LP Reader Object Detection Dataset and Pre-Trained Model by ELM

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Explore Dataset

Here are a few use cases for this project:

Automatic License Plate Recognition: The LP Reader model can be used in security and law enforcement applications to automatically recognize and identify license plates. By comparing this information with a database, it can aid in vehicle tracking or locating stolen vehicles.
Parking Management Systems: This system can assist in the automation of parking facilities by recognizing and logging license plates as cars enter and exit, without requiring physical tickets or human intervention.
Traffic regulation and enforcement: By identifying vehicle license plates, the model could be used in traffic control systems to detect vehicles that have violated traffic rules such as speeding, illegal parking, or running red lights.
Toll Collection: Automatic identification of license plates could be used in a toll collection system, eliminating the need for manual labor and speeding up the process.
Enhanced CCTV systems: Integrating this model within CCTV systems can provide additional functionality, like tracking specific vehicles based on their license plates in situations like shopping malls or private property surveillance.

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{
                            lp-reader_dataset,
                            title = { LP Reader Dataset },
                            type = { Open Source Dataset },
                            author = { ELM },
                            howpublished = { \url{ https://universe.roboflow.com/elm/lp-reader } },
                            url = { https://universe.roboflow.com/elm/lp-reader },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-05-11 },
                            }