DocumentCode :
3575711
Title :
An adaptive-weight regularization method for multi-classifier fusion decision
Author :
Zhu Xufeng ; Ma Biao ; Guo Guanjun
Author_Institution :
Aerosp. Intell. Control, Beijing Aerosp. Autom. Control Inst., Beijing, China
fYear :
2014
Firstpage :
343
Lastpage :
346
Abstract :
The difficulties of aircraft type recognition methods are introduced and the necessity of multi-classifier fusion decision method is discussed. The some kinds of invariants: Hu moments, Affine moments, Zernike moments, Wavelet moments, are used for constructing four SVM classifiers. Based on the above four classifiers, an adaptive-weight regularization method is proposed for improving aircraft type classification performance. Experiments are shown that, the recognition rate by the proposed method in this paper is better than any classifier of the above four classifiers, the fixed-weight multi-classifier fusion method and the majority multi-classifier fusion method.
Keywords :
aircraft; image classification; image fusion; support vector machines; Hu moment; SVM classifier; Zernike moment; adaptive-weight regularization method; affine moment; aircraft type recognition method; multiclassifier fusion decision method; wavelet moment; Aircraft; Aircraft manufacture; Image recognition; Support vector machines; Target recognition; Testing; Training; adaptive-weight; aircraft type recognition; decision-level fusion; multi-classifier;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
Type :
conf
DOI :
10.1109/ICMC.2014.7231575
Filename :
7231575
Link To Document :
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