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

In recent years, convolutional neural network has achieved good results in the field of face
recognition, but it ignores the local features of face in feature extraction. Therefore, this …

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 order to further improve the ability of automatic feature extraction of deep learning
technology and better solve the problem of system recognition ability declining when the …

It is difficult to extract suitable face feature for classification, and the face recognition
accuracy is low under unconstrained condition. To solve the above problems, a new method …

As a prevailing research in artificial intelligence, the application of computer vision is widely
used in many fields which are closely related to people's livelihood, such as industrial …

Aiming at the problems of low non-constrained feature discriminative ability and poor face
recognition performance of current many algorithms, an improved face recognition algorithm …

With the rapid development of computer science and Internet technology, face recognition
technology is widely used in such as public security, judicial and criminal investigation …

The current research results of face recognition have poor recognition accuracy, time-
consuming and high information loss rate. A method of automatic face recognition based on …

At present, the correct recognition rate of face recognition algorithm is limited under
unconstrained conditions. To solve this problem, a face recognition algorithm based on …