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- W2897072956 abstract "Optical Character Recognition (OCR) is the process of recognizing characters automatically from scanned or image documents. OCR software uses machine learning to recognize characters in the document. Such software needs to pass a training phase to learn how to recognize the letters in the text. In order to implement the training phase the OCR needs to use a standard dataset. The dataset can be used to evaluate the obtained results. In this research, we propose an Arabic printed OCR dataset. To the best of our knowledge, there is no Arabic OCR dataset that is available to be used by the research community with its ground truth with a size that is suitable to build a robust Arabic OCR. The proposed dataset is extracted randomly from Wikipedia to have different topics. It consists of 4,587 Arabic articles with a total of 8,994 images." @default.
- W2897072956 created "2018-10-26" @default.
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- W2897072956 date "2018-07-01" @default.
- W2897072956 modified "2023-10-16" @default.
- W2897072956 title "Yarmouk Arabic OCR Dataset" @default.
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- W2897072956 doi "https://doi.org/10.1109/csit.2018.8486162" @default.
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