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IJCV
2008
188views more  IJCV 2008»
13 years 7 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
ISCAS
2008
IEEE
122views Hardware» more  ISCAS 2008»
14 years 1 months ago
A nano-CMOS process variation induced read failure tolerant SRAM cell
— In a nanoscale technology, memory bits are highly susceptible to process variation induced read/write failures. To address the above problem, in this paper a new memory cell is...
Jawar Singh, Jimson Mathew, Saraju P. Mohanty, Dhi...
ICA
2012
Springer
12 years 3 months ago
New Online EM Algorithms for General Hidden Markov Models. Application to the SLAM Problem
In this contribution, new online EM algorithms are proposed to perform inference in general hidden Markov models. These algorithms update the parameter at some deterministic times ...
Sylvain Le Corff, Gersende Fort, Eric Moulines
ICASSP
2009
IEEE
14 years 2 months ago
Bayesian sparse image reconstruction for MRFM
In this paper, we propose a Bayesian model and a Monte Carlo Markov chain (MCMC) algorithm for reconstructing images that consist of only few non-zero pixels. An appropriate distr...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...
IPSN
2004
Springer
14 years 26 days ago
A probabilistic approach to inference with limited information in sensor networks
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Rahul Biswas, Sebastian Thrun, Leonidas J. Guibas