计算机科学
像素
CMOS芯片
卷积神经网络
背景(考古学)
图像传感器
探测器
灵敏度(控制系统)
计算
人工智能
嵌入式系统
计算机体系结构
电子工程
计算机工程
炸薯条
工程类
电信
生物
算法
古生物学
作者
Edoardo Charbon,Claudio Bruschini,Myung‐Jae Lee
出处
期刊:International Conference on Electronics, Circuits, and Systems
日期:2018-12-01
被引量:23
标识
DOI:10.1109/icecs.2018.8617983
摘要
3D-stacked CMOS SPAD based image sensors hold the promise for better sensitivity and more functionality per pixel. The technology enables to separate detection from computation onto different chips, or tiers, that are stacked onto one another. One advantage is to be able to independently optimize detection and processing in dedicated processes. Another is to achieve extremely low skews across large chips, thus enabling accurate timing over multi-megapixel image sensors. A further advantage is the potential of implementing advanced functionality requiring large arrays of computational units directly connected with the detectors, thus paving the way to on-chip convolutional neural networks and deep learning engines. In this paper we review several technologies enabling this interesting evolution and examples of possible implementations in the context of actual applications.
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