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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| Published in: | Frontiers in bioengineering and biotechnology Vol. 12; p. 1350135 |
|---|---|
| Main Authors: | , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Switzerland
Frontiers Media SA
14.02.2024
Frontiers Media S.A |
| Subjects: | |
| ISSN: | 2296-4185, 2296-4185 |
| Online Access: | Get full text |
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