Using Convolutional Neural Networks, Arabic Handwritten Character Recognition

Authors

  • Surendra Kumar Shukla, POONAM VERMA

Keywords:

Convolutional Neural Network, MADBase, Arabic handwriting digit Recognition.

Abstract

Recognizing handwritten Arabic numbers is a challenging research topic. Impulsive by this research topic proposed two convolutional neural networks for recognizing Arabic handwritten numerals. Two proposed models have been analyzed using different filter sizes. The Arabic Number dataset exported from Kaggle was trained. The simplest proposed model achieved high recognition accuracy of 99.92%, outperforming the other complex with a more reasonable accuracy. For the MADBase dataset

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Published

2022-09-05

How to Cite

Surendra Kumar Shukla, POONAM VERMA. (2022). Using Convolutional Neural Networks, Arabic Handwritten Character Recognition. SJIS-P, 34(2), 139–144. Retrieved from http://sjis.scandinavian-iris.org/index.php/sjis/article/view/487

Issue

Vol. 34 No. 2 (2022)

Section

Articles