Automatic feature generation for handwritten digit recognition | IEEE Journals & Magazine | IEEE Xplore

Automatic feature generation for handwritten digit recognition


Abstract:

An automatic feature generation method for handwritten digit recognition is described. Two different evaluation measures, orthogonality and information, are used to guide...Show More

Abstract:

An automatic feature generation method for handwritten digit recognition is described. Two different evaluation measures, orthogonality and information, are used to guide the search for features. The features are used in a backpropagation trained neural network. Classification rates compare favorably with results published in a survey of high-performance handwritten digit recognition systems. This classifier is combined with several other high performance classifiers. Recognition rates of around 98% are obtained using two classifiers on a test set with 1000 digits per class.
Page(s): 1256 - 1261
Date of Publication: 06 August 2002

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