11 citations · 11 across the 1 of their papers we have counts for
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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…