Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Teaching Tool for Fun Learning of AI-based Banknote Detection Technology

Cheng-Yu Yeh, Chun-Cheng Lin, and Kuan-Chun Hsu

(Received November 18, 2020; Accepted February 3, 2021)

Keywords: object detection, artificial intelligence (AI), deep learning, you only look once (YOLO)

This paper presents a teaching tool for schoolchildren to learn AI technology through which a variety of banknotes can be recognized. This was done by first using a pretrained YOLOv3 object detection model. Secondly, transfer learning was conducted on the pretrained model using 11 collected banknotes, including US$, Euro, Japanese Yen, and NT$. The banknote detection model was experimentally validated to give an average precision (AP) of up to 99.09% if the threshold Intersection over Union (IoU) is not less than 0.8. Once a banknote was successfully recognized, the face value and the country name thereon were displayed, and schoolchildren can access suggested websites, i.e., Wikipedia, Google Maps, and the Bank of Taiwan, to learn more about the exchange rate between currencies and the history and location of the country that issued the banknote. Consequently, schoolchildren can have fun using this tool and acquire a more a global outlook. Moreover, they may be motivated to become AI professionals in the future.

Corresponding author: Cheng-Yu Yeh

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