Hyperspectral CNN compression and band selection
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Updated
Feb 16, 2020 - Jupyter Notebook
Hyperspectral CNN compression and band selection
Hyperspectral Band Selection using Self-Representation Learning with Sparse 1D-Operational Autoencoder (SRL-SOA)
Independent component analysis for dimensionality reduction of hyperspectral images
Neural network visualization tool after an optional model compression with parameter pruning: (integrated) gradients, guided/visual backpropagation, activation maps for the cao model on the IndianPines dataset
A Third-Party Implementation of Paper A Geometry-Based Band Selection Approach for Hyperspectral Image Analysis
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