A comparative study of super-resolution algorithms for video streaming application-Reference-Cited by-同舟云学术

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A comparative study of super-resolution algorithms for video streaming application

Published:2023-10-13 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

He Xiaonan,Qiao Yuansong,Lee Brian,Ye Yuhang^ORCID

Funder

Presidents Doctoral Scholarship, Technological University of the Shannon

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-17230-8.pdf

Reference37 articles.

1. Jiang J, Sekar V, Zhang H (2014) Improving fairness, efficiency, and stability in http-based adaptive video streaming with festive. IEEE/ACM Trans Netw 22:326–340

2. Li Z, Zhu X, Gahm J, Pan R, Hu H, Begen A, Oran D (2014) Probe and adapt: rate adaptation for http video streaming at scale. IEEE J Sel Areas Commun 32:719–733

3. Wen W, Ren W, Shi Y, Nie Y, Zhang J, Cao X (2022) Video super-resolution via a spatio-temporal alignment network. IEEE Trans Image Process 31:1761–1773

4. Zhang W, Zhou M, Ji C, Sui X, Bai J (2022) Cross-frame transformer-based spatio-temporal video super-resolution. IEEE Trans, Broadcast

5. Chen Z, Yang W, Yang J (2022) Video super-resolution network using detail component extraction and optical flow enhancement algorithm. Appl Intell 1–13

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. DRCNN-WS: A Novel Approach for High-Resolution Video Using Recurrent Neural Networks and Walrus Search;2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO);2024-03-14

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