Comparison of different classification algorithms for underwater target discrimination

IEEE Transactions on Neural Networks
Donghui LiMarc Robinson

Abstract

Classification of underwater targets from the acoustic backscattered signals is considered here. Several different classification algorithms are tested and benchmarked not only for their performance but also to gain insight to the properties of the feature space. Results on a wideband 80-kHz acoustic backscattered data set collected for six different objects are presented in terms of the receiver operating characteristic (ROC) and robustness of the classifiers wrt reverberation.

References

Feb 6, 2008·IEEE Transactions on Neural Networks·M R Azimi-SadjadiG J Dobeck
Jan 1, 1994·IEEE Transactions on Neural Networks·R L Streit, T E Luginbuhl

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Citations

May 3, 2007·The Journal of the Acoustical Society of America·Paul L D Roberts, Jules S Jaffe
Dec 5, 2008·IEEE Transactions on Neural Networks·Andreas Brandstetter, Alessandro Artusi
Apr 23, 2008·Journal of Health Services Research & Policy·Andrea Seymour, Kathryne Dupré
Apr 2, 2018·The Journal of the Acoustical Society of America·Michael RobinsonJennifer Dumiak

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