Sparse representations for hyperspectral data classification

Keyphrases

• Hyperspectral 100%
• Hyperspectral Image Classification 100%
• Sparse Representation 100%
• Sparse Principal Components 100%
• Feature Extraction Methods 66%
• Feature Selection 66%
• Low Dimensionality 66%
• Dimensionality Reduction 33%
• Exhaustive Search 33%
• Feature Selection Methods 33%
• Linear Combination 33%
• Multispectral Data 33%
• Linear Transformation 33%
• Feature Subset 33%
• Low-dimensional Space 33%
• Human Understanding 33%
• Traditional Features 33%
• Class Separability 33%
• Sparse Vector 33%

Computer Science

• Hyperspectral Data 100%
• Data Classification 100%
• Sparse Representation 100%
• Feature Extraction 100%
• Principal Components 60%
• Feature Selection 60%
• Hyperspectral Image 20%
• Exhaustive Search 20%
• Linear Combination 20%
• Data Representation 20%
• Linear Transformation 20%
• Lower Dimensional Space 20%
• Multispectral Data 20%

Engineering

• Feature Extraction 100%
• Hyperspectral Data 100%
• Principal Components 60%
• Dimensionality 40%
• Hyperspectral Image 20%
• Hyperspectral Imagery 20%
• Linear Combination 20%
• Dimensional Space 20%
• Exhaustive Search 20%
• Data Representation 20%
• Class Separability 20%
• Multispectral Data 20%
• Linear Transformation 20%