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Published in: International Journal on Document Analysis and Recognition (IJDAR) 1/2020

21-09-2019 | Original Paper

Document analysis systems that improve with use

Author: George Nagy

Published in: International Journal on Document Analysis and Recognition (IJDAR) | Issue 1/2020

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Abstract

Document analysis tasks for which representative labeled training samples are available have been largely solved. The next frontier is coping with hitherto unseen formats, unusual typefaces, idiosyncratic handwriting and imperfect image acquisition. Adaptive and style-constrained classification methods can overcome some expected variability, but human intervention will remain necessary in many tasks. Interactive pattern recognition includes data exploration and active learning as well as access to stored documents. The principle of “green interaction” is to make use of every intervention to reduce the likelihood that the automated system will make the same mistake again and again. Some of these techniques may pop up in forthcoming personal camera-based memex-like applications that will have a far broader range of input documents and scene text than the current, successful but highly specialized, systems for patents, postal addresses, bank checks and books.

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Metadata
Title
Document analysis systems that improve with use
Author
George Nagy
Publication date
21-09-2019
Publisher
Springer Berlin Heidelberg
Published in
International Journal on Document Analysis and Recognition (IJDAR) / Issue 1/2020
Print ISSN: 1433-2833
Electronic ISSN: 1433-2825
DOI
https://doi.org/10.1007/s10032-019-00344-x

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