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Philipp Schwesig, "Development of a Realtime System for Gender Adaptive Formant Extraction", University of Applied Sciences Frankfurt, 2008.

Abstract

The purpose of this diploma thesis is the extension of the existing formant extraction system to the parameter of the gender. The formants describing the resonance frequencies of the vocal tract are slightly different for male and female speakers. This was the essential point leading to the attempt of improving the robustness of the existing formant extraction system by the gender information. Previous to this diploma thesis it has been shown tha...



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Jens Schmüdderich, Volker Willert, Julian Eggert, Sven Rebhan, Christian Goerick, Gerhard Sagerer, Edgar Körner, "Estimating Object Proper Motion Using Optical Flow, Kinematics, and Depth Information", IEEE Systems, Man, and Cybernetics Part B: Cybernetics, vol. 38, no. 4, pp. 1139-1151, 2008.

Abstract

For the interaction of a mobile robot with a dynamic environment, the estimation of object motion is desired while the robot is walking and/or turning its head. In this paper, we describe a system which manages this task by combining depth from a stereo camera and computation of the camera movement from robot kinematics in order to stabilize the camera images. Moving objects are detected by applying optical flow to the stabilized images followed ...



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Ingo Paenke, Tadeusz Kawecki, Bernhard Sendhoff, "The influence of learning on evolution – A mathematical framework", Artificial Life, vol. 15, no. 2, 2008.



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Sebastian Kannengiesser, "Hippokampales Indizieren reichhaltiger sensorischer Information", University of Tuebingen, 2008.



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Dudy Lim, Yaochu Jin, Yew-Soon Ong, Bernhard Sendhoff, "Generalizing Surrogate-Assisted Evolutionary Computation", IEEE Transactions on Evolutionary Computation, 2008.



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Andreas Knoblauch, "The role of silent synapses and structural plasticity for memory and amnesia in a model of cortico-hippocampal interplay.", Proceedings of the 11th Neural Computation and Psychology Workshop (NCPW), 2008.



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Claudius Gläser, Frank Joublin, Christian Goerick, "Homeostatic Development of Dynamic Neural Fields", Proceedings of the IEEE 7th International Conference on Development and Learning (ICDL), pp. 121-126, 2008.

Abstract

Dynamic neural field theory has become a popular technique for modeling the spatio-temporal evolution of activity within the cortex. When using neural fields the right balance between excitation and inhibition within the field is crucial for a stable operation. Finding this balance is a severe problem, particularly in face of experience-driven changes of synaptic strengths. Homeostatic plasticity where the objective function for each unit is to r...



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Andreas Knoblauch, "Neural associative memory and the Willshaw-Palm probability distribution.", SIAM Journal on Applied Mathematics, vol. 69(1), pp. 169–196, 2008.



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Jannik Fritsch, Thomas Michalke, Alexander Gepperth, Sven Bone, Falko Waibel, Marcus Kleinehagenbrock, Jens Gayko, Christian Goerick, "Towards a Human-like Vision System for Driver Assistance", Proceedings of the IEEE Intelligent Vehicles Symposium (IV), 2008.

Abstract

Several Advanced Driver Assistance Systems realizing elementary perception and analysis tasks have been introduced to market in recent years. For example, collision mitigation brake systems detect the distance and relative velocity of vehicles in front to assess the risk of a rear-end collision in a clearly defined following situation. In order to go beyond such elementary analysis tasks, today's research is focusing more and more on powerful per...



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Claudius Gläser, Frank Joublin, Christian Goerick, "Enhancing Topology Preservation during Neural Field Development via Wiring Length Minimization", Proceedings of the 18th International Conference on Artificial Neural Networks - ICANN 2008, Part I, Springer Verlag, pp. 593–602, 2008.

Abstract

We recently proposed a recurrent neural network model for the development of dynamic neural fields [1]. The learning regime incorporates homeostatic processes, such that the network is able to selforganize and maintain a stable operation mode even in face of experiencedriven changes in synaptic strengths. However, the learned mappings do not necessarily have to be topology preserving. Here we extend our model by incorporating another mechanism wh...



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