Chinese character recognition method based on multi-features and parallel neural network computation

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Abstract

Based on neural network with favorable adaptability to handwritten Chinese character multi-features, in this paper a new method is proposed, using existing multi-features as inputs to structure multi neural network recognition subsystems and these subsystems are integrated with parallel connection mode. The integrated system has the lowest false recognition rate. When using traditional von Neumann architecture computer to implement this system, the system response time is longer as a result of serial computation. This paper introduces a kind of parallel computation method of using pc cluster to implement multi subsystems. It can reduce effectively recognition system's response time. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Li, Y., Yang, H., Xu, J., He, W., & Fan, J. (2007). Chinese character recognition method based on multi-features and parallel neural network computation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4681 LNCS, pp. 1103–1111). Springer Verlag. https://doi.org/10.1007/978-3-540-74171-8_112

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