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ISBI
2004
IEEE
16 years 7 months ago
Statistical Surface-Based Morphometry Using a Non-Parametric Approach
We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests. In order to evaluate morphologicaldifferences of brain str...
Dimitrios Pantazis, Richard M. Leahy, Thomas E. Ni...
ICIP
1997
IEEE
16 years 8 months ago
An Optimization Approach to Unsupervised Hierarchical Texture Segmentation
In this paper we introduce a novel optimization framework for hierarchical data clustering and apply it to the problem of unsupervised texture segmentation. The proposed objective...
Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
IJON
2011
186views more  IJON 2011»
14 years 10 months ago
Discriminative structure selection method of Gaussian Mixture Models with its application to handwritten digit recognition
, Yunde Jia Model structure selection is currently an open problem in modeling data via Gaussian Mixture Models (GMM). This paper proposes a discriminative method to select GMM st...
Xuefeng Chen, Xiabi Liu, Yunde Jia
GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
15 years 11 months ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
EMMCVPR
2001
Springer
15 years 11 months ago
Designing the Minimal Structure of Hidden Markov Model by Bisimulation
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
Manuele Bicego, Agostino Dovier, Vittorio Murino