Design of a High-Efficiency Temporal Engine for Real-Time Spatial Satellite Image Classification Using Augmented Incremental Transfer Learning for Crop Analysis

Engineering

• Convolutional Neural Network 100%
• Transfer Learning 100%
• Image Classification 100%
• Feature Extraction 66%
• Image Processing 66%
• Network Model 33%
• Signal-to-Noise Ratio 33%
• Limitations 33%
• Processing Task 33%
• Peak Signal 33%
• Process Parameter 33%
• Internal Process 33%
• Process Requirement 33%
• Damage Detection 33%
• Geographical Area 33%

Computer Science

• Transfer Learning 100%
• Image Classification 100%
• Satellite Image 100%
• Convolutional Neural Network 60%
• Feature Extraction 40%
• Image Processing 40%
• Neural Network Model 20%
• Processing Task 20%
• Average Accuracy 20%
• de-noising 20%
• peak signal to noise ratio 20%
• Geographical Area 20%
• Process Requirement 20%
• Postprocessing 20%
• Processing Model 20%

Earth and Planetary Sciences

• Real Time 100%
• Satellite Image 100%
• Image Classification 100%
• Image Processing 40%
• State of the Art 20%
• Pattern Recognition 20%
• Satellite Data 20%