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Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence

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 cou...

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Detalles Bibliográficos
Autores principales: Han, Miseon, Kim, Jeongtae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719953/
https://www.ncbi.nlm.nih.gov/pubmed/31430971
http://dx.doi.org/10.3390/s19163607
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author Han, Miseon
Kim, Jeongtae
author_facet Han, Miseon
Kim, Jeongtae
author_sort Han, Miseon
collection PubMed
description 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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spelling pubmed-67199532019-09-10 Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence Han, Miseon Kim, Jeongtae Sensors (Basel) Article 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. MDPI 2019-08-19 /pmc/articles/PMC6719953/ /pubmed/31430971 http://dx.doi.org/10.3390/s19163607 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Han, Miseon
Kim, Jeongtae
Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
title Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
title_full Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
title_fullStr Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
title_full_unstemmed Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
title_short Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
title_sort joint banknote recognition and counterfeit detection using explainable artificial intelligence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719953/
https://www.ncbi.nlm.nih.gov/pubmed/31430971
http://dx.doi.org/10.3390/s19163607
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