Framework for Pothole Detection, Quantification, and Maintenance System (PDQMS) for Smart Cities

Development of a Multi-Distress Detection System for Asphalt Pavements: Transfer Learning-Based Approach

“…The presented architecture outperformed a well-recognized CNN in respect of the detection rate, albeit the precision was found to be lower than the CNN-based approach. Recently, the authors also used YOLOv3 and developed a framework architecture that was capable of detecting potholes and quantifying the amount of patching material required for maintenance ( 25 ). The developed severity-based detection algorithm was capable of measuring the extent of distresses, potentially useful for decision making such as pavement maintenance interventions.…”