Generative Adversarial Network (GAN) trained on 60,000+ abstract images
How Neural Visions Work
These artworks are generated using Deep Convolutional GANs trained on a mix of cubist, surreal, and digital art. The generator learns style patterns while the discriminator critiques originality, evolving new forms.
- 64-layer deep ResNet architecture
- 200,000 training steps
- AdaBelief optimizer with weight clipping
