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Till Steiner , "Artificial Evolutionary Development", Bielefeld University, 2010.
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Fernando Martinelli , "Scene Layout Segmentation of Traffic Environments Using a Conditional Random Field", University of Girona, 2010.
AbstractAt least 80% of the traffic accidents in the world are caused by human mistakes. Whether drivers are too tired, drunk or speeding, most accidents have their root in the improper behavior of drivers. Many of these accidents could be avoided if cars were equipped with some kind of intelligent system able to detect inappropriate actions of the driver and autonomously intervene by controlling the car in emergency situations. Such an advanced driver a...
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Benjamin Dittes and Christian Goerick , "Unsupervised Self-Development in a Multi-Reward Environment", Proceedings of the 10th International Workshop on Epigenetic Robotics, 2010.
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Lisa Schramm, Vander Valente Martins, Yaochu Jin, Bernhard Sendhoff , "Analysis of Gene Regulatory Network Motifs in Evolutionary Development of Multicellular Organisms", Twelfth International Conference on the Synthesis and Simulation of Living Systems, 2010.
AbstractBiological development is governed by gene regulatory networks (GRNs), although detailed genetic and cellular mechanisms underlying biological development remain unclear. It is believed that some GRN motifs have played an important role in the evolution of biological development by means of analyzing biological data. In this work, we investigate in a computational model for development to verify if these motifs can also be evolved as in biology, ...
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Claudius Gläser and Frank Joublin , "Perceptually Grounded Word Meaning Acquisition: A Computational Model", Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci), pp. 1744–1749, 2010.
AbstractWe present a computational model for the incremental acquisition of word meanings. Inspired by Complementary Learning Systems theory the model comprises different components which are specifically tailored to satisfy the contradictory needs of (1) rapid memorization of word-scene associations and (2) statistical feature extraction to reveal word meanings. Both components are recurrently coupled to achieve a memory consolidation. This process refl...
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Nicole Naue, Daniel Strüber, Ingo Fründ, Jeanette Schadow, Daniel Lenz, Stefan Rach, Ursula Körner, Christoph Herrmann , "Pattern reversal elicits stronger evoked and induced gamma-band responses than motion", NeuroImage, vol. 55, no. 2, pp. 808-817, 2010.
AbstractHitherto, it is unclear whether gamma-band responses (GBRs, ≈40 Hz) of the electroencephalogram are more strongly modulated by visual stimulation with moving or rather with static objects. Most results suggest that GBRs occur more consistently in response to motion. We measured the electroencephalogram of healthy subjects watching high contrast, achromatic gratings. Briefly after their onset, the gratings either started to move or reversed their ...
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Gervasio Puertas, Jörg Bornschein, Marc Henniges, Jörg Lücke , "The Maximal Causes of Natural Scenes are Edge Filters", Advances in Neural Information Processing Systems, vol. 23, pp. 1939-1947, 2010.
AbstractWe study the application of a strongly non-linear generative model to image patches. As in standard approaches such as Sparse Coding or Independent Component Analysis, the mod el assumes a sparse prior with independent hidden variables. However, in the place where standard approaches use the sum to combine basis functions we use the maximum. To derive tractable approximations for parameter estimation we apply a novel approach based on variationa...
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Matthias Platho , "Learning of sensory representations for task-dependent control of search processes", Learning of sensory representations for task-dependent control of search processes, University Mannheim, 2010.
AbstractFulfilling demanding tasks in complex, dynamic environments poses a tough challenge for nowadays systems. A system relying on visual information has to handle a lot of data concerning the environment, the task and relevant objects. In order to reduce the amount of data a compression method for object datasets is proposed, that aims for maintaining task performance. An object dataset comprises numerical representations of object features in differ...
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Robert Kastner, Thomas Michalke, Jannik Fritsch, Christian Goerick , "Towards a Task Dependent Representation Generation for Scene Analysis", IEEE Intelligent Vehicles Symposium (IV), 2010.
AbstractState-of-the-art advanced driver assistance systems (ADAS) typically focus on single tasks and therefore, have clearly defined functionalities. Although said ADAS functions (e.g. lane departure warning) show good performance, they lack the general ability to extract spatial relations of the environment. These spatial relations are required for scene analysis on a higher layer of abstraction, providing a new quality of scene understanding, e.g. fo...
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Mathias Franzius and Heiko Wersing , "Learning Invariant Visual Shape Representations from Physics", ICANN (3), pp. 298-302, 2010.
Abstract3D shape determines an object’s physical properties to a large degree. In this article, we introduce an autonomous learning system for categorizing 3D shape of simulated objects from single views. The system extends an unsupervised bottom-up learning architecture based on the slowness principle with top-down information derived from the physical behavior of objects. The unsupervised bottom-up learning leads to pose invariant representations. Shap...
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