Name: bridge crack Dataset
License: https://creativecommons.org/publicdomain/zero/1.0/

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Explore Dataset

Here are a few use cases for this project:

Infrastructure Maintenance: Government bodies or infrastructure companies can use this model to conduct regular check-ups of bridges. It can help detect cracks in a timely manner, thereby helping to prevent accidents and maintain the integrity of the bridges.
Construction Quality Assurance: Construction companies can utilize this model during various project phases to ensure the quality of their work. It can be particularly useful in detecting any cracks that appear during or shortly after construction, ensuring that they are promptly addressed.
Remote Inspection Systems: Companies that provide drone-based surveys or inspections can integrate this model into their system for conducting comprehensive bridge inspections, helping to reduce human risk involved in such inspections and increase efficiency.
Insurance Claims Investigations: Insurance companies may use this model to investigate claims related to damaged infrastructure. By detecting and evaluating the severity of bridge cracks, they can more accurately estimate repair costs and verify the claims' validity.
Research and Development: Institutions that conduct research in civil engineering can use this model to study the behavior of different materials under strain, effects of environmental factors on infrastructure, or for developing more durable construction materials.

Cite This Project

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

@misc{
                            bridge-crack-ee7ns_dataset,
                            title = { bridge crack Dataset },
                            type = { Open Source Dataset },
                            author = { HWKWAK },
                            howpublished = { \url{ https://universe.roboflow.com/hwkwak-fngrb/bridge-crack-ee7ns } },
                            url = { https://universe.roboflow.com/hwkwak-fngrb/bridge-crack-ee7ns },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-06-09 },
                            }