• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Using Fuzzy Neural Network to Assess Network Video Quality

Vol. 16, No. 7, July 31, 2022
10.3837/tiis.2022.07.014, Download Paper (Free):

Abstract

At present people have higher and higher requirements for network video quality, but video quality will be impaired by various factors, so video quality assessment has become more and more important. This paper focuses on the video quality assessment method using different fuzzy neural networks. Firstly, the main factors that impair the video quality are introduced, such as unit time jamming times, average pause time, blur degree and block effect. Secondly, two fuzzy neural network models are used to build the objective assessment method. By adjusting the network structure to optimize the assessment model, the objective assessment value of video quality is obtained. Meanwhile the advantages and disadvantages of the two models are analysed. Lastly, the proposed method is compared with many recent related assessment methods. This paper will give the experimental results and the detail of assessment process.


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Cite this article

[IEEE Style]
Z. Shi, "Using Fuzzy Neural Network to Assess Network Video Quality," KSII Transactions on Internet and Information Systems, vol. 16, no. 7, pp. 2377-2389, 2022. DOI: 10.3837/tiis.2022.07.014.

[ACM Style]
Zhiming Shi. 2022. Using Fuzzy Neural Network to Assess Network Video Quality. KSII Transactions on Internet and Information Systems, 16, 7, (2022), 2377-2389. DOI: 10.3837/tiis.2022.07.014.

[BibTeX Style]
@article{tiis:25847, title="Using Fuzzy Neural Network to Assess Network Video Quality", author="Zhiming Shi and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2022.07.014}, volume={16}, number={7}, year="2022", month={July}, pages={2377-2389}}