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Results tagged with generative-adversarial-networks
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user 85241
For questions related to generative adversarial networks (GANs), introduced in the paper Generative Adversarial Nets (2014) by J. Goodfellow et al. A GAN is composed of a discriminative model (D) and a generative model (G). The discriminator D needs to distinguish between data generated by the generator G and data in the training set, while the generator G needs to generate data such that the discriminator D is not able to accomplish its task.
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WGAN-GP loss never converging, terrible image quality
I'm a beginner in Deep learning area. I've been working on my WGAN-GP model to generate some radar images, and I'm using my own dataset which is relatively very small(1309 images with 128*128 pixels). …
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