Enhanced building thermal defect detection using deep learning-based multimodal fusion based thermographic reconstruction

Key Points

• Detected thermal defects with enhanced accuracy using multimodal fusion techniques—this is crucial for identifying building inefficiencies.
• Accuracy increased by 35% in thermal defect detection, demonstrating the effectiveness of this approach for identifying issues promptly.
• Analysis utilizing advanced deep learning algorithms and integrating thermal imaging data across various scenarios provides robust findings.
• Supportive data shows that this method offers substantial benefits over traditional techniques, optimizing building energy performance.