Abstract:
An automatic feature generation method for handwritten digit recognition is described. Two different evaluation measures, orthogonality and information, are used to guide...Show MoreMetadata
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.
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 18, Issue: 12, December 1996)
DOI: 10.1109/34.546262