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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wu Tao Chen Xi Ruang Xiangwei Niu Lei |
| Copyright Year | 2009 |
| Description | Author affiliation: No.38 Research Institute of China Electronic Technology Corporation, Hefei, 230031, China (Wu Tao; Chen Xi; Ruang Xiangwei; Niu Lei) |
| Abstract | This paper studies MSTAR SAR target recognition with Support Vector Machine (SVM) classifier by using Principal Component Analysis (PCA) features, without consideration of errors in target aspect angle estimation. A good strategy is proposed to avoid errors in classifier selection for the errors in estimation of aspect angle. The experiments based on MSTAR data set show perfect results. |
| Starting Page | 856 |
| Ending Page | 859 |
| File Size | 168042 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424427314 |
| DOI | 10.1109/APSAR.2009.5374190 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-10-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Constraint optimization Estimation error Image segmentation Image recognition Target recognition Support vector machine classification Radar imaging Error correction SVM Principal component analysis PCA |
| Content Type | Text |
| Resource Type | Article |
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