Multitask Deep Neural Network With Knowledge-Guided Attention for Blind Image Quality Assessment-Reference-Cited by-同舟云学术

Multitask Deep Neural Network With Knowledge-Guided Attention for Blind Image Quality Assessment

Published:2024-08 Issue:8 Volume:34 Page:7577-7588
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Zhou Tianwei¹^ORCID,Tan Songbai¹^ORCID,Zhao Baoquan²^ORCID,Yue Guanghui³^ORCID

Affiliation:

1. School of Management, Shenzhen University, Shenzhen, China

2. School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China

3. National-Regional Key Technology Engineering Laboratory for Medical Ultrasound and Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

National Natural Science Foundation of China

Social Science Youth Foundation of Ministry of Education of China

Natural Science Foundation of Shenzhen

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

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/76/10634006/10464346.pdf?arnumber=10464346

Reference61 articles.

1. Data-Driven Transform-Based Compressed Image Quality Assessment

2. A No-Reference Metric for Perceived Ringing Artifacts in Images

3. No-Reference Screen Content Image Quality Assessment With Unsupervised Domain Adaptation

4. EHNQ: Subjective and Objective Quality Evaluation of Enhanced Night-Time Images

5. Perceptual Quality Assessment of Enhanced Colonoscopy Images: A Benchmark Dataset and an Objective Method

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Adaptive Mixed-Scale Feature Fusion Network for Blind AI-Generated Image Quality Assessment;IEEE Transactions on Broadcasting;2024