Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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Garbage Image Classification based on Deep Learning

Authors
Wanqing Wang1, *
1College of Century, Beijing University of Posts and Telecommunications, Beijing, China
*Corresponding author. Email: wangwanqing@stu.ahu.edu.cn
Corresponding Author
Wanqing Wang
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_42How to use a DOI?
Keywords
ResNet50; Learning model; Inception v3; SENet; Garbage image classification
Abstract

Today, there are many disadvantages to using manual sorting for refuse classification. How can we solve the problem of garbage classification efficiently and correctly? It is necessary to solve it at present. In order to solve this problem, researchers have begun to use deep learning technology to sort waste in recent years and have come up with some effective methods. The application and development of different deep learning models in garbage classification are introduced from the aspects of methods and principles. In order to avoid duplication of work by other researchers, improve the significance and value of research, help other researchers to be familiar with and understand the existing research results of deep learning garbage classification, find out the frontier problems of these models, and expand the research ideas and methods of deep learning garbage classification. In this paper, three models are analyzed: ResNet50 model, transfer learning model, Inception-v3 model, and network model combining ResNet and SENet, and a new feasible model is proposed.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
10.2991/978-94-6463-370-2_42
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_42How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Wanqing Wang
PY  - 2024
DA  - 2024/02/14
TI  - Garbage Image Classification based on Deep Learning
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 400
EP  - 410
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_42
DO  - 10.2991/978-94-6463-370-2_42
ID  - Wang2024
ER  -