Automated Detection and Severity Assessment of Asphalt Pavement Distress Using YOLOv8: A Deep Learning Approach

Ravi Kumar; Smita Tung

doi:10.1007/s42947-025-00584-7

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JOURNAL ARTICLE

Automated Detection and Severity Assessment of Asphalt Pavement Distress Using YOLOv8: A Deep Learning Approach

Ravi Kumar Smita Tung

Year: 2025 Journal: International Journal of Pavement Research and Technology Publisher: Springer Science+Business Media

DOI: 10.1007/s42947-025-00584-7

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Keywords:

Asphalt pavement Asphalt Distress Forensic engineering Engineering Materials science Artificial intelligence Computer science Psychology Composite material Clinical psychology

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Topics

Infrastructure Maintenance and Monitoring

Physical Sciences → Engineering → Civil and Structural Engineering

Asphalt Pavement Performance Evaluation

Physical Sciences → Engineering → Civil and Structural Engineering

Non-Destructive Testing Techniques

Physical Sciences → Engineering → Mechanical Engineering

Automated Detection and Severity Assessment of Asphalt Pavement Distress Using YOLOv8: A Deep Learning Approach

Metrics

Citation History

Topics

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