ContrastSense: domain-invariant contrastive learning for in-the-wild wearable sensing
Existing wearable sensing models often struggle with domain shifts and class label scarcity. Contrastive learning is a promising technique to address class label scarcity, which however captures domain-related features and suffers from low-quality negatives. To address both problems, we propose Cont...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/182272 |