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Parallel compact integration in handwritten Chinese character recognition

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Abstract

In this paper, a new parallel compact integration scheme based on multi-layer perceptron (MLP) networks is proposed to solve handwritten Chinese character recognition (HCCR) problems. The idea of metasynthesis is applied to HCCR, and compact MLP network classifier is defined. Human intelligence and computer capabilities are combined together effectively through a procedure of two-step supervised learning. Compared with previous integration schemes, this scheme is characterized with parallel compact structure and better performance. It provides a promising way for applying MLP to large vocabulary classification.

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Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, 100080, Beijing, China

    Wang Chunheng, Xiao Baihua & Dai Ruwei

Authors
  1. Wang Chunheng
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  2. Xiao Baihua
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  3. Dai Ruwei
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Corresponding author

Correspondence to Dai Ruwei.

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Wang, C., Xiao, B. & Dai, R. Parallel compact integration in handwritten Chinese character recognition. Sci China Ser F 47, 89–96 (2004). https://doi.org/10.1360/02yf0068

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