Abstract:Aiming at the problem of convolutional layer parameter redundancy and low operation efficiency in convolutional neural network, a convolution neural network (CNN) model compression method based on statistical analysis is proposed in this paper. On the premise of ensuring a good ability of convolutional neural network to process information, the well-trained convolution neural network model is compressed by pruning the convolution kernels which have less influence on the whole model in the convolution layer, meanwhile, reducing the parameters of CNN without losing the model accuracy so as to reduce the amount of computation. Experiments show that the proposed method can effectively compress the convolution neural network model while maintaining a good performance.