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A Novel Multi-Branch Channel Expansion Network for Garbage Image Classification
Due to the lack of data available for training, deep learning hardly performed well in the field of garbage image classification. We choose the TrashNet data set which is widely used in the field of garbage image classification, and try to overcome data deficiencies in this field by optimizing the network structure. In this paper, it is found that the deeper network and short-circuit connection, which are generally accepted in the field of deep learning, will not work well on the TrashNet datadoi:10.1109/access.2020.3016116 fatcat:z3d6cgaqmndxtkqd2loqyttbxa