Growing hierarchical self-organizing map for images hierarchical clustering

Authors:
Bartłomiej M. Buczek;Paweł B. Myszkowski
Affiliations:
Applied Informatics Institute, Artifical Intelligence Department, Wrocław University of Technology, Wrocaw, Poland;Applied Informatics Institute, Artifical Intelligence Department, Wrocław University of Technology, Wrocaw, Poland
Venue:
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Year:
2011

Citing 7
Cited 0

Self-Organizing Maps

Self-Organizing Maps
Clustering validity checking methods: part II

ACM SIGMOD Record
A tutorial on spectral clustering

Statistics and Computing
Growing Hierarchical Self-Organizing Maps for Web Mining

WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
The MIR flickr retrieval evaluation

MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Automatic Image Annotation Using GHSOM

ICICIC '09 Proceedings of the 2009 Fourth International Conference on Innovative Computing, Information and Control
The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents approaches to hierarchical clustering of images using a GHSOM in application as image search engine. It is analysed some hierarchical clustering and SOMs variants. Experiments are based on benchmark ICPR and MIRFlickr image datasets. As quality of gained solution the external and the internal measures are analysed.