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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… 
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Related topics

Related topics

43 relations
Automatic target recognitionBayesian networkCluster-weighted modelingCompositional data

Broader (2)

Cluster analysisMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2011
Highly Cited
2011
GMM based SPECT image classification for the diagnosis of Alzheimer's disease
Highly Cited
2008
Highly Cited
2008
Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium
Highly Cited
2005
Highly Cited
2005
Statistical modeling and conceptualization of natural images
Highly Cited
2005
Highly Cited
2005
Scalar dissipation rate at extinction and the effects of oxygen-enriched combustion
Highly Cited
2000
Highly Cited
2000
Extended Models and Tools for High-performance Part-of-speech
Statistical part-of-speech (POS) taggers achieve high accuracy and robustness when based on large scale manually tagged corpora… 
Highly Cited
1998
Highly Cited
1998
A method of combining multiple probabilistic classifiers through soft competition on different feature sets
Highly Cited
1996
Highly Cited
1996
Ammonia recycled percolation process for pretreatment of herbaceous biomass
An ammonia-based pretreatment method termed ammonia recycled percolation (ARP) was developed for pretreating herbaceous biomass… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Highly Cited
1994
Highly Cited
1994
Low-Temperature Cracking: Test Selection
This report describes the thermal stress restrained specimen test (TSRST), which was selected to evaluate the low-temperature… 
Highly Cited
1989
Highly Cited
1989
Practical Characteristics of Neural Network and Conventional Pattern Classifiers on Artificial and Speech Problems
Eight neural net and conventional pattern classifiers (Bayesian-unimodal Gaussian, k-nearest neighbor, standard back-propagation… 
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