Crack Detection Computer Vision Project

SHM

Updated 4 months ago

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Description

Here are a few use cases for this project:

  1. Infrastructure Maintenance: This model can be used by government bodies or construction firms to monitor public infrastructure such as bridges, roads, or buildings for any signs of hairline cracks, spalling, damage, or delamination. Early detection can ensure timely repair and prevent major accidents.

  2. Aircraft Inspections: Aviation industry can use this model to continuously monitor the aircraft bodies for any external damage. This can help to increase the operational safety and maintenance of aircraft.

  3. Historical Monuments Conservation: For archaeologists and preservationists, this model could be a crucial tool to detect early signs of damage on historical monuments, enabling timely restoration to prolong their lifespan.

  4. Industrial Equipment Monitoring: Crack Detection can be used in factories or power plants to monitor machinery and detect any cracks or damages. This can help in preventive maintenance and avoiding costly system shutdowns.

  5. Pipeline Monitoring: Oil and gas industry can implement this model to monitor pipeline infrastructure. Early damage recognition can help prevent potential leaks or catastrophic failures.

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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{
                            crack-detection-7lgyo_dataset,
                            title = { Crack Detection Dataset },
                            type = { Open Source Dataset },
                            author = { SHM },
                            howpublished = { \url{ https://universe.roboflow.com/shm-v25ds/crack-detection-7lgyo } },
                            url = { https://universe.roboflow.com/shm-v25ds/crack-detection-7lgyo },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { aug },
                            note = { visited on 2024-12-26 },
                            }
                        
                    

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