Generating Images of University of Virginia Architecture with GANs ; Regulating Innovation: How Advocates Fight for Algorithmic Regulation

Arthur Harris
Digital systems imperfectly sense and represent external phenomena, constraining their capacity to depict or interpret them accurately or equitably. Generative modeling can now create realistic images. To evaluate generative modeling of complex images, images of the University of Virginia’s Rotunda were generated through a Generative Adversarial Network (GAN). The model required several thousand iterations to roughly approximate the Rotunda’s shape. Such results indicate that with sufficient training examples, time to train, and hardware, generative modeling...
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