Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks

Daniel Berio, Memo Akten, Frédéric Fol Leymarie, Mick Grierson and Réjean Plamondon

Paper (2017)

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Department:	Department of Electrical Engineering
ISBN:	9781450352093
PolyPublie URL:	https://publications.polymtl.ca/38998/
Conference Title:	4th International Conference on Movement Computing (MOCO 2017)
Conference Location:	London, UK
Conference Date(s):	2017-06-28 - 2017-06-30
Publisher:	ACM
DOI:	10.1145/3077981.3078049
Official URL:	https://doi.org/10.1145/3077981.3078049
Date Deposited:	18 Apr 2023 15:04
Last Modified:	08 Apr 2025 12:22

Cite in APA 7:	Berio, D., Akten, M., Leymarie, F. F., Grierson, M., & Plamondon, R. (2017, June). Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks [Paper]. 4th International Conference on Movement Computing (MOCO 2017), London, UK. https://doi.org/10.1145/3077981.3078049
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