Enhancing biomechanical machine learning with limited data: generating realistic synthetic posture data using generative artificial intelligence

Objective: Biomechanical Machine Learning (ML) models, particularly deep-learning models, demonstrate the best performance when trained using extensive datasets. However, biomechanical data are frequently limited due to diverse challenges. Effective methods for augmenting data in developing ML model...

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Bibliographic Details
Published in:Frontiers in bioengineering and biotechnology Vol. 12; p. 1350135
Main Authors: Dindorf, Carlo, Dully, Jonas, Konradi, Jürgen, Wolf, Claudia, Becker, Stephan, Simon, Steven, Huthwelker, Janine, Werthmann, Frederike, Kniepert, Johanna, Drees, Philipp, Betz, Ulrich, Fröhlich, Michael
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media SA 14.02.2024
Frontiers Media S.A
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ISSN:2296-4185, 2296-4185
Online Access:Get full text
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