Open Access
SHS Web Conf.
Volume 144, 2022
2022 International Conference on Science and Technology Ethics and Human Future (STEHF 2022)
Article Number 03002
Number of page(s) 6
Section Application of Artificial Intelligence Technology and Machine Learning Algorithms
Published online 26 August 2022
  1. G. Wu, A study on the function of artificial intelligence machine learning to assist script creativity [J]. Arts Management, 2020, (02):57-63. [Google Scholar]
  2. T. Sun, Application of artificial intelligence in the field of film and television media [J]. Journal of Journalism Research, 2020, 11(21):253-254. [Google Scholar]
  3. Y. Chai, The opportunities and challenges of artificial intelligence for film and television industry [J]. Modern Film Technology, 2020(10):51-55. [Google Scholar]
  4. C. Olah, Understanding lstm networks, 2015. [Google Scholar]
  5. H. Mo, J. Zhao, The application of face aging and reverse aging technology in film special effects production [J]. Modern Film Technology, 2021(2):914. [Google Scholar]
  6. D. Dong, B. Li, The development and application of age-defying visual effects technology in The Irishman [J]. Modern Film Technology, 2021(6):18-24. [Google Scholar]
  7. X. Bai, An introduction to the application of artificial intelligence in film restoration [J]. Modern Film Technology, 2020(5):52-55. DOI:10.3969/j.issn.1673-3215.2020.05.010. [Google Scholar]
  8. C. Dong, C. C. Loy, K. He and X. Tang, Image SuperResolution Using Deep Convolutional Networks, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 2, pp. 295-307, Feb. 1, 2016, doi: 10.1109/TPAMI.2015.2439281. [Google Scholar]
  9. C. Ledig, L. Theis, F. Huszár, et al. Photo-realistic single image super-resolution using a generative adversarial network. In Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 4681-4690. [Google Scholar]
  10. X. Wang, K. Yu, S. Wu, et al. Esrgan: Enhanced super-resolution generative adversarial networks. In Proceedings of the European conference on computer vision (ECCV) workshops, 2018, pp. 0-0. [Google Scholar]

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