Puzzlebot_Signals Object Detection Dataset and Pre-Trained Model by puzzlebot

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Here are a few use cases for this project:

Autonomous Vehicle Navigation: The Puzzlebot_Signals model can be integrated into the visual systems of self-driving cars, allowing them to recognize and respond to different traffic signals, resulting in safe and efficient navigation.
Traffic Monitoring Systems: The model can be used in advanced traffic control systems to identify different types of signs and monitor compliance, thus helping in traffic management and reducing accidents.
Augmented Reality Navigation Apps: This model can be utilized in AR-based navigation applications where real-time signage recognition can enhance the user's directional indication and safety alerts.
Driver Assistance Systems: The model can be implemented in advanced driver-assistance systems (ADAS) to help drivers by alerting them about their immediate surroundings like a warning for construction ahead, or indicating need to stop etc.
Road Maintenance and Planning: Government or road maintenance agencies can use this model to digitally map out and track the condition and presence of different road signs, aiding in targeted maintenance and planning of road signage.

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{ puzzlebot_signals_dataset,
    title = { Puzzlebot_Signals Dataset },
    type = { Open Source Dataset },
    author = { puzzlebot },
    howpublished = { \url{ https://universe.roboflow.com/puzzlebot-kspwi/puzzlebot_signals } },
    url = { https://universe.roboflow.com/puzzlebot-kspwi/puzzlebot_signals },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { jun },
    note = { visited on 2023-12-06 },
}