87 citations · 282 across the 59 of their papers we have counts for
60 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…
Smart membrane: high content in situ monitoring barrier on chip with artificial neural network
Bo Tang, Victor Krajka, Mengxi Liu +7
Conventional transepithelial electrical resistance (TEER) technique provides only a low-content analysis of cell-layer conditions, necessitating repeated microscopic assessments of…
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…
A Case Study on Energy-Efficient Edge AI Crack Segmentation
Matthias Tschope, Mohamed Moursi, Vladimir Rybalkin +3
Crack segmentation on edge devices can support continuous infrastructure monitoring and maintenance and thereby help to preserve public safety. Furthermore, autonomous infrastructu…
This Is Taking Too Long -- Investigating Time as a Proxy for Energy Consumption of LLMs
Lars Krupp, Daniel Geißler, Francisco M. Calatrava-Nicolas +3
The energy consumption of Large Language Models (LLMs) is raising growing concerns due to their adverse effects on environmental stability and resource use. Yet, these energy costs…