@misc{cogprints2706,
          editor = {Jos{\'e} R. Dorronsoro},
           title = {Applying Slow Feature Analysis to Image Sequences Yields a Rich Repertoire of Complex Cell Properties},
          author = {Pietro Berkes and Laurenz Wiskott},
       publisher = {Springer Verlag},
            year = {2002},
           pages = {81--86},
        keywords = {Complex cells, slow feature analysis, temporal slowness, model , spatio-temporal, receptive fields},
             url = {http://cogprints.org/2706/},
        abstract = {We apply Slow Feature Analysis (SFA) to image sequences generated from natural images using a range of spatial transformations. An analysis of the resulting receptive fields shows that they have a rich spectrum of invariances and share many properties with complex and hypercomplex cells of the primary visual cortex. Furthermore, the dependence of the solutions on the statistics of the transformations is investigated.
}
}

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