Image Shifting Tracking Leveraging Memristive Devices

Theodoros Panagiotis Chatzinikolaou, Iosif-Angelos Fyrigos, G. Sirakoulis
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引用次数: 1

Abstract

Unconventional circuits with built-in memory and computing functionalities are becoming the cornerstones of artificial intelligence (AI) at the edge. In the currently deployed systems, sensing and computing occur in separate physical locations, imposing a vast amount of data shuttling between the sensor module and the cloud-computing platforms. Regarding the acceleration of image processing at the edge, in this work, a memristive computing circuit has been designed. By exploiting the non-linear behavior and memory capabilities of memristor devices, a memristive circuit, capable of tracking the shifting of an image is proposed. The presented circuit design can be also combined with an array of sensors, aiming to implement a discrete image tracking module.
利用记忆器件的图像移位跟踪
具有内置内存和计算功能的非常规电路正在成为边缘人工智能(AI)的基石。在目前部署的系统中,传感和计算发生在不同的物理位置,在传感器模块和云计算平台之间进行了大量的数据传输。针对图像边缘处理的加速问题,本文设计了忆阻计算电路。利用忆阻器器件的非线性特性和存储能力,提出了一种能够跟踪图像位移的忆阻电路。所提出的电路设计也可以与传感器阵列相结合,旨在实现一个离散图像跟踪模块。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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