2 citations · 5 across the 5 of their papers we have counts for
5 papers
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional Mamba
Shuangjian Li, Tao Zhu, Furong Duan +4
Wearable sensor-based human activity recognition (HAR) is a critical research domain in activity perception. However, achieving high efficiency and long sequence recognition remain…
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer
Shuangjian Li, Tao Zhu, Mingxing Nie +3
Traditional deep learning methods struggle to simultaneously segment, recognize, and forecast human activities from sensor data. This limits their usefulness in many fields such as…
A Multi-Task Deep Learning Approach for Sensor-based Human Activity Recognition and Segmentation
Furong Duan, Tao Zhu, Jinqiang Wang +3
Sensor-based human activity segmentation and recognition are two important and challenging problems in many real-world applications and they have drawn increasing attention from th…
Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition
Jinqiang Wang, Tao Zhu, Liming Chen +2
Contrastive learning has been applied to Human Activity Recognition (HAR) based on sensor data owing to its ability to achieve performance comparable to supervised learning with a…
Sensor Data Augmentation by Resampling for Contrastive Learning in Human Activity Recognition
Jinqiang Wang, Tao Zhu, Jingyuan Gan +3
While deep learning has contributed to the advancement of sensor-based Human Activity Recognition (HAR), it is usually a costly and challenging supervised task with the needs of a…