NOUN
cana-5088	38	32	.	.	PUNCT
cana-5088	39	1	this	this	DET
cana-5088	39	2	study	study	NOUN
cana-5088	39	3	aims	aim	VERB
cana-5088	39	4	to	to	PART
cana-5088	39	5	address	address	VERB
cana-5088	39	6	these	these	DET
cana-5088	39	7	challenges	challenge	NOUN
cana-5088	39	8	by	by	ADP
cana-5088	39	9	utilizing	utilize	VERB
cana-5088	39	10	a	a	DET
cana-5088	39	11	dataset	dataset	NOUN
cana-5088	39	12	comprising	comprise	VERB
cana-5088	39	13	real	real	ADJ
cana-5088	39	14	waste	waste	NOUN
cana-5088	39	15	items	item	NOUN
cana-5088	39	16	captured	capture	VERB
cana-5088	39	17	in	in	ADP
cana-5088	39	18	authentic	authentic	ADJ
cana-5088	39	19	landfill	landfill	NOUN
cana-5088	39	20	environments	environment	NOUN
cana-5088	39	21	,	,	PUNCT
cana-5088	39	22	ensuring	ensure	VERB
cana-5088	39	23	greater	great	ADJ
cana-5088	39	24	relevance	relevance	NOUN
cana-5088	39	25	and	and	CCONJ
cana-5088	39	26	applicability	applicability	NOUN
cana-5088	39	27	to	to	ADP
cana-5088	39	28	real	real	ADJ
cana-5088	39	29	-	-	PUNCT
cana-5088	39	30	world	world	NOUN
cana-5088	39	31	scenarios	scenario	NOUN
cana-5088	39	32	.	.	PUNCT
cana-5088	40	1	to	to	PART
cana-5088	40	2	further	far	ADV
cana-5088	40	3	improve	improve	VERB
cana-5088	40	4	model	model	NOUN
cana-5088	40	5	generalization	generalization	NOUN
cana-5088	40	6	,	,	PUNCT
cana-5088	40	7	the	the	DET
cana-5088	40	8	communications	communication	NOUN
cana-5088	40	9	on	on	ADP
cana-5088	40	10	applied	apply	VERB
cana-5088	40	11	nonlinear	nonlinear	ADJ
cana-5088	40	12	analysis	analysis	NOUN
cana-5088	40	13	issn	issn	NOUN
cana-5088	40	14	:	:	PUNCT
cana-5088	40	15	1074	1074	NUM
cana-5088	40	16	-	-	PUNCT
cana-5088	40	17	133x	133x	NUM
cana-5088	40	18	vol	vol	NOUN
cana-5088	40	19	32	32	NUM
cana-5088	40	20	no	no	NOUN
cana-5088	40	21	.	.	PUNCT
cana-5088	41	1	icmasd	icmasd	NOUN
cana-5088	41	2	(	(	PUNCT
cana-5088	41	3	2025	2025	NUM
cana-5088	41	4	)	)	PUNCT
cana-5088	41	5	589	589	NUM
cana-5088	41	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	41	7	research	research	NOUN
cana-5088	41	8	leverages	leverage	NOUN
cana-5088	41	9	transfer	transfer	NOUN
cana-5088	41	10	learning	learn	VERB
cana-5088	41	11	with	with	ADP
cana-5088	41	12	pre	pre	ADJ
cana-5088	41	13	-	-	ADJ
cana-5088	41	14	trained	train	VERB
cana-5088	41	15	cnn	cnn	PROPN
cana-5088	41	16	models	model	NOUN
cana-5088	41	17	,	,	PUNCT
cana-5088	41	18	which	which	PRON
cana-5088	41	19	have	have	AUX
cana-5088	41	20	already	already	ADV
cana-5088	41	21	demonstrated	demonstrate	VERB
cana-5088	41	22	exceptional	exceptional	ADJ
cana-5088	41	23	performance	performance	NOUN
cana-5088	41	24	on	on	ADP
cana-5088	41	25	large	large	ADJ
cana-5088	41	26	-	-	PUNCT
cana-5088	41	27	scale	scale	NOUN
cana-5088	41	28	image	image	NOUN
cana-5088	41	29	datasets	dataset	NOUN
cana-5088	41	30	.	.	PUNCT
cana-5088	42	1	pre	pre	VERB
cana-5088	42	2	-	-	ADJ
cana-5088	42	3	trained	train	VERB
cana-5088	42	4	cnns	cnn	NOUN
cana-5088	42	5	are	be	AUX
cana-5088	42	6	chosen	choose	VERB
cana-5088	42	7	over	over	ADP
cana-5088	42	8	custombuilt	custombuilt	VERB
cana-5088	42	9	models	model	NOUN
cana-5088	42	10	because	because	SCONJ
cana-5088	42	11	of	of	ADP
cana-5088	42	12	their	their	PRON
cana-5088	42	13	ability	ability	NOUN
cana-5088	42	14	to	to	PART
cana-5088	42	15	extract	extract	VERB
cana-5088	42	16	rich	rich	ADJ
cana-5088	42	17	,	,	PUNCT
cana-5088	42	18	hierarchical	hierarchical	ADJ
cana-5088	42	19	features	feature	NOUN
cana-5088	42	20	while	while	SCONJ
cana-5088	42	21	reducing	reduce	VERB
cana-5088	42	22	training	training	NOUN
cana-5088	42	23	time	time	NOUN
cana-5088	42	24	and	and	CCONJ
cana-5088	42	25	performing	perform	VERB
cana-5088	42	26	well	well	ADV
cana-5088	42	27	even	even	ADV
cana-5088	42	28	with	with	ADP
cana-5088	42	29	limited	limited	ADJ
cana-5088	42	30	labeled	label	VERB
cana-5088	42	31	data	datum	NOUN
cana-5088	42	32	,	,	PUNCT
cana-5088	42	33	making	make	VERB
cana-5088	42	34	them	they	PRON
cana-5088	42	35	ideal	ideal	ADJ
cana-5088	42	36	for	for	ADP
cana-5088	42	37	complicated	complicated	ADJ
cana-5088	42	38	tasks	task	NOUN
cana-5088	42	39	such	such	ADJ
cana-5088	42	40	as	as	ADP
cana-5088	42	41	waste	waste	NOUN
cana-5088	42	42	classification	classification	NOUN
cana-5088	42	43	.	.	PUNCT
cana-5088	43	1	the	the	DET
cana-5088	43	2	study	study	NOUN
cana-5088	43	3	specifically	specifically	ADV
cana-5088	43	4	aims	aim	VERB
cana-5088	43	5	to	to	PART
cana-5088	43	6	evaluate	evaluate	VERB
cana-5088	43	7	and	and	CCONJ
cana-5088	43	8	compare	compare	VERB
cana-5088	43	9	the	the	DET
cana-5088	43	10	performance	performance	NOUN
cana-5088	43	11	of	of	ADP
cana-5088	43	12	resnet50	resnet50	NOUN
cana-5088	43	13	,	,	PUNCT
cana-5088	43	14	efficientnet	efficientnet	NOUN
cana-5088	43	15	-	-	PUNCT
cana-5088	43	16	b0	b0	NOUN
cana-5088	43	17	,	,	PUNCT
cana-5088	43	18	and	and	CCONJ
cana-5088	43	19	densenet121	densenet121	PROPN
cana-5088	43	20	models	model	NOUN
cana-5088	43	21	in	in	ADP
cana-5088	43	22	accurately	accurately	ADV
cana-5088	43	23	categorizing	categorize	VERB
cana-5088	43	24	waste	waste	NOUN
cana-5088	43	25	materials	material	NOUN
cana-5088	43	26	.	.	PUNCT
cana-5088	44	1	the	the	DET
cana-5088	44	2	structure	structure	NOUN
cana-5088	44	3	of	of	ADP
cana-5088	44	4	the	the	DET
cana-5088	44	5	paper	paper	NOUN
cana-5088	44	6	is	be	AUX
cana-5088	44	7	as	as	SCONJ
cana-5088	44	8	follows	follow	VERB
cana-5088	44	9	:	:	PUNCT
cana-5088	44	10	section	section	NOUN
cana-5088	44	11	2	2	NUM
cana-5088	44	12	provides	provide	VERB
cana-5088	44	13	an	an	DET
cana-5088	44	14	extensive	extensive	ADJ
cana-5088	44	15	review	review	NOUN
cana-5088	44	16	of	of	ADP
cana-5088	44	17	related	related	ADJ
cana-5088	44	18	work	work	NOUN
cana-5088	44	19	in	in	ADP
cana-5088	44	20	waste	waste	NOUN
cana-5088	44	21	classification	classification	NOUN
cana-5088	44	22	.	.	PUNCT
cana-5088	45	1	section	section	NOUN
cana-5088	45	2	3	3	NUM
cana-5088	45	3	details	detail	NOUN
cana-5088	45	4	the	the	DET
cana-5088	45	5	methodology	methodology	NOUN
cana-5088	45	6	employed	employ	VERB
cana-5088	45	7	for	for	ADP
cana-5088	45	8	addressing	address	VERB
cana-5088	45	9	waste	waste	NOUN
cana-5088	45	10	classification	classification	NOUN
cana-5088	45	11	tasks	task	NOUN
cana-5088	45	12	.	.	PUNCT
cana-5088	46	1	section	section	NOUN
cana-5088	46	2	4	4	NUM
cana-5088	46	3	presents	present	VERB
cana-5088	46	4	the	the	DET
cana-5088	46	5	results	result	NOUN
cana-5088	46	6	along	along	ADP
cana-5088	46	7	with	with	ADP
cana-5088	46	8	a	a	DET
cana-5088	46	9	discussion	discussion	NOUN
cana-5088	46	10	of	of	ADP
cana-5088	46	11	the	the	DET
cana-5088	46	12	findings	finding	NOUN
cana-5088	46	13	.	.	PUNCT
cana-5088	47	1	finally	finally	ADV
cana-5088	47	2	,	,	PUNCT
cana-5088	47	3	section	section	NOUN
cana-5088	47	4	5	5	NUM
cana-5088	47	5	concludes	conclude	VERB
cana-5088	47	6	the	the	DET
cana-5088	47	7	study	study	NOUN
cana-5088	47	8	and	and	CCONJ
cana-5088	47	9	highlights	highlight	VERB
cana-5088	47	10	potential	potential	ADJ
cana-5088	47	11	directions	direction	NOUN
cana-5088	47	12	for	for	ADP
cana-5088	47	13	future	future	ADJ
cana-5088	47	14	research	research	NOUN
cana-5088	47	15	.	.	PUNCT
cana-5088	48	1	2	2	X
cana-5088	48	2	.	.	X
cana-5088	48	3	literature	literature	NOUN
cana-5088	48	4	review	review	PROPN
cana-5088	48	5	this	this	DET
cana-5088	48	6	section	section	NOUN
cana-5088	48	7	provides	provide	VERB
cana-5088	48	8	an	an	DET
cana-5088	48	9	overview	overview	NOUN
cana-5088	48	10	of	of	ADP
cana-5088	48	11	related	related	ADJ
cana-5088	48	12	works	work	NOUN
cana-5088	48	13	,	,	PUNCT
cana-5088	48	14	focusing	focus	VERB
cana-5088	48	15	on	on	ADP
cana-5088	48	16	the	the	DET
cana-5088	48	17	application	application	NOUN
cana-5088	48	18	of	of	ADP
cana-5088	48	19	deep	deep	ADJ
cana-5088	48	20	cnns	cnn	NOUN
cana-5088	48	21	,	,	PUNCT
cana-5088	48	22	the	the	DET
cana-5088	48	23	role	role	NOUN
cana-5088	48	24	of	of	ADP
cana-5088	48	25	transfer	transfer	NOUN
cana-5088	48	26	learning	learning	NOUN
cana-5088	48	27	,	,	PUNCT
cana-5088	48	28	and	and	CCONJ
cana-5088	48	29	the	the	DET
cana-5088	48	30	effectiveness	effectiveness	NOUN
cana-5088	48	31	of	of	ADP
cana-5088	48	32	pre	pre	ADJ
cana-5088	48	33	-	-	ADJ
cana-5088	48	34	trained	train	VERB
cana-5088	48	35	models	model	NOUN
cana-5088	48	36	in	in	ADP
cana-5088	48	37	addressing	address	VERB
cana-5088	48	38	the	the	DET
cana-5088	48	39	challenges	challenge	NOUN
cana-5088	48	40	associated	associate	VERB
cana-5088	48	41	with	with	ADP
cana-5088	48	42	automated	automate	VERB
cana-5088	48	43	waste	waste	NOUN
cana-5088	48	44	classification	classification	NOUN
cana-5088	48	45	.	.	PUNCT
cana-5088	49	1	ramírez	ramírez	PROPN
cana-5088	49	2	et	et	PROPN
cana-5088	49	3	al	al	PROPN
cana-5088	49	4	.	.	PROPN
cana-5088	50	1	(	(	PUNCT
cana-5088	50	2	2020	2020	NUM
cana-5088	50	3	)	)	PUNCT
cana-5088	50	4	employed	employ	VERB
cana-5088	50	5	transfer	transfer	NOUN
cana-5088	50	6	learning	learning	NOUN
cana-5088	50	7	with	with	ADP
cana-5088	50	8	google	google	PROPN
cana-5088	50	9	's	's	PART
cana-5088	50	10	inception	inception	PROPN
cana-5088	50	11	-	-	PUNCT
cana-5088	50	12	v3	v3	NOUN
cana-5088	50	13	cnn	cnn	PROPN
cana-5088	50	14	and	and	CCONJ
cana-5088	50	15	a	a	DET
cana-5088	50	16	novel	novel	NOUN
cana-5088	50	17	semisupervised	semisupervise	VERB
cana-5088	50	18	learning	learn	VERB
cana-5088	50	19	approach	approach	NOUN
cana-5088	50	20	to	to	PART
cana-5088	50	21	achieve	achieve	VERB
cana-5088	50	22	high	high	ADJ
cana-5088	50	23	accuracy	accuracy	NOUN
cana-5088	50	24	with	with	ADP
cana-5088	50	25	minimal	minimal	ADJ
cana-5088	50	26	human	human	ADJ
cana-5088	50	27	image	image	NOUN
cana-5088	50	28	labeling	labeling	NOUN
cana-5088	50	29	.	.	PUNCT
cana-5088	51	1	their	their	PRON
cana-5088	51	2	method	method	NOUN
cana-5088	51	3	uses	use	VERB
cana-5088	51	4	a	a	DET
cana-5088	51	5	three	three	NUM
cana-5088	51	6	-	-	PUNCT
cana-5088	51	7	round	round	NOUN
cana-5088	51	8	retraining	retraining	ADJ
cana-5088	51	9	process	process	NOUN
cana-5088	51	10	,	,	PUNCT
cana-5088	51	11	comparing	compare	VERB
cana-5088	51	12	a	a	DET
cana-5088	51	13	baseline	baseline	ADJ
cana-5088	51	14	approach	approach	NOUN
cana-5088	51	15	to	to	ADP
cana-5088	51	16	two	two	NUM
cana-5088	51	17	improved	improved	ADJ
cana-5088	51	18	methods	method	NOUN
cana-5088	51	19	:	:	PUNCT
cana-5088	51	20	half	half	ADV
cana-5088	51	21	-	-	PUNCT
cana-5088	51	22	worst	bad	ADJ
cana-5088	51	23	and	and	CCONJ
cana-5088	51	24	gaussian	gaussian	ADJ
cana-5088	51	25	mixture	mixture	NOUN
cana-5088	51	26	model	model	NOUN
cana-5088	51	27	(	(	PUNCT
cana-5088	51	28	gmm	gmm	PROPN
cana-5088	51	29	)	)	PUNCT
cana-5088	51	30	.	.	PUNCT
cana-5088	52	1	the	the	DET
cana-5088	52	2	system	system	NOUN
cana-5088	52	3	achieves	achieve	VERB
cana-5088	52	4	88	88	NUM
cana-5088	52	5	%	%	NOUN
cana-5088	52	6	accuracy	accuracy	NOUN
cana-5088	52	7	,	,	PUNCT
cana-5088	52	8	which	which	PRON
cana-5088	52	9	represents	represent	VERB
cana-5088	52	10	94	94	NUM
cana-5088	52	11	%	%	NOUN
cana-5088	52	12	of	of	ADP
cana-5088	52	13	the	the	DET
cana-5088	52	14	performance	performance	NOUN
cana-5088	52	15	achieved	achieve	VERB
cana-5088	52	16	using	use	VERB
cana-5088	52	17	a	a	DET
cana-5088	52	18	fully	fully	ADV
cana-5088	52	19	labeled	label	VERB
cana-5088	52	20	dataset	dataset	NOUN
cana-5088	52	21	,	,	PUNCT
cana-5088	52	22	demonstrating	demonstrate	VERB
cana-5088	52	23	the	the	DET
cana-5088	52	24	effectiveness	effectiveness	NOUN
cana-5088	52	25	of	of	ADP
cana-5088	52	26	their	their	PRON
cana-5088	52	27	approach	approach	NOUN
cana-5088	52	28	.	.	PUNCT
cana-5088	53	1	feng	feng	PROPN
cana-5088	53	2	and	and	CCONJ
cana-5088	53	3	tang	tang	PROPN
cana-5088	53	4	(	(	PUNCT
cana-5088	53	5	2020	2020	NUM
cana-5088	53	6	)	)	PUNCT
cana-5088	53	7	proposed	propose	VERB
cana-5088	53	8	an	an	DET
cana-5088	53	9	intelligent	intelligent	ADJ
cana-5088	53	10	garbage	garbage	NOUN
cana-5088	53	11	classification	classification	NOUN
cana-5088	53	12	system	system	NOUN
cana-5088	53	13	using	use	VERB
cana-5088	53	14	a	a	DET
cana-5088	53	15	convolutional	convolutional	ADJ
cana-5088	53	16	neural	neural	ADJ
cana-5088	53	17	network	network	NOUN
cana-5088	53	18	.	.	PUNCT
cana-5088	54	1	the	the	DET
cana-5088	54	2	authors	author	NOUN
cana-5088	54	3	utilized	utilize	VERB
cana-5088	54	4	transfer	transfer	NOUN
cana-5088	54	5	learning	learn	VERB
cana-5088	54	6	with	with	ADP
cana-5088	54	7	the	the	DET
cana-5088	54	8	inception	inception	PROPN
cana-5088	54	9	-	-	PUNCT
cana-5088	54	10	v3	v3	NOUN
cana-5088	54	11	model	model	NOUN
cana-5088	54	12	,	,	PUNCT
cana-5088	54	13	achieving	achieve	VERB
cana-5088	54	14	a	a	DET
cana-5088	54	15	95.33	95.33	NUM
cana-5088	54	16	%	%	NOUN
cana-5088	54	17	accuracy	accuracy	NOUN
cana-5088	54	18	in	in	ADP
cana-5088	54	19	classifying	classify	VERB
cana-5088	54	20	six	six	NUM
cana-5088	54	21	types	type	NOUN
cana-5088	54	22	of	of	ADP
cana-5088	54	23	office	office	NOUN
cana-5088	54	24	waste	waste	NOUN
cana-5088	54	25	.	.	PUNCT
cana-5088	55	1	the	the	DET
cana-5088	55	2	study	study	NOUN
cana-5088	55	3	addresses	address	VERB
cana-5088	55	4	the	the	DET
cana-5088	55	5	growing	grow	VERB
cana-5088	55	6	problem	problem	NOUN
cana-5088	55	7	of	of	ADP
cana-5088	55	8	garbage	garbage	NOUN
cana-5088	55	9	pollution	pollution	NOUN
cana-5088	55	10	and	and	CCONJ
cana-5088	55	11	offers	offer	VERB
cana-5088	55	12	a	a	DET
cana-5088	55	13	cost	cost	NOUN
cana-5088	55	14	-	-	PUNCT
cana-5088	55	15	effective	effective	ADJ
cana-5088	55	16	solution	solution	NOUN
cana-5088	55	17	for	for	ADP
cana-5088	55	18	automated	automate	VERB
cana-5088	55	19	waste	waste	NOUN
cana-5088	55	20	sorting	sorting	NOUN
cana-5088	55	21	.	.	PUNCT
cana-5088	56	1	parameter	parameter	NOUN
cana-5088	56	2	optimization	optimization	NOUN
cana-5088	56	3	for	for	ADP
cana-5088	56	4	the	the	DET
cana-5088	56	5	embedded	embed	VERB
cana-5088	56	6	system	system	NOUN
cana-5088	56	7	was	be	AUX
cana-5088	56	8	also	also	ADV
cana-5088	56	9	explored	explore	VERB
cana-5088	56	10	to	to	PART
cana-5088	56	11	maximize	maximize	VERB
cana-5088	56	12	efficiency	efficiency	NOUN
cana-5088	56	13	and	and	CCONJ
cana-5088	56	14	accuracy	accuracy	NOUN
cana-5088	56	15	.	.	PUNCT
cana-5088	57	1	atikuzzaman	atikuzzaman	NOUN
cana-5088	57	2	et	et	PROPN
cana-5088	57	3	al	al	PROPN
cana-5088	57	4	.	.	PROPN
cana-5088	58	1	(	(	PUNCT
cana-5088	58	2	2021	2021	NUM
cana-5088	58	3	)	)	PUNCT
cana-5088	58	4	trained	train	VERB
cana-5088	58	5	and	and	CCONJ
cana-5088	58	6	compared	compare	VERB
cana-5088	58	7	different	different	ADJ
cana-5088	58	8	cnn	cnn	PROPN
cana-5088	58	9	architectures	architecture	NOUN
cana-5088	58	10	:	:	PUNCT
cana-5088	58	11	resnet	resnet	NOUN
cana-5088	58	12	(	(	PUNCT
cana-5088	58	13	resnet34	resnet34	NOUN
cana-5088	58	14	,	,	PUNCT
cana-5088	58	15	resnet50	resnet50	NOUN
cana-5088	58	16	,	,	PUNCT
cana-5088	58	17	resnet101	resnet101	PROPN
cana-5088	58	18	,	,	PUNCT
cana-5088	58	19	resnet152	resnet152	PROPN
cana-5088	58	20	)	)	PUNCT
cana-5088	58	21	and	and	CCONJ
cana-5088	58	22	vgg	vgg	NOUN
cana-5088	58	23	(	(	PUNCT
cana-5088	58	24	vgg11	vgg11	PROPN
cana-5088	58	25	,	,	PUNCT
cana-5088	58	26	vgg16	vgg16	PROPN
cana-5088	58	27	,	,	PUNCT
cana-5088	58	28	vgg19	vgg19	PROPN
cana-5088	58	29	)	)	PUNCT
cana-5088	58	30	,	,	PUNCT
cana-5088	58	31	using	use	VERB
cana-5088	58	32	a	a	DET
cana-5088	58	33	dataset	dataset	NOUN
cana-5088	58	34	of	of	ADP
cana-5088	58	35	1989	1989	NUM
cana-5088	58	36	trash	trash	NOUN
cana-5088	58	37	images	image	NOUN
cana-5088	58	38	categorized	categorize	VERB
cana-5088	58	39	into	into	ADP
cana-5088	58	40	six	six	NUM
cana-5088	58	41	classes	class	NOUN
cana-5088	58	42	(	(	PUNCT
cana-5088	58	43	cardboard	cardboard	NOUN
cana-5088	58	44	,	,	PUNCT
cana-5088	58	45	glass	glass	NOUN
cana-5088	58	46	,	,	PUNCT
cana-5088	58	47	metal	metal	NOUN
cana-5088	58	48	,	,	PUNCT
cana-5088	58	49	paper	paper	NOUN
cana-5088	58	50	,	,	PUNCT
cana-5088	58	51	plastic	plastic	NOUN
cana-5088	58	52	,	,	PUNCT
cana-5088	58	53	and	and	CCONJ
cana-5088	58	54	trash	trash	NOUN
cana-5088	58	55	)	)	PUNCT
cana-5088	58	56	.	.	PUNCT
cana-5088	59	1	resnet152	resnet152	PROPN
cana-5088	59	2	achieved	achieve	VERB
cana-5088	59	3	the	the	DET
cana-5088	59	4	highest	high	ADJ
cana-5088	59	5	accuracy	accuracy	NOUN
cana-5088	59	6	(	(	PUNCT
cana-5088	59	7	93.86	93.86	NUM
cana-5088	59	8	%	%	NOUN
cana-5088	59	9	)	)	PUNCT
cana-5088	59	10	among	among	ADP
cana-5088	59	11	all	all	DET
cana-5088	59	12	resnet	resnet	NOUN
cana-5088	59	13	models	model	NOUN
cana-5088	59	14	,	,	PUNCT
cana-5088	59	15	while	while	SCONJ
cana-5088	59	16	vgg16	vgg16	NOUN
cana-5088	59	17	achieved	achieve	VERB
cana-5088	59	18	the	the	DET
cana-5088	59	19	highest	high	ADJ
cana-5088	59	20	accuracy	accuracy	NOUN
cana-5088	59	21	(	(	PUNCT
cana-5088	59	22	90.49	90.49	NUM
cana-5088	59	23	%	%	NOUN
cana-5088	59	24	)	)	PUNCT
cana-5088	59	25	among	among	ADP
cana-5088	59	26	the	the	DET
cana-5088	59	27	vgg	vgg	NOUN
cana-5088	59	28	models	model	NOUN
cana-5088	59	29	.	.	PUNCT
cana-5088	60	1	the	the	DET
cana-5088	60	2	study	study	NOUN
cana-5088	60	3	highlights	highlight	VERB
cana-5088	60	4	the	the	DET
cana-5088	60	5	potential	potential	NOUN
cana-5088	60	6	of	of	ADP
cana-5088	60	7	cnns	cnn	NOUN
cana-5088	60	8	for	for	ADP
cana-5088	60	9	automating	automate	VERB
cana-5088	60	10	waste	waste	NOUN
cana-5088	60	11	management	management	NOUN
cana-5088	60	12	and	and	CCONJ
cana-5088	60	13	suggests	suggest	VERB
cana-5088	60	14	future	future	ADJ
cana-5088	60	15	improvements	improvement	NOUN
cana-5088	60	16	by	by	ADP
cana-5088	60	17	expanding	expand	VERB
cana-5088	60	18	the	the	DET
cana-5088	60	19	dataset	dataset	NOUN
cana-5088	60	20	and	and	CCONJ
cana-5088	60	21	handling	handle	VERB
cana-5088	60	22	multiple	multiple	ADJ
cana-5088	60	23	trash	trash	NOUN
cana-5088	60	24	items	item	NOUN
cana-5088	60	25	within	within	ADP
cana-5088	60	26	a	a	DET
cana-5088	60	27	single	single	ADJ
cana-5088	60	28	image	image	NOUN
cana-5088	60	29	.	.	PUNCT
cana-5088	61	1	ling	ling	PROPN
cana-5088	61	2	and	and	CCONJ
cana-5088	61	3	tianyi	tianyi	PROPN
cana-5088	61	4	(	(	PUNCT
cana-5088	61	5	2021	2021	NUM
cana-5088	61	6	)	)	PUNCT
cana-5088	61	7	proposed	propose	VERB
cana-5088	61	8	designing	design	VERB
cana-5088	61	9	and	and	CCONJ
cana-5088	61	10	implementing	implement	VERB
cana-5088	61	11	a	a	DET
cana-5088	61	12	smart	smart	ADJ
cana-5088	61	13	trash	trash	NOUN
cana-5088	61	14	can	can	AUX
cana-5088	61	15	leveraging	leverage	VERB
cana-5088	61	16	cnns	cnn	NOUN
cana-5088	61	17	and	and	CCONJ
cana-5088	61	18	transfer	transfer	NOUN
cana-5088	61	19	learning	learning	NOUN
cana-5088	61	20	for	for	ADP
cana-5088	61	21	automated	automate	VERB
cana-5088	61	22	waste	waste	NOUN
cana-5088	61	23	sorting	sorting	NOUN
cana-5088	61	24	.	.	PUNCT
cana-5088	62	1	the	the	DET
cana-5088	62	2	system	system	NOUN
cana-5088	62	3	integrates	integrate	VERB
cana-5088	62	4	image	image	NOUN
cana-5088	62	5	recognition	recognition	NOUN
cana-5088	62	6	capabilities	capability	NOUN
cana-5088	62	7	,	,	PUNCT
cana-5088	62	8	utilizing	utilize	VERB
cana-5088	62	9	a	a	DET
cana-5088	62	10	fine	fine	ADV
cana-5088	62	11	-	-	PUNCT
cana-5088	62	12	tuned	tune	VERB
cana-5088	62	13	inceptionv3	inceptionv3	NOUN
cana-5088	62	14	model	model	NOUN
cana-5088	62	15	trained	train	VERB
cana-5088	62	16	on	on	ADP
cana-5088	62	17	a	a	DET
cana-5088	62	18	custom	custom	NOUN
cana-5088	62	19	dataset	dataset	NOUN
cana-5088	62	20	comprising	comprise	VERB
cana-5088	62	21	1,200	1,200	NUM
cana-5088	62	22	images	image	NOUN
cana-5088	62	23	of	of	ADP
cana-5088	62	24	various	various	ADJ
cana-5088	62	25	garbage	garbage	NOUN
cana-5088	62	26	types	type	NOUN
cana-5088	62	27	.	.	PUNCT
cana-5088	63	1	experimental	experimental	ADJ
cana-5088	63	2	results	result	NOUN
cana-5088	63	3	highlight	highlight	VERB
cana-5088	63	4	the	the	DET
cana-5088	63	5	system	system	NOUN
cana-5088	63	6	's	's	PART
cana-5088	63	7	high	high	ADJ
cana-5088	63	8	accuracy	accuracy	NOUN
cana-5088	63	9	and	and	CCONJ
cana-5088	63	10	operational	operational	ADJ
cana-5088	63	11	efficiency	efficiency	NOUN
cana-5088	63	12	,	,	PUNCT
cana-5088	63	13	with	with	ADP
cana-5088	63	14	cnns	cnn	NOUN
cana-5088	63	15	achieving	achieve	VERB
cana-5088	63	16	an	an	DET
cana-5088	63	17	average	average	ADJ
cana-5088	63	18	recognition	recognition	NOUN
cana-5088	63	19	rate	rate	NOUN
cana-5088	63	20	between	between	ADP
cana-5088	63	21	82.64	82.64	NUM
cana-5088	63	22	%	%	NOUN
cana-5088	63	23	and	and	CCONJ
cana-5088	63	24	89.6	89.6	NUM
cana-5088	63	25	%	%	NOUN
cana-5088	63	26	.	.	PUNCT
cana-5088	64	1	the	the	DET
cana-5088	64	2	application	application	NOUN
cana-5088	64	3	of	of	ADP
cana-5088	64	4	transfer	transfer	NOUN
cana-5088	64	5	learning	learn	VERB
cana-5088	64	6	further	far	ADV
cana-5088	64	7	improved	improve	VERB
cana-5088	64	8	the	the	DET
cana-5088	64	9	performance	performance	NOUN
cana-5088	64	10	,	,	PUNCT
cana-5088	64	11	increasing	increase	VERB
cana-5088	64	12	accuracy	accuracy	NOUN
cana-5088	64	13	from	from	ADP
cana-5088	64	14	85.32	85.32	NUM
cana-5088	64	15	%	%	NOUN
cana-5088	64	16	communications	communication	NOUN
cana-5088	64	17	on	on	ADP
cana-5088	64	18	applied	apply	VERB
cana-5088	64	19	nonlinear	nonlinear	ADJ
cana-5088	64	20	analysis	analysis	NOUN
cana-5088	64	21	issn	issn	NOUN
cana-5088	64	22	:	:	PUNCT
cana-5088	64	23	1074	1074	NUM
cana-5088	64	24	-	-	PUNCT
cana-5088	64	25	133x	133x	NUM
cana-5088	64	26	vol	vol	NOUN
cana-5088	64	27	32	32	NUM
cana-5088	64	28	no	no	NOUN
cana-5088	64	29	.	.	PUNCT
cana-5088	65	1	icmasd	icmasd	NOUN
cana-5088	65	2	(	(	PUNCT
cana-5088	65	3	2025	2025	NUM
cana-5088	65	4	)	)	PUNCT
cana-5088	65	5	590	590	NUM
cana-5088	65	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	65	7	to	to	ADP
cana-5088	65	8	92.2	92.2	NUM
cana-5088	65	9	%	%	NOUN
cana-5088	65	10	.	.	PUNCT
cana-5088	66	1	these	these	DET
cana-5088	66	2	findings	finding	NOUN
cana-5088	66	3	underscore	underscore	VERB
cana-5088	66	4	the	the	DET
cana-5088	66	5	effectiveness	effectiveness	NOUN
cana-5088	66	6	of	of	ADP
cana-5088	66	7	transfer	transfer	NOUN
cana-5088	66	8	learning	learning	NOUN
cana-5088	66	9	in	in	ADP
cana-5088	66	10	optimizing	optimize	VERB
cana-5088	66	11	waste	waste	NOUN
cana-5088	66	12	classification	classification	NOUN
cana-5088	66	13	systems	system	NOUN
cana-5088	66	14	.	.	PUNCT
cana-5088	67	1	srivatsan	srivatsan	PROPN
cana-5088	67	2	et	et	PROPN
cana-5088	67	3	al	al	PROPN
cana-5088	67	4	.	.	PROPN
cana-5088	68	1	(	(	PUNCT
cana-5088	68	2	2021	2021	NUM
cana-5088	68	3	)	)	PUNCT
cana-5088	68	4	applied	apply	VERB
cana-5088	68	5	transfer	transfer	NOUN
cana-5088	68	6	learning	learning	NOUN
cana-5088	68	7	,	,	PUNCT
cana-5088	68	8	leveraging	leverage	VERB
cana-5088	68	9	the	the	DET
cana-5088	68	10	pre	pre	ADJ
cana-5088	68	11	-	-	ADJ
cana-5088	68	12	trained	trained	ADJ
cana-5088	68	13	weights	weight	NOUN
cana-5088	68	14	of	of	ADP
cana-5088	68	15	mobilenetv2	mobilenetv2	PROPN
cana-5088	68	16	,	,	PUNCT
cana-5088	68	17	resnet34	resnet34	NOUN
cana-5088	68	18	,	,	PUNCT
cana-5088	68	19	and	and	CCONJ
cana-5088	68	20	densenet121	densenet121	PROPN
cana-5088	68	21	models	model	NOUN
cana-5088	68	22	on	on	ADP
cana-5088	68	23	the	the	DET
cana-5088	68	24	compostnet	compostnet	NOUN
cana-5088	68	25	dataset	dataset	NOUN
cana-5088	68	26	,	,	PUNCT
cana-5088	68	27	to	to	PART
cana-5088	68	28	achieve	achieve	VERB
cana-5088	68	29	exceptional	exceptional	ADJ
cana-5088	68	30	waste	waste	NOUN
cana-5088	68	31	classification	classification	NOUN
cana-5088	68	32	accuracy	accuracy	NOUN
cana-5088	68	33	across	across	ADP
cana-5088	68	34	seven	seven	NUM
cana-5088	68	35	categories	category	NOUN
cana-5088	68	36	.	.	PUNCT
cana-5088	69	1	densenet121	densenet121	PROPN
cana-5088	69	2	achieved	achieve	VERB
cana-5088	69	3	the	the	DET
cana-5088	69	4	highest	high	ADJ
cana-5088	69	5	accuracy	accuracy	NOUN
cana-5088	69	6	at	at	ADP
cana-5088	69	7	96.43	96.43	NUM
cana-5088	69	8	%	%	NOUN
cana-5088	69	9	,	,	PUNCT
cana-5088	69	10	closely	closely	ADV
cana-5088	69	11	followed	follow	VERB
cana-5088	69	12	by	by	ADP
cana-5088	69	13	resnet34	resnet34	NOUN
cana-5088	69	14	and	and	CCONJ
cana-5088	69	15	mobilenetv2	mobilenetv2	PROPN
cana-5088	69	16	,	,	PUNCT
cana-5088	69	17	which	which	PRON
cana-5088	69	18	both	both	PRON
cana-5088	69	19	recorded	record	VERB
cana-5088	69	20	accuracies	accuracy	NOUN
cana-5088	69	21	of	of	ADP
cana-5088	69	22	96.27	96.27	NUM
cana-5088	69	23	%	%	NOUN
cana-5088	69	24	.	.	PUNCT
cana-5088	70	1	this	this	DET
cana-5088	70	2	research	research	NOUN
cana-5088	70	3	addresses	address	VERB
cana-5088	70	4	the	the	DET
cana-5088	70	5	pressing	press	VERB
cana-5088	70	6	global	global	ADJ
cana-5088	70	7	issue	issue	NOUN
cana-5088	70	8	of	of	ADP
cana-5088	70	9	inefficient	inefficient	ADJ
cana-5088	70	10	waste	waste	NOUN
cana-5088	70	11	management	management	NOUN
cana-5088	70	12	,	,	PUNCT
cana-5088	70	13	striving	strive	VERB
cana-5088	70	14	to	to	PART
cana-5088	70	15	improve	improve	VERB
cana-5088	70	16	resource	resource	NOUN
cana-5088	70	17	recovery	recovery	NOUN
cana-5088	70	18	and	and	CCONJ
cana-5088	70	19	support	support	VERB
cana-5088	70	20	sustainable	sustainable	ADJ
cana-5088	70	21	practices	practice	NOUN
cana-5088	70	22	.	.	PUNCT
cana-5088	71	1	masand	masand	NOUN
cana-5088	71	2	et	et	PROPN
cana-5088	71	3	al	al	PROPN
cana-5088	71	4	.	.	PROPN
cana-5088	72	1	(	(	PUNCT
cana-5088	72	2	2021	2021	NUM
cana-5088	72	3	)	)	PUNCT
cana-5088	72	4	introduced	introduce	VERB
cana-5088	72	5	scrapnet	scrapnet	NOUN
cana-5088	72	6	,	,	PUNCT
cana-5088	72	7	a	a	DET
cana-5088	72	8	new	new	ADJ
cana-5088	72	9	,	,	PUNCT
cana-5088	72	10	larger	large	ADJ
cana-5088	72	11	,	,	PUNCT
cana-5088	72	12	and	and	CCONJ
cana-5088	72	13	more	more	ADV
cana-5088	72	14	diverse	diverse	ADJ
cana-5088	72	15	dataset	dataset	NOUN
cana-5088	72	16	for	for	ADP
cana-5088	72	17	trash	trash	NOUN
cana-5088	72	18	classification	classification	NOUN
cana-5088	72	19	,	,	PUNCT
cana-5088	72	20	addressing	address	VERB
cana-5088	72	21	the	the	DET
cana-5088	72	22	limitations	limitation	NOUN
cana-5088	72	23	of	of	ADP
cana-5088	72	24	existing	exist	VERB
cana-5088	72	25	datasets	dataset	NOUN
cana-5088	72	26	.	.	PUNCT
cana-5088	73	1	the	the	DET
cana-5088	73	2	authors	author	NOUN
cana-5088	73	3	compare	compare	VERB
cana-5088	73	4	various	various	ADJ
cana-5088	73	5	deep	deep	ADJ
cana-5088	73	6	learning	learning	NOUN
cana-5088	73	7	architectures	architecture	NOUN
cana-5088	73	8	,	,	PUNCT
cana-5088	73	9	including	include	VERB
cana-5088	73	10	resnet	resnet	NOUN
cana-5088	73	11	,	,	PUNCT
cana-5088	73	12	resnext	resnext	ADJ
cana-5088	73	13	,	,	PUNCT
cana-5088	73	14	and	and	CCONJ
cana-5088	73	15	efficientnet	efficientnet	NOUN
cana-5088	73	16	,	,	PUNCT
cana-5088	73	17	finding	find	VERB
cana-5088	73	18	that	that	SCONJ
cana-5088	73	19	a	a	DET
cana-5088	73	20	modified	modify	VERB
cana-5088	73	21	efficientnet	efficientnet	NOUN
cana-5088	73	22	b3	b3	PROPN
cana-5088	73	23	model	model	NOUN
cana-5088	73	24	achieves	achieve	VERB
cana-5088	73	25	state	state	NOUN
cana-5088	73	26	-	-	PUNCT
cana-5088	73	27	of	of	ADP
cana-5088	73	28	-	-	PUNCT
cana-5088	73	29	the	the	DET
cana-5088	73	30	-	-	PUNCT
cana-5088	73	31	art	art	NOUN
cana-5088	73	32	accuracy	accuracy	NOUN
cana-5088	73	33	(	(	PUNCT
cana-5088	73	34	92.87	92.87	NUM
cana-5088	73	35	%	%	NOUN
cana-5088	73	36	)	)	PUNCT
cana-5088	73	37	on	on	ADP
cana-5088	73	38	scrapnet	scrapnet	NOUN
cana-5088	73	39	and	and	CCONJ
cana-5088	73	40	98	98	NUM
cana-5088	73	41	%	%	NOUN
cana-5088	73	42	on	on	ADP
cana-5088	73	43	the	the	DET
cana-5088	73	44	standard	standard	ADJ
cana-5088	73	45	trashnet	trashnet	NOUN
cana-5088	73	46	dataset	dataset	NOUN
cana-5088	73	47	.	.	PUNCT
cana-5088	74	1	the	the	DET
cana-5088	74	2	study	study	NOUN
cana-5088	74	3	also	also	ADV
cana-5088	74	4	explores	explore	VERB
cana-5088	74	5	sub	sub	ADJ
cana-5088	74	6	-	-	ADJ
cana-5088	74	7	classifying	classify	VERB
cana-5088	74	8	plastic	plastic	ADJ
cana-5088	74	9	waste	waste	NOUN
cana-5088	74	10	as	as	ADP
cana-5088	74	11	recyclable	recyclable	ADJ
cana-5088	74	12	or	or	CCONJ
cana-5088	74	13	nonrecyclable	nonrecyclable	ADJ
cana-5088	74	14	using	use	VERB
cana-5088	74	15	deep	deep	ADJ
cana-5088	74	16	learning	learning	NOUN
cana-5088	74	17	,	,	PUNCT
cana-5088	74	18	achieving	achieve	VERB
cana-5088	74	19	89.21	89.21	NUM
cana-5088	74	20	%	%	NOUN
cana-5088	74	21	accuracy	accuracy	NOUN
cana-5088	74	22	.	.	PUNCT
cana-5088	75	1	the	the	DET
cana-5088	75	2	improved	improved	ADJ
cana-5088	75	3	accuracy	accuracy	NOUN
cana-5088	75	4	and	and	CCONJ
cana-5088	75	5	efficiency	efficiency	NOUN
cana-5088	75	6	of	of	ADP
cana-5088	75	7	the	the	DET
cana-5088	75	8	proposed	propose	VERB
cana-5088	75	9	model	model	NOUN
cana-5088	75	10	offer	offer	VERB
cana-5088	75	11	a	a	DET
cana-5088	75	12	viable	viable	ADJ
cana-5088	75	13	solution	solution	NOUN
cana-5088	75	14	for	for	ADP
cana-5088	75	15	the	the	DET
cana-5088	75	16	recycling	recycling	NOUN
cana-5088	75	17	industry	industry	NOUN
cana-5088	75	18	's	's	PART
cana-5088	75	19	challenges	challenge	NOUN
cana-5088	75	20	in	in	ADP
cana-5088	75	21	waste	waste	NOUN
cana-5088	75	22	classification	classification	NOUN
cana-5088	75	23	.	.	PUNCT
cana-5088	76	1	the	the	DET
cana-5088	76	2	scrapnet	scrapnet	NOUN
cana-5088	76	3	dataset	dataset	NOUN
cana-5088	76	4	is	be	AUX
cana-5088	76	5	intended	intend	VERB
cana-5088	76	6	to	to	PART
cana-5088	76	7	become	become	VERB
cana-5088	76	8	a	a	DET
cana-5088	76	9	new	new	ADJ
cana-5088	76	10	benchmark	benchmark	NOUN
cana-5088	76	11	for	for	ADP
cana-5088	76	12	future	future	ADJ
cana-5088	76	13	research	research	NOUN
cana-5088	76	14	in	in	ADP
cana-5088	76	15	this	this	DET
cana-5088	76	16	area	area	NOUN
cana-5088	76	17	.	.	PUNCT
cana-5088	77	1	yuan	yuan	NOUN
cana-5088	77	2	and	and	CCONJ
cana-5088	77	3	liu	liu	PROPN
cana-5088	77	4	(	(	PUNCT
cana-5088	77	5	2022	2022	NUM
cana-5088	77	6	)	)	PUNCT
cana-5088	77	7	proposed	propose	VERB
cana-5088	77	8	a	a	DET
cana-5088	77	9	novel	novel	ADJ
cana-5088	77	10	hybrid	hybrid	ADJ
cana-5088	77	11	deep	deep	ADJ
cana-5088	77	12	learning	learning	NOUN
cana-5088	77	13	model	model	NOUN
cana-5088	77	14	for	for	ADP
cana-5088	77	15	trash	trash	NOUN
cana-5088	77	16	classification	classification	NOUN
cana-5088	77	17	.	.	PUNCT
cana-5088	78	1	the	the	DET
cana-5088	78	2	model	model	NOUN
cana-5088	78	3	uses	use	VERB
cana-5088	78	4	a	a	DET
cana-5088	78	5	two	two	NUM
cana-5088	78	6	-	-	PUNCT
cana-5088	78	7	stream	stream	NOUN
cana-5088	78	8	approach	approach	NOUN
cana-5088	78	9	,	,	PUNCT
cana-5088	78	10	initially	initially	ADV
cana-5088	78	11	categorizing	categorize	VERB
cana-5088	78	12	images	image	NOUN
cana-5088	78	13	into	into	ADP
cana-5088	78	14	broader	broad	ADJ
cana-5088	78	15	groups	group	NOUN
cana-5088	78	16	(	(	PUNCT
cana-5088	78	17	metal	metal	NOUN
cana-5088	78	18	,	,	PUNCT
cana-5088	78	19	paper	paper	NOUN
cana-5088	78	20	,	,	PUNCT
cana-5088	78	21	plastic	plastic	NOUN
cana-5088	78	22	;	;	PUNCT
cana-5088	78	23	or	or	CCONJ
cana-5088	78	24	cardboard	cardboard	NOUN
cana-5088	78	25	,	,	PUNCT
cana-5088	78	26	glass	glass	NOUN
cana-5088	78	27	,	,	PUNCT
cana-5088	78	28	trash	trash	NOUN
cana-5088	78	29	)	)	PUNCT
cana-5088	78	30	before	before	ADP
cana-5088	78	31	final	final	ADJ
cana-5088	78	32	classification	classification	NOUN
cana-5088	78	33	.	.	PUNCT
cana-5088	79	1	it	it	PRON
cana-5088	79	2	leverages	leverage	VERB
cana-5088	79	3	transfer	transfer	NOUN
cana-5088	79	4	learning	learning	NOUN
cana-5088	79	5	from	from	ADP
cana-5088	79	6	a	a	DET
cana-5088	79	7	pre	pre	ADJ
cana-5088	79	8	-	-	ADJ
cana-5088	79	9	trained	train	VERB
cana-5088	79	10	resnext	resnext	NOUN
cana-5088	79	11	model	model	NOUN
cana-5088	79	12	and	and	CCONJ
cana-5088	79	13	achieves	achieve	VERB
cana-5088	79	14	a	a	DET
cana-5088	79	15	98.5	98.5	NUM
cana-5088	79	16	%	%	NOUN
cana-5088	79	17	accuracy	accuracy	NOUN
cana-5088	79	18	on	on	ADP
cana-5088	79	19	the	the	DET
cana-5088	79	20	trashnet	trashnet	NOUN
cana-5088	79	21	dataset	dataset	NOUN
cana-5088	79	22	,	,	PUNCT
cana-5088	79	23	surpassing	surpass	VERB
cana-5088	79	24	existing	exist	VERB
cana-5088	79	25	methods	method	NOUN
cana-5088	79	26	.	.	PUNCT
cana-5088	80	1	the	the	DET
cana-5088	80	2	authors	author	NOUN
cana-5088	80	3	analyze	analyze	VERB
cana-5088	80	4	the	the	DET
cana-5088	80	5	model	model	NOUN
cana-5088	80	6	's	's	PART
cana-5088	80	7	performance	performance	NOUN
cana-5088	80	8	using	use	VERB
cana-5088	80	9	class	class	NOUN
cana-5088	80	10	activation	activation	NOUN
cana-5088	80	11	maps	map	NOUN
cana-5088	80	12	,	,	PUNCT
cana-5088	80	13	explaining	explain	VERB
cana-5088	80	14	its	its	PRON
cana-5088	80	15	superior	superior	ADJ
cana-5088	80	16	accuracy	accuracy	NOUN
cana-5088	80	17	.	.	PUNCT
cana-5088	81	1	chazhoor	chazhoor	PROPN
cana-5088	81	2	et	et	PROPN
cana-5088	81	3	al	al	PROPN
cana-5088	81	4	.	.	PROPN
cana-5088	82	1	(	(	PUNCT
cana-5088	82	2	2022	2022	NUM
cana-5088	82	3	)	)	PUNCT
cana-5088	82	4	benchmarked	benchmarke	VERB
cana-5088	82	5	six	six	NUM
cana-5088	82	6	pre	pre	ADJ
cana-5088	82	7	-	-	ADJ
cana-5088	82	8	trained	train	VERB
cana-5088	82	9	cnn	cnn	PROPN
cana-5088	82	10	architectures	architecture	NOUN
cana-5088	82	11	:	:	PUNCT
cana-5088	82	12	alexnet	alexnet	ADJ
cana-5088	82	13	,	,	PUNCT
cana-5088	82	14	resnet50	resnet50	NOUN
cana-5088	82	15	,	,	PUNCT
cana-5088	82	16	resnext	resnext	ADJ
cana-5088	82	17	,	,	PUNCT
cana-5088	82	18	squeezenet	squeezenet	NOUN
cana-5088	82	19	,	,	PUNCT
cana-5088	82	20	mobilenetv2	mobilenetv2	PROPN
cana-5088	82	21	,	,	PUNCT
cana-5088	82	22	and	and	CCONJ
cana-5088	82	23	densenet	densenet	NOUN
cana-5088	82	24	for	for	ADP
cana-5088	82	25	classifying	classify	VERB
cana-5088	82	26	plastic	plastic	ADJ
cana-5088	82	27	waste	waste	NOUN
cana-5088	82	28	types	type	NOUN
cana-5088	82	29	based	base	VERB
cana-5088	82	30	on	on	ADP
cana-5088	82	31	their	their	PRON
cana-5088	82	32	resin	resin	NOUN
cana-5088	82	33	codes	code	NOUN
cana-5088	82	34	using	use	VERB
cana-5088	82	35	transfer	transfer	NOUN
cana-5088	82	36	learning	learning	NOUN
cana-5088	82	37	.	.	PUNCT
cana-5088	83	1	the	the	DET
cana-5088	83	2	study	study	NOUN
cana-5088	83	3	utilized	utilize	VERB
cana-5088	83	4	the	the	DET
cana-5088	83	5	wadaba	wadaba	NOUN
cana-5088	83	6	dataset	dataset	NOUN
cana-5088	83	7	,	,	PUNCT
cana-5088	83	8	addressing	address	VERB
cana-5088	83	9	class	class	NOUN
cana-5088	83	10	imbalance	imbalance	NOUN
cana-5088	83	11	through	through	ADP
cana-5088	83	12	under	under	ADV
cana-5088	83	13	-	-	PUNCT
cana-5088	83	14	sampling	sampling	NOUN
cana-5088	83	15	.	.	PUNCT
cana-5088	84	1	resnext	resnext	NOUN
cana-5088	84	2	achieves	achieve	VERB
cana-5088	84	3	the	the	DET
cana-5088	84	4	highest	high	ADJ
cana-5088	84	5	accuracy	accuracy	NOUN
cana-5088	84	6	(	(	PUNCT
cana-5088	84	7	87.44	87.44	NUM
cana-5088	84	8	%	%	NOUN
cana-5088	84	9	)	)	PUNCT
cana-5088	84	10	within	within	ADP
cana-5088	84	11	13	13	NUM
cana-5088	84	12	minutes	minute	NOUN
cana-5088	84	13	.	.	PUNCT
cana-5088	85	1	mobilenetv2	mobilenetv2	PROPN
cana-5088	85	2	demonstrated	demonstrate	VERB
cana-5088	85	3	comparable	comparable	ADJ
cana-5088	85	4	accuracy	accuracy	NOUN
cana-5088	85	5	with	with	ADP
cana-5088	85	6	faster	fast	ADJ
cana-5088	85	7	training	training	NOUN
cana-5088	85	8	.	.	PUNCT
cana-5088	86	1	alexnet	alexnet	PROPN
cana-5088	86	2	and	and	CCONJ
cana-5088	86	3	squeezenet	squeezenet	NOUN
cana-5088	86	4	exhibited	exhibit	VERB
cana-5088	86	5	lower	low	ADJ
cana-5088	86	6	accuracy	accuracy	NOUN
cana-5088	86	7	and	and	CCONJ
cana-5088	86	8	struggled	struggle	VERB
cana-5088	86	9	with	with	ADP
cana-5088	86	10	validation	validation	NOUN
cana-5088	86	11	loss	loss	NOUN
cana-5088	86	12	reduction	reduction	NOUN
cana-5088	86	13	.	.	PUNCT
cana-5088	87	1	the	the	DET
cana-5088	87	2	models	model	NOUN
cana-5088	87	3	were	be	AUX
cana-5088	87	4	evaluated	evaluate	VERB
cana-5088	87	5	based	base	VERB
cana-5088	87	6	on	on	ADP
cana-5088	87	7	accuracy	accuracy	NOUN
cana-5088	87	8	,	,	PUNCT
cana-5088	87	9	loss	loss	NOUN
cana-5088	87	10	,	,	PUNCT
cana-5088	87	11	area	area	NOUN
cana-5088	87	12	under	under	ADP
cana-5088	87	13	curve	curve	NOUN
cana-5088	87	14	(	(	PUNCT
cana-5088	87	15	auc	auc	NOUN
cana-5088	87	16	)	)	PUNCT
cana-5088	87	17	,	,	PUNCT
cana-5088	87	18	and	and	CCONJ
cana-5088	87	19	receiver	receiver	NOUN
cana-5088	87	20	operating	operate	VERB
cana-5088	87	21	characteristic	characteristic	NOUN
cana-5088	87	22	(	(	PUNCT
cana-5088	87	23	roc	roc	PROPN
cana-5088	87	24	)	)	PUNCT
cana-5088	87	25	curve	curve	NOUN
cana-5088	87	26	.	.	PUNCT
cana-5088	88	1	dawood	dawood	PROPN
cana-5088	88	2	(	(	PUNCT
cana-5088	88	3	2023	2023	NUM
cana-5088	88	4	)	)	PUNCT
cana-5088	88	5	explored	explore	VERB
cana-5088	88	6	the	the	DET
cana-5088	88	7	application	application	NOUN
cana-5088	88	8	of	of	ADP
cana-5088	88	9	deep	deep	ADJ
cana-5088	88	10	convolutional	convolutional	ADJ
cana-5088	88	11	neural	neural	ADJ
cana-5088	88	12	networks	network	NOUN
cana-5088	88	13	(	(	PUNCT
cana-5088	88	14	dcnns	dcnns	ADJ
cana-5088	88	15	)	)	PUNCT
cana-5088	88	16	,	,	PUNCT
cana-5088	88	17	focusing	focus	VERB
cana-5088	88	18	on	on	ADP
cana-5088	88	19	cnn	cnn	PROPN
cana-5088	88	20	and	and	CCONJ
cana-5088	88	21	vgg-16	vgg-16	NOUN
cana-5088	88	22	models	model	NOUN
cana-5088	88	23	with	with	ADP
cana-5088	88	24	transfer	transfer	NOUN
cana-5088	88	25	learning	learning	NOUN
cana-5088	88	26	,	,	PUNCT
cana-5088	88	27	to	to	PART
cana-5088	88	28	enhance	enhance	VERB
cana-5088	88	29	the	the	DET
cana-5088	88	30	accuracy	accuracy	NOUN
cana-5088	88	31	of	of	ADP
cana-5088	88	32	garbage	garbage	NOUN
cana-5088	88	33	classification	classification	NOUN
cana-5088	88	34	for	for	ADP
cana-5088	88	35	sustainable	sustainable	ADJ
cana-5088	88	36	waste	waste	NOUN
cana-5088	88	37	management	management	NOUN
cana-5088	88	38	.	.	PUNCT
cana-5088	89	1	utilizing	utilize	VERB
cana-5088	89	2	the	the	DET
cana-5088	89	3	trashnet	trashnet	NOUN
cana-5088	89	4	dataset	dataset	NOUN
cana-5088	89	5	,	,	PUNCT
cana-5088	89	6	the	the	DET
cana-5088	89	7	research	research	NOUN
cana-5088	89	8	evaluates	evaluate	VERB
cana-5088	89	9	the	the	DET
cana-5088	89	10	performance	performance	NOUN
cana-5088	89	11	of	of	ADP
cana-5088	89	12	these	these	DET
cana-5088	89	13	models	model	NOUN
cana-5088	89	14	in	in	ADP
cana-5088	89	15	terms	term	NOUN
cana-5088	89	16	of	of	ADP
cana-5088	89	17	accuracy	accuracy	NOUN
cana-5088	89	18	,	,	PUNCT
cana-5088	89	19	loss	loss	NOUN
cana-5088	89	20	,	,	PUNCT
cana-5088	89	21	and	and	CCONJ
cana-5088	89	22	computational	computational	ADJ
cana-5088	89	23	efficiency	efficiency	NOUN
cana-5088	89	24	.	.	PUNCT
cana-5088	90	1	the	the	DET
cana-5088	90	2	results	result	NOUN
cana-5088	90	3	indicate	indicate	VERB
cana-5088	90	4	that	that	SCONJ
cana-5088	90	5	while	while	SCONJ
cana-5088	90	6	vgg-16	vgg-16	NOUN
cana-5088	90	7	achieves	achieve	VERB
cana-5088	90	8	higher	high	ADJ
cana-5088	90	9	training	training	NOUN
cana-5088	90	10	accuracy	accuracy	NOUN
cana-5088	90	11	(	(	PUNCT
cana-5088	90	12	99.55	99.55	NUM
cana-5088	90	13	%	%	NOUN
cana-5088	90	14	)	)	PUNCT
cana-5088	90	15	compared	compare	VERB
cana-5088	90	16	to	to	ADP
cana-5088	90	17	cnn	cnn	PROPN
cana-5088	90	18	(	(	PUNCT
cana-5088	90	19	96.29	96.29	NUM
cana-5088	90	20	%	%	NOUN
cana-5088	90	21	)	)	PUNCT
cana-5088	90	22	,	,	PUNCT
cana-5088	90	23	it	it	PRON
cana-5088	90	24	comes	come	VERB
cana-5088	90	25	at	at	ADP
cana-5088	90	26	the	the	DET
cana-5088	90	27	cost	cost	NOUN
cana-5088	90	28	of	of	ADP
cana-5088	90	29	increased	increase	VERB
cana-5088	90	30	computational	computational	ADJ
cana-5088	90	31	complexity	complexity	NOUN
cana-5088	90	32	.	.	PUNCT
cana-5088	91	1	in	in	ADP
cana-5088	91	2	contrast	contrast	NOUN
cana-5088	91	3	,	,	PUNCT
cana-5088	91	4	cnn	cnn	PROPN
cana-5088	91	5	provides	provide	VERB
cana-5088	91	6	a	a	DET
cana-5088	91	7	balanced	balanced	ADJ
cana-5088	91	8	approach	approach	NOUN
cana-5088	91	9	,	,	PUNCT
cana-5088	91	10	offering	offer	VERB
cana-5088	91	11	competitive	competitive	ADJ
cana-5088	91	12	accuracy	accuracy	NOUN
cana-5088	91	13	with	with	ADP
cana-5088	91	14	greater	great	ADJ
cana-5088	91	15	efficiency	efficiency	NOUN
cana-5088	91	16	.	.	PUNCT
cana-5088	92	1	this	this	DET
cana-5088	92	2	study	study	NOUN
cana-5088	92	3	aims	aim	VERB
cana-5088	92	4	to	to	PART
cana-5088	92	5	advance	advance	VERB
cana-5088	92	6	more	more	ADV
cana-5088	92	7	effective	effective	ADJ
cana-5088	92	8	and	and	CCONJ
cana-5088	92	9	sustainable	sustainable	ADJ
cana-5088	92	10	waste	waste	NOUN
cana-5088	92	11	sorting	sort	VERB
cana-5088	92	12	solutions	solution	NOUN
cana-5088	92	13	by	by	ADP
cana-5088	92	14	addressing	address	VERB
cana-5088	92	15	the	the	DET
cana-5088	92	16	trade	trade	NOUN
cana-5088	92	17	-	-	PUNCT
cana-5088	92	18	offs	off	NOUN
cana-5088	92	19	between	between	ADP
cana-5088	92	20	accuracy	accuracy	NOUN
cana-5088	92	21	and	and	CCONJ
cana-5088	92	22	computational	computational	ADJ
cana-5088	92	23	requirements	requirement	NOUN
cana-5088	92	24	.	.	PUNCT
cana-5088	93	1	poudel	poudel	NOUN
cana-5088	93	2	and	and	CCONJ
cana-5088	93	3	poudyal	poudyal	ADJ
cana-5088	93	4	(	(	PUNCT
cana-5088	93	5	2023	2023	NUM
cana-5088	93	6	)	)	PUNCT
cana-5088	93	7	explored	explore	VERB
cana-5088	93	8	cnns	cnn	NOUN
cana-5088	93	9	and	and	CCONJ
cana-5088	93	10	transfer	transfer	NOUN
cana-5088	93	11	learning	learning	NOUN
cana-5088	93	12	to	to	PART
cana-5088	93	13	classify	classify	VERB
cana-5088	93	14	waste	waste	NOUN
cana-5088	93	15	images	image	NOUN
cana-5088	93	16	into	into	ADP
cana-5088	93	17	seven	seven	NUM
cana-5088	93	18	categories	category	NOUN
cana-5088	93	19	:	:	PUNCT
cana-5088	93	20	cardboard	cardboard	NOUN
cana-5088	93	21	,	,	PUNCT
cana-5088	93	22	glass	glass	NOUN
cana-5088	93	23	,	,	PUNCT
cana-5088	93	24	metal	metal	NOUN
cana-5088	93	25	,	,	PUNCT
cana-5088	93	26	organic	organic	ADJ
cana-5088	93	27	,	,	PUNCT
cana-5088	93	28	paper	paper	NOUN
cana-5088	93	29	,	,	PUNCT
cana-5088	93	30	plastic	plastic	NOUN
cana-5088	93	31	,	,	PUNCT
cana-5088	93	32	and	and	CCONJ
cana-5088	93	33	trash	trash	NOUN
cana-5088	93	34	.	.	PUNCT
cana-5088	94	1	the	the	DET
cana-5088	94	2	study	study	NOUN
cana-5088	94	3	utilized	utilize	VERB
cana-5088	94	4	the	the	DET
cana-5088	94	5	stanford	stanford	PROPN
cana-5088	94	6	communications	communication	NOUN
cana-5088	94	7	on	on	ADP
cana-5088	94	8	applied	apply	VERB
cana-5088	94	9	nonlinear	nonlinear	ADJ
cana-5088	94	10	analysis	analysis	NOUN
cana-5088	94	11	issn	issn	NOUN
cana-5088	94	12	:	:	PUNCT
cana-5088	94	13	1074	1074	NUM
cana-5088	94	14	-	-	PUNCT
cana-5088	94	15	133x	133x	NUM
cana-5088	94	16	vol	vol	NOUN
cana-5088	94	17	32	32	NUM
cana-5088	94	18	no	no	NOUN
cana-5088	94	19	.	.	PUNCT
cana-5088	95	1	icmasd	icmasd	NOUN
cana-5088	95	2	(	(	PUNCT
cana-5088	95	3	2025	2025	NUM
cana-5088	95	4	)	)	PUNCT
cana-5088	95	5	591	591	NUM
cana-5088	95	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	95	7	trashnet	trashnet	NOUN
cana-5088	95	8	dataset	dataset	NOUN
cana-5088	95	9	,	,	PUNCT
cana-5088	95	10	augmented	augment	VERB
cana-5088	95	11	with	with	ADP
cana-5088	95	12	an	an	DET
cana-5088	95	13	organic	organic	ADJ
cana-5088	95	14	class	class	NOUN
cana-5088	95	15	,	,	PUNCT
cana-5088	95	16	totaling	total	VERB
cana-5088	95	17	3242	3242	NUM
cana-5088	95	18	images	image	NOUN
cana-5088	95	19	for	for	ADP
cana-5088	95	20	training	training	NOUN
cana-5088	95	21	and	and	CCONJ
cana-5088	95	22	validation	validation	NOUN
cana-5088	95	23	.	.	PUNCT
cana-5088	96	1	the	the	DET
cana-5088	96	2	researchers	researcher	NOUN
cana-5088	96	3	compared	compare	VERB
cana-5088	96	4	the	the	DET
cana-5088	96	5	performance	performance	NOUN
cana-5088	96	6	of	of	ADP
cana-5088	96	7	several	several	ADJ
cana-5088	96	8	pre	pre	ADJ
cana-5088	96	9	-	-	ADJ
cana-5088	96	10	trained	train	VERB
cana-5088	96	11	cnn	cnn	PROPN
cana-5088	96	12	models	model	NOUN
cana-5088	96	13	(	(	PUNCT
cana-5088	96	14	inceptionv3	inceptionv3	NOUN
cana-5088	96	15	,	,	PUNCT
cana-5088	96	16	inceptionresnetv2	inceptionresnetv2	PROPN
cana-5088	96	17	,	,	PUNCT
cana-5088	96	18	xception	xception	PROPN
cana-5088	96	19	,	,	PUNCT
cana-5088	96	20	vgg19	vgg19	PROPN
cana-5088	96	21	,	,	PUNCT
cana-5088	96	22	mobilenet	mobilenet	NOUN
cana-5088	96	23	,	,	PUNCT
cana-5088	96	24	resnet50	resnet50	NOUN
cana-5088	96	25	,	,	PUNCT
cana-5088	96	26	and	and	CCONJ
cana-5088	96	27	densenet201	densenet201	PROPN
cana-5088	96	28	)	)	PUNCT
cana-5088	96	29	,	,	PUNCT
cana-5088	96	30	finding	find	VERB
cana-5088	96	31	that	that	SCONJ
cana-5088	96	32	densenet201	densenet201	PROPN
cana-5088	96	33	achieved	achieve	VERB
cana-5088	96	34	the	the	DET
cana-5088	96	35	highest	high	ADJ
cana-5088	96	36	validation	validation	NOUN
cana-5088	96	37	accuracy	accuracy	NOUN
cana-5088	96	38	(	(	PUNCT
cana-5088	96	39	95.05	95.05	NUM
cana-5088	96	40	%	%	NOUN
cana-5088	96	41	)	)	PUNCT
cana-5088	96	42	and	and	CCONJ
cana-5088	96	43	performed	perform	VERB
cana-5088	96	44	well	well	ADV
cana-5088	96	45	in	in	ADP
cana-5088	96	46	classifying	classify	VERB
cana-5088	96	47	most	most	ADJ
cana-5088	96	48	waste	waste	NOUN
cana-5088	96	49	categories	category	NOUN
cana-5088	96	50	.	.	PUNCT
cana-5088	97	1	their	their	PRON
cana-5088	97	2	work	work	NOUN
cana-5088	97	3	aims	aim	VERB
cana-5088	97	4	to	to	PART
cana-5088	97	5	improve	improve	VERB
cana-5088	97	6	waste	waste	NOUN
cana-5088	97	7	management	management	NOUN
cana-5088	97	8	efficiency	efficiency	NOUN
cana-5088	97	9	by	by	ADP
cana-5088	97	10	automating	automate	VERB
cana-5088	97	11	waste	waste	NOUN
cana-5088	97	12	sorting	sorting	NOUN
cana-5088	97	13	,	,	PUNCT
cana-5088	97	14	ultimately	ultimately	ADV
cana-5088	97	15	contributing	contribute	VERB
cana-5088	97	16	to	to	ADP
cana-5088	97	17	a	a	DET
cana-5088	97	18	cleaner	clean	ADJ
cana-5088	97	19	environment	environment	NOUN
cana-5088	97	20	.	.	PUNCT
cana-5088	98	1	sayed	say	VERB
cana-5088	98	2	et	et	PROPN
cana-5088	98	3	al	al	PROPN
cana-5088	98	4	.	.	PROPN
cana-5088	99	1	(	(	PUNCT
cana-5088	99	2	2024	2024	NUM
cana-5088	99	3	)	)	PUNCT
cana-5088	99	4	introduced	introduce	VERB
cana-5088	99	5	an	an	DET
cana-5088	99	6	intelligent	intelligent	ADJ
cana-5088	99	7	waste	waste	NOUN
cana-5088	99	8	classification	classification	NOUN
cana-5088	99	9	model	model	NOUN
cana-5088	99	10	built	build	VERB
cana-5088	99	11	on	on	ADP
cana-5088	99	12	the	the	DET
cana-5088	99	13	inceptionv3	inceptionv3	NOUN
cana-5088	99	14	deep	deep	ADJ
cana-5088	99	15	learning	learning	NOUN
cana-5088	99	16	architecture	architecture	NOUN
cana-5088	99	17	,	,	PUNCT
cana-5088	99	18	enhanced	enhance	VERB
cana-5088	99	19	with	with	ADP
cana-5088	99	20	a	a	DET
cana-5088	99	21	multi	multi	ADJ
cana-5088	99	22	-	-	ADJ
cana-5088	99	23	objective	objective	ADJ
cana-5088	99	24	beluga	beluga	ADJ
cana-5088	99	25	whale	whale	NOUN
cana-5088	99	26	optimization	optimization	NOUN
cana-5088	99	27	algorithm	algorithm	NOUN
cana-5088	99	28	for	for	ADP
cana-5088	99	29	hyperparameter	hyperparameter	NOUN
cana-5088	99	30	tuning	tune	VERB
cana-5088	99	31	.	.	PUNCT
cana-5088	100	1	the	the	DET
cana-5088	100	2	model	model	NOUN
cana-5088	100	3	employed	employ	VERB
cana-5088	100	4	random	random	ADJ
cana-5088	100	5	oversampling	oversampling	NOUN
cana-5088	100	6	and	and	CCONJ
cana-5088	100	7	data	datum	NOUN
cana-5088	100	8	augmentation	augmentation	NOUN
cana-5088	100	9	techniques	technique	NOUN
cana-5088	100	10	to	to	PART
cana-5088	100	11	address	address	VERB
cana-5088	100	12	the	the	DET
cana-5088	100	13	class	class	NOUN
cana-5088	100	14	imbalance	imbalance	NOUN
cana-5088	100	15	in	in	ADP
cana-5088	100	16	the	the	DET
cana-5088	100	17	trashnet	trashnet	NOUN
cana-5088	100	18	dataset	dataset	NOUN
cana-5088	100	19	.	.	PUNCT
cana-5088	101	1	it	it	PRON
cana-5088	101	2	achieved	achieve	VERB
cana-5088	101	3	a	a	DET
cana-5088	101	4	remarkable	remarkable	ADJ
cana-5088	101	5	accuracy	accuracy	NOUN
cana-5088	101	6	of	of	ADP
cana-5088	101	7	97.75	97.75	NUM
cana-5088	101	8	%	%	NOUN
cana-5088	101	9	in	in	ADP
cana-5088	101	10	waste	waste	NOUN
cana-5088	101	11	material	material	NOUN
cana-5088	101	12	classification	classification	NOUN
cana-5088	101	13	,	,	PUNCT
cana-5088	101	14	outperforming	outperform	VERB
cana-5088	101	15	existing	exist	VERB
cana-5088	101	16	state	state	NOUN
cana-5088	101	17	-	-	PUNCT
cana-5088	101	18	of	of	ADP
cana-5088	101	19	-	-	PUNCT
cana-5088	101	20	the	the	DET
cana-5088	101	21	-	-	PUNCT
cana-5088	101	22	art	art	NOUN
cana-5088	101	23	models	model	NOUN
cana-5088	101	24	.	.	PUNCT
cana-5088	102	1	a	a	DET
cana-5088	102	2	comprehensive	comprehensive	ADJ
cana-5088	102	3	evaluation	evaluation	NOUN
cana-5088	102	4	of	of	ADP
cana-5088	102	5	the	the	DET
cana-5088	102	6	model	model	NOUN
cana-5088	102	7	's	's	PART
cana-5088	102	8	performance	performance	NOUN
cana-5088	102	9	and	and	CCONJ
cana-5088	102	10	components	component	NOUN
cana-5088	102	11	highlights	highlight	NOUN
cana-5088	102	12	substantial	substantial	ADJ
cana-5088	102	13	improvements	improvement	NOUN
cana-5088	102	14	in	in	ADP
cana-5088	102	15	efficiency	efficiency	NOUN
cana-5088	102	16	and	and	CCONJ
cana-5088	102	17	accuracy	accuracy	NOUN
cana-5088	102	18	,	,	PUNCT
cana-5088	102	19	contributing	contribute	VERB
cana-5088	102	20	to	to	ADP
cana-5088	102	21	advancements	advancement	NOUN
cana-5088	102	22	in	in	ADP
cana-5088	102	23	sustainable	sustainable	ADJ
cana-5088	102	24	waste	waste	NOUN
cana-5088	102	25	management	management	NOUN
cana-5088	102	26	practices	practice	NOUN
cana-5088	102	27	.	.	PUNCT
cana-5088	103	1	the	the	DET
cana-5088	103	2	literature	literature	PROPN
cana-5088	103	3	review	review	NOUN
cana-5088	103	4	highlighted	highlight	VERB
cana-5088	103	5	the	the	DET
cana-5088	103	6	potential	potential	NOUN
cana-5088	103	7	of	of	ADP
cana-5088	103	8	pre	pre	ADJ
cana-5088	103	9	-	-	ADJ
cana-5088	103	10	trained	train	VERB
cana-5088	103	11	cnn	cnn	PROPN
cana-5088	103	12	models	model	NOUN
cana-5088	103	13	for	for	ADP
cana-5088	103	14	waste	waste	NOUN
cana-5088	103	15	classification	classification	NOUN
cana-5088	103	16	tasks	task	NOUN
cana-5088	103	17	,	,	PUNCT
cana-5088	103	18	demonstrating	demonstrate	VERB
cana-5088	103	19	their	their	PRON
cana-5088	103	20	ability	ability	NOUN
cana-5088	103	21	to	to	PART
cana-5088	103	22	achieve	achieve	VERB
cana-5088	103	23	impressive	impressive	ADJ
cana-5088	103	24	accuracy	accuracy	NOUN
cana-5088	103	25	in	in	ADP
cana-5088	103	26	categorizing	categorize	VERB
cana-5088	103	27	waste	waste	NOUN
cana-5088	103	28	materials	material	NOUN
cana-5088	103	29	.	.	PUNCT
cana-5088	104	1	however	however	ADV
cana-5088	104	2	,	,	PUNCT
cana-5088	104	3	most	most	ADJ
cana-5088	104	4	existing	exist	VERB
cana-5088	104	5	studies	study	NOUN
cana-5088	104	6	predominantly	predominantly	ADV
cana-5088	104	7	rely	rely	VERB
cana-5088	104	8	on	on	ADP
cana-5088	104	9	datasets	dataset	NOUN
cana-5088	104	10	of	of	ADP
cana-5088	104	11	six	six	NUM
cana-5088	104	12	waste	waste	NOUN
cana-5088	104	13	categories	category	NOUN
cana-5088	104	14	in	in	ADP
cana-5088	104	15	pristine	pristine	ADJ
cana-5088	104	16	forms	form	NOUN
cana-5088	104	17	,	,	PUNCT
cana-5088	104	18	limiting	limit	VERB
cana-5088	104	19	their	their	PRON
cana-5088	104	20	applicability	applicability	NOUN
cana-5088	104	21	to	to	ADP
cana-5088	104	22	real	real	ADJ
cana-5088	104	23	-	-	PUNCT
cana-5088	104	24	world	world	NOUN
cana-5088	104	25	scenarios	scenario	NOUN
cana-5088	104	26	and	and	CCONJ
cana-5088	104	27	affecting	affect	VERB
cana-5088	104	28	model	model	NOUN
cana-5088	104	29	generalization	generalization	NOUN
cana-5088	104	30	across	across	ADP
cana-5088	104	31	diverse	diverse	ADJ
cana-5088	104	32	waste	waste	NOUN
cana-5088	104	33	categories	category	NOUN
cana-5088	104	34	.	.	PUNCT
cana-5088	105	1	to	to	PART
cana-5088	105	2	address	address	VERB
cana-5088	105	3	these	these	DET
cana-5088	105	4	gaps	gap	NOUN
cana-5088	105	5	,	,	PUNCT
cana-5088	105	6	this	this	DET
cana-5088	105	7	research	research	NOUN
cana-5088	105	8	utilizes	utilize	VERB
cana-5088	105	9	techniques	technique	NOUN
cana-5088	105	10	such	such	ADJ
cana-5088	105	11	as	as	ADP
cana-5088	105	12	transfer	transfer	NOUN
cana-5088	105	13	learning	learning	NOUN
cana-5088	105	14	,	,	PUNCT
cana-5088	105	15	fine	fine	ADV
cana-5088	105	16	-	-	PUNCT
cana-5088	105	17	tuning	tuning	NOUN
cana-5088	105	18	,	,	PUNCT
cana-5088	105	19	and	and	CCONJ
cana-5088	105	20	data	datum	NOUN
cana-5088	105	21	augmentation	augmentation	NOUN
cana-5088	105	22	to	to	PART
cana-5088	105	23	improve	improve	VERB
cana-5088	105	24	model	model	NOUN
cana-5088	105	25	performance	performance	NOUN
cana-5088	105	26	and	and	CCONJ
cana-5088	105	27	robustness	robustness	NOUN
cana-5088	105	28	.	.	PUNCT
cana-5088	106	1	in	in	ADP
cana-5088	106	2	addition	addition	NOUN
cana-5088	106	3	,	,	PUNCT
cana-5088	106	4	the	the	DET
cana-5088	106	5	study	study	NOUN
cana-5088	106	6	utilizes	utilize	VERB
cana-5088	106	7	a	a	DET
cana-5088	106	8	dataset	dataset	NOUN
cana-5088	106	9	comprising	comprise	VERB
cana-5088	106	10	real	real	ADJ
cana-5088	106	11	waste	waste	NOUN
cana-5088	106	12	images	image	NOUN
cana-5088	106	13	from	from	ADP
cana-5088	106	14	actual	actual	ADJ
cana-5088	106	15	landfill	landfill	NOUN
cana-5088	106	16	environments	environment	NOUN
cana-5088	106	17	to	to	PART
cana-5088	106	18	enhance	enhance	VERB
cana-5088	106	19	model	model	NOUN
cana-5088	106	20	applicability	applicability	NOUN
cana-5088	106	21	in	in	ADP
cana-5088	106	22	practical	practical	ADJ
cana-5088	106	23	scenarios	scenario	NOUN
cana-5088	106	24	.	.	PUNCT
cana-5088	107	1	3	3	X
cana-5088	107	2	.	.	X
cana-5088	107	3	research	research	NOUN
cana-5088	107	4	methodology	methodology	NOUN
cana-5088	107	5	this	this	DET
cana-5088	107	6	section	section	NOUN
cana-5088	107	7	outlines	outline	VERB
cana-5088	107	8	a	a	DET
cana-5088	107	9	comprehensive	comprehensive	ADJ
cana-5088	107	10	methodology	methodology	NOUN
cana-5088	107	11	encompassing	encompass	VERB
cana-5088	107	12	dataset	dataset	NOUN
cana-5088	107	13	details	detail	NOUN
cana-5088	107	14	,	,	PUNCT
cana-5088	107	15	preprocessing	preprocesse	VERB
cana-5088	107	16	techniques	technique	NOUN
cana-5088	107	17	,	,	PUNCT
cana-5088	107	18	and	and	CCONJ
cana-5088	107	19	the	the	DET
cana-5088	107	20	architectural	architectural	ADJ
cana-5088	107	21	specifications	specification	NOUN
cana-5088	107	22	of	of	ADP
cana-5088	107	23	the	the	DET
cana-5088	107	24	three	three	NUM
cana-5088	107	25	cnn	cnn	NOUN
cana-5088	107	26	based	base	VERB
cana-5088	107	27	pre	pre	ADJ
cana-5088	107	28	-	-	ADJ
cana-5088	107	29	trained	train	VERB
cana-5088	107	30	models	model	NOUN
cana-5088	107	31	utilized	utilize	VERB
cana-5088	107	32	in	in	ADP
cana-5088	107	33	this	this	DET
cana-5088	107	34	study	study	NOUN
cana-5088	107	35	.	.	PUNCT
cana-5088	108	1	the	the	DET
cana-5088	108	2	approach	approach	NOUN
cana-5088	108	3	leverages	leverage	VERB
cana-5088	108	4	transfer	transfer	NOUN
cana-5088	108	5	learning	learn	VERB
cana-5088	108	6	to	to	PART
cana-5088	108	7	enhance	enhance	VERB
cana-5088	108	8	model	model	NOUN
cana-5088	108	9	performance	performance	NOUN
cana-5088	108	10	,	,	PUNCT
cana-5088	108	11	ensuring	ensure	VERB
cana-5088	108	12	efficient	efficient	ADJ
cana-5088	108	13	and	and	CCONJ
cana-5088	108	14	accurate	accurate	ADJ
cana-5088	108	15	waste	waste	NOUN
cana-5088	108	16	classification	classification	NOUN
cana-5088	108	17	.	.	PUNCT
cana-5088	109	1	3.1	3.1	NUM
cana-5088	109	2	dataset	dataset	ADJ
cana-5088	109	3	description	description	NOUN
cana-5088	109	4	for	for	ADP
cana-5088	109	5	this	this	DET
cana-5088	109	6	study	study	NOUN
cana-5088	109	7	,	,	PUNCT
cana-5088	109	8	we	we	PRON
cana-5088	109	9	employed	employ	VERB
cana-5088	109	10	the	the	DET
cana-5088	109	11	realwaste	realwaste	ADJ
cana-5088	109	12	image	image	NOUN
cana-5088	109	13	classification	classification	NOUN
cana-5088	109	14	dataset	dataset	NOUN
cana-5088	109	15	created	create	VERB
cana-5088	109	16	by	by	ADP
cana-5088	109	17	(	(	PUNCT
cana-5088	109	18	sam	sam	PROPN
cana-5088	109	19	single	single	ADJ
cana-5088	109	20	,	,	PUNCT
cana-5088	109	21	2023	2023	NUM
cana-5088	109	22	)	)	PUNCT
cana-5088	109	23	,	,	PUNCT
cana-5088	109	24	which	which	PRON
cana-5088	109	25	contains	contain	VERB
cana-5088	109	26	4,752	4,752	NUM
cana-5088	109	27	high	high	ADJ
cana-5088	109	28	-	-	PUNCT
cana-5088	109	29	resolution	resolution	NOUN
cana-5088	109	30	(	(	PUNCT
cana-5088	109	31	524x524	524x524	NUM
cana-5088	109	32	pixels	pixel	NOUN
cana-5088	109	33	)	)	PUNCT
cana-5088	109	34	color	color	NOUN
cana-5088	109	35	images	image	NOUN
cana-5088	109	36	of	of	ADP
cana-5088	109	37	waste	waste	NOUN
cana-5088	109	38	materials	material	NOUN
cana-5088	109	39	collected	collect	VERB
cana-5088	109	40	in	in	ADP
cana-5088	109	41	a	a	DET
cana-5088	109	42	landfill	landfill	NOUN
cana-5088	109	43	environment	environment	NOUN
cana-5088	109	44	.	.	PUNCT
cana-5088	110	1	the	the	DET
cana-5088	110	2	dataset	dataset	NOUN
cana-5088	110	3	is	be	AUX
cana-5088	110	4	organized	organize	VERB
cana-5088	110	5	into	into	ADP
cana-5088	110	6	nine	nine	NUM
cana-5088	110	7	distinct	distinct	ADJ
cana-5088	110	8	categories	category	NOUN
cana-5088	110	9	:	:	PUNCT
cana-5088	110	10	cardboard	cardboard	NOUN
cana-5088	110	11	,	,	PUNCT
cana-5088	110	12	glass	glass	NOUN
cana-5088	110	13	,	,	PUNCT
cana-5088	110	14	metal	metal	NOUN
cana-5088	110	15	,	,	PUNCT
cana-5088	110	16	food	food	NOUN
cana-5088	110	17	organics	organic	NOUN
cana-5088	110	18	,	,	PUNCT
cana-5088	110	19	paper	paper	NOUN
cana-5088	110	20	,	,	PUNCT
cana-5088	110	21	plastic	plastic	NOUN
cana-5088	110	22	,	,	PUNCT
cana-5088	110	23	miscellaneous	miscellaneous	ADJ
cana-5088	110	24	trash	trash	NOUN
cana-5088	110	25	,	,	PUNCT
cana-5088	110	26	textile	textile	NOUN
cana-5088	110	27	trash	trash	NOUN
cana-5088	110	28	,	,	PUNCT
cana-5088	110	29	and	and	CCONJ
cana-5088	110	30	vegetation	vegetation	NOUN
cana-5088	110	31	.	.	PUNCT
cana-5088	111	1	this	this	DET
cana-5088	111	2	dataset	dataset	NOUN
cana-5088	111	3	provided	provide	VERB
cana-5088	111	4	a	a	DET
cana-5088	111	5	comprehensive	comprehensive	ADJ
cana-5088	111	6	and	and	CCONJ
cana-5088	111	7	realistic	realistic	ADJ
cana-5088	111	8	basis	basis	NOUN
cana-5088	111	9	for	for	ADP
cana-5088	111	10	developing	develop	VERB
cana-5088	111	11	a	a	DET
cana-5088	111	12	solid	solid	ADJ
cana-5088	111	13	waste	waste	NOUN
cana-5088	111	14	classification	classification	NOUN
cana-5088	111	15	model	model	NOUN
cana-5088	111	16	using	use	VERB
cana-5088	111	17	transfer	transfer	NOUN
cana-5088	111	18	learning	learning	NOUN
cana-5088	111	19	techniques	technique	NOUN
cana-5088	111	20	.	.	PUNCT
cana-5088	112	1	the	the	DET
cana-5088	112	2	total	total	ADJ
cana-5088	112	3	number	number	NOUN
cana-5088	112	4	of	of	ADP
cana-5088	112	5	images	image	NOUN
cana-5088	112	6	in	in	ADP
cana-5088	112	7	each	each	DET
cana-5088	112	8	class	class	NOUN
cana-5088	112	9	is	be	AUX
cana-5088	112	10	shown	show	VERB
cana-5088	112	11	in	in	ADP
cana-5088	112	12	table	table	NOUN
cana-5088	112	13	1	1	NUM
cana-5088	112	14	.	.	PUNCT
cana-5088	112	15	table	table	NOUN
cana-5088	112	16	1	1	NUM
cana-5088	112	17	.	.	X
cana-5088	112	18	number	number	NOUN
cana-5088	112	19	of	of	ADP
cana-5088	112	20	images	image	NOUN
cana-5088	112	21	in	in	ADP
cana-5088	112	22	each	each	DET
cana-5088	112	23	class	class	NOUN
cana-5088	112	24	class	class	NOUN
cana-5088	112	25	image	image	NOUN
cana-5088	112	26	count	count	NOUN
cana-5088	112	27	cardboard	cardboard	NOUN
cana-5088	112	28	461	461	NUM
cana-5088	112	29	food	food	NOUN
cana-5088	112	30	organics	organic	NOUN
cana-5088	113	1	411	411	NUM
cana-5088	113	2	glass	glass	NOUN
cana-5088	113	3	420	420	NUM
cana-5088	113	4	communications	communication	NOUN
cana-5088	113	5	on	on	ADP
cana-5088	113	6	applied	apply	VERB
cana-5088	113	7	nonlinear	nonlinear	ADJ
cana-5088	113	8	analysis	analysis	NOUN
cana-5088	113	9	issn	issn	NOUN
cana-5088	113	10	:	:	PUNCT
cana-5088	113	11	1074	1074	NUM
cana-5088	113	12	-	-	PUNCT
cana-5088	113	13	133x	133x	NUM
cana-5088	113	14	vol	vol	NOUN
cana-5088	113	15	32	32	NUM
cana-5088	113	16	no	no	NOUN
cana-5088	113	17	.	.	PUNCT
cana-5088	114	1	icmasd	icmasd	NOUN
cana-5088	114	2	(	(	PUNCT
cana-5088	114	3	2025	2025	NUM
cana-5088	114	4	)	)	PUNCT
cana-5088	114	5	592	592	NUM
cana-5088	114	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	114	7	metal	metal	NOUN
cana-5088	114	8	790	790	NUM
cana-5088	114	9	miscellaneous	miscellaneous	ADJ
cana-5088	114	10	trash	trash	NOUN
cana-5088	114	11	495	495	NUM
cana-5088	114	12	paper	paper	NOUN
cana-5088	114	13	500	500	NUM
cana-5088	114	14	plastic	plastic	NOUN
cana-5088	114	15	921	921	NUM
cana-5088	114	16	textile	textile	NOUN
cana-5088	114	17	trash	trash	NOUN
cana-5088	114	18	318	318	NUM
cana-5088	114	19	vegetation	vegetation	NOUN
cana-5088	114	20	436	436	NUM
cana-5088	114	21	fig	fig	NOUN
cana-5088	114	22	.	.	PUNCT
cana-5088	115	1	1	1	NUM
cana-5088	115	2	illustrates	illustrate	VERB
cana-5088	115	3	the	the	DET
cana-5088	115	4	sample	sample	NOUN
cana-5088	115	5	images	image	NOUN
cana-5088	115	6	from	from	ADP
cana-5088	115	7	the	the	DET
cana-5088	115	8	realwaste	realwaste	ADJ
cana-5088	115	9	dataset	dataset	NOUN
cana-5088	115	10	utilized	utilize	VERB
cana-5088	115	11	for	for	ADP
cana-5088	115	12	training	training	NOUN
cana-5088	115	13	models	model	NOUN
cana-5088	115	14	with	with	ADP
cana-5088	115	15	labels	label	NOUN
cana-5088	115	16	indicating	indicate	VERB
cana-5088	115	17	the	the	DET
cana-5088	115	18	type	type	NOUN
cana-5088	115	19	of	of	ADP
cana-5088	115	20	waste	waste	NOUN
cana-5088	115	21	material	material	NOUN
cana-5088	115	22	.	.	PUNCT
cana-5088	116	1	fig.1	fig.1	PROPN
cana-5088	116	2	.	.	PUNCT
cana-5088	117	1	sample	sample	NOUN
cana-5088	117	2	images	image	NOUN
cana-5088	117	3	from	from	ADP
cana-5088	117	4	the	the	DET
cana-5088	117	5	realwaste	realwaste	ADJ
cana-5088	117	6	dataset	dataset	NOUN
cana-5088	117	7	communications	communication	NOUN
cana-5088	117	8	on	on	ADP
cana-5088	117	9	applied	apply	VERB
cana-5088	117	10	nonlinear	nonlinear	ADJ
cana-5088	117	11	analysis	analysis	NOUN
cana-5088	117	12	issn	issn	NOUN
cana-5088	117	13	:	:	PUNCT
cana-5088	117	14	1074	1074	NUM
cana-5088	117	15	-	-	PUNCT
cana-5088	117	16	133x	133x	NUM
cana-5088	117	17	vol	vol	NOUN
cana-5088	117	18	32	32	NUM
cana-5088	117	19	no	no	NOUN
cana-5088	117	20	.	.	PUNCT
cana-5088	118	1	icmasd	icmasd	NOUN
cana-5088	118	2	(	(	PUNCT
cana-5088	118	3	2025	2025	NUM
cana-5088	118	4	)	)	PUNCT
cana-5088	118	5	593	593	NUM
cana-5088	118	6	https://internationalpubls.com	https://internationalpubls.com	SYM
cana-5088	118	7	3.2	3.2	NUM
cana-5088	118	8	data	datum	NOUN
cana-5088	118	9	preprocessing	preprocesse	VERB
cana-5088	118	10	to	to	PART
cana-5088	118	11	ensure	ensure	VERB
cana-5088	118	12	that	that	SCONJ
cana-5088	118	13	the	the	DET
cana-5088	118	14	train	train	NOUN
cana-5088	118	15	,	,	PUNCT
cana-5088	118	16	validation	validation	NOUN
cana-5088	118	17	,	,	PUNCT
cana-5088	118	18	and	and	CCONJ
cana-5088	118	19	test	test	NOUN
cana-5088	118	20	sets	set	NOUN
cana-5088	118	21	accurately	accurately	ADV
cana-5088	118	22	represent	represent	VERB
cana-5088	118	23	all	all	DET
cana-5088	118	24	waste	waste	NOUN
cana-5088	118	25	classes	class	NOUN
cana-5088	118	26	and	and	CCONJ
cana-5088	118	27	avoid	avoid	VERB
cana-5088	118	28	biases	bias	NOUN
cana-5088	118	29	associated	associate	VERB
cana-5088	118	30	with	with	ADP
cana-5088	118	31	image	image	NOUN
cana-5088	118	32	ordering	ordering	NOUN
cana-5088	118	33	,	,	PUNCT
cana-5088	118	34	stratified	stratify	VERB
cana-5088	118	35	sampling	sampling	NOUN
cana-5088	118	36	was	be	AUX
cana-5088	118	37	employed	employ	VERB
cana-5088	118	38	.	.	PUNCT
cana-5088	119	1	this	this	DET
cana-5088	119	2	method	method	NOUN
cana-5088	119	3	inherently	inherently	ADV
cana-5088	119	4	shuffles	shuffle	VERB
cana-5088	119	5	and	and	CCONJ
cana-5088	119	6	splits	split	VERB
cana-5088	119	7	the	the	DET
cana-5088	119	8	dataset	dataset	NOUN
cana-5088	119	9	while	while	SCONJ
cana-5088	119	10	preserving	preserve	VERB
cana-5088	119	11	the	the	DET
cana-5088	119	12	proportional	proportional	ADJ
cana-5088	119	13	distribution	distribution	NOUN
cana-5088	119	14	of	of	ADP
cana-5088	119	15	each	each	DET
cana-5088	119	16	class	class	NOUN
cana-5088	119	17	across	across	ADP
cana-5088	119	18	the	the	DET
cana-5088	119	19	subsets	subset	NOUN
cana-5088	119	20	.	.	PUNCT
cana-5088	120	1	initially	initially	ADV
cana-5088	120	2	,	,	PUNCT
cana-5088	120	3	the	the	DET
cana-5088	120	4	dataset	dataset	NOUN
cana-5088	120	5	was	be	AUX
cana-5088	120	6	divided	divide	VERB
cana-5088	120	7	into	into	ADP
cana-5088	120	8	80	80	NUM
cana-5088	120	9	%	%	NOUN
cana-5088	120	10	training	training	NOUN
cana-5088	120	11	and	and	CCONJ
cana-5088	120	12	20	20	NUM
cana-5088	120	13	%	%	NOUN
cana-5088	120	14	test	test	NOUN
cana-5088	120	15	sets	set	NOUN
cana-5088	120	16	.	.	PUNCT
cana-5088	121	1	subsequently	subsequently	ADV
cana-5088	121	2	,	,	PUNCT
cana-5088	121	3	the	the	DET
cana-5088	121	4	training	training	NOUN
cana-5088	121	5	set	set	NOUN
cana-5088	121	6	was	be	AUX
cana-5088	121	7	further	far	ADV
cana-5088	121	8	divided	divide	VERB
cana-5088	121	9	into	into	ADP
cana-5088	121	10	70	70	NUM
cana-5088	121	11	%	%	NOUN
cana-5088	121	12	training	training	NOUN
cana-5088	121	13	and	and	CCONJ
cana-5088	121	14	10	10	NUM
cana-5088	121	15	%	%	NOUN
cana-5088	121	16	validation	validation	NOUN
cana-5088	121	17	sets	set	NOUN
cana-5088	121	18	,	,	PUNCT
cana-5088	121	19	maintaining	maintain	VERB
cana-5088	121	20	the	the	DET
cana-5088	121	21	class	class	NOUN
cana-5088	121	22	label	label	NOUN
cana-5088	121	23	proportions	proportion	NOUN
cana-5088	121	24	throughout	throughout	ADP
cana-5088	121	25	.	.	PUNCT
cana-5088	122	1	the	the	DET
cana-5088	122	2	final	final	ADJ
cana-5088	122	3	split	split	NOUN
cana-5088	122	4	resulted	result	VERB
cana-5088	122	5	in	in	ADP
cana-5088	122	6	70	70	NUM
cana-5088	122	7	%	%	NOUN
cana-5088	122	8	for	for	ADP
cana-5088	122	9	training	training	NOUN
cana-5088	122	10	,	,	PUNCT
cana-5088	122	11	10	10	NUM
cana-5088	122	12	%	%	NOUN
cana-5088	122	13	for	for	ADP
cana-5088	122	14	validation	validation	NOUN
cana-5088	122	15	,	,	PUNCT
cana-5088	122	16	and	and	CCONJ
cana-5088	122	17	20	20	NUM
cana-5088	122	18	%	%	NOUN
cana-5088	122	19	for	for	ADP
cana-5088	122	20	testing	testing	NOUN
cana-5088	122	21	,	,	PUNCT
cana-5088	122	22	ensuring	ensure	VERB
cana-5088	122	23	a	a	DET
cana-5088	122	24	balanced	balanced	ADJ
cana-5088	122	25	representation	representation	NOUN
cana-5088	122	26	for	for	ADP
cana-5088	122	27	robust	robust	ADJ
cana-5088	122	28	model	model	NOUN
cana-5088	122	29	evaluation	evaluation	NOUN
cana-5088	122	30	and	and	CCONJ
cana-5088	122	31	generalization	generalization	NOUN
cana-5088	122	32	.	.	PUNCT
cana-5088	123	1	given	give	VERB
cana-5088	123	2	the	the	DET
cana-5088	123	3	limited	limited	ADJ
cana-5088	123	4	number	number	NOUN
cana-5088	123	5	of	of	ADP
cana-5088	123	6	images	image	NOUN
cana-5088	123	7	in	in	ADP
cana-5088	123	8	the	the	DET
cana-5088	123	9	dataset	dataset	NOUN
cana-5088	123	10	,	,	PUNCT
cana-5088	123	11	data	datum	NOUN
cana-5088	123	12	augmentation	augmentation	NOUN
cana-5088	123	13	was	be	AUX
cana-5088	123	14	applied	apply	VERB
cana-5088	123	15	to	to	ADP
cana-5088	123	16	the	the	DET
cana-5088	123	17	training	training	NOUN
cana-5088	123	18	set	set	VERB
cana-5088	123	19	to	to	PART
cana-5088	123	20	mitigate	mitigate	VERB
cana-5088	123	21	the	the	DET
cana-5088	123	22	risk	risk	NOUN
cana-5088	123	23	of	of	ADP
cana-5088	123	24	overfitting	overfitte	VERB
cana-5088	123	25	.	.	PUNCT
cana-5088	124	1	augmentation	augmentation	NOUN
cana-5088	124	2	techniques	technique	NOUN
cana-5088	124	3	included	include	VERB
cana-5088	124	4	random	random	ADJ
cana-5088	124	5	rotations	rotation	NOUN
cana-5088	124	6	,	,	PUNCT
cana-5088	124	7	flips	flip	NOUN
cana-5088	124	8	,	,	PUNCT
cana-5088	124	9	zooming	zooming	NOUN
cana-5088	124	10	,	,	PUNCT
cana-5088	124	11	and	and	CCONJ
cana-5088	124	12	slight	slight	ADJ
cana-5088	124	13	shifts	shift	NOUN
cana-5088	124	14	,	,	PUNCT
cana-5088	124	15	enhancing	enhance	VERB
cana-5088	124	16	the	the	DET
cana-5088	124	17	model	model	NOUN
cana-5088	124	18	's	's	PART
cana-5088	124	19	generalization	generalization	NOUN
cana-5088	124	20	capability	capability	NOUN
cana-5088	124	21	.	.	PUNCT
cana-5088	125	1	importantly	importantly	ADV
cana-5088	125	2	,	,	PUNCT
cana-5088	125	3	no	no	DET
cana-5088	125	4	augmentations	augmentation	NOUN
cana-5088	125	5	were	be	AUX
cana-5088	125	6	applied	apply	VERB
cana-5088	125	7	to	to	ADP
cana-5088	125	8	the	the	DET
cana-5088	125	9	validation	validation	NOUN
cana-5088	125	10	and	and	CCONJ
cana-5088	125	11	test	test	NOUN
cana-5088	125	12	sets	set	NOUN
cana-5088	125	13	to	to	PART
cana-5088	125	14	ensure	ensure	VERB
cana-5088	125	15	an	an	DET
cana-5088	125	16	unbiased	unbiased	ADJ
cana-5088	125	17	evaluation	evaluation	NOUN
cana-5088	125	18	of	of	ADP
cana-5088	125	19	the	the	DET
cana-5088	125	20	models	model	NOUN
cana-5088	125	21	on	on	ADP
cana-5088	125	22	unseen	unseen	ADJ
cana-5088	125	23	data	datum	NOUN
cana-5088	125	24	.	.	PUNCT
cana-5088	126	1	all	all	DET
cana-5088	126	2	images	image	NOUN
cana-5088	126	3	were	be	AUX
cana-5088	126	4	resized	resize	VERB
cana-5088	126	5	to	to	ADP
cana-5088	126	6	384x384	384x384	NUM
cana-5088	126	7	pixels	pixel	NOUN
cana-5088	126	8	to	to	PART
cana-5088	126	9	maintain	maintain	VERB
cana-5088	126	10	a	a	DET
cana-5088	126	11	consistent	consistent	ADJ
cana-5088	126	12	square	square	ADJ
cana-5088	126	13	shape	shape	NOUN
cana-5088	126	14	,	,	PUNCT
cana-5088	126	15	aligning	align	VERB
cana-5088	126	16	with	with	ADP
cana-5088	126	17	the	the	DET
cana-5088	126	18	input	input	NOUN
cana-5088	126	19	requirements	requirement	NOUN
cana-5088	126	20	of	of	ADP
cana-5088	126	21	the	the	DET
cana-5088	126	22	resnet50	resnet50	NOUN
cana-5088	126	23	,	,	PUNCT
cana-5088	126	24	densenet121	densenet121	PROPN
cana-5088	126	25	,	,	PUNCT
cana-5088	126	26	and	and	CCONJ
cana-5088	126	27	efficientnet	efficientnet	NOUN
cana-5088	126	28	-	-	PUNCT
cana-5088	126	29	b0	b0	NOUN
cana-5088	126	30	architectures	architecture	NOUN
cana-5088	126	31	.	.	PUNCT
cana-5088	127	1	this	this	DET
cana-5088	127	2	resizing	resize	VERB
cana-5088	127	3	step	step	NOUN
cana-5088	127	4	ensures	ensure	VERB
cana-5088	127	5	compatibility	compatibility	NOUN
cana-5088	127	6	across	across	ADP
cana-5088	127	7	all	all	DET
cana-5088	127	8	three	three	NUM
cana-5088	127	9	pre	pre	ADJ
cana-5088	127	10	-	-	ADJ
cana-5088	127	11	trained	train	VERB
cana-5088	127	12	models	model	NOUN
cana-5088	127	13	while	while	SCONJ
cana-5088	127	14	preserving	preserve	VERB
cana-5088	127	15	the	the	DET
cana-5088	127	16	structural	structural	ADJ
cana-5088	127	17	integrity	integrity	NOUN
cana-5088	127	18	of	of	ADP
cana-5088	127	19	the	the	DET
cana-5088	127	20	waste	waste	NOUN
cana-5088	127	21	images	image	NOUN
cana-5088	127	22	.	.	PUNCT
cana-5088	128	1	class	class	NOUN
cana-5088	128	2	weights	weight	NOUN
cana-5088	128	3	were	be	AUX
cana-5088	128	4	generated	generate	VERB
cana-5088	128	5	and	and	CCONJ
cana-5088	128	6	applied	apply	VERB
cana-5088	128	7	during	during	ADP
cana-5088	128	8	training	training	NOUN
cana-5088	128	9	to	to	PART
cana-5088	128	10	correct	correct	VERB
cana-5088	128	11	dataset	dataset	NOUN
cana-5088	128	12	class	class	NOUN
cana-5088	128	13	imbalances	imbalance	NOUN
cana-5088	128	14	and	and	CCONJ
cana-5088	128	15	prioritize	prioritize	VERB
cana-5088	128	16	underrepresented	underrepresented	ADJ
cana-5088	128	17	classes	class	NOUN
cana-5088	128	18	.	.	PUNCT
cana-5088	129	1	additionally	additionally	ADV
cana-5088	129	2	,	,	PUNCT
cana-5088	129	3	class	class	NOUN
cana-5088	129	4	label	label	NOUN
cana-5088	129	5	mapping	mapping	NOUN
cana-5088	129	6	was	be	AUX
cana-5088	129	7	implemented	implement	VERB
cana-5088	129	8	to	to	PART
cana-5088	129	9	accurately	accurately	ADV
cana-5088	129	10	associate	associate	VERB
cana-5088	129	11	class	class	NOUN
cana-5088	129	12	weights	weight	NOUN
cana-5088	129	13	with	with	ADP
cana-5088	129	14	the	the	DET
cana-5088	129	15	corresponding	correspond	VERB
cana-5088	129	16	one	one	NUM
cana-5088	129	17	-	-	PUNCT
cana-5088	129	18	hot	hot	ADJ
cana-5088	129	19	encoded	encode	VERB
cana-5088	129	20	labels	label	NOUN
cana-5088	129	21	during	during	ADP
cana-5088	129	22	training	training	NOUN
cana-5088	129	23	.	.	PUNCT
cana-5088	130	1	this	this	DET
cana-5088	130	2	comprehensive	comprehensive	ADJ
cana-5088	130	3	preprocessing	preprocessing	NOUN
cana-5088	130	4	pipeline	pipeline	NOUN
cana-5088	130	5	ensures	ensure	VERB
cana-5088	130	6	optimal	optimal	ADJ
cana-5088	130	7	data	datum	NOUN
cana-5088	130	8	preparation	preparation	NOUN
cana-5088	130	9	for	for	ADP
cana-5088	130	10	leveraging	leverage	VERB
cana-5088	130	11	the	the	DET
cana-5088	130	12	capabilities	capability	NOUN
cana-5088	130	13	of	of	ADP
cana-5088	130	14	resnet50	resnet50	NOUN
cana-5088	130	15	,	,	PUNCT
cana-5088	130	16	densenet121	densenet121	PROPN
cana-5088	130	17	,	,	PUNCT
cana-5088	130	18	and	and	CCONJ
cana-5088	130	19	efficientnet	efficientnet	NOUN
cana-5088	130	20	-	-	PUNCT
cana-5088	130	21	b0	b0	NOUN
cana-5088	130	22	in	in	ADP
cana-5088	130	23	the	the	DET
cana-5088	130	24	solid	solid	ADJ
cana-5088	130	25	waste	waste	NOUN
cana-5088	130	26	classification	classification	NOUN
cana-5088	130	27	task	task	NOUN
cana-5088	130	28	.	.	PUNCT
cana-5088	131	1	3.3	3.3	NUM
cana-5088	131	2	model	model	NOUN
cana-5088	131	3	architecture	architecture	NOUN
cana-5088	131	4	this	this	DET
cana-5088	131	5	study	study	NOUN
cana-5088	131	6	employs	employ	VERB
cana-5088	131	7	three	three	NUM
cana-5088	131	8	pre	pre	ADJ
cana-5088	131	9	-	-	ADJ
cana-5088	131	10	trained	train	VERB
cana-5088	131	11	cnn	cnn	PROPN
cana-5088	131	12	architectures	architecture	NOUN
cana-5088	131	13	—	—	PUNCT
cana-5088	131	14	resnet50	resnet50	NOUN
cana-5088	131	15	,	,	PUNCT
cana-5088	131	16	densenet121	densenet121	PROPN
cana-5088	131	17	,	,	PUNCT
cana-5088	131	18	and	and	CCONJ
cana-5088	131	19	efficientnetb0	efficientnetb0	NOUN
cana-5088	131	20	—	—	PUNCT
cana-5088	131	21	to	to	PART
cana-5088	131	22	enhance	enhance	VERB
cana-5088	131	23	the	the	DET
cana-5088	131	24	performance	performance	NOUN
cana-5088	131	25	of	of	ADP
cana-5088	131	26	waste	waste	NOUN
cana-5088	131	27	classification	classification	NOUN
cana-5088	131	28	tasks	task	NOUN
cana-5088	131	29	.	.	PUNCT
cana-5088	132	1	pre	pre	VERB
cana-5088	132	2	-	-	VERB
cana-5088	132	3	trained	train	VERB
cana-5088	132	4	on	on	ADP
cana-5088	132	5	the	the	DET
cana-5088	132	6	imagenet	imagenet	NOUN
cana-5088	132	7	dataset	dataset	NOUN
cana-5088	132	8	,	,	PUNCT
cana-5088	132	9	these	these	DET
cana-5088	132	10	architectures	architecture	NOUN
cana-5088	132	11	are	be	AUX
cana-5088	132	12	widely	widely	ADV
cana-5088	132	13	recognized	recognize	VERB
cana-5088	132	14	for	for	ADP
cana-5088	132	15	their	their	PRON
cana-5088	132	16	robust	robust	ADJ
cana-5088	132	17	feature	feature	NOUN
cana-5088	132	18	extraction	extraction	NOUN
cana-5088	132	19	and	and	CCONJ
cana-5088	132	20	strong	strong	ADJ
cana-5088	132	21	performance	performance	NOUN
cana-5088	132	22	across	across	ADP
cana-5088	132	23	diverse	diverse	ADJ
cana-5088	132	24	image	image	NOUN
cana-5088	132	25	classification	classification	NOUN
cana-5088	132	26	challenges	challenge	NOUN
cana-5088	132	27	.	.	PUNCT
cana-5088	133	1	the	the	DET
cana-5088	133	2	deep	deep	ADJ
cana-5088	133	3	neural	neural	ADJ
cana-5088	133	4	network	network	NOUN
cana-5088	133	5	resnet50	resnet50	NOUN
cana-5088	133	6	,	,	PUNCT
cana-5088	133	7	consisting	consist	VERB
cana-5088	133	8	of	of	ADP
cana-5088	133	9	50	50	NUM
cana-5088	133	10	layers	layer	NOUN
cana-5088	133	11	,	,	PUNCT
cana-5088	133	12	introduces	introduce	VERB
cana-5088	133	13	residual	residual	ADJ
cana-5088	133	14	connections	connection	NOUN
cana-5088	133	15	to	to	PART
cana-5088	133	16	address	address	VERB
cana-5088	133	17	the	the	DET
cana-5088	133	18	vanishing	vanish	VERB
cana-5088	133	19	gradient	gradient	NOUN
cana-5088	133	20	problem	problem	NOUN
cana-5088	133	21	,	,	PUNCT
cana-5088	133	22	enabling	enable	VERB
cana-5088	133	23	the	the	DET
cana-5088	133	24	training	training	NOUN
cana-5088	133	25	of	of	ADP
cana-5088	133	26	very	very	ADV
cana-5088	133	27	deep	deep	ADJ
cana-5088	133	28	networks	network	NOUN
cana-5088	133	29	(	(	PUNCT
cana-5088	133	30	he	he	PRON
cana-5088	133	31	et	et	PROPN
cana-5088	133	32	al	al	PROPN
cana-5088	133	33	.	.	PROPN
cana-5088	133	34	,	,	PUNCT
cana-5088	133	35	2015	2015	NUM
cana-5088	133	36	)	)	PUNCT
cana-5088	133	37	.	.	PUNCT
cana-5088	134	1	it	it	PRON
cana-5088	134	2	excels	excel	VERB
cana-5088	134	3	at	at	ADP
cana-5088	134	4	extracting	extract	VERB
cana-5088	134	5	hierarchical	hierarchical	ADJ
cana-5088	134	6	features	feature	NOUN
cana-5088	134	7	through	through	ADP
cana-5088	134	8	its	its	PRON
cana-5088	134	9	layered	layered	ADJ
cana-5088	134	10	design	design	NOUN
cana-5088	134	11	.	.	PUNCT
cana-5088	135	1	densenet121	densenet121	PROPN
cana-5088	135	2	,	,	PUNCT
cana-5088	135	3	comprising	comprise	VERB
cana-5088	135	4	121	121	NUM
cana-5088	135	5	layers	layer	NOUN
cana-5088	135	6	,	,	PUNCT
cana-5088	135	7	connects	connect	VERB
cana-5088	135	8	each	each	DET
cana-5088	135	9	layer	layer	NOUN
cana-5088	135	10	to	to	ADP
cana-5088	135	11	every	every	DET
cana-5088	135	12	other	other	ADJ
cana-5088	135	13	layer	layer	NOUN
cana-5088	135	14	in	in	ADP
cana-5088	135	15	a	a	DET
cana-5088	135	16	feedforward	feedforward	NOUN
cana-5088	135	17	manner	manner	NOUN
cana-5088	135	18	,	,	PUNCT
cana-5088	135	19	promoting	promote	VERB
cana-5088	135	20	feature	feature	NOUN
cana-5088	135	21	reuse	reuse	NOUN
cana-5088	135	22	and	and	CCONJ
cana-5088	135	23	efficient	efficient	ADJ
cana-5088	135	24	gradient	gradient	NOUN
cana-5088	135	25	flow	flow	NOUN
cana-5088	135	26	,	,	PUNCT
cana-5088	135	27	which	which	PRON
cana-5088	135	28	improves	improve	VERB
cana-5088	135	29	learning	learn	VERB
cana-5088	135	30	efficiency	efficiency	NOUN
cana-5088	135	31	(	(	PUNCT
cana-5088	135	32	huang	huang	PROPN
cana-5088	135	33	et	et	PROPN
cana-5088	135	34	al	al	PROPN
cana-5088	135	35	.	.	PROPN
cana-5088	135	36	,	,	PUNCT
cana-5088	135	37	2018	2018	NUM
cana-5088	135	38	)	)	PUNCT
cana-5088	135	39	.	.	PUNCT
cana-5088	136	1	designed	design	VERB
cana-5088	136	2	using	use	VERB
cana-5088	136	3	a	a	DET
cana-5088	136	4	compound	compound	NOUN
cana-5088	136	5	scaling	scaling	NOUN
cana-5088	136	6	method	method	NOUN
cana-5088	136	7	,	,	PUNCT
cana-5088	136	8	efficientnet	efficientnet	NOUN
cana-5088	136	9	-	-	PUNCT
cana-5088	136	10	b0	b0	NOUN
cana-5088	136	11	balances	balance	NOUN
cana-5088	136	12	network	network	NOUN
cana-5088	136	13	depth	depth	NOUN
cana-5088	136	14	,	,	PUNCT
cana-5088	136	15	width	width	ADJ
cana-5088	136	16	,	,	PUNCT
cana-5088	136	17	and	and	CCONJ
cana-5088	136	18	resolution	resolution	NOUN
cana-5088	136	19	,	,	PUNCT
cana-5088	136	20	achieving	achieve	VERB
cana-5088	136	21	high	high	ADJ
cana-5088	136	22	accuracy	accuracy	NOUN
cana-5088	136	23	with	with	ADP
cana-5088	136	24	fewer	few	ADJ
cana-5088	136	25	parameters	parameter	NOUN
cana-5088	136	26	and	and	CCONJ
cana-5088	136	27	computational	computational	ADJ
cana-5088	136	28	resources	resource	NOUN
cana-5088	136	29	compared	compare	VERB
cana-5088	136	30	to	to	ADP
cana-5088	136	31	traditional	traditional	ADJ
cana-5088	136	32	architectures	architecture	NOUN
cana-5088	136	33	(	(	PUNCT
cana-5088	136	34	tan	tan	PROPN
cana-5088	136	35	&	&	CCONJ
cana-5088	136	36	le	le	PROPN
cana-5088	136	37	,	,	PUNCT
cana-5088	136	38	2020	2020	NUM
cana-5088	136	39	)	)	PUNCT
cana-5088	136	40	.	.	PUNCT
cana-5088	137	1	building	building	NOUN
cana-5088	137	2	and	and	CCONJ
cana-5088	137	3	training	training	NOUN
cana-5088	137	4	complex	complex	ADJ
cana-5088	137	5	cnn	cnn	NOUN
cana-5088	137	6	models	model	NOUN
cana-5088	137	7	from	from	ADP
cana-5088	137	8	scratch	scratch	NOUN
cana-5088	137	9	can	can	AUX
cana-5088	137	10	lead	lead	VERB
cana-5088	137	11	to	to	ADP
cana-5088	137	12	inconsistent	inconsistent	ADJ
cana-5088	137	13	performance	performance	NOUN
cana-5088	137	14	on	on	ADP
cana-5088	137	15	smaller	small	ADJ
cana-5088	137	16	datasets	dataset	NOUN
cana-5088	137	17	due	due	ADP
cana-5088	137	18	to	to	ADP
cana-5088	137	19	challenges	challenge	NOUN
cana-5088	137	20	like	like	ADP
cana-5088	137	21	overfitting	overfitte	VERB
cana-5088	137	22	and	and	CCONJ
cana-5088	137	23	uneven	uneven	ADJ
cana-5088	137	24	class	class	NOUN
cana-5088	137	25	distributions	distribution	NOUN
cana-5088	137	26	.	.	PUNCT
cana-5088	138	1	to	to	PART
cana-5088	138	2	address	address	VERB
cana-5088	138	3	this	this	PRON
cana-5088	138	4	,	,	PUNCT
cana-5088	138	5	transfer	transfer	NOUN
cana-5088	138	6	learning	learning	NOUN
cana-5088	138	7	was	be	AUX
cana-5088	138	8	employed	employ	VERB
cana-5088	138	9	,	,	PUNCT
cana-5088	138	10	which	which	PRON
cana-5088	138	11	allows	allow	VERB
cana-5088	138	12	pre	pre	ADJ
cana-5088	138	13	-	-	ADJ
cana-5088	138	14	trained	train	VERB
cana-5088	138	15	models	model	NOUN
cana-5088	138	16	to	to	PART
cana-5088	138	17	be	be	AUX
cana-5088	138	18	fine	fine	ADV
cana-5088	138	19	-	-	PUNCT
cana-5088	138	20	tuned	tune	VERB
cana-5088	138	21	to	to	PART
cana-5088	138	22	adapt	adapt	VERB
cana-5088	138	23	to	to	ADP
cana-5088	138	24	specific	specific	ADJ
cana-5088	138	25	datasets	dataset	NOUN
cana-5088	138	26	.	.	PUNCT
cana-5088	139	1	in	in	ADP
cana-5088	139	2	transfer	transfer	NOUN
cana-5088	139	3	learning	learning	NOUN
cana-5088	139	4	,	,	PUNCT
cana-5088	139	5	earlier	early	ADJ
cana-5088	139	6	layers	layer	NOUN
cana-5088	139	7	that	that	PRON
cana-5088	139	8	capture	capture	VERB
cana-5088	139	9	general	general	ADJ
cana-5088	139	10	features	feature	NOUN
cana-5088	139	11	are	be	AUX
cana-5088	139	12	typically	typically	ADV
cana-5088	139	13	retained	retain	VERB
cana-5088	139	14	,	,	PUNCT
cana-5088	139	15	while	while	SCONJ
cana-5088	139	16	deeper	deep	ADJ
cana-5088	139	17	layers	layer	NOUN
cana-5088	139	18	are	be	AUX
cana-5088	139	19	fine	fine	ADV
cana-5088	139	20	-	-	PUNCT
cana-5088	139	21	tuned	tune	VERB
cana-5088	139	22	to	to	PART
cana-5088	139	23	learn	learn	VERB
cana-5088	139	24	task	task	NOUN
cana-5088	139	25	-	-	PUNCT
cana-5088	139	26	specific	specific	ADJ
cana-5088	139	27	features	feature	NOUN
cana-5088	139	28	.	.	PUNCT
cana-5088	140	1	this	this	DET
cana-5088	140	2	approach	approach	NOUN
cana-5088	140	3	makes	make	VERB
cana-5088	140	4	the	the	DET
cana-5088	140	5	models	model	NOUN
cana-5088	140	6	more	more	ADV
cana-5088	140	7	robust	robust	ADJ
cana-5088	140	8	and	and	CCONJ
cana-5088	140	9	less	less	ADV
cana-5088	140	10	prone	prone	ADJ
cana-5088	140	11	to	to	ADP
cana-5088	140	12	overfitting	overfitte	VERB
cana-5088	140	13	.	.	PUNCT
cana-5088	141	1	for	for	ADP
cana-5088	141	2	this	this	DET
cana-5088	141	3	study	study	NOUN
cana-5088	141	4	,	,	PUNCT
cana-5088	141	5	resnet50	resnet50	NOUN
cana-5088	141	6	,	,	PUNCT
cana-5088	141	7	densenet121	densenet121	PROPN
cana-5088	141	8	,	,	PUNCT
cana-5088	141	9	and	and	CCONJ
cana-5088	141	10	efficientnet	efficientnet	NOUN
cana-5088	141	11	-	-	PUNCT
cana-5088	141	12	b0	b0	NOUN
cana-5088	141	13	architectures	architecture	NOUN
cana-5088	141	14	were	be	AUX
cana-5088	141	15	loaded	load	VERB
cana-5088	141	16	without	without	ADP
cana-5088	141	17	their	their	PRON
cana-5088	141	18	top	top	ADJ
cana-5088	141	19	classifier	classifier	NOUN
cana-5088	141	20	layers	layer	NOUN
cana-5088	141	21	to	to	PART
cana-5088	141	22	accommodate	accommodate	VERB
cana-5088	141	23	the	the	DET
cana-5088	141	24	dataset	dataset	NOUN
cana-5088	141	25	's	's	PART
cana-5088	141	26	nine	nine	NUM
cana-5088	141	27	waste	waste	NOUN
cana-5088	141	28	classes	class	NOUN
cana-5088	141	29	.	.	PUNCT
cana-5088	142	1	the	the	DET
cana-5088	142	2	input	input	NOUN
cana-5088	142	3	shape	shape	NOUN
cana-5088	142	4	was	be	AUX
cana-5088	142	5	set	set	VERB
cana-5088	142	6	to	to	ADP
cana-5088	142	7	(	(	PUNCT
cana-5088	142	8	384	384	NUM
cana-5088	142	9	,	,	PUNCT
cana-5088	142	10	384	384	NUM
cana-5088	142	11	,	,	PUNCT
cana-5088	142	12	3	3	NUM
cana-5088	142	13	)	)	PUNCT
cana-5088	142	14	to	to	PART
cana-5088	142	15	align	align	VERB
cana-5088	142	16	with	with	ADP
cana-5088	142	17	the	the	DET
cana-5088	142	18	dataset	dataset	NOUN
cana-5088	142	19	's	's	PART
cana-5088	142	20	image	image	NOUN
cana-5088	142	21	dimensions	dimension	NOUN
cana-5088	142	22	.	.	PUNCT
cana-5088	143	1	a	a	DET
cana-5088	143	2	communications	communication	NOUN
cana-5088	143	3	on	on	ADP
cana-5088	143	4	applied	apply	VERB
cana-5088	143	5	nonlinear	nonlinear	ADJ
cana-5088	143	6	analysis	analysis	NOUN
cana-5088	143	7	issn	issn	NOUN
cana-5088	143	8	:	:	PUNCT
cana-5088	143	9	1074	1074	NUM
cana-5088	143	10	-	-	PUNCT
cana-5088	143	11	133x	133x	NUM
cana-5088	143	12	vol	vol	NOUN
cana-5088	143	13	32	32	NUM
cana-5088	143	14	no	no	NOUN
cana-5088	143	15	.	.	PUNCT
cana-5088	144	1	icmasd	icmasd	NOUN
cana-5088	144	2	(	(	PUNCT
cana-5088	144	3	2025	2025	NUM
cana-5088	144	4	)	)	PUNCT
cana-5088	144	5	594	594	NUM
cana-5088	144	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5088	144	7	balanced	balanced	ADJ
cana-5088	144	8	strategy	strategy	NOUN
cana-5088	144	9	was	be	AUX
cana-5088	144	10	adopted	adopt	VERB
cana-5088	144	11	to	to	PART
cana-5088	144	12	freeze	freeze	VERB
cana-5088	144	13	the	the	DET
cana-5088	144	14	earlier	early	ADJ
cana-5088	144	15	layers	layer	NOUN
cana-5088	144	16	,	,	PUNCT
cana-5088	144	17	which	which	PRON
cana-5088	144	18	capture	capture	VERB
cana-5088	144	19	broad	broad	ADJ
cana-5088	144	20	and	and	CCONJ
cana-5088	144	21	general	general	ADJ
cana-5088	144	22	features	feature	NOUN
cana-5088	144	23	while	while	SCONJ
cana-5088	144	24	fine	fine	ADV
cana-5088	144	25	-	-	PUNCT
cana-5088	144	26	tuning	tune	VERB
cana-5088	144	27	the	the	DET
cana-5088	144	28	latter	latter	ADJ
cana-5088	144	29	layers	layer	NOUN
cana-5088	144	30	to	to	PART
cana-5088	144	31	adapt	adapt	VERB
cana-5088	144	32	to	to	ADP
cana-5088	144	33	the	the	DET
cana-5088	144	34	specific	specific	ADJ
cana-5088	144	35	waste	waste	NOUN
cana-5088	144	36	classification	classification	NOUN
cana-5088	144	37	task	task	NOUN
cana-5088	144	38	.	.	PUNCT
cana-5088	145	1	the	the	DET
cana-5088	145	2	pre	pre	ADJ
cana-5088	145	3	-	-	ADJ
cana-5088	145	4	trained	train	VERB
cana-5088	145	5	models	model	NOUN
cana-5088	145	6	were	be	AUX
cana-5088	145	7	extended	extend	VERB
cana-5088	145	8	with	with	ADP
cana-5088	145	9	custom	custom	NOUN
cana-5088	145	10	layers	layer	NOUN
cana-5088	145	11	for	for	ADP
cana-5088	145	12	enhanced	enhanced	ADJ
cana-5088	145	13	task	task	NOUN
cana-5088	145	14	suitability	suitability	NOUN
cana-5088	145	15	.	.	PUNCT
cana-5088	146	1	after	after	ADP
cana-5088	146	2	feature	feature	NOUN
cana-5088	146	3	extraction	extraction	NOUN
cana-5088	146	4	using	use	VERB
cana-5088	146	5	the	the	DET
cana-5088	146	6	pre	pre	ADJ
cana-5088	146	7	-	-	ADJ
cana-5088	146	8	trained	train	VERB
cana-5088	146	9	models	model	NOUN
cana-5088	146	10	,	,	PUNCT
cana-5088	146	11	a	a	DET
cana-5088	146	12	global	global	ADJ
cana-5088	146	13	average	average	ADJ
cana-5088	146	14	pooling	pooling	NOUN
cana-5088	146	15	(	(	PUNCT
cana-5088	146	16	gap	gap	NOUN
cana-5088	146	17	)	)	PUNCT
cana-5088	146	18	layer	layer	NOUN
cana-5088	146	19	was	be	AUX
cana-5088	146	20	added	add	VERB
cana-5088	146	21	to	to	PART
cana-5088	146	22	reduce	reduce	VERB
cana-5088	146	23	the	the	DET
cana-5088	146	24	spatial	spatial	ADJ
cana-5088	146	25	dimensions	dimension	NOUN
cana-5088	146	26	of	of	ADP
cana-5088	146	27	the	the	DET
cana-5088	146	28	feature	feature	NOUN
cana-5088	146	29	maps	map	NOUN
cana-5088	146	30	.	.	PUNCT
cana-5088	147	1	to	to	PART
cana-5088	147	2	mitigate	mitigate	VERB
cana-5088	147	3	overfitting	overfitting	NOUN
cana-5088	147	4	,	,	PUNCT
cana-5088	147	5	a	a	DET
cana-5088	147	6	dropout	dropout	NOUN
cana-5088	147	7	layer	layer	NOUN
cana-5088	147	8	was	be	AUX
cana-5088	147	9	incorporated	incorporate	VERB
cana-5088	147	10	for	for	ADP
cana-5088	147	11	regularization	regularization	NOUN
cana-5088	147	12	.	.	PUNCT
cana-5088	148	1	finally	finally	ADV
cana-5088	148	2	,	,	PUNCT
cana-5088	148	3	a	a	DET
cana-5088	148	4	dense	dense	ADJ
cana-5088	148	5	layer	layer	NOUN
cana-5088	148	6	with	with	ADP
cana-5088	148	7	a	a	DET
cana-5088	148	8	softmax	softmax	NOUN
cana-5088	148	9	activation	activation	NOUN
cana-5088	148	10	function	function	NOUN
cana-5088	148	11	was	be	AUX
cana-5088	148	12	added	add	VERB
cana-5088	148	13	to	to	PART
cana-5088	148	14	classify	classify	VERB
cana-5088	148	15	the	the	DET
cana-5088	148	16	inputs	input	NOUN
cana-5088	148	17	into	into	ADP
cana-5088	148	18	the	the	DET
cana-5088	148	19	nine	nine	NUM
cana-5088	148	20	distinct	distinct	ADJ
cana-5088	148	21	waste	waste	NOUN
cana-5088	148	22	classes	class	NOUN
cana-5088	148	23	.	.	PUNCT
cana-5088	149	1	the	the	DET
cana-5088	149	2	models	model	NOUN
cana-5088	149	3	were	be	AUX
cana-5088	149	4	compiled	compile	VERB
cana-5088	149	5	using	use	VERB
cana-5088	149	6	the	the	DET
cana-5088	149	7	adam	adam	PROPN
cana-5088	149	8	optimizer	optimizer	NOUN
cana-5088	149	9	with	with	ADP
cana-5088	149	10	a	a	DET
cana-5088	149	11	learning	learn	VERB
cana-5088	149	12	rate	rate	NOUN
cana-5088	149	13	of	of	ADP
cana-5088	149	14	0.0001	0.0001	NUM
cana-5088	149	15	.	.	PUNCT
cana-5088	150	1	the	the	DET
cana-5088	150	2	loss	loss	NOUN
cana-5088	150	3	function	function	NOUN
cana-5088	150	4	was	be	AUX
cana-5088	150	5	set	set	VERB
cana-5088	150	6	to	to	AUX
cana-5088	150	7	categorical	categorical	ADJ
cana-5088	150	8	cross	cross	NOUN
cana-5088	150	9	-	-	NOUN
cana-5088	150	10	entropy	entropy	ADJ
cana-5088	150	11	,	,	PUNCT
cana-5088	150	12	ideal	ideal	ADJ
cana-5088	150	13	for	for	ADP
cana-5088	150	14	multi	multi	ADJ
cana-5088	150	15	-	-	ADJ
cana-5088	150	16	class	class	ADJ
cana-5088	150	17	classification	classification	NOUN
cana-5088	150	18	tasks	task	NOUN
cana-5088	150	19	like	like	ADP
cana-5088	150	20	waste	waste	NOUN
cana-5088	150	21	type	type	NOUN
cana-5088	150	22	identification	identification	NOUN
cana-5088	150	23	.	.	PUNCT
cana-5088	151	1	early	early	ADJ
cana-5088	151	2	stopping	stopping	NOUN
cana-5088	151	3	was	be	AUX
cana-5088	151	4	implemented	implement	VERB
cana-5088	151	5	to	to	PART
cana-5088	151	6	monitor	monitor	VERB
cana-5088	151	7	validation	validation	NOUN
cana-5088	151	8	loss	loss	NOUN
cana-5088	151	9	and	and	CCONJ
cana-5088	151	10	halt	halt	VERB
cana-5088	151	11	training	training	NOUN
cana-5088	151	12	if	if	SCONJ
cana-5088	151	13	no	no	DET
cana-5088	151	14	improvement	improvement	NOUN
cana-5088	151	15	was	be	AUX
cana-5088	151	16	observed	observe	VERB
cana-5088	151	17	within	within	ADP
cana-5088	151	18	a	a	DET
cana-5088	151	19	specified	specified	ADJ
cana-5088	151	20	number	number	NOUN
cana-5088	151	21	of	of	ADP
cana-5088	151	22	epochs	epoch	NOUN
cana-5088	151	23	to	to	PART
cana-5088	151	24	further	far	ADV
cana-5088	151	25	mitigate	mitigate	VERB
cana-5088	151	26	overfitting	overfitte	VERB
cana-5088	151	27	.	.	PUNCT
cana-5088	152	1	additionally	additionally	ADV
cana-5088	152	2	,	,	PUNCT
cana-5088	152	3	a	a	DET
cana-5088	152	4	learning	learning	NOUN
cana-5088	152	5	rate	rate	NOUN
cana-5088	152	6	reduction	reduction	NOUN
cana-5088	152	7	on	on	ADP
cana-5088	152	8	the	the	DET
cana-5088	152	9	plateau	plateau	NOUN
cana-5088	152	10	was	be	AUX
cana-5088	152	11	used	use	VERB
cana-5088	152	12	to	to	PART
cana-5088	152	13	decrease	decrease	VERB
cana-5088	152	14	the	the	DET
cana-5088	152	15	learning	learning	NOUN
cana-5088	152	16	rate	rate	NOUN
cana-5088	152	17	when	when	SCONJ
cana-5088	152	18	the	the	DET
cana-5088	152	19	validation	validation	NOUN
cana-5088	152	20	loss	loss	NOUN
cana-5088	152	21	plateaued	plateaue	VERB
cana-5088	152	22	,	,	PUNCT
cana-5088	152	23	enabling	enable	VERB
cana-5088	152	24	finer	fine	ADJ
cana-5088	152	25	adjustments	adjustment	NOUN
cana-5088	152	26	during	during	ADP
cana-5088	152	27	the	the	DET
cana-5088	152	28	later	later	ADJ
cana-5088	152	29	stages	stage	NOUN
cana-5088	152	30	of	of	ADP
cana-5088	152	31	training	training	NOUN
cana-5088	152	32	.	.	PUNCT
cana-5088	153	1	the	the	DET
cana-5088	153	2	models	model	NOUN
cana-5088	153	3	were	be	AUX
cana-5088	153	4	trained	train	VERB
cana-5088	153	5	for	for	ADP
cana-5088	153	6	30	30	NUM
cana-5088	153	7	epochs	epoch	NOUN
cana-5088	153	8	with	with	ADP
cana-5088	153	9	a	a	DET
cana-5088	153	10	batch	batch	NOUN
cana-5088	153	11	size	size	NOUN
cana-5088	153	12	of	of	ADP
cana-5088	153	13	32	32	NUM
cana-5088	153	14	to	to	PART
cana-5088	153	15	strike	strike	VERB
cana-5088	153	16	a	a	DET
cana-5088	153	17	balance	balance	NOUN
cana-5088	153	18	between	between	ADP
cana-5088	153	19	gradient	gradient	ADJ
cana-5088	153	20	stability	stability	NOUN
cana-5088	153	21	and	and	CCONJ
cana-5088	153	22	computational	computational	ADJ
cana-5088	153	23	efficiency	efficiency	NOUN
cana-5088	153	24	.	.	PUNCT
cana-5088	154	1	further	far	ADV
cana-5088	154	2	,	,	PUNCT
cana-5088	154	3	the	the	DET
cana-5088	154	4	performance	performance	NOUN
cana-5088	154	5	of	of	ADP
cana-5088	154	6	these	these	DET
cana-5088	154	7	models	model	NOUN
cana-5088	154	8	was	be	AUX
cana-5088	154	9	evaluated	evaluate	VERB
cana-5088	154	10	using	use	VERB
cana-5088	154	11	standard	standard	ADJ
cana-5088	154	12	metrics	metric	NOUN
cana-5088	154	13	,	,	PUNCT
cana-5088	154	14	including	include	VERB
cana-5088	154	15	accuracy	accuracy	NOUN
cana-5088	154	16	,	,	PUNCT
cana-5088	154	17	precision	precision	NOUN
cana-5088	154	18	,	,	PUNCT
cana-5088	154	19	recall	recall	NOUN
cana-5088	154	20	,	,	PUNCT
cana-5088	154	21	and	and	CCONJ
cana-5088	154	22	f1	f1	NOUN
cana-5088	154	23	-	-	PUNCT
cana-5088	154	24	score	score	NOUN
cana-5088	154	25	.	.	PUNCT
cana-5088	155	1	4	4	X
cana-5088	155	2	.	.	NOUN
cana-5088	155	3	results	result	NOUN
cana-5088	155	4	and	and	CCONJ
cana-5088	155	5	discussion	discussion	VERB
cana-5088	155	6	the	the	DET
cana-5088	155	7	performance	performance	NOUN
cana-5088	155	8	of	of	ADP
cana-5088	155	9	the	the	DET
cana-5088	155	10	resnet50	resnet50	NOUN
cana-5088	155	11	,	,	PUNCT
cana-5088	155	12	densenet121	densenet121	PROPN
cana-5088	155	13	,	,	PUNCT
cana-5088	155	14	and	and	CCONJ
cana-5088	155	15	efficientnetb0	efficientnetb0	NOUN
cana-5088	155	16	architectures	architecture	NOUN
cana-5088	155	17	was	be	AUX
cana-5088	155	18	systematically	systematically	ADV
cana-5088	155	19	evaluated	evaluate	VERB
cana-5088	155	20	for	for	ADP
cana-5088	155	21	the	the	DET
cana-5088	155	22	waste	waste	NOUN
cana-5088	155	23	classification	classification	NOUN
cana-5088	155	24	task	task	NOUN
cana-5088	155	25	,	,	PUNCT
cana-5088	155	26	considering	consider	VERB
cana-5088	155	27	their	their	PRON
cana-5088	155	28	training	training	NOUN
cana-5088	155	29	,	,	PUNCT
cana-5088	155	30	validation	validation	NOUN
cana-5088	155	31	,	,	PUNCT
cana-5088	155	32	test	test	NOUN
cana-5088	155	33	accuracies	accuracy	NOUN
cana-5088	155	34	,	,	PUNCT
cana-5088	155	35	and	and	CCONJ
cana-5088	155	36	the	the	DET
cana-5088	155	37	corresponding	corresponding	ADJ
cana-5088	155	38	loss	loss	NOUN
cana-5088	155	39	metrics	metric	NOUN
cana-5088	155	40	.	.	PUNCT
cana-5088	156	1	table	table	NOUN
cana-5088	156	2	2	2	NUM
cana-5088	156	3	.	.	PUNCT
cana-5088	157	1	accuracy	accuracy	NOUN
cana-5088	157	2	comparison	comparison	NOUN
cana-5088	157	3	of	of	ADP
cana-5088	157	4	three	three	NUM
cana-5088	157	5	pre	pre	ADJ
cana-5088	157	6	-	-	ADJ
cana-5088	157	7	trained	train	VERB
cana-5088	157	8	models	model	NOUN
cana-5088	157	9	model	model	VERB
cana-5088	157	10	train	train	NOUN
cana-5088	157	11	accuracy	accuracy	NOUN
cana-5088	157	12	validation	validation	NOUN
cana-5088	157	13	accuracy	accuracy	NOUN
cana-5088	157	14	test	test	NOUN
cana-5088	157	15	accuracy	accuracy	NOUN
cana-5088	157	16	resnet50	resnet50	NOUN
cana-5088	157	17	100	100	NUM
cana-5088	157	18	%	%	NOUN
cana-5088	157	19	92.24	92.24	NUM
cana-5088	157	20	%	%	NOUN
cana-5088	157	21	91.82	91.82	NUM
cana-5088	157	22	%	%	NOUN
cana-5088	157	23	densenet1	densenet1	NOUN
cana-5088	157	24	21	21	NUM
cana-5088	157	25	99.99	99.99	NUM
cana-5088	157	26	%	%	NOUN
cana-5088	157	27	91.82	91.82	NUM
cana-5088	157	28	%	%	NOUN
cana-5088	157	29	94.33	94.33	NUM
cana-5088	157	30	%	%	NOUN
cana-5088	157	31	efficientn	efficientn	ADJ
cana-5088	157	32	etb0	etb0	NOUN
cana-5088	157	33	99.83	99.83	NUM
cana-5088	157	34	%	%	NOUN
cana-5088	157	35	91.19	91.19	NUM
cana-5088	157	36	%	%	NOUN
cana-5088	157	37	91.40	91.40	NUM
cana-5088	157	38	%	%	NOUN
cana-5088	157	39	table	table	NOUN
cana-5088	157	40	2	2	NUM
cana-5088	157	41	compares	compare	VERB
cana-5088	157	42	the	the	DET
cana-5088	157	43	training	training	NOUN
cana-5088	157	44	,	,	PUNCT
cana-5088	157	45	validation	validation	NOUN
cana-5088	157	46	,	,	PUNCT
cana-5088	157	47	and	and	CCONJ
cana-5088	157	48	testing	testing	NOUN
cana-5088	157	49	accuracies	accuracy	NOUN
cana-5088	157	50	of	of	ADP
cana-5088	157	51	resnet50	resnet50	NOUN
cana-5088	157	52	,	,	PUNCT
cana-5088	157	53	densenet121	densenet121	PROPN
cana-5088	157	54	,	,	PUNCT
cana-5088	157	55	and	and	CCONJ
cana-5088	157	56	efficientnetb0	efficientnetb0	PROPN
cana-5088	157	57	.	.	PUNCT
cana-5088	158	1	during	during	ADP
cana-5088	158	2	training	training	NOUN
cana-5088	158	3	and	and	CCONJ
cana-5088	158	4	validation	validation	NOUN
cana-5088	158	5	,	,	PUNCT
cana-5088	158	6	resnet50	resnet50	NOUN
cana-5088	158	7	achieved	achieve	VERB
cana-5088	158	8	a	a	DET
cana-5088	158	9	training	training	NOUN
cana-5088	158	10	accuracy	accuracy	NOUN
cana-5088	158	11	of	of	ADP
cana-5088	158	12	100	100	NUM
cana-5088	158	13	%	%	NOUN
cana-5088	158	14	and	and	CCONJ
cana-5088	158	15	a	a	DET
cana-5088	158	16	validation	validation	NOUN
cana-5088	158	17	accuracy	accuracy	NOUN
cana-5088	158	18	of	of	ADP
cana-5088	158	19	92.24	92.24	NUM
cana-5088	158	20	%	%	NOUN
cana-5088	158	21	,	,	PUNCT
cana-5088	158	22	with	with	ADP
cana-5088	158	23	corresponding	corresponding	ADJ
cana-5088	158	24	losses	loss	NOUN
cana-5088	158	25	of	of	ADP
cana-5088	158	26	0.0021	0.0021	NUM
cana-5088	158	27	and	and	CCONJ
cana-5088	158	28	0.3450	0.3450	NUM
cana-5088	158	29	,	,	PUNCT
cana-5088	158	30	respectively	respectively	ADV
cana-5088	158	31	.	.	PUNCT
cana-5088	159	1	early	early	ADJ
cana-5088	159	2	stopping	stop	VERB
cana-5088	159	3	restored	restore	VERB
cana-5088	159	4	weights	weight	NOUN
cana-5088	159	5	from	from	ADP
cana-5088	159	6	the	the	DET
cana-5088	159	7	9th	9th	ADJ
cana-5088	159	8	epoch	epoch	NOUN
cana-5088	159	9	,	,	PUNCT
cana-5088	159	10	indicating	indicate	VERB
cana-5088	159	11	efficient	efficient	ADJ
cana-5088	159	12	convergence	convergence	NOUN
cana-5088	159	13	.	.	PUNCT
cana-5088	160	1	densenet121	densenet121	PROPN
cana-5088	160	2	completed	complete	VERB
cana-5088	160	3	the	the	DET
cana-5088	160	4	full	full	ADJ
cana-5088	160	5	30	30	NUM
cana-5088	160	6	epochs	epoch	NOUN
cana-5088	160	7	,	,	PUNCT
cana-5088	160	8	restoring	restore	VERB
cana-5088	160	9	weights	weight	NOUN
cana-5088	160	10	from	from	ADP
cana-5088	160	11	the	the	DET
cana-5088	160	12	21st	21st	ADJ
cana-5088	160	13	epoch	epoch	NOUN
cana-5088	160	14	,	,	PUNCT
cana-5088	160	15	and	and	CCONJ
cana-5088	160	16	achieved	achieve	VERB
cana-5088	160	17	a	a	DET
cana-5088	160	18	training	training	NOUN
cana-5088	160	19	accuracy	accuracy	NOUN
cana-5088	160	20	of	of	ADP
cana-5088	160	21	99.99	99.99	NUM
cana-5088	160	22	%	%	NOUN
cana-5088	160	23	and	and	CCONJ
cana-5088	160	24	a	a	DET
cana-5088	160	25	validation	validation	NOUN
cana-5088	160	26	accuracy	accuracy	NOUN
cana-5088	160	27	of	of	ADP
cana-5088	160	28	91.82	91.82	NUM
cana-5088	160	29	%	%	NOUN
cana-5088	160	30	,	,	PUNCT
cana-5088	160	31	with	with	ADP
cana-5088	160	32	training	training	NOUN
cana-5088	160	33	and	and	CCONJ
cana-5088	160	34	validation	validation	NOUN
cana-5088	160	35	losses	loss	NOUN
cana-5088	160	36	of	of	ADP
cana-5088	160	37	0.0047	0.0047	NUM
cana-5088	160	38	and	and	CCONJ
cana-5088	160	39	0.3001	0.3001	NUM
cana-5088	160	40	,	,	PUNCT
cana-5088	160	41	respectively	respectively	ADV
cana-5088	160	42	.	.	PUNCT
cana-5088	161	1	efficientnetb0	efficientnetb0	PROPN
cana-5088	161	2	,	,	PUNCT
cana-5088	161	3	trained	train	VERB
cana-5088	161	4	for	for	ADP
cana-5088	161	5	30	30	NUM
cana-5088	161	6	epochs	epoch	NOUN
cana-5088	161	7	with	with	ADP
cana-5088	161	8	weights	weight	NOUN
cana-5088	161	9	restored	restore	VERB
cana-5088	161	10	from	from	ADP
cana-5088	161	11	the	the	DET
cana-5088	161	12	28th	28th	ADJ
cana-5088	161	13	epoch	epoch	NOUN
cana-5088	161	14	,	,	PUNCT
cana-5088	161	15	attained	attain	VERB
cana-5088	161	16	a	a	DET
cana-5088	161	17	training	training	NOUN
cana-5088	161	18	accuracy	accuracy	NOUN
cana-5088	161	19	of	of	ADP
cana-5088	161	20	99.83	99.83	NUM
cana-5088	161	21	%	%	NOUN
cana-5088	161	22	,	,	PUNCT
cana-5088	161	23	a	a	DET
cana-5088	161	24	validation	validation	NOUN
cana-5088	161	25	accuracy	accuracy	NOUN
cana-5088	161	26	of	of	ADP
cana-5088	161	27	91.19	91.19	NUM
cana-5088	161	28	%	%	NOUN
cana-5088	161	29	,	,	PUNCT
cana-5088	161	30	and	and	CCONJ
cana-5088	161	31	training	training	NOUN
cana-5088	161	32	and	and	CCONJ
cana-5088	161	33	validation	validation	NOUN
cana-5088	161	34	losses	loss	NOUN
cana-5088	161	35	of	of	ADP
cana-5088	161	36	0.0127	0.0127	NUM
cana-5088	161	37	and	and	CCONJ
cana-5088	161	38	0.3254	0.3254	NUM
cana-5088	161	39	,	,	PUNCT
cana-5088	161	40	respectively	respectively	ADV
cana-5088	161	41	.	.	PUNCT
cana-5088	162	1	regarding	regard	VERB
cana-5088	162	2	test	test	NOUN
cana-5088	162	3	performance	performance	NOUN
cana-5088	162	4	,	,	PUNCT
cana-5088	162	5	densenet121	densenet121	PROPN
cana-5088	162	6	outperformed	outperform	VERB
cana-5088	162	7	the	the	DET
cana-5088	162	8	other	other	ADJ
cana-5088	162	9	models	model	NOUN
cana-5088	162	10	with	with	ADP
cana-5088	162	11	a	a	DET
cana-5088	162	12	test	test	NOUN
cana-5088	162	13	accuracy	accuracy	NOUN
cana-5088	162	14	of	of	ADP
cana-5088	162	15	94.33	94.33	NUM
cana-5088	162	16	%	%	NOUN
cana-5088	162	17	and	and	CCONJ
cana-5088	162	18	the	the	DET
cana-5088	162	19	lowest	low	ADJ
cana-5088	162	20	test	test	NOUN
cana-5088	162	21	loss	loss	NOUN
cana-5088	162	22	of	of	ADP
cana-5088	162	23	0.2586	0.2586	NUM
cana-5088	162	24	.	.	PUNCT
cana-5088	163	1	resnet50	resnet50	NOUN
cana-5088	163	2	followed	follow	VERB
cana-5088	163	3	communications	communication	NOUN
cana-5088	163	4	on	on	ADP
cana-5088	163	5	applied	apply	VERB
cana-5088	163	6	nonlinear	nonlinear	ADJ
cana-5088	163	7	analysis	analysis	NOUN
cana-5088	163	8	issn	issn	NOUN
cana-5088	163	9	:	:	PUNCT
cana-5088	163	10	1074	1074	NUM
cana-5088	163	11	-	-	PUNCT
cana-5088	163	12	133x	133x	NUM
cana-5088	163	13	vol	vol	NOUN
cana-5088	163	14	32	32	NUM
cana-5088	163	15	no	no	NOUN
cana-5088	163	16	.	.	PUNCT
cana-5088	164	1	icmasd	icmasd	NOUN
cana-5088	164	2	(	(	PUNCT
cana-5088	164	3	2025	2025	NUM
cana-5088	164	4	)	)	PUNCT
cana-5088	164	5	595	595	NUM
cana-5088	164	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	164	7	closely	closely	ADV
cana-5088	164	8	with	with	ADP
cana-5088	164	9	a	a	DET
cana-5088	164	10	test	test	NOUN
cana-5088	164	11	accuracy	accuracy	NOUN
cana-5088	164	12	of	of	ADP
cana-5088	164	13	91.82	91.82	NUM
cana-5088	164	14	%	%	NOUN
cana-5088	164	15	and	and	CCONJ
cana-5088	164	16	a	a	DET
cana-5088	164	17	test	test	NOUN
cana-5088	164	18	loss	loss	NOUN
cana-5088	164	19	of	of	ADP
cana-5088	164	20	0.2998	0.2998	NUM
cana-5088	164	21	,	,	PUNCT
cana-5088	164	22	while	while	SCONJ
cana-5088	164	23	efficientnetb0	efficientnetb0	NOUN
cana-5088	164	24	achieved	achieve	VERB
cana-5088	164	25	a	a	DET
cana-5088	164	26	test	test	NOUN
cana-5088	164	27	accuracy	accuracy	NOUN
cana-5088	164	28	of	of	ADP
cana-5088	164	29	91.40	91.40	NUM
cana-5088	164	30	%	%	NOUN
cana-5088	164	31	and	and	CCONJ
cana-5088	164	32	a	a	DET
cana-5088	164	33	test	test	NOUN
cana-5088	164	34	loss	loss	NOUN
cana-5088	164	35	of	of	ADP
cana-5088	164	36	0.3552	0.3552	NUM
cana-5088	164	37	.	.	PUNCT
cana-5088	165	1	the	the	DET
cana-5088	165	2	performance	performance	NOUN
cana-5088	165	3	variation	variation	NOUN
cana-5088	165	4	curves	curve	NOUN
cana-5088	165	5	for	for	ADP
cana-5088	165	6	resnet50	resnet50	NOUN
cana-5088	165	7	,	,	PUNCT
cana-5088	165	8	densenet121	densenet121	PROPN
cana-5088	165	9	,	,	PUNCT
cana-5088	165	10	and	and	CCONJ
cana-5088	165	11	efficientnetb0	efficientnetb0	NOUN
cana-5088	165	12	for	for	ADP
cana-5088	165	13	training	training	NOUN
cana-5088	165	14	and	and	CCONJ
cana-5088	165	15	validation	validation	NOUN
cana-5088	165	16	data	datum	NOUN
cana-5088	165	17	accuracy	accuracy	NOUN
cana-5088	165	18	and	and	CCONJ
cana-5088	165	19	loss	loss	NOUN
cana-5088	165	20	with	with	ADP
cana-5088	165	21	epochs	epoch	NOUN
cana-5088	165	22	are	be	AUX
cana-5088	165	23	shown	show	VERB
cana-5088	165	24	in	in	ADP
cana-5088	165	25	figures	figure	NOUN
cana-5088	165	26	2	2	NUM
cana-5088	165	27	-	-	SYM
cana-5088	165	28	4	4	NUM
cana-5088	165	29	.	.	PUNCT
cana-5088	165	30	fig	fig	NOUN
cana-5088	165	31	.	.	PUNCT
cana-5088	166	1	2	2	X
cana-5088	166	2	.	.	X
cana-5088	166	3	training	training	NOUN
cana-5088	166	4	and	and	CCONJ
cana-5088	166	5	validation	validation	NOUN
cana-5088	166	6	accuracy	accuracy	NOUN
cana-5088	166	7	and	and	CCONJ
cana-5088	166	8	loss	loss	NOUN
cana-5088	166	9	curves	curve	NOUN
cana-5088	166	10	for	for	ADP
cana-5088	166	11	resnet50	resnet50	NOUN
cana-5088	166	12	fig	fig	NOUN
cana-5088	166	13	.	.	PUNCT
cana-5088	167	1	3	3	X
cana-5088	167	2	.	.	X
cana-5088	167	3	training	training	NOUN
cana-5088	167	4	and	and	CCONJ
cana-5088	167	5	validation	validation	NOUN
cana-5088	167	6	accuracy	accuracy	NOUN
cana-5088	167	7	and	and	CCONJ
cana-5088	167	8	loss	loss	NOUN
cana-5088	167	9	curves	curve	NOUN
cana-5088	167	10	for	for	ADP
cana-5088	167	11	densenet121	densenet121	PROPN
cana-5088	167	12	fig	fig	NOUN
cana-5088	167	13	.	.	PUNCT
cana-5088	168	1	4	4	X
cana-5088	168	2	.	.	X
cana-5088	168	3	training	training	NOUN
cana-5088	168	4	and	and	CCONJ
cana-5088	168	5	validation	validation	NOUN
cana-5088	168	6	accuracy	accuracy	NOUN
cana-5088	168	7	and	and	CCONJ
cana-5088	168	8	loss	loss	NOUN
cana-5088	168	9	curves	curve	NOUN
cana-5088	168	10	for	for	ADP
cana-5088	168	11	efficientnetb0	efficientnetb0	NOUN
cana-5088	168	12	tables	table	NOUN
cana-5088	168	13	3	3	NUM
cana-5088	168	14	-	-	SYM
cana-5088	168	15	5	5	NUM
cana-5088	168	16	show	show	NOUN
cana-5088	168	17	performance	performance	NOUN
cana-5088	168	18	metrics	metric	NOUN
cana-5088	168	19	for	for	ADP
cana-5088	168	20	resnet50	resnet50	NOUN
cana-5088	168	21	,	,	PUNCT
cana-5088	168	22	densenet121	densenet121	PROPN
cana-5088	168	23	,	,	PUNCT
cana-5088	168	24	and	and	CCONJ
cana-5088	168	25	efficientnetb0	efficientnetb0	PROPN
cana-5088	168	26	,	,	PUNCT
cana-5088	168	27	including	include	VERB
cana-5088	168	28	precision	precision	NOUN
cana-5088	168	29	,	,	PUNCT
cana-5088	168	30	recall	recall	NOUN
cana-5088	168	31	,	,	PUNCT
cana-5088	168	32	and	and	CCONJ
cana-5088	168	33	f1	f1	NOUN
cana-5088	168	34	-	-	PUNCT
cana-5088	168	35	score	score	NOUN
cana-5088	168	36	.	.	PUNCT
cana-5088	169	1	the	the	DET
cana-5088	169	2	classification	classification	NOUN
cana-5088	169	3	report	report	NOUN
cana-5088	169	4	of	of	ADP
cana-5088	169	5	test	test	NOUN
cana-5088	169	6	data	datum	NOUN
cana-5088	169	7	for	for	ADP
cana-5088	169	8	resnet50	resnet50	NOUN
cana-5088	169	9	demonstrates	demonstrate	VERB
cana-5088	169	10	a	a	DET
cana-5088	169	11	solid	solid	ADJ
cana-5088	169	12	overall	overall	ADJ
cana-5088	169	13	performance	performance	NOUN
cana-5088	169	14	in	in	ADP
cana-5088	169	15	waste	waste	NOUN
cana-5088	169	16	classification	classification	NOUN
cana-5088	169	17	,	,	PUNCT
cana-5088	169	18	with	with	ADP
cana-5088	169	19	balanced	balanced	ADJ
cana-5088	169	20	metrics	metric	NOUN
cana-5088	169	21	across	across	ADP
cana-5088	169	22	most	most	ADJ
cana-5088	169	23	categories	category	NOUN
cana-5088	169	24	.	.	PUNCT
cana-5088	170	1	classes	class	NOUN
cana-5088	170	2	like	like	ADP
cana-5088	170	3	communications	communication	NOUN
cana-5088	170	4	on	on	ADP
cana-5088	170	5	applied	apply	VERB
cana-5088	170	6	nonlinear	nonlinear	ADJ
cana-5088	170	7	analysis	analysis	NOUN
cana-5088	170	8	issn	issn	NOUN
cana-5088	170	9	:	:	PUNCT
cana-5088	170	10	1074	1074	NUM
cana-5088	170	11	-	-	PUNCT
cana-5088	170	12	133x	133x	NUM
cana-5088	170	13	vol	vol	NOUN
cana-5088	170	14	32	32	NUM
cana-5088	170	15	no	no	NOUN
cana-5088	170	16	.	.	PUNCT
cana-5088	171	1	icmasd	icmasd	NOUN
cana-5088	171	2	(	(	PUNCT
cana-5088	171	3	2025	2025	NUM
cana-5088	171	4	)	)	PUNCT
cana-5088	171	5	596	596	NUM
cana-5088	171	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	171	7	glass	glass	NOUN
cana-5088	171	8	,	,	PUNCT
cana-5088	171	9	vegetation	vegetation	NOUN
cana-5088	171	10	,	,	PUNCT
cana-5088	171	11	and	and	CCONJ
cana-5088	171	12	food	food	NOUN
cana-5088	171	13	organics	organic	NOUN
cana-5088	171	14	exhibit	exhibit	VERB
cana-5088	171	15	high	high	ADJ
cana-5088	171	16	precision	precision	NOUN
cana-5088	171	17	,	,	PUNCT
cana-5088	171	18	recall	recall	NOUN
cana-5088	171	19	,	,	PUNCT
cana-5088	171	20	and	and	CCONJ
cana-5088	171	21	f1	f1	NOUN
cana-5088	171	22	-	-	PUNCT
cana-5088	171	23	scores	score	NOUN
cana-5088	171	24	,	,	PUNCT
cana-5088	171	25	indicating	indicate	VERB
cana-5088	171	26	the	the	DET
cana-5088	171	27	model	model	NOUN
cana-5088	171	28	’s	’s	PART
cana-5088	171	29	strong	strong	ADJ
cana-5088	171	30	ability	ability	NOUN
cana-5088	171	31	to	to	PART
cana-5088	171	32	classify	classify	VERB
cana-5088	171	33	these	these	DET
cana-5088	171	34	categories	category	NOUN
cana-5088	171	35	.	.	PUNCT
cana-5088	172	1	however	however	ADV
cana-5088	172	2	,	,	PUNCT
cana-5088	172	3	miscellaneous	miscellaneous	ADJ
cana-5088	172	4	trash	trash	NOUN
cana-5088	172	5	shows	show	VERB
cana-5088	172	6	a	a	DET
cana-5088	172	7	notable	notable	ADJ
cana-5088	172	8	drop	drop	NOUN
cana-5088	172	9	in	in	ADP
cana-5088	172	10	recall	recall	NOUN
cana-5088	172	11	,	,	PUNCT
cana-5088	172	12	suggesting	suggest	VERB
cana-5088	172	13	that	that	SCONJ
cana-5088	172	14	some	some	DET
cana-5088	172	15	instances	instance	NOUN
cana-5088	172	16	were	be	AUX
cana-5088	172	17	misclassified	misclassifie	VERB
cana-5088	172	18	,	,	PUNCT
cana-5088	172	19	likely	likely	ADJ
cana-5088	172	20	due	due	ADP
cana-5088	172	21	to	to	ADP
cana-5088	172	22	overlaps	overlap	NOUN
cana-5088	172	23	with	with	ADP
cana-5088	172	24	other	other	ADJ
cana-5088	172	25	categories	category	NOUN
cana-5088	172	26	.	.	PUNCT
cana-5088	173	1	similarly	similarly	ADV
cana-5088	173	2	,	,	PUNCT
cana-5088	173	3	plastic	plastic	NOUN
cana-5088	173	4	and	and	CCONJ
cana-5088	173	5	cardboard	cardboard	NOUN
cana-5088	173	6	show	show	VERB
cana-5088	173	7	slight	slight	ADJ
cana-5088	173	8	variability	variability	NOUN
cana-5088	173	9	in	in	ADP
cana-5088	173	10	precision	precision	NOUN
cana-5088	173	11	and	and	CCONJ
cana-5088	173	12	recall	recall	NOUN
cana-5088	173	13	,	,	PUNCT
cana-5088	173	14	reflecting	reflect	VERB
cana-5088	173	15	occasional	occasional	ADJ
cana-5088	173	16	confusion	confusion	NOUN
cana-5088	173	17	.	.	PUNCT
cana-5088	174	1	densenet121	densenet121	VERB
cana-5088	174	2	consistently	consistently	ADV
cana-5088	174	3	demonstrated	demonstrate	VERB
cana-5088	174	4	better	well	ADJ
cana-5088	174	5	generalization	generalization	NOUN
cana-5088	174	6	,	,	PUNCT
cana-5088	174	7	with	with	ADP
cana-5088	174	8	high	high	ADJ
cana-5088	174	9	precision	precision	NOUN
cana-5088	174	10	,	,	PUNCT
cana-5088	174	11	recall	recall	NOUN
cana-5088	174	12	,	,	PUNCT
cana-5088	174	13	and	and	CCONJ
cana-5088	174	14	f1	f1	NOUN
cana-5088	174	15	-	-	PUNCT
cana-5088	174	16	scores	score	NOUN
cana-5088	174	17	for	for	ADP
cana-5088	174	18	key	key	ADJ
cana-5088	174	19	categories	category	NOUN
cana-5088	174	20	such	such	ADJ
cana-5088	174	21	as	as	ADP
cana-5088	174	22	cardboard	cardboard	NOUN
cana-5088	174	23	,	,	PUNCT
cana-5088	174	24	glass	glass	NOUN
cana-5088	174	25	,	,	PUNCT
cana-5088	174	26	textile	textile	NOUN
cana-5088	174	27	trash	trash	NOUN
cana-5088	174	28	,	,	PUNCT
cana-5088	174	29	and	and	CCONJ
cana-5088	174	30	paper	paper	NOUN
cana-5088	174	31	.	.	PUNCT
cana-5088	175	1	however	however	ADV
cana-5088	175	2	,	,	PUNCT
cana-5088	175	3	food	food	NOUN
cana-5088	175	4	organics	organic	NOUN
cana-5088	175	5	and	and	CCONJ
cana-5088	175	6	miscellaneous	miscellaneous	ADJ
cana-5088	175	7	trash	trash	NOUN
cana-5088	175	8	show	show	NOUN
cana-5088	175	9	slightly	slightly	ADV
cana-5088	175	10	lower	low	ADJ
cana-5088	175	11	recall	recall	NOUN
cana-5088	175	12	,	,	PUNCT
cana-5088	175	13	suggesting	suggest	VERB
cana-5088	175	14	that	that	SCONJ
cana-5088	175	15	some	some	DET
cana-5088	175	16	instances	instance	NOUN
cana-5088	175	17	were	be	AUX
cana-5088	175	18	misclassified	misclassifie	VERB
cana-5088	175	19	,	,	PUNCT
cana-5088	175	20	likely	likely	ADJ
cana-5088	175	21	due	due	ADJ
cana-5088	175	22	to	to	ADP
cana-5088	175	23	shared	share	VERB
cana-5088	175	24	features	feature	NOUN
cana-5088	175	25	with	with	ADP
cana-5088	175	26	other	other	ADJ
cana-5088	175	27	categories	category	NOUN
cana-5088	175	28	.	.	PUNCT
cana-5088	176	1	efficientnetb0	efficientnetb0	PROPN
cana-5088	176	2	demonstrated	demonstrate	VERB
cana-5088	176	3	satisfactory	satisfactory	ADJ
cana-5088	176	4	performance	performance	NOUN
cana-5088	176	5	,	,	PUNCT
cana-5088	176	6	achieving	achieve	VERB
cana-5088	176	7	high	high	ADJ
cana-5088	176	8	f1	f1	NOUN
cana-5088	176	9	-	-	PUNCT
cana-5088	176	10	scores	score	NOUN
cana-5088	176	11	for	for	ADP
cana-5088	176	12	categories	category	NOUN
cana-5088	176	13	such	such	ADJ
cana-5088	176	14	as	as	ADP
cana-5088	176	15	glass	glass	NOUN
cana-5088	176	16	,	,	PUNCT
cana-5088	176	17	paper	paper	NOUN
cana-5088	176	18	,	,	PUNCT
cana-5088	176	19	and	and	CCONJ
cana-5088	176	20	vegetation	vegetation	NOUN
cana-5088	176	21	indicating	indicate	VERB
cana-5088	176	22	strong	strong	ADJ
cana-5088	176	23	precision	precision	NOUN
cana-5088	176	24	and	and	CCONJ
cana-5088	176	25	recall	recall	NOUN
cana-5088	176	26	for	for	ADP
cana-5088	176	27	these	these	DET
cana-5088	176	28	waste	waste	NOUN
cana-5088	176	29	types	type	NOUN
cana-5088	176	30	.	.	PUNCT
cana-5088	177	1	cardboard	cardboard	NOUN
cana-5088	177	2	and	and	CCONJ
cana-5088	177	3	metal	metal	NOUN
cana-5088	177	4	also	also	ADV
cana-5088	177	5	performed	perform	VERB
cana-5088	177	6	well	well	ADV
cana-5088	177	7	,	,	PUNCT
cana-5088	177	8	though	though	SCONJ
cana-5088	177	9	cardboard	cardboard	NOUN
cana-5088	177	10	showed	show	VERB
cana-5088	177	11	slightly	slightly	ADV
cana-5088	177	12	lower	low	ADJ
cana-5088	177	13	recall	recall	NOUN
cana-5088	177	14	,	,	PUNCT
cana-5088	177	15	suggesting	suggest	VERB
cana-5088	177	16	occasional	occasional	ADJ
cana-5088	177	17	misclassification	misclassification	NOUN
cana-5088	177	18	.	.	PUNCT
cana-5088	178	1	however	however	ADV
cana-5088	178	2	,	,	PUNCT
cana-5088	178	3	it	it	PRON
cana-5088	178	4	struggled	struggle	VERB
cana-5088	178	5	in	in	ADP
cana-5088	178	6	categories	category	NOUN
cana-5088	178	7	like	like	ADP
cana-5088	178	8	food	food	NOUN
cana-5088	178	9	organics	organic	NOUN
cana-5088	178	10	and	and	CCONJ
cana-5088	178	11	miscellaneous	miscellaneous	ADJ
cana-5088	178	12	trash	trash	NOUN
cana-5088	178	13	,	,	PUNCT
cana-5088	178	14	where	where	SCONJ
cana-5088	178	15	lower	low	ADJ
cana-5088	178	16	recall	recall	NOUN
cana-5088	178	17	impacted	impact	VERB
cana-5088	178	18	its	its	PRON
cana-5088	178	19	overall	overall	ADJ
cana-5088	178	20	performance	performance	NOUN
cana-5088	178	21	.	.	PUNCT
cana-5088	179	1	overall	overall	ADV
cana-5088	179	2	,	,	PUNCT
cana-5088	179	3	densenet121	densenet121	PROPN
cana-5088	179	4	slightly	slightly	ADV
cana-5088	179	5	edges	edge	VERB
cana-5088	179	6	out	out	ADP
cana-5088	179	7	the	the	DET
cana-5088	179	8	others	other	NOUN
cana-5088	179	9	in	in	ADP
cana-5088	179	10	balancing	balance	VERB
cana-5088	179	11	precision	precision	NOUN
cana-5088	179	12	and	and	CCONJ
cana-5088	179	13	recall	recall	NOUN
cana-5088	179	14	.	.	PUNCT
cana-5088	180	1	table	table	NOUN
cana-5088	180	2	3	3	NUM
cana-5088	180	3	.	.	PUNCT
cana-5088	180	4	performance	performance	NOUN
cana-5088	180	5	metrics	metric	NOUN
cana-5088	180	6	of	of	ADP
cana-5088	180	7	resnet50	resnet50	NOUN
cana-5088	180	8	model	model	NOUN
cana-5088	180	9	class	class	PROPN
cana-5088	180	10	precision	precision	NOUN
cana-5088	180	11	recall	recall	NOUN
cana-5088	180	12	f1score	f1score	NOUN
cana-5088	180	13	cardboard	cardboard	NOUN
cana-5088	180	14	0.88	0.88	NUM
cana-5088	180	15	0.96	0.96	NUM
cana-5088	180	16	0.92	0.92	NUM
cana-5088	180	17	food	food	NOUN
cana-5088	180	18	organics	organic	NOUN
cana-5088	180	19	0.97	0.97	NUM
cana-5088	180	20	0.90	0.90	NUM
cana-5088	180	21	0.94	0.94	NUM
cana-5088	180	22	glass	glass	NOUN
cana-5088	180	23	0.98	0.98	NUM
cana-5088	180	24	0.95	0.95	NUM
cana-5088	180	25	0.96	0.96	NUM
cana-5088	180	26	metal	metal	NOUN
cana-5088	180	27	0.92	0.92	NUM
cana-5088	180	28	0.93	0.93	NUM
cana-5088	180	29	0.92	0.92	NUM
cana-5088	180	30	miscellaneous	miscellaneous	ADJ
cana-5088	180	31	trash	trash	NOUN
cana-5088	180	32	0.97	0.97	NUM
cana-5088	180	33	0.72	0.72	NUM
cana-5088	180	34	0.83	0.83	NUM
cana-5088	180	35	paper	paper	NOUN
cana-5088	180	36	0.90	0.90	NUM
cana-5088	180	37	0.95	0.95	NUM
cana-5088	180	38	0.92	0.92	NUM
cana-5088	180	39	plastic	plastic	NOUN
cana-5088	180	40	0.88	0.88	NUM
cana-5088	180	41	0.95	0.95	NUM
cana-5088	180	42	0.91	0.91	NUM
cana-5088	180	43	textile	textile	NOUN
cana-5088	180	44	trash	trash	NOUN
cana-5088	180	45	0.95	0.95	NUM
cana-5088	180	46	0.89	0.89	NUM
cana-5088	180	47	0.92	0.92	NUM
cana-5088	180	48	vegetation	vegetation	NOUN
cana-5088	180	49	0.91	0.91	NUM
cana-5088	180	50	0.99	0.99	NUM
cana-5088	180	51	0.95	0.95	NUM
cana-5088	180	52	table	table	NOUN
cana-5088	180	53	4	4	NUM
cana-5088	180	54	.	.	PUNCT
cana-5088	180	55	performance	performance	NOUN
cana-5088	180	56	metrics	metric	NOUN
cana-5088	180	57	of	of	ADP
cana-5088	180	58	densenet121	densenet121	PROPN
cana-5088	180	59	model	model	NOUN
cana-5088	180	60	class	class	NOUN
cana-5088	180	61	precision	precision	NOUN
cana-5088	180	62	recall	recall	NOUN
cana-5088	180	63	f1score	f1score	NOUN
cana-5088	180	64	cardboard	cardboard	PROPN
cana-5088	180	65	0.96	0.96	NUM
cana-5088	180	66	0.98	0.98	NUM
cana-5088	180	67	0.97	0.97	NUM
cana-5088	180	68	food	food	NOUN
cana-5088	180	69	organics	organic	NOUN
cana-5088	180	70	0.99	0.99	NUM
cana-5088	180	71	0.84	0.84	NUM
cana-5088	180	72	0.91	0.91	NUM
cana-5088	180	73	glass	glass	NOUN
cana-5088	180	74	0.95	0.95	NUM
cana-5088	180	75	0.98	0.98	NUM
cana-5088	180	76	0.96	0.96	NUM
cana-5088	180	77	metal	metal	NOUN
cana-5088	180	78	0.94	0.94	NUM
cana-5088	180	79	0.97	0.97	NUM
cana-5088	180	80	0.96	0.96	NUM
cana-5088	180	81	miscellaneous	miscellaneous	ADJ
cana-5088	180	82	trash	trash	NOUN
cana-5088	180	83	0.90	0.90	NUM
cana-5088	180	84	0.88	0.88	NUM
cana-5088	180	85	0.89	0.89	NUM
cana-5088	180	86	paper	paper	NOUN
cana-5088	180	87	0.97	0.97	NUM
cana-5088	180	88	1.00	1.00	NUM
cana-5088	180	89	0.99	0.99	NUM
cana-5088	180	90	plastic	plastic	NOUN
cana-5088	180	91	0.95	0.95	NUM
cana-5088	180	92	0.92	0.92	NUM
cana-5088	180	93	0.93	0.93	NUM
cana-5088	180	94	textile	textile	NOUN
cana-5088	180	95	trash	trash	NOUN
cana-5088	180	96	0.98	0.98	NUM
cana-5088	180	97	0.91	0.91	NUM
cana-5088	180	98	0.94	0.94	NUM
cana-5088	180	99	communications	communication	NOUN
cana-5088	180	100	on	on	ADP
cana-5088	180	101	applied	apply	VERB
cana-5088	180	102	nonlinear	nonlinear	ADJ
cana-5088	180	103	analysis	analysis	NOUN
cana-5088	180	104	issn	issn	NOUN
cana-5088	180	105	:	:	PUNCT
cana-5088	180	106	1074	1074	NUM
cana-5088	180	107	-	-	PUNCT
cana-5088	180	108	133x	133x	NUM
cana-5088	180	109	vol	vol	NOUN
cana-5088	180	110	32	32	NUM
cana-5088	180	111	no	no	NOUN
cana-5088	180	112	.	.	PUNCT
cana-5088	181	1	icmasd	icmasd	NOUN
cana-5088	181	2	(	(	PUNCT
cana-5088	181	3	2025	2025	NUM
cana-5088	181	4	)	)	PUNCT
cana-5088	181	5	597	597	NUM
cana-5088	181	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	181	7	vegetation	vegetation	NOUN
cana-5088	181	8	0.88	0.88	NUM
cana-5088	181	9	1.00	1.00	NUM
cana-5088	181	10	0.94	0.94	NUM
cana-5088	181	11	table	table	NOUN
cana-5088	181	12	5	5	NUM
cana-5088	181	13	.	.	PUNCT
cana-5088	181	14	performance	performance	NOUN
cana-5088	181	15	metrics	metric	NOUN
cana-5088	181	16	of	of	ADP
cana-5088	181	17	efficientnetb0	efficientnetb0	PROPN
cana-5088	181	18	model	model	NOUN
cana-5088	181	19	class	class	PROPN
cana-5088	181	20	precision	precision	PROPN
cana-5088	181	21	recall	recall	NOUN
cana-5088	181	22	f1score	f1score	NOUN
cana-5088	181	23	cardboard	cardboard	PROPN
cana-5088	181	24	0.96	0.96	NUM
cana-5088	181	25	0.88	0.88	NUM
cana-5088	181	26	0.92	0.92	NUM
cana-5088	181	27	food	food	NOUN
cana-5088	181	28	organics	organic	NOUN
cana-5088	181	29	1.00	1.00	NUM
cana-5088	181	30	0.80	0.80	NUM
cana-5088	181	31	0.89	0.89	NUM
cana-5088	181	32	glass	glass	NOUN
cana-5088	181	33	0.98	0.98	NUM
cana-5088	181	34	0.94	0.94	NUM
cana-5088	181	35	0.96	0.96	NUM
cana-5088	181	36	metal	metal	NOUN
cana-5088	181	37	0.87	0.87	NUM
cana-5088	181	38	0.98	0.98	NUM
cana-5088	181	39	0.92	0.92	NUM
cana-5088	181	40	miscellaneous	miscellaneous	ADJ
cana-5088	181	41	trash	trash	NOUN
cana-5088	181	42	0.91	0.91	NUM
cana-5088	181	43	0.81	0.81	NUM
cana-5088	181	44	0.86	0.86	NUM
cana-5088	181	45	paper	paper	NOUN
cana-5088	181	46	0.88	0.88	NUM
cana-5088	181	47	0.99	0.99	NUM
cana-5088	181	48	0.93	0.93	NUM
cana-5088	181	49	plastic	plastic	NOUN
cana-5088	181	50	0.92	0.92	NUM
cana-5088	181	51	0.89	0.89	NUM
cana-5088	181	52	0.90	0.90	NUM
cana-5088	181	53	textile	textile	NOUN
cana-5088	181	54	trash	trash	NOUN
cana-5088	181	55	0.93	0.93	NUM
cana-5088	181	56	0.89	0.89	NUM
cana-5088	181	57	0.91	0.91	NUM
cana-5088	181	58	vegetation	vegetation	NOUN
cana-5088	181	59	0.86	0.86	NUM
cana-5088	181	60	1.00	1.00	NUM
cana-5088	181	61	0.93	0.93	NUM
cana-5088	181	62	the	the	DET
cana-5088	181	63	confusion	confusion	NOUN
cana-5088	181	64	matrices	matrix	NOUN
cana-5088	181	65	for	for	ADP
cana-5088	181	66	the	the	DET
cana-5088	181	67	resnet50	resnet50	NOUN
cana-5088	181	68	,	,	PUNCT
cana-5088	181	69	densenet121	densenet121	PROPN
cana-5088	181	70	,	,	PUNCT
cana-5088	181	71	and	and	CCONJ
cana-5088	181	72	efficientnetb0	efficientnetb0	NOUN
cana-5088	181	73	models	model	NOUN
cana-5088	181	74	shown	show	VERB
cana-5088	181	75	in	in	ADP
cana-5088	181	76	figures	figure	NOUN
cana-5088	181	77	5	5	NUM
cana-5088	181	78	-	-	SYM
cana-5088	181	79	7	7	NUM
cana-5088	181	80	reveal	reveal	VERB
cana-5088	181	81	strong	strong	ADJ
cana-5088	181	82	classification	classification	NOUN
cana-5088	181	83	performance	performance	NOUN
cana-5088	181	84	across	across	ADP
cana-5088	181	85	most	most	ADJ
cana-5088	181	86	waste	waste	NOUN
cana-5088	181	87	categories	category	NOUN
cana-5088	181	88	,	,	PUNCT
cana-5088	181	89	with	with	ADP
cana-5088	181	90	some	some	DET
cana-5088	181	91	variations	variation	NOUN
cana-5088	181	92	in	in	ADP
cana-5088	181	93	accuracy	accuracy	NOUN
cana-5088	181	94	and	and	CCONJ
cana-5088	181	95	misclassifications	misclassification	NOUN
cana-5088	181	96	.	.	PUNCT
cana-5088	182	1	all	all	DET
cana-5088	182	2	three	three	NUM
cana-5088	182	3	models	model	NOUN
cana-5088	182	4	excel	excel	VERB
cana-5088	182	5	in	in	ADP
cana-5088	182	6	categories	category	NOUN
cana-5088	182	7	like	like	ADP
cana-5088	182	8	metal	metal	NOUN
cana-5088	182	9	,	,	PUNCT
cana-5088	182	10	glass	glass	NOUN
cana-5088	182	11	,	,	PUNCT
cana-5088	182	12	and	and	CCONJ
cana-5088	182	13	vegetation	vegetation	NOUN
cana-5088	182	14	,	,	PUNCT
cana-5088	182	15	showcasing	showcase	VERB
cana-5088	182	16	their	their	PRON
cana-5088	182	17	ability	ability	NOUN
cana-5088	182	18	to	to	PART
cana-5088	182	19	distinguish	distinguish	VERB
cana-5088	182	20	well	well	ADV
cana-5088	182	21	-	-	PUNCT
cana-5088	182	22	defined	define	VERB
cana-5088	182	23	features	feature	NOUN
cana-5088	182	24	.	.	PUNCT
cana-5088	183	1	resnet50	resnet50	NOUN
cana-5088	183	2	demonstrates	demonstrate	VERB
cana-5088	183	3	high	high	ADJ
cana-5088	183	4	accuracy	accuracy	NOUN
cana-5088	183	5	but	but	CCONJ
cana-5088	183	6	struggles	struggle	VERB
cana-5088	183	7	slightly	slightly	ADV
cana-5088	183	8	with	with	ADP
cana-5088	183	9	miscellaneous	miscellaneous	ADJ
cana-5088	183	10	trash	trash	NOUN
cana-5088	183	11	,	,	PUNCT
cana-5088	183	12	confusing	confuse	VERB
cana-5088	183	13	it	it	PRON
cana-5088	183	14	with	with	ADP
cana-5088	183	15	food	food	NOUN
cana-5088	183	16	organics	organic	NOUN
cana-5088	183	17	and	and	CCONJ
cana-5088	183	18	plastic	plastic	NOUN
cana-5088	183	19	.	.	PUNCT
cana-5088	184	1	densenet121	densenet121	PROPN
cana-5088	184	2	achieves	achieve	VERB
cana-5088	184	3	strong	strong	ADJ
cana-5088	184	4	results	result	NOUN
cana-5088	184	5	in	in	ADP
cana-5088	184	6	most	most	ADJ
cana-5088	184	7	categories	category	NOUN
cana-5088	184	8	,	,	PUNCT
cana-5088	184	9	with	with	ADP
cana-5088	184	10	minimal	minimal	ADJ
cana-5088	184	11	misclassifications	misclassification	NOUN
cana-5088	184	12	,	,	PUNCT
cana-5088	184	13	but	but	CCONJ
cana-5088	184	14	shows	show	VERB
cana-5088	184	15	confusion	confusion	NOUN
cana-5088	184	16	between	between	ADP
cana-5088	184	17	vegetation	vegetation	NOUN
cana-5088	184	18	and	and	CCONJ
cana-5088	184	19	food	food	NOUN
cana-5088	184	20	organics	organic	NOUN
cana-5088	184	21	.	.	PUNCT
cana-5088	185	1	efficientnetb0	efficientnetb0	PROPN
cana-5088	185	2	also	also	ADV
cana-5088	185	3	performs	perform	VERB
cana-5088	185	4	well	well	ADV
cana-5088	185	5	but	but	CCONJ
cana-5088	185	6	exhibits	exhibit	VERB
cana-5088	185	7	slight	slight	ADJ
cana-5088	185	8	difficulty	difficulty	NOUN
cana-5088	185	9	in	in	ADP
cana-5088	185	10	distinguishing	distinguish	VERB
cana-5088	185	11	plastic	plastic	NOUN
cana-5088	185	12	from	from	ADP
cana-5088	185	13	cardboard	cardboard	NOUN
cana-5088	185	14	and	and	CCONJ
cana-5088	185	15	metal	metal	NOUN
cana-5088	185	16	.	.	PUNCT
cana-5088	186	1	across	across	ADP
cana-5088	186	2	all	all	DET
cana-5088	186	3	models	model	NOUN
cana-5088	186	4	,	,	PUNCT
cana-5088	186	5	visually	visually	ADV
cana-5088	186	6	or	or	CCONJ
cana-5088	186	7	texturally	texturally	ADV
cana-5088	186	8	similar	similar	ADJ
cana-5088	186	9	categories	category	NOUN
cana-5088	186	10	,	,	PUNCT
cana-5088	186	11	such	such	ADJ
cana-5088	186	12	as	as	ADP
cana-5088	186	13	food	food	NOUN
cana-5088	186	14	organics	organic	NOUN
cana-5088	186	15	and	and	CCONJ
cana-5088	186	16	vegetation	vegetation	NOUN
cana-5088	186	17	or	or	CCONJ
cana-5088	186	18	plastic	plastic	NOUN
cana-5088	186	19	and	and	CCONJ
cana-5088	186	20	miscellaneous	miscellaneous	ADJ
cana-5088	186	21	trash	trash	NOUN
cana-5088	186	22	,	,	PUNCT
cana-5088	186	23	pose	pose	VERB
cana-5088	186	24	challenges	challenge	NOUN
cana-5088	186	25	,	,	PUNCT
cana-5088	186	26	indicating	indicate	VERB
cana-5088	186	27	areas	area	NOUN
cana-5088	186	28	where	where	SCONJ
cana-5088	186	29	fine	fine	ADV
cana-5088	186	30	-	-	PUNCT
cana-5088	186	31	tuning	tuning	NOUN
cana-5088	186	32	or	or	CCONJ
cana-5088	186	33	additional	additional	ADJ
cana-5088	186	34	data	datum	NOUN
cana-5088	186	35	preprocessing	preprocessing	NOUN
cana-5088	186	36	may	may	AUX
cana-5088	186	37	improve	improve	VERB
cana-5088	186	38	performance	performance	NOUN
cana-5088	186	39	.	.	PUNCT
cana-5088	187	1	fig	fig	NOUN
cana-5088	187	2	.	.	PUNCT
cana-5088	188	1	5	5	NUM
cana-5088	188	2	.	.	X
cana-5088	188	3	confusion	confusion	NOUN
cana-5088	188	4	matrix	matrix	NOUN
cana-5088	188	5	for	for	ADP
cana-5088	188	6	resnet50	resnet50	NOUN
cana-5088	188	7	model	model	NOUN
cana-5088	188	8	communications	communication	NOUN
cana-5088	188	9	on	on	ADP
cana-5088	188	10	applied	apply	VERB
cana-5088	188	11	nonlinear	nonlinear	ADJ
cana-5088	188	12	analysis	analysis	NOUN
cana-5088	188	13	issn	issn	NOUN
cana-5088	188	14	:	:	PUNCT
cana-5088	188	15	1074	1074	NUM
cana-5088	188	16	-	-	PUNCT
cana-5088	188	17	133x	133x	NUM
cana-5088	188	18	vol	vol	NOUN
cana-5088	188	19	32	32	NUM
cana-5088	188	20	no	no	NOUN
cana-5088	188	21	.	.	PUNCT
cana-5088	189	1	icmasd	icmasd	NOUN
cana-5088	189	2	(	(	PUNCT
cana-5088	189	3	2025	2025	NUM
cana-5088	189	4	)	)	PUNCT
cana-5088	189	5	598	598	NUM
cana-5088	189	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	189	7	fig	fig	NOUN
cana-5088	189	8	.	.	PUNCT
cana-5088	190	1	6	6	NUM
cana-5088	190	2	.	.	X
cana-5088	190	3	confusion	confusion	NOUN
cana-5088	190	4	matrix	matrix	NOUN
cana-5088	190	5	for	for	ADP
cana-5088	190	6	densenet121	densenet121	PROPN
cana-5088	190	7	model	model	NOUN
cana-5088	190	8	fig	fig	NOUN
cana-5088	190	9	.	.	PUNCT
cana-5088	191	1	7	7	X
cana-5088	191	2	.	.	X
cana-5088	191	3	confusion	confusion	NOUN
cana-5088	191	4	matrix	matrix	NOUN
cana-5088	191	5	for	for	ADP
cana-5088	191	6	efficientnetb0	efficientnetb0	NOUN
cana-5088	191	7	model	model	NOUN
cana-5088	191	8	the	the	DET
cana-5088	191	9	results	result	NOUN
cana-5088	191	10	reveal	reveal	VERB
cana-5088	191	11	several	several	ADJ
cana-5088	191	12	key	key	ADJ
cana-5088	191	13	insights	insight	NOUN
cana-5088	191	14	into	into	ADP
cana-5088	191	15	the	the	DET
cana-5088	191	16	comparative	comparative	ADJ
cana-5088	191	17	performance	performance	NOUN
cana-5088	191	18	of	of	ADP
cana-5088	191	19	the	the	DET
cana-5088	191	20	three	three	NUM
cana-5088	191	21	pre	pre	ADJ
cana-5088	191	22	-	-	ADJ
cana-5088	191	23	trained	train	VERB
cana-5088	191	24	models	model	NOUN
cana-5088	191	25	.	.	PUNCT
cana-5088	192	1	densenet121	densenet121	PROPN
cana-5088	192	2	emerged	emerge	VERB
cana-5088	192	3	as	as	ADP
cana-5088	192	4	the	the	DET
cana-5088	192	5	most	most	ADV
cana-5088	192	6	robust	robust	ADJ
cana-5088	192	7	model	model	NOUN
cana-5088	192	8	in	in	ADP
cana-5088	192	9	the	the	DET
cana-5088	192	10	study	study	NOUN
cana-5088	192	11	,	,	PUNCT
cana-5088	192	12	showing	show	VERB
cana-5088	192	13	the	the	DET
cana-5088	192	14	highest	high	ADJ
cana-5088	192	15	test	test	NOUN
cana-5088	192	16	accuracy	accuracy	NOUN
cana-5088	192	17	of	of	ADP
cana-5088	192	18	94.33	94.33	NUM
cana-5088	192	19	%	%	NOUN
cana-5088	192	20	and	and	CCONJ
cana-5088	192	21	the	the	DET
cana-5088	192	22	lowest	low	ADJ
cana-5088	192	23	test	test	NOUN
cana-5088	192	24	loss	loss	NOUN
cana-5088	192	25	.	.	PUNCT
cana-5088	193	1	its	its	PRON
cana-5088	193	2	strong	strong	ADJ
cana-5088	193	3	generalization	generalization	NOUN
cana-5088	193	4	ability	ability	NOUN
cana-5088	193	5	is	be	AUX
cana-5088	193	6	attributed	attribute	VERB
cana-5088	193	7	to	to	ADP
cana-5088	193	8	its	its	PRON
cana-5088	193	9	architecture	architecture	NOUN
cana-5088	193	10	,	,	PUNCT
cana-5088	193	11	which	which	PRON
cana-5088	193	12	preserves	preserve	VERB
cana-5088	193	13	feature	feature	NOUN
cana-5088	193	14	flow	flow	NOUN
cana-5088	193	15	through	through	ADP
cana-5088	193	16	dense	dense	ADJ
cana-5088	193	17	connections	connection	NOUN
cana-5088	193	18	,	,	PUNCT
cana-5088	193	19	allowing	allow	VERB
cana-5088	193	20	for	for	ADP
cana-5088	193	21	better	well	ADJ
cana-5088	193	22	feature	feature	NOUN
cana-5088	193	23	reuse	reuse	NOUN
cana-5088	193	24	.	.	PUNCT
cana-5088	194	1	the	the	DET
cana-5088	194	2	model	model	NOUN
cana-5088	194	3	did	do	AUX
cana-5088	194	4	not	not	PART
cana-5088	194	5	exhibit	exhibit	VERB
cana-5088	194	6	early	early	ADJ
cana-5088	194	7	stopping	stopping	NOUN
cana-5088	194	8	,	,	PUNCT
cana-5088	194	9	demonstrating	demonstrate	VERB
cana-5088	194	10	stable	stable	ADJ
cana-5088	194	11	learning	learning	NOUN
cana-5088	194	12	even	even	ADV
cana-5088	194	13	over	over	ADP
cana-5088	194	14	prolonged	prolonged	ADJ
cana-5088	194	15	training	training	NOUN
cana-5088	194	16	,	,	PUNCT
cana-5088	194	17	which	which	PRON
cana-5088	194	18	is	be	AUX
cana-5088	194	19	particularly	particularly	ADV
cana-5088	194	20	advantageous	advantageous	ADJ
cana-5088	194	21	for	for	ADP
cana-5088	194	22	tasks	task	NOUN
cana-5088	194	23	requiring	require	VERB
cana-5088	194	24	comprehensive	comprehensive	ADJ
cana-5088	194	25	feature	feature	NOUN
cana-5088	194	26	extraction	extraction	NOUN
cana-5088	194	27	.	.	PUNCT
cana-5088	195	1	densenet121	densenet121	PROPN
cana-5088	195	2	’s	’s	PART
cana-5088	195	3	balanced	balanced	ADJ
cana-5088	195	4	training	training	NOUN
cana-5088	195	5	and	and	CCONJ
cana-5088	195	6	validation	validation	NOUN
cana-5088	195	7	performance	performance	NOUN
cana-5088	195	8	further	far	ADV
cana-5088	195	9	underscore	underscore	VERB
cana-5088	195	10	its	its	PRON
cana-5088	195	11	reliability	reliability	NOUN
cana-5088	195	12	for	for	ADP
cana-5088	195	13	waste	waste	NOUN
cana-5088	195	14	classification	classification	NOUN
cana-5088	195	15	.	.	PUNCT
cana-5088	196	1	resnet50	resnet50	NOUN
cana-5088	196	2	demonstrated	demonstrate	VERB
cana-5088	196	3	efficient	efficient	ADJ
cana-5088	196	4	learning	learning	NOUN
cana-5088	196	5	,	,	PUNCT
cana-5088	196	6	benefiting	benefit	VERB
cana-5088	196	7	from	from	ADP
cana-5088	196	8	early	early	ADJ
cana-5088	196	9	stopping	stopping	NOUN
cana-5088	196	10	at	at	ADP
cana-5088	196	11	an	an	DET
cana-5088	196	12	earlier	early	ADJ
cana-5088	196	13	epoch	epoch	NOUN
cana-5088	196	14	.	.	PUNCT
cana-5088	197	1	this	this	PRON
cana-5088	197	2	reflects	reflect	VERB
cana-5088	197	3	its	its	PRON
cana-5088	197	4	ability	ability	NOUN
cana-5088	197	5	to	to	PART
cana-5088	197	6	capture	capture	VERB
cana-5088	197	7	meaningful	meaningful	ADJ
cana-5088	197	8	patterns	pattern	NOUN
cana-5088	197	9	in	in	ADP
cana-5088	197	10	the	the	DET
cana-5088	197	11	training	training	NOUN
cana-5088	197	12	data	datum	NOUN
cana-5088	197	13	quickly	quickly	ADV
cana-5088	197	14	.	.	PUNCT
cana-5088	198	1	while	while	SCONJ
cana-5088	198	2	resnet50	resnet50	PROPN
cana-5088	198	3	's	's	PART
cana-5088	198	4	test	test	NOUN
cana-5088	198	5	accuracy	accuracy	NOUN
cana-5088	198	6	(	(	PUNCT
cana-5088	198	7	91.82	91.82	NUM
cana-5088	198	8	%	%	NOUN
cana-5088	198	9	)	)	PUNCT
cana-5088	198	10	was	be	AUX
cana-5088	198	11	competitive	competitive	ADJ
cana-5088	198	12	,	,	PUNCT
cana-5088	198	13	its	its	PRON
cana-5088	198	14	performance	performance	NOUN
cana-5088	198	15	suggests	suggest	VERB
cana-5088	198	16	that	that	SCONJ
cana-5088	198	17	it	it	PRON
cana-5088	198	18	is	be	AUX
cana-5088	198	19	well	well	ADV
cana-5088	198	20	-	-	PUNCT
cana-5088	198	21	suited	suit	VERB
cana-5088	198	22	for	for	ADP
cana-5088	198	23	scenarios	scenario	NOUN
cana-5088	198	24	where	where	SCONJ
cana-5088	198	25	training	training	NOUN
cana-5088	198	26	time	time	NOUN
cana-5088	198	27	is	be	AUX
cana-5088	198	28	critical	critical	ADJ
cana-5088	198	29	,	,	PUNCT
cana-5088	198	30	though	though	SCONJ
cana-5088	198	31	further	further	ADJ
cana-5088	198	32	regularization	regularization	NOUN
cana-5088	198	33	could	could	AUX
cana-5088	198	34	improve	improve	VERB
cana-5088	198	35	generalization	generalization	NOUN
cana-5088	198	36	.	.	PUNCT
cana-5088	199	1	efficientnetb0	efficientnetb0	PROPN
cana-5088	199	2	,	,	PUNCT
cana-5088	199	3	known	know	VERB
cana-5088	199	4	for	for	ADP
cana-5088	199	5	its	its	PRON
cana-5088	199	6	computational	computational	ADJ
cana-5088	199	7	efficiency	efficiency	NOUN
cana-5088	199	8	,	,	PUNCT
cana-5088	199	9	performed	perform	VERB
cana-5088	199	10	well	well	ADV
cana-5088	199	11	but	but	CCONJ
cana-5088	199	12	slightly	slightly	ADV
cana-5088	199	13	underperformed	underperform	VERB
cana-5088	199	14	with	with	ADP
cana-5088	199	15	a	a	DET
cana-5088	199	16	test	test	NOUN
cana-5088	199	17	accuracy	accuracy	NOUN
cana-5088	199	18	of	of	ADP
cana-5088	199	19	91.40	91.40	NUM
cana-5088	199	20	%	%	NOUN
cana-5088	199	21	and	and	CCONJ
cana-5088	199	22	higher	high	ADJ
cana-5088	199	23	test	test	NOUN
cana-5088	199	24	loss	loss	NOUN
cana-5088	199	25	compared	compare	VERB
cana-5088	199	26	to	to	ADP
cana-5088	199	27	the	the	DET
cana-5088	199	28	other	other	ADJ
cana-5088	199	29	models	model	NOUN
cana-5088	199	30	.	.	PUNCT
cana-5088	200	1	the	the	DET
cana-5088	200	2	validation	validation	NOUN
cana-5088	200	3	and	and	CCONJ
cana-5088	200	4	communications	communication	NOUN
cana-5088	200	5	on	on	ADP
cana-5088	200	6	applied	apply	VERB
cana-5088	200	7	nonlinear	nonlinear	ADJ
cana-5088	200	8	analysis	analysis	NOUN
cana-5088	200	9	issn	issn	NOUN
cana-5088	200	10	:	:	PUNCT
cana-5088	200	11	1074	1074	NUM
cana-5088	200	12	-	-	PUNCT
cana-5088	200	13	133x	133x	NUM
cana-5088	200	14	vol	vol	NOUN
cana-5088	200	15	32	32	NUM
cana-5088	200	16	no	no	NOUN
cana-5088	200	17	.	.	PUNCT
cana-5088	201	1	icmasd	icmasd	NOUN
cana-5088	201	2	(	(	PUNCT
cana-5088	201	3	2025	2025	NUM
cana-5088	201	4	)	)	PUNCT
cana-5088	201	5	599	599	NUM
cana-5088	201	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5088	201	7	test	test	NOUN
cana-5088	201	8	results	result	NOUN
cana-5088	201	9	of	of	ADP
cana-5088	201	10	efficientnetb0	efficientnetb0	NOUN
cana-5088	201	11	suggest	suggest	VERB
cana-5088	201	12	it	it	PRON
cana-5088	201	13	may	may	AUX
cana-5088	201	14	be	be	AUX
cana-5088	201	15	more	more	ADV
cana-5088	201	16	sensitive	sensitive	ADJ
cana-5088	201	17	to	to	ADP
cana-5088	201	18	dataset	dataset	ADJ
cana-5088	201	19	variability	variability	NOUN
cana-5088	201	20	,	,	PUNCT
cana-5088	201	21	requiring	require	VERB
cana-5088	201	22	additional	additional	ADJ
cana-5088	201	23	optimization	optimization	NOUN
cana-5088	201	24	,	,	PUNCT
cana-5088	201	25	such	such	ADJ
cana-5088	201	26	as	as	ADP
cana-5088	201	27	better	well	ADJ
cana-5088	201	28	hyperparameter	hyperparameter	NOUN
cana-5088	201	29	tuning	tuning	NOUN
cana-5088	201	30	or	or	CCONJ
cana-5088	201	31	enhanced	enhanced	ADJ
cana-5088	201	32	data	datum	NOUN
cana-5088	201	33	augmentation	augmentation	NOUN
cana-5088	201	34	,	,	PUNCT
cana-5088	201	35	to	to	PART
cana-5088	201	36	improve	improve	VERB
cana-5088	201	37	its	its	PRON
cana-5088	201	38	generalization	generalization	NOUN
cana-5088	201	39	.	.	PUNCT
cana-5088	202	1	nonetheless	nonetheless	ADV
cana-5088	202	2	,	,	PUNCT
cana-5088	202	3	its	its	PRON
cana-5088	202	4	lightweight	lightweight	ADJ
cana-5088	202	5	design	design	NOUN
cana-5088	202	6	makes	make	VERB
cana-5088	202	7	it	it	PRON
cana-5088	202	8	an	an	DET
cana-5088	202	9	appealing	appealing	ADJ
cana-5088	202	10	choice	choice	NOUN
cana-5088	202	11	for	for	ADP
cana-5088	202	12	resource	resource	NOUN
cana-5088	202	13	-	-	PUNCT
cana-5088	202	14	constrained	constrain	VERB
cana-5088	202	15	environments	environment	NOUN
cana-5088	202	16	.	.	PUNCT
cana-5088	203	1	the	the	DET
cana-5088	203	2	results	result	NOUN
cana-5088	203	3	demonstrate	demonstrate	VERB
cana-5088	203	4	that	that	SCONJ
cana-5088	203	5	the	the	DET
cana-5088	203	6	proposed	propose	VERB
cana-5088	203	7	densenet121	densenet121	PROPN
cana-5088	203	8	model	model	NOUN
cana-5088	203	9	outperformed	outperform	VERB
cana-5088	203	10	state	state	NOUN
cana-5088	203	11	-	-	PUNCT
cana-5088	203	12	of	of	ADP
cana-5088	203	13	-	-	PUNCT
cana-5088	203	14	the	the	DET
cana-5088	203	15	-	-	PUNCT
cana-5088	203	16	art	art	NOUN
cana-5088	203	17	models	model	NOUN
cana-5088	203	18	discussed	discuss	VERB
cana-5088	203	19	in	in	ADP
cana-5088	203	20	the	the	DET
cana-5088	203	21	literature	literature	NOUN
cana-5088	203	22	review	review	PROPN
cana-5088	203	23	,	,	PUNCT
cana-5088	203	24	achieving	achieve	VERB
cana-5088	203	25	an	an	DET
cana-5088	203	26	impressive	impressive	ADJ
cana-5088	203	27	accuracy	accuracy	NOUN
cana-5088	203	28	of	of	ADP
cana-5088	203	29	94.33	94.33	NUM
cana-5088	203	30	%	%	NOUN
cana-5088	203	31	.	.	PUNCT
cana-5088	204	1	unlike	unlike	ADP
cana-5088	204	2	existing	exist	VERB
cana-5088	204	3	studies	study	NOUN
cana-5088	204	4	,	,	PUNCT
cana-5088	204	5	which	which	PRON
cana-5088	204	6	predominantly	predominantly	ADV
cana-5088	204	7	relied	rely	VERB
cana-5088	204	8	on	on	ADP
cana-5088	204	9	datasets	dataset	NOUN
cana-5088	204	10	with	with	ADP
cana-5088	204	11	limited	limited	ADJ
cana-5088	204	12	waste	waste	NOUN
cana-5088	204	13	categories	category	NOUN
cana-5088	204	14	,	,	PUNCT
cana-5088	204	15	this	this	DET
cana-5088	204	16	research	research	NOUN
cana-5088	204	17	utilized	utilize	VERB
cana-5088	204	18	a	a	DET
cana-5088	204	19	real	real	ADJ
cana-5088	204	20	-	-	PUNCT
cana-5088	204	21	world	world	NOUN
cana-5088	204	22	dataset	dataset	NOUN
cana-5088	204	23	of	of	ADP
cana-5088	204	24	4,752	4,752	NUM
cana-5088	204	25	images	image	NOUN
cana-5088	204	26	categorized	categorize	VERB
cana-5088	204	27	into	into	ADP
cana-5088	204	28	nine	nine	NUM
cana-5088	204	29	diverse	diverse	ADJ
cana-5088	204	30	waste	waste	NOUN
cana-5088	204	31	classes	class	NOUN
cana-5088	204	32	.	.	PUNCT
cana-5088	205	1	in	in	ADP
cana-5088	205	2	comparison	comparison	NOUN
cana-5088	205	3	,	,	PUNCT
cana-5088	205	4	a	a	DET
cana-5088	205	5	finetuned	finetune	VERB
cana-5088	205	6	inceptionv3	inceptionv3	NOUN
cana-5088	205	7	model	model	NOUN
cana-5088	205	8	proposed	propose	VERB
cana-5088	205	9	by	by	ADP
cana-5088	205	10	ling	ling	PROPN
cana-5088	205	11	and	and	CCONJ
cana-5088	205	12	tianyi	tianyi	PROPN
cana-5088	205	13	(	(	PUNCT
cana-5088	205	14	2021	2021	NUM
cana-5088	205	15	)	)	PUNCT
cana-5088	205	16	,	,	PUNCT
cana-5088	205	17	trained	train	VERB
cana-5088	205	18	on	on	ADP
cana-5088	205	19	a	a	DET
cana-5088	205	20	custom	custom	NOUN
cana-5088	205	21	dataset	dataset	NOUN
cana-5088	205	22	of	of	ADP
cana-5088	205	23	1,200	1,200	NUM
cana-5088	205	24	images	image	NOUN
cana-5088	205	25	achieved	achieve	VERB
cana-5088	205	26	an	an	DET
cana-5088	205	27	accuracy	accuracy	NOUN
cana-5088	205	28	of	of	ADP
cana-5088	205	29	92.2	92.2	NUM
cana-5088	205	30	%	%	NOUN
cana-5088	205	31	.	.	PUNCT
cana-5088	206	1	another	another	DET
cana-5088	206	2	study	study	NOUN
cana-5088	206	3	by	by	ADP
cana-5088	206	4	atikuzzaman	atikuzzaman	NOUN
cana-5088	206	5	et	et	PROPN
cana-5088	206	6	al	al	PROPN
cana-5088	206	7	.	.	PROPN
cana-5088	206	8	(	(	PUNCT
cana-5088	206	9	2021	2021	NUM
cana-5088	206	10	)	)	PUNCT
cana-5088	206	11	reported	report	VERB
cana-5088	206	12	that	that	SCONJ
cana-5088	206	13	a	a	DET
cana-5088	206	14	resnet152	resnet152	PROPN
cana-5088	206	15	model	model	NOUN
cana-5088	206	16	obtained	obtain	VERB
cana-5088	206	17	the	the	DET
cana-5088	206	18	highest	high	ADJ
cana-5088	206	19	accuracy	accuracy	NOUN
cana-5088	206	20	of	of	ADP
cana-5088	206	21	93.86	93.86	NUM
cana-5088	206	22	%	%	NOUN
cana-5088	206	23	,	,	PUNCT
cana-5088	206	24	using	use	VERB
cana-5088	206	25	a	a	DET
cana-5088	206	26	dataset	dataset	NOUN
cana-5088	206	27	of	of	ADP
cana-5088	206	28	1,989	1,989	NUM
cana-5088	206	29	trash	trash	NOUN
cana-5088	206	30	images	image	NOUN
cana-5088	206	31	categorized	categorize	VERB
cana-5088	206	32	into	into	ADP
cana-5088	206	33	six	six	NUM
cana-5088	206	34	classes	class	NOUN
cana-5088	206	35	.	.	PUNCT
cana-5088	207	1	other	other	ADJ
cana-5088	207	2	studies	study	NOUN
cana-5088	207	3	achieved	achieve	VERB
cana-5088	207	4	an	an	DET
cana-5088	207	5	accuracy	accuracy	NOUN
cana-5088	207	6	of	of	ADP
cana-5088	207	7	92.87	92.87	NUM
cana-5088	207	8	%	%	NOUN
cana-5088	207	9	with	with	ADP
cana-5088	207	10	an	an	DET
cana-5088	207	11	efficientnet	efficientnet	ADJ
cana-5088	207	12	-	-	PUNCT
cana-5088	207	13	b3	b3	NOUN
cana-5088	207	14	model	model	NOUN
cana-5088	207	15	proposed	propose	VERB
cana-5088	207	16	by	by	ADP
cana-5088	207	17	chazhoor	chazhoor	PROPN
cana-5088	207	18	et	et	PROPN
cana-5088	207	19	al	al	PROPN
cana-5088	207	20	.	.	PROPN
cana-5088	208	1	(	(	PUNCT
cana-5088	208	2	2022	2022	NUM
cana-5088	208	3	)	)	PUNCT
cana-5088	208	4	and	and	CCONJ
cana-5088	208	5	87.44	87.44	NUM
cana-5088	208	6	%	%	NOUN
cana-5088	208	7	with	with	ADP
cana-5088	208	8	a	a	DET
cana-5088	208	9	resnext	resnext	ADJ
cana-5088	208	10	model	model	NOUN
cana-5088	208	11	proposed	propose	VERB
cana-5088	208	12	by	by	ADP
cana-5088	208	13	(	(	PUNCT
cana-5088	208	14	masand	masand	NOUN
cana-5088	208	15	et	et	PROPN
cana-5088	208	16	al	al	PROPN
cana-5088	208	17	.	.	PROPN
cana-5088	208	18	,	,	PUNCT
cana-5088	208	19	2021	2021	NUM
cana-5088	208	20	)	)	PUNCT
cana-5088	208	21	.	.	PUNCT
cana-5088	209	1	the	the	DET
cana-5088	209	2	superior	superior	ADJ
cana-5088	209	3	performance	performance	NOUN
cana-5088	209	4	of	of	ADP
cana-5088	209	5	the	the	DET
cana-5088	209	6	densenet121	densenet121	PROPN
cana-5088	209	7	model	model	NOUN
cana-5088	209	8	underscores	underscore	VERB
cana-5088	209	9	its	its	PRON
cana-5088	209	10	ability	ability	NOUN
cana-5088	209	11	to	to	PART
cana-5088	209	12	address	address	VERB
cana-5088	209	13	real	real	ADJ
cana-5088	209	14	-	-	PUNCT
cana-5088	209	15	world	world	NOUN
cana-5088	209	16	waste	waste	NOUN
cana-5088	209	17	classification	classification	NOUN
cana-5088	209	18	challenges	challenge	NOUN
cana-5088	209	19	effectively	effectively	ADV
cana-5088	209	20	,	,	PUNCT
cana-5088	209	21	demonstrating	demonstrate	VERB
cana-5088	209	22	the	the	DET
cana-5088	209	23	benefits	benefit	NOUN
cana-5088	209	24	of	of	ADP
cana-5088	209	25	employing	employ	VERB
cana-5088	209	26	transfer	transfer	NOUN
cana-5088	209	27	learning	learning	NOUN
cana-5088	209	28	techniques	technique	NOUN
cana-5088	209	29	.	.	PUNCT
cana-5088	210	1	5	5	X
cana-5088	210	2	.	.	X
cana-5088	210	3	conclusion	conclusion	NOUN
cana-5088	210	4	this	this	DET
cana-5088	210	5	study	study	NOUN
cana-5088	210	6	evaluated	evaluate	VERB
cana-5088	210	7	the	the	DET
cana-5088	210	8	performance	performance	NOUN
cana-5088	210	9	of	of	ADP
cana-5088	210	10	three	three	NUM
cana-5088	210	11	pre	pre	ADJ
cana-5088	210	12	-	-	ADJ
cana-5088	210	13	trained	train	VERB
cana-5088	210	14	models	model	NOUN
cana-5088	210	15	—	—	PUNCT
cana-5088	210	16	resnet50	resnet50	NOUN
cana-5088	210	17	,	,	PUNCT
cana-5088	210	18	densenet121	densenet121	PROPN
cana-5088	210	19	,	,	PUNCT
cana-5088	210	20	and	and	CCONJ
cana-5088	210	21	efficientnetb0	efficientnetb0	PROPN
cana-5088	210	22	—	—	PUNCT
cana-5088	210	23	for	for	ADP
cana-5088	210	24	the	the	DET
cana-5088	210	25	waste	waste	NOUN
cana-5088	210	26	classification	classification	NOUN
cana-5088	210	27	task	task	NOUN
cana-5088	210	28	using	use	VERB
cana-5088	210	29	the	the	DET
cana-5088	210	30	realwaste	realwaste	ADJ
cana-5088	210	31	dataset	dataset	NOUN
cana-5088	210	32	.	.	PUNCT
cana-5088	211	1	the	the	DET
cana-5088	211	2	dataset	dataset	NOUN
cana-5088	211	3	comprises	comprise	VERB
cana-5088	211	4	4,752	4,752	NUM
cana-5088	211	5	images	image	NOUN
cana-5088	211	6	collected	collect	VERB
cana-5088	211	7	in	in	ADP
cana-5088	211	8	a	a	DET
cana-5088	211	9	real	real	ADJ
cana-5088	211	10	landfill	landfill	NOUN
cana-5088	211	11	environment	environment	NOUN
cana-5088	211	12	,	,	PUNCT
cana-5088	211	13	categorized	categorize	VERB
cana-5088	211	14	into	into	ADP
cana-5088	211	15	nine	nine	NUM
cana-5088	211	16	waste	waste	NOUN
cana-5088	211	17	types	type	NOUN
cana-5088	211	18	.	.	PUNCT
cana-5088	212	1	among	among	ADP
cana-5088	212	2	the	the	DET
cana-5088	212	3	three	three	NUM
cana-5088	212	4	state	state	NOUN
cana-5088	212	5	-	-	PUNCT
cana-5088	212	6	of	of	ADP
cana-5088	212	7	-	-	PUNCT
cana-5088	212	8	the	the	DET
cana-5088	212	9	-	-	PUNCT
cana-5088	212	10	art	art	NOUN
cana-5088	212	11	pre	pre	ADJ
cana-5088	212	12	-	-	ADJ
cana-5088	212	13	trained	train	VERB
cana-5088	212	14	models	model	NOUN
cana-5088	212	15	,	,	PUNCT
cana-5088	212	16	densenet121	densenet121	PROPN
cana-5088	212	17	emerged	emerge	VERB
cana-5088	212	18	as	as	ADP
cana-5088	212	19	the	the	DET
cana-5088	212	20	most	most	ADV
cana-5088	212	21	suitable	suitable	ADJ
cana-5088	212	22	for	for	ADP
cana-5088	212	23	waste	waste	NOUN
cana-5088	212	24	classification	classification	NOUN
cana-5088	212	25	due	due	ADP
cana-5088	212	26	to	to	ADP
cana-5088	212	27	its	its	PRON
cana-5088	212	28	superior	superior	ADJ
cana-5088	212	29	generalization	generalization	NOUN
cana-5088	212	30	capabilities	capability	NOUN
cana-5088	212	31	and	and	CCONJ
cana-5088	212	32	overall	overall	ADJ
cana-5088	212	33	performance	performance	NOUN
cana-5088	212	34	across	across	ADP
cana-5088	212	35	training	training	NOUN
cana-5088	212	36	,	,	PUNCT
cana-5088	212	37	validation	validation	NOUN
cana-5088	212	38	,	,	PUNCT
cana-5088	212	39	and	and	CCONJ
cana-5088	212	40	testing	testing	NOUN
cana-5088	212	41	phases	phase	NOUN
cana-5088	212	42	.	.	PUNCT
cana-5088	213	1	its	its	PRON
cana-5088	213	2	dense	dense	ADJ
cana-5088	213	3	connectivity	connectivity	NOUN
cana-5088	213	4	architecture	architecture	NOUN
cana-5088	213	5	enabled	enable	VERB
cana-5088	213	6	effective	effective	ADJ
cana-5088	213	7	feature	feature	NOUN
cana-5088	213	8	reuse	reuse	NOUN
cana-5088	213	9	and	and	CCONJ
cana-5088	213	10	hierarchical	hierarchical	ADJ
cana-5088	213	11	feature	feature	NOUN
cana-5088	213	12	extraction	extraction	NOUN
cana-5088	213	13	,	,	PUNCT
cana-5088	213	14	resulting	result	VERB
cana-5088	213	15	in	in	ADP
cana-5088	213	16	the	the	DET
cana-5088	213	17	highest	high	ADJ
cana-5088	213	18	test	test	NOUN
cana-5088	213	19	accuracy	accuracy	NOUN
cana-5088	213	20	of	of	ADP
cana-5088	213	21	94.33	94.33	NUM
cana-5088	213	22	%	%	NOUN
cana-5088	213	23	and	and	CCONJ
cana-5088	213	24	the	the	DET
cana-5088	213	25	lowest	low	ADJ
cana-5088	213	26	loss	loss	NOUN
cana-5088	213	27	.	.	PUNCT
cana-5088	214	1	this	this	PRON
cana-5088	214	2	makes	make	VERB
cana-5088	214	3	densenet121	densenet121	PROPN
cana-5088	214	4	particularly	particularly	ADV
cana-5088	214	5	well	well	ADV
cana-5088	214	6	-	-	PUNCT
cana-5088	214	7	suited	suit	VERB
cana-5088	214	8	for	for	ADP
cana-5088	214	9	real	real	ADJ
cana-5088	214	10	-	-	PUNCT
cana-5088	214	11	world	world	NOUN
cana-5088	214	12	waste	waste	NOUN
cana-5088	214	13	management	management	NOUN
cana-5088	214	14	scenarios	scenario	NOUN
cana-5088	214	15	that	that	PRON
cana-5088	214	16	require	require	VERB
cana-5088	214	17	precise	precise	ADJ
cana-5088	214	18	and	and	CCONJ
cana-5088	214	19	reliable	reliable	ADJ
cana-5088	214	20	classification	classification	NOUN
cana-5088	214	21	.	.	PUNCT
cana-5088	215	1	resnet50	resnet50	NOUN
cana-5088	215	2	demonstrated	demonstrate	VERB
cana-5088	215	3	strong	strong	ADJ
cana-5088	215	4	performance	performance	NOUN
cana-5088	215	5	with	with	ADP
cana-5088	215	6	rapid	rapid	ADJ
cana-5088	215	7	convergence	convergence	NOUN
cana-5088	215	8	,	,	PUNCT
cana-5088	215	9	achieving	achieve	VERB
cana-5088	215	10	competitive	competitive	ADJ
cana-5088	215	11	results	result	NOUN
cana-5088	215	12	efficiently	efficiently	ADV
cana-5088	215	13	.	.	PUNCT
cana-5088	216	1	its	its	PRON
cana-5088	216	2	ability	ability	NOUN
cana-5088	216	3	to	to	PART
cana-5088	216	4	learn	learn	VERB
cana-5088	216	5	effectively	effectively	ADV
cana-5088	216	6	within	within	ADP
cana-5088	216	7	fewer	few	ADJ
cana-5088	216	8	epochs	epoch	NOUN
cana-5088	216	9	makes	make	VERB
cana-5088	216	10	it	it	PRON
cana-5088	216	11	a	a	DET
cana-5088	216	12	practical	practical	ADJ
cana-5088	216	13	choice	choice	NOUN
cana-5088	216	14	for	for	ADP
cana-5088	216	15	scenarios	scenario	NOUN
cana-5088	216	16	where	where	SCONJ
cana-5088	216	17	computational	computational	ADJ
cana-5088	216	18	time	time	NOUN
cana-5088	216	19	is	be	AUX
cana-5088	216	20	critical	critical	ADJ
cana-5088	216	21	.	.	PUNCT
cana-5088	217	1	meanwhile	meanwhile	ADV
cana-5088	217	2	,	,	PUNCT
cana-5088	217	3	efficientnetb0	efficientnetb0	NOUN
cana-5088	217	4	provided	provide	VERB
cana-5088	217	5	a	a	DET
cana-5088	217	6	lightweight	lightweight	ADJ
cana-5088	217	7	and	and	CCONJ
cana-5088	217	8	resourceefficient	resourceefficient	ADJ
cana-5088	217	9	solution	solution	NOUN
cana-5088	217	10	,	,	PUNCT
cana-5088	217	11	offering	offer	VERB
cana-5088	217	12	solid	solid	ADJ
cana-5088	217	13	performance	performance	NOUN
cana-5088	217	14	with	with	ADP
cana-5088	217	15	minimal	minimal	ADJ
cana-5088	217	16	computational	computational	ADJ
cana-5088	217	17	requirements	requirement	NOUN
cana-5088	217	18	,	,	PUNCT
cana-5088	217	19	making	make	VERB
cana-5088	217	20	it	it	PRON
cana-5088	217	21	an	an	DET
cana-5088	217	22	appealing	appealing	ADJ
cana-5088	217	23	option	option	NOUN
cana-5088	217	24	for	for	ADP
cana-5088	217	25	deployment	deployment	NOUN
cana-5088	217	26	in	in	ADP
cana-5088	217	27	environments	environment	NOUN
cana-5088	217	28	with	with	ADP
cana-5088	217	29	constrained	constrained	ADJ
cana-5088	217	30	resources	resource	NOUN
cana-5088	217	31	.	.	PUNCT
cana-5088	218	1	this	this	DET
cana-5088	218	2	research	research	NOUN
cana-5088	218	3	highlights	highlight	VERB
cana-5088	218	4	the	the	DET
cana-5088	218	5	strengths	strength	NOUN
cana-5088	218	6	and	and	CCONJ
cana-5088	218	7	trade	trade	NOUN
cana-5088	218	8	-	-	PUNCT
cana-5088	218	9	offs	off	NOUN
cana-5088	218	10	of	of	ADP
cana-5088	218	11	these	these	DET
cana-5088	218	12	pre	pre	ADJ
cana-5088	218	13	-	-	ADJ
cana-5088	218	14	trained	train	VERB
cana-5088	218	15	models	model	NOUN
cana-5088	218	16	in	in	ADP
cana-5088	218	17	waste	waste	NOUN
cana-5088	218	18	classification	classification	NOUN
cana-5088	218	19	.	.	PUNCT
cana-5088	219	1	densenet121	densenet121	PROPN
cana-5088	219	2	is	be	AUX
cana-5088	219	3	recommended	recommend	VERB
cana-5088	219	4	for	for	ADP
cana-5088	219	5	tasks	task	NOUN
cana-5088	219	6	requiring	require	VERB
cana-5088	219	7	high	high	ADJ
cana-5088	219	8	accuracy	accuracy	NOUN
cana-5088	219	9	and	and	CCONJ
cana-5088	219	10	robust	robust	ADJ
cana-5088	219	11	generalization	generalization	NOUN
cana-5088	219	12	,	,	PUNCT
cana-5088	219	13	resnet50	resnet50	NOUN
cana-5088	219	14	for	for	ADP
cana-5088	219	15	applications	application	NOUN
cana-5088	219	16	needing	need	VERB
cana-5088	219	17	quick	quick	ADJ
cana-5088	219	18	training	training	NOUN
cana-5088	219	19	and	and	CCONJ
cana-5088	219	20	deployment	deployment	NOUN
cana-5088	219	21	,	,	PUNCT
cana-5088	219	22	and	and	CCONJ
cana-5088	219	23	efficientnetb0	efficientnetb0	NOUN
cana-5088	219	24	for	for	ADP
cana-5088	219	25	settings	setting	NOUN
cana-5088	219	26	where	where	SCONJ
cana-5088	219	27	computational	computational	ADJ
cana-5088	219	28	efficiency	efficiency	NOUN
cana-5088	219	29	is	be	AUX
cana-5088	219	30	paramount	paramount	ADJ
cana-5088	219	31	.	.	PUNCT
cana-5088	220	1	future	future	ADJ
cana-5088	220	2	work	work	NOUN
cana-5088	220	3	could	could	AUX
cana-5088	220	4	explore	explore	VERB
cana-5088	220	5	ensemble	ensemble	ADJ
cana-5088	220	6	methods	method	NOUN
cana-5088	220	7	to	to	PART
cana-5088	220	8	combine	combine	VERB
cana-5088	220	9	the	the	DET
cana-5088	220	10	strengths	strength	NOUN
cana-5088	220	11	of	of	ADP
cana-5088	220	12	these	these	DET
cana-5088	220	13	models	model	NOUN
cana-5088	220	14	and	and	CCONJ
cana-5088	220	15	expand	expand	VERB
cana-5088	220	16	the	the	DET
cana-5088	220	17	dataset	dataset	NOUN
cana-5088	220	18	to	to	PART
cana-5088	220	19	include	include	VERB
cana-5088	220	20	images	image	NOUN
cana-5088	220	21	from	from	ADP
cana-5088	220	22	diverse	diverse	ADJ
cana-5088	220	23	waste	waste	NOUN
cana-5088	220	24	management	management	NOUN
cana-5088	220	25	environments	environment	NOUN
cana-5088	220	26	.	.	PUNCT
cana-5088	221	1	this	this	PRON
cana-5088	221	2	would	would	AUX
cana-5088	221	3	enhance	enhance	VERB
cana-5088	221	4	the	the	DET
cana-5088	221	5	robustness	robustness	NOUN
cana-5088	221	6	and	and	CCONJ
cana-5088	221	7	applicability	applicability	NOUN
cana-5088	221	8	of	of	ADP
cana-5088	221	9	the	the	DET
cana-5088	221	10	models	model	NOUN
cana-5088	221	11	,	,	PUNCT
cana-5088	221	12	further	far	ADV
cana-5088	221	13	supporting	support	VERB
cana-5088	221	14	advancements	advancement	NOUN
cana-5088	221	15	in	in	ADP
cana-5088	221	16	automated	automate	VERB
cana-5088	221	17	waste	waste	NOUN
cana-5088	221	18	sorting	sorting	NOUN
cana-5088	221	19	and	and	CCONJ
cana-5088	221	20	management	management	NOUN
cana-5088	221	21	systems	system	NOUN
cana-5088	221	22	.	.	PUNCT
cana-5088	222	1	communications	communication	NOUN
cana-5088	222	2	on	on	ADP
cana-5088	222	3	applied	apply	VERB
cana-5088	222	4	nonlinear	nonlinear	ADJ
cana-5088	222	5	analysis	analysis	NOUN
cana-5088	222	6	issn	issn	NOUN
cana-5088	222	7	:	:	PUNCT
cana-5088	222	8	1074	1074	NUM
cana-5088	222	9	-	-	PUNCT
cana-5088	222	10	133x	133x	NUM
cana-5088	222	11	vol	vol	NOUN
cana-5088	222	12	32	32	NUM
cana-5088	222	13	no	no	NOUN
cana-5088	222	14	.	.	PUNCT
cana-5088	223	1	icmasd	icmasd	NOUN
cana-5088	223	2	(	(	PUNCT
cana-5088	223	3	2025	2025	NUM
cana-5088	223	4	)	)	PUNCT
cana-5088	223	5	600	600	NUM
cana-5088	223	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5088	223	7	references	reference	NOUN
cana-5088	223	8	[	[	X
cana-5088	223	9	1	1	NUM
cana-5088	223	10	]	]	PUNCT
cana-5088	223	11	atikuzzaman	atikuzzaman	NOUN
cana-5088	223	12	,	,	PUNCT
cana-5088	223	13	m.	m.	NOUN
cana-5088	223	14	,	,	PUNCT
cana-5088	223	15	hossain	hossain	PROPN
cana-5088	223	16	,	,	PUNCT
cana-5088	223	17	m.	m.	PROPN
cana-5088	223	18	p.	p.	PROPN
cana-5088	223	19	,	,	PUNCT
cana-5088	223	20	islam	islam	PROPN
cana-5088	223	21	,	,	PUNCT
cana-5088	223	22	m.	m.	PROPN
cana-5088	223	23	z.	z.	PROPN
cana-5088	223	24	,	,	PUNCT
cana-5088	223	25	&	&	CCONJ
cana-5088	223	26	kabir	kabir	PROPN
cana-5088	223	27	,	,	PUNCT
cana-5088	223	28	s.	s.	PROPN
cana-5088	223	29	a.	a.	PROPN
cana-5088	223	30	(	(	PUNCT
cana-5088	223	31	2021	2021	NUM
cana-5088	223	32	)	)	PUNCT
cana-5088	223	33	.	.	PUNCT
cana-5088	224	1	a	a	DET
cana-5088	224	2	comparative	comparative	ADJ
cana-5088	224	3	analysis	analysis	NOUN
cana-5088	224	4	of	of	ADP
cana-5088	224	5	convolutional	convolutional	ADJ
cana-5088	224	6	neural	neural	ADJ
cana-5088	224	7	networks	network	NOUN
cana-5088	224	8	for	for	ADP
cana-5088	224	9	trash	trash	NOUN
cana-5088	224	10	classification	classification	NOUN
cana-5088	224	11	.	.	PUNCT
cana-5088	225	1	gub	gub	PROPN
cana-5088	225	2	journal	journal	PROPN
cana-5088	225	3	of	of	ADP
cana-5088	225	4	science	science	NOUN
cana-5088	225	5	and	and	CCONJ
cana-5088	225	6	engineering	engineering	NOUN
cana-5088	225	7	,	,	PUNCT
cana-5088	225	8	8(1	8(1	NOUN
cana-5088	225	9	)	)	PUNCT
cana-5088	225	10	,	,	PUNCT
cana-5088	225	11	article	article	NOUN
cana-5088	225	12	1	1	NUM
cana-5088	225	13	.	.	PUNCT
cana-5088	226	1	https://doi.org/10.3329/gubjse.v8i1.62327	https://doi.org/10.3329/gubjse.v8i1.62327	NOUN
cana-5088	227	1	[	[	X
cana-5088	227	2	2	2	NUM
cana-5088	227	3	]	]	X
cana-5088	227	4	chazhoor	chazhoor	NOUN
cana-5088	227	5	,	,	PUNCT
cana-5088	227	6	a.	a.	NOUN
cana-5088	227	7	a.	a.	NOUN
cana-5088	227	8	p.	p.	PROPN
cana-5088	227	9	,	,	PUNCT
cana-5088	227	10	ho	ho	PROPN
cana-5088	227	11	,	,	PUNCT
cana-5088	227	12	e.	e.	PROPN
cana-5088	227	13	s.	s.	PROPN
cana-5088	227	14	l.	l.	PROPN
cana-5088	227	15	,	,	PUNCT
cana-5088	227	16	gao	gao	PROPN
cana-5088	227	17	,	,	PUNCT
cana-5088	227	18	b.	b.	PROPN
cana-5088	227	19	,	,	PUNCT
cana-5088	227	20	&	&	CCONJ
cana-5088	227	21	woo	woo	PROPN
cana-5088	227	22	,	,	PUNCT
cana-5088	227	23	w.	w.	PROPN
cana-5088	227	24	l.	l.	PROPN
cana-5088	227	25	(	(	PUNCT
cana-5088	227	26	2022	2022	NUM
cana-5088	227	27	)	)	PUNCT
cana-5088	227	28	.	.	PUNCT
cana-5088	228	1	deep	deep	ADJ
cana-5088	228	2	transfer	transfer	NOUN
cana-5088	228	3	learning	learn	VERB
cana-5088	228	4	benchmark	benchmark	NOUN
cana-5088	228	5	for	for	ADP
cana-5088	228	6	plastic	plastic	ADJ
cana-5088	228	7	waste	waste	NOUN
cana-5088	228	8	classification	classification	NOUN
cana-5088	228	9	.	.	PUNCT
cana-5088	229	1	intelligence	intelligence	NOUN
cana-5088	229	2	&	&	CCONJ
cana-5088	229	3	robotics	robotic	NOUN
cana-5088	229	4	,	,	PUNCT
cana-5088	229	5	2(1	2(1	NUM
cana-5088	229	6	)	)	PUNCT
cana-5088	229	7	,	,	PUNCT
cana-5088	229	8	1–19	1–19	PROPN
cana-5088	229	9	.	.	PUNCT
cana-5088	230	1	https://doi.org/10.20517/ir.2021.15	https://doi.org/10.20517/ir.2021.15	NOUN
cana-5088	231	1	[	[	X
cana-5088	231	2	3	3	X
cana-5088	231	3	]	]	X
cana-5088	231	4	chen	chen	PROPN
cana-5088	231	5	,	,	PUNCT
cana-5088	231	6	l.	l.	PROPN
cana-5088	231	7	,	,	PUNCT
cana-5088	231	8	li	li	PROPN
cana-5088	231	9	,	,	PUNCT
cana-5088	231	10	s.	s.	PROPN
cana-5088	231	11	,	,	PUNCT
cana-5088	231	12	bai	bai	PROPN
cana-5088	231	13	,	,	PUNCT
cana-5088	231	14	q.	q.	PROPN
cana-5088	231	15	,	,	PUNCT
cana-5088	231	16	yang	yang	PROPN
cana-5088	231	17	,	,	PUNCT
cana-5088	231	18	j.	j.	PROPN
cana-5088	231	19	,	,	PUNCT
cana-5088	231	20	jiang	jiang	PROPN
cana-5088	231	21	,	,	PUNCT
cana-5088	231	22	s.	s.	PROPN
cana-5088	231	23	,	,	PUNCT
cana-5088	231	24	&	&	CCONJ
cana-5088	231	25	miao	miao	PROPN
cana-5088	231	26	,	,	PUNCT
cana-5088	231	27	y.	y.	NOUN
cana-5088	231	28	(	(	PUNCT
cana-5088	231	29	2021	2021	NUM
cana-5088	231	30	)	)	PUNCT
cana-5088	231	31	.	.	PUNCT
cana-5088	232	1	review	review	NOUN
cana-5088	232	2	of	of	ADP
cana-5088	232	3	image	image	NOUN
cana-5088	232	4	classification	classification	NOUN
cana-5088	232	5	algorithms	algorithm	NOUN
cana-5088	232	6	based	base	VERB
cana-5088	232	7	on	on	ADP
cana-5088	232	8	convolutional	convolutional	ADJ
cana-5088	232	9	neural	neural	ADJ
cana-5088	232	10	networks	network	NOUN
cana-5088	232	11	.	.	PUNCT
cana-5088	233	1	remote	remote	ADJ
cana-5088	233	2	sensing	sensing	NOUN
cana-5088	233	3	,	,	PUNCT
cana-5088	233	4	13(22	13(22	NUM
cana-5088	233	5	)	)	PUNCT
cana-5088	233	6	,	,	PUNCT
cana-5088	233	7	article	article	NOUN
cana-5088	233	8	22	22	NUM
cana-5088	233	9	.	.	PUNCT
cana-5088	234	1	https://doi.org/10.3390/rs13224712	https://doi.org/10.3390/rs13224712	PUNCT
cana-5088	235	1	[	[	X
cana-5088	235	2	4	4	NUM
cana-5088	235	3	]	]	X
cana-5088	235	4	dawood	dawood	PROPN
cana-5088	235	5	,	,	PUNCT
cana-5088	235	6	a.	a.	PROPN
cana-5088	235	7	s.	s.	PROPN
cana-5088	235	8	(	(	PUNCT
cana-5088	235	9	2023	2023	NUM
cana-5088	235	10	)	)	PUNCT
cana-5088	235	11	.	.	PUNCT
cana-5088	236	1	a	a	DET
cana-5088	236	2	comparative	comparative	ADJ
cana-5088	236	3	study	study	NOUN
cana-5088	236	4	of	of	ADP
cana-5088	236	5	dcnn	dcnn	PROPN
cana-5088	236	6	models	model	NOUN
cana-5088	236	7	and	and	CCONJ
cana-5088	236	8	transfer	transfer	VERB
cana-5088	236	9	learning	learning	NOUN
cana-5088	236	10	effect	effect	NOUN
cana-5088	236	11	for	for	ADP
cana-5088	236	12	sustainability	sustainability	NOUN
cana-5088	236	13	assessment	assessment	NOUN
cana-5088	236	14	:	:	PUNCT
cana-5088	236	15	the	the	DET
cana-5088	236	16	case	case	NOUN
cana-5088	236	17	of	of	ADP
cana-5088	236	18	garbage	garbage	NOUN
cana-5088	236	19	classification	classification	NOUN
cana-5088	236	20	.	.	PUNCT
cana-5088	237	1	technium	technium	NOUN
cana-5088	237	2	:	:	PUNCT
cana-5088	237	3	romanian	romanian	ADJ
cana-5088	237	4	journal	journal	NOUN
cana-5088	237	5	of	of	ADP
cana-5088	237	6	applied	apply	VERB
cana-5088	237	7	sciences	science	NOUN
cana-5088	237	8	and	and	CCONJ
cana-5088	237	9	technology	technology	NOUN
cana-5088	237	10	,	,	PUNCT
cana-5088	237	11	12	12	NUM
cana-5088	237	12	,	,	PUNCT
cana-5088	237	13	33–44	33–44	NUM
cana-5088	237	14	.	.	PUNCT
cana-5088	238	1	https://doi.org/10.47577/technium.v12i.9346	https://doi.org/10.47577/technium.v12i.9346	VERB
cana-5088	238	2	[	[	PUNCT
cana-5088	238	3	5	5	NUM
cana-5088	238	4	]	]	X
cana-5088	238	5	feng	feng	PROPN
cana-5088	238	6	,	,	PUNCT
cana-5088	238	7	j.	j.	PROPN
cana-5088	238	8	,	,	PUNCT
cana-5088	238	9	&	&	CCONJ
cana-5088	238	10	tang	tang	PROPN
cana-5088	238	11	,	,	PUNCT
cana-5088	238	12	x.	x.	NOUN
cana-5088	238	13	(	(	PUNCT
cana-5088	238	14	2020	2020	NUM
cana-5088	238	15	)	)	PUNCT
cana-5088	238	16	.	.	PUNCT
cana-5088	239	1	office	office	NOUN
cana-5088	239	2	garbage	garbage	NOUN
cana-5088	239	3	intelligent	intelligent	ADJ
cana-5088	239	4	classification	classification	NOUN
cana-5088	239	5	based	base	VERB
cana-5088	239	6	on	on	ADP
cana-5088	239	7	inception	inception	PROPN
cana-5088	239	8	-	-	PUNCT
cana-5088	239	9	v3	v3	NOUN
cana-5088	239	10	transfer	transfer	NOUN
cana-5088	239	11	learning	learning	NOUN
cana-5088	239	12	model	model	NOUN
cana-5088	239	13	.	.	PUNCT
cana-5088	240	1	journal	journal	PROPN
cana-5088	240	2	of	of	ADP
cana-5088	240	3	physics	physics	PROPN
cana-5088	240	4	:	:	PUNCT
cana-5088	240	5	conference	conference	NOUN
cana-5088	240	6	series	series	NOUN
cana-5088	240	7	,	,	PUNCT
cana-5088	240	8	1487(1	1487(1	NUM
cana-5088	240	9	)	)	PUNCT
cana-5088	240	10	,	,	PUNCT
cana-5088	240	11	012008	012008	NUM
cana-5088	240	12	.	.	PUNCT
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cana-5088	242	2	6	6	NUM
cana-5088	242	3	]	]	PUNCT
cana-5088	242	4	he	he	PRON
cana-5088	242	5	,	,	PUNCT
cana-5088	242	6	k.	k.	PROPN
cana-5088	242	7	,	,	PUNCT
cana-5088	242	8	zhang	zhang	PROPN
cana-5088	242	9	,	,	PUNCT
cana-5088	242	10	x.	x.	PROPN
cana-5088	242	11	,	,	PUNCT
cana-5088	242	12	ren	ren	PROPN
cana-5088	242	13	,	,	PUNCT
cana-5088	242	14	s.	s.	PROPN
cana-5088	242	15	,	,	PUNCT
cana-5088	242	16	&	&	CCONJ
cana-5088	242	17	sun	sun	PROPN
cana-5088	242	18	,	,	PUNCT
cana-5088	242	19	j.	j.	PROPN
cana-5088	242	20	(	(	PUNCT
cana-5088	242	21	2015	2015	NUM
cana-5088	242	22	)	)	PUNCT
cana-5088	242	23	.	.	PUNCT
cana-5088	243	1	deep	deep	ADJ
cana-5088	243	2	residual	residual	ADJ
cana-5088	243	3	learning	learning	NOUN
cana-5088	243	4	for	for	ADP
cana-5088	243	5	image	image	NOUN
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cana-5088	243	7	(	(	PUNCT
cana-5088	243	8	arxiv:1512.03385	arxiv:1512.03385	PROPN
cana-5088	243	9	)	)	PUNCT
cana-5088	243	10	.	.	PUNCT
cana-5088	244	1	arxiv	arxiv	PROPN
cana-5088	244	2	.	.	PUNCT
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cana-5088	246	2	7	7	NUM
cana-5088	246	3	]	]	X
cana-5088	246	4	huang	huang	PROPN
cana-5088	246	5	,	,	PUNCT
cana-5088	246	6	g.	g.	PROPN
cana-5088	246	7	,	,	PUNCT
cana-5088	246	8	liu	liu	PROPN
cana-5088	246	9	,	,	PUNCT
cana-5088	246	10	z.	z.	PROPN
cana-5088	246	11	,	,	PUNCT
cana-5088	246	12	maaten	maaten	VERB
cana-5088	246	13	,	,	PUNCT
cana-5088	246	14	l.	l.	PROPN
cana-5088	246	15	van	van	PROPN
cana-5088	246	16	der	der	PROPN
cana-5088	246	17	,	,	PUNCT
cana-5088	246	18	&	&	CCONJ
cana-5088	246	19	weinberger	weinberger	PROPN
cana-5088	246	20	,	,	PUNCT
cana-5088	246	21	k.	k.	PROPN
cana-5088	246	22	q.	q.	PROPN
cana-5088	246	23	(	(	PUNCT
cana-5088	246	24	2018	2018	NUM
cana-5088	246	25	)	)	PUNCT
cana-5088	246	26	.	.	PUNCT
cana-5088	247	1	densely	densely	ADV
cana-5088	247	2	connected	connect	VERB
cana-5088	247	3	convolutional	convolutional	ADJ
cana-5088	247	4	networks	network	NOUN
cana-5088	247	5	(	(	PUNCT
cana-5088	247	6	arxiv:1608.06993	arxiv:1608.06993	X
cana-5088	247	7	)	)	PUNCT
cana-5088	247	8	.	.	PUNCT
cana-5088	248	1	arxiv	arxiv	PROPN
cana-5088	248	2	.	.	PUNCT
cana-5088	249	1	https://doi.org/10.48550/arxiv.1608.06993	https://doi.org/10.48550/arxiv.1608.06993	PROPN
cana-5088	250	1	[	[	X
cana-5088	250	2	8	8	NUM
cana-5088	250	3	]	]	PUNCT
cana-5088	250	4	iván	iván	NOUN
cana-5088	250	5	.	.	PUNCT
cana-5088	251	1	(	(	PUNCT
cana-5088	251	2	2024	2024	NUM
cana-5088	251	3	,	,	PUNCT
cana-5088	251	4	may	may	AUX
cana-5088	251	5	17	17	NUM
cana-5088	251	6	)	)	PUNCT
cana-5088	251	7	.	.	PUNCT
cana-5088	252	1	what	what	PRON
cana-5088	252	2	are	be	AUX
cana-5088	252	3	the	the	DET
cana-5088	252	4	recycling	recycling	NOUN
cana-5088	252	5	rates	rate	NOUN
cana-5088	252	6	in	in	ADP
cana-5088	252	7	the	the	DET
cana-5088	252	8	world	world	NOUN
cana-5088	252	9	?	?	PUNCT
cana-5088	253	1	recycl3r	recycl3r	NOUN
cana-5088	253	2	.	.	PUNCT
cana-5088	254	1	https://recycl3r.com/what-are-the-recycling-rates-in-the-world/	https://recycl3r.com/what-are-the-recycling-rates-in-the-world/	PROPN
cana-5088	254	2	[	[	X
cana-5088	254	3	9	9	NUM
cana-5088	254	4	]	]	X
cana-5088	254	5	lenkiewicz	lenkiewicz	NOUN
cana-5088	254	6	,	,	PUNCT
cana-5088	254	7	z.	z.	PROPN
cana-5088	254	8	(	(	PUNCT
cana-5088	254	9	2016	2016	NUM
cana-5088	254	10	,	,	PUNCT
cana-5088	254	11	may	may	AUX
cana-5088	254	12	11	11	NUM
cana-5088	254	13	)	)	PUNCT
cana-5088	254	14	.	.	PUNCT
cana-5088	255	1	waste	waste	NOUN
cana-5088	255	2	and	and	CCONJ
cana-5088	255	3	the	the	DET
cana-5088	255	4	sustainable	sustainable	ADJ
cana-5088	255	5	development	development	NOUN
cana-5088	255	6	goals	goal	NOUN
cana-5088	255	7	.	.	PUNCT
cana-5088	256	1	wasteaid	wasteaid	VERB
cana-5088	256	2	.	.	PUNCT
cana-5088	257	1	https://wasteaid.org/waste-and-the-sustainable-development-goals/	https://wasteaid.org/waste-and-the-sustainable-development-goals/	X
cana-5088	257	2	[	[	X
cana-5088	257	3	10	10	NUM
cana-5088	257	4	]	]	X
cana-5088	257	5	ling	ling	NOUN
cana-5088	257	6	,	,	PUNCT
cana-5088	257	7	p.	p.	PROPN
cana-5088	257	8	,	,	PUNCT
cana-5088	257	9	&	&	CCONJ
cana-5088	257	10	tianyi	tianyi	PROPN
cana-5088	257	11	,	,	PUNCT
cana-5088	257	12	l.	l.	PROPN
cana-5088	257	13	(	(	PUNCT
cana-5088	257	14	2021	2021	NUM
cana-5088	257	15	)	)	PUNCT
cana-5088	257	16	.	.	PUNCT
cana-5088	258	1	design	design	NOUN
cana-5088	258	2	and	and	CCONJ
cana-5088	258	3	research	research	NOUN
cana-5088	258	4	of	of	ADP
cana-5088	258	5	intelligent	intelligent	ADJ
cana-5088	258	6	trash	trash	NOUN
cana-5088	258	7	can	can	AUX
cana-5088	258	8	based	base	VERB
cana-5088	258	9	on	on	ADP
cana-5088	258	10	convolutional	convolutional	ADJ
cana-5088	258	11	neural	neural	ADJ
cana-5088	258	12	network	network	NOUN
cana-5088	258	13	and	and	CCONJ
cana-5088	258	14	transfer	transfer	NOUN
cana-5088	258	15	learning	learning	NOUN
cana-5088	258	16	.	.	PUNCT
cana-5088	259	1	journal	journal	PROPN
cana-5088	259	2	of	of	ADP
cana-5088	259	3	physics	physics	PROPN
cana-5088	259	4	:	:	PUNCT
cana-5088	259	5	conference	conference	NOUN
cana-5088	259	6	series	series	NOUN
cana-5088	259	7	,	,	PUNCT
cana-5088	259	8	2033(1	2033(1	NUM
cana-5088	259	9	)	)	PUNCT
cana-5088	259	10	,	,	PUNCT
cana-5088	259	11	012177	012177	NUM
cana-5088	259	12	.	.	PUNCT
cana-5088	260	1	https://doi.org/10.1088/1742-6596/2033/1/012177	https://doi.org/10.1088/1742-6596/2033/1/012177	X
cana-5088	261	1	[	[	X
cana-5088	261	2	11	11	NUM
cana-5088	261	3	]	]	X
cana-5088	261	4	majchrowska	majchrowska	PROPN
cana-5088	261	5	,	,	PUNCT
cana-5088	261	6	s.	s.	PROPN
cana-5088	261	7	,	,	PUNCT
cana-5088	261	8	mikołajczyk	mikołajczyk	PROPN
cana-5088	261	9	,	,	PUNCT
cana-5088	261	10	a.	a.	PROPN
cana-5088	261	11	,	,	PUNCT
cana-5088	261	12	ferlin	ferlin	PROPN
cana-5088	261	13	,	,	PUNCT
cana-5088	261	14	m.	m.	NOUN
cana-5088	261	15	,	,	PUNCT
cana-5088	261	16	klawikowska	klawikowska	PROPN
cana-5088	261	17	,	,	PUNCT
cana-5088	261	18	z.	z.	PROPN
cana-5088	261	19	,	,	PUNCT
cana-5088	261	20	plantykow	plantykow	NOUN
cana-5088	261	21	,	,	PUNCT
cana-5088	261	22	m.	m.	NOUN
cana-5088	261	23	a.	a.	PROPN
cana-5088	261	24	,	,	PUNCT
cana-5088	261	25	kwasigroch	kwasigroch	PROPN
cana-5088	261	26	,	,	PUNCT
cana-5088	261	27	a.	a.	PROPN
cana-5088	261	28	,	,	PUNCT
cana-5088	261	29	&	&	CCONJ
cana-5088	261	30	majek	majek	NOUN
cana-5088	261	31	,	,	PUNCT
cana-5088	261	32	k.	k.	PROPN
cana-5088	261	33	(	(	PUNCT
cana-5088	261	34	2022	2022	NUM
cana-5088	261	35	)	)	PUNCT
cana-5088	261	36	.	.	PUNCT
cana-5088	262	1	deep	deep	ADJ
cana-5088	262	2	learning	learning	NOUN
cana-5088	262	3	-	-	PUNCT
cana-5088	262	4	based	base	VERB
cana-5088	262	5	waste	waste	NOUN
cana-5088	262	6	detection	detection	NOUN
cana-5088	262	7	in	in	ADP
cana-5088	262	8	natural	natural	ADJ
cana-5088	262	9	and	and	CCONJ
cana-5088	262	10	urban	urban	ADJ
cana-5088	262	11	environments	environment	NOUN
cana-5088	262	12	.	.	PUNCT
cana-5088	263	1	waste	waste	NOUN
cana-5088	263	2	management	management	PROPN
cana-5088	263	3	,	,	PUNCT
cana-5088	263	4	138	138	NUM
cana-5088	263	5	,	,	PUNCT
cana-5088	263	6	274–284	274–284	NUM
cana-5088	263	7	.	.	PUNCT
cana-5088	264	1	https://doi.org/10.1016/j.wasman.2021.12.001	https://doi.org/10.1016/j.wasman.2021.12.001	VERB
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cana-5088	265	2	12	12	NUM
cana-5088	265	3	]	]	PUNCT
cana-5088	265	4	malik	malik	PROPN
cana-5088	265	5	,	,	PUNCT
cana-5088	265	6	m.	m.	NOUN
cana-5088	265	7	,	,	PUNCT
cana-5088	265	8	sharma	sharma	PROPN
cana-5088	265	9	,	,	PUNCT
cana-5088	265	10	s.	s.	PROPN
cana-5088	265	11	,	,	PUNCT
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cana-5088	265	13	,	,	PUNCT
cana-5088	265	14	m.	m.	NOUN
cana-5088	265	15	,	,	PUNCT
cana-5088	265	16	chen	chen	PROPN
cana-5088	265	17	,	,	PUNCT
cana-5088	265	18	c.-l	c.-l	PROPN
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cana-5088	265	20	,	,	PUNCT
cana-5088	265	21	wu	wu	PROPN
cana-5088	265	22	,	,	PUNCT
cana-5088	265	23	c.-m	c.-m	NOUN
cana-5088	265	24	.	.	PUNCT
cana-5088	265	25	,	,	PUNCT
cana-5088	265	26	soni	soni	PROPN
cana-5088	265	27	,	,	PUNCT
cana-5088	265	28	p.	p.	PROPN
cana-5088	265	29	,	,	PUNCT
cana-5088	265	30	&	&	CCONJ
cana-5088	265	31	chaudhary	chaudhary	PROPN
cana-5088	265	32	,	,	PUNCT
cana-5088	265	33	s.	s.	PROPN
cana-5088	265	34	(	(	PUNCT
cana-5088	265	35	2022	2022	NUM
cana-5088	265	36	)	)	PUNCT
cana-5088	265	37	.	.	PUNCT
cana-5088	266	1	waste	waste	VERB
cana-5088	266	2	classification	classification	NOUN
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cana-5088	266	4	sustainable	sustainable	ADJ
cana-5088	266	5	development	development	NOUN
cana-5088	266	6	using	use	VERB
cana-5088	266	7	image	image	NOUN
cana-5088	266	8	recognition	recognition	NOUN
cana-5088	266	9	with	with	ADP
cana-5088	266	10	deep	deep	ADJ
cana-5088	266	11	learning	learn	VERB
cana-5088	266	12	neural	neural	ADJ
cana-5088	266	13	network	network	NOUN
cana-5088	266	14	models	model	NOUN
cana-5088	266	15	.	.	PUNCT
cana-5088	267	1	sustainability	sustainability	NOUN
cana-5088	267	2	,	,	PUNCT
cana-5088	267	3	14(12	14(12	NUM
cana-5088	267	4	)	)	PUNCT
cana-5088	267	5	,	,	PUNCT
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cana-5088	267	7	12	12	NUM
cana-5088	267	8	.	.	PUNCT
cana-5088	268	1	https://doi.org/10.3390/su14127222	https://doi.org/10.3390/su14127222	NOUN
cana-5088	268	2	communications	communication	NOUN
cana-5088	268	3	on	on	ADP
cana-5088	268	4	applied	apply	VERB
cana-5088	268	5	nonlinear	nonlinear	ADJ
cana-5088	268	6	analysis	analysis	NOUN
cana-5088	268	7	issn	issn	NOUN
cana-5088	268	8	:	:	PUNCT
cana-5088	268	9	1074	1074	NUM
cana-5088	268	10	-	-	PUNCT
cana-5088	268	11	133x	133x	NUM
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cana-5088	268	13	32	32	NUM
cana-5088	268	14	no	no	NOUN
cana-5088	268	15	.	.	PUNCT
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cana-5088	269	4	)	)	PUNCT
cana-5088	269	5	601	601	NUM
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cana-5088	270	1	[	[	X
cana-5088	270	2	13	13	NUM
cana-5088	270	3	]	]	X
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cana-5088	270	7	,	,	PUNCT
cana-5088	270	8	chauhan	chauhan	PROPN
cana-5088	270	9	,	,	PUNCT
cana-5088	270	10	s.	s.	PROPN
cana-5088	270	11	,	,	PUNCT
cana-5088	270	12	jangid	jangid	ADJ
cana-5088	270	13	,	,	PUNCT
cana-5088	270	14	m.	m.	NOUN
cana-5088	270	15	,	,	PUNCT
cana-5088	270	16	kumar	kumar	PROPN
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cana-5088	270	18	r.	r.	PROPN
cana-5088	270	19	,	,	PUNCT
cana-5088	270	20	&	&	CCONJ
cana-5088	270	21	roy	roy	PROPN
cana-5088	270	22	,	,	PUNCT
cana-5088	270	23	s.	s.	PROPN
cana-5088	270	24	(	(	PUNCT
cana-5088	270	25	2021	2021	NUM
cana-5088	270	26	)	)	PUNCT
cana-5088	270	27	.	.	PUNCT
cana-5088	271	1	scrapnet	scrapnet	NOUN
cana-5088	271	2	:	:	PUNCT
cana-5088	271	3	an	an	DET
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cana-5088	271	5	approach	approach	NOUN
cana-5088	271	6	to	to	PART
cana-5088	271	7	trash	trash	VERB
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cana-5088	271	9	.	.	PUNCT
cana-5088	272	1	ieee	ieee	NOUN
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cana-5088	272	3	,	,	PUNCT
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cana-5088	272	5	,	,	PUNCT
cana-5088	272	6	130947–130958	130947–130958	NUM
cana-5088	272	7	.	.	PUNCT
cana-5088	273	1	ieee	ieee	NOUN
cana-5088	273	2	access	access	NOUN
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cana-5088	275	3	]	]	X
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cana-5088	275	5	,	,	PUNCT
cana-5088	275	6	s.	s.	PROPN
cana-5088	275	7	,	,	PUNCT
cana-5088	275	8	&	&	CCONJ
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cana-5088	275	10	,	,	PUNCT
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cana-5088	275	14	)	)	PUNCT
cana-5088	275	15	.	.	PUNCT
cana-5088	276	1	classification	classification	NOUN
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cana-5088	276	5	using	use	VERB
cana-5088	276	6	cnn	cnn	PROPN
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cana-5088	276	11	.	.	PUNCT
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cana-5088	277	7	of	of	ADP
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cana-5088	277	10	for	for	ADP
cana-5088	277	11	information	information	NOUN
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cana-5088	277	13	evaluation	evaluation	NOUN
cana-5088	277	14	,	,	PUNCT
cana-5088	277	15	29–33	29–33	NUM
cana-5088	277	16	.	.	PUNCT
cana-5088	278	1	https://doi.org/10.1145/3574318.3574345	https://doi.org/10.1145/3574318.3574345	PRON
cana-5088	279	1	[	[	X
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cana-5088	279	3	]	]	X
cana-5088	279	4	ramírez	ramírez	NOUN
cana-5088	279	5	,	,	PUNCT
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cana-5088	279	7	,	,	PUNCT
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cana-5088	279	13	,	,	PUNCT
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cana-5088	279	17	j.	j.	PROPN
cana-5088	279	18	,	,	PUNCT
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cana-5088	279	20	,	,	PUNCT
cana-5088	279	21	a.	a.	PROPN
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cana-5088	279	26	j.	j.	PROPN
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cana-5088	279	32	,	,	PUNCT
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cana-5088	279	37	&	&	CCONJ
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cana-5088	279	41	(	(	PUNCT
cana-5088	279	42	2020	2020	NUM
cana-5088	279	43	)	)	PUNCT
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cana-5088	280	5	computer	computer	NOUN
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cana-5088	280	12	.	.	PUNCT
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cana-5088	281	2	computing	computing	NOUN
cana-5088	281	3	and	and	CCONJ
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cana-5088	281	5	,	,	PUNCT
cana-5088	281	6	32(17	32(17	NUM
cana-5088	281	7	)	)	PUNCT
cana-5088	281	8	,	,	PUNCT
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cana-5088	283	2	16	16	NUM
cana-5088	283	3	]	]	X
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cana-5088	283	6	,	,	PUNCT
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cana-5088	283	10	2023	2023	NUM
cana-5088	283	11	)	)	PUNCT
cana-5088	283	12	.	.	PUNCT
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cana-5088	284	2	[	[	X
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cana-5088	284	4	]	]	X
cana-5088	284	5	.	.	PUNCT
cana-5088	285	1	uci	uci	PROPN
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cana-5088	285	3	learning	learn	VERB
cana-5088	285	4	repository	repository	NOUN
cana-5088	285	5	.	.	PUNCT
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cana-5088	286	2	g	g	NOUN
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cana-5088	286	4	17	17	NUM
cana-5088	286	5	]	]	PUNCT
cana-5088	286	6	sayed	say	VERB
cana-5088	286	7	,	,	PUNCT
cana-5088	286	8	g.	g.	PROPN
cana-5088	286	9	i.	i.	PROPN
cana-5088	286	10	,	,	PUNCT
cana-5088	286	11	abd	abd	PROPN
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cana-5088	286	13	,	,	PUNCT
cana-5088	286	14	m.	m.	NOUN
cana-5088	286	15	,	,	PUNCT
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cana-5088	286	17	,	,	PUNCT
cana-5088	286	18	a.	a.	NOUN
cana-5088	286	19	,	,	PUNCT
cana-5088	286	20	&	&	CCONJ
cana-5088	286	21	hassanien	hassanien	PROPN
cana-5088	286	22	,	,	PUNCT
cana-5088	286	23	a.	a.	PROPN
cana-5088	286	24	e.	e.	PROPN
cana-5088	286	25	(	(	PUNCT
cana-5088	286	26	2024	2024	NUM
cana-5088	286	27	)	)	PUNCT
cana-5088	286	28	.	.	PUNCT
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cana-5088	287	3	sustainable	sustainable	ADJ
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cana-5088	287	6	model	model	NOUN
cana-5088	287	7	based	base	VERB
cana-5088	287	8	on	on	ADP
cana-5088	287	9	multi	multi	ADJ
cana-5088	287	10	-	-	ADJ
cana-5088	287	11	objective	objective	ADJ
cana-5088	287	12	beluga	beluga	ADJ
cana-5088	287	13	whale	whale	NOUN
cana-5088	287	14	optimization	optimization	NOUN
cana-5088	287	15	and	and	CCONJ
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cana-5088	287	17	learning	learning	NOUN
cana-5088	287	18	.	.	PUNCT
cana-5088	288	1	environmental	environmental	ADJ
cana-5088	288	2	science	science	NOUN
cana-5088	288	3	and	and	CCONJ
cana-5088	288	4	pollution	pollution	NOUN
cana-5088	288	5	research	research	NOUN
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cana-5088	288	7	31(21	31(21	NUM
cana-5088	288	8	)	)	PUNCT
cana-5088	288	9	,	,	PUNCT
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cana-5088	288	11	.	.	PUNCT
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cana-5088	290	2	18	18	NUM
cana-5088	290	3	]	]	PUNCT
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cana-5088	290	5	,	,	PUNCT
cana-5088	290	6	k.	k.	PROPN
cana-5088	290	7	,	,	PUNCT
cana-5088	290	8	dhiman	dhiman	NOUN
cana-5088	290	9	,	,	PUNCT
cana-5088	290	10	s.	s.	PROPN
cana-5088	290	11	,	,	PUNCT
cana-5088	290	12	&	&	CCONJ
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cana-5088	290	14	,	,	PUNCT
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cana-5088	290	17	2021	2021	NUM
cana-5088	290	18	)	)	PUNCT
cana-5088	290	19	.	.	PUNCT
cana-5088	291	1	waste	waste	NOUN
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cana-5088	291	3	using	use	VERB
cana-5088	291	4	transfer	transfer	NOUN
cana-5088	291	5	learning	learning	NOUN
cana-5088	291	6	with	with	ADP
cana-5088	291	7	convolutional	convolutional	ADJ
cana-5088	291	8	neural	neural	ADJ
cana-5088	291	9	networks	network	NOUN
cana-5088	291	10	.	.	PUNCT
cana-5088	292	1	iop	iop	PROPN
cana-5088	292	2	conference	conference	PROPN
cana-5088	292	3	series	series	PROPN
cana-5088	292	4	:	:	PUNCT
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cana-5088	292	6	and	and	CCONJ
cana-5088	292	7	environmental	environmental	ADJ
cana-5088	292	8	science	science	NOUN
cana-5088	292	9	,	,	PUNCT
cana-5088	292	10	775(1	775(1	NUM
cana-5088	292	11	)	)	PUNCT
cana-5088	292	12	,	,	PUNCT
cana-5088	292	13	012010	012010	NUM
cana-5088	292	14	.	.	PUNCT
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cana-5088	293	4	]	]	X
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cana-5088	293	6	,	,	PUNCT
cana-5088	293	7	m.	m.	NOUN
cana-5088	293	8	,	,	PUNCT
cana-5088	293	9	&	&	CCONJ
cana-5088	293	10	le	le	PROPN
cana-5088	293	11	,	,	PUNCT
cana-5088	293	12	q.	q.	PROPN
cana-5088	293	13	v.	v.	PROPN
cana-5088	293	14	(	(	PUNCT
cana-5088	293	15	2020	2020	NUM
cana-5088	293	16	)	)	PUNCT
cana-5088	293	17	.	.	PUNCT
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cana-5088	294	5	scaling	scale	VERB
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cana-5088	294	8	neural	neural	ADJ
cana-5088	294	9	networks	network	NOUN
cana-5088	294	10	(	(	PUNCT
cana-5088	294	11	arxiv:1905.11946	arxiv:1905.11946	PROPN
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cana-5088	294	13	.	.	PUNCT
cana-5088	295	1	arxiv	arxiv	PROPN
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cana-5088	296	1	https://doi.org/10.48550/arxiv.1905.11946	https://doi.org/10.48550/arxiv.1905.11946	PROPN
cana-5088	297	1	[	[	X
cana-5088	297	2	20	20	NUM
cana-5088	297	3	]	]	X
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cana-5088	297	5	,	,	PUNCT
cana-5088	297	6	g.	g.	PROPN
cana-5088	297	7	,	,	PUNCT
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cana-5088	297	9	,	,	PUNCT
cana-5088	297	10	v.	v.	ADV
cana-5088	297	11	,	,	PUNCT
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cana-5088	297	13	,	,	PUNCT
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cana-5088	297	15	,	,	PUNCT
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cana-5088	297	23	,	,	PUNCT
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cana-5088	297	26	c.	c.	PROPN
cana-5088	297	27	,	,	PUNCT
cana-5088	297	28	&	&	CCONJ
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cana-5088	297	30	,	,	PUNCT
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cana-5088	297	33	2021	2021	NUM
cana-5088	297	34	)	)	PUNCT
cana-5088	297	35	.	.	PUNCT
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cana-5088	298	2	solid	solid	ADJ
cana-5088	298	3	waste	waste	NOUN
cana-5088	298	4	management	management	NOUN
cana-5088	298	5	and	and	CCONJ
cana-5088	298	6	adverse	adverse	ADJ
cana-5088	298	7	health	health	NOUN
cana-5088	298	8	outcomes	outcome	NOUN
cana-5088	298	9	:	:	PUNCT
cana-5088	298	10	a	a	DET
cana-5088	298	11	systematic	systematic	ADJ
cana-5088	298	12	review	review	NOUN
cana-5088	298	13	.	.	PUNCT
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cana-5088	299	2	journal	journal	PROPN
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cana-5088	299	4	environmental	environmental	ADJ
cana-5088	299	5	research	research	NOUN
cana-5088	299	6	and	and	CCONJ
cana-5088	299	7	public	public	ADJ
cana-5088	299	8	health	health	NOUN
cana-5088	299	9	,	,	PUNCT
cana-5088	299	10	18(8	18(8	NUM
cana-5088	299	11	)	)	PUNCT
cana-5088	299	12	,	,	PUNCT
cana-5088	299	13	4331	4331	NUM
cana-5088	299	14	.	.	PUNCT
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cana-5088	301	2	21	21	NUM
cana-5088	301	3	]	]	X
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cana-5088	301	8	2023	2023	NUM
cana-5088	301	9	)	)	PUNCT
cana-5088	301	10	.	.	PUNCT
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cana-5088	302	4	for	for	ADP
cana-5088	302	5	image	image	NOUN
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cana-5088	302	7	.	.	PUNCT
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cana-5088	303	4	2022	2022	NUM
cana-5088	303	5	6th	6th	ADJ
cana-5088	303	6	international	international	ADJ
cana-5088	303	7	conference	conference	NOUN
cana-5088	303	8	on	on	ADP
cana-5088	303	9	electronic	electronic	ADJ
cana-5088	303	10	information	information	NOUN
cana-5088	303	11	technology	technology	NOUN
cana-5088	303	12	and	and	CCONJ
cana-5088	303	13	computer	computer	NOUN
cana-5088	303	14	engineering	engineering	NOUN
cana-5088	303	15	,	,	PUNCT
cana-5088	303	16	1494–1498	1494–1498	NUM
cana-5088	303	17	.	.	PUNCT
cana-5088	303	18	https://doi.org/10.1145/3573428.3573691	https://doi.org/10.1145/3573428.3573691	PUNCT
cana-5088	304	1	[	[	X
cana-5088	304	2	22	22	NUM
cana-5088	304	3	]	]	X
cana-5088	304	4	yuan	yuan	NOUN
cana-5088	304	5	,	,	PUNCT
cana-5088	304	6	z.	z.	PROPN
cana-5088	304	7	,	,	PUNCT
cana-5088	304	8	&	&	CCONJ
cana-5088	304	9	liu	liu	PROPN
cana-5088	304	10	,	,	PUNCT
cana-5088	304	11	j.	j.	PROPN
cana-5088	304	12	(	(	PUNCT
cana-5088	304	13	2022	2022	NUM
cana-5088	304	14	)	)	PUNCT
cana-5088	304	15	.	.	PUNCT
cana-5088	305	1	a	a	DET
cana-5088	305	2	hybrid	hybrid	ADJ
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cana-5088	305	4	learning	learning	NOUN
cana-5088	305	5	model	model	NOUN
cana-5088	305	6	for	for	ADP
cana-5088	305	7	trash	trash	NOUN
cana-5088	305	8	classification	classification	NOUN
cana-5088	305	9	based	base	VERB
cana-5088	305	10	on	on	ADP
cana-5088	305	11	deep	deep	ADJ
cana-5088	305	12	trasnsfer	trasnsfer	NOUN
cana-5088	305	13	learning	learning	NOUN
cana-5088	305	14	.	.	PUNCT
cana-5088	306	1	journal	journal	PROPN
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cana-5088	306	3	electrical	electrical	ADJ
cana-5088	306	4	and	and	CCONJ
cana-5088	306	5	computer	computer	NOUN
cana-5088	306	6	engineering	engineering	NOUN
cana-5088	306	7	,	,	PUNCT
cana-5088	306	8	2022(1	2022(1	NUM
cana-5088	306	9	)	)	PUNCT
cana-5088	306	10	,	,	PUNCT
cana-5088	306	11	7608794	7608794	NUM
cana-5088	306	12	.	.	PUNCT
cana-5088	307	1	https://doi.org/10.1155/2022/7608794	https://doi.org/10.1155/2022/7608794	NOUN