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arXiv · 1912.03634

Capsule-Based Persian/Arabic Robust Handwritten Digit Recognition Using EM Routing

Ali Ghofrani·Rahil Mahdian Toroghi
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Abstract

In this paper, the problem of handwritten digit recognition has been addressed. However, the underlying language is Persian/Arabic, and the system with which this task is a capsule network (CapsNet) has recently emerged as a more advanced architecture than its ancestor, namely CNN (Convolutional Neural Network). The training of the architecture is performed using the Hoda dataset, which has been provided for Persian/Arabic handwritten digits. The output of the system clearly outperforms the results achieved by its ancestors, as well as other previously presented recognition algorithms.

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Ali Ghofrani, Rahil Mahdian Toroghi. 2019-12-08. Capsule-Based Persian/Arabic Robust Handwritten Digit Recognition Using EM Routing. https://doi.org/10.1109/pria.2019.8785981

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