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ICDAR
2003
IEEE
13 years 10 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ICPR
2002
IEEE
14 years 6 months ago
Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit Recognition
This paper discusses the use of genetic algorithm for feature selection for handwriting recognition. Its novelty lies in the use of a multi-objective genetic algorithms where sens...
Luiz E. Soares de Oliveira, Robert Sabourin, Fl&aa...
ICDAR
2003
IEEE
13 years 10 months ago
Feature Selection for Ensembles: A Hierarchical Multi-Objective Genetic Algorithm Approach
Feature selection for ensembles has shown to be an effective strategy for ensemble creation. In this paper we present an ensemble feature selection approach based on a hierarchica...
Luiz E. Soares de Oliveira, Robert Sabourin, Fl&aa...
ICDAR
2003
IEEE
13 years 10 months ago
Optimizing Binary Feature Vector Similarity Measure using Genetic Algorithm and Handwritten Character Recognition
Classifying an unknown input is a fundamental problem in pattern recognition. A common method is to define a distance metric between patterns and find the most similar pattern i...
Sung-Hyuk Cha, Charles C. Tappert, Sargur N. Sriha...
ICPR
2008
IEEE
13 years 11 months ago
A feature selection algorithm for handwritten character recognition
We present a Genetic Algorithm based feature selection approach according to which feature subsets are represented by individuals of an evolving population. Evolution is controlle...
Luigi P. Cordella, Claudio De Stefano, Francesco F...