Thomas Roth-Berghofer
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Thomas Roth-Berghofer has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Andreas Dengel
German Research Center for Artificial Intelligence (DFKI)
1 shared publication - Federico Raue
German Research Center for Artificial Intelligence (DFKI)
1 shared publication - Marcus Liwicki
Kaiserslautern University
1 shared publication - Marcus Liwicki
German Research Ctr. for Articial Intelligence (Germany)
1 shared publication - Martin Atzmueller
Tilburg University
1 shared publication Mayce Al Azawi
Technische Univ. Kaiserslautern (Germany)
1 shared publication
Latest Publications
- 13 August 2016
- Published by Springer Nature in Lecture Notes in Computer Science
- p. 347-354
Symbolic Association Using Parallel Multilayer Perceptron
- 13 August 2016
- Published by Springer Nature in Lecture Notes in Computer Science
- p. 347-354
Symbolic Association Using Parallel Multilayer Perceptron
- 4 February 2013
- Published by SPIE-Intl Soc Optical Eng
- Vol. 8658, 865818
WFST-based ground truth alignment for difficult historical documents with text modification and layout variations
This work proposes several approaches that can be used for generating correspondences between real scanned books and their transcriptions which might have different modifications and layout variations, also taking OCR errors into account. Our approaches for the alignment between the manuscript and the transcription are based on weighted finite state transducers (WFST). In particular, we propose adapted WFSTs to represent the transcription to be aligned with the OCR lattices. The character-level alignment has edit rules to allow edit operations (insertion, deletion, substitution). Those edit operations allow the transcription model to deal with OCR segmentation and recognition errors, and also with the task of aligning with different text editions. We implemented an alignment model with a hyphenation model, so it can adapt the non-hyphenated transcription. Our models also work with Fraktur ligatures, which are typically found in historical Fraktur documents. We evaluated our approach on Fraktur documents from Wanderungen durch die Mark Brandenburg" volumes (1862-1889) and observed the performance of those models under OCR errors. We compare the performance of our model for three different scenarios: having no information about the correspondence at the word (i), line (ii), sentence (iii) or page (iv) level.
- 4 February 2013
- Published by SPIE-Intl Soc Optical Eng
- Vol. 8658, 865818
WFST-based ground truth alignment for difficult historical documents with text modification and layout variations
This work proposes several approaches that can be used for generating correspondences between real scanned books and their transcriptions which might have different modifications and layout variations, also taking OCR errors into account. Our approaches for the alignment between the manuscript and the transcription are based on weighted finite state transducers (WFST). In particular, we propose adapted WFSTs to represent the transcription to be aligned with the OCR lattices. The character-level alignment has edit rules to allow edit operations (insertion, deletion, substitution). Those edit operations allow the transcription model to deal with OCR segmentation and recognition errors, and also with the task of aligning with different text editions. We implemented an alignment model with a hyphenation model, so it can adapt the non-hyphenated transcription. Our models also work with Fraktur ligatures, which are typically found in historical Fraktur documents. We evaluated our approach on Fraktur documents from Wanderungen durch die Mark Brandenburg" volumes (1862-1889) and observed the performance of those models under OCR errors. We compare the performance of our model for three different scenarios: having no information about the correspondence at the word (i), line (ii), sentence (iii) or page (iv) level.
- 29 October 2010
- Published by Springer Nature
- p. 273-278
The Mining and Analysis Continuum of Explaining Uncovered
- 29 October 2010
- Published by Springer Nature
- p. 273-278
The Mining and Analysis Continuum of Explaining Uncovered
- 17 November 2009
- Published by Elsevier in Artificial Intelligence
- Vol. 174 (2) , 143-144
A review of the textbook Graph-based Knowledge Representation
- 17 November 2009
- Published by Elsevier in Artificial Intelligence
- Vol. 174 (2) , 143-144
A review of the textbook Graph-based Knowledge Representation