• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International journal of computational intelligence systems >Alphanumeric Character Recognition Based on BP Neural Network Classification and Combined Features
【24h】

Alphanumeric Character Recognition Based on BP Neural Network Classification and Combined Features

机译：基于BP神经网络分类和组合特征的字母数字字符识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper puts forward a new method of alphanumeric character recognition based on BP neural network classification and combined features. This method firstly establishes three BP networks respectively for three categories of characters which are classified according to their Euler numbers, with the combination of grid feature and projection feature as the input of each BP network. When recognizing a character, its combined features are fed into the three BP networks simultaneously without the necessity for judging its Euler number. The final recognition result is elaborated by synthetically analyzing the outputs of three BP networks. Experimental results show that the proposed method can effectively improve the recognition ability and efficiency, and has a good property of fault tolerance and robustness. Furthermore, the weight coefficients of combined features for each BP network are optimized, which can further improve the recognition rate.
机译：提出了一种基于BP神经网络分类和组合特征的字母数字字符识别新方法。该方法首先针对三个类别的字符分别建立了三个BP网络，并根据网格特征和投影特征作为每个BP网络的输入，并根据欧拉数对它们进行分类。识别字符时，其组合特征同时输入到三个BP网络中，而无需判断其Euler数。通过综合分析三个BP网络的输出来详细阐述最终识别结果。实验结果表明，该方法能够有效提高识别能力和识别效率，具有良好的容错性和鲁棒性。此外，针对每个BP网络的组合特征的权重系数被优化，这可以进一步提高识别率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号