26 citations · 103 across the 33 of their papers we have counts for
5 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…
KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition
Mengxi Liu, Sizhen Bian, Vitor Fortes +5
Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional data but struggle to maintain performance on noisy a…
Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook
Sizhen Bian, Mengxi Liu, Lala Shakti Swarup Ray +7
Sensor-based Human Activity Recognition (HAR) underpins many ubiquitous and wearable computing applications, yet current models remain limited by scarce labels, sensor heterogeneit…
Calibration-Free Induced Magnetic Field Indoor and Outdoor Positioning via Data-Driven Modeling
Qiushi Guo, Matthias Tschoepe, Mengxi Liu +2
Induced magnetic field (IMF)-based localization offers a robust alternative to wave-based positioning technologies due to its resilience to non-line-of-sight conditions, environmen…