This article presents a simple yet effective face recognition method, called local structure-
based sparse representation classification (LS_SRC). Motivated by the “divide-and …

In this paper, we propose local structure based sparse representation classification (LS
SRC) to solve single sample per person (SSPP) problem. By adopting the “divide-conquer …

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention
for its applications to various tasks, especially in biometric techniques such as face …

The sparse representation based classification methods has achieved significant
performance in recent years. To fully exploit both the holistic and locality information of face …

Sparse representation-based classification (SRC) has acquired prominent capability in
fields of machine learning and pattern recognition. Collaborative representation-based …

Sparse representation classification, as one of the state-of-the-art classification methods,
has been widely studied and successfully applied in face recognition since it was proposed …

The sparse representation-based classification (SRC) has been proven to be a robust face
recognition method. However, its computational complexity is very high due to solving a …

Sparse representation (or coding)-based classification (SRC) has gained great success in
face recognition in recent years. However, SRC emphasizes the sparsity too much and …

Sparse representation has shown its merits in solving some classification problems and
delivered some impressive results in face recognition. However, the unsupervised …

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