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

The camera provides rich visual information regarding objects and becomes one of the most
mainstream sensors in the automation community. However, it is often difficult to be …

We propose a generalized Sparse Representation-based Classification (SRC) algorithm for
open set recognition where not all classes presented during testing are known during …

Visual tracking using multiple features has been proved as a robust approach because
features could complement each other. Since different types of variations such as …

This book revolves around the question of designing a matrix D∈ Rm× n called dictionary,
such that to obtain good sparse representations y≈ Dx for a class of signals y∈ Rm given …

The recently proposed multilayer convolutional sparse coding (ML-CSC) model, consisting
of a cascade of convolutional sparse layers, provides a new interpretation of convolutional …

Protection of wetlands is important for ecosystem in recent years, and the classification of
wetland ground cover is the foundation of investigation and protection work. Probabilistic …

Despite the promising progress made in recent years, person re-identification (re-ID)
remains a challenging task due to the complex variations in human appearances from …

The big data samples are important source for analytics. However, its relevant/irrelevant
information, unspecified variables/scales, noise/null, and so forth impose huge challenges …

Traditional grasping analysis of mechanical dexterous grippers tends to flatten a multifinger
tactile series into 1-D, which ignores the force coupling between fingers and their different …