PLM_marcius Computer Vision Project

PLMmarcius

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Description

Here are a few use cases for this project:

  1. Quality Assurance in Manufacturing: The PLM_marcius model could be used for screening parts or products on a manufacturing assembly line. The model could identify if any essential components or classes are missing from the product, like missing screws or specific parts in electronic devices.

  2. Packaging Inspection in Retail: This model could be used in retail for packaging verification, examining whether packages have all necessary components, such as handles, barcodes, or product labels.

  3. Educational Tools: The PLM_marcius model could be used for creating interactive educational tools or games, where students have to identify what's missing in a series of images, enhancing their learning experience while also teaching them about different objects.

  4. Traffic Monitoring System: The model could be applied to analyze traffic surveillance footage for missing classes such as traffic signs or signals. This can help authorities resolve issues or hazards more efficiently.

  5. Archaeology & Art Restoration: The model could be useful in identifying missing elements in archaeological finds or in artworks, helping guide restoration efforts.

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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{
                            plm_marcius_dataset,
                            title = { PLM_marcius Dataset },
                            type = { Open Source Dataset },
                            author = { PLMmarcius },
                            howpublished = { \url{ https://universe.roboflow.com/plmmarcius/plm_marcius } },
                            url = { https://universe.roboflow.com/plmmarcius/plm_marcius },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-09-28 },
                            }
                        
                    

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