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Arab Handwriting Character Recognition Using Deep Learning

  • Aissa Kerkour ElmiadEmail author
Conference paper
  • 536 Downloads
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 7)

Abstract

Recent work has shown that neural networks have great potential in the field of handwriting recognition. The advantage of using this type of architecture, besides being robust, is that the network learns the characteristic vectors automatically thanks to the convolution layers. We can say that it creates intelligent filters. In this article we study deep learning in the field of Arab handwritten character in order to have a better understanding of its functioning. In this paper we present the work we have done on convolutional neural networks. First, we explain the theoretical aspects of neural networks, then we present our experimental protocols and we comment on the results obtained.

Keywords

Convolutional neural network Deep neural networks Arabic handwritten character recognition 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science Research Laboratory, Faculty of Sciences OujdaUniversity Mohammed 1erOujdaMorocco

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