Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee,
"Efficient hierarchical parallel genetic algorithms using grid computing",
Future Generation Computer Systems – The International Journal of Grid Computing: Theory, Methods and Applications, vol. 23, no. 4, pp. 658-670, 2007.
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Ingo Paenke, Bernhard Sendhoff, Jon Rowe, Chrisantha Fernando,
"On the Adaptive Disadvantage of Lamarckianism in Rapidly Changing Environments",
Advances in Artificial Life – Proceedings of the 9th European Conference ECAL, pp. 355–364, 2007.
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Cem Karaoguz,
"Adaptation of Gaze Fixation for An Active Stereo Vision System",
University of Applied Sciences Darmstadt, 2007.
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Pan Zhang, Xin Yao, Lei Ja, Bernhard Sendhoff, Thorsten Schnier,
"Target shape design optimization by evolving splines",
IEEE Congress on Evolutionary Computation, CEC, pp. 2009–2016, 2007.
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Toyotaka Sonoda, Martina Hasenjäger, Toshiyuki Arima, Bernhard Sendhoff,
"Effect of endwall contouring on performance of ultra-low aspect ratio transonic turbine inlet guide vanes",
Proceedings of the ASME Turbo Expo, 2007.
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Hans Plesser, Jochen Eppler, Abigail Morrison, Markus Diesmann, Marc-Oliver Gewaltig,
"Efficient parallel Simulation of Large-Scale Neuronal Networks on Clusters of Multiprocessor Computers",
Euro-Par 2007 Parallel Processing, issue Volume 4641/2007, pp. 672-681, 2007.
Abstract
To understand the principles of information processing in the brain, we depend on models with more than 10^5 neurons and 10^9 connections. These networks can be described as graphs of threshold elements that exchange point events over their connections. From the computer science perspective, the key challenges are to represent the connections succinctly; to transmit events and update neuron states efficiently; and to provide a comfortable user in...
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Heiko Wersing, Stephan Kirstein, Michael Götting, Holger Brandl, Mark Dunn, Inna Mikhailova, Christian Goerick, Jochen Steil, Helge Ritter, Edgar Körner,
"Online Learning of Objects in a Biologically Motivated Visual Architecture",
International Journal of Neural Systems, vol. 17, no. 4, pp. 219–230, 2007.
Abstract
We present a biologically motivated architecture for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The system combines biological principles such as appearance-based representation in topographical feature detection hierarchies and context-driven transfer between different levels of object memory. Training can be performed in an unconstrained environment by presenting objects i...
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Nils Einecke,
"Analysis of nonlinear dimensionality reduction for view-based object parameterization",
TU Ilmenau, 2007.
Abstract
Compact and descriptive object representation is a key element for object recognition and tracking. Traditional view-based object representations usually consist of a number of alternative view representatives, leading to a spotty representation in a high dimensional feature space. What is lacking in such a representation is the notion that each view representative is related to low dimensional parameters that characterize the objects appearance ...
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Florian Röhrbein, Julian Eggert, Edgar Körner,
"Prototypical Relations for Cortex-Inspired Semantic Representations",
Proceedings of the 8th International Conference on Cognitive Modeling (ICCM 2007), pp. 307-312, 2007.
Abstract
Cognitive systems for the representation of declarative knowledge like semantic networks and other graph-based systems are widely unrelated to characteristic neurobiological mechanisms in the brain. In this contribution we report on our efforts in bridging the gap between typical semantic relations like “is part of”, “has property” etc. and the laminar wiring pattern of the neocortex. Central to our approach is the identification of the c...
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Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff,
"Adaptive modeling strategy for continuous multi-objective optimization",
IEEE Congress on Evolutionary Computation, pp. 431-437, 2007.
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