EnYOLO: A Real-Time Framework for Domain-Adaptive Underwater Object Detection with Image Enhancement-Reference-Cited by-同舟云学术

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EnYOLO: A Real-Time Framework for Domain-Adaptive Underwater Object Detection with Image Enhancement

Published:2024-05-13 Issue: Volume:35 Page:12613-12619
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Wen Junjie¹,Cui Jinqiang²,Zhao Benyun¹,Han Bingxin¹,Liu Xuchen¹,Gao Zhi³,Chen Ben M.¹

Affiliation:

1. Chinese University of Hong Kong,Department of Mechanical and Automation Engineering,Shatin,N.T.,Hong Kong

2. Peng Cheng Laboratory,Department of Mathematics and Theories,Shenzhen,China

3. Wuhan University,School of Remote Sensing and Information Engineering,Wuhan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10610639.pdf?arnumber=10610639

Reference39 articles.

1. Underwater Object Classification and Detection: first results and open challenges

2. Autonomous agents for observing marine life

3. Sea-Thru: A Method for Removing Water From Underwater Images

4. SyreaNet: A Physically Guided Underwater Image Enhancement Framework Integrating Synthetic and Real Images

5. Underwater Species Detection using Channel Sharpening Attention

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