Stephan Kirstein, Heiko Wersing, Edgar Körner,
"Rapid Online Learning of Objects in a Biologically Motivated Recognition Architecture",
27th Pattern Recognition Symposium DAGM, pp. 301-308, 2005.
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Heiner Markert, Andreas Knoblauch, Günther Palm,
"Detecting sequences and understanding language with neural associative memories and cell assemblies.",
Biomimetic Neural Learning for Intelligent Robots, Springer Verlag, pp. 107–117, 2005.
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Christian Igel and Bernhard Sendhoff,
"Synergies between Evolutionary and Neural Computation",
European Symposium on Artificial Neural Networks (ESANN), pp. 241-252, 2005.
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Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff,
"A new approach to dynamics analysis of genetic algorithms without selection",
Congress on Evolutionary Computation, pp. 374-381, 2005.
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Yaochu Jin and Jürgen Branke,
"Evolutionary optimization in uncertain environments",
IEEE Transactions on Evolutionary Computation, vol. 9, no. 3, pp. 303-317, 2005.
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Lars Gräning, Yaochu Jin, Bernhard Sendhoff,
"Efficient evolutionary optimization using individual-based evolution control and neural networks – a comparative Study",
European Symposium on Artificial Neural Networks (ESANN), pp. 273-278, 2005.
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Marco Moebus,
"Speaker-independent Voiced-Unvoiced-Detection for different Speaking Styles",
TU Darmstadt, 2005.
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Martina Hasenjäger, Toyotaka Sonoda, Bernhard Sendhoff, Toshiyuki Arima,
"Single and Multi-Objective Approaches to 3D Evolutionary Aerodynamic Design Optimization",
Sixth World Congress on Structural and Multidisciplinary Optimization ({WCSMO6}), 2005.
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Heiner Markert, Andreas Knoblauch, Günther Palm,
"Detecting sequences and understanding language with neural associative memories and cell assemblies.",
Biomimetic Neural Learning for Intelligent Robots, Springer Verlag, pp. 107–117, 2005.
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Thomas Guthier, Volker Willert, Julian Eggert,
"Topological Sparse Learning of Dynamic Form Patterns",
Neural Computation, vol. 27, no. 1, pp. 42-73, 2005.
Abstract
Motion is a crucial source of information for a variety of tasks in social interactions. The process of how humans recognize complex articulated movements such as gestures or face expressions remains largely unclear. There is an ongoing discussion on how explicit low-level motion information, such as optical flow, is involved in the recognition process. We contribute to the discussion by introducing a computational model that classifies the spati...
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