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164885

A Neural Network for Arabic Character Recognition.

Article

Last updated: 22 Jan 2023

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Tags

Electrical Engineering

Abstract

Neural network-based learning is an essential part of any intelligent system and is an inherent property in Artificial Neural Network (ANN) models. Recently, artificial neural network models have begun to emerge as powerful tools for learning. 
Neural networks are designed and applied to the classification of isolated Arabic characters. We have studied the ability of networks to correctly classify both training and testing examples. Multilayered neural networks were trained to classify the characters using the error backpropagation learning algorithm. Noisy characters could be efficiently recognized. In this paper we evaluate the performance of the backpropagation technique on recognition of Arabic characters. Results indicate a high percentage of correct recognition and fault tolerance capability. The most effective number of neural network layers and the number of units in the bidden layers are conducted through extensive experimental work on isolated Arabic characters, Further research for recognition of connected hand written characters is going on. 

DOI

10.21608/bfemu.1993.164885

Authors

First Name

Ahmed

Last Name

Alam El-Din

MiddleName

El-Saeed Tolba

Affiliation

Lecturer at Electrical Engineering Department., Faculty of Engineering., University of Suez Canal., Port Said., Egypt.

Email

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City

Port Said

Orcid

-

Volume

18

Article Issue

1

Related Issue

24033

Issue Date

1993-03-01

Receive Date

1993-01-11

Publish Date

2021-03-01

Page Start

61

Page End

71

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 18_Issue 1_Pages 61-71.pdf

PDF . 480.8kB

Link

https://bfemu.journals.ekb.eg/article_164885.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=164885

Order

2

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

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Details

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Article

Created At

22 Jan 2023