Slow feature analysis: Unsupervised learning of invariances
- Author
- WISKOTT, Laurenz1 2 3 ; SEJNOWSKI, Terrence J4 5
[1] Computational Neurobiology Laboratory, Salk Institute for Biological Studies, San Diego, CA 92168, United States
[2] Institute for Advanced Studies, 14193, Berlin, Germany
[3] Innovationskolleg Theoretische Biologie, Institute for Biology, Humboldt-University Berlin, 10115 Berlin, Germany
[4] Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States
[5] Department of Biology, University of California at San Diego, La Jolla, CA 92037, United States - Source
Neural computation. 2002, Vol 14, Num 4, pp 715-770 ; ref : 1 p.1/2
- ISSN
- 0899-7667
- Scientific domain
- Computer science; Neurology; Psychology, psychopathology, psychiatry
- Publisher
- MIT Press, Cambridge, MA
- Publication country
- United States
- Document type
- Article
- Language
- English
- Keyword (fr)
- Analyse composante principale Analyse mouvement Analyse sensorielle Analyse signal Apprentissage Invariance Normalisation Réseau neuronal Traitement image Analyse caractéristics
- Keyword (en)
- Principal component analysis Motion analysis Sensory analysis Signal analysis Learning Invariance Standardization Neural network Image processing Feature analysis
- Keyword (es)
- Análisis componente principal Análisis movimiento Análisis sensorial Análisis de señal Aprendizaje Invarianza Normalización Red neuronal Procesamiento imagen
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C02 Learning and adaptive systems
- Pascal
- 002 Biological and medical sciences / 002A Fundamental and applied biological sciences. Psychology / 002A26 Psychology. Psychophysiology / 002A26F Learning. Memory / 002A26F01 Theories
- Discipline
- Computer science : theoretical automation and systems Psychology. Ethology
- Origin
- Inist-CNRS
- Database
- FRANCIS ; PASCAL
- INIST identifier
- 13505893
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1162/089976602317318938 
https://dx.doi.org/10.1162/089976602317318938
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