In this paper, we investigate an approach to feature extraction for bank note classification by
exploiting the potential of wavelet transform. In the proposed method, high spatial frequency …

The improvement of reliability in banknote neuro-classifier is investigated and a reject option
is proposed based on the probability density function of the input data. The classification …

This work summarizes the design for test (DFT) circuitry and test methods that enabled Intel
to shift away from traditional functional testing of I/O's. This shift was one of the key enablers …

We present a method based on principal component analysis (PCA) for increasing the
reliability of banknote recognition. The system is intended for classifying any kind of …

This paper addresses the reliability of neuro-classifiers for bank note recognition. A local
principal component analysis (PCA) method is applied to remove non-linear dependencies …

This paper addresses the reliability of neuro-classifiers for bank note recognition. A local
principal component analysis (PCA) method is applied to remove non-linear dependencies …

This paper addresses the reliability of neuro-classifiers for paper currency recognition. A
local principal component analysis (PCA) method is applied to remove non-linear …

This paper addresses the reliability of neuro-classifiers for bank note recognition. A local
principal component analysis (PCA) method is applied to remove nonlinear dependencies …

The counter propagation networks (CPN) is used to improve the accuracy of the grade of
banknotes recognition. First, self-organizing map (SOM) is used to cluster banknotes data …

In this paper the reliability of the paper currency classifiers is studied and a new method is
proposed for improving the reliability based on the local principal components analysis …