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ICASSP
2010
IEEE
15 years 7 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
192
Voted
ICMCS
2007
IEEE
167views Multimedia» more  ICMCS 2007»
15 years 6 months ago
A Probability Model for Image Annotation
Automatic image annotation is a promising solution to enable more effective image retrieval by keywords. Traditionally, statistical models for image auto-annotation predicate each...
Yong Ge, Richang Hong, Zhiwei Gu, Rong Zhang, Xiuq...
AMC
2006
79views more  AMC 2006»
15 years 6 months ago
VC-dimension and structural risk minimization for the analysis of nonlinear ecological models
The problem of distinguishing density-independent (DI) from density-dependent (DD) demographic time series is important for understanding the mechanisms that regulate populations ...
Giorgio Corani, Marino Gatto
NIPS
2003
15 years 8 months ago
Human and Ideal Observers for Detecting Image Curves
This paper compares the ability of human observers to detect target image curves with that of an ideal observer. The target curves are sampled from a generative model which speciï...
Alan L. Yuille, Fang Fang, Paul R. Schrater, Danie...
CSDA
2006
98views more  CSDA 2006»
15 years 6 months ago
GS-distributions: A new family of distributions for continuous unimodal variables
The choice of the best-suited statistical distribution for modeling data is not a trivial issue. Unless a sound theoretical background exists for selecting a particular distributi...
J. M. Muiño, Eberhard O. Voit, Albert Sorri...