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» Multivariate Information Bottleneck
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ICPR
2000
IEEE
15 years 4 months ago
Geometrically Guided Fuzzy C-Means Clustering for Multivariate Image Segmentation
Fuzzy C-means (FCM) clustering is an unsupervised clustering technique and is often used for the unsupervised segmentation of multivariate images. The segmentation of the image in...
J. C. Noordam, W. H. A. M. Van den Broek, Lutgarde...
CSDA
2006
142views more  CSDA 2006»
14 years 11 months ago
A Bayesian approach to bandwidth selection for multivariate kernel density estimation
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...
Xibin Zhang, Maxwell L. King, Rob J. Hyndman
ICCV
2009
IEEE
14 years 9 months ago
Shape analysis with multivariate tensor-based morphometry and holomorphic differentials
In this paper, we propose multivariate tensor-based surface morphometry, a new method for surface analysis, using holomorphic differentials; we also apply it to study brain anatom...
Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M. ...
CIVR
2007
Springer
192views Image Analysis» more  CIVR 2007»
15 years 5 months ago
Texture retrieval based on a non-parametric measure for multivariate distributions
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...
VISUALIZATION
1999
IEEE
15 years 4 months ago
Hierarchical Parallel Coordinates for Exploration of Large Datasets
Our ability to accumulate large, complex (multivariate) data sets has far exceeded our ability to effectively process them in search of patterns, anomalies, and other interesting ...
Ying-Huey Fua, Matthew O. Ward, Elke A. Rundenstei...