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Found 3 papers, 1 papers with code
HierMUD: Hierarchical Multi-task Unsupervised Domain Adaptation between Bridges for Drive-by Damage Diagnosis
Monitoring bridge health using vibrations of drive-by vehicles has various benefits, such as no need for directly installing and maintaining sensors on the bridge.
Knowledge transfer between bridges for drive-by monitoring using adversarial and multi-task learning
Specifically, we train a deep network in an adversarial way to learn features that are 1) sensitive to damage and 2) invariant to different bridges.
Incremental Real-Time Personalization in Human Activity Recognition Using Domain Adaptive Batch Normalization
Previous work has addressed this challenge by personalizing general recognition models to the unique motion pattern of a new user in a static batch setting.
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