An efficient face recognition algorithm using the improved convolutional neural network

Abstract

This paper concentrates on the problem of human face recognition problem, which is a crucial problem in computer vision. In this paper, the semi-supervised learning based convolutional neural network is used to implement the face recognition system with high efficiency. Convolutional neural networks denote a multi-layer neural network, in which each layer is made up of multiple two-dimension planes and each plane consists of a lot of independent neurons. To extract the rich and discriminative information of human face images, the sparse Laplacian filter learning is utilized to learn the filters of the network with a large scale unlabeled human face images. Afterwards, a softmax classifier layer is trained by multi-task learning using only a small number of labeled human face images as the output layer. In the end, a series of experiments are conducted to test the performance of our proposed algorithm. Experimental results show that face recognition accuracy of the proposed improved CNN method performs better than other methods.