A stacked convolutional sparse denoising autoencoder model for underwater heterogeneous information data

•A novel stacked convolutional sparse denoising autoencoder (SCSDA) model is proposed.•The unrelated dataset was developed to simulate the underwater heterogeneous information data as the training set.•The blind denoising performance of underwater heterogeneous information data is studied. Deep lear...

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Bibliographic Details

Published in:	Applied acoustics Vol. 167; p. 107391
Main Authors:	Wang, Xingmei, Zhao, Yixu, Teng, Xuyang, Sun, Weiqi
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.10.2020
Subjects:	Blind denoising Convolutional neural network Deep learning Stacked sparse denoising autoencoder Underwater heterogeneous information data Stacked sparse denoising autoencoder Deep learning Underwater heterogeneous information data Blind denoising Convolutional neural network
ISSN:	0003-682X, 1872-910X
Online Access:	Get full text
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