26 citations · 103 across the 33 of their papers we have counts for
6 papers · 1 filter
You Don't Need To Train: Agentic Heuristic Learning Studio for Executable Human Activity Recognition
Siyu Yuan, He Zhang, Sizhen Bian +1
Human activity recognition (HAR) is usually framed as gradient-based training of neural networks. Agentic Heuristic Learning (AHL) Studio explores a complementary view inspired by…
EdgeHAR: An Edge-Native Compact Sensor Foundation Model for Human Activity Recognition
He Zhang, Siyu Yuan, Siyu Liu +2
Sensor-based human activity recognition (HAR) is fundamental to ubiquitous and wearable computing, yet existing foundation models are largely designed for cloud-scale deployment an…
Bridging Generalization and Personalization in Human Activity Recognition via On-Device Few-Shot Learning
Pixi Kang, Julian Moosmann, Mengxi Liu +4
Human Activity Recognition (HAR) with different sensing modalities requires both strong generalization across diverse users and efficient personalization for individuals. However,…
Initial Investigation of Kolmogorov-Arnold Networks (KANs) as Feature Extractors for IMU Based Human Activity Recognition
Mengxi Liu, Daniel Geißler, Dominique Nshimyimana +3
In this work, we explore the use of a novel neural network architecture, the Kolmogorov-Arnold Networks (KANs) as feature extractors for sensor-based (specifically IMU) Human Activ…
iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets
Mengxi Liu, Sizhen Bian, Bo Zhou +1
This work proposes an incremental learning (IL) framework for wearable sensor human activity recognition (HAR) that tackles two challenges simultaneously: catastrophic forgetting a…
Worker Activity Recognition in Manufacturing Line Using Near-body Electric Field
Sungho Suh, Vitor Fortes Rey, Sizhen Bian +5
Manufacturing industries strive to improve production efficiency and product quality by deploying advanced sensing and control systems. Wearable sensors are emerging as a promising…