关键词: 人工智能, 人脸识别, 卷积神经网络, 结构改进, 激活函数优化

Abstract: Aiming at the problem of overfitting, slow convergence, local optimization and low recognition accuracy of existing Convolutional Neural Network（CNN） in face recognition training, a new LeNet-FC convolutional neural network model is proposed in this paper.By improving the network structure of the network layer, reducing the convolution kernel, and using the optimized Logarithmic Rectified Linear Unit（L_ReLU） activation function, the recognition accuracy of the model in face recognition training reaches 99.85%.Simultaneously, a face recognition system is designed based on the LeNet-FC convolutional neural network model. The recognition accuracy of the system in the simulation test experiment with ORL face database reaches 96%.

Key words: artificial intelligence, face recognition, convolutional neural network, network structure improvement, activation function optimization