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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Martin Schneider, Jens Gayko, Christian Goerick,
"About robust hypotheses generation and object validation in traffic scenes",
IEEE Intelligent Vehicles Symposium (IV), 2007.
Abstract
Environmental perception is an important element of Advanced Driver Assistance Systems. The perception mainly consists of the steps sensing and data interpretation. Both of these steps are affected by errors due to noise and misinterpretations. Therefore, we present a system design addressing the problem of robust processing under limited resources in a hierarchical system architecture that can use state of the art data-fusion and object-recognit...
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Andreas Knoblauch, Marc-Oliver Gewaltig, Rüdiger Kupper, Ursula Körner, Edgar Körner,
"Improving the storage capacity of neocortical associative networks by structural plasticity and hippocampal training.",
Proceedings of the 4th HRI Global Workshop on Advances in Computational Intelligence, pp. 17–26, 2007.
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Till Steiner, Lisa Schramm, Yaochu Jin, Bernhard Sendhoff,
"Emergence of Feedback in Artificial Gene Regulatory Networks",
IEEE Congress on Evolutionary Computation, CEC, 2007.
Abstract
In this paper, we present a model for simulating the evolution of development together with a method for the analysis of emergence of negative feedback inside the regulatory network. In order to record the development of feedback during evolution, we analyze both the static as well as the dynamic interactions between the transcription factors in the regulatory network. When perturbing the gene regulatory network using random mutations, we find th...
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Tobias Rodemann, Kalina Karova, Frank Joublin, Christian Goerick,
"Purely Auditory Online-Adaptation of Auditory-Motor Maps",
IEEE-RSJ International Conference on Intelligent Robot and Systems (IROS 2007), 2007.
Abstract
We present a system for an online-adaptation of auditory-motor maps that doesn't require a special set-up or dedicated robot movements and can therefore work during the normal operation of the robot. Our approach is based purely on auditory cues and motor position feedback for estimating the correct sound source position. The system can learn the correct auditory-motor map within 1–2 hours, starting from a random initialization, in a room with ...
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Yaochu Jin, Bernhard Sendhoff, Edgar Körner,
"Rule extraction from compact Pareto-optimal neural networks",
Multi-objective Evolutionary Algorithms for Knowledge from Databases, Springer, 2007.
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Mark Toussaint, Michael Gienger, Christian Goerick,
"Optimization of Sequential Attractor-based Movement for Compact Behaviour Generation",
IEEE-RAS International Conference on Humanoid Robots, 2007.
Abstract
In this paper, we propose a novel method to generate optimal robot motion based on a sequence of attractor dynamics in task space. This is motivated by the biological evidence that movements in the motor cortex of animals are encoded in a similar fashion – and by the need for compact movement representations on which efficient optimization can be performed. We represent the motion as a sequence of attractor points acting in the task space of th...
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