Discriminative dictionary learning aims to learn a dictionary from training samples to
enhance the discriminative capability of their coding vectors. Several discrimination terms …

Deep convolutional neural networks (CNNs) have shown their great success on image
classification. CNNs mainly consist of convolutional and pooling layers, both of which are …

This research paper introduces the novel local binary pattern (LBP) variant for face
recognition (FR) called as neighborhood and center difference-based-LBP (NCDB-LBP). In …

Recent advances in bioinformatics and the significant increase in computational power
available to researchers have made it possible to make better use of the vast amounts of …

Dictionary learning (DL) for sparse coding has shown promising results in classification
tasks, while how to adaptively build the relationship between dictionary atoms and class …

Recovering low-rank and sparse subspaces jointly for enhanced robust representation and
classification is discussed. Technically, we first propose a transductive low-rank and sparse …

Object recognition is challenging especially when the objects from different categories are
visually similar to each other. In this paper, we present a novel joint dictionary learning (JDL) …

Automatic violence detection from video is a hot topic for many video surveillance
applications. However, there has been little success in developing an algorithm that can …

Sparse representation is a new approach that has received significant attention for image
classification and recognition. This paper presents a PCA-based dictionary building for …

Human activity analysis in videos has increasingly attracted attention in computer vision
research with the massive number of videos now accessible online. Although many …