Semi-Supervised Authentically Distorted Image Quality Assessment with Consistency-Preserving Dual-Branch Convolutional Neural Network-Reference-Cited by-同舟云学术

Semi-Supervised Authentically Distorted Image Quality Assessment with Consistency-Preserving Dual-Branch Convolutional Neural Network

Published:2022 Issue: Volume: Page:1-13
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Yue Guanghui¹^ORCID,Cheng Di¹,Li Leida²^ORCID,Zhou Tianwei³,Liu Hantao⁴^ORCID,Wang Tianfu¹^ORCID

Affiliation:

1. National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, the School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China

2. School of Artificial Intelligence, Xidian University, Xi'an, China

3. College of Management, Shenzhen University, Shenzhen, China

4. School of Computer Science and Informatics, Cardiff University, Cardiff, U.K

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Natural Science Foundation of Shenzhen

Shenzhen Science and Technology Program

Tencent Rhinoceros Birds Scientific Research Foundation for Young Teachers of Shenzhen University

Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6046/4456689/09903545.pdf?arnumber=9903545

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