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Arabian Journal for Science and Engineering

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23.01.2022 | Research Article-Computer Engineering and Computer Science

Arabic Handwritten Recognition Using Deep Learning: A Survey

verfasst von: Naseem Alrobah, Saleh Albahli

Erschienen in: Arabian Journal for Science and Engineering | Ausgabe 8/2022

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Abstract

In recent times, many research projects and experiments target machines that automatically recognize handwritten characters, but most of them are done in Latin. Recognizing handwritten Arabic characters is a complicated process compared to English and other languages as a nature of Arabic words. In the past few years, deep learning approaches have been increasingly used in the field of Arabic recognition. This paper aims to categorize, analyze and presents a comprehensive survey in Arabic handwritten recognition literature, focusing on state-of-the-art methods for deep learning in feature extraction. The paper focuses on offline text recognition, with a detailed discussion of the systematic analysis of the literature. Additionally, the paper is critically analyzing the current literature and identifying the problem areas and challenges faced by the previous studies. After investigating the studies, a new classification of the literature is proposed. Besides, an analysis is performed based on the findings, and several issues and challenges related to the recognition of Arabic scripts are discussed.

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Titel: Arabic Handwritten Recognition Using Deep Learning: A Survey
verfasst von: Naseem Alrobah
Saleh Albahli
Publikationsdatum: 23.01.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Arabian Journal for Science and Engineering / Ausgabe 8/2022
Print ISSN: 2193-567X
Elektronische ISSN: 2191-4281
DOI: https://doi.org/10.1007/s13369-021-06363-3

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