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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM14990

Fake Currency Detection Using Deep Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM14990

Volume:

6 |

6 |

Jun 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

CKR

Chandana K R

KKN

Kusuma K N

GVK

G V Keerthana

GA

Geetha A

GSS

Gutta Sai Sandhya

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Abstract

Fake currency is the money produced without the approval of the government, creation of it is considered as a great offence. The progression of shading printing innovation has expanded the rate of Fake currency copying notes on a large scale. Albeit electronic monetary exchanges are turning out to be more popular and the utilization of paper cash has been diminishing as of late, banknotes still remain in distribution attributable to their dependability and straight forwardness in use. Few years ago, the printing should be possible in a printing-houses, yet presently anybody can print a money paper with most extreme exactness utilizing a straightforward laser printer. As an outcome, the issue of duplicate currency rather than the authentic ones has been increases generally. India had reviled the problems like defilement and dark cash and fake of money notes is likewise a big issue to it. To handle this problem, a deep learning-based framework is proposed to identify the fake Indian currency. The MATLAB tool has been used to identify the fake currency. The outcome will classify whether the Indian currency note is Real or Fake

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Cite This Article

Chandana K R, Kusuma K N, G V Keerthana, Geetha A, Gutta Sai Sandhya, "Fake Currency Detection Using Deep Learning," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 6, Jun 2022.

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Publication Date

4/27/2024

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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