Counterfeit Currency Recognition Using Deep Learning: A Review

Sabat Muhamad and Twana Ahmed
Additional contact information
Sabat Muhamad: Computer Science Department, Faculty of Science, Soran University
Twana Ahmed: Horticulture and Landscape design Department, Bakrajo Technical institute, Sulaimani Polytechnic University

Technium, 2021, vol. 3, issue 7, 14-26

Abstract: This review article reviews some previous work in the literature about using deep learning techniques for recognizing fake notes from the real notes. A human-visual system can be utilized for identifying and confirming currency-notes. Yet, our eyesight cannot sense everything, and it is frequently hard for humans to recognize genuine currency without using technology assistance. Deep learning methods have been revealed to be more efficient for numerous applications. Consequently, deep learning has been used to enhance currency recognition accuracy. The methods that are used including Classic neural networks, CNN, and GANs for recognizing fake notes.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://techniumscience.com/index.php/technium/article/view/4178 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tec:techni:ojs:4178

Access Statistics for this article

Technium is currently edited by Scurtu Ionut Cristian

More articles in Technium from Technium Science
Bibliographic data for series maintained by Ana Maria Golita ().