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1
Raising the Titanic: Prospects for Reviving the Century Dictionary ...
Triggs, Jeffery A.. - : Rutgers University, 2022
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2
Exploiting Script Similarities to Compensate for the Large Amount of Data in Training Tesseract LSTM: Towards Kurdish OCR
In: Applied Sciences ; Volume 11 ; Issue 20 (2021)
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3
Reconocimiento automático de un censo histórico impreso sin recursos lingüísticos
Anitei, Dan. - : Universitat Politècnica de València, 2021
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4
Quality Measurement for Optical Character Recognition without ground truth data ...
Weltevrede, Mike. - : Zenodo, 2020
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5
Quality Measurement for Optical Character Recognition without ground truth data ...
Weltevrede, Mike. - : Zenodo, 2020
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6
AI in gastronomic tourism ...
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7
Improving the recognition of Dutch Gothic machine print, at four levels in the processing pipeline, in four days ...
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8
AI in gastronomic tourism ...
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9
Improving the recognition of Dutch Gothic machine print, at four levels in the processing pipeline, in four days ...
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10
NAT: Noise-Aware Training for Robust Neural Sequence Labeling
In: Fraunhofer IAIS (2020)
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11
OPTICAL CHARACTER RECOGNITION APPLIED TO ANDROID-BASED BILINGUAL TRANSLATOR APPLICATION (ENGLISH AND INDONESIAN) TO SIGN LANGUAGE ...
Pratama, Juan Adhiasta. - : Zenodo, 2019
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12
OPTICAL CHARACTER RECOGNITION APPLIED TO ANDROID-BASED BILINGUAL TRANSLATOR APPLICATION (ENGLISH AND INDONESIAN) TO SIGN LANGUAGE ...
Pratama, Juan Adhiasta. - : Zenodo, 2019
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13
Bilingual text detection in natural scene images using invariant moments
Abstract: In today's world, there have been lots of unique optical character recognition systems. One drawback of these systems is that they cannot work effectively on natural scene images where the text is not only subject to different orientations, lightning, and background but can be of multiple scripts as well. The paper, proposes a state of the art algorithm to detect texts of different dialects and orientations in an image. The whole text detection pipeline is divided into two parts. First, extraction of probable text regions in an image is performed based on a combination of statistical filters, which results in a high recall. These regions are then fed to an Artificial Neural Networks (ANN) based classifier which classifies whether the proposed regions are text or non-text, which increases the overall precision. The validity of the algorithm is verified on the most challenging bilingual text detection dataset MSRA-TD500 and a promising F1 score of 0.67 is reported.
Keyword: bilingualism; neural networks (computer science); optical character recognition; XXXXXX - Unknown
URL: https://hdl.handle.net/1959.7/uws:56250
https://doi.org/10.3233/JIFS-190339
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14
Wenn Algorithmen Zeitschriften lesen - vom Mehrwert automatisierter Textanreicherung ...
Wanger, Regina; Gasser, Michael. - : ETH Zurich, 2018
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15
Generating a training corpus for OCR post-correction using encoder-decoder model
In: Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers) ; International Joint Conference on Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-01831147 ; International Joint Conference on Natural Language Processing, Nov 2017, Taipei, Taiwan ; https://www.aclweb.org/anthology/I17-1101 (2017)
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16
Corpus linguistics for History ... : the methodology of investigating place-name discourses in digitised nineteenth-century newspapers ...
Joulain, Amelia Tahirih. - : Lancaster University, 2017
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17
Radical Recognition in Off-Line Handwritten Chinese Characters Using Non-Negative Matrix Factorization
In: Senior Projects Spring 2016 (2016)
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18
Using SMT for OCR error correction of historical texts
In: Afli, Haithem orcid:0000-0002-7449-4707 , Qui, Zhengwei, Way, Andy orcid:0000-0001-5736-5930 and Sheridan, Páraic (2016) Using SMT for OCR error correction of historical texts. In: Tenth International Conference on Language Resources and Evaluation (LREC 2016), 23-28 May 2016, Portorož, Slovenia. ISBN 978-2-9517408-9-1 (2016)
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19
Augmented reality applied to language translation
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20
Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection ...
Bloodgood, Michael; Strauss, Benjamin. - : Digital Repository at the University of Maryland, 2016
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