Generative Adversarial and Self-Supervised Dehazing Network

Author:

Zhang Shengdong1ORCID,Zhang Xiaoqin1ORCID,Wan Shaohua2ORCID,Ren Wenqi3ORCID,Zhao Liping4ORCID,Shen Linlin5ORCID

Affiliation:

1. Key Laboratory of Intelligent Informatics for Safety and Emergency of Zhejiang Province, Wenzhou University, Wenzhou, China

2. Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China

3. School of Cyber Science and Technology, Sun Yat-sen University, Shenzhen, China

4. Department of Computer Science and Engineering, Shaoxing University, Shaoxing, China

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

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation

Science and Technology Plan Project in Basic Public Welfare Class of Shaoxing City

Guangdong Basic and Applied Basic Research Foundation

Shenzhen Municipal Science and Technology Innovation Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

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4. GAN-based E-D Network to Dehaze Satellite Images;Data and Metadata;2024-05-28

5. A Semantic-Consistent Conditional Generative Adversarial Model for Zero-Shot Learning In Bearing Fault Diagnosis;2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS);2024-05-17

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