Biying Deng1
, Desheng Zheng1, *, Zhifeng Liu1
, Yanling Lai1, Zhihong Zhang2
Journal of Quantum Computing, Vol.3, No.3, pp. 119-126, 2021, DOI:10.32604/jqc.2021.017250
- 21 December 2021
Abstract There are two difficult in the existing image restoration methods. One
is that the method is difficult to repair the image with a large damaged, the other
is the result of image completion is not good and the speed is slow. With the
development and application of deep learning, the image repair algorithm based
on generative adversarial networks can repair images by simulating the
distribution of data. In the process of image completion, the first step is trained the
generator to simulate data distribution and generate samples. Then a large number
of falsified images More >
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