Jordan Banners Object Detection Dataset and Pre-Trained Model by Princess Sumaya University for Technology

Images

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Explore Dataset

Here are a few use cases for this project:

Traffic Monitoring Systems: The "Jordan Banners" model can be used to monitor and analyze traffic patterns based on the identification of road signs, especially in areas where Arabic is predominantly spoken. The system could detect specific sign categories, traffic updates or alert drivers about upcoming road conditions or changes ahead.
Autonomous Vehicles Navigation: In the realm of self-driving cars, this computer vision model can help vehicles recognize and understand road signs, thereby facilitating effective navigation and ensuring safety on the road, particularly in regions where the banners or signs are in Arabic.
Augmented Reality Applications: For tourists or foreigners in Arabic-speaking regions, the model could power AR applications to translate Arabic banners in real-time into the user's native language, enhancing their navigation experience.
Cultural Heritage and Historical Studies: Researchers studying historical or cultural sites can use this model to identify and understand the importance of various banners in Arabic and their significance. It could also assist in digital preservation of these sites.
Public and Urban Planning: City planners and public workers can use the model to assess the clarity, visibility and positioning of the banners or signs for better urban development planning.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            jordan-banners_dataset,
                            title = { Jordan Banners Dataset },
                            type = { Open Source Dataset },
                            author = { Princess Sumaya University for Technology },
                            howpublished = { \url{ https://universe.roboflow.com/princess-sumaya-university-for-technology-jizje/jordan-banners } },
                            url = { https://universe.roboflow.com/princess-sumaya-university-for-technology-jizje/jordan-banners },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-06-18 },
                            }