road_defect Object Detection Dataset and Pre-Trained Model by TUM

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Explore Dataset

Here are a few use cases for this project:

Road Maintenance Prioritization: Municipalities and transportation departments can use the "road_defect" model to prioritize road repair and maintenance by automatically detecting and classifying road cracks and potholes, helping to allocate resources more efficiently.
Infrastructure Monitoring: Civil engineers and infrastructure monitoring companies can use the model to assess the overall health of roads and highways, enabling them to identify and address problematic areas that may lead to more severe issues if left unattended.
Traffic Management: The model can help traffic management agencies identify sections of roads with high defect density, allowing them to create safer detours and alternate routes for motorists to avoid accidents and reduce traffic congestion.
Road Damage Assessment after Natural Disasters: In the aftermath of natural disasters like earthquakes, floods, or hurricanes, the "road_defect" model can expedite damage assessment efforts, enabling faster emergency response and road repair operations to ensure the safety of affected communities.
Insurance Claims Evaluation: Insurance companies can use the "road_defect" model to objectively evaluate and quantify road damage claims, helping them to make more accurate decisions regarding payouts and reducing the time needed to process claims.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            road_defect_dataset,
                            title = { road_defect Dataset },
                            type = { Open Source Dataset },
                            author = { TUM },
                            howpublished = { \url{ https://universe.roboflow.com/tum-z9rop/road_defect } },
                            url = { https://universe.roboflow.com/tum-z9rop/road_defect },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-04-20 },
                            }