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- W2124103492 abstract "Neural nets are considered as the underlying computing mechanism for a robust approach to the problem of handwritten character recognition. It is expected that recognition mechanisms will be developed through learning algorithms. A key factor to this problem is the set of primitive features which are used to form the raw input vectors representing the digitized image of a character. The authors have explored a number of conventional and new features that can be used in concert with adaptive clustering schemes. Experiences of the performance of these features are presented. A feature which the authors call shadow and which is presented here has produced particularly encouraging results." @default.
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- W2124103492 date "2002-12-30" @default.
- W2124103492 modified "2023-09-24" @default.
- W2124103492 title "On features used for handwritten character recognition in a neural network environment" @default.
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- W2124103492 doi "https://doi.org/10.1109/tai.1993.633968" @default.
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