Dimensionality reduction based on determinantal point process and singular spectrum analysis for hyperspectral images

Abstract: Dimensionality reduction is of high importance in hyperspectral data processing, which can effectively reduce the data redundancy and computation time for improved classification accuracy. Band selec...
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