The limited capacity to recognise faces under occlusions is a long‐standing problem that
presents a unique challenge for face recognition systems and even humans. The problem …

Face recognition has received significant attention because of its numerous applications in
access control, law enforcement, security, surveillance, Internet communication and …

Vehicle detection and type recognition based on static images is highly practical and directly
applicable for various operations in a traffic surveillance system. This paper will introduce …

A general technique for the recovery of significant image features is presented. The
technique is based on the mean shift algorithm, a simple nonparametric procedure for …

Due to the difficulty in acquiring massive task-specific occluded images, the classification of
occluded images with deep convolutional neural networks (CNNs) remains highly …

Sparse representation based classification (SRC) has recently been proposed for robust
face recognition. To deal with occlusion, SRC introduces an identity matrix as an occlusion …

Over the past three decades, a number of face recognition methods have been proposed in
computer vision, and most of them use holistic face images for person identification. In many …

This paper reviews the state-of-the-art representation-based classification and detection
approaches for hyperspectral remote sensing imagery, including sparse representation …

Sparse subspace clustering (SSC), as one of the most successful subspace clustering
methods, has achieved notable clustering accuracy in computer vision tasks. However, SSC …

Despite the recent success of convolutional neural networks for computer vision
applications, unconstrained face recognition remains a challenge. In this work, we make two …