In this paper, an efficient face recognition method using AGA and ANFIS-ABC has been
proposed. At first stage, the face images gathered from the database are preprocessed. At …

Deep neural network (DNN) has been used as a learning model for modeling the
hierarchical architecture of human brain. However, DNN suffers from problems of learning …

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 …

This study presents a comprehensive review of the automated classification in partial
discharge (PD) source identification and probabilistic interpretation of the classification …

For sparse representation or sparse coding based image classification, the dictionary, which
is required to faithfully and robustly represent query images, plays an important role on its …

Abstract Strict '0-1'block-diagonal structure has been widely used for learning structured
representation in face recognition problems. However, it is questionable and unreasonable …

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 …

In this paper, a robust sparse representation for medical image classification is proposed
based on the adaptive type-2 fuzzy learning (T2-FDL) system. In the proposed method …

Sparse representation-based classification (SRC) and collaborative representation-based
classification (CRC) have shown promising classification results. Both methods are distance …

In this work, we introduce a new modeling and inferential tool for dynamical processing of
time series. The approach is called recurrent dictionary learning (RDL). The proposed model …