The use of sparse representation (SR) and collaborative representation (CR) for pattern
classification has been widely studied in tasks such as face recognition and object …

In recent years, there has been a growing interest in the study of dictionary learning for face
recognition. Most of the conventional dictionary learning methods focus only on a single …

As an effective method of biometrics, palmprint recognition allows the safe identity
recognition of humans without spatial and temporal limitations. To build a more robust …

Many successful algorithms for analyzing ECG signals leverage data-driven models that are
learned for each specific user. Unfortunately, a few algorithmic challenges are still to be …

In this paper, a new discriminative dictionary learning algorithm is introduced. An entropy
based criterion is embedded into the objective function to enforce a proper structure for the …

Discriminative dictionary learning (DDL) has demonstrated significantly improved
performance for image classification. However, most of the existing DDL methods just adopt …

In practical applications, due to a long distance between the monitored population and
monitoring equipment, the face images or human pose captured by the cameras often incur …

Dictionary learning has become a research hotspot. How to construct a robust dictionary is a
key issue. In face recognition problem, differences in expressions, postures, and lighting …

Discriminative dictionary learning plays a key role in sparse representation-based
classification. In this paper, we propose a low-rank graph preserving discriminative …

To address the problem of face recognition where the number of the labeled samples is
insufficient and those samples involve pose, illumination and expression variations, etc., this …