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• W2617603463 abstract "The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use." @default.
• W2617603463 created "2017-06-05" @default.
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• W2617603463 date "2017-07-01" @default.
• W2617603463 modified "2023-09-26" @default.
• W2617603463 title "The State-of-the-Art Technology of Currency Identification" @default.
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• W2617603463 doi "https://doi.org/10.4018/ijdcf.2017070106" @default.
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