My process is to create raw materials using neural networks (GANs), composite them together by hand, and transfer the results to a gilded panel. For now, I am creating the designs inscribed on gold by hand in Illustrator. The process … Read More
In a recent post, I worked on improving the raw material my GANs pass along for me to use making composite portraits. I noticed that the Renaissance faces I’m using for training do a lot more head tilting than the … Read More
My project imagines stories told through pictures by distant future artificial intelligent machines, who rummage through humanity’s physical traces, finding mostly e-waste and some preserved works of art. I am training neural networks (GANs) to create new images from large … Read More
I’ve been using faces extracted from Renaissance paintings to train the neural networks (GANs) and create “new” faces and portraits. I am collaborating with these neural networks to make portraits of what distant future artificially intelligent machines might remember as … Read More
I hoped that transfer learning would allow me to do more with less. Less training data, less computing power, and less time. In the context of image generation with GANs, transfer learning means taking a neural network (GAN) trained on … Read More
This week I showed some of the pieces I’ve made so far to fellow students and faculty in the Digital Futures program at OCAD U. A quick recap: my project asks how intelligent machines would portray their own creation if … Read More
Using the same datasets over and over when training leads to Neural Networks that generate repetitive results. I am trying different approaches to control the kind of images my Networks generate. Previously, I have tried under-training a CycleGAN to hybridize … Read More
I wanted to see if I could pre-train a network on various kinds of art before adding my Renaissance faces dataset. Maybe, like with generalized Style Transfer, the network would pick up some general insights about images from the larger … Read More
