Multi-class SAR feature space trajectory (FST) neural network class and pose estimation results

被引：3
|
作者：
Shenoy, R
Casasent, D
机构：
来源：
ALGORITHMS FOR SYNTHETIC APERTURE RADAR IMAGERY IV | 1997年 / 3070卷
关键词：
D O I：
10.1117/12.281549
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The feature space trajectory representation and neural network is used for classification and pose estimation of distorted objects in SXR data. New feature spaces and techniques to extend the concept ro multiple classes are emphasized with initial four class results. On 4 class data, we obtain P-C = 98.3% and clutter P-FA = 0.026/km(2).
引用
收藏
页码：121 / 124
页数：4
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