Johannes Bauer

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—We present an algorithm based on the self-organizing map (SOM) which models multi-sensory integration as realized by the superior colliculus (SC). Our algorithm differs from other algorithms for multi-sensory integration in that it learns mappings between modalities' coordinate systems, it learns their respective reliabilities for different points in(More)
—Considerable time and effort often go into designing and implementing experimental setups (ES) in robotics. These activities are usually not at the focus of our research and thus go underreported. This results in replication of work and lack of comparability. This paper lays out our view of the theoretical considerations necessary when deciding on the type(More)
In this paper, we describe an approach for ontology comprehension support called model exploration in which models for ontologies are generated and presented interactively. We also discuss the issues involved in using tableau reasoners for the generation of models for model exploration and report on a user study we conducted on our prototype implementation,(More)
With information about the world implicitly embedded in complex, high-dimensional neural population responses, the brain must perform some sort of statistical inference on a large scale to form hypotheses about the state of the environment. This ability is, in part, acquired after birth and often with very little feedback to guide learning. This is a very(More)
Top-down cognitive processes affect the way bottom-up cross-sensory stimuli are integrated. In this paper, we therefore extend a successful previous neural network model of learning multisensory integration in the superior colliculus (SC) by top-down, attentional input and train it on different classes of cross-modal stimuli. The network not only learns to(More)
(2014): Modeling development of natural multi-sensory integration using neural self-organisation and probabilistic population codes, Connection Science, Taylor & Francis makes every effort to ensure the accuracy of all the information (the " Content ") contained in the publications on our platform. Taylor & Francis, our agents, and our licensors make no(More)
— Mobile assistive robots can enhance elderly peo-ple's perception of safety and prevent loss of confidence at home. Therefore, multi-modal systems that allow robots to operate in complex environments represent an enticing milestone for self-care and independent living applications. We present a humanoid robot that assists a person in daily activities and(More)
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