Advancements in CNN Architectures for Offline Handwritten Arabic Character Recognition

Analyzing and classifying images of Arabic handwritten characters is crucial for text understanding and interpretation from image data. The recognition of handwritten Arabic characters not only preserves the integrity of the Arabic language but also enhances computer vision applications tailored for...

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Bibliographic Details
Main Authors:	El Ibrahimi Aissam, Elzaar Abdellah, El Akchioui Nabil, Benaya Nabil, El Allati Abderrahim
Format:	Article
Language:	English
Published:	EDP Sciences 2025-01-01
Series:	E3S Web of Conferences
Subjects:	andwritten arabic character recognition deep learning object recognition convolutional neural network offline arabic handwritten recognition (oahr)
Online Access:	https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00015.pdf
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Advancements in CNN Architectures for Offline Handwritten Arabic Character Recognition

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