Deep Domain Adaptation, Pseudo-Labeling, and Shallow Network for Accurate and Fast Gait Prediction of Unlabeled Datasets
Developing personalized gait phase prediction models is difficult because acquiring accurate gait phases requires expensive experiments. This problem can be addressed via semi-supervised domain adaptation (DA), which minimizes the discrepancy between the source and target subject features. However,...
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| Main Authors: | , , , |
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| Format: | Book |
| Published: |
IEEE,
2023-01-01T00:00:00Z.
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |