Deep Learning Methods for Underwater Target Feature Extraction and Recognition

Computational Intelligence and Neuroscience
Gang HuLiangliang Liu

Abstract

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04...Continue Reading

References

Jul 29, 2006·Science·G E Hinton, R R Salakhutdinov
Dec 3, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Gao HuangKeyou You
May 29, 2015·Nature·Yann LeCunGeoffrey Hinton

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Citations

Jan 10, 2020·Journal of Healthcare Engineering·Santiago Tello-MijaresFrancisco Flores
Oct 25, 2020·ISA Transactions·Jean-Michel A SarrS El Ayoubi
May 7, 2021·Scientific Reports·Shengzhao TianJingfa Liu
Sep 3, 2021·The Journal of the Acoustical Society of America·Ryan A McCarthyMadison Kemerling
Sep 3, 2021·The Journal of the Acoustical Society of America·Lu WangLuyang Guan

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Methods Mentioned

BETA
feature extraction

Software Mentioned

MATLAB
CUDA

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