一个强大的事件驱动的方法来实现始终在线的对象识别

Antoine Grimaldi1, Victor Boutin2, Sio-Hoi Ieng3

  • 1Aix-Marseille Universit, Institut de Neurosciences de la Timone, CNRS, Marseille, France.

概括

这项研究介绍了一种常在的神经模拟架构,用于实时模式识别. 通过增强基于事件的时间表面层次 (HOTS) 算法,以恒温增益控制和尖端神经网络 (SNN) 集成,它实现了超快的在线对象识别.

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