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» Learning Mixtures of Gaussians
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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 12 days ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
TMM
2008
167views more  TMM 2008»
14 years 11 months ago
Mining Appearance Models Directly From Compressed Video
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...
Datong Chen, Qiang Liu, Mingui Sun, Jie Yang
ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
15 years 4 months ago
Blind separation of statistically independent signals with mixed sub-Gaussian and super-Gaussian probability distributions
— In the context of Independent Component Analysis (ICA), we propose a simple method for online estimation of activation functions in order to blindly separate instantaneous mixt...
Muhammad Tufail, Masahide Abe, Masayuki Kawamata
NN
2006
Springer
14 years 11 months ago
Missing data imputation through GTM as a mixture of t-distributions
The Generative Topographic Mapping (GTM) was originally conceived as a probabilistic alternative to the well-known, neural networkinspired, Self-Organizing Maps. The GTM can also ...
Alfredo Vellido
AVSS
2006
IEEE
15 years 5 months ago
Dynamic Control of Adaptive Mixture-of-Gaussians Background Model
We propose a method for create a background model in non-stationary scenes. Each pixel has a dynamic Gaussian mixture model. Our approach can automatically change the number of Ga...
Atsushi Shimada, Daisaku Arita, Rin-ichiro Taniguc...