A life-long learning vector quantization approach for interactive learning of multiple categories

Neural Networks

Volumn 28, Issue , 2012, Pages 90-105

  Kirstein, Stephan ^a,b   Wersing, Heiko ^a   Gross, Horst Michael ^b   Körner, Edgar ^a  

^a HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

^b ILMENAU UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Category learning; Feature selection; Life long learning; Vector quantization

Indexed keywords

CATEGORY LEARNING; COGNITIVE ROBOTICS; FEATURE SELECTION METHODS; INCREMENTAL LEARNING; INTERACTIVE LEARNING; LEARNING PROCESS; LEARNING VECTOR QUANTIZATION; LIFE LONG LEARNING; REPRESENTATION SPACE; STABILITY-PLASTICITY DILEMMA; VISUAL CATEGORIZATION;

COGNITIVE SYSTEMS; FEATURE EXTRACTION; LEARNING SYSTEMS;

VECTOR QUANTIZATION;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALCULATION; CONTROLLED STUDY; DECISION SUPPORT SYSTEM; KERNEL METHOD; LEARNING ALGORITHM; LIFELONG LEARNING; LINEAR SYSTEM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PERCEPTRON; PREDICTION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; QUANTITATIVE STUDY; ROBOTICS; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

LEARNING; LONGEVITY; ROBOTICS;

EID: 84857797119     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2011.12.003     Document Type: Article

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