Blind Hyperspectral Unmixing Using Autoencoders: A Critical Comparison
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DOI: 10.1109/jstars.2021.3140154
Abstract: Deep learning (DL) has heavily impacted the data-intensive field of remote sensing. Autoencoders are a type of DL methods that have been found to be powerful for blind hyperspectral unmixing (HU). HU is the process… read more here.
Keywords: critical comparison; using autoencoders; unmixing using; blind hyperspectral ... See more keywords