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Volume: 19 | Article ID: 8
Isolated Handwritten Character Recognition of Ancient Hebrew Manuscripts
  DOI :  10.2352/issn.2168-3204.2022.19.1.8  Published OnlineJune 2022

Character recognition is widely considered an essential factor in preserving and digitizing historical handwritten documents. While it has shown a significant impact, the character recognition of historical handwritten documents is still a challenging task. This work aims to present a study on building a character recognition system for a handwritten ancient Hebrew text utilizing convolutional neural networks, dealing with material degradation, script complexity, and varied handwriting style. Our research underlined the importance of creating a ground-truth dataset for a robust and reliable character recognition system. Moreover, this study compares the performance of four convolutional neural network models applied to our dataset.

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Tabita L. Tobing, Sule Y. Yayilgan, Sony George, Torleif Elgvin, "Isolated Handwritten Character Recognition of Ancient Hebrew Manuscriptsin Archiving Conference,  2022,  pp 35 - 39,

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