The growing availability of hyperspectral remote sensing data, specifically from the new
hyperspectral satellite missions, requires efficient data compression due to limitations in …

This study compares two machine learning pixel classifiers with classical approaches for
detecting camouflage targets in hyperspectral data. Recent applications of machine learning …

This work addresses the challenge of including the spatial dimension into the autoencoder
models for lossy compression of different spatially independent and unknown hyperspectral …

This work discusses three individual camouflage experiments from a drone-based
hyperspectral measurement campaign conducted in 2021. The experiments were designed …

HyperThun'22 was a multi-sensor and multi-temporal camouflage detection campaign with
drone-carried hyper-spectral, thermal, and RGB instruments. In more than 20 flights, various …