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Recylable Waste Materials Recognition Using Deep Learning Framework

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dc.contributor.authorVikneshwaran a/l Maiyauenen_US
dc.date.accessioned2023-05-03T15:03:37Z
dc.date.available2023-05-03T15:03:37Z
dc.date.issued2019-10
dc.description.abstractWaste materials sorting or separation is a significant and useful process in waste management industry. However, it is a long process in waste management field and consumes time. This is because, waste management can be done at home but doing it efficiently is whole new topic to be discussed. People nowadays have difficulties in spending time in waste management due to other commitments. Thus, this project helps in recognising recyclable wastes materials using deep learning framework. Graphical Processing Unit (GPU) provides better training mainly because of its speed. In addition to that, Faster R-CNN Inception V2 COCO model has been used with new set of recyclable waste materials dataset to complete the training.en_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/20516
dc.language.isoenen_US
dc.subjectDeep Learningen_US
dc.subjectObject Recognitionen_US
dc.subjectRecyclable Waste Materialsen_US
dc.titleRecylable Waste Materials Recognition Using Deep Learning Frameworken_US
dc.typeResource Types::text::Final Year Project
dspace.entity.typePublication
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