Screenshots Computer Vision Project

Niklas Nielsen

Updated 2 years ago

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Classes (3)
logo_attribution
logos
testimonials

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Description

Here are a few use cases for this project:

  1. Brand Monitoring: This model can be used to monitor online brand presence and unauthorized usage of logos across different websites. By tracking the occurrences of a specific company logo, organizations can ensure compliance with copyright regulations.

  2. Testimonial Validation: Content-based platforms can utilize this model to validate testimonials, ensuring that the logo of the endorsed brand correctly matches with the content. It can also be used in the analysis of success stories in marketing research.

  3. Online Advertising Analysis: The 'Screenshots' model can be effective in the analysis of ad campaigns to identify logos or testimonial placements within online advertisements. This can assist in competitive analysis and strategic marketing decisions.

  4. Web Design Quality Control: Web developers and designers can use this model to automatically inspect sites for correct logo placement and attribution, ensuring brand guidelines are upheld.

  5. Content Verification in Educational Portals: Portals that host educational content from various brands could harness this model to verify correct logo attribution, ensuring the content is appropriately identified and credited to its originating institution.

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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{
                            screenshots-pmqjy_dataset,
                            title = { Screenshots Dataset },
                            type = { Open Source Dataset },
                            author = { Niklas Nielsen },
                            howpublished = { \url{ https://universe.roboflow.com/niklas-nielsen-ninuj/screenshots-pmqjy } },
                            url = { https://universe.roboflow.com/niklas-nielsen-ninuj/screenshots-pmqjy },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { nov },
                            note = { visited on 2024-11-24 },
                            }