55 citations · 136 across the 8 of their papers we have counts for
4 papers · 1 filter
Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images
Adrien Lagrange, Mathieu Fauvel, Stéphane May +1
Hyperspectral unmixing aims at identifying a set of elementary spectra and the corresponding mixture coefficients for each pixel of an image. As the elementary spectra correspond t…
Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis
Adrien Lagrange, Mathieu Fauvel, Stéphane May +2
Supervised classification and representation learning are two widely used classes of methods to analyze multivariate images. Although complementary, these methods have been scarcel…
Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning
Adrien Lagrange, Mathieu Fauvel, Stéphane May +1
Within a supervised classification framework, labeled data are used to learn classifier parameters. Prior to that, it is generally required to perform dimensionality reduction via…
Fast forward feature selection for the nonlinear classification of hyperspectral images
Mathieu Fauvel, Clement Dechesne, Anthony Zullo +1
A fast forward feature selection algorithm is presented in this paper. It is based on a Gaussian mixture model (GMM) classifier. GMM are used for classifying hyperspectral images.…