Abundant spectral information endows unique advantages of hyperspectral remote sensing
images in target location and recognition. Target detection techniques locate materials or …

Hyperspectral target detection can be described as locating targets of interest within a
hyperspectral image based on prior information of targets. The complexity of actual scenes …

Hyperspectral image (HSI) has received considerable attention in the field of target detection
due to its powerful ability to capture the spectral information of land covers, and plenty of …

Anomaly detection has become an important remote sensing application due to the
abundant spectral and spatial information contained in hyperspectral images. Recently …

When predicting data for which limited supervised information is available, hyperspectral
target detection methods based on deep transfer learning expect that the network will not …

Deep learning-based hyperspectral target detection (HTD) methods are limited by the lack of
prior information. Self-supervised learning is a kind of unsupervised learning, which mainly …

The detection of camouflaged targets in the complex background is a hot topic of current
research. The existing hyperspectral target detection algorithms do not take advantage of …

Hyperspectral target detection (HTD) is an important issue in Earth observation, with
applications in both military and civilian domains. However, conventional representation …

Anomaly detection in hyperspectral images (HSIs) has attracted considerable interest in the
remote-sensing domain, which aims to identify pixels with different spectral and spatial …

Target detection in hyperspectral images (HSIs) mainly relies on the spectral information of
the target prior. However, prior spectra with precise variation information are often hard to …