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Thomas Michalke, Jannik Fritsch, Christian Goerick , "Enhancing Robustness of a Saliency-based Attention System for Driver Assistance", The 6th International Conference on Computer Vision Systems (ICVS), 2008.
AbstractBiologically motivated attention systems prefilter the visual environment for scene elements that pop out most or match the current system task best. However, the robustness of biological attention systems is difficult to achieve, given e.g., the high variability of scene content, changes in illumination, and scene dynamics. Most computational attention models do not show real time capability or are tested in a controlled indoor environment only....
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Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff , "Combination of EDA and DE for Continuous Bi-objective Optimization", Congress on Evolutionary Computation, pp. pp.1447-1454, 2008.
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Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick, Sethu Vijayakumar , "Learning potential-based policies from constrained motions", International Conference on Humanoid Robots, 2008.
AbstractWe present a method for learning potential-based policies from constrained motion data. In contrast to previous approaches to direct policy learning, our method can combine observations from a variety of contexts where different constraints are in force, to learn the underlying unconstrained policy in form of its potential function. This allows us to generalise and predict behaviour where novel constraints apply. As a key ingredient, we first cre...
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Manuel Mühlig , "Task learning of bimanual object handling", TU Ilmenau, 2008.
AbstractThe focus of this work lies on providing the humanoid robot ASIMO with the ability to learn new bi-manual tasks through the observation of object trajectories. For this, an imitation learning framework is presented which allows the robot to learn the essence of an observed movement task by application of probabilistic encoding with Gaussian Mixture Models. The learned information is used to initialize an attractor-based movement generation algori...
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Volker Willert, Jens Schmüdderich, Julian Eggert, Christian Goerick, Edgar Körner , "Probabilistic Optical Flow Estimation for Large Pixel Displacements Utilizing Egomotion Flow Compensation", British Machine Vision Conference 2008, pp. 695-704, 2008.
AbstractThe pixel movements in an image sequence grabbed by a camera that is mounted on a mobile platform comprise the superposition of several motion components. These motion components are caused by the egomotion of the camera and by the different movements of the objects seen by the camera. Utilizing sensory information from a calibrated stereo rig and egomotion measurements of the mobile platform we develop a probabilistic framework that estimates op...
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Ingo Paenke , "Dynamics of evolution and learning", University of Karlsruhe, 2008.
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Christian Igel and Bernhard Sendhoff , "Genesis of organic computing systems: Coupling evolution and learning", Organic Computing, pp. 141–166, 2008.
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Andreas Knoblauch , "Symbols and embodiment from the perspective of a neural modeller.", Symbols and Embodiment: Debates on Meaning and Cognition., Oxford University Press, pp. 117–143, 2008.
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Andreas Knoblauch, Friedrich Sommer, Marc-Oliver Gewaltig, Rüdiger Kupper, Ursula Körner, Edgar Körner , "On the collective computational abilities of inhibitory neurons.", Proceedings of the 5th Computational and Systems Neuroscience Meeting (COSYNE), pp. 160, 2008.
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Alexander Denecke, Heiko Wersing, Jochen Steil, Edgar Körner , "Robust object segmentation by adaptive metrics in Generalized LVQ", Proceedings of the European Symposium on Artificial Neural Networks (ESANN), pp. 319–324, 2008.
AbstractWe investigate the effect of several adaptive metrics in the context of figure-ground segregation, using Generalized LVQ to train a classifier for image regions. Extending the Euclidean metrics towards local matrices of relevance-factors does not only lead to a higher classification accuracy and increased robustness on heterogeneous/noisy data, but also figureground segregation using this adaptive metrics enables a considerably higher recognition...
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