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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Vydané v:	Applied acoustics Ročník 167; s. 107391
Hlavní autori:	Wang, Xingmei, Zhao, Yixu, Teng, Xuyang, Sun, Weiqi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.10.2020
Predmet:	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
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