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Perceiving distance from two camera images, a task called stereo vision, is fundamental for many applications in robotics or automation. However, algorithms that compute this information at high accuracy have a high computational complexity. One such algorithm, Semi Global Matching (SGM), performs well in many stereo vision benchmarks, while maintaining a(More)
Semi-Global Matching (SGM) is a high-performance method for computing high-quality disparity maps from stereo camera images in machine vision applications. It is also suitable for direct hardware execution, e.g., in ASICs or reconfigurable logic devices. We present a highly parametrized FPGA implementation, scalable from simple low-resolution low-power(More)
State-of-the-art neuron simulators are capable of simulating at most few tens/hundreds of neurons in real-time due to the exponential growth in the communication costs with the number of simulated neurons. In this paper, we present a novel, reconfigurable, multi-chip system architecture based on localized communication, which effectively reduces the(More)
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