May 2019
Intermediate to advanced
272 pages
7h 19m
English
Content preview from Hands-On Generative Adversarial Networks with Keras
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Input normalization
We have two cases of normalization:
- Normalize the images between 0 and 1, where Sigmoid is added to the output of the generator.
- Normalize the images between -1 and 1, where Tanh is added to the output of the generator
In both cases, these preceding alterations not only normalize the inputs but also make their ranges bounded, which is helpful for training.
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