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 …

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

Unsupervised feature selection always occupies a key position as a preprocessing in the
tasks of classification or clustering due to the existence of extra essential features within high …

Aiming at the difficult problem of plant leaf recognition on the large-scale database, a two-
stage local similarity based classification learning (LSCL) method is proposed by combining …

Unsupervised feature selection (UFS) aims to remove the redundant information and select
the most representative feature subset from the original data, so it occupies a core position …

Existing block-diagonal representation studies mainly focuses on casting block-diagonal
regularization on training data, while only little attention is dedicated to concurrently learning …

Background Proteins are the important molecules which participate in virtually every aspect
of cellular function within an organism in pairs. Although high-throughput technologies have …

Collaborative representation is an effective way to design classifiers for many practical
applications. In this paper, we propose a novel classifier, called the prior knowledge-based …

Regression analysis based methods have shown strong robustness and achieved great
success in face recognition. In these methods, convex-norm and nuclear norm are usually …

Increasing demand for the knowledge about protein‐protein interactions (PPIs) is promoting
the development of methods for predicting protein interaction network. Although high …