Deep Learning Approach for No-Reference Screen Content Video Quality Assessment-Reference-Cited by-同舟云学术

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Deep Learning Approach for No-Reference Screen Content Video Quality Assessment

Published:2024-06 Issue:2 Volume:70 Page:555-569
ISSN:0018-9316
Container-title:IEEE Transactions on Broadcasting
language:
Short-container-title:IEEE Trans. on Broadcast.

Author:

Kwong Ngai-Wing¹^ORCID,Chan Yui-Lam¹^ORCID,Tsang Sik-Ho¹^ORCID,Huang Ziyin¹^ORCID,Lam Kin-Man¹^ORCID

Affiliation:

1. Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China

Funder

Hong Kong Research Grants Council (RGC) under Research

Innovation and Technology Fund - Partnership Research Programme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/11/10552063/10479473.pdf?arnumber=10479473

Reference49 articles.

1. Screen Content Quality Assessment: Overview, Benchmark, and Beyond

2. Overview of Screen Content Coding in Recently Developed Video Coding Standards

3. Video quality assessment: A review of full-referenced, reduced-referenced and no-referenced methods

4. Perceptual image quality assessment: a survey

5. Recent developments and future trends in visual quality assessment;Liu

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. Enhancing QoE for Multi-Device Video Delivery: A Novel Dataset and Model Perspective;IEEE Transactions on Broadcasting;2024

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