Incremental classification of invoice documents

Hatem Hamza 1 Yolande Belaïd 1 Abdel Belaïd 1 Bidyut Baran Chaudhuri 2
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LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper deals with incremental classification and its particular application to invoice classification. An improved version of an already existant incremental neural network called IGNG (Incremental Growing Neural Gas) is used for this purpose . This neural network tries to cover the space of data by adding or deleting neurons as data is fed to the system. The improved version of the IGNG, called I2GNG used local thresholds in order to create or delete neurons. Applied on invoice documents represented with graphs, I2GNG shows a recognition rate of 97.63%.
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Communication dans un congrès
19th International Conference on Pattern Recognition - ICPR 2008, Dec 2008, Tampa, United States. IEEE, 4 p., 2008, 〈10.1109/ICPR.2008.4761832〉
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https://hal.inria.fr/inria-00346942
Contributeur : Yolande Belaid <>
Soumis le : jeudi 5 février 2009 - 09:09:30
Dernière modification le : samedi 28 juillet 2018 - 14:54:01
Document(s) archivé(s) le : mardi 8 juin 2010 - 16:08:57

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Hatem Hamza, Yolande Belaïd, Abdel Belaïd, Bidyut Baran Chaudhuri. Incremental classification of invoice documents. 19th International Conference on Pattern Recognition - ICPR 2008, Dec 2008, Tampa, United States. IEEE, 4 p., 2008, 〈10.1109/ICPR.2008.4761832〉. 〈inria-00346942〉

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