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Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence.
Han, Miseon; Kim, Jeongtae.
  • Han M; Department of Electronics and Electrical Engineering, Ewha Womans University, Seoul 03760, Korea.
  • Kim J; Department of Electronics and Electrical Engineering, Ewha Womans University, Seoul 03760, Korea. jtkim@ewha.ac.kr.
Sensors (Basel) ; 19(16)2019 Aug 19.
Article en En | MEDLINE | ID: mdl-31430971
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.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2019 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2019 Tipo del documento: Article