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9 results for “Medieval Latin”
Early Medieval Latin Manuscripts Transmitting the Text of the Etymologiae of Isidore of Seville: an excel datasheet
<p>This excel file contains structured and formalized data about all surviving and identified early medieval Western manuscripts containing the text of the <em>Etymologiae</em> of Isidore of Seville, fully or partially. It records information about the place of origin, provenance, preservation, the date of origin, material properties, script, content, the state of preservation, presence of notable features, online representation, and bibliography of 507 manuscripts (v2.3.4: 496 manuscripts; v 2.3.2: 492 manuscripts; v2.1: 484 manuscripts; v2.0: 478 manuscripts) dated from the seventh to the first half of the eleventh centuries. This datasheet corresponds to the data published in the <em>Innovating Knowledge</em> database on 23 September 2024 (v2.3.4: 26 September 2023; v2.3.2: 2 August 2022; v2.1: 9 December 2021; v2.0: 12 October 2021), at: <a href="https://db.innovatingknowledge.nl/">db.innovatingknowledge.nl</a><br> </p> <p>More information about the <em>Innovating Knowledge</em> project is available at: <a href="https://innovatingknowledge.nl">innovatingknowledge.nl</a></p>
ICFHR 2016 Competition on the Classification of Medieval Handwritings in Latin Script - Dataset
<p>The ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script (CLaMM), jointly organized by Computer Scientists and Humanists (paleographers) provided a rich database of European medieval manuscripts to the community on Handwriting Analysis and Recognition.</p> <p>If you use this dataset, please cite:</p> <p>Florence Cloppet, Véronique Eglin, Van Cuong Kieu, Dominique Stutzmann, and Nicole Vincent, "ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script", <em>Proceedings of International Conference on Frontiers in Handwriting Recognition</em>, Los Alamos : IEEE, 2016, p. 590-595. [<a href="https://doi.org/10.1109/ICFHR.2016.0113">https://doi.org/10.1109/ICFHR.2016.0113</a>]</p> <p>At this competition, we proposed two independent classification tasks which attracted five participants with seven submitted classifiers. Those classifiers are trained on a set of 2000 images with their ground truths. In the first task of script crisp classification, the classifiers have been evaluated on a test set of 1000 single-type manuscripts. In the second task of “Fuzzy Classification”, the classifiers have been carried out on a set of 2000 multi-script-type manuscripts.</p> <p>The present dataset contains the training dataset, both test datasets (task 1 and task 2) and the matrices provided by the competitors. It was first published on a https://clamm.irht.cnrs.fr/icfhr2016-clamm/ in Oct. 2016.</p> <p> </p>
Dataset and evaluation for HTR models for Latin and French Medieval Documentary Manuscripts
<p><strong>1. Dataset presentation.</strong></p> <p>This is the dataset used to produce the HTR models applied to documentary Latin and French manuscripts presented in the paper: Sergio Torres Aguilar, Vincent Jolivet. <strong>Handwritten Text Recognition for Documentary Medieval<br> Manuscripts. </strong>2022. https://hal.science/hal-03892163</p> <p>The dataset contains mostly charters and registers from the Late-medieval period (12th-15th). The training and evaluation, entailing 1855 pages, 120k lines of text and almost 1M tokens, were conducted using three freely available ground-truth corpora :</p> <p><strong>The Alcar-HOME database </strong>: https://zenodo.org/record/5600884</p> <p><strong>The e-NDP corpus </strong>: https://github.com/chartes/e-NDP_HTR</p> <p><strong>The Himanis project </strong>: https://zenodo.org/record/5535306</p> <p>The final model operates in a multilingual environment (Latin and French) and it is able to recognize several Latin script families (mostly <em>Textualis</em> and <em>Cursiva</em>) in documents produced in ca. 12th - 15th centuries. During the evaluation the models shows an accuracy of <strong>94.01%</strong> on the validation set and a CER (character error ratio) of about <strong>0.12</strong> to <strong>0.17</strong> on four external unseen datasets. A fine-tuning exercise using 10 ground-truth pages can raise these results to a CER between <strong>0.06</strong> to <strong>0.10</strong> respectively.</p> <p> </p> <p><strong>2. Dataset contents .</strong></p> <p>a) <em>GT_list : </em>List containing the GT file names which constitute the training, evaluation and test sets. The images and transcriptions can be downloaded from their original repositories.</p> <p>b) <em>Training :</em> Contains the training and testing results (evaluation and prediction files) presented in the original paper for the two training phases: Regular (Textualis and Cursiva separated training) and Quartiles (mixed training by quartiles).</p> <p>c) <em>Useful_scripts :</em> Scripts to produce the HTR metrics (CER, WER, SER) and plot the model's accuracy.</p> <p>d) <em>Best_model :</em> Contains the best multilingual and multi-script model.</p>
An Artificial Eye for Palaeography. Applying Deep Machine Learning for the Study of Medieval Latin Scripts
<p>The project “Digital Forensics for Historical Documents” (at Huygens ING, Amsterdam) attempts to create a digital tool, based on a deep learning system, in which the unique characteristics of one medieval script sample will be matched with similar script samples by making use of digitized manuscript collections available in the world wide web.</p> <p>Project website and contact: <a href="https://www.youtube.com/redirect?q=https%3A%2F%2Fen.huygens.knaw.nl%2Fprojecten%2Fdigital-forensics-for-historical-documents%2F&v=WYtseNK-1Dc&event=video_description&redir_token=QUFFLUhqbDM0WDRJRjN0V3QzOXV6d0ZNbDB2TVYzV1hUQXxBQ3Jtc0ttLVJHMEE1RlRkZjJVV3poYnpQOHZseTFzZHVqWHRGR2k2eWpVWTJSSldtV2p4aFhKbFRIQTFjVHQ5YnM0Mkd4ajBzOTNtdE1yOVJLVktqWlhqWUgzZXc3YmNQMS1nNGFpZ3p2amNOTFNqTDVUSTdtZw%3D%3D">https://en.huygens.knaw.nl/projecten/...</a> </p> <p>Presented as a Lightning Talk for the Schoenberg Symposium 2020</p>
Dataset for the paper "Ground-truth Free Evaluation of HTR on Old French and Latin Medieval Literary Manuscripts"
<p>This dataset was used in the context of the article <em>Ground-truth Free Evaluation of HTR on Old French and Latin Medieval Literary Manuscripts</em>, at the Computational Humanities Research 2022 conference.</p> <p>Predictions.zip contains the XML ALTO for the HTR and Segmentation prediction of around 10 pages of 1900 manuscripts from the Bibliothèque nationale de France.</p> <p>Varying ground truth contains the original training material for training a classifier for CER classification (see the article).</p> <p>The ManuscriptsIIIF.csv contains metadata about the manuscripts.</p> <p>This work was funded by the DIM MAP under the CREMMALab funding.</p>
Latin inscribed Medieval standingstone, Yarrow
Canmore 53078 53078NGR: NT 34805 27441 Just over 1.5m high the standing stone bears an important six line Latin inscription, fairly roughly carved and in parts badly weathered. The letters are mainly Roman capitals, irregular and sprawling; the words are badly set out and carelessly written! Certain letters, however, provide parallels with stones elsewhere, notably in Wales and Cornwall, and help date it to the early 6th century. A brief translation would run: ''This (is) the everlasting memorial In (this) place (lie) the most famous princes Nudus and Dumnogenus In this tomb lie the two sons of Liberalis". Source: Objaverse 1.0 / Sketchfab
ICDAR 2017 Competition on the Classification of Medieval Handwritings in Latin Script - Dataset
<p>The ICDAR2017 Competition on the Classification of Medieval Handwritings in Latin Script (CLaMM), jointly organized by Computer Scientists and Humanists (paleographers) followed a competition at ICFHR2016 and provided a rich annotated database of European medieval manuscripts to the community on Handwriting Analysis and Recognition, containing information on date of production and class of script.</p> <p>If you use this upload, please cite:</p> <p>Florence Cloppet, Véronique Eglin, Marlène Helias-Baron, van Cuong Kieu, Dominique Stutzmann, Nicole Vincent, "ICDAR 2017 Competition on the Classification of Medieval Handwritings in Latin Script", in <em>14th IAPR International Conference on Document Analysis and Recognition</em>. ICDAR 2017, 1371-76. Kyoto: CPS, 2017. <a href="https://doi.org/10.1109/ICDAR.2017.224">https://doi.org/10.1109/ICDAR.2017.224</a></p> <p>We proposed four independent classification tasks which attracted 10 registered teams, with 6 submitted classifiers from 4 participants. Those classifiers are trained on a set of 3540 images with their ground<br> truths. In task 1 (Script classification) and task 3 (Date classification), the classifiers have been evaluated by a test set of 2000 greyscale, tiff, 300 dpi images. In task 2 (Script classification) and task 4 (Date classification), the test set consists of 1000 images in different formats, resolutions and color<br> representation.</p> <p>The present dataset contains the training dataset, both test datasets (tasks 1 and 3, and tasks 2 and 4) and the matrices provided by the competitors. It was first published on <a href="https://clamm.irht.cnrs.fr/icdar-2017/">https://clamm.irht.cnrs.fr/icdar-2017/</a> in Nov. 2017.</p>
The Lost Patriarchs Project: discovering Greek patristics in the medieval Latin tradition
<p>A video and transcript on The Lost Patriarchs Project, delivered for the Dark Archives Conference, September 8-10, 2020. More information can be found on the<a href="https://www.lostpatriarchsproject.com/"> project website</a>.</p>
eFontes. The Electronic Corpus of Polish Medieval Latin
<p><a href="https://corpus.scriptores.pl/#open">https://corpus.scriptores.pl/</a></p>
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