In the past ten years, research on face recognition has shifted to using 3D facial surfaces, as
3D geometric information provides more discriminative features. This comprehensive survey …

Three-dimensional (3D) face recognition has been extensively investigated in the last two
decades due to its wide range of applications in many areas, such as security and forensics …

Three-dimensional face recognition is an important part of the field of computer vision. Point
clouds are widely used in the field of 3D vision due to the simple mathematical expression …

In this paper, we present a deep learning-based method for 3D face recognition. Unlike
some previous works, our process does not rely on face representation methods as a proxy …

As a biometric identification method in the post-epidemic era, face recognition owing more
and more attention in practical applications to its non-contact and interaction-friendly …

Face recognition is one of the most studied research topics in the community. In recent
years, the research on face recognition has shifted to using 3D facial surfaces, as more …

Face recognition has recently become most important and popular in biometrics and
computer vision applications. Nowadays, 3D face recognition fascinates researchers with …

Early detection of lung cancer is critical for improvement of patient survival. To address the
clinical need for efficacious treatments, genetically engineered mouse models (GEMM) have …

The human face is a research hotspot in the existing biometric technology. The collection of
the faces is affected by unpredictable factors in reality, such as expression change, posture …

A principal component analysis network (PCANet), as one of the representative deep
subspace learning networks, utilizes principal component analysis (PCA) to learn filters that …