Fast Extreme Learning Machine for Berber Handwritten Latin Script

Authors

  • Mokrane Kemiche Research Center for Amazigh Language and Culture, Bejaia, Algeria
  • Sadou Malika
  • Bousba Nassima

DOI:

https://doi.org/10.3991/ijes.v10i02.30663

Keywords:

Character Recognition, Extreme Learning Machine, Machine learning, Amazigh script

Abstract


This article deals with the problem of Berber handwritten character recognition using Extreme Learning Machine. This paradigm has gained significant attention in pattern recognition field thanks to its efficient learning speed and its high accuracy. In this paper, we have used a fast Extreme Learning Machine to recognize efficiently the Latin Berber characters. So, the proposed ELM has been trained over a Berber-MNIST dataset containing images of Amazigh alphabets. This algorithm learns much faster than traditional popular learning algorithms thanks to the use of JAX library which contains several functions to reduce the execution time of our solution.
The simulation results show that the handwritten recognition system based on our developed extreme learning machine decreases computational cost and reduces the time required for the whole recognition process. Furthermore, the developed ELM achieves a high performance in terms of recognition accuracy.

Cover iJES Vol. 10 No. 02 (2022)

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Published

2022-06-22

How to Cite

Kemiche, M., Malika, S., & Nassima, B. (2022). Fast Extreme Learning Machine for Berber Handwritten Latin Script. International Journal of Recent Contributions from Engineering, Science & IT (iJES), 10(02), pp. 43–52. https://doi.org/10.3991/ijes.v10i02.30663

Issue

Vol. 10 No. 02 (2022)

Section

Short Papers

License

Copyright (c) 2022 Mokrane Kemiche, Sadou Malika, Bousba Nassima

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