Yemeni Paper Currency Recognition System Using Deep Learning Approach

Author:

Ba Alawi Abdulfattah E.,Saeed Ahmed Y. A.,Al-Zekri Burhan T.,Radman Borhan M. N.,Saif Alaa A.,Alshami Maged,Alshadadi Ahmed,Mohammad Muneef A.,Mohammed Ala’a M.,Saeed Osama Y. A.,Saeed Adeeb M.

Publisher

Springer Singapore

Reference23 articles.

1. Raval, V., Shah, A.: A Comparative analysis on currency recognition systems for iCu₹ e and an improved grab-cut for android devices. In: Emerging Technologies in Data Mining and Information Security, pp. 279–286. Springer (2019)

2. Bae, R.E.T., Arboleda, E.R., Andilab, A., Dellosa, R.M.J.I.J.S.T.R.: Implementation of template matching, fuzzy logic and K nearest neighbor classifier on Philippine banknote. Recogn. Syst. 8(08), 1451–1453 (2019)

3. Takeda, F., Onami, S., Kadono, T., Terada, K., Omatu, S.: A paper currency recognition method by a small size neural network with optimized masks by GA. In: Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), pp. 4243–4246. IEEE (1994)

4. Takeda, F., Omatu, S.J.I.T.o.N.N.: High speed paper currency recognition by neural networks. IEEE Trans. Neural Netw. 6(1), 73–77 (1995)

5. Ahmadi, A., Omatu, S., Yoshioka, M.: Implementing a reliable neuro-classifier for paper currency using PCA algorithm. In: Proceedings of the 41st SICE Annual Conference. SICE 2002, pp. 2466–2468. IEEE (2002)

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