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ICPPW
2007
IEEE
14 years 1 months ago
Cooperative Localization with Pre-Knowledge Using Bayesian Network for Wireless Sensor Networks
Obtaining location information by localization schemes for sensor nodes makes applications of wireless sensor networks (WSNs) more meaningful. Most of localization schemes only us...
Shih-Hsiang Lo, Chun-Hsien Wu, Yeh-Ching Chung
SMA
1993
ACM
107views Solid Modeling» more  SMA 1993»
13 years 11 months ago
Relaxed parametric design with probabilistic constraints
: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs ...
Yacov Hel-Or, Ari Rappoport, Michael Werman
ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 7 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
TOSN
2011
116views more  TOSN 2011»
13 years 2 months ago
A model framework for greedy routing in a sensor network with a stochastic power scheme
A stochastic model is formulated and analyzed to study the advancements of messages under greedy routing in a sensor network with a power-saving scheme. The aim of this model is g...
Holger Paul Keeler, Peter G. Taylor
MICCAI
2009
Springer
13 years 12 months ago
Bayesian Maximal Paths for Coronary Artery Segmentation from 3D CT Angiograms
We propose a recursive Bayesian model for the delineation of coronary arteries from 3D CT angiograms (cardiac CTA) and discuss the use of discrete minimal path techniques as an eï¬...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...