Road Inspection

Road inspection, crucial for maintaining infrastructure safety and efficiency, is undergoing a rapid transformation driven by advancements in artificial intelligence and computer vision. Current research focuses on automating the detection and classification of road defects using various imaging techniques (e.g., LiDAR, cameras) and deep learning models, including convolutional neural networks and transformers, often incorporating techniques like domain generalization and anomaly detection to improve robustness and reduce reliance on extensive labeled datasets. This automation promises significant improvements in inspection speed, accuracy, and cost-effectiveness, leading to safer roads and more efficient resource allocation for maintenance.