Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/4693
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMalavika. M-
dc.date.accessioned2025-03-27T05:41:54Z-
dc.date.available2025-03-27T05:41:54Z-
dc.date.issued2024-03-31-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4693-
dc.publisherSt. Teresa' s College( autonomous) Ernakulamen_US
dc.titleDEEP LEARNING APPROACHES FOR WASTE CLASSIFICATION: A COMPARATIVE STUDY OF RESNET152, INCEPTION V3, AND VGG19en_US
dc.typeThesisen_US
Appears in Collections:Theses/Dissertation/Projects

Files in This Item:
File Description SizeFormat 
Malavika M.PDF6.37 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.