Convolutional neural networks are currently popular multi-layer neural networks. They differ from traditional neural networks in some ways. They are mainly reflected in the introduction of three new concepts: weight sharing, receptive fields, and pooling. In this paper, for the handwritten digit character data set, a deep neural network is used to construct a LeNet network for training and recognition, and the data is enhanced differently to study and compare the recognition accuracy of the final network structure.
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