Human face recognition have been an active research area for the last few decades.
Especially, during the last five years, it has gained significant research attention from …

The capacity to recognize faces under varied poses is a fundamental human ability that
presents a unique challenge for computer vision systems. Compared to frontal face …

This paper explores multi-task learning (MTL) for face recognition. First, we propose a multi-
task convolutional neural network (CNN) for face recognition, where identity classification is …

Sparse representation has shown an attractive performance in a number of applications.
However, the available sparse representation methods still suffer from some problems, and …

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

Hyperspectral imagery contains hundreds of contiguous bands with a wealth of spectral
signatures, making it possible to distinguish materials through subtle spectral discrepancies …

Objective Accurately segmenting and quantifying brain gliomas from magnetic resonance
(MR) images remains a challenging task because of the large spatial and structural …

In this paper, a human–machine interface for disabled people with spinal cord injuries is
proposed. The designed human–machine interface is an assistive system that uses head …

Two well-known techniques, extreme learning machine (ELM) and sparse representation
based classification (SRC) method, have attracted significant attention due to their …

This paper presents a new symmetrical SURF descriptor to detect vehicles on roads and
then proposes a novel sparsity-based classification scheme to recognize their makes and …