Feature selection using multi-objective genetic algorithms for handwritten digit recognition

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 568-571

  Oliveira, L S ^a,b   Sabourin, R ^a,c   Bortolozzi, F ^c   Suen, C Y ^b  

^a ÉCOLE DE TECHNOLOGIE SUPÉRIEURE   (Canada)

^b Gina Cody School of Engineering and Computer Science   (Canada)

^c PONTIFICAL CATHOLIC UNIVERSITY OF PARANÁ   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

CHARACTER RECOGNITION; DATABASE SYSTEMS; GENETIC ALGORITHMS; NEURAL NETWORKS; SENSITIVITY ANALYSIS; ALGORITHMS; FEATURE EXTRACTION;

FEATURE SELECTIONS; HANDWRITTEN DIGIT RECOGNITION; MULTI-OBJECTIVE GENETIC ALGORITHMS;

FEATURE EXTRACTION; PATTERN RECOGNITION;

HANDWRITING RECOGNITION; HANDWRITTEN DIGIT RECOGNITION; MULTI-OBJECTIVE GENETIC ALGORITHM; NIST DATABASE;

EID: 18044365477     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (7)

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6. L. S. Oliveira, R. Sabourin, F. Bortolozzi, and C. Y. Suen. Automatic recognition of handwritten numerical strings: A recognition and verification strategy. IEEE Trans. on Pattern Analysis and Machine Intelligence, to appear.
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