Feature-independent classification of hyperspectral images by projection-based random forests

Abstract

The automatic classification of land cover types from hyper-spectral images often relies on expert knowledge and focuses on the extraction of meaningful features that enable a subsequent classifier to distinguish between different land cover classes. In this work Projection-Based Random Forests are applied to hyperspectral images, which completely overcome… (More)
DOI: 10.1109/WHISPERS.2015.8075462

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