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Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox
Rasti, B.; Hong, D.; Hang, R.; Ghamisi, P.; Kang, X.; Chanussot, J.; Benediktsson, J. A.
Hyperspectral images (HSIs) provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands), which can be used to accurately classify diverse materials of interest. The increased dimensionality of such data makes it possible to significantly improve data information content but provides a challenge to conventional techniques (the so-called curse of dimensionality) for accurate analysis of HSIs.
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- Feature Extraction for Hyperspectral Imagery: The … (Id 31906) HZDR-primary research data are used by this (Id 32303) publication
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IEEE Geoscience and Remote Sensing Magazine 8(2020)4, 60-88
DOI: 10.1109/MGRS.2020.2979764
Permalink: https://www.hzdr.de/publications/Publ-32303
Publ.-Id: 32303