首页> 外文会议>2011 International Symposium on Computer Science and Society >Defect Recognition of X-Ray Steel Rope Cord Conveyer Belt Image Based on BP Neural Network
【24h】

Defect Recognition of X-Ray Steel Rope Cord Conveyer Belt Image Based on BP Neural Network

机译:基于BP神经网络的X射线钢丝绳输送带图像缺陷识别。

获取原文

摘要

BP neural network is used to recognize X-ray steel rope cord conveyer belt image with defect in this paper. Firstly, the model of three layers BP neural network is established, and it is made up of 240 input nodes, 20 hidden layer nodes, and 1 output node. Then, the BP neural network is trained and tested in MATLAB. The results show that X-ray steel rope cord conveyer belt image with defect can be identified by the neural network.
机译:本文采用BP神经网络识别有缺陷的X射线钢丝绳输送带图像。首先建立了三层BP神经网络模型,由240个输入节点,20个隐层节点和1个输出节点组成。然后,在MATLAB中对BP神经网络进行训练和测试。结果表明,利用神经网络可以识别出有缺陷的X射线钢丝绳输送带图像。

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