Research Article
Research on Garbage Classification Algorithm Based on Machine Learning
@INPROCEEDINGS{10.1007/978-3-031-71716-1_3, author={Yuxin Bai and Shaoru Li and Jingjing Fan and Jiana Zhao}, title={Research on Garbage Classification Algorithm Based on Machine Learning}, proceedings={Machine Learning and Intelligent Communication. 8th EAI International Conference, MLICOM 2023, Beijing, China, December 17, 2023, Proceedings}, proceedings_a={MLICOM}, year={2024}, month={9}, keywords={Waste classification machine learning PyTorch VGG model}, doi={10.1007/978-3-031-71716-1_3} }- Yuxin Bai
Shaoru Li
Jingjing Fan
Jiana Zhao
Year: 2024
Research on Garbage Classification Algorithm Based on Machine Learning
MLICOM
Springer
DOI: 10.1007/978-3-031-71716-1_3
Abstract
With the development of urbanization and the improvement of consumption levels, garbage disposal has become one of the major challenges facing environmental protection. In order to classify garbage efficiently and accurately and promote the construction of “two-oriented society” and smart cities, this topic studies a garbage classification technology based on machine learning. Based on the PyTorch framework design, I compared the training and testing of the AlexNet model and the VGG model. Through testing the experimental results, it was found that using the VGG19 model and optimization method, the accuracy of garbage classification can reach 95%, which is higher than other models. Finally, the VGG19 model is used for training and transfer learning.
