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EMO
2009
Springer
159views Optimization» more  EMO 2009»
15 years 11 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel
SCALESPACE
2009
Springer
15 years 11 months ago
A Combined Segmentation and Registration Framework with a Nonlinear Elasticity Smoother
In this paper, we present a new non-parametric combined segmentation and registration method. The problem is cast as an optimization one, combining a matching criterion based on th...
Carole Le Guyader, Luminita A. Vese
147
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ICASSP
2008
IEEE
15 years 11 months ago
Efficient 4D motion compensated lossless compression of dynamic volumetric medical image data
Dynamic volumetric (four dimensional- 4D) medical images are typically huge in file size and require a vast amount of resources for storage and transmission purposes. In this pape...
Victor Sanchez, Panos Nasiopoulos, Rafeef Abugharb...
ICPR
2008
IEEE
15 years 11 months ago
Optimal feature weighting for the continuous HMM
We propose new Continuous Hidden Markov Model (CHMM) structure that integrates feature weighting component. We assume that each feature vector could include different subsets of f...
Oualid Missaoui, Hichem Frigui
IPPS
2006
IEEE
15 years 10 months ago
A calculus of functional BSP programs with projection
Bulk Synchronous Parallel ML (BSML) is an extension of the functional language Objective Caml to program Bulk Synchronous Parallel (BSP) algorithms. It is deterministic, deadlock ...
Frédéric Loulergue