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Published on: July 9, 2020

神经启发的光学传感器阵列用于高精度的静态图像识别和动态痕迹提取.

Pei-Yu Huang¹, Bi-Yi Jiang^2,3, Hong-Ji Chen¹

¹Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China.

Nature communications

|October 23, 2023

概括

这项研究介绍了一种新的神经启发的光学传感器,使用NbS2 / MoS2片进行边缘计算. 传感器有效处理静态和动态视觉数据,实现高精度图像识别和移动目标检测.

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科学领域:

材料科学材料科学材料科学
人工智能的人工智能
边缘计算边缘计算

背景情况:

边缘计算需要对人工智能应用程序进行高效的数据处理.
神经启发的视觉系统需要能够处理静态和动态视觉信息的硬件.
开发低功耗,高性能传感器对于先进的人工视觉至关重要.

研究的目的:

为了展示基于二维NbS2/MoS2混合膜的神经启发光学传感器阵列.
为了实现静态图像的集成传感,记忆和对比度增强.
为了使传感器内可记录移动目标的轨迹.

主要方法:

制造一个10x10数组的NbS2/MoS2光电晶体管.
光诱导导电可塑性和能源消耗的表征.
对移动光斑的传感器轨迹记录的实验实施.

主要成果:

传感器阵列表现出了显著的光感应导电可塑性和低能耗.
当与卷积神经网络 (CNN) 集成时,实现了高图像识别精度.
通过传感器内处理,可以准确地恢复移动光点轨迹.

结论:

开发的神经启发的光学传感器阵列为静态和动态视觉数据处理提供了集成的功能.
该平台显示了在边缘计算中实施高性能人工视觉系统的巨大潜力.
使用NbS2/MoS2混合膜为先进的神经形态传感应用提供了一个有前途的途径.