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- W2019668813 abstract "The recognition of connected characters in cursive handwriting is a difficult task with ordinary pattern-matching techniques, since the shape of the individual character is affected by its preceding and succeeding characters. One of the authors has proposed a neural network model called the selective attention model, which has the ability to recognize and extract individual patterns from a composite of a number of elementary patterns. However, when a large number of patterns are presented concurrently, this model doe not always work correctly. In this paper, we extend the idea of this model and construct a new system, which has the ability to recognize the connected characters in cursive handwriting. it has been verified by computer simulation that this system can be used to correctly recognize connected characters." @default.
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- W2019668813 modified "2023-09-23" @default.
- W2019668813 title "Character recognition in cursive handwriting with the mechanism of selective attention" @default.
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- W2019668813 doi "https://doi.org/10.1002/scj.4690240309" @default.
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