75 search results - page 9 / 15 » Learning mixture models using a genetic version of the EM al... |
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
MICCAI
2005
Springer
14 years 8 months ago
2005
Springer
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...