Abstract The Artificial Intelligence Internet of Things (AIoT) is an emerging concept aiming to
perceive, understand and connect the 'intelligent things' to make the intercommunication of …

Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …

Feature selection (FS), which identifies the relevant features in a data set to facilitate
subsequent data analysis, is a fundamental problem in machine learning and has been …

This paper addresses the problem of face recognition when there is only few, or even only a
single, labeled examples of the face that we wish to recognize. Moreover, these examples …

Visual information is increasingly recognized as a useful method to detect rail surface
defects due to its high efficiency and stability. However, it cannot sufficiently detect a …

Multi-view clustering refers to the task of partitioning numerous unlabeled multimedia data
into several distinct clusters using multiple features. In this paper, we propose a novel …

Computer vision based methods have been widely used in surface defect inspection.
However, most of these approaches are task specific, and it is hard to transfer them to similar …

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

Feature extraction plays a significant role in pattern recognition. Recently, many
representation-based feature extraction methods have been proposed and achieved …

Recently, deep learning-based methods have drawn increasing attention in hyperspectral
imagery (HSI) classification, due to their strong nonlinear mapping capability. However …