PREDICTING TEMPORAL FILTER EFFECTS ON QUALITY OF VIDEO SEQUENCES
DOI:
https://doi.org/10.24867/05BE38KudusKeywords:
Video quality, Image processing, Machine learningAbstract
This paper describes a machine learning algorithm for predicting temporal filter effects on video sequences.
References
[1] Vladimir Crnojević, “Prepoznavanje oblika za inženjere”, FTN Izdavaštvo, Novi Sad, 2014.
[2] Josh Patterson, Adam Gibson, “Deep learning- a practitioner's approach“, Sebastopol, CA 2017
[3] Dr. V. Petrovic, Mr. M. Willcox, Mr. C. B. Jackson, “Augmenting enhanced video quality assessment and enhanced Video quality control-milestone M2 report”, 2019.
[4] Deeplearning.ai, https://www.coursera.org/learn/introduction-tensorflow
[5] Deeplearning.ai, https://www.coursera.org/learn/convolutional-neural-networks-tensorflow
[6] Deeplearning.ai, https://www.youtube.com/channel/UCcIXc5mJsHVYTZR1maL5l9w
[2] Josh Patterson, Adam Gibson, “Deep learning- a practitioner's approach“, Sebastopol, CA 2017
[3] Dr. V. Petrovic, Mr. M. Willcox, Mr. C. B. Jackson, “Augmenting enhanced video quality assessment and enhanced Video quality control-milestone M2 report”, 2019.
[4] Deeplearning.ai, https://www.coursera.org/learn/introduction-tensorflow
[5] Deeplearning.ai, https://www.coursera.org/learn/convolutional-neural-networks-tensorflow
[6] Deeplearning.ai, https://www.youtube.com/channel/UCcIXc5mJsHVYTZR1maL5l9w
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Published
2019-11-05
Issue
Section
Electrotechnical and Computer Engineering
