The SpaCEM3 software is dedicated to Spatial Clustering with EM and Markov Models. It proposes a variety of algorithms for supervised and unsupervised classification of multidimensional and spatially-located data. The main techniques use the EM algorithm for soft clustering and Markov Random Fields (MRF) for spatial modelling. The learning and inference parts are based on recent developments in mean field-like approximations. Its applications range from image segmentation (e.g. tissue detection in MRI, retrieval of planet surface properties from hyperspectral satellite images...) to gene clustering (e.g. biological module detection), remote sensing and mapping epidemics of ecological species.
References in zbMATH (referenced in 1 article )
Showing result 1 of 1.
- Marie Chavent, Vanessa Kuentz-Simonet, Amaury Labenne, J. Saracco: ClustGeo: an R package for hierarchical clustering with spatial constraints. (2017) arXiv
Further publications can be found at: http://spacem3.gforge.inria.fr/#Publications