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- Title
The Detection of Counterfeit Banknotes Using Ensemble Learning Techniques of AdaBoost and Voting.
- Authors
Khairy, Rihab Salah; Hussein, Ameer Saleh; Salim ALRikabi, Haider TH.
- Abstract
The movement of cash flow transactions by either electronic channels or physically created openings for the influx of counterfeit banknotes in financial markets. Aided by global economic integration and expanding international trade, attention must be geared at robust techniques for the recognition and detection of counterfeit banknotes. This paper presents ensemble learning algorithms for banknotes detection. The AdaBoost and voting ensemble are deployed in combination with machine learning algorithms. Improved detection accuracies are produced by the ensemble methods. Simulation results certify that the ensemble models of AdaBoost and voting provided accuracies of up to 100% for counterfeit banknotes.
- Subjects
BANK notes; INTERNATIONAL economic integration; FORGERY; CASH transactions; VOTING
- Publication
International Journal of Intelligent Engineering & Systems, 2021, Vol 14, Issue 1, p326
- ISSN
2185-310X
- Publication type
Article
- DOI
10.22266/ijies2021.0228.31