Deep Convolutional Generative Adversarial Networks (dcgan) are ai architectural structures used for conveluted systems, that do not depend on the standard mean-squared error pathing, and so these ai systems learn of their own volition. dcgans are typically used to generate unique content.
Deep Convolutional Generative Adversarial Networks (dcgan) are architectural structures used for conveluted systems, that do not depend on the standard mean-squared error pathing, and so thse ai systems learn of their own volition. dcgans are typically used to generate unique content.
dcgan typically comprises two parts;
The discriminator, which learns how to distinguish fake from real objects of the type we’d like to create
The generator, which creates new content and tries to fool the discriminator
