Learning viewpoint invariant object representations using a temporal coherence principle

Biological Cybernetics

Volumn 93, Issue 1, 2005, Pages 79-90

  Einhäuser, Wolfgang ^a,d   Hipp, Jörg ^a   Eggert, Julian ^b   Körner, Edgar ^b   König, Peter ^a,c  

^a Institute of Neuroinformatics Zurich   (Switzerland)

^b HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

^c UNIVERSITY OF OSNABRÜCK   (Germany)

^d CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMECHANICS; CELLS; COMPUTER VISION; MATRIX ALGEBRA;

INVARIANT RECOGNITION; MAMMALIAN VISUAL SYSTEMS; OBJECT REPRESENTATION; TEMPORAL COHERENCE;

OBJECT RECOGNITION;

MAMMALIA;

ACTION POTENTIAL; ANALYSIS OF VARIANCE; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; CLUSTER ANALYSIS; COMPARATIVE STUDY; CYTOLOGY; HUMAN; LEARNING; METHODOLOGY; NERVE CELL; PATTERN RECOGNITION; PHOTOSTIMULATION; PHYSIOLOGY; VISUAL CORTEX;

ACTION POTENTIALS; ANALYSIS OF VARIANCE; ANIMALS; CLUSTER ANALYSIS; GENERALIZATION (PSYCHOLOGY); HUMANS; LEARNING; NEURAL NETWORKS (COMPUTER); NEURONS; PATTERN RECOGNITION, VISUAL; PHOTIC STIMULATION; VISUAL CORTEX;

EID: 23044508992     PISSN: 03401200     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00422-005-0585-8     Document Type: Article

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