Currency Recognition and Calculation System using Machine Learning Techniques

Richard Wasi, James Alick, M. Assaf
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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.
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。
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