首页> 外文会议>International Symposium on Neural Networks(ISNN 2006) pt.2; 20060528-0601; Chengdu(CN) >A Method of Chinese Fax Recipient's Name Recognition Based on Hybrid Neural Networks
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A Method of Chinese Fax Recipient's Name Recognition Based on Hybrid Neural Networks

机译:基于混合神经网络的中文传真收件人姓名识别方法

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摘要

A professional Chinese fax information processing system is designed which has functions to automate incoming fax distribution in a company or institution, read an incoming fax cover sheet and route the fax to the receiver's email box. This paper reports our research as part of an effort to realize such a system and focuses on recognition of the handwritten recipient's on fax cover pages. We propose hybrid neural networks for large scale Chinese handwritten character recognition. The network is composed of the self-organizing competitive fuzzy layer and the multi-layer neural network using BP method, connected in cascade. The characteristic features of this network structure for Chinese handwritten character recognition are discussed and performances are evaluated on 8208 real world faxes which are taken from one company in 2004, the results of experiments compared to standard neural solutions based on MLP show that the whole system is of reasonable structure and satisfactory performance.
机译:设计了一个专业的中文传真信息处理系统,该系统具有以下功能:在公司或机构中自动进行传入传真的分发,阅读传入的传真封面并将传真路由到接收者的电子邮件箱。本文报告了我们的研究,作为实现这种系统的一项工作,重点是在传真封面上识别手写收件人。我们提出了用于大规模中文手写字符识别的混合神经网络。该网络由自组织竞争性模糊层和采用BP方法的多层神经网络串联而成。讨论了这种用于中文手写字符识别的网络结构的特征,并在2004年从一家公司获得的8208个现实传真中对性能进行了评估,与基于MLP的标准神经解决方案进行的实验结果比较表明,整个系统具有合理的结构和令人满意的性能。

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