In order to avoid overfitting of face recognition results in complex Convolutional Neural
Network (CNN) on small and medium face situation, this paper provides a face recognition …

With the development of computer vision and artificial intelligence, face recognition is widely
used in daily life. As one of the most concerned methods of biometric recognition, face …

At present, the loss function in the deep convolutional neural network (CNN) can not make
the face feature reach the ideal feature classification criteria, that is, maximizing the inter …

In this paper, we mainly refers to the network structure of Alexnet, the traditional convolution
layer is modified to Multi-layer Perceptron (MLP) convolution layer to enhance the face …

Face recognition technology is an important research field for deep learning. In order to
overcome the shortcomings of traditional open-loop face cognition mode and deep neural …

Today, with the rapid development of science and technology, the era of big data has been
proposed and triggered reforms in all walks of life. Face recognition is a biometric …

In complex environment, the performance of traditional face recognition algorithm decreases
greatly. In order to further improve the recognition accuracy of current face recognition …

For traditional face recognition algorithm based on convolution neural network in the
insufficient light, side face of 45° environment, for large-scale face recognition accuracy is …

In recent years, pattern recognition has received wide attention, especially face recognition.
Research shows that traditional methods have limits in face recognition under unrestricted …

Many methods about face recognition have been put forward. Generally, the feature of the
face image is extracted and then the classifier is used to complete the face recognition …