When low rank representation based hyperspectral imagery classification meets segmented stacked denoising auto-encoder based spatial-spectral feature

Computer Science

• Representation Learning 100%
• de-noising 100%
• Spectral Feature 100%
• Low-Rank Representation 100%
• Extracted Feature 66%
• Spectral Characteristic 33%
• Support Vector Machine 33%
• Learning Scheme 33%
• Classification Accuracy 33%
• Unlabeled Sample 33%
• Classification Framework 33%