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This Convolutional Neural Network (CNN) learned through many training samples to recognize certain objects. The network consists of several consecutive layers that have learned during the training phase to recognize different characteristics in an image and pass on this information in turn to the next layer. While the first layers recognize more primitive characteristics such as straight lines, colors, and curves, the next layers specialize in more complex forms. The network VGG16 used here is one of the best-known models of this kind.
Credit: Ars Electronica - Robert Bauernhansl
This is a painting I have reimagined with Google's DeepDream convolutional neural network software -- Neuroscience and Artificial Intelligence are two of my greatest passions and they are of great interest to the field of art.
Kyriaki Goni
Counting Craters on the Moon
Aksioma Project Space
Komenskega 18, Ljubljana
2–25 October 2019
Production: Aksioma - Institute for Contemporary Art, Ljubljana, 2019
Photo: Janez Janša
This Convolutional Neural Network (CNN) learned through many training samples to recognize certain objects. The network consists of several consecutive layers that have learned during the training phase to recognize different characteristics in an image and pass on this information in turn to the next layer. While the first layers recognize more primitive characteristics such as straight lines, colors, and curves, the next layers specialize in more complex forms. The network VGG16 used here is one of the best-known models of this kind.
Photo: Philipp Greindl