62 search results - page 3 / 13 » A Beta-Mixture Model for Dimensionality Reduction, Sample Cl... |
ESANN
2006
13 years 7 months ago
2006
Spectral classification, segmentation and data reduction are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach which ...
BMCBI
2010
13 years 5 months ago
2010
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
TNN
2008
13 years 5 months ago
2008
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
IJCV
2008
13 years 5 months ago
2008
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
MICCAI
2000
Springer
13 years 9 months ago
2000
Springer
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...