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Conference papers

An end-to-end administrative document analysis system

Hatem Hamza 1 Yolande Belaïd 1 Abdel Belaïd 1 Bidyut B. Chaudhuri 2
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper presents an end-to-end administrative document analysis system. This system uses case-based reasoning in order to process documents from known and unknown classes. For each document, the system retrieves the nearest processing experience in order to analyze and interpret the current document. When a complete analysis is done, this document needs to be added to the document database. This requires an incremental learning process in order to take into account every new information, without losing the previous learnt ones. For this purpose, we proposed an improved version of an already existing neural network called Incremental Growing Neural Gas. Applied on documents learning and classification, this neural network reaches a recognition rate of 97.63%.
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Submitted on : Friday, December 12, 2008 - 4:14:54 PM
Last modification on : Friday, February 26, 2021 - 3:28:07 PM
Long-term archiving on: : Tuesday, June 8, 2010 - 4:04:12 PM


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  • HAL Id : inria-00346019, version 1



Hatem Hamza, Yolande Belaïd, Abdel Belaïd, Bidyut B. Chaudhuri. An end-to-end administrative document analysis system. The Eighth IAPR International Workshop on Document Analysis Systems - DAS 2008, Sep 2008, Nara, Japan. pp.175-182. ⟨inria-00346019⟩



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