43 citations
- Fraunhofer Institute for Manufacturing Engineering and AutomationDE2 papers
- GESIS - Leibniz Institute for the Social SciencesDE2 papers
- Institute of Science TokyoJP2 papers
- University of Duisburg-EssenDE2 papers
- University of MannheimDE2 papers
- University of StuttgartDE2 papers
- Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-InstitutDE1 paper
- Fraunhofer Institute for Transportation and Infrastructure SystemsDE1 paper
- Fraunhofer Institute of Optronics, System Technologies and Image ExploitationDE1 paper
- Karlsruhe Institute of TechnologyDE1 paper
- Technische Hochschule MannheimDE1 paper
- The University of TokyoJP1 paper
4 papers · 1 filter
Know What Not To Know: Users' Perception of Abstaining Classifiers
Andrea Papenmeier, Daniel Hienert, Yvonne Kammerer +2
Machine learning systems can help humans to make decisions by providing decision suggestions (i.e., a label for a datapoint). However, individual datapoints do not always provide e…
Balancing of competitive two-player Game Levels with Reinforcement Learning
Florian Rupp, Manuel Eberhardinger, Kai Eckert
The balancing process for game levels in a competitive two-player context involves a lot of manual work and testing, particularly in non-symmetrical game levels. In this paper, we…
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…
How Accurate Does It Feel? -- Human Perception of Different Types of Classification Mistakes
Andrea Papenmeier, Dagmar Kern, Daniel Hienert +2
Supervised machine learning utilizes large datasets, often with ground truth labels annotated by humans. While some data points are easy to classify, others are hard to classify, w…