Single sample face recognition (SSFR) is a challenging research problem in which only one
face image per person is available for training. Moreover, the face image may have different …

Face recognition has become popular in the last few decades among researchers across
the globe due to its applicability in several domains. This problem becomes more …

Single Sample Face Recognition (SSFR) is considered one of the most challenging issues
in biometrics. This paper suggested a hybrid model to overcome the SSFR problem using …

Even for the present-day computer technology, the biometric recognition of human face is a
difficult task and continually evolving concept in the area of biometric recognition. The area …

Abstract Single Sample Per Person (SSPP) Face Recognition is receiving a significant
attention due to the challenges it opens especially when conceived for real applications …

Single training sample face recognition (STSFR) is a tricky problem. It can cause a sharp
decline in face recognition (FR) rate since each person only has one training sample. To …

The single sample per person problem (SSPP) is quite common in real-world face
recognition applications. In such circumstance, the lack of enough training samples often …

Collecting samples is one of the main difficulties for face recognition, for example, in most of
the real-world applications such as law enhancement, e-passport, and ID card identification …

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

Face recognition has long been an active research area in the field of artificial intelligence,
particularly since the rise of deep learning in recent years. In some practical situations, each …