RESEARCH ON FACE RECOGNITION ALGORITHM BASED ON DEEP LEARNING

• 1、Institute of Network Technology, Beijing University Of Posts And Telecommunications, Beijing 100876

Abstract：The traditional face recognition algorithm is mainly based on the image of the shallow feature extraction, such as LBP, SIFT, HOG image feature descriptors, and then a variety of shallow features fusion, PCA dimension reduction and then use the traditional machine learning classifier for face recognition, such as linear discriminant, SVM, Joint Bayesian distribution. Deep learning can extract the high-level, abstract and conceptual features of the image, and can extract the most essential features of the human face from the perspective of the image. The global features can well solve the problems of facial pose, expression, light, age, cover and other noise effects. The innovation of this paper is to design a highly efficient facial feature extractor using the combination of the current and efficient Inception-ResNet and SqueezeNet network models with a variety of loss functions and to test directly on the LFW public test set, achieving very high Performance.?????

Keywords： artificial intelligence；face recognition； CNN； loss function