FRF-Net: Land Cover Classification from Large-Scale VHR Optical Remote Sensing Images

Computer Science

• Receptive Field 100%
• Attention (Machine Learning) 100%
• Remote Sensing Image 100%
• Self-Attention Mechanism 50%
• Feature Extraction 50%
• Computation Cost 50%
• Feature Fusion 50%
• Residual Neural Network 50%
• Deep Learning Technique 50%
• semantic description 50%

Engineering

• High Resolution 100%
• Land Cover 100%
• Receptive Field 50%
• Level Feature 50%
• Feature Extraction 25%
• State-of-the-Art Method 25%
• Decoding Method 25%
• Deep Learning 25%
• Learning Technique 25%
• Sensing Application 25%
• Nonlinear Feature 25%
• Combined Mechanism 25%

Earth and Planetary Sciences

• High Resolution 100%
• Optical Remote Sensing 100%
• Land Cover 100%
• State of the Art 25%
• Self-Attention 25%
• Remote Sensing Application 25%
• Pattern Recognition 25%