bill-currency Object Detection Dataset and Pre-Trained Model by cloudstrats

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Explore Dataset

Here are a few use cases for this project:

Financial Institutions: The "bill-currency" model can be utilized to automate the process of money counting in banks, exchange points, and ATMs. It can also help visually verify the authenticity of currency bills and track serial numbers for accountability purposes.
Retail Sector: Stores can use the AI model to quickly and accurately identify various forms of global currency during transactions, ensuring seamless business operations and preventing human-related cash handling errors.
Travel & Tourism: Travel agencies and airport exchange counters can use the model to identify and exchange different types of currency accurately, improving customer satisfaction and operational efficiency.
Education: The model can be used in educational institutions to provide practical training to students in finance and economics courses, teaching them about different types of global currency, their features, and their value.
Law Enforcement: The system could help authorities in forensic departments to identify counterfeits during investigations, thus preventing currency fraud.

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{
                            bill-currency_dataset,
                            title = { bill-currency Dataset },
                            type = { Open Source Dataset },
                            author = { cloudstrats },
                            howpublished = { \url{ https://universe.roboflow.com/cloudstrats-erog9/bill-currency } },
                            url = { https://universe.roboflow.com/cloudstrats-erog9/bill-currency },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-25 },
                            }