The Augmented Museum - A Machinic Experience with Deep Learning
Immanuel Koh · Proceedings of the International Conference on Computer-Aided Architectural Design Research in Asia · 2020
Today we witness a shift in the role with which museum used to play -- from one that was simply a spatial container filled with physical artworks on display, to one that is now layered with the digital/online version of the artworks themselves. Deep learning algorithms have become an important means to process such large datasets of digital artworks in providing an alternative curatorial practice (biased/unbiased), and consequentially, augmenting the navigation of the museum's physical spaces. In collaboration with a selection of museums, a series of web/mobile applications have been made to investigate the potential of such machinic inference, as well as interference of the physical experience.