Typical problems in the analysis of data sets like time-series or images crucially rely on the extraction of primitive features based on segmentation. Variational approaches are a popular and convenient framework in which such problems can be studied. We focus on Potts models as simple nontrivial instances. The discussion proceeds along two data sets from brain mapping and functional genomics.
|Title of host publication||Innovations in Classification, Data Science, and Information Systems (Proceedings of the 27th Annual Conference of the Gesellschaft für Klassifikation e.V., Cottbus, Germany, March 12-14, 2003), Part II|
|Editors||D. Baier, K.D. Warnecke|
|Place of Publication||Berlin|
|Number of pages||9|
|ISBN (Print)||3-540-23221-4, 978-3-540-23221-6|
|Publication status||Published - 2005|
|Name||Studies in Classification, Data Analysis, and Knowledge Organization|