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– ABSTRACT
The one important asset of our country is Bank currency and to create discrepancies
of money miscreants introduce the fake notes which resembles to original note in the
financial market. During demonetization time it is seen that so much of fake currency
is floating in market. In general by a human being it is very difficult to identify forged
note from the genuine not instead of various parameters designed for identification
as many features of forged note are similar to original one. To discriminate between
fake bank currency and original note is a challenging task. So, there must be an
automated system that will be available in banks or in ATM machines. To design such
an automated system there is need to design an efficient algorithm which is able to
predict weather the banknote is genuine or forged bank currency as fake notes are
designed with high precision. In this paper we are using CNN algorithm on dataset
available on UCI machine learning repository for detection of Bank currency
authentication. To implement this we have applied machine learning algorithms are
measured their performance on the basis various quantitative analysis parameter.
