Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence.

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ID: 37495
2019
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Abstract
We investigated machine learning-based joint banknote recognition and counterfeit detection method. Unlike existing methods, since the proposed method simultaneously recognize banknote type and detect counterfeit detection, it is significantly faster than existing serial banknote recognition and counterfeit detection methods. Furthermore, we propose an explainable artificial intelligence method for visualizing regions that contributed to the recognition and detection. Using the visualization, it is possible to understand the behavior of the trained machine learning system. In experiments using the United State Dollar and the European Union Euro banknotes, the proposed method shows significant improvement in computation time from conventional serial method.
Reference Key
han2019jointsensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Han, Miseon;Kim, Jeongtae;
Journal sensors
Year 2019
DOI
E3607
URL
Keywords
particulate matter health south korea social big-data analysis

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