Source Journal of CSCD
Source Journal for Chinese Scientific and Technical Papers
Core Journal of RCCSE
Included in JST China
Volume 40 Issue 1
Mar.  2022
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Article Contents
JIN Peiwei, YAO Yan, LIANG Xiaoyu, CAI Jinhui. OVERVIEW OF RESEARCHES ON MUNICIPAL SOLID WASTE IMAGE RECOGNITION[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(1): 196-206. doi: 10.13205/j.hjgc.202201029
Citation: JIN Peiwei, YAO Yan, LIANG Xiaoyu, CAI Jinhui. OVERVIEW OF RESEARCHES ON MUNICIPAL SOLID WASTE IMAGE RECOGNITION[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(1): 196-206. doi: 10.13205/j.hjgc.202201029

OVERVIEW OF RESEARCHES ON MUNICIPAL SOLID WASTE IMAGE RECOGNITION

doi: 10.13205/j.hjgc.202201029
  • Received Date: 2021-01-21
    Available Online: 2022-03-30
  • Publish Date: 2022-03-30
  • Realizing the automatic classification of domestic waste is an effective way to solve the increasing problems on municipal solid waste(MSW). The thesis focused on the researches on waste image recognition based on computer vision in the past ten years. According to the differences of automatic waste classification methods, the current existing related research was divided into traditional machine learning methods and deep learning methods. It illustrated the machine learning method and the feature extraction method of the deep learning method, compared and analyzed the advantages and disadvantages of the traditional machine learning method and the waste type recognition based on the deep learning method, focused on the application research of the general neural network of the deep learning method. In addition, the data sets used in the current research on waste image recognition were introduced, and the problem of current waste image recognition were analyzed and prospected finally.
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