511 dataset yolo Computer Vision Project
Updated 2 years ago
50
2
Metrics
Here are a few use cases for this project:
-
Road Maintenance and Infrastructure Improvement: Governmental bodies dealing with infrastructure can use this model to detect potholes and schedule their repair.
-
Autonomous Driving Systems: Self-driving car manufacturers may use this dataset for training their systems to recognize potholes and navigate more effectively avoiding any potential damage.
-
Mapping app enhancements: This model can be used to improve navigation and mapping applications by providing real-time information about potholes, enabling rerouting for a smoother driving experience.
-
Insurance Claim Automation: Insurance companies can use this model to automate processing claims related to vehicle damage due to potholes, by having concrete evidential proof that the damage was caused by the pothole.
-
Aid in Traffic Management Systems: Traffic management bodies can utilize this model to detect areas with a high occurrence of potholes, making it possible to redirect traffic to alternative routes to enhance safety and manage congestion.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
511-dataset-yolo_dataset,
title = { 511 dataset yolo Dataset },
type = { Open Source Dataset },
author = { YOLOv5 pothole },
howpublished = { \url{ https://universe.roboflow.com/yolov5-pothole/511-dataset-yolo } },
url = { https://universe.roboflow.com/yolov5-pothole/511-dataset-yolo },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { feb },
note = { visited on 2024-11-08 },
}