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IPSN
2004
Springer
13 years 10 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
ISMAR
2006
IEEE
13 years 11 months ago
Online camera pose estimation in partially known and dynamic scenes
One of the key requirements of augmented reality systems is a robust real-time camera pose estimation. In this paper we present a robust approach, which does neither depend on ofï...
Gabriele Bleser, Harald Wuest, Didier Stricker
BMCBI
2006
130views more  BMCBI 2006»
13 years 5 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
BMCBI
2008
186views more  BMCBI 2008»
13 years 5 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells