January 2019
Intermediate to advanced
316 pages
8h 16m
English
Content preview from Generative Adversarial Networks Projects
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Adversarial loss
The adversarial loss is the loss between the image from the real distribution A or B, and the images generated by the generator networks. We have two mapping functions and we will be applying adversarial loss to both of the mappings.
The adversarial loss for the mapping 
is written as follows:
Here, x is an image from one domain from distribution A, and y is an image from another domain from distribution B. The discriminator tries to distinguish between the image generated by the G mapping (), and the real image y from a different ...
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