pounds detection Object Detection Dataset and Pre-Trained Model by pounds yoloV5

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Explore Dataset

Here are a few use cases for this project:

Automated Currency Sorting: The model could be leveraged in banks or financial institutions for sorting currencies into their appropriate classes, thus increasing efficiency and reducing manual labor.
Transactional Applications: The model can be used in grocery stores or other businesses that frequently handle cash transactions. The automatic detection system could increase speed and reduce the chance of human error in counting money.
Travel Apps: The model can be integrated into travel apps to help tourists visiting the UK in real-time currency identification, thus aiding in lessening confusion and potential financial loss due to currency misidentification.
Educational Use: The model can be utilized in educational platforms teaching about different world currencies, providing a visual reference for different values of pounds.
Anti-Counterfeiting Efforts: Law enforcement or banking institutions could use this model to identify counterfeit bills based on the pattern of legitimate currency. For example, if a detected value doesn't match the physical appearance of the bill, it could be flagged as potentially counterfeit.

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{
                            pounds-detection_dataset,
                            title = { pounds detection Dataset },
                            type = { Open Source Dataset },
                            author = { pounds yoloV5 },
                            howpublished = { \url{ https://universe.roboflow.com/pounds-yolov5-3on8g/pounds-detection } },
                            url = { https://universe.roboflow.com/pounds-yolov5-3on8g/pounds-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-06-18 },
                            }