With the increasing use of surveillance cameras, face recognition is being studied by many
researchers for security purposes. Although high accuracy has been achieved for frontal …

Sparse representation plays an important role in the research of face recognition. As a
deformable sample classification task, face recognition is often used to test the performance …

Nonnegative sparse representation has become a popular methodology in medical analysis
and diagnosis in recent years. In order to resolve network degradation, higher …

Performance of deep learning methods for face recognition often relies on abundant data,
posing challenges in surveillance and security where data availability is limited and …

Finger-vein recognition is a new type of biometric identification technology compared to
traditional biometric identification methods such as fingerprint recognition. Finger-vein is …

Conventional facial expression recognition (FER) methods often assume that the training
and test procedures are carried out on a single database, without considering the cross …

Deep learning networks are considered as an important technique for face recognition and
image recognition. Convolutional Neural Networks (CNN) is regarded as a problem solver in …

Face detection is a computer technology being used in a variety of applications that identify
human faces in digital images. In many face recognition challenges, Convolutional Neural …

Face recognition is an active research area in biometric authentication, which has gained
more attention among researchers due to the availability of feasible technologies, including …

It is highly challenging to obtain high performance with limited and unconstrained data in
real time face recognition applications. Sparse Approximation is a fast and computationally …