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ICPR
2002
IEEE
14 years 9 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
AAAI
2006
13 years 10 months ago
Hard Constrained Semi-Markov Decision Processes
In multiple criteria Markov Decision Processes (MDP) where multiple costs are incurred at every decision point, current methods solve them by minimising the expected primary cost ...
Wai-Leong Yeow, Chen-Khong Tham, Wai-Choong Wong
CF
2010
ACM
14 years 1 months ago
Interval-based models for run-time DVFS orchestration in superscalar processors
We develop two simple interval-based models for dynamic superscalar processors. These models allow us to: i) predict with great accuracy performance and power consumption under va...
Georgios Keramidas, Vasileios Spiliopoulos, Stefan...
CVPR
2008
IEEE
13 years 8 months ago
Meshless deformable models for LV motion analysis
We propose a novel meshless deformable model for in vivo cardiac left ventricle (LV) 3D motion estimation. As a relatively new technology, tagged MRI (tMRI) provides a direct and ...
Xiaoxu Wang, Dimitris N. Metaxas, Ting Chen, Leon ...
IPSN
2005
Springer
14 years 2 months ago
The sensor selection problem for bounded uncertainty sensing models
We address the problem of selecting sensors so as to minimize the error in estimating the position of a target. We consider a generic sensor model where the measurements can be in...
Volkan Isler, Ruzena Bajcsy