Self-Supervised Adaptive Illumination Estimation for Low-Light Image Enhancement-Reference-Cited by-同舟云学术

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Self-Supervised Adaptive Illumination Estimation for Low-Light Image Enhancement

Published:2024-04 Issue:2 Volume:8 Page:1882-1893
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Yu Ting¹^ORCID,Wang Shuai¹^ORCID,Chen Wei¹^ORCID,Yu F. Richard²^ORCID,Leung Victor C. M.³^ORCID,Tian Zijian¹^ORCID

Affiliation:

1. School of Artificial Intelligence, China University of Mining and Technology, Beijing, China

2. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada

3. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

Funder

National Natural Science Foundation of China

Open Research Fund of Key Laboratory of Wireless Sensor Network and Communication

Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences

Chinese Academy of Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7433297/10480102/10429762.pdf?arnumber=10429762

Reference59 articles.

1. Coded exposure photography

2. Learning Degradation Representations for Image Deblurring

3. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

4. YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors

5. Simple online and realtime tracking with a deep association metric

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