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» Bayesian Calibration for Monte Carlo Localization
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HUC
2009
Springer
14 years 5 days ago
Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors
In this paper we describe a new Bayesian estimation approach for simultaneous mapping and localization for pedestrians based on odometry with foot mounted inertial sensors. When s...
Patrick Robertson, Michael Angermann, Bernhard Kra...
IJRR
2010
185views more  IJRR 2010»
13 years 6 months ago
FISST-SLAM: Finite Set Statistical Approach to Simultaneous Localization and Mapping
The solution to the problem of mapping an environment and at the same time using this map to localize (the simultaneous localization and mapping, SLAM, problem) is a key prerequis...
Bharath Kalyan, K. W. Lee, W. Sardha Wijesoma
IPPS
2010
IEEE
13 years 5 months ago
On the parallelisation of MCMC-based image processing
Abstract--The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov C...
Jonathan M. R. Byrd, Stephen A. Jarvis, Abhir H. B...
JCB
2008
159views more  JCB 2008»
13 years 7 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 11 days ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel