Sparse Coding

Thomas Martinetz (Université de Lubeck, Allemagne)
vendredi 6 mai 2011

Résumé : There are various hints that sparse coding is one of the fundamental structural principles of the brain. We are interested in applying this principle to technical cognitive tasks. One of these tasks is pattern recognition, where one needs features which clearly describe the patterns involved. As soon as such features are identified, also the following classification task becomes feasible. Unfortunately, there is no theoretically founded method yet for extracting features with which a pattern recognition problem can be solved optimally. The visual cortex employs sparse coding for representing natural images. In experiments on digit recognition and face finding we demonstrate that sparse coding provides very promising results in these technical task. We show that the principle of sparse coding can also be applied to 3D-images of time-of-flight cameras and, perhaps as an ideal scenario, to manipulating space-time video patches for attention control.


Cet exposé se tiendra en salle C20-13, 20ème étage, Université Paris 1, Centre Pierre Mendès-France, 90 rue de Tolbiac, 75013 Paris (métro : Olympiades).


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