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- W2384442198 abstract "Aimed at the low accuracy of handwritten numeral recognition at present,through the research of handwritten numerals image,a method of feature extraction based on handwritten numeral images space,rotation,level and structure characteristics is proposed.This method combined statistical and structural features of the handwritten numerals.Based feature extraction method,handwritten numerals characteristics are trained and recognized through LibSVM algorithm.Recommended values to each parameter are given by the experimentation,and the MNIST handwritten numerals recognition rate can reach 99.3333% by this recommended values.The experimental result shows that this method can recognize the handwritten numeral effectively and accurately." @default.
- W2384442198 created "2016-06-24" @default.
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- W2384442198 date "2012-01-01" @default.
- W2384442198 modified "2023-09-23" @default.
- W2384442198 title "Research of handwritten numeral recognition based on statistical and structure characteristics" @default.
- W2384442198 hasPublicationYear "2012" @default.
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