crackme Computer Vision Project

paru

Updated a year ago

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Description

Here are a few use cases for this project:

  1. Infrastructure Inspection: "crackme" could be used by civil engineers to automatically detect and classify cracks in infrastructure such as bridges, roads, or buildings, improving the efficiency and effectiveness of safety inspections.

  2. Aerospace Industry: This model can be used in the aerospace industry to identify potential structural issues in aircraft. Early detection of cracks can prevent catastrophic failures and increase the lifespan of aircraft components.

  3. Manufacturing Quality Control: Manufacturers of various goods, from electronics to automobiles, could use "crackme" to identify cracks in materials or finished products during quality assurance processes.

  4. Geological Studies: "crackme" could assist geologists in identifying and categorizing different types of cracks in rock formations or soil layers, providing valuable data for understanding geological processes or assessing potential risks in certain areas.

  5. Medical Imaging: The model may also find uses in the medical field where it could be trained to identify certain types of cracks in bone in x-ray, CT, or MRI images, aiding in the diagnosis of fractures or other bone conditions.

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{
                            crackme_dataset,
                            title = { crackme Dataset },
                            type = { Open Source Dataset },
                            author = { paru },
                            howpublished = { \url{ https://universe.roboflow.com/paru-o8jua/crackme } },
                            url = { https://universe.roboflow.com/paru-o8jua/crackme },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-09-27 },
                            }