MCSTN learns corruption-invariant representations by enforcing consistency across dual-level simulated corruptions using a dual-stream spatio-temporal architecture for robust sensor-based HAR.
Human Activity Recognition (HAR) Using Deep Learning: Review, Methodologies, Progress and Future Research Directions: P. Kumar et al
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Leveraging Imperfect Medical Data: A Manifold-Consistent Spatio-Temporal Network for Sensor-based Human Activity Recognition
MCSTN learns corruption-invariant representations by enforcing consistency across dual-level simulated corruptions using a dual-stream spatio-temporal architecture for robust sensor-based HAR.