NEU_Original_Split Computer Vision Project

NSIT

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Description

Here are a few use cases for this project:

  1. Industrial Quality Control: The model could be used in manufacturing industries to automate quality control processes. By identifying defects such as inclusion, patches, crazing, rolled-in scale, scratches, pitted surface on products or machinery, it can help prevent the distribution of defected goods or predict the need for machine maintenance.

  2. Automobile Industry: The model could be useful for car inspections. Used in car manufacturing or repair shops, it can identify and classify damages to the car body or components, speeding up the estimation and repair process.

  3. Antique Restoration and Art Conservation: The model can help conservators detect defects or damages, such as crazing and scratches, on antique items or old paintings, aiding in the restoration process by determining what type of restoration methods to use.

  4. Construction Industry: The model can be used to inspect building materials for any defects or damages that may affect the structural integrity of buildings, ensuring safety standards are met.

  5. Consumer Electronics: The computer vision model could be used in electronics manufacturing, helping to identify defects on devices' surfaces or screens. Such proactive identification could improve the quality of the produced items and minimize customer complaints and returns.

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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{
                            neu_original_split-pa5lh_dataset,
                            title = { NEU_Original_Split Dataset },
                            type = { Open Source Dataset },
                            author = { NSIT },
                            howpublished = { \url{ https://universe.roboflow.com/nsit/neu_original_split-pa5lh } },
                            url = { https://universe.roboflow.com/nsit/neu_original_split-pa5lh },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { nov },
                            note = { visited on 2024-11-18 },
                            }
                        
                    

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