Abstract
With the development of deep learning, face recognition technology based on CNN (Convolutional Neural Network) has become the main method adopted in the field of face recognition. In this paper, the basic principles of CNN are studied, and the convolutional and downsampled layers of CNN are constructed by using the convolution function and downsampling function in opencv to process the pictures. At the same time, the basic principle of MLP Grasp the full connection layer and classification layer, and use Python's theano library to achieve. The construction and training of CNN model based on face recognition are studied. To simplify the CNN model, the convolution and sampling layers are combined into a single layer. Based on the already trained network, greatly improve the image recognition rate.
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