...
首页> 外文期刊>Tsinghua Science and Technology >Classification of cancer cells using neural neural networks in combination with expert experience
【24h】

Classification of cancer cells using neural neural networks in combination with expert experience

机译:利用神经网络结合专家经验对癌细胞进行分类

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

This paper briefly reviews sorre neural networks and discusses their drawbacks, the main defaults is that these neural networks do not use expert experience (or knowledge) and have the human flexibility, therefore, a new better method for the combination of neural networks with expert experience (or knowledge) was proposed. Probabilistic neural networks (PNNs) classification of cancer cell image is described. This networks is simpler and faster than back-propagating neural networks (BPNNs) during training and learning. Neural networks combined with expert experience is presented in order to improve the classification accuracy of the networks and the simulation experiments were performed and the results have shown that the method presented is very efficient and feasible.
机译:本文简要回顾了sorre神经网络并讨论了它们的缺点,主要的默认设置是这些神经网络不使用专家经验(或知识)并且具有人为灵活性,因此,这是一种将神经网络与专家经验相结合的更好的新方法(或知识)被提出。描述了癌细胞图像的概率神经网络(PNN)分类。在训练和学习过程中,该网络比反向传播神经网络(BPNN)更简单,更快。提出了结合专家经验的神经网络,以提高网络的分类精度,并进行了仿真实验,结果表明所提出的方法非常有效和可行。

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