Treat Noise as Domain Shift: Noise Feature Disentanglement for Underwater Perception and Maritime Surveys in Side-Scan Sonar Images-Reference-Cited by-同舟云学术

Treat Noise as Domain Shift: Noise Feature Disentanglement for Underwater Perception and Maritime Surveys in Side-Scan Sonar Images

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yu Yongcan¹^ORCID,Zhao Jianhu¹^ORCID,Huang Chao¹,Zhao Xi¹^ORCID

Affiliation:

1. School of Geodesy and Geomatics and the Institute of Marine Science and Technology, Wuhan University, Wuhan, China

Funder

National Key Research and Development Program of China

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/ielx7/36/10006360/10274511.pdf?arnumber=10274511

Reference74 articles.

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3. Research on Obstacle Detection and Avoidance of Autonomous Underwater Vehicle Based on Forward-Looking Sonar

4. YOLOv5s-M: A deep learning network model for road pavement damage detection from urban street-view imagery;ren;Int J Appl Earth Observ Geoinf,2023

5. Deep Gabor neural network for automatic detection of mine-like objects in sonar imagery;le;IEEE Access,2020

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