Herbert J. Reitboeck

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The performance of technical and biological vision systems crucially relies on powerful processing capabilities. Robust object recognition must be based on representations of segmented object candidates which are kept stable and sparse despite the highly variable nature of the environment. Here, we propose a network of pulse-coding neurons based on(More)
We present an approach for position invariant recognition of individual objects in composite scenes, combining neural networks and algorithmic methods. A dynamic network of spiking neurons is used to generate object definition and figure/ground separation via temporal signal correlations. A shift invariant representation of the network spike activity(More)
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