@inproceedings{c0c0efb60e014c4da40dce2ea84a5c6a,
title = "Extracting slow subspaces from natural videos leads to complex cells",
abstract = "Natural videos obtained from a camera mounted on a cat{\textquoteright}s head are used as stimuli for a network of subspace energy detectors. The network is trained by gradient ascent on an objective function defined by the squared temporal derivatives of the cells{\textquoteright} outputs. The resulting receptive fields are invariant to both contrast polarity and translation and thus resemble complex type receptive fields.",
keywords = "Computational neuroscience, Learning, Temporal smothness",
author = "Christoph Kayser and Wolfgang Einh{\"a}user and Olaf D{\"u}mmer and Peter K{\"o}nig and Konrad K{\"o}rding",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; International Conference on Artificial Neural Networks, ICANN 2001 ; Conference date: 21-08-2001 Through 25-08-2001",
year = "2001",
doi = "10.1007/3-540-44668-0_149",
language = "English (US)",
isbn = "3540424865",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1075--1080",
editor = "Kurt Hornik and Georg Dorffner and Horst Bischof",
booktitle = "Artificial Neural Networks - ICANN 2001 - International Conference, Proceedings",
}