GWENN-SS: a simple semi-supervised nearest-neighbor density-based classification method with application to hyperspectral images

A generic framework is proposed to demonstrate that two ubiquitous image analysis methods, namely supervised classification and representation learning, can be unified into a unique

plastic matter, carbonate, clay, vegetation (dark green, dense green, sparse green, stressed), house1. roof / tile, asphalt, vehicle / paint / metal surface and

Mixmod is a well-established software package for fitting a mixture model of mul- tivariate Gaussian or multinomial probability distribution functions to a given data set with either

Pour répondre à ces questions, l’ensemble des acteurs du monde agricole (Organisations Professionnelles, Chambre d’Agriculture, Interprofessions, Enseignement

Class specific covariance matrices are regularized by a probabilistic model which is based on the data living in a subspace spanned by the p first principal components.. The inverse

dominated by mixed pixels, even if the associated ground-truth information is only available in full-pixel form. Hence, the use of spectral unmixing presents distinctive features

neighborhood effects on walking behavior tend to be greater than self-selection

récent. En outre, nous n’avons pas affaire à un récit fictionnel dont l’auteur essaierait de nous faire croire que nous sommes physiquement présents dans