Perceptions
2021
Daniela Mihai and Jonathon Hare

Perceptions is a study of how a machine perceives a photograph at different layers within its neural network. We generate sets of pen strokes which are drawn by a robot using pen and ink on Bristol board. The illustrations are produced by maximising the similarity between the machine's internal perception of the illustration and chosen target photographs. The study focusses on the difference between different inductive biases (shape versus texture) in the training of the neural network, as well as how the machine's perception changes as a function of depth within its network. The photos chosen are from travels to far away cities, taken before the COVID-19 pandemic.