Study and evaluation of a multi-class SVM classifier using diminishing learning technique

Neurocomputing

Volumn 73, Issue 10-12, 2010, Pages 1676-1685

  Manikandan, J ^a   Venkataramani, B ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Isolated digit recognition; Multi class classification; Support vector machines; Support vectors

Indexed keywords

AUTOMATED PROCEDURES; CLASSIFICATION ACCURACY; DESIGN OBJECTIVES; DIGIT RECOGNITION; DIMENSIONALITY REDUCTION; DIRECTED ACYCLIC GRAPHS; FEATURE INPUT; FEATURE MAP; HALF AGAINST HALVES; LEARNING TECHNIQUES; MULTI-CLASS CLASSIFICATION; MULTICLASS SVM; NONLINEAR PATTERN; NOVEL TECHNIQUES; RECOGNITION ACCURACY; SELF-ORGANIZED; SEQUENTIAL CLASSIFIER; SPEAKER DEPENDENTS; SUPPORT VECTOR; SVM CLASSIFIERS;

CLASSIFIERS; CONFORMAL MAPPING; FEATURE EXTRACTION; GEARS; LEARNING ALGORITHMS; VECTORS;

SUPPORT VECTOR MACHINES;

ARTICLE; AUTOMATED PATTERN RECOGNITION; CLASSIFIER; KERNEL METHOD; LEARNING ALGORITHM; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SUPPORT VECTOR MACHINE;

EID: 77952549421     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.11.042     Document Type: Article

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