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@misc{1596539,
author = {Horáková, Jana and Schimmel, Jiří and Sikora, Pavel},
address = {Linec, Rakousko},
edition = {1.},
keywords = {deep learning; machine learnig; media archive; video art; poetics; Woody and Steina Vasulka},
language = {eng},
location = {Linec, Rakousko},
publisher = {Ars Electronica Festival},
title = {Deep Learning from Vasulkas Video Archive},
url = {https://ars.electronica.art/outofthebox/en/deep-learning/},
year = {2019}
}
TY - GEN
ID - 1596539
AU - Horáková, Jana - Schimmel, Jiří - Sikora, Pavel
PY - 2019
TI - Deep Learning from Vasulkas Video Archive
PB - Ars Electronica Festival
CY - Linec, Rakousko
KW - deep learning
KW - machine learnig
KW - media archive
KW - video art
KW - poetics
KW - Woody and Steina Vasulka
UR - https://ars.electronica.art/outofthebox/en/deep-learning/
L2 - https://ars.electronica.art/outofthebox/en/deep-learning/
N2 - 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.
ER -
HORÁKOVÁ, Jana, Jiří SCHIMMEL and Pavel SIKORA. \textit{Deep Learning from Vasulkas Video Archive}. 1st ed. Linec, Rakousko: Ars Electronica Festival, 2019.
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