Automated Pothole Detection with Convolutional Neural Networks

The presence of potholes on roads is a major contributor to road accidents and vehicle damage. The increase in traffic and pollution has led to a proliferation of potholes in nearly every city. This study presents a method for classifying road potholes using Convolutional Neural Networks (CNN) with TensorFlow and Keras. The proposed system utilizes CNNs to identify potholes from road images. By incorporating additional feature extraction techniques, the accuracy of pothole detection is expected to improve. This research highlights the effectiveness of deep CNNs in identifying potholes, with the aim of eventually deploying the model using the Django framework.