66 citations · 158 across the 15 of their papers we have counts for
6 papers · 1 filter
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…
Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation
Jibinraj Antony, Florian Schlather, Georgij Safronov +2
With the rise of deep learning models in the field of computer vision, new possibilities for their application in industrial processes proves to return great benefits. Nevertheless…
On-site Online Feature Selection for Classification of Switchgear Actuations
Christina Nicolaou, Ahmad Mansour, Kristof Van Laerhoven
As connected sensors continue to evolve, interest in low-voltage monitoring solutions is increasing. This also applies in the area of switchgear monitoring, where the detection of…