SC-CAN: Spectral Convolution and Channel Attention Network for Wheat Stress Classification

Engineering

• Convolutional Layer 100%
• Experimental Result 50%
• Early Stage 50%
• Interrelationship 50%
• State-of-the-Art Technique 50%
• Hyperspectral Data 50%
• Spectral Feature 50%
• Spectral Response 50%
• Deep Learning Method 50%
• Receptive Field 50%

Computer Science

• Attention (Machine Learning) 100%
• Convolution 100%
• Feature Map 42%
• local feature 28%
• Convolutional Layer 28%
• Global Feature 14%
• Deep Learning Method 14%
• Convolution Layer 14%
• Attention Score 14%
• Experimental Result 14%
• Spectral Feature 14%
• Hyperspectral Data 14%
• Fully Connected Layer 14%
• Receptive Field 14%