no code implementations • 4 Apr 2023 • Nilah Ravi Nair, Fernando Moya Rueda, Christopher Reining, Gernot A. Fink
On-body device (OBD) recordings of human movements are often preferred for HAR applications not only for their reliability but as an approach for identity protection, e. g., in industrial settings.
no code implementations • 19 Jan 2023 • Nilah Ravi Nair, Lena Schmid, Fernando Moya Rueda, Markus Pauly, Gernot A. Fink, Christopher Reining
It is unknown what physical characteristics and/or soft-biometrics, such as age, height, and weight, need to be taken into account to train a classifier to achieve robustness towards heterogeneous populations in the training and testing data.
no code implementations • 2 Dec 2022 • Shrutarv Awasthi, Fernando Moya Rueda, Gernot A. Fink
HAR is challenging due to the inter and intra-variance of human movements; moreover, annotated datasets from on-body devices are scarce.
no code implementations • 28 Oct 2021 • Stefan Lüdtke, Fernando Moya Rueda, Waqas Ahmed, Gernot A. Fink, Thomas Kirste
Here, we show how such context information can be integrated systematically into a deep neural network-based HAR system.
no code implementations • 2 Feb 2018 • Fernando Moya Rueda, Gernot A. Fink
Attribute representations became relevant in image recognition and word spotting, providing support under the presence of unbalance and disjoint datasets.
no code implementations • 21 Jul 2017 • Fernando Moya Rueda, Rene Grzeszick, Gernot A. Fink
Furthermore, it will be shown that neuron pruning can be combined with subsequent weight pruning, reducing the size of the LeNet-5 and VGG16 up to $92\%$ and $80\%$ respectively.