plates detection Object Detection Dataset and Pre-Trained Model by Yael Marom

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Explore Dataset

Here are a few use cases for this project:

Traffic Enforcement: The "plates detection" model can be used to automatically detect and identify license plates of vehicles that violate traffic rules such as speeding, illegal parking, or running red lights. This information can be used by law enforcement to issue tickets and fines.
Parking Management: The model can be integrated into parking systems to automatically recognize license plates, allowing for efficient management of parking lots, tracking of vehicle usage, and automated billing for paid parking spaces.
Stolen Vehicle Recovery: The "plates detection" model can be employed in surveillance systems and traffic cameras to identify stolen vehicles by matching license plates against a database of reported stolen vehicles, thereby aiding law enforcement in vehicle recovery.
Access Control: The model can be utilized in restricted access areas, such as gated communities or company premises, to automatically grant or deny access to vehicles based on the license plate recognition.
Congestion Charging: The "plates detection" system can be implemented in cities with congestion charging schemes to identify vehicles entering and leaving congestion zones, enabling automated charging for road usage and supporting traffic reduction initiatives.

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{ plates-detection_dataset,
    title = { plates detection Dataset },
    type = { Open Source Dataset },
    author = { Yael Marom },
    howpublished = { \url{ https://universe.roboflow.com/yael-marom-s2mbp/plates-detection } },
    url = { https://universe.roboflow.com/yael-marom-s2mbp/plates-detection },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { feb },
    note = { visited on 2023-12-01 },
}