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《Journal of Data Acquisition & Processing》 2009-01
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Synthetic Aperture Radar Image Target Recognition Using Fuzzy AdaBoost Algorithm

Huan Ruohong1,2,Yang Ruliang1(1.Institute of Electronics,Chinese Academy of Sciences,Beijing,100190,China;2.Graduate School,Chinese Academy of Sciences,Beijing,100190,China)  
A method of multi-class classification for extending AdaBoost algorithm is presented and a new algorithm is used on synthetic aperture radar image target recognition.Because the basic AdaBoost algorithm is only suited for two class classification,it needs to be extended for multi-class classification.A multi-class classification problem is decomposed into multiple two class classification problems by using "one against one" method,and a fuzzy algorithm is proposed to give a decision from outputs of multiple two class AdaBoost classifiers.From the end of the fuzzy algorithm,the final classification outcome is obtained.Then the extended fuzzy AdaBoost algorithm on SAR image target recognition is used and three military targets in MSTAR database are experimented.Experimental results show that the extended fuzzy AdaBoost algorithm is effective on SAR image target recognition and a better target correct recognition rate is obtained.
【CateGory Index】: TN957.52
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Chinese Journal Full-text Database 1 Hits
1 LIU Xian-kang, LIANG Jing, REN Jie, JIANG Guang-qing(No.701 Factory of PLA(N),Beijing 100016,China);Design of modified nearest neighbor fuzzy classifier based on Fisher discriminant weighting[J];Ship Science and Technology;2010-02
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