Granular Dance
Autorzy:
Daniel Bisig
Opublikowane w:
Conference: 9th Conference on Computation, Communication, Aesthetics & X, 2021, Strona(/y) 176 - 195, ISBN 978-989-9049-06-2
Wydawca:
i2ADS, Research Institute in Art, Design and Society, School of Fine Arts, University of Porto
Strings P
Autorzy:
Daniel Bisig, Ephraim Wegner, Harald Kimmig
Opublikowane w:
Proceedings of the 9th Conference on Computation, Communication, Aesthetics & X, 2021, Strona(/y) 546 - 553, ISBN 978-989-9049-06-2
Wydawca:
i2ADS, Research Institute in Art, Design and Society, School of Fine Arts, University of Porto
Puppeteering an AI - Interactive Control of a Machine-Learning based Artificial Dancer
Autorzy:
Daniel Bisig, Ephraim Wegner
Opublikowane w:
Proceedings of the XXIII conference on Generative Art, 2021, Strona(/y) 315 - 332, ISBN 978-88-96610-43-5
Wydawca:
Domus Argenia Publisher
Raw Music from Free Movements: Early Experiments in Using Machine Learning toCreate Raw Audio from Dance Movements
Autorzy:
Daniel Bisig, Kivanç Tatar
Opublikowane w:
Proceedings of the 2nd Conference on AI Music Creativity, 2021, ISBN 978-3-200-08272-4
Wydawca:
Institute of Electronic Music and Acoustics / University of Music and Performing Arts, Graz
Puppeteering AI - Interactive Control of an Artificial Dancer
Autorzy:
Daniel Bisig, Ephraim Wegner
Opublikowane w:
Proceedings of the Generative AI and HCI - CHI 2022 Workshop, 2022
Wydawca:
Self Published
Expressive Aliens - Laban Effort Factors for Non-Anthropomorphic Morphologies
(odnośnik otworzy się w nowym oknie)
Autorzy:
Daniel Bisig
Opublikowane w:
Artificial Intelligence in Music, Sound, Art and Design, 11th International Conference, EvoMUSART 2022, Numer Lecture Notes in Computer Science (LNCS, volume 13221), 2022, Strona(/y) 36-51, ISBN 978-3-031-03789-4
Wydawca:
Springer Cham
DOI:
10.1007/978-3-031-03789-4_3
Generative Dance - a Taxonomy and Survey
(odnośnik otworzy się w nowym oknie)
Autorzy:
Daniel Bisig
Opublikowane w:
Proceedings of the 8th International Conference on Movement and Computing, 2022, ISBN 978-1-4503-8716-3
Wydawca:
Association for Computing Machinery
DOI:
10.1145/3537972.3537978
