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TKDE
2010
182views more  TKDE 2010»
15 years 4 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
CVPR
2009
IEEE
1942views Computer Vision» more  CVPR 2009»
17 years 1 months ago
Learning Similarity Measure for Multi-Modal 3D Image Registration
Multi-modal image registration is a challenging problem in medical imaging. The goal is to align anatomically identical structures; however, their appearance in images acquired wit...
Bernhard Schölkopf, Daewon Lee, Florian Stein...
ECCV
2002
Springer
16 years 8 months ago
Stereo Matching Using Belief Propagation
In this paper, we formulate the stereo matching problem as a Markov network consisting of three coupled Markov random fields (MRF's). These three MRF's model a smooth fie...
Jian Sun, Heung-Yeung Shum, Nanning Zheng
MICCAI
2007
Springer
16 years 7 months ago
Shape Analysis Using a Point-Based Statistical Shape Model Built on Correspondence Probabilities
A fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. Often, homologies between po...
Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Heinz...
CEC
2009
IEEE
16 years 1 months ago
Particle Swarm CMA Evolution Strategy for the optimization of multi-funnel landscapes
— We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES...
Christian L. Müller, Benedikt Baumgartner, Iv...