A Novel Noise-Aware Deep Learning Model for Underwater Acoustic Denoising-Reference-Cited by-同舟云学术

A Novel Noise-Aware Deep Learning Model for Underwater Acoustic Denoising

Published:2023 Issue: Volume:61 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhou Aolong¹^ORCID,Zhang Wen²^ORCID,Li Xiaoyong¹^ORCID,Xu Guojun³,Zhang Bingbing³^ORCID,Ma Yanxin³,Song Junqiang¹^ORCID

Affiliation:

1. College of Computer Science and Technology and the College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China

2. Strategic Evaluation and Consultation Center, Academy of Military Sciences, Beijing, China

3. College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10064313.pdf?arnumber=10064313

Reference51 articles.

1. DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement

2. Deep‐learning‐based line enhancer for passive sonar systems

3. FullSubNet+: Channel Attention Fullsubnet with Complex Spectrograms for Speech Enhancement

4. S-DCCRN: Super Wide Band DCCRN with Learnable Complex Feature for Speech Enhancement

5. Frequency Domain Based Approach for Denoising of Underwater Acoustic Signal Using EMD

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