Deep Learning from Vasulkas Video Archive

Authors

HORÁKOVÁ Jana SCHIMMEL Jiří SIKORA Pavel

Year of publication 2019
Type R&D Presentation
MU Faculty or unit

Faculty of Arts

Citation
Description Audio-visual document describing three ways how to sort the Vašulkas's video archive content with help of artificial neural networks. The goal of the project is to experimentally test the utility of artificial neural networks in service of media art historiography and theory. Artificial neural networks conduct iconographic and audiographic analyses of the Woody and Steina Vasulka video archive. We suppose that the application of deep learning technologies in the study of the archive content could serve not only for data mining purposes but, more importantly, can become a creative means for rethinking the poetics of early electronic art. Project Credits: Application partners of the project are: The Vašulka Kitchen Brno – Center for New Media Art and The Brno House of Arts. The project (TL02000270 Media Art Live Archive) is conducted with financial support from TA ČR. Technological Agency of the Czech Republic.
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