66 citations · 129 across the 6 of their papers we have counts for
6 papers
Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensors
Alexander Hoelzemann, Julia Lee Romero, Marius Bock +2
We present a benchmark dataset for evaluating physical human activity recognition methods from wrist-worn sensors, for the specific setting of basketball training, drills, and game…
A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors
Alexander Hoelzemann, Kristof Van Laerhoven
Research into the detection of human activities from wearable sensors is a highly active field, benefiting numerous applications, from ambulatory monitoring of healthcare patients…
Tutorial on Deep Learning for Human Activity Recognition
Marius Bock, Alexander Hoelzemann, Michael Moeller +1
Activity recognition systems that are capable of estimating human activities from wearable inertial sensors have come a long way in the past decades. Not only have state-of-the-art…
Detecting Handwritten Mathematical Terms with Sensor Based Data
Lukas Wegmeth, Alexander Hoelzemann, Kristof Van Laerhoven
In this work we propose a solution to the UbiComp 2021 Challenge by Stabilo in which handwritten mathematical terms are supposed to be automatically classified based on time series…
Transformer Networks for Data Augmentation of Human Physical Activity Recognition
Sandeep Ramachandra, Alexander Hoelzemann, Kristof Van Laerhoven
Data augmentation is a widely used technique in classification to increase data used in training. It improves generalization and reduces amount of annotated human activity data nee…
Improving Deep Learning for HAR with shallow LSTMs
Marius Bock, Alexander Hoelzemann, Michael Moeller +1
Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms. One popular Deep Learning arc…