Showing 3 open source projects for "energy"

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  • 1
    Portable Robotics Eye Vergence Control

    Portable Robotics Eye Vergence Control

    Eye movements control portable on different robotic stereo heads

    ...The project is now available for the iCub platform to work on YARP [https://github.com/stino78/vergence-control/][1] The algorithm works on the top of a distributed representation of binocular disparity supplied by a population of binocular energy-model neural units. The project allows a robust control and adaptive binocular coordination for different robot stereo platforms. Reference publications: Gibaldi, A., Vanegas, M., Canessa, A., & Sabatini, S. P. (2017). A portable bio-inspired architecture for efficient robotic vergence control. International Journal of Computer Vision,. ...
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  • 2
    Low-power approximate adders provide basic building blocks for approximate computing hardware that have shown remarkable energy efficiency for error-resilient applications (like image/video processing, computer vision, etc.), especially for battery-driven portable systems. In this paper, we present a novel scalable, fast yet accurate analytical method to evaluate the output error probability of multi-bit low power adders for a predetermined probability of input bits.
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  • 3

    LBP in multiple platforms

    LBP implementation in multiple computing platforms (ARM,GPU, DSP...)

    The Local Binary Pattern (LBP) is a texture operator that is used in several different computer vision applications and implemented in a variety of platforms. When selecting a suitable LBP implementation platform, the specific application and its requirements in terms of performance, size, energy efficiency, cost and developing time has to be carefully considered. This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. ...
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