Real-time face recognition targets to match a human's face in a digital image or a video
frame against faces in a database, which plays an important role in various fields nowadays …

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

Based on the advance in GPU and big data, deep learning has brought progress, especially
in computer vision. But the acceleration by GPU is not cost-effective on the dedicated …

With the continuous improvement of computer software and hardware performance, a large
amount of image and video data can be easily collected and quickly transmitted, and new …

With the increase in the number of data, the traditional shallow image features cannot meet
the needs of image representation. As an important means of image research, deep learning …

With the explosive growth of population and the development of technology, face recognition
has been widely applied to various fields. At the same time, there are problems of low …

In order to overcome the problems of OpenCV in face detection, such as missing detection,
false detection and poor recognition effect, a new method of Dlib face recognition based on …

At present, the face recognition methods based on deep learning have the problems of large
model parameter size and slow feature extraction speed, and the existing face datasets …

Low-resolution face recognition is one of the research hotspots of face recognition today. It
can be widely used in face recognition in various scenarios, such as identity verification at …