论文信息 - Genetic Algorithm Selection of Features for Hand-printed Character Identification

Genetic Algorithm Selection of Features for Hand-printed Character Identification

We have constructed a linear discriminator for handprinted character recognition that uses a (binary) vector of 1, 500 features based on an equidistributed collection of products of pixel pairs. This classifier is competitive with other techniques, but faster to train and to run for classification.

Peter G. Anderson | Roger S. Gaborski | Christopher Thomas C O Asbury | David G C O Eastman Kod Tilley

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