Real-time Yemeni Currency Detection
Edrees AL-Edreesi, Ghaleb Al-Gaphari

TL;DR
This paper introduces a real-time mobile application utilizing deep learning to assist visually impaired individuals in recognizing Yemeni banknotes, enhancing their independence in daily transactions.
Contribution
It presents a novel deep learning-based system specifically designed for Yemeni currency recognition, deployed on mobile devices for real-time assistance.
Findings
High accuracy in Yemeni banknote recognition
Effective real-time performance on mobile devices
Significant aid for visually impaired users
Abstract
Banknote recognition is a major problem faced by visually Challenged people. So we propose a application to help the visually Challenged people to identify the different types of Yemenian currencies through deep learning technique. As money has a significant role in daily life for any business transactions, real-time detection and recognition of banknotes become necessary for a person, especially blind or visually impaired, or for a system that sorts the data. This paper presents a real-time Yemeni currency detection system for visually impaired persons. The proposed system exploits the deep learning approach to facilitate the visually impaired people to prosperously recognize banknotes. For real-time recognition, we have deployed the system into a mobile application.
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Taxonomy
TopicsCurrency Recognition and Detection
