more labelling Computer Vision Project

Tanmoy

Updated 2 years ago

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Classes (9)
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crack
discoloration
exposed bricks
spalling
Description

Here are a few use cases for this project:

  1. Building Inspection and Maintenance: This model can be used by construction companies or property managers to assess the current condition of buildings, and promptly identify and categorize defects.

  2. Historic Preservation: Conservationist organizations or architects specialized in restoring historical structures can utilize the model to identify areas of concern such as cracks or discoloration, which might signify structural issues.

  3. Real Estate Evaluations: Real estate agents could use this technology to provide potential buyers with detailed information about the condition of a property, adding to the depth and reliability of their assessments.

  4. Insurance Claims: Insurance companies could apply the model to evaluate claims related to property damages. By identifying and categorizing defects, they can more accurately estimate the cost of repairs.

  5. Training Construction Workers: This model can also serve as an educational tool for training those in the construction industry to identify and understand different types of structural defects.

Supervision

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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{
                            more-labelling_dataset,
                            title = { more labelling Dataset },
                            type = { Open Source Dataset },
                            author = { Tanmoy },
                            howpublished = { \url{ https://universe.roboflow.com/tanmoy-l4qts/more-labelling } },
                            url = { https://universe.roboflow.com/tanmoy-l4qts/more-labelling },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-09-26 },
                            }
                        
                    

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