concrete Computer Vision Project
Updated a year ago
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Metrics
Here are a few use cases for this project:
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Infrastructure Health Assessment: This model could help identify signs of infrastructure degradation in civil structures such as bridges, tunnels, buildings, etc., thus aiding in routine checks and early detection of potentially dangerous conditions. The model could alert engineers about issues like cracks, exposed bars, water stains, etc.
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Construction Quality Control: The "concrete" model can be used as a tool to monitor and ensure the quality of construction activities. It could identify whether the construction process is causing unwanted defects like cracks, steel-joint issues, fall-block etc, which might lead to an overall reduction in the quality of the constructed structure.
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Maintenance Planning: Facilities management teams can use this model to plan their repair and maintenance schedules more efficiently by identifying areas of concern like repairs, water stains, and cracks in the concrete structure. This would save cost and time by targeting specific problem areas.
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Insurance Claims Processing: Insurers can use this model to validate claims related to structural damage. The model can help assess the extent and nature of the damage by identifying cracks, exposed bars, or any other issue present in the concrete structure.
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Archaeological Structures Study: Archaeologists can use this model to study ancient structures and infrastructures as it could highlight aspects of these structures that hint towards construction methods, damages, restorations, or changes made over time. The “concrete” model could identify seams, cracks, repairs, or other discrete classes.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
concrete-m2ves_dataset,
title = { concrete Dataset },
type = { Open Source Dataset },
author = { crt },
howpublished = { \url{ https://universe.roboflow.com/crt-uxkd7/concrete-m2ves } },
url = { https://universe.roboflow.com/crt-uxkd7/concrete-m2ves },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-11-21 },
}