DETECTION OF INDIAN CURRENCY NOTES USING DEEP LEARNING TECHNIQUES

Aniket Suryawanshi , Akash Toshniwal , Shruti Salve , Ruchita Shinde , K.V.Metre

Fake currency, security features, RNN

Currency duplication is very harmful for the economy of a particular nation and also it is global issue. We are developing a system through which we are able to identify those fake currency notes. In our system we mainly focus on the security features of currency note like intaglio, microlettering, number panel, bleed lines, latent image, security thread, optical variable link, etc. Previously, the fake currency identification system is developed with the helps various algorithms, but as per our survey the neural network algorithms (RNN) are more efficient than previously used algorithms. So, with the help of these security features and Recurrent Neural Network algorithm.

Published Paper   E-Certificate

"DETECTION OF INDIAN CURRENCY NOTES USING DEEP LEARNING TECHNIQUES", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 12, page no.860 - 862, December-2022, Available :https://ijsdr.org/papers/IJSDR2212132.pdf

Volume 7 Issue 12, December-2022

Pages : 860 - 862

Paper Reg. ID: IJSDR_203192

Published Paper Id: IJSDR2212132

Downloads: 000347243

Research Area: Engineering

Country: -, --, -

Published Paper PDF: https://ijsdr.org/papers/IJSDR2212132

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2212132

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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