Improved Genetic Neural Network for Image Segmentation

摘要：

The paper provides the method of the improved genetic neural network for image segmentation. The method uses improved genetic algorithm BP neural network weights and thresholds to optimize, and use the definition of bipolar fitness function mapping compression to speed up neural network training speed, and then use iterative improved neural network algorithm to achieve image segmentation. The results of experimental show that the improved genetic neural network can better achieve the image segmentation, compared with the traditional method; Compared with BP neural network training speed is greatly improved.

作者: Qing-sheng WANG Yue-qin ZHANG Bin HU Jian-guang ZHAO

作者单位: Computer Science and Technology Institute, Taiyuan University of Technology, Taiyuan, Shanxi, China

会议类型: 国际会议

会议名称: 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management(2011 IEEE 第十八届工业工程与工程管理国际会议 IEEM2011)

会议地点: 长春

会议语种:英文

页码: 1694-1698

在线出版日期: 2011-09-03（万方平台首次上网日期，不代表论文的发表时间）