Road Damage Detection

Developed a computer vision pipeline integrating camera input and YOLOv8 inference to detect road cracks and

potholes, achieving 95% detection precision.

Implemented an automated damage scoring algorithm using a 0–100 severity index and Bash automation to reduce

manual setup overhead by 90%.

Applied machine learning and deep learning concepts to a real-world perception and classification problem.