Deep learning approaches for thermographic imaging

Keyphrases

• Thermographic Imaging 100%
• Deep Learning Methods 100%
• Deep Neural Network 100%
• Virtual Wave 66%
• Hybrid Method 66%
• Surface Temperature Measurement 66%
• Non-destructive Testing 33%
• Reconstruction Method 33%
• Deep Learning 33%
• Temperature Profile 33%
• Thermography 33%
• Sparsity 33%
• Network Architecture 33%
• Reconstruction Technique 33%
• Supportability Evaluation 33%
• Nondestructive Testing of Materials 33%
• Number of Training Samples 33%
• Thermographic Images 33%
• Computationally Efficient 33%
• Temperature Measurement 33%
• Non-negativity 33%
• Computationally Expensive 33%
• Physical Phantom 33%
• Compact Network 33%
• Reconstruction Accuracy 33%
• Data Generator 33%
• Synthetic Aperture Focusing Technique 33%
• Curvelet Denoising 33%
• Unseen 33%
• Model Reconstruction 33%
• End-to-end Reconstruction 33%
• Metal Wire 33%
• Network Use 33%
• State-of-the-art Models 33%
• Abel Transform 33%

Computer Science

• Learning Approach 100%
• Deep Learning Method 100%
• Deep Neural Network 75%
• Domain Knowledge 50%
• Hybrid Approach 50%
• Complex Task 25%
• Sparsity 25%
• Network Architecture 25%
• Training Sample 25%
• Synthetic Aperture 25%
• Research Community 25%
• Frequency Domain 25%
• de-noising 25%
• Reconstruction Accuracy 25%
• Initial Temperature 25%

Physics

• Deep Learning Method 100%
• Neural Network 75%
• Nondestructive Test 25%
• Synthetic Aperture 25%
• Temperature Profile 25%