Research on Pavement Distress Detection in UAV Images Based on Deep Learning

With the rapid development of road transportation, pavement damage detection becomes very important. In this study, a pavement damage detection method based on UAV images is proposed, using an improved YOLOv5 algorithm, combined with Local window attention, to improve the accuracy and efficiency of detection. The experimental results show that compared with the original YOLOv5, the improved model has a 7.8%increase in the mean accuracy (mAP), which proves its effectiveness in pavement damage detection.