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» Inverse Kinematics Using Sequential Monte Carlo Methods
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IJCV
2008
188views more  IJCV 2008»
13 years 4 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
ICASSP
2011
IEEE
12 years 8 months ago
Sequential Monte Carlo method for parameter estimation in diffusion models of affinity-based biosensors
Estimation of the amounts of target molecules in realtime affinity-based biosensors is studied. The problem is mapped to inferring the parameters of a temporally sampled diffusio...
Manohar Shamaiah, Xiaohu Shen, Haris Vikalo
TSP
2008
91views more  TSP 2008»
13 years 4 months ago
A Sequential Monte Carlo Method for Motif Discovery
We propose a sequential Monte Carlo (SMC)-based motif discovery algorithm that can efficiently detect motifs in datasets containing a large number of sequences. The statistical di...
Kuo-ching Liang, Xiaodong Wang, Dimitris Anastassi...
BIBM
2007
IEEE
162views Bioinformatics» more  BIBM 2007»
13 years 11 months ago
Multiple Interacting Subcellular Structure Tracking by Sequential Monte Carlo Method
With the wide application of green fluorescent protein (GFP) in the study of live cells, there is a surging need for the computer-aided analysis on the huge amount of image seque...
Quan Wen, Jean Gao, Kate Luby-Phelps
SAC
2008
ACM
13 years 4 months ago
Particle methods for maximum likelihood estimation in latent variable models
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Adam M. Johansen, Arnaud Doucet, Manuel Davy