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Titlebook: Document Analysis Systems; 15th IAPR Internatio Seiichi Uchida,Elisa Barney,Véronique Eglin Conference proceedings 2022 Springer Nature Swi

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Font Shape-to-Impression Translatione analysis, i.e., multi-label classification and translation. A quantitative evaluation shows that our Transformer-based approaches estimate the font impressions from a set of local parts more accurately than other approaches. A qualitative evaluation then indicates the important local parts for a specific impression.
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Recognition and Information Extraction in Historical Handwritten Tables: Toward Understanding Early rther improved our results. We also introduce through this communication two annotated datasets for handwriting recognition that are now publicly available, and an open-source toolkit to apply WFST on CTC lattices.
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Historical Map Toponym Extraction for Efficient Information Retrievalor research and educational purposes. Then, we propose a novel approach for toponym classification based on KAZE descriptor. Next we compare and evaluate several state-of-the-art methods for text and object detection on our toponym detection task. We further show the results of toponym text recognition using popular Tesseract engine.
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The Winner Takes It All: Choosing the “best” Binarization Algorithm for Photographed Documentsor portable devices have space and processing limitations that allow to implement only the “best” algorithm. This paper presents the methodology and assesses the time-quality performance of 61 binarization algorithms to choose the most time-quality efficient one, under two criteria.
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Information Extraction from Handwritten Tables in Historical Documentsach that is based on heuristic rules to extract information in historical pre-printed forms with handwritten information. We analyze how each approach performs at each step of the extraction process. The proposed approaches improve the heuristic-rule baseline by up to 0.14 F-measure points throughout the information extraction pipeline.
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Tsuyoshi Kato,Eddy Maerten,Antoine Baceiredoe analysis, i.e., multi-label classification and translation. A quantitative evaluation shows that our Transformer-based approaches estimate the font impressions from a set of local parts more accurately than other approaches. A qualitative evaluation then indicates the important local parts for a specific impression.
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