GAN image processing method and system
An image processing and image technology, applied in the field of image processing, can solve problems such as poor generalization ability, difficult convergence, and easy gradient disappearance, and achieve high quality, avoid gradient disappearance, and good generalization ability
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[0037] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.
[0038] The embodiment of the invention discloses a GAN image processing method, see figure 1 Shown and figure 2 As shown, the method includes:
[0039] Step S11: Receive random noise, and use an improved LSGAN-based generation network to generate a generated image.
[0040] Specifically, based on the improved LSGAN (Loss Sensitive GAN, loss-sensitive generative adversarial network), a system including the first fully connected layer, the first
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