Currency Classification System Using Deep Learning

Authors

  • P. Kavya Sree  PG Student, Department of Computer Application, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India
  • Dr. J. Srinivasan  Assistant Professor, Department of Computer Application, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

Keywords:

Currency image dataset, CNN algorithm, MobileNet, Data Augmentation, Tensorflow.

Abstract

In recent years, deep learning has become the most popular research direction. It mainly trains the dataset through neural networks. There are many different models that can be used in this research project. Throughout these models, accuracy of currency recognition can be improved. Obviously, such research methods are in line with our expectations. In this paper, we mainly use transfer learning (MobileNet) model based on deep learning as the framework, Convolutional Neural Network (CNN) model to extract the features of paper currency, so that we can more accurately classify the currency. Our main contribution is through using CNN and MobileNet, the average accuracy of currency classification is up to 99%.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-08-30

Issue

Volume 8, Issue 4, July-August-2022

Section

Research Articles

License

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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
P. Kavya Sree, Dr. J. Srinivasan, " Currency Classification System Using Deep Learning, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 4, pp.287-293, July-August-2022.