Currency Recognition and Calculation System using Machine Learning Techniques

Richard Wasi, James Alick, M. Assaf
{"title":"Currency Recognition and Calculation System using Machine Learning Techniques","authors":"Richard Wasi, James Alick, M. Assaf","doi":"10.37394/232014.2020.16.5","DOIUrl":null,"url":null,"abstract":"Different currencies are being processed in money exchange shops and banks around the globe on a daily basis, where money exchange and transfer takes place. Identifying different currency is a difficult task and can lead to financial loss. There are approximately 180 currencies being used around the world, and each of them differ in color, size and texture. Thus, to correctly identify different currencies, a currency recognition systems needs to be designed. In this paper, we propose the design of an AlexNet based currency recognition system to recognize different international currency notes. We use 10-fold Cross Validation to obtain the cross-validation results of the AlexNet model. The features for the Alex model is extracted from the images back and front of each currency note. We also explore and implement deep learning models to compare the performance of the AlexNet model.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/232014.2020.16.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Different currencies are being processed in money exchange shops and banks around the globe on a daily basis, where money exchange and transfer takes place. Identifying different currency is a difficult task and can lead to financial loss. There are approximately 180 currencies being used around the world, and each of them differ in color, size and texture. Thus, to correctly identify different currencies, a currency recognition systems needs to be designed. In this paper, we propose the design of an AlexNet based currency recognition system to recognize different international currency notes. We use 10-fold Cross Validation to obtain the cross-validation results of the AlexNet model. The features for the Alex model is extracted from the images back and front of each currency note. We also explore and implement deep learning models to compare the performance of the AlexNet model.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于机器学习技术的货币识别与计算系统
世界各地的货币兑换商店和银行每天都在处理不同的货币,进行货币兑换和转账。识别不同的货币是一项艰巨的任务,可能会导致经济损失。世界上大约有180种货币,每种货币的颜色、大小和质地都不同。因此,要正确识别不同的货币,就需要设计货币识别系统。在本文中,我们提出了一个基于AlexNet的货币识别系统来识别不同的国际货币。我们使用10倍交叉验证来获得AlexNet模型的交叉验证结果。Alex模型的特征是从每张纸币的背面和正面图像中提取的。我们还探索和实现了深度学习模型,以比较AlexNet模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Robust Recursive Least-Squares Fixed-Point Smoother and Filter using Covariance Information in Linear Continuous-Time Stochastic Systems with Uncertainties Driving Aid for Rotator Cuff Injured Patients using Hand Gesture Recognition CTM Tongue Image Consulting System based on Deep Learning Technology Robust Estimators for Missing Observations in Linear Discrete-Time Stochastic Systems with Uncertainties Pattern Wafer x/y Auto Align System using Machine Vision
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1