activity
20242026
most citedMulti-modal Atmospheric Sensing to Augment Wearable IMU-Based Hand Washing Detection

4 citations · 8 across the 19 of their papers we have counts for

collaborators

21 papers

cs.CV2026

X-MULTI: VLM-based Imaging Factor Disentanglement for Factor-Aware Image Synthesis

Sonali Godavarthy, Matthias Neuwirth-Trapp, Tim-Felix Faasch +4

Imaging factor disentanglement in text-to-image generation aims to independently control image acquisition properties such as types of camera lenses, sensor types, viewpoints, and…

cs.LG2026

A Comparison of Fusion Techniques for Multi-Modal Human Activity Recognition on the HARMES Dataset

Ahmed Mohamady, Robin Burchard, Kristof Van Laerhoven

Recent advances in Human Activity Recognition (HAR) from wearable sensors have shown that multi-modal deep learning models consistently outperform their uni-modal counterparts. Mod…

cs.LG2026

HARMES: A Multi-Modal Dataset for Wearable Human Activity Recognition with Motion, Environmental Sensing and Sound

Robin Burchard, Pascal-André Brückner, Marius Bock +2

With each sensing modality exhibiting inherent strengths and limitations, multi-modal approaches for wearable Human Activity Recognition (HAR) are becoming increasingly relevant --…

cs.RO2026

Eye-Tracking-Driven Control in Daily Task Assistance for Assistive Robotic Arms

Anke Fischer-Janzen, Thomas M. Wendt, Kristof Van Laerhoven

Shared control improves Human-Robot Interaction by reducing the user's workload and increasing the robot's autonomy. It allows robots to perform tasks under the user's supervision.…

cs.NI2025

Environment-Aware Indoor LoRaWAN Path Loss: Parametric Regression Comparisons, Shadow Fading, and Calibrated Fade Margins

Nahshon Mokua Obiri, Kristof Van Laerhoven

Indoor long range wide area network (LoRaWAN) propagation is shaped by structural and time-varying environmental factors, which limit single-slope log-distance models and the stand…

cs.CV2025

-Quant: Towards Learnable Quantization for Low-bit Pattern Recognition

Mishal Fatima, Shashank Agnihotri, Marius Bock +4

Most pattern recognition models are developed on pre-proce\-ssed data. In computer vision, for instance, RGB images processed through image signal processing (ISP) pipelines design…