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Indian Currency Recognition for Visually Challenged using Machine Learning and Deep Learning

Nijil Raj N.1 , Anandu S. Ram2 , Aneeta Binoo Joseph3 , Shabna S.4

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-7 , Page no. 116-121, Jul-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i7.116121

Online published on Jul 31, 2020

Copyright © Nijil Raj N., Anandu S. Ram, Aneeta Binoo Joseph, Shabna S. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Nijil Raj N., Anandu S. Ram, Aneeta Binoo Joseph, Shabna S., “Indian Currency Recognition for Visually Challenged using Machine Learning and Deep Learning,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.116-121, 2020.

MLA Style Citation: Nijil Raj N., Anandu S. Ram, Aneeta Binoo Joseph, Shabna S. "Indian Currency Recognition for Visually Challenged using Machine Learning and Deep Learning." International Journal of Computer Sciences and Engineering 8.7 (2020): 116-121.

APA Style Citation: Nijil Raj N., Anandu S. Ram, Aneeta Binoo Joseph, Shabna S., (2020). Indian Currency Recognition for Visually Challenged using Machine Learning and Deep Learning. International Journal of Computer Sciences and Engineering, 8(7), 116-121.

BibTex Style Citation:
@article{N._2020,
author = {Nijil Raj N., Anandu S. Ram, Aneeta Binoo Joseph, Shabna S.},
title = {Indian Currency Recognition for Visually Challenged using Machine Learning and Deep Learning},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2020},
volume = {8},
Issue = {7},
month = {7},
year = {2020},
issn = {2347-2693},
pages = {116-121},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5176},
doi = {https://doi.org/10.26438/ijcse/v8i7.116121}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i7.116121}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5176
TI - Indian Currency Recognition for Visually Challenged using Machine Learning and Deep Learning
T2 - International Journal of Computer Sciences and Engineering
AU - Nijil Raj N., Anandu S. Ram, Aneeta Binoo Joseph, Shabna S.
PY - 2020
DA - 2020/07/31
PB - IJCSE, Indore, INDIA
SP - 116-121
IS - 7
VL - 8
SN - 2347-2693
ER -

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Abstract

Vision Impairment has been treated as a deterrent to normal functioning in human beings, so for such people, it is difficult to recognize the notes. The current system uses Malaysian Ringgit banknotes and extracts RGB values from the banknotes. The algorithms used were KNN, SVM, Naive Bayes, Decision Tree, and deep learning Alexnet. The proposed system uses Indian Currency and is divided into 3 phases. In phase I four features are extracted, phase II RGB values are extracted, and finally, in phase III, phase I and phase II are concatenated to produce better results. The algorithms used are KNN, Decision tree, SVM, Naive Bayes and deep learning VGGnet. Our system provides an accuracy of 98 percent in KNN, 95 percent in Decision Tree, 100 percent in SVM and 90 percent in Naive Bayes

Key-Words / Index Term

Banknote Recognition, Deep Learning, Machine Learning

References

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