Results 21 to 30 of about 203,616 (288)
Optical Recognition Assisted Transcription with Transkribus: The Experiment concerning Eugène Wilhelm's Personal Diary (1885-1951) Transcription assistée par reconnaissance optique avec Transkribus : L’expérience du journal intime d’Eugène Wilhelm (1885-1951) [PDF]
Journal of Data Mining and Digital Humanities, 2020 This article proposes use the Transkribus software to report on a "user experiment" in a French-speaking context. It is based on the semi-automated transcription project using the diary of the jurist Eugène Wilhelm (1866-1951).
Régis Schlagdenhauffen
doaj
Bielschowsky head-tilt test-I. Ocular counterrolling and Bielschowsky head-tilt test in 23 cases of superior oblique palsy [PDF]
, 1985 We have measured the amplitude of ocular counterrolling (OCR) and the change in vertical deviation in the Bielschowsky head-tilt test (BHT) in 23 cases of unilateral superior oblique palsy.
Crone, R.A. +4 more
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International Journal for Research in Applied Science and Engineering Technology, 2022 Abstract: As we are familiar that there are many languages around the world, which many of us might even not be aware of but due to globalization and digitalization we have got to see and learn many languages. During those days of colonization, English became an integral part of many people’s language and still continues to be in dominance.
Kavita Pathak +3 more
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Improving OCR Accuracy on Early Printed Books by combining Pretraining, Voting, and Active Learning [PDF]
, 2018 We combine three methods which significantly improve the OCR accuracy of OCR models trained on early printed books: (1) The pretraining method utilizes the information stored in already existing models trained on a variety of typesets (mixed models ...
Puppe, Frank +3 more
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, 2022 A novel scene text recognizer based on Vision-Language Transformer (VLT) is presented. Inspired by Levenshtein Transformer in the area of NLP, the proposed method (named Levenshtein OCR, and LevOCR for short) explores an alternative way for automatically transcribing textual content from cropped natural images.
Da, Cheng, Wang, Peng, Yao, Cong
openaire +2 more sources
The Page-Building a Pennsylvania German Thesaurus through the Correction of OCR Errors
Iperstoria, 2018 The aim of our project is to build an online Thesaurus of Pennsylvania German. This North American minority language has been in contact with American English ever since its emergence around 1800 and is still lacking a received standard, producing thus ...
Camilla Balsamo, Barbara Hans-Bianchi
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Automatic Transcription of Organ Tablature Music Notation with Deep Neural Networks
Transactions of the International Society for Music Information Retrieval, 2021 Organ tablature music notation differs considerably in structure and form from the music notation used today. The manual transcription of organ tablature compositions to modern music notation is time-consuming and often prone to errors. In this paper, we
Daniel Schneider +4 more
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Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage, 2019 Various research projects were concerned with the development and adaptation of methods for OCR specifically for historical printed documents (cf. METAe [20], IMPACT [1], eMOP [9]). However, these initiatives have ended before the wide adoption of deep neural networks and, despite the various project's achievements, there remains a lack of OCR software
Neudecker, Clemens +6 more
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Ground Truth for training OCR engines on historical documents in German Fraktur and Early Modern Latin [PDF]
, 2018 In this paper we describe a dataset of German and Latin \textit{ground truth} (GT) for historical OCR in the form of printed text line images paired with their transcription.
Baiter, Johannes +3 more
core +3 more sources
A tool for facilitating OCR postediting in historical documents [PDF]
, 2020 Optical character recognition (OCR) for historical documents is a complex procedure subject to a unique set of material issues, including inconsistencies in typefaces and low quality scanning. Consequently, even the most sophisticated OCR engines produce
Aboomar, Mohammad +4 more
core +1 more source