A machine-learning-driven solution to the problem of perceptual video quality metrics | Zendy

Stamos Katsigiannis | Zendy; Hassan Rabah | Zendy; Naeem Ramzan | Zendy

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A machine-learning-driven solution to the problem of perceptual video quality metrics

Author(s) -

Stamos Katsigiannis,

Hassan Rabah,

Naeem Ramzan

Publication year - 2020

Publication title -

institution of engineering and technology ebooks

Language(s) - English

Resource type - Book series

DOI - 10.1049/pbpc034e_ch12

Subject(s) - computer science , video quality , subjective video quality , quality of experience , mean opinion score , pevq , quality (philosophy) , peak signal to noise ratio , the internet , fidelity , coding (social sciences) , multimedia , real time computing , video tracking , artificial intelligence , video processing , image quality , video compression picture types , computer network , quality of service , metric (unit) , statistics , telecommunications , world wide web , philosophy , epistemology , operations management , mathematics , economics , image (mathematics)

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