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

Autor: Henry F. Korth, Bart Lamiroy, Daniel P. Lopresti, Jeff Heflin
Přispěvatelé: Querying Graphics through Analysis and Recognition (QGAR), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Knowledge representation, reasonning (ORPAILLEUR), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Computer Science & Engineering Department (CSE), Lehigh University [Bethlehem], Congressional appropriation administered through DARPA IPTO via Raytheon BBN Technologies., SPIE, Gady Agam, Christian Viard-Gaudin
Jazyk: angličtina
Rok vydání: 2011
Předmět:
Zdroj: Document Recognition and Retrieval XVIII-DRR 2011
Document Recognition and Retrieval XVIII-DRR 2011, SPIE, Jan 2011, San Francisco, United States. ⟨10.1117/12.876483⟩
DRR
DOI: 10.1117/12.876483⟩
Popis: ISBN : 9780819484116; International audience; 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.
Databáze: OpenAIRE