@inproceedings{2beb1cdd6c664236a144bfc1a2207458,
title = "Support vector machines for automatic target recognition using wavelet kernel",
abstract = "The classification problem of small target is a very significant but challenging task in the field of Automatic target recognition. In this paper, an enhanced Support Vector machine with the wavelet kernel function was proposed. In order to concentrate on the classification, It is assumed that regions containing possible targets are provided. Then the Hu's moment invariants are chosen as the feature vectors used for classifiers. Finally, the classification is performed by a Support Vector classifier used Db4 wavelet kernel. Compared to the Gaussian kernel classifier, simulation results show that this method leads to a more admissible result in terms of classification accuracy and robustness.",
keywords = "Automatic target recognition, Feature extraction, Support vector machine, Wavelet kernel",
author = "Jiong Zhao and Fan, {Yang Yu} and Liu, {Yuan Kui}",
year = "2007",
doi = "10.1109/ICWAPR.2007.4421658",
language = "英语",
isbn = "1424410665",
series = "Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1424--1427",
booktitle = "Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07",
note = "2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07 ; Conference date: 02-11-2007 Through 04-11-2007",
}