关键词: 人脸识别, 卷积神经网络, 孪生网络, 差异深度度量学习（DDML）, 深度学习

Abstract: In order to overcome the noise interference of illumination, pose, color in face recognition, this paper combines the advantages of convolutional neural networks with twin neural network, puts forward an improved CNN network structure. The structure is composed of two convolutional neural network’s twin network and sharing the weights, using the Discriminative Deep Metric Learning（DDML） algorithm in the training of the network. The convolutional structure can effectively remove external noises and automatically extract homologous features by the trick of sharing weights. It evaluates the method on the ORL, YaleB and AR face data sets and shows that it outperforms other approaches and its recognition rate up nearly 5 percent compared to the PCA and CNN algorithm.

Key words: face recognition, convolutional neural network, twin network, Discriminative Deep Metric Learning（DDML）, deep learning