Trademark Computer Vision Project

SSS

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Description

Here are a few use cases for this project:

  1. Intellectual Property Protection: Utilize the "Trademark" model to detect potential trademark or copyright infringements by automatically identifying and flagging similar images or logos used by other businesses or individuals within a given platform or marketplace.

  2. Brand Recognition and Analysis: Employ the model to analyze marketing and social media content by detecting branded materials (text or images) to monitor brand exposure, campaign engagement, and unauthorized use in various media streams.

  3. Product Comparison and Market Research: Use the "Trademark" model to identify competitor products and compare them based on the visuals and text, offering useful insights for new product development and design improvements.

  4. Document Analysis and Redaction: Apply the model to identify sensitive information (such as trademarks or company logos) on documents for secure redaction purposes, ensuring compliance with privacy regulations and confidentiality agreements.

  5. Counterfeit Detection for E-commerce Platforms: Use the model to identify and flag counterfeit or unauthorized sales of trademarked products on e-commerce platforms, protecting the interests of brand owners and ensuring customer trust in the platform.

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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{
                            trademark_dataset,
                            title = { Trademark Dataset },
                            type = { Open Source Dataset },
                            author = { SSS },
                            howpublished = { \url{ https://universe.roboflow.com/sss-ezrvx/trademark } },
                            url = { https://universe.roboflow.com/sss-ezrvx/trademark },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-12-26 },
                            }
                        
                    

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