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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 1, March 2014
  4. Interactive handwriting recognition with limited user effort
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 4, December 2014
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 3, September 2014
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 2, June 2014
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17, Issue 1, March 2014
Large scale document image retrieval by automatic word annotation
Text recognition in multimedia documents: a study of two neural-based OCRs using and avoiding character segmentation
A keyword retrieval system for historical Mongolian document images
Interactive handwriting recognition with limited user effort
Integrating vocabulary clustering with spatial relations for symbol recognition
Discrimination of similar characters using nonlinear normalization based on regional importance measure
An over-segmentation method for single-touching Chinese handwriting with learning-based filtering
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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Interactive handwriting recognition with limited user effort

Content Provider Springer Nature Link
Author Serra, Nicolás Giménez, Adrià Civera, Jorge Sanchis, Alberto Juan, Alfons
Copyright Year 2013
Abstract Transcription of handwritten text in (old) documents is an important, time-consuming task for digital libraries. Although post-editing automatic recognition of handwritten text is feasible, it is not clearly better than simply ignoring it and transcribing the document from scratch. A more effective approach is to follow an interactive approach in which both the system is guided by the user, and the user is assisted by the system to complete the transcription task as efficiently as possible. Nevertheless, in some applications, the user effort available to transcribe documents is limited and fully supervision of the system output is not realistic. To circumvent these problems, we propose a novel interactive approach which efficiently employs user effort to transcribe a document by improving three different aspects. Firstly, the system employs a limited amount of effort to solely supervise recognised words that are likely to be incorrect. Thus, user effort is efficiently focused on the supervision of words for which the system is not confident enough. Secondly, it refines the initial transcription provided to the user by recomputing it constrained to user supervisions. In this way, incorrect words in unsupervised parts can be automatically amended without user supervision. Finally, it improves the underlying system models by retraining the system from partially supervised transcriptions. In order to prove these statements, empirical results are presented on two real databases showing that the proposed approach can notably reduce user effort in the transcription of handwritten text in (old) documents.
Starting Page 47
Ending Page 59
Page Count 13
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 17
Issue Number 1
e-ISSN 14332825
Language English
Publisher Springer Berlin Heidelberg
Publisher Date 2013-03-19
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Handwriting recognition Computer-assisted text transcription Active learning Semi-supervised learning Confidence measures Constrained Viterbi search Image Processing and Computer Vision Pattern Recognition
Content Type Text
Resource Type Article
Subject Computer Science Applications Computer Vision and Pattern Recognition Software
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