Search Results for author: Michael Fop

Found 2 papers, 0 papers with code

A consensus-constrained parsimonious Gaussian mixture model for clustering hyperspectral images

no code implementations5 Mar 2024 Ganesh Babu, Aoife Gowen, Michael Fop, Isobel Claire Gormley

Here a consensus-constrained parsimonious Gaussian mixture model (ccPGMM) is proposed to label pixels in hyperspectral images using a model-based clustering approach.

Computational Efficiency Constrained Clustering

Unobserved classes and extra variables in high-dimensional discriminant analysis

no code implementations3 Feb 2021 Michael Fop, Pierre-Alexandre Mattei, Charles Bouveyron, Thomas Brendan Murphy

In supervised classification problems, the test set may contain data points belonging to classes not observed in the learning phase.

Classification General Classification +2

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