Statistical Post-processing Approaches for OCR Texts-Reference-Cited by-同舟云学术

Statistical Post-processing Approaches for OCR Texts

Published:2022 Issue: Volume: Page:457-467
ISSN:2524-7565
Container-title:Algorithms for Intelligent Systems
language:
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Author:

Nguyen Quoc-Dung^ORCID,Le Duc-Anh,Phan Nguyet-Minh,Phan Nguyet-Thuan,Kromer Pavel

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-0332-8_34

Reference25 articles.

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2. Bassil Y, Alwani M (2012) OCR post-processing error correction algorithm using Google’s Online spelling suggestion. J Emerg Trends Comput Inf Sci 3(1):90–99

3. Kissos I, Dershowitz N (2016) OCR error correction using character correction and feature-based word classification. In: 12th IAPR workshop on document analysis systems (DAS), pp 198–203

4. Mei J, Islam A, Moh’d A, Wu Y, Milios E (2018) Statistical learning for OCR error correction. Inf Process Manag 54(6):874–887

5. Nguyen TTH, Coustaty M, Doucet A, Jatowt A, Nguyen NV (2018) Adaptive edit-distance and regression approach for Post-OCR text correction. In: Dobreva M, Hinze A, Žumer M (eds) Maturity and Innovation in Digital Libraries. ICADL 2018. Lecture Notes in Computer Science, vol 11279. Springer, Cham, pp 278–289 https://doi.org/10.1007/978-3-030-04257-8_29

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