Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick, Sethu Vijayakumar,
"A Novel Method for Learning Policies from Constrained Motion",
International Conference on Robotics and Automation (ICRA), 2009.
Abstract
Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently change between contexts. In this paper, we present a novel approach for learning (unconstrained) control policies from movement data, where observations come from movements under different constraints. As a key ingredient, we introduce a small but highly effective modifica...
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Stefan Menzel,
"Topographic Arrangement of 3D Design Components on 2D Maps by Unsupervised Feature Extraction",
Proceedings of World Academy of Science, Engineering and Technology, issue Volume 55, pp. 74–81, 2009.
Abstract
As a result of the daily workflow in the design development departments of companies, databases containing huge numbers of 3D geometric models are generated. According to the given problem engineers create CAD drawings based on their design ideas and evaluate the performance of the resulting design, e.g. by computational simulations. Usually, new geometries are built either by utilizing and modifying sets of existing components or by adding singl...
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Jeanette Schadow, Daniel Lenz, Nicole Dettler, Ingo Fründ, Christoph Herrmann,
"Early gamma-band responses reflect anticipatory top-down modulation in the auditory cortex",
NeuroImage, vol. 47, no. 2, pp. 651-658, 2009.
Abstract
For efficient and fast encoding of our complex acoustic environment, not only aspects of bottom-up processing are significant, but rather top-down influences such as attention, memory, and anticipation promote specific behavior and perception. Neural oscillatory activity in the gamma-range (30-80 Hz) is discussed as a conceivable candidate to represent very rapid modulations of top-down factors. We investigated effects of anticipation on early ga...
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Alexander Denecke, Heiko Wersing, Jochen Steil, Edgar Körner,
"Online Figure-Ground Segmentation with Adaptive Metrics in Generalized LVQ",
Neurocomputing, vol. 72, no. 7-9, pp. 1470-1482, 2009.
Abstract
We address the problem of fast figure-ground segmentation of single objects from cluttered backgrounds to improve object learning and recognition. For the segmentation, we use an initial foreground hypothesis to train a classifier for figure and ground on topographically ordered feature maps with Generalized Learning Vector Quantization. We investigate the contribution of several adaptive metrics to enable generalization to the main object parts ...
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Björn Schölling,
"Binaural Signal Processing",
Technische Universität Darmstadt, 2009.
Abstract
The processing and analysis of audio signals play an important role in the interaction of humans and robots. Crucial for the performance of such methods, e.g. speech recognition and source localization, is that the signal of interest is dominant in comparison to the other perceived audio signals. Interfering speech signals, noise, and echoes (reverbera- tion) lead to a severe degradation in performance, and methods that are able to filter the des...
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Bernhard Sendhoff, Edgar Körner, Olaf Sporns,
"Creating Brain-like Intelligence",
Creating Brain-like Intelligence, pp. 1–15, 2008.
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Claudius Gläser, Martin Heckmann, Frank Joublin, Christian Goerick,
"Auditory-based Formant Estimation in Noise using a Probabilistic Framework",
Proceedings of the INTERSPEECH, pp. 2606–2609, 2008.
Abstract
We recently introduced a computationally efficient framework for tracking formants which combines a biologically inspired preprocessing for enhancing formants in spectrograms with a probabilistic framework for estimating formant trajectories. In contrast to previously published approaches our tracking scheme relies on the joint distribution of formants rather than using independent tracking instances for each formant separately. Therewith more pr...
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Yaochu Jin, Lisa Schramm, Bernhard Sendhoff,
"A Gene Regulatory Model for the Development of Primitive Nervous Systems",
INNS-NNN Symposia on Modeling the Brain and Nervous Systems, 2008.
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Imran Bhatti,
"Autonomous learning in intelligent vehicles",
TU Darmstadt, 2008.
Abstract
Autonomous systems, i.e., intelligent vehicles and robots use machine learning techniques to classify or recognise the identity of an object. The object identification aids them to make intelligent decisions in different situations. Research on classification techniques shows that classification techniques are not always accurate and reliable. In this thesis we apply a newly proposed concept termed ”cross-module learning” for cognitive system...
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Ben Jones, Yaochu Jin, Xin Yao, Bernhard Sendhoff,
"Evolution of Neural Organization in A Hydra-Like Animat",
International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP-2008), 2008.
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