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Strategies for Getting the Highest Likelihood in Mixture Models
We compare simple strategies to get maximum likelihood parameter estimation in mixture models when using the EM algorithm. All considered strategies are aiming to... -
Unsupervised amplitude and texture classification of SAR images with multinom...
International audience -
Unsupervised amplitude and texture based classification of SAR images with mu...
We combine both amplitude and texture statistics of the Synthetic Aperture Radar (SAR) images for classification purpose. We use Nakagami density to model the class... -
A Comparison of Texture and Amplitude based Unsupervised SAR Image Classifica...
International audience -
Model-based Cluster and Discriminant Analysis with the MIXMOD software
The mixmod (mixture modelling) software fits mixture models to a given data set with a density estimation, a clustering or a discriminant analysis purpose. A large... -
Unsupervised Classification of SAR Images Using Hierarchical Agglomeration an...
International audience
