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Two of the biggest challenges in analyzing HyperSpectral Image (HSI) data are that, first, the data is very high-dimensional, and secondly, by its very nature, HSI contains both spatial and spectral information. In order to make full use of this information, models and algorithms should incorporate both aspects of the data; unfortunately, this is a decidedly non-trivial problem. In recent years, spectral...
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