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| 概率神经网络与BP网络模型在遥感图像分类中的对比研究 | |
| 引用本文： | 李朝锋,杨茂龙,许磊,杨蒙召.概率神经网络与BP网络模型在遥感图像分类中的对比研究[J].国土资源遥感,2004,15(4):11-13,18. |
| 作者姓名： | 李朝锋 杨茂龙 许磊 杨蒙召 |
| 作者单位： | 1. 江南大学信息工程学院,无锡,214036 2. 解放军国际关系学院航天侦察教研室,南京,210039 |
| 摘 要： | 通过分析概率神经网络(以下称PNN)的基本结构及其训练算法,建立了卫星图像分类的概率神经网络模型,并通过实例对比分析了概率神经网络与BP网络分类模型的分类效果。实验表明,PNN图像分类方法在分类精度上优于误差反向传播神经网络模型,且分类时间相当,是一种有效的图像分类方法。 |
| 关 键 词： | 概率神经网络 遥感图像分类 反向传播神经网络 |
| 文章编号： | 1001-070(2004)04-0011-04 |
| 收稿时间： | 2003-12-27 |
| 修稿时间： | 2004-05-09 |
A COMPARATIVE STUDY OF PROBABILISTIC NEURAL NETWORK AND BP NETWORKS FOR REMOTE SENSING IMAGE CLASSIFICATION |
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| LI Chao-feng,YANG Mao-long,XU Lei,YANG Meng-zhao.A COMPARATIVE STUDY OF PROBABILISTIC NEURAL NETWORK AND BP NETWORKS FOR REMOTE SENSING IMAGE CLASSIFICATION[J].Remote Sensing for Land & Resources,2004,15(4):11-13,18. | |
| Authors: | LI Chao-feng YANG Mao-long XU Lei YANG Meng-zhao |
| Institution: | 1. School of Information Technology, Southern Yangtze University, Wuxi 214036, China; 2. Department of Space Reconnaissance, University of Foreign Relations, PLA, Nanjing 210039, China |
| Abstract: | This paper has analyzed the basic theory and algorithm of the probabilistic neural network, and established the remote sensing image classification model based on the probabilistic neural network. Examples show that the probabilistic neural network model outperforms the improved back-propagation neural network model in classification precision and is close to the latter in time consumption. It proves to be an efficient image classification method. |
| Keywords: | Probabilistic neural network Remote sensing image classification Back-propagation neural network |
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