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- W2352958173 abstract "To recognize numeral and letter characters efficiently, a novel method based on characteristic parameters of the projection of binary images was proposed to construct the eigenvectors. The eigenvectors were normalized and selected as training set of support vector machines. Through training the eigen vectors of characters using support vector machines and multilayer perception networks, 26 letter classifiers, 10 number classifiers and 36 letter-number integrated classifiers were constructed respectively. Testing results showed that the average veracity and velocity of characters recognition reached 96.5% and 20.5()ms/character respectively, and that SVM is a promising method for characters recognition." @default.
- W2352958173 created "2016-06-24" @default.
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- W2352958173 date "2005-01-01" @default.
- W2352958173 modified "2023-09-23" @default.
- W2352958173 title "Application of support vector machines in classification and recognition of characters" @default.
- W2352958173 hasPublicationYear "2005" @default.
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