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» Density Estimation by Mixture Models with Smoothing Priors
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SIAMSC
2011
219views more  SIAMSC 2011»
14 years 6 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
ICIP
2000
IEEE
16 years 1 months ago
Normalized Training for HMM-Based Visual Speech Recognition
This paper presents an approach to estimating the parameters of continuous density HMMs for visual speech recognition. One of the key issues of image-based visual speech recogniti...
Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamur...
99
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IDA
2009
Springer
15 years 4 months ago
Image Source Separation Using Color Channel Dependencies
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
Koray Kayabol, Ercan E. Kuruoglu, Bülent Sank...
VDA
2010
185views Visualization» more  VDA 2010»
15 years 2 months ago
Visualizing multidimensional data through granularity-dependent spatialization
Spatialization is a special kind of visualization that projects multidimensional data into low-dimensional representational spaces by making use of spatial metaphors. Spatializati...
Sofia Kontaxaki, Eleni Tomai, Margarita Kokla, Mar...
CDC
2008
IEEE
132views Control Systems» more  CDC 2008»
15 years 1 months ago
Global symplectic uncertainty propagation on SO(3)
Abstract-- This paper introduces a global uncertainty propagation scheme for the attitude dynamics of a rigid body, through a combination of numerical parametric uncertainty techni...
Taeyoung Lee, Melvin Leok, N. Harris McClamroch