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Recylable Waste Materials Recognition Using Deep Learning Framework

Waste 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...

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Main Author: Vikneshwaran a/l Maiyauen
Format:
Language:English
Published: 2023
Subjects:
Deep Learning
Object Recognition
Recyclable Waste Materials
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id my.uniten.dspace-20516
record_format dspace
spelling my.uniten.dspace-205162023-05-05T08:51:25Z Recylable Waste Materials Recognition Using Deep Learning Framework Vikneshwaran a/l Maiyauen Deep Learning Object Recognition Recyclable Waste Materials Waste 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. 2023-05-03T15:03:37Z 2023-05-03T15:03:37Z 2019-10 https://irepository.uniten.edu.my/handle/123456789/20516 en application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic Deep Learning
Object Recognition
Recyclable Waste Materials
spellingShingle Deep Learning
Object Recognition
Recyclable Waste Materials
Vikneshwaran a/l Maiyauen
Recylable Waste Materials Recognition Using Deep Learning Framework
description Waste 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.
format
author Vikneshwaran a/l Maiyauen
author_facet Vikneshwaran a/l Maiyauen
author_sort Vikneshwaran a/l Maiyauen
title Recylable Waste Materials Recognition Using Deep Learning Framework
title_short Recylable Waste Materials Recognition Using Deep Learning Framework
title_full Recylable Waste Materials Recognition Using Deep Learning Framework
title_fullStr Recylable Waste Materials Recognition Using Deep Learning Framework
title_full_unstemmed Recylable Waste Materials Recognition Using Deep Learning Framework
title_sort recylable waste materials recognition using deep learning framework
publishDate 2023
_version_ 1806427887532769280
score 13.222552

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