Změny mezi verzí 26 a verzí 27 u OcrDataset
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- 30. 11. 2022 16:36:06 (před 20 měsíci)
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OcrDataset
v26 v27 2 2 This is an open dataset of scanned images and OCR texts from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains human annotations for layout analysis, OCR evaluation, and language identification. 3 3 4 You can [https://hdl.handle.net/11234/1-4615 download the dataset from 2021] and [http ://hdl.handle.net/11234/1-4935 supplementary materials from 2022] in the LINDAT/CLARIAH-CZ repository.4 You can [https://hdl.handle.net/11234/1-4615 download the dataset from 2021] and [https://hdl.handle.net/11234/1-4935 supplementary materials from 2022] in the LINDAT/CLARIAH-CZ repository. 5 5 6 6 == Contents == … … 17 17 * The archive [https://lindat.mff.cuni.cz/repository/xmlui/bitstream/handle/11234/1-4615/annotations-language-identification.zip?sequence=3&isAllowed=y annotations-language-identification.zip] (1.1 MB) contains 122 annotations for the evaluation of language identification. 18 18 19 [http ://hdl.handle.net/11234/1-4935 The supplementary materials from 2022] are structured as follows:19 [https://hdl.handle.net/11234/1-4935 The supplementary materials from 2022] are structured as follows: 20 20 21 * The archive [https://nlp.fi.muni.cz/projects/ahisto/ocr-texts-supplementary.zip ocr-texts-supplementary.zip](23.26 MB) contains 110 OCR texts for which we have both high-resolution scanned images and annotations for OCR evaluation.[[BR]]The archive is divided into a number of subdirectories with outputs of different OCR engines:21 * The archive [https://lindat.mff.cuni.cz/repository/xmlui/bitstream/handle/11234/1-4935/ocr-texts-supplementary.zip?sequence=1&isAllowed=y ocr-texts-supplementary.zip] (23.26 MB) contains 110 OCR texts for which we have both high-resolution scanned images and annotations for OCR evaluation.[[BR]]The archive is divided into a number of subdirectories with outputs of different OCR engines: 22 22 * The subdirectory `google-vision-ai-old` contains JSON and TXT documents from the Google Vision AI OCR engine from 2020-10-02. 23 23 * The subdirectory `google-vision-ai` contains JSON and TXT documents from the Google Vision AI OCR engine from 2022-08-11. … … 32 32 If you use our dataset in your work, please cite the following articles: 33 33 34 Novotný, V., Seidlová, K., Vrabcová, T., Horák, A.: When Tesseract Brings Friends: Layout Analysis, Language Identification, and Super-Resolution in the Optical Character Recognition of Medieval Texts. In: Horák, A., Rychlý, P., Rambousek, A. (eds.) '' Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN 2021''. pp. 91–100. ISSN 2336-4289. ISBN 978-80-263-1600-8. Tribun EU (2021). Available also from WWW: https://nlp.fi.muni.cz/raslan/2021/paper10.pdf34 Novotný, V., Seidlová, K., Vrabcová, T., Horák, A.: When Tesseract Brings Friends: Layout Analysis, Language Identification, and Super-Resolution in the Optical Character Recognition of Medieval Texts. In: Horák, A., Rychlý, P., Rambousek, A. (eds.) '' Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN 2021'' . pp. 91–100. ISSN 2336-4289. ISBN 978-80-263-1600-8. Tribun EU (2021). Available also from WWW: https://nlp.fi.muni.cz/raslan/2021/paper10.pdf 35 35 36 Novotný, V., Horák, A.: When Tesseract Meets PERO: Open-Source Optical Character Recognition of Medieval Texts. In: Horák, A., Rychlý, P., Rambousek, A. (eds.) '' Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN 2022''. pp. 157–160. ISSN 2336-4289. ISBN 978-80-263-1752-4. Tribun EU (2022). Available also from WWW: https://nlp.fi.muni.cz/raslan/2022/paper12.pdf36 Novotný, V., Horák, A.: When Tesseract Meets PERO: Open-Source Optical Character Recognition of Medieval Texts. In: Horák, A., Rychlý, P., Rambousek, A. (eds.) '' Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN 2022'' . pp. 157–160. ISSN 2336-4289. ISBN 978-80-263-1752-4. Tribun EU (2022). Available also from WWW: https://nlp.fi.muni.cz/raslan/2022/paper12.pdf 37 37 38 38 If you use LaTeX, you can use the following BibTeX entries: