Unsupervised Domain Adaptation for Source Localization Using Ships of Opportunity With a Deep Vertical Line Array-Reference-Cited by-同舟云学术

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Unsupervised Domain Adaptation for Source Localization Using Ships of Opportunity With a Deep Vertical Line Array

Published:2023 Issue: Volume: Page:1-17
ISSN:0364-9059
Container-title:IEEE Journal of Oceanic Engineering
language:
Short-container-title:IEEE J. Oceanic Eng.

Author:

Liu Yining¹^ORCID,Niu Haiqiang²^ORCID,Li Zhenglin³^ORCID,Zhai Duo²

Affiliation:

1. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

2. State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China

3. School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai, China

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Southern Marine Science and Engineering Guangdong Laboratory

State Key Laboratory of Acoustics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Ocean Engineering

Link

http://xplorestaging.ieee.org/ielx7/48/4554198/10260236.pdf?arnumber=10260236

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Shallow water source depth discrimination based on a vertical linear array using deep learning;Applied Ocean Research;2024-11

2. BO-GRNN: Machine Learning for Underwater Acoustic Source Localization;Marine Geodesy;2024-09-13

3. Deep unsupervised adversarial domain adaptation for underwater source range estimation;The Journal of the Acoustical Society of America;2023-11-01

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