5 papers · 1 filter
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 --…
FedFitTech: A Baseline in Federated Learning for Fitness Tracking
Zeyneddin Oz, Shreyas Korde, Marius Bock +1
The rapid evolution of sensors and resource-efficient machine learning models has spurred the widespread adoption of wearable fitness tracking devices. Equipped with inertial senso…
Label Leakage in Federated Inertial-based Human Activity Recognition
Marius Bock, Maximilian Hopp, Kristof Van Laerhoven +1
While prior work has shown that Federated Learning updates can leak sensitive information, label reconstruction attacks, which aim to recover input labels from shared gradients, ha…
DeepConvContext: A Multi-Scale Approach to Timeseries Classification in Human Activity Recognition
Marius Bock, Michael Moeller, Juergen Gall +1
Despite recognized limitations in modeling long-range temporal dependencies, Human Activity Recognition (HAR) has traditionally relied on a sliding window approach to segment label…
Temporal Action Localization for Inertial-based Human Activity Recognition
Marius Bock, Michael Moeller, Kristof Van Laerhoven
As of today, state-of-the-art activity recognition from wearable sensors relies on algorithms being trained to classify fixed windows of data. In contrast, video-based Human Activi…