6 papers · 1 filter
Collaborative Temporal Feature Generation via Critic-Free Reinforcement Learning for Cross-User Sensor-Based Activity Recognition
Xiaozhou Ye, Feng Jiang, Zihan Wang +3
Human Activity Recognition using wearable inertial sensors is foundational to healthcare monitoring, fitness analytics, and context-aware computing, yet its deployment is hindered…
Reinforcement Learning Driven Generalizable Feature Representation for Cross-User Activity Recognition
Xiaozhou Ye, Kevin I-Kai Wang
Human Activity Recognition (HAR) using wearable sensors is crucial for healthcare, fitness tracking, and smart environments, yet cross-user variability -- stemming from diverse mot…
Graph-Based Adversarial Domain Generalization with Anatomical Correlation Knowledge for Cross-User Human Activity Recognition
Xiaozhou Ye, Kevin I-Kai Wang
Cross-user variability poses a significant challenge in sensor-based Human Activity Recognition (HAR) systems, as traditional models struggle to generalize across users due to diff…
Domain-Adversarial Anatomical Graph Networks for Cross-User Human Activity Recognition
Xiaozhou Ye, Kevin I-Kai Wang
Cross-user variability in Human Activity Recognition (HAR) remains a critical challenge due to differences in sensor placement, body dynamics, and behavioral patterns. Traditional…
Adversarial Domain Adaptation for Cross-user Activity Recognition Using Diffusion-based Noise-centred Learning
Xiaozhou Ye, Kevin I-Kai Wang
Human Activity Recognition (HAR) plays a crucial role in various applications such as human-computer interaction and healthcare monitoring. However, challenges persist in HAR model…
Deep Generative Domain Adaptation with Temporal Attention for Cross-User Activity Recognition
Xiaozhou Ye, Kevin I-Kai Wang
In Human Activity Recognition (HAR), a predominant assumption is that the data utilized for training and evaluation purposes are drawn from the same distribution. It is also assume…