A computer Vision project for avoiding potholes on road.

The pilot vehicle rounds the city daily and sends the pothole coordinates to the cloud. The app will display the pothole and if the user is near the pothole, the user will be alerted

Поиск выбоин на дорогах с использованием YOLOv8 Nano

Pothole Detection using Faster-RCNN and YOLO v3

A pothole detection DL algorithm using Yolo v2 and Tensorflow

1200-Videos-Potholed-Road-Collection-Data

Street Quality Mapper - A web app that consists of a complete map of the street quality surface of a city and gives a bird's eye view of the roads, enabling the administrator to keep an eye on the state of roads in real time and take informed decisions to improve the road condition.

The pilot vehicle rounds the city daily and sends the pothole coordinates to the cloud. The app will display the pothole and if the user is near the pothole, the user will be alerted.

Pothole Detection Using Transfer Learning Models: A Comparative Study

A beginner level prediction models for data science and computer vision

An intelligent Pothole Detection system using YOLOv4 Tiny, capable of identifying and categorizing potholes . The severity level of each pothole (Low, Medium, High) is assessed based on its area in the frame. This system provides a valuable tool for monitoring road conditions and prioritizing maintenance efforts.

An intelligent Pothole Detection system using YOLOv4 Tiny, capable of identifying and categorizing potholes . The severity level of each pothole (Low, Medium, High) is assessed based on its area in the frame. This system provides a valuable tool for monitoring road conditions and prioritizing maintenance efforts.

Eye on the Asphalt (Hackathon winning project) automates pothole detection using video data from public buses. Developed for the Google Cloud Day '24 Lisbon Hackathon, this AI-powered system processes real-time footage to identify and report road issues, improving urban road maintenance and sustainability. Recognized as the Hackathon winner!

A road condition checking system with Arduino and Machine Learning.

The goal of this project is to develop a robust and scalable solution that can automatically identify and classify potholes in real-time using image and video data from various sources, such as dashcams, traffic cameras, or drones.

Pothole Detection and mapping using YoloV4, done for S6 Mini project

Pothole Detection using Ultralytics YOLOv8. Topics

Pothole detection using python OpenCV on GUI based Console

Build a computer vision-based technology to process and detect the potholes present in an image.

This is a pothole detection detection system created using Image Classification by Convolutional Neural Networks.