Growing mechanisms and cluster identification with TurSOM

Authors:
Derek Beaton;Iren Valova;Dan MacLean
Affiliations:
James J Kaput Center for Research and Innovation in Mathematics Education, University of Massachusetts Dartmouth, Fairhaven, MA;Department of Computer and Information Science, University of Massachusett Dartmouth, North Dartmouth, MA;Computer and Information Science Department, University of Massachusett Dartmouth, North Dartmouth, MA
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 8
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Abstract

TurSOM [1] is a novel self-organizing map algorithm with the capability of connection reorganization, not just neuron reorganization. This behavior facilitates the ability to map distinct patterns in a given input space. Multiple networks exist, and operate independently. This work presents an application driven approach, based on the theoretical and empirical work of previous TurSOM experiments. TurSOM is a highly robust algorithm, designed to eliminate the need for post processing methods of cluster identification using SOM algorithms. One of the applications TurSOM is suitable for, but obviously not limited to, is image segmentation, as it is demonstrated in this work.