32 citations
- University of SalzburgAT4 papers
- Halmstad UniversitySE2 papers
- Pädagogische Hochschule SalzburgAT2 papers
- Coburg University of Applied SciencesDE1 paper
- Delft University of TechnologyNL1 paper
- Graz University of TechnologyAT1 paper
- Hochschule Campus WienAT1 paper
- Technische Universität BerlinDE1 paper
- Universidade Federal do TocantinsBR1 paper
- Universitätszahnklinik WienAT1 paper
- University of ViennaAT1 paper
10 papers
An Architecture for Deploying Reinforcement Learning in Industrial Environments
Georg Schäfer, Reuf Kozlica, Stefan Wegenkittl +1
Industry 4.0 is driven by demands like shorter time-to-market, mass customization of products, and batch size one production. Reinforcement Learning (RL), a machine learning paradi…
-continuous Spline Approximation with TensorFlow Gradient Descent Optimizers
Stefan Huber, Hannes Waclawek
In this work we present an "out-of-the-box" application of Machine Learning (ML) optimizers for an industrial optimization problem. We introduce a piecewise polynomial model (splin…
A Commons-Compatible Implementation of the Sharing Economy: Blockchain-Based Open Source Mediation
Petra Tschuchnig, Manfred Mayr, Maximilian Tschuchnig +1
The network economical sharing economy, with direct exchange as a core characteristic, is implemented both, on a commons and platform economical basis. This is due to a gain in imp…
Experimental analysis regarding the influence of iris segmentation on the recognition rate
Heinz Hofbauer, Fernando Alonso-Fernandez, Josef Bigun +1
In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will ex…
Iris super-resolution using CNNs: is photo-realism important to iris recognition?
Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez
The use of low-resolution images adopting more relaxed acquisition conditions such as mobile phones and surveillance videos is becoming increasingly common in iris recognition nowa…
Randomized Local Fast Rerouting for Datacenter Networks with Almost Optimal Congestion
Gregor Bankhamer, Robert Elsässer, Stefan Schmid
To ensure high availability, datacenter networks must rely on local fast rerouting mechanisms that allow routers to quickly react to link failures, in a fully decentralized manner.…