Learning a selectivity-invariance-selectivity feature extraction architecture for images

Michael Gutmann, Aapo Hyvärinen

Abstract: Selectivity and invariance are thought to be important ingredients in biological or artificial visual systems. A fundamental problem is, however, to know what the visual system should be selective to and what to be invariant to. Building a statistical model of images, we learn here a three-layer feature extraction system where the selectivity and invariance emerges from the properties of the images.