Face Image Recognition in Smart City Based On Improved Convolutional Neural Network

Abstract

The rapid development of big data and artificial intelligence technology has given new vitality and value to smart cities, which provide rich algorithm models and knowledge computing capabilities. Since the recognition results of the traditional Convolutional Neural Network (CNN) model in the face database are prone to over-fitting, this paper proposes a face recognition algorithm based on an improved CNN model and deep learning. The improved CNN model has a good network image recognition performance, improves the data training speed, and optimizes the network structure parameters. Based on an improved CNN model, using the facial expression recognition (FER2013) data to test the model performance, to achieve more accurate face recognition. Experimental results show that the recognition rate of the improved model and deep learning algorithm on the FER2013 dataset reaches 98.36%, which is 4.63% higher than before the improvement.