984 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of StuttgartDE21 papers
- Fraunhofer Institute for Industrial EngineeringDE2 papers
- Fraunhofer Institute of Optronics, System Technologies and Image ExploitationDE2 papers
- Heilbronn UniversityDE2 papers
- Software (Germany)DE2 papers
- Stuttgart Media UniversityDE2 papers
- Carnegie Mellon UniversityUS1 paper
- Delft University of TechnologyNL1 paper
- Deutscher WetterdienstDE1 paper
- Esslingen University of Applied SciencesDE1 paper
- Forschungszentrum JülichDE1 paper
- Friedrich-Alexander-Universität Erlangen-NürnbergDE1 paper
9 papers · 1 filter
PerSival: Neural-network-based visualisation for pervasive continuum-mechanical simulations in musculoskeletal biomechanics
David Rosin, Johannes Kässinger, Xingyao Yu +3
This paper presents a novel neural network architecture for the purpose of pervasive visualisation of a 3D human upper limb musculoskeletal system model. Bringing simulation capabi…
Self-supervised Optimization of Hand Pose Estimation using Anatomical Features and Iterative Learning
Christian Jauch, Timo Leitritz, Marco F. Huber
Manual assembly workers face increasing complexity in their work. Human-centered assistance systems could help, but object recognition as an enabling technology hinders sophisticat…
Information-based Preprocessing of PLC Data for Automatic Behavior Modeling
Brandon K. Sai, Jonas Gram, Thomas Bauernhansl
Cyber-physical systems (CPS) offer immense optimization potential for manufacturing processes through the availability of multivariate time series data of actors and sensors. Based…
Automated Machine Learning for Remaining Useful Life Predictions
Marc-André Zöller, Fabian Mauthe, Peter Zeiler +2
Being able to predict the remaining useful life (RUL) of an engineering system is an important task in prognostics and health management. Recently, data-driven approaches to RUL pr…
Reduction of finite sampling noise in quantum neural networks
David A. Kreplin, Marco Roth
Quantum neural networks (QNNs) use parameterized quantum circuits with data-dependent inputs and generate outputs through the evaluation of expectation values. Calculating these ex…
Quantum Gaussian Process Regression for Bayesian Optimization
Frederic Rapp, Marco Roth
Gaussian process regression is a well-established Bayesian machine learning method. We propose a new approach to Gaussian process regression using quantum kernels based on paramete…
Designing the mobile robot Kevin for a life science laboratory
Sarah Kleine-Wechelmann, Kim Bastiaanse, Matthias Freundel +1
Laboratories are being increasingly automated. In small laboratories individual processes can be fully automated, but this is usually not economically viable. Nevertheless, individ…
INoD: Injected Noise Discriminator for Self-Supervised Representation Learning in Agricultural Fields
Julia Hindel, Nikhil Gosala, Kevin Bregler +1
Perception datasets for agriculture are limited both in quantity and diversity which hinders effective training of supervised learning approaches. Self-supervised learning techniqu…
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction
Jonas Kneifl, David Rosin, Oliver Röhrle +1
In recent decades, the main focus of computer modeling has been on supporting the design and development of engineering prototyes, but it is now ubiquitous in non-traditional areas…