Deep convolution stack for waveform in underwater acoustic target recognition

Abstract In underwater acoustic target recognition, deep learning methods have been proved to be effective on recognizing original signal waveform. Previous methods often utilize large convolutional kernels to extract features at the beginning of neural networks. It leads to a lack of depth and stru...

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Autores principales: Shengzhao Tian, Duanbing Chen, Hang Wang, Jingfa Liu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/0a2e8f2785584d68a2ccc8d0c380e1cc
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