How Carefully Designed Open Resource Sharing Can Help and Expand Document Analysis Research

Bart Lamiroy 1, 2 Daniel Lopresti 3 Hank Korth 3 Jeff Heflin 3
1 QGAR - Querying Graphics through Analysis and Recognition
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Making datasets available for peer reviewing of published document analysis methods or distributing large commonly used document corpora for benchmarking are extremely useful and sound practices and initiatives. This paper shows that they cover only a very tiny segment of the uses shared and commonly available research data may have. We develop a completely new paradigm for sharing and accessing common data sets, benchmarks and other tools that is based on a very open and free community based contribution model. The model is operational and has been implemented so that it can be tested on a broad scale. The new interactions that will arise from its use may spark innovative ways of conducting document analysis research on the one hand, but create very challenging interactions with other research domains as well.
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Gady Agam, Christian Viard-Gaudin. Document Recognition and Retrieval XVIII - DRR 2011, Jan 2011, San Francisco, United States. SPIE, 7874, 2011, Document Recognition and Retrieval XVIII, Part of the IST/SPIE 23rd Annual Symposium on Electronic Imaging. 〈10.1117/12.876483〉
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Bart Lamiroy, Daniel Lopresti, Hank Korth, Jeff Heflin. How Carefully Designed Open Resource Sharing Can Help and Expand Document Analysis Research. Gady Agam, Christian Viard-Gaudin. Document Recognition and Retrieval XVIII - DRR 2011, Jan 2011, San Francisco, United States. SPIE, 7874, 2011, Document Recognition and Retrieval XVIII, Part of the IST/SPIE 23rd Annual Symposium on Electronic Imaging. 〈10.1117/12.876483〉. 〈inria-00537035〉

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