17 papers
LITEWAY: LIghtweight HAR via Temporal Efficient highWAY
Dominique Nshimyimana, Vitor Fortes Rey, Mengxi Liu +2
Wearable human activity recognition (HAR) remains challenging due to the computational and energy constraints of deep learning models on resource-limited devices. Existing lightwei…
VSMP-IMU: Video-Grounded Semantic Motion Programs for Sensor-Aware Synthetic IMU Generation
Lala Shakti Swarup Ray, Vitor Fortes Rey, Mengxi Liu +2
Wearable human activity recognition (HAR) is often limited by the scarcity of labeled sensor data, especially in low-resource, class-imbalanced, and subject-generalization settings…
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…
Embedded Inter-Subject Variability in Adversarial Learning for Inertial Sensor-Based Human Activity Recognition
Francisco M. Calatrava-Nicolás, Shoko Miyauchi, Vitor Fortes Rey +3
This paper addresses the problem of Human Activity Recognition (HAR) using data from wearable inertial sensors. An important challenge in HAR is the model's generalization capabili…
On the Generalization Limits of Quantum Generative Adversarial Networks with Pure State Generators
Jasmin Frkatovic, Akash Malemath, Ivan Kankeu +7
We investigate the capabilities of Quantum Generative Adversarial Networks (QGANs) in image generations tasks. Our analysis centers on fully quantum implementations of both the gen…