IRIS:在图像传感器中集成视网膜功能
Zihan Yin1, Md Abdullah-Al Kaiser1, Lamine Ousmane Camara2
1Information Sciences Institute, University of Southern California, Los Angeles, CA, United States.
Frontiers in neuroscience
|September 18, 2023
概括
这项研究引入了由视网膜启发的新型神经形态图像传感器. 这些传感器实现了先进的运动检测,用于在动态环境中实时决策.
科学领域:
- 神经科学是一个神经科学.
- 计算机工程 计算机工程
- 电气工程 电气工程
背景情况:
- 神经形态图像传感器模仿生物视网膜进行视觉计算.
- 早期的传感器实现了视网膜的基本功能;先进的下游处理在很大程度上仍未被探索.
- 最近在视网膜电路上的发现为传感器开发提供了新的机会.
研究的目的:
- 开发一种技术电路联合设计,用于在神经形态图像传感器中实现先进的运动计算.
- 在传感器的输出阶段整合物体运动灵敏度和迫在眉的检测.
- 为了实现基于视觉的系统的实时,节能决策.
主要方法:
- 使用了技术电路联合设计方法.
- 模拟了Globalfoundries 22nm技术节点上的拟议电路.
- 利用半导体芯片堆叠技术的进步.
主要成果:
- 证明了实现对象运动灵敏度和迫在眉的检测的可行性.
- 验证了视网膜启发的电路可以在现有的图像传感平台上制造.
- 展示了使用先进芯片堆叠集成的潜力.
结论:
- 拟议的图像传感器 (IRIS) 技术中的综合视网膜功能可实现先进的运动处理.
- 使用当前的半导体制造能力,可以制造IRIS技术.
- 这一进步有望增强需要低带宽,实时决策的机器视觉应用.
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