Banknote recognition Computer Vision Project
Updated 2 years ago
Here are a few use cases for this project:
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Automated Teller Machines (ATMs): The "Banknote recognition" model can be deployed to identify and validate the denominations of banknotes for ATM transactions, which would enhance the accuracy and efficiency of these machines.
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Cash Counter Machines: The model can be used in automated cash counting machines at banks, retail stores, casinos, and other businesses that handle a large amount of physical money to ensure accurate counting and sorting of different banknote classes.
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Anti-Counterfeiting Solutions: The model can be employed as a tool to detect counterfeit banknotes, by comparing the physical characteristics of a note against the features of authentic banknotes it has been trained on.
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Financial Institutions: Human tellers or auditors at banks and other financial institutions could use this model to automate the process of cash handling, thereby reducing human error and increasing productivity.
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Assistive Technologies for Visually Impaired: The computer vision model can be incorporated into mobile applications to help visually impaired individuals identify banknote denominations, providing them greater financial independence.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
banknote-recognition-mdm4g_dataset,
title = { Banknote recognition Dataset },
type = { Open Source Dataset },
author = { FYP },
howpublished = { \url{ https://universe.roboflow.com/fyp-leirw/banknote-recognition-mdm4g } },
url = { https://universe.roboflow.com/fyp-leirw/banknote-recognition-mdm4g },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { dec },
note = { visited on 2024-12-25 },
}