@inproceedings{2849fe3fdda54877a56c2cb0bc63c012,
title = "Learning multiple feature representations from natural image sequences",
abstract = "Hierarchical neural networks require the parallel extraction of multiple features. This raises the question how a subpopulation of cells can become specific to one feature and invariant to another, while a different subpopulation becomes invariant to the first but specific to the second feature. Using a colour image sequence recorded by a camera mounted to a cat's head, we train a population of neurons to achieve optimally stable responses. We find that colour sensitive cells emerge. Adding the additional objective of decorrelating the neurons' outputs leads a subpopulation to develop achromatic receptive fields. The colour sensitive cells tend to be non-oriented, while the achromatic cells are orientation-tuned, in accordance with physiological findings. The proposed objective thus successfully separates cells which are specific for orientation and invariant to colour from orientation invariant colour cells.",
keywords = "Colour UTN:I0109, Learning, Natural stimuli, Temporal coherence, Visual cortex",
author = "Wolfgang Einh{\"a}user and Christoph Kayser and K{\"o}rding, {Konrad P.} and Peter K{\"o}nig",
year = "2002",
doi = "10.1007/3-540-46084-5_4",
language = "English (US)",
isbn = "9783540440741",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "21--26",
editor = "Dorronsoro, {Jose R.} and Dorronsoro, {Jose R.}",
booktitle = "Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings",
note = "2002 International Conference on Artificial Neural Networks, ICANN 2002 ; Conference date: 28-08-2002 Through 30-08-2002",
}