Face recognition technique has obtained great progress and excellent results on public data
sets. However, traditional algorithms suffer from various changes such as illumination …

Recently, regression analysis has become a popular method for face recognition. Various
robust regression methods have been proposed to handle with different recognition tasks. In …

There has been a lot of work on face modeling, analysis, and landmark detection, with Active
Appearance Models being one of the most successful techniques. A major drawback of …

A variety of factors affect English classroom teaching, which prevents teachers from
effectively grasping students' learning status and learning situation. In particular, classroom …

The theory of compressive sensing applies the sparse representation to the extraction of
useful information from signals and brings a breakthrough to the theory of signal sampling …

In recent years, college campus incidents caused by mental health problems have been
increasing year by year, and college students' mental health problems have become the …

Face recognition technologies (FRTs) have many practical security-related purposes, but
advocacy groups and individuals have expressed apprehensions about their use. This …

Face recognition is a critical component in many computer vision applications. Although now
big data computing could bring high face recognition rate, it needs strong computing power …

Face recognition (FR) has been one of the most fundamental problems in computer vision.
Two issues are always concerned in a FR task: one is the dimensionality reduction (DR) of …

The extended sparse representation classification (ESRC) is one of the benchmark
classification algorithms in the field of single sample face recognition (SSFR). However …