A Study of Garbage Classification with Convolutional Neural Networks

Shanshan Meng, Wei Ta Chu

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

Recycling is already a significant work for all countries. Among the work needed for recycling, garbage classification is the most fundamental step to enable cost-efficient recycling. In this paper, we attempt to identify single garbage object in images and classify it into one of the recycling categories. We study several approaches and provide comprehensive evaluation. The models we used include support vector machines (SVM) with HOG features, simple convolutional neural network (CNN), and CNN with residual blocks. According to the evaluation results, we conclude that simple CNN networks with or without residual blocks show promising performances. Thanks to deep learning techniques, the garbage classification problem for the target database can be effectively solved.

原文English
主出版物標題Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面152-157
頁數6
ISBN(電子)9781728149998
DOIs
出版狀態Published - 2020 二月
事件Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020 - Rajpura, Punjab, India
持續時間: 2020 二月 72020 二月 15

出版系列

名字Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020 - Proceedings

Conference

ConferenceIndo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020
國家/地區India
城市Rajpura, Punjab
期間20-02-0720-02-15

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 電腦科學應用
  • 資訊系統
  • 資訊系統與管理

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