Evaluation of CNN Models Using Deep Reinforcement Learning for Band Selection on Hyperspectral Image Classification
Saziye Ozge Atik
Abstract:Along with the high spectral rich information it provides, one of the difficulties in processing a hyperspectral image is the need for expert knowledge and high-spec hardware to process very high-dimensional data. The use of the most relevant bands in the hyperspectral image is quite decisive in deep CNN networks without loss of information and loss of accuracy. It is crucial to classify hyperspectral images with faster and less hardware-requiring models by creating subset groups by choosing a limited number o… Show more
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