Machine learning-based authentication of banknotes: a comprehensive analysis
This research investigates the utilization of machine learning techniques for the identification and classification of counterfeit currency. The study utilizes a dataset consisting of authentic and counterfeit banknotes, employing various classification algorithms to construct a robust model for aut...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
REA Press
2024-03-01
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| Series: | Big Data and Computing Visions |
| Subjects: | |
| Online Access: | https://www.bidacv.com/article_197120_03eff6036b03cdd0d0b1fa6d97326e74.pdf |
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| Summary: | This research investigates the utilization of machine learning techniques for the identification and classification of counterfeit currency. The study utilizes a dataset consisting of authentic and counterfeit banknotes, employing various classification algorithms to construct a robust model for automated detection. Key features, including texture, color distribution, and security attributes, are extracted to train the model, enabling a thorough analysis of banknote authenticity. The proposed system exhibits promising accuracy in distinguishing genuine currency from counterfeits, thereby enhancing security measures in financial transactions and mitigating economic fraud. |
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| ISSN: | 2783-4956 2821-014X |