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.
This paper research is supported from national ministry of education excellent backbone teacher assistance plan.
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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: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_112
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DOI: https://doi.org/10.1007/978-3-540-74171-8_112
Publisher Name: Springer, Berlin, Heidelberg
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