With the application of deep convolutional neural networks, the performance of computer
vision tasks has been improved to a new level. The construction of a deeper and more …

Face recognition is difficult due to the higher dimension of face image features and fewer
training samples. Firstly, in order to improve the performance of feature extraction, we …

In this paper, a face recognition method based on deep learning is studied and
implemented. By adjusting the hierarchical depth and structure of the typical convolutional …

Purpose: Due to the lack of prior knowledge of face images, large illumination changes, and
complex backgrounds, the accuracy of face recognition is low. To address this issue, we …

The face targets in the dynamic scene video stream avoidably have external factors such as
occlusion, fast movement, blurred background, uncontrollable lighting, etc., which are likely …

The traditional face recognition technology requires a lot of computation time for human face
feature extraction, and the recognition accuracy is limited by the extracted face features …

In this paper, we propose a face detection and recognition system using deep learning
method. It can be used as an access control system that performs face detection and …

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 …

Because a large number of labeled face data samples in special scenes need a large
number of training samples with identity markers, and it is impossible to accurately extract …