Publication | Closed Access
The Performance Comparison of Adaboost and SVM Applied to SAR ATR
39
Citations
6
References
2006
Year
Unknown Venue
RadarSupport Vector MachineImage AnalysisEngineeringAutomatic Target RecognitionSynthetic Aperture RadarPattern RecognitionImaging RadarRadar Image ProcessingRadar ApplicationRadar Signal ProcessingPerformance ComparisonPrincipal Component AnalysisSvm ClassifierSvm AppliedSar Atr
In this paper, Adaboost and SVM are applied to SAR ATR (synthetic aperture radar automatic target recognition) respectively. The performance of these two classifiers is analyzed and compared in target aspect window with different size. First, PCA (principal component analysis) features are selected as target feature, and then Adaboost.Ml and SVM are used to classify, respectively. Experimental results based on MSTAR data sets show that Adaboost classifier has better robustness than SVM classifier
| Year | Citations | |
|---|---|---|
Page 1
Page 1