Classification of hyperspectral images by deep learning of spectral-spatial features

Keyphrases

• Spectral-spatial Feature 100%
• Deep Learning 100%
• Hyperspectral 100%
• Hyperspectral Image Classification 100%
• Stacked Autoencoder 75%
• Texture Features 50%
• Principal Coordinate Analysis (PCoA) 50%
• Spectral Information 50%
• Deep Learning Network 50%
• Spatial Features 50%
• Autoencoder Architecture 50%
• Gray Level Co-occurrence Matrix 50%
• Spatial Data 25%
• Classification Accuracy 25%
• Image Classification 25%
• Encoder 25%
• Remote Sensing Image 25%
• Remote Sensing Data 25%
• Spectral Features 25%
• Decoder 25%
• Support Vector Machine Classifier 25%
• Feature Extracting 25%
• Autoencoder 25%
• Land Use Land Cover 25%
• Land Cover Mapping 25%
• Multispectral Sensor 25%
• Neighbor Region 25%

Computer Science

• Deep Learning Method 100%
• Hyperspectral Image 100%
• Autoencoder 80%
• Texture Feature 40%
• Principal Components 40%
• Component Analysis 40%
• Spectral Information 40%
• Remote Sensing Image 20%
• Image Classification 20%
• Remotely Sensed Data 20%
• Support Vector Machine 20%
• Spatial Information 20%
• Classification Accuracy 20%
• Spectral Feature 20%

Earth and Planetary Sciences

• Hyperspectral Image 100%
• Principal Component Analysis 40%
• Land Cover 20%
• Stacking 20%
• Image Classification 20%
• Spatial Analysis 20%
• Remote Sensing 20%
• Land Use 20%
• Support Vector Machine 20%