As deep residual network has problems such as complex network structure and high time
cost in face recognition applications of small mobile devices, a lightweight model based on …

Face recognition technology is a powerful means to capture biological facial features and
match facial data in existing databases. With the advantages of noncontact and long …

At present, there are two main challenges for large-scale face recognition based on deep
learning. One is to design an appropriate loss function to enhance the discrimination ability …

A Deep Convolutional Support Vector Machine with Bottleneck Attention module (DCSVM-
BAM) to improve the accuracy of recognising face images is proposed and discussed in this …

Face recognition algorithms based on deep learning methods have become increasingly
popular. Most of these are based on highly precise but complex convolutional neural …

With the continuous development of deep learning, convolutional neural networks have
achieved good results in the field of face recognition. However, deep convolutional neural …

The inspiration behind the huge attention given to face recognition systems by the research
community and computer vision specialists is the need to enhance face recognition systems' …

The emergence of deep learning has greatly promoted the development of the field of face
recognition. The accuracy of face recognition in real scenes is affected by many factors …

Face recognition is one of the most popular applications in video surveillance systems and
computer vision. The researches of face recognition in recent years have been shown that …

In recent years, applications of face recognition have increased significantly. Despite the
successful application of deep convolutional neural network (DCNN), training such networks …