Automated Road Damage Detection Using UAV Images and Deep Learing Techniques
Jan 2024 - Apr 2024 (4 months)
For automatically road damage using UAV images and deep learing.Road infrastructure maintenance is crucial for safe transportation but manual data collection is time consuming and hazardous. To address this,we propose a solution the leverages UAVs and AI to enhance detection accurancy and efficiency. Our approach utilizes YOLOv5 and YOLOv7 algorithms for object detection in UAV images,trained and tested with datasets from china and spain results show impressive performance with upto 73.20% accurancy. Potential of UAVS and deep learing in automated road damage detection ,opening avenues for future research.