Real-Time Potholes Detection and Prevention Using Deep Learning Techniques
摘要
Road infrastructure safety and maintenance have received more attention recently due to the significant influence that it has on traffic flow and road user safety. Potholes are one common kind of road defect that seriously endangers drivers. Manual checks take a lot of time and may delay necessary repairs. In response to these challenges, a real-time pothole recognition system utilizing state-of-the-art computer vision and deep learning techniques was developed. The system leverages the Faster R-CNN model for precise pothole identification, enabling fast detection and timely repairs. The automated detection and instantaneous notification of authorities by the system enhances road safety and maintenance efficiency. This ingenious tactic improves the standard of the transportation network and creates roads safer.