sign Computer Vision Project

new-workspace-muc97

Updated 2 years ago

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Classes (10)
Arabic
Danger
Directional
Latin
Number
Priority
Prohibitory
Regularity
Temporary
panel_guide
Description

Here are a few use cases for this project:

  1. Navigation and Map Services: The "sign" model can enhance GPS mapping services by capturing and interpreting various signs. The model could provide real-time updates on traffic guidance, danger zones, temporary constructions and other related issues that could aid in a smoother navigation experience.

  2. Autonomous Vehicles: This computer vision model can be implemented in self-driving vehicles for them to understand and follow traffic rules, such as understanding priority rights, prohibitory signs, or directional hints. It's also significant for recognizing number signs indicating speed limits or identifying potential danger signs.

  3. Assistive Technology for the Visually Impaired: The "sign" model could be utilized in creating an assistive device for visually impaired individuals, which can identify and narrate the signs in the environment, hence aiding them in navigation or understanding their surroundings.

  4. Education and Learning Platforms: The model can be used in educational platforms for teaching languages. As it includes Arabic and Latin classes, it can help learners get familiar with these languages in real-world contexts.

  5. Traffic Management and Control Systems: The model provides valuable insights for traffic management systems by identifying regularity, priority, and prohibitory signs. Based on this data, traffic flow can be optimized and it can assist in planning adjustments or improvements to traffic signs and rules.

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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{
                            sign-qrurb_dataset,
                            title = { sign Dataset },
                            type = { Open Source Dataset },
                            author = { new-workspace-muc97 },
                            howpublished = { \url{ https://universe.roboflow.com/new-workspace-muc97/sign-qrurb } },
                            url = { https://universe.roboflow.com/new-workspace-muc97/sign-qrurb },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-09-26 },
                            }
                        
                    

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