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What is Self-Organising Neural Networks

Encyclopedia of Artificial Intelligence
A class of artificial neural networks that are able to self-organize themselves to recognize patterns automatically without previous training preserving neighbourhood relations.
Published in Chapter:
Representing Non-Rigid Objects with Neural Networks
José García-Rodríguez (University of Alicante, Spain), Francisco Flórez-Revuelta (University of Alicante, Spain), and Juan Manuel García-Chamizo (University of Alicante, Spain)
Copyright: © 2009 |Pages: 7
DOI: 10.4018/978-1-59904-849-9.ch200
Abstract
Self-organising neural networks try to preserve the topology of an input space by means of their competitive learning. This capacity has been used, among others, for the representation of objects and their motion. In this work we use a kind of self-organising network, the Growing Neural Gas, to represent deformations in objects along a sequence of images. As a result of an adaptive process the objects are represented by a topology representing graph that constitutes an induced Delaunay triangulation of their shapes. These maps adapt the changes in the objects topology without reset the learning process.
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