My road crack dataset Computer Vision Project

NewRoadCrack

Updated 2 years ago

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Classes (4)
Crocodile
Longitudinal
Pothole
Transverse
Description

Here are a few use cases for this project:

  1. Infrastructure Maintenance: This computer vision model can help local government agencies, transportation departments, and infrastructure management companies identify road damage, prioritize repair work, and optimize maintenance schedules based on the types and severity of road cracks detected.

  2. Road Safety Improvement: Using the model to identify and monitor road crack classes in real-time, traffic management centers can provide drivers with up-to-date information on road conditions, helping them avoid hazardous routes, reducing accidents, and enhancing overall road safety.

  3. Autonomous Vehicle Navigation: Integration of the model into the systems of autonomous vehicles can enable them to detect and avoid road cracks or potholes, ensuring a smooth and safe driving experience for passengers.

  4. Road Quality Assessment: Urban planning and infrastructure development agencies can use this model to assess the quality of existing roads in various locations, helping prioritize funding and allocation of resources for road construction and repair projects.

  5. Insurance Claim Analysis: Insurance companies can leverage the model to assess road conditions at the time of accidents, which can aid in determining liability and evaluating the legitimacy of insurance claims related to road damages.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            my-road-crack-dataset_dataset,
                            title = { My road crack dataset Dataset },
                            type = { Open Source Dataset },
                            author = { NewRoadCrack },
                            howpublished = { \url{ https://universe.roboflow.com/newroadcrack/my-road-crack-dataset } },
                            url = { https://universe.roboflow.com/newroadcrack/my-road-crack-dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-12-03 },
                            }