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» On Fitting Mixture Models
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171
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ICPR
2000
IEEE
16 years 8 months ago
On Gaussian Radial Basis Function Approximations: Interpretation, Extensions, and Learning Strategies
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...
Mário A. T. Figueiredo
192
Voted
ECCV
2010
Springer
15 years 8 months ago
Object of Interest Detection by Saliency Learning
In this paper, we present a method for object of interest detection. This method is statistical in nature and hinges in a model which combines salient features using a mixture of l...
ICMCS
2005
IEEE
169views Multimedia» more  ICMCS 2005»
16 years 19 days ago
Dynamic language model adaptation using latent topical information and automatic transcripts
This paper considers dynamic language model adaptation for Mandarin broadcast news recognition. Both contemporary newswire texts and in-domain automatic transcripts were exploited...
Berlin Chen
188
Voted
ICASSP
2009
IEEE
16 years 1 months ago
Humming-based human verification and identification
This paper considers humming-based human verification and identification systems. Humming of a target person is modeled as a Gaussian mixture model, and the matching score betwe...
Minho Jin, Jaewook Kim, Chang D. Yoo
173
Voted
ICASSP
2008
IEEE
16 years 1 months ago
Towards the use of full covariance models for missing data speaker recognition
This work investigates the use of missing data techniques for noise robust speaker identification. Most previous work in this field relies on the diagonal covariance assumption ...
Marco Kühne, Daniel Pullella, Roberto Togneri...