Comparison of Generative Adversarial Networks (GAN) and CNN
If GAN is compared to CNN than it outclass CNN because GAN has generation capability and it can work with unlabeled data because it belongs to unsupervised learning techniques.
Generative Adversarial Networks Uses
GANs open up deep learning to a broader range of unsupervised tasks in which labeled data does not exist or is too expensive to obtain. They also reduce the load required for a deep neural network because the two systems share the burden. Expect to see more business applications, such as cyber detection, employ GANs.
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