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By the People Crowdsourcing Datasets from the Library of Congress
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In: Journal of Open Humanities Data; Vol 8 (2022); 5 ; 2059-481X (2022)
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A Pipeline Approach to Context-Aware Handwritten Text Recognition
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In: Applied Sciences; Volume 12; Issue 4; Pages: 1870 (2022)
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Medieval manuscripts from digitization to historical analysis
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In: On the way to the future of Digital Manuscript Studies ; https://hal.archives-ouvertes.fr/hal-03503308 ; On the way to the future of Digital Manuscript Studies, Radboud University, Oct 2021, Nijmegen, Netherlands ; https://www.ru.nl/rich/news-events/events/redactionele/online-workshop-on-the-way-to-the-future-digital/ (2021)
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HOME-Alcar: Aligned and Annotated Cartularies
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In: https://hal.archives-ouvertes.fr/hal-03503062 ; 2021, ⟨10.5281/zenodo.5600884⟩ (2021)
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Handling Heavily Abbreviated Manuscripts: HTR engines vs text normalisation approaches
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In: International Conference on Document Analysis and Recognition 2021 ; https://hal-enc.archives-ouvertes.fr/hal-03279602 ; International Conference on Document Analysis and Recognition 2021, 2021, Lausanne, Switzerland. pp.306-316, ⟨10.1007/978-3-030-86159-9_21⟩ (2021)
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Abstract:
International audience ; Although abbreviations are fairly common in handwritten sources, particularly in medieval and modern Western manuscripts, previous research dealing with computational approaches to their expansion is scarce. Yet abbreviations present particular challenges to computational approaches such as handwritten text recognition and natural language processing tasks. Often, pre-processing ultimately aims to lead from a digitised image of the source to a normalised text, which includes expansion of the abbreviations. We explore different setups to obtain such a normalised text, either directly, by training HTR engines on normalised (i.e., expanded, disabbreviated) text, or by decomposing the process into discrete steps, each making use of specialist models for recognition, word segmentation and normalisation. The case studies considered here are drawn from the medieval Latin tradition.
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Keyword:
[SHS.HIST]Humanities and Social Sciences/History; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; Abbreviations; Computational methods; Handwritten Text Recognition; Medieval Western Manuscripts; Paleography
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URL: https://doi.org/10.1007/978-3-030-86159-9_21 https://hal-enc.archives-ouvertes.fr/hal-03279602 https://hal-enc.archives-ouvertes.fr/hal-03279602/file/IWCP2021_Handling_Abreviations_ArXiv.pdf https://hal-enc.archives-ouvertes.fr/hal-03279602/document
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Gado2: multilingual newspapers from the Netherlands Indies ...
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Gado2: multilingual newspapers from the Netherlands Indies ...
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Gado2: multilingual newspapers from the Netherlands Indies ...
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Gado2: multilingual newspapers from the Netherlands Indies ...
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Digitising (Romanian) Cyrillic using Transkribus: new perspectives
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Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition
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Advances on the Transcription of Historical Manuscripts based on Multimodality, Interactivity and Crowdsourcing
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Flexible Sequence Matching Technique:An Effective Learning-free Approach For word-spotting
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In: ISSN: 0031-3203 ; Pattern Recognition ; https://hal.archives-ouvertes.fr/hal-01321130 ; Pattern Recognition, Elsevier, 2016, ⟨10.1016/j.patcog.2016.05.011⟩ ; http://authors.elsevier.com/sd/article/S0031320316300942 (2016)
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Text extraction in document images: highlight on using corner points
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In: Proceedings of 12th International Workshop on Document Analysis Systems ; International Workshop on Document Analysis Systems (DAS) ; https://hal.archives-ouvertes.fr/hal-01269802 ; International Workshop on Document Analysis Systems (DAS), Apr 2016, Santorini, Greece (2016)
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Querying out-of-vocabulary words in lexicon-based keyword spotting
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Contributions to the joint segmentation and classification of sequences (My two cents on decoding and handwriting recognition)
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Multimodal output combination for transcribing historical handwritten documents
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