| 基于几种不变量融合信息的缺损目标识别 |
| |
| 引用本文： | 廖原,袁捷,赵恒卓,胡正仪,王延平. 基于几种不变量融合信息的缺损目标识别[J]. 武汉大学学报(理学版), 1998, 0(1) |
| |
| 作者姓名： | 廖原 袁捷 赵恒卓 胡正仪 王延平 |
| |
| 作者单位： | 武汉大学电子信息学学院 |
| |
| 摘 要： | 论述了基于３种不变量的融合信息来识别缺损目标的方法．该方法采用Ｄｅｍｐｓｔｅｒ－Ｓｈａｆｅｒ证据推理方法作为决策层的融合工具，将拐点、线矩、高阶神经网络的分类结果进行信息融合．分类实验证明，该方法可以有效地提高系统的识别精度．
|
| 关 键 词： | 缺损目标识别，不变量，信息融合，Dempster－Shafer证据推理 |
RECOGNITION OF OCCLUDED TARGET WITH FUSED DATA OF SEVERAL INVARIANCES |
| |
| Liao Yuan,Yuan Jie,Zhao Hengzhuo,Hu Zhengyi,Wang Yanping. RECOGNITION OF OCCLUDED TARGET WITH FUSED DATA OF SEVERAL INVARIANCES[J]. JOurnal of Wuhan University:Natural Science Edition, 1998, 0(1) |
| |
| Authors: | Liao Yuan Yuan Jie Zhao Hengzhuo Hu Zhengyi Wang Yanping |
| |
| Abstract: | This paper presents a method of recognizing occluded target with fused data,which comes from three kinds of invariances such as corner, moment and high order neural network. In this paper, Dempster Shafer Evidential reasoning is selected and used for data fusion at report level. The classification experiment shows that this method effectively improves the matching precision of the recognizing system. |
| |
| Keywords: | recognition of occluded target invariance data fusion Dempster Shafer evidential reasoning |
| 本文献已被 CNKI 等数据库收录！ |
