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Mixture model

Known as: Contaminated Gaussian noise, Mixture coefficient, Contaminated Gaussian 
In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without… Expand
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Papers overview

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Highly Cited
2007
Highly Cited
2007
Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite… Expand
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Highly Cited
2004
Highly Cited
2004
Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient… Expand
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Highly Cited
2004
Highly Cited
2004
  • Z. Zivkovic
  • Proceedings of the 17th International Conference…
  • 2004
  • Corpus ID: 206845371
Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient… Expand
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Highly Cited
2002
Highly Cited
2002
This paper proposes an unsupervised algorithm for learning a finite mixture model from multivariate data. The adjective… Expand
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Highly Cited
2000
Highly Cited
2000
Reynolds, Douglas A., Quatieri, Thomas F., and Dunn, Robert B., Speaker Verification Using Adapted Gaussian Mixture Models… Expand
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Highly Cited
1999
Highly Cited
1999
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction", or… Expand
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Highly Cited
1999
Highly Cited
1999
In a Bayesian mixture model it is not necessary a priori to limit the number of components to be finite. In this paper an… Expand
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Highly Cited
1995
Highly Cited
1995
This paper introduces and motivates the use of Gaussian mixture models (GMM) for robust text-independent speaker identification… Expand
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Highly Cited
1993
Highly Cited
1993
Consider a random sample on variables X1, …, Xv with some values of Xv missing. Selection models specify the distribution of X1… Expand
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Highly Cited
1988
Highly Cited
1988
General Introduction Introduction History of Mixture Models Background to the General Classification Problem Mixture Likelihood… Expand
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