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An End-to-End OCR Framework for Robust Arabic-Handwriting Recognition using a Novel Transformers-based Model and an Innovative 270 Million-Words Multi-Font Corpus of Classical Arabic with Diacritics. (arXiv:2208.11484v2 [cs.CV] UPDATED)
Aug. 30, 2022, 1:14 a.m. | Aly Mostafa, Omar Mohamed, Ali Ashraf, Ahmed Elbehery, Salma Jamal, Anas Salah, Amr S. Ghoneim
cs.CV updates on arXiv.org arxiv.org
This research is the second phase in a series of investigations on developing
an Optical Character Recognition (OCR) of Arabic historical documents and
examining how different modeling procedures interact with the problem. The
first research studied the effect of Transformers on our custom-built Arabic
dataset. One of the downsides of the first research was the size of the
training data, a mere 15000 images from our 30 million images, due to lack of
resources. Also, we add an image enhancement …
More from arxiv.org / cs.CV updates on arXiv.org
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