Detection and Classification of Potholes using CNN

Potholes on roads are a common problem that leads to accidents and damage to vehicles. Detecting potholes using computer vision techniques can help address this issue. In this paper, we propose a method for pothole detection using Convolutional Neural Networks. We train a CNN model on a dataset of road images, with labeled pothole and non-pothole regions. The trained algorithms, specifically ResNetV2, ResNet50, VGG19, and YOLOv8, for the task of pothole detection and capable of accurately classifying different regions in road images as either pothole or non-pothole areas.