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1 Ergebnisse
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Efficiency of deep neural networks for joint angle modeling..:
Conte Alcaraz, Javier
;
Moghaddamnia, Sanam
;
Peissig, Jürgen
DOI:https://doi.org/10.1186/s13634-020-00715-1. , 2021
Link:
https://www.repo.uni-hannover.de/handle/123456789/1126
RT Journal T1
Efficiency of deep neural networks for joint angle modeling in digital gait assessment
UL https://suche.suub.uni-bremen.de/peid=base-ftunivhannover:oai:www.repo.uni-hannover.de:123456789_11265&Exemplar=1&LAN=DE A1 Conte Alcaraz, Javier A1 Moghaddamnia, Sanam A1 Peissig, Jürgen PB Heidelberg : Springer YR 2021 K1 Deep neural network K1 Digital gait analysis K1 Machine learning K1 Nonlinear modeling K1 Inertial measurement unit K1 ddc:620 JF DOI:https://doi.org/10.1186/s13634-020-00715-1 LK http://dx.doi.org/https://www.repo.uni-hannover.de/handle/123456789/11265 DO https://www.repo.uni-hannover.de/handle/123456789/11265 SF ELIB - SuUB Bremen
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