Recently, in the field of face recognition, deep learning has achieved great success.
FaceNet, one of the Google's deep learning frameworks, obtained nearly 100% accuracy in …

Regarding the problem that the increasing number of layers of CNN (convolutional neural
network) leads to the decline of accuracy, an improved loss function algorithm based on the …

In recent years, deep learning has become a very prevalent technology in face recognition.
Google came up with a deep convolution neural network called Facenet which performs …

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 …

For the problem that the face image of surveillance video cannot be accurately identified due
to the low resolution, this paper proposes a low resolution face recognition solution based …

This paper represents a low error face recognition system constructed on convolutional
neural network structure. The proposed method introduces a new layer arrangement for the …

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 …

Deep convolutional neural networks (CNNs) based face recognition approaches have been
dominating the field. The success of CNNs is attributed to their ability to learn rich image …

With the continuous development of convolutional neural networks, more hardware
resources are required. Lightweight convolutional neural networks show their own …

Images from the surveillance networks are being extensively used for the purpose of
monitoring and criminal investigations. However, it is often difficult to recognize faces using …