Semantic-discriminative mixup for generalizable sensor-based cross-domain activity recognition
It is expensive and time-consuming to collect sufficient labeled data to build human activity recognition (HAR) models. Training on existing data often makes the model biased towards the distribution of the training data, thus the model might perform terribly on test data with different distribution...
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Main Authors: | , , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/164234 |
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Institution: | Nanyang Technological University |
Language: | English |