add one Object Detection Dataset and Pre-Trained Model by aag

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Explore Dataset

Here are a few use cases for this project:

Traffic Management Systems: The "add one" model can assist in recognizing and interpreting traffic signboards for automated systems, aiding in predictive traffic flow adjustments, traffic rule adherence, and security enforcement around city streets or highways.
Autonomous Vehicles: Utilization in self-driving cars or semi-automated vehicles to identify different signboards on the route, thereby helping the vehicle's system to make safe and accurate road decisions.
Virtual Reality Driving Simulations: The model could be used in a virtual reality (VR) driving simulation for better recognition and interpretation of in-game signboards, enhancing the realism and interactive experience for users.
City Planning: Urban planners could utilize the model to identify and catalogue signboards across the city, helping create more structured and accessible maps.
Tourism and Navigation Applications: This model could be beneficial in GPS and travel apps to more accurately recognize signboards for places of interest, assisting tourists and travelers in navigation.

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{
                            add-one_dataset,
                            title = { add one Dataset },
                            type = { Open Source Dataset },
                            author = { aag },
                            howpublished = { \url{ https://universe.roboflow.com/aag/add-one } },
                            url = { https://universe.roboflow.com/aag/add-one },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-06-28 },
                            }