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

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

Paper (2017)

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Department: Department of Electrical Engineering
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: 05 Apr 2024 11:34
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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