A Lightweight Network Based on Multi-Scale Asymmetric Convolutional Neural Networks with Attention Mechanism for Ship-Radiated Noise Classification

A Lightweight Network Based on Multi-Scale Asymmetric Convolutional Neural Networks with Attention Mechanism for Ship-Radiated Noise Classification

Ship-radiated noise classification is critical in ocean acoustics. Recently, the feature extraction method combined with time–frequency spectrograms and convolutional neural networks (CNNs) has effectively described the differences between various underwater targets. However, many existing CNNs are...

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Bibliographic Details
Main Authors: Chenhong Yan, Shefeng Yan, Tianyi Yao, Yang Yu, Guang Pan, Lu Liu, Mou Wang, Jisheng Bai
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Journal of Marine Science and Engineering
Subjects:
ship-radiated noise classification
lightweight network
asymmetric convolution
multi-scale features
attention mechanism
Online Access:https://www.mdpi.com/2077-1312/12/1/130

Internet

https://www.mdpi.com/2077-1312/12/1/130

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