The optimization network video quality assessment method based on fuzzy inference
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-021-02092-0.pdf
Reference33 articles.
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3. Tao, Xiaoming, Duan, Yiping, Mai, Xu., Meng, Zhishen, Jianhua, Lu.: Learning QoE of mobile video transmission with deep neural network: a data-driven approach”. IEEE Journal on Selected Areas in Communications 37(6), 1337–1348 (2019)
4. Zhang, Yu., Gao, X., He, L., et al.: Objective video quality assessment combining transfer learning with CNN. IEEE Trans. Neural Networks and Learn. Syst 31(8), 2716–2730 (2020)
5. Ling, S., Gutiérrez, J., Ke, Gu., Le Callet, P.: Prediction of the influence of navigation scan-path on perceived quality of free-viewpoint videos. IEEE J. Emerg. Select Topics. Circ. Syst 9(1), 204–216 (2019)
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