Nils Einecke, Sven Rebhan, Julian Eggert,
"Depth from Perspective Transformations",
5th HRI Global Workshop, 2008.
Abstract
All binocular depth estimation algorithms need to apply some kind of matching process for correspondence search. Unfortunately, this search process is difficult because of ambiguities. One possibility to reduce ambiguities is to use 3-D models of the scene geometry. In this paper we interpret the scene as a composition of basic parameterizable surfaces. We present a general way of deriving formulas for perspectively mapping such surfaces from one...
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Zdravko Bozakov, Lars Gräning, Stephan Hasler, Heiko Wersing, Stefan Menzel,
"Unsupervised Extraction of Design Components for a 3D parts-based Representation",
Proceedings of the 2008 International Joint Conference on Neural Networks (IJCNN), pp. 2009–2016, 2008.
Abstract
During CAD development and any kind of design optimisation over years a huge amount of geometries accumulate in a design department. To organize and structure these designs with respect to reusability, a hierarchical set of components on different scalings is extracted by the designers. This hierarchy allows to compose designs from several parts and to adapt the composition to the current task. Nevertheless, this hierarchy is imposed by humans an...
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Lars Gräning, Stefan Menzel, Martina Hasenjäger, Thomas Bihrer, Markus Olhofer, Bernhard Sendhoff,
"Knowledge Extraction from Aerodynamic Design Data and its Application to 3D Turbine Blade Geometries",
Journal of Mathematical Modelling and Algorithms, JMMA (2008), vol. 7, no. 4, pp. 329–350, 2008.
Abstract
Applying numerical optimisation methods in the field of aerodynamic design optimisation normally leads to a huge amount of heterogeneous design data. While most often only the most promising results are investigated and used to drive further optimisations, general methods for investigating the entire design dataset are rare. We propose methods that allow the extraction of comprehensible knowledge from aerodynamic design data represented by discre...
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Hans-Georg Beyer and Bernhard Sendhoff,
"Covariance matrix adaptation revisited - The CMSA Evolution Strategy",
Parallel Problem Solving From Nature X, pp. 123–132, 2008.
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Ben Jones, Yaochu Jin, Bernhard Sendhoff, Xin Yao,
"Evolving functional symmetry in a three dimensional model of an elongated organism",
Artificial Life XI, pp. 305-312, 2008.
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Sven Schrader, Rüdiger Kupper, Marc-Oliver Gewaltig, Ursula Körner, Edgar Körner,
"Complex object representation in a computer simulation of the neocortex",
5th HRI Global Workshop, 2008.
Abstract
In vision, an object representation is constructed through a cascade of areas, each processing more and more elaborate features of the stimulus image. We hypothesize that the necessary signal flow involves a feed-forward path to compose the object representation as well as a feedback path to refine the representation and to correct errors. Using word recognition as a metaphor for visual stimuli, we have implemented this architecture in a spiking ...
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Martin Heckmann, Xavier Domont, Frank Joublin, Christian Goerick,
"A Closer Look on Hierarchical Spectro-Temporal Features (HIST)",
Proc. INTERSPEECH 2008, 2008.
Abstract
Speech recognition robust against interfering noise remains a difficult task. We previously presented a set of spectrotemporal speech features which we termed Hierarchical Spectro-Temporal (HIST) features showing improved robustness, especially when combined with RASTA-PLP. They are inspired by the receptive fields found in the mammalian auditory cortex and are organized in two hierarchical levels. A set of filters learned via ICA captures local ...
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Till Steiner, Yaochu Jin, Bernhard Sendhoff,
"A cellular model for the evolutionary development of lightweight material with an inner structure",
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008), 2008.
Abstract
We present a model of simulated evolutionary development on the basis of cells as building blocks for growth. In this model, cells grow and interact in a three-dimensional (3D) environment, where development is controlled by a simple genome. Using cell-cell interaction such as differential adhesion, cells sort and form complex arrangements. This developmental process is evolved using a multi-objective evolutionary algorithm to achieve lightweight...
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Xavier Domont, Martin Heckmann, Frank Joublin, Christian Goerick,
"Hierarchical Spectro-Temporal Features for Robust Speech Recognition",
Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 4417-4420, 2008.
Abstract
Previously we presented an auditory-inspired feed-forward architecture which achieves good performance in noisy conditions on a segmented word recognition task. In this paper we propose to use a modified version of this hierarchical model to generate features for standard Hidden Markov Models. To obtain these features we firstly compute the spectrograms using a Gammatone filterbank. A filtering over the channels permits to enhance the formant fre...
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Stephan Kirstein, Heiko Wersing, Horst-Michael Groß, Edgar Körner,
"A Vector Quantization Approach for Life-Long Learning of Categories",
Proceedings of the International Conference on Neural Information Processing (ICONIP), 2008.
Abstract
We present a category learning vector quantization (cLVQ) approach for incremental and life-long learning of multiple visual categories where we focus on approaching the stability-plasticity dilemma. To achieve the life-long learning ability an incremental learning vector quantization approach is combined with a category-specific feature selection method in a novel way to allow several metrical “views” on the representation space for the same...
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