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Live Demonstration: Low-Power Static Neural Network Circuits for Long-Term Change Detection

机译:现场演示:用于长期变化检测的低功耗静态神经网络电路

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Low power neural network hardware and its new applications have been explored to exploit its inherent advantage of artificial intelligence in comparison with humans. One such application, long-term change detection, is proposed and presented in this live demonstration. Owing to the low power operation in static analog/digital-mixed neural network circuits, our system using them can detect a change of human-friendly information, e.g., handwritten digits, whereas humans have difficulty noticing a gradual change over the long-term.
机译:人们已经探索了低功耗神经网络硬件及其新应用,以利用人工智能与人类相比的固有优势。在此现场演示中提出并提出了一种这样的应用程序,即长期变化检测。由于静态模拟/数字混合神经网络电路的低功耗操作,因此使用它们的我们的系统可以检测到人类友好信息(例如手写数字)的变化,而人类很难长期注意逐渐变化的情况。

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