CNN structure is composed of convolution layer, pooling layer and full connection layer. Features are extracted through convolution layer, then dimensionality is reduced through pooling layer, and finally classification results are output through full connection layer. In order to avoid over quasi merging and improve the prediction ability of the model for unknown data, a regular term dropout is added between the full connection layer and the pooling layer.
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