[1]ZHANG Jingyu,XU Xinying,XIE Gang,et al.Continuous classification of garbage based on the elastic weightconsolidation and knowledge distillation[J].CAAI Transactions on Intelligent Systems,2023,18(4):878-885.[doi:10.11992/tis.202211023]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
18
Number of periods:
2023 4
Page number:
878-885
Column:
吴文俊人工智能科学技术奖论坛
Public date:
2023-07-15
- Title:
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Continuous classification of garbage based on the elastic weightconsolidation and knowledge distillation
- Author(s):
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ZHANG Jingyu1; XU Xinying1; XIE Gang1; LIU Huaping2
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1. College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China;
2. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
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- Keywords:
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domestic garbage; image classification; continuous learning; deep learning; knowledge distillation; regularization; temperature coefficient; generalization capability
- CLC:
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TP391
- DOI:
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10.11992/tis.202211023
- Abstract:
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The current garbage classification methods focus on the classification of common domestic garbage of fixed classes, which cannot meet the dynamic and continuous classification requirements brought by the growth of the number of garbage classes. To solve this problem, the paper proposes an elastic weight consolidation and knowledge distillation (EWC-KD) continuous garbage classification method. The method enhances the memory ability of the model through EWC regularization loss function and distillation loss function. EWC regularization loss function limits the update range of important parameters, and the distillation loss function with temperature coefficient enhances the generalization ability of the model by protecting the class information carried in the class label. Experiments on five garbage classification tasks show that the performance of this method is better than that of the comparison method. Our method can maintain high classification accuracy and low backward transfer value on all tasks, and can enhance the continuous classification ability of the garbage classification system.