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Christian Reul
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2020 – today
- 2024
- [c22]Christian Reul, Maximilian Nöth, Herbert Baier, Florian Langhanki, Kevin Chadbourne:
Human-Centred Open-Source Automatic Text Recognition for the Humanities with OCR4all. CHAI@KI 2024: 75-82 - 2023
- [j5]Simon Gabay, Thibault Clérice, Christian Reul:
OCR17: Ground Truth and Models for 17th c. French Prints (and hopefully more). J. Data Min. Digit. Humanit. 2023 (2023) - [c21]Julia Nantke, Christian Reul, Sandra Bläß, Marie Flüh:
Algorithmen-gestützte Analyse visuell-materieller Eigenschaften von Briefen. DHd 2023: 88 - [c20]Yannik Herbst, Torsten Roeder, Christian Reul:
Synoptische Interfaces Digitaler Editionen. DHd 2023: 296 - [c19]Sandra Bläß, Marie Flüh, Julia Nantke, Christian Reul:
Analyse, Produktion, Reflexion: Nachnutzungsszenarien für Forschungsdaten am Beispiel der Daten des Projekts Dehmel digital. DHd 2023: 355 - [c18]Florian Langhanki, Maximilian Wehner, Torsten Roeder, Christian Reul:
OCR4all - Open-Source OCR and HTR Across the Centuries. DH 2023 - 2022
- [c17]Christian Reul, Stefan Tomasek, Florian Langhanki, Uwe Springmann:
Open Source Handwritten Text Recognition on Medieval Manuscripts Using Mixed Models and Document-Specific Finetuning. DAS 2022: 414-428 - [c16]Jan Sebastian Klaes, Kristof Korwisi, Katharina Krüger, Christian Reul, Nadine Towara:
Volltexterkennung für historische Sammlungen mit OCR4all-libraries iterativ und partizipativ gestalten. DHd 2022 - [c15]Jan Sebastian Klaes, Kristof Korwisi, Katharina Krüger, Christian Reul, Nadine Towara:
Volltexterkennung für historische Sammlungen mit OCR4all-libraries iterativ und partizipativ gestalten. DHd 2022 - [c14]Florian Langhanki, Maximilian Wehner, Konstantin Baierer, Lena Hinrichsen, Christian Reul:
Flexibles Arbeiten mit OCR4all - Massenvolltextdigitalisierung von Drucken mithilfe von OCR-D und hochqualitative Transkription von Handschriften. DHd 2022 - [c13]Stefan Tomasek, Christian Reul, Maximilian Wehner:
Handwritten Text Recognition und Word Mover's Distance als Grundlagen der digitalen Edition "Die Kindheit Jesu Konrads von Fußesbrunnen". DHd 2022 - [i12]Christian Reul, Stefan Tomasek, Florian Langhanki, Uwe Springmann:
Open Source Handwritten Text Recognition on Medieval Manuscripts using Mixed Models and Document-Specific Finetuning. CoRR abs/2201.07661 (2022) - 2021
- [c12]Christian Reul, Christoph Wick, Maximilian Nöth, Andreas Büttner, Maximilian Wehner, Uwe Springmann:
Mixed Model OCR Training on Historical Latin Script for Out-of-the-Box Recognition and Finetuning. HIP@ICDAR 2021: 7-12 - [c11]Christoph Wick, Christian Reul:
One-Model Ensemble-Learning for Text Recognition of Historical Printings. ICDAR (1) 2021: 385-399 - [c10]Konstantin Baierer, Andreas Büttner, Elisabeth Engl, Lena Hinrichsen, Christian Reul:
OCR-D & OCR4all: Two Complementary Approaches for Improved OCR of Historical Sources. HistoInformatics@JCDL 2021 - [i11]Christian Reul, Christoph Wick, Maximilian Nöth, Andreas Büttner, Maximilian Wehner, Uwe Springmann:
Mixed Model OCR Training on Historical Latin Script for Out-of-the-Box Recognition and Finetuning. CoRR abs/2106.07881 (2021) - 2020
- [b1]Christian Reul:
An Intelligent Semi-Automatic Workflow for Optical Character Recognition of Historical Printings (Ein intelligenter semi-automatischer Workflow für die OCR historischer Drucke). Würzburg University, Germany, 2020 - [j4]Christoph Wick, Christian Reul, Frank Puppe:
Calamari - A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition. Digit. Humanit. Q. 14(2) (2020) - [c9]Nico Balbach, Christian Reul, Frank Puppe:
Typisierte Varianz-Analyse von Texten. DHd 2020 - [c8]Maximilian Wehner, Michael Dahnke, Florian Landes, Robert Nasarek, Christian Reul:
OCR4all - Eine semi-automatische Open-Source-Software für die OCR historischer Drucke. DHd 2020
2010 – 2019
- 2019
- [c7]Christian Reul, Sebastian Göttel, Uwe Springmann, Christoph Wick, Kay-Michael Würzner, Frank Puppe:
Automatic Semantic Text Tagging on Historical Lexica by Combining OCR and Typography Classification: A Case Study on Daniel Sander's Wörterbuch der Deutschen Sprache. DATeCH 2019: 33-38 - [c6]Markus Bald, Vincenzo Damiani, Holger Essler, Björn Eyeselein, Christian Reul, Frank Puppe:
Korrektur von fehlerhaften OCR Ergebnissen durch automatisches Alignment mit Texten eines Korpus. DHd 2019 - [c5]Christian Reul, Uwe Springmann, Christoph Wick, Frank Puppe:
State of the Art Optical Character Recognition of 19th Century Fraktur Scripts using Open Source Engines. DHd 2019 - [i10]Christian Reul, Dennis Christ, Alexander Hartelt, Nico Balbach, Maximilian Wehner, Uwe Springmann, Christoph Wick, Christine Grundig, Andreas Büttner, Frank Puppe:
OCR4all - An Open-Source Tool Providing a (Semi-)Automatic OCR Workflow for Historical Printings. CoRR abs/1909.04032 (2019) - 2018
- [j3]Christian Reul, Uwe Springmann, Christoph Wick, Frank Puppe:
Improving OCR Accuracy on Early Printed Books by combining Pretraining, Voting, and Active Learning. J. Lang. Technol. Comput. Linguistics 33(1): 3-24 (2018) - [j2]Christoph Wick, Christian Reul, Frank Puppe:
Comparison of OCR Accuracy on Early Printed Books using the Open Source Engines Calamari and OCRopus. J. Lang. Technol. Comput. Linguistics 33(1): 79-96 (2018) - [j1]Uwe Springmann, Christian Reul, Stefanie Dipper, Johannes Baiter:
Ground Truth for training OCR engines on historical documents in German Fraktur and Early Modern Latin. J. Lang. Technol. Comput. Linguistics 33(1): 97-114 (2018) - [c4]Christian Reul, Uwe Springmann, Christoph Wick, Frank Puppe:
Improving OCR Accuracy on Early Printed Books by Utilizing Cross Fold Training and Voting. DAS 2018: 423-428 - [i9]Christoph Wick, Christian Reul, Frank Puppe:
Improving OCR Accuracy on Early Printed Books using Deep Convolutional Networks. CoRR abs/1802.10033 (2018) - [i8]Christian Reul, Uwe Springmann, Christoph Wick, Frank Puppe:
Improving OCR Accuracy on Early Printed Books by combining Pretraining, Voting, and Active Learning. CoRR abs/1802.10038 (2018) - [i7]Christoph Wick, Christian Reul, Frank Puppe:
Calamari - A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition. CoRR abs/1807.02004 (2018) - [i6]Uwe Springmann, Christian Reul, Stefanie Dipper, Johannes Baiter:
Ground Truth for training OCR engines on historical documents in German Fraktur and Early Modern Latin. CoRR abs/1809.05501 (2018) - [i5]Christian Reul, Uwe Springmann, Christoph Wick, Frank Puppe:
State of the Art Optical Character Recognition of 19th Century Fraktur Scripts using Open Source Engines. CoRR abs/1810.03436 (2018) - 2017
- [c3]Christian Reul, Uwe Springmann, Frank Puppe:
LAREX: A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books. DATeCH 2017: 137-142 - [c2]Christian Reul, Marco Dittrich, Martin Gruner:
Case Study of a highly automated Layout Analysis and OCR of an incunabulum: 'Der Heiligen Leben' (1488). DATeCH 2017: 155-160 - [i4]Christian Reul, Marco Dittrich, Martin Gruner:
Case Study of a highly automated Layout Analysis and OCR of an incunabulum: 'Der Heiligen Leben' (1488). CoRR abs/1701.07395 (2017) - [i3]Christian Reul, Uwe Springmann, Frank Puppe:
LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books. CoRR abs/1701.07396 (2017) - [i2]Christian Reul, Uwe Springmann, Christoph Wick, Frank Puppe:
Improving OCR Accuracy on Early Printed Books by utilizing Cross Fold Training and Voting. CoRR abs/1711.09670 (2017) - [i1]Christian Reul, Christoph Wick, Uwe Springmann, Frank Puppe:
Transfer Learning for OCRopus Model Training on Early Printed Books. CoRR abs/1712.05586 (2017) - 2016
- [c1]Christian Reul, Philipp Köberle, Nurcan Üçeyler, Frank Puppe:
Expectation-Driven Text Extraction from Medical Ultrasound Images. MIE 2016: 712-716
Coauthor Index
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