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| Research on GPR Multi-object Recognition |
| Hu Jin-feng;Zhou Zheng-ou; Kong Ling-jiang |
| College of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China |
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Abstract With limited samples, SVM has stronger ability of generalization in comparison with machine learning algorithm. In this paper, the SVM is combined with the Ground Penetrating Radar(GPR) multi-object recognition, and a GPR multi-object recognition method is proposed based on the one against one SVM. The proposed method includes the GPR multi-object recognition method based on one against one SVM, the parameter selection method based on the cross-validation and the multichannel recognition method. The contrast analysis between the proposed method and the conventional neural network method is given. The proposed method can be combined with object-feature extraction methods. It is shown that the method is effective in the experimental analysis. The conclusion can direct the research on GPR object recognition.
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Received: 15 June 2004
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2006, Vol. 28 
