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Document Logical Structure Analysis Based on Perceptive Cycles

Yves Rangoni 1 Abdel Belaïd 1
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LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper describes a Neural Network (NN) approach for logical document structure extraction. In this NN architecture, called Transparent Neural Network (TNN), the document structure is stretched along the layers, allowing an interpretation decomposition from physical (NN input) to logical (NN output) level. The intermediate layers represent successive interpretation steps. Each neuron is apparent and associated to a logical element. The recognition proceeds by repetitive perceptive cycles propagating the information through the layers. In case of low recognition rate, an enhancement is achieved by error backpropagation leading to correct or pick up a more adapted input feature subset. Several feature subsets are created using a modified filter method. The first experiments performed on scientific documents are encouraging.
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https://hal.inria.fr/inria-00112229
Contributor : Abdel Belaid <>
Submitted on : Friday, December 1, 2006 - 5:00:25 PM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 9:51:06 PM

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Yves Rangoni, Abdel Belaïd. Document Logical Structure Analysis Based on Perceptive Cycles. 7th International IAPR Workshop on Document Analysis Systems - DAS 2006, Feb 2006, Nelson, New Zealand. pp.118 - 128, ⟨10.1007/11669487_11⟩. ⟨inria-00112229⟩

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