Pavement Crack

Pavement crack detection is crucial for maintaining road infrastructure, and recent research focuses on automating this process using deep learning. Current efforts center on improving the accuracy and robustness of crack segmentation algorithms, employing architectures like encoder-decoder networks, YOLO, and GANs, often incorporating techniques such as multi-modal image fusion (RGB and thermal) and attention mechanisms to enhance performance under diverse conditions. These advancements offer significant potential for reducing the cost and time associated with manual inspection, leading to more efficient and proactive road maintenance strategies.