Excellent performance, real time and strong robustness are three vital requirements for
infrared small target detection. Unfortunately, many current state-of-the-art methods merely …

Incomplete multi-view clustering (IMVC) has attracted remarkable attention due to the
emergence of multi-view data with missing views in real applications. Recent methods …

This paper studies the subspace clustering problem. Given some data points approximately
drawn from a union of subspaces, the goal is to group these data points into their underlying …

Gait is one of the most promising biometrics that aims to identify pedestrians from their
walking patterns. However, prevailing methods are susceptible to confounders, resulting in …

Many state-of-the-art methods have been proposed for infrared small target detection. They
work well on the images with homogeneous backgrounds and high-contrast targets …

Intelligent Transportation Systems (ITSs) are vital for alleviating traffic congestion and
improving traffic efficiency. Due to the delay of network transmission and failure of detectors …

The precise classification of land covers with hyperspectral imagery (HSI) is a major
research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) …

Hyperspectral image (HSI) denoising is challenging not only because of the difficulty in
preserving both spectral and spatial structures simultaneously, but also due to the …

This work studies the low-rank tensor completion problem, which aims to exactly recover a
low-rank tensor from partially observed entries. Our model is inspired by the recently …

Multi-view clustering is widely used to improve clustering performance. Recently, the
subspace clustering tensor learning method based on Markov chain is a crucial branch of …