Combination of multiple classifiers by minimizing the upper bound of Bayes error rate for unconstrained handwritten numeral recognition

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 19, Issue 3, 2005, Pages 395-413

  Kang, Hee Joong ^a   Lee, Seong Whan ^b  

^a Hansung University   (South Korea)

^b Korea University   (South Korea)

Author keywords

Approximation scheme: mutual information; Bayes error rate; Combination of multiple classifiers; Dependency; Handwritten numeral recognition

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; DATA ACQUISITION; PROBABILITY DISTRIBUTIONS; SET THEORY; VECTORS;

APPROXIMATION SCHEME; BAYES ERROR RATE; COMBINATION OF MULTIPLE CLASSIFIERS; DEPENDENCY; HANDWRITTEN NUMERAL RECOGNITION; MUTUAL INFORMATION;

PATTERN RECOGNITION;

EID: 18644367804     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001405004101     Document Type: Article

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