Title :
Growing mechanisms and cluster identification with TurSOM
Author :
Beaton, Derek ; Valova, Iren ; MacLean, Dan
Author_Institution :
James J Kaput Center for Res. & Innovation in Math. Educ., Univ. of Massachusetts Dartmouth, Fairhaven, MA, USA
Abstract :
TurSOM 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.
Keywords :
pattern clustering; self-organising feature maps; SOM algorithms; TurSOM; application driven approach; cluster identification; connection reorganization; image segmentation; neuron reorganization; robust algorithm; self-organizing map algorithm; Algorithm design and analysis; Clustering algorithms; Convergence; Image segmentation; Information science; Neural networks; Neurons; Pattern recognition; Resonance; Robustness;
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2009.5178750