Abstract
Hidden Worlds is a series of artworks created by Machine Learning exploring gender through the lens of computer vision. The works are first created by a DCGAN, then responded to by J. Rosenbaum before being reinterpreted into a generative narrative using image classifiers and tied together using Augmented Reality. This collaborative series of works is part of Rosenbaum's ongoing work with machines using 3D Modeling, machine learning and Augmented Reality.
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Cite
CITATION STYLE
Rosenbaum, J. (2019). Hidden worlds. In Proceedings of the 10th International Conference on Computational Creativity, ICCC 2019 (pp. 352–353). Association for Computational Creativity (ACC). https://doi.org/10.51444/ij.v17i02.394
Readers over time
Readers' Seniority
Readers' Discipline
