Face recognition has become an attractive field in computer-based application development
in the last few decades. This is because of the wide range of areas in which it is used. In …

A fast automated biometric solution has been proposed to satisfy the future border control
needs of airports resulting from the rapid growth in the number of passengers worldwide …

Single-Sample Face Recognition (SSFR) is a computer vision challenge. In this scenario,
there is only one example from each individual on which to train the system, making it …

Face recognition is receiving a significant attention due to the need of facing important
challenges when develo** real applications under unconstrained environments. The …

With the aid of a universal facial variation dictionary, sparse representation based classifier
(SRC) has been naturally extended for face recognition (FR) with single sample per person …

The issue of single sample per person (SSPP) face recognition has attracted more and more
attention in recent years. Patch/local-based algorithm is one of the most popular categories …

Among several local descriptors invented in literature, the local binary pattern (LBP) is the
prolific one. Despite its advantages like low computational complexity and monotonic gray …

This work investigates the problem of undersampled face recognition (ie, insufficient training
data) encountered in practical Internet-of-Things (IoT) applications. Insufficient and uncertain …

Face recognition (FR) with a single sample per person (SSPP) is one of the most
challenging problems in computer vision. In this scenario, it is difficult to predict facial …

In this paper, we present a novel high-frequency facial feature and a high-frequency-based
sparse representation classification to tackle single sample face recognition (SSFR) under …