HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Multi-Topographic Neural Network Communication and Generalization for Multi-Viewpoint Analysis

Shadi Al Shehabi 1 Jean-Charles Lamirel 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper presents a new generic multitopographic neural network model whose main area of application is clustering and knowledge extraction tasks on documentary data. The most powefull features of this model are its generalization mechanism and its mechanism of communication between topographies. This paper shows how these mechanisms can be exploited within the framework of the SOM and NG models. An evaluation of the generalization mechanism based on original quality and propagation coherency measures is also proposed. A secondary result of this evaluation is to proof that the generalization mechanism could significantly reduce the wellknown border effect of the SOM map.
Complete list of metadata

Contributor : Shadi Al Shehabi Connect in order to contact the contributor
Submitted on : Tuesday, November 29, 2005 - 9:32:57 AM
Last modification on : Friday, February 4, 2022 - 3:30:44 AM
Long-term archiving on: : Friday, April 2, 2010 - 11:08:27 PM


  • HAL Id : inria-00000842, version 1



Shadi Al Shehabi, Jean-Charles Lamirel. Multi-Topographic Neural Network Communication and Generalization for Multi-Viewpoint Analysis. International Joint Conference on Neural Networks - IJCNN'05, Jul 2005, Montréal/Canada, pp.1564--1569. ⟨inria-00000842⟩



Record views


Files downloads