Advanced Crack Detection in Building Structures Using Pix2Pix and U-Net Architectures
Emmanuella Ogun et al.
Traditional crack detection methods, including manual inspection and classical computer vision techniques, often suffer from inconsistencies due to variations in lighting, surface texture, and environmental noise, resulting in unreliable and inefficient evaluations for large-scale inspections. This study presents a deep learning-based crack detection system designed to enhance segmentation accuracy and structural coherence in building inspections. The approach integrates a Pix2Pix conditional GA