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Alexander Gepperth, Britta Mersch, Christian Goerick, Jannik Fritsch, "Color object recognition in real-world scenes", Artificial Neural Networks, 17th International Conference ICANN, Part II, Springer Verlag, pp. 583-592, 2007.
AbstractThis work investigates the role of color in object recognition. We approach the problem from a computational perspective by measuring the performance of biologically inspired object recognition methods. As benchmarks, we use image datasets proceeding from a real-world object detection scenario and compare classification performance using color and gray-scale versions of the same datasets. In order to make our results as general as possible, we co...
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Volker Willert, Mark Toussaint, Julian Eggert, Edgar Körner, "Uncertainty Optimization for Robust Dynamic Optical Flow Estimation", Proceedings of the 2007 International Conference on Machine Learning and Applications (ICMLA), 2007.
AbstractWe develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of motion information using a dynamic and robust prior that incorporates spatial and temporal coherence constraints on the flow field. The main contribution is the embedding of these particular assumptions on optical flow evolution into the Bayesian propagation approach that...
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Michael Gienger, Bram Bolder, Mark Dunn, Hisashi Sugiura, Herbert Janßen, Christian Goerick, "Predictive behaviour generation - A sensor-based walking and reaching architecture for humanoid robots", Autonome Mobile Systeme 2007, issue siebte, pp. 275-281, 2007.
AbstractThis contribution presents a sensor-based walking and reaching architecture for humanoid robots. It enables a humanoid robot to interact with its environment using a smooth whole body motion control driven by stabilized visual targets. Interactive selection mechanisms are used to switch between behavior alternatives for searching or tracking objects as well as different whole body motion strategies for reaching. The decision between different mot...
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Gökhan Ince, "Noise Reduction During Ego-motion of the Head", Technische Universität Darmstadt, 2007.
AbstractAn active auditory perception system is very essential for robots to be able to interact with their environment. Tasks like sound localization and speech recognition have to be performed with high accuracy even when the head (or whole robot) is moving. However, the movement of the head inevitably generates noise due to its motors. This problem is very crucial, because the motors are located closer to the microphones than the sound sources. Consid...
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Yaochu Jin, Ruojing Wen, Bernhard Sendhoff, "Evolutionary multi-objective optimization of spiking neural networks", Artificial Neeural Networks-ICANN, 17. International Conference, 2007.
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Zdravko Bozakov, "Unsupervised Component Extraction for Design Optimization using Feature Analysis Methods", TU Darmstadt, 2007.
AbstractEvolutionary algorithms offer an approach to alleviate some of the difficulties existing in traditional design optimization techniques. The choice of an appropriate design representation greatly influences the quality of achievable solutions. Representations which encode shapes using deformations applied to an initial design allow the number of optimization parameters to be decoupled from the complexity of the evaluated design. A novel technique ...
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Ingo Fründ, "Speed in early visual processing", Universität Magdeburg, 2007.
AbstractThe visual system of vertebrates rapidly provides a basis for execution of behavioral responses (Kirchner & Thorpe, 2006). At the same time it is up to amazingly detailed representations of the environment and even learning of these representations. Different investigators have proposed mechanisms how a network of neurons could achieve either the speed (see Thorpe et al., 2001) or the analytic capability (e.g. Freeman, 2003; König & Krüger, 200...
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Ingo Paenke, Bernhard Sendhoff, Tadeusz Kawecki, "Influence of plasticity and learning on evolution under directional selection", American Naturalist, vol. 170, no. 2, pp. 1–12, 2007.
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Florian Röhrbein, Julian Eggert, Edgar Körner, "A Cortex-Inspired Neural-Symbolic Network for Knowledge Representation", Proceedings of the IJCAI Workshop on Neural-Symbolic Learning and Reasoning, 2007.
AbstractSemantic systems for the representation of declarative knowledge are usually unconnected to neurobiological mechanisms in the brain. In this paper we report on efforts to bridge this gap by proposing a neural-symbolic network based on processing principles of the cortical column. We show how a locally controlled activation spread on conceptual nodes leads to bottom-up and top-down processing streams which allow for feature inheritance, context ef...
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Marc-Oliver Gewaltig and Markus Diesmann, "NEST (Neural Simulation Tool)", Scholarpedia Encyclopedia of Computational Neuroscience, online, pp. 11204, 2007.
AbstractThe Neural Simulation Tool NEST is a computer program for simulating large heterogeneous networks of point neurons or neurons with a small number of compartments. NEST is best suited for models that focus on the dynamics, size, and structure of neural systems rather than on the detailed morphological and biophysical properties of individual neurons. Examples are: * Models of sensory processing e.g. in the visual or auditory cortex of mammals. * M...
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