Survey on classification methods for hyper spectral remote sensing imagery

Classification of hyperspectral remote sensing images is key to extract abundant information. The researchers are focusing on the development of algorithms for accurate classifiers from last few decades. With the technological advancement and new modern methods of learning provide confidence for efficient and accurate classification when compared to the direct implementation of conventional learning algorithms. The variations in the conventional algorithm leads to active learning based and transfer learning based approaches and provide promising results. This paper attempt to explore various recent technologies applied to Hyperspectral imagery for classification.

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