… a variational feature representation-based classification approach … features, we also design
a new sparse representation based model to further enhance the robustness to gross facial …

… We compare our method with recently proposed sparserepresentation-based classical …
For θ = 0 our algorithm is forced in any case to classify the test subject as one of the subject …

… representation-based classification (SRC) has attracted much attention by casting the
recognition … Each individual has about 64 images taken under various laboratory-controlled …

… , for example, the sparse representation-based classifier (SRC) and … that provides abundant
variational information fits to … convolution feature for face recognition with single sample per …

… Sparse representation-based classification (SRC) techniques have been shown to achieve
a high level of performance in video-based face recognition (FR). However, matching faces …

… sparse representation-based reconstruction … classification accuracies yielded by the
parallel classification algorithms for probe face image P are combined into a single classification …

… representation-based classification (SRC) has been shown to achieve a high level of accuracy
in face recognition … framework referred as the synthetic plus variational model (S+V) is …

… model [18] employed the synthetic plus variational model to augment the gallery … representation
based classification (FKESRC) [6] utilized the coordinate descent method in the feature …

… semi-supervised sparse representation based classification (S3RC) [31… Kingma and Welling
[41] developed a variational auto-… convolution feature for face recognition with single sample …

… face datasets that have been commonly used for evaluating single sample face recognition
… Additionally, we discuss problems with existing single sample face recognition methods, …