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Proceedings Paper

Hierarchical partition scheme in feature space for multivariate clustering
Author(s): Kai Zhang; Ming Tang; Hanqing Lu
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Paper Abstract

In this article we propose a hierarchical partition of the feature space based on statistical information on each dimension, and then use mean-shift to properly fuse the obtained super-cubics to reveal the genuine data structure. It not only greatly reduces calculation, but also provides a desirable priori knowledge for bandwidth selection.

Paper Details

Date Published: 25 September 2003
PDF: 6 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539882
Show Author Affiliations
Kai Zhang, Institute of Automation, CAS (China)
Ming Tang, Institute of Automation, CAS (China)
Hanqing Lu, Institute of Automation, CAS (China)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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