DSNet fuses autoencoder-derived abundance maps with CNN features to classify hyperspectral images, achieving the best reported accuracy on Indian Pines, Berlin, and Augsburg.
Hyperspectral vegetation indices and novel algorithms for predicting green lai of crop canopies: Modeling and validation in the context of precision agriculture,
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Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification
DSNet fuses autoencoder-derived abundance maps with CNN features to classify hyperspectral images, achieving the best reported accuracy on Indian Pines, Berlin, and Augsburg.