A CMOS Image Sensor and an AI Accelerator for Realizing Edge-Computing-Based Surveillance Camera Systems

F. Morishita, Norihito Kato, S. Okubo, T. Toi, M. Hiraki, S. Otani, Hideaki Abe, Yuji Shinohara, H. Kondo
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引用次数: 8

Abstract

This paper presents a CMOS image sensor and an AI accelerator to realize surveillance camera systems based on edge computing. For CMOS image sensors to be used for surveillance, it is desirable that they are highly sensitive even in low illuminance. We propose a new timing shift ADC used in CMOS image sensors for improving high sensitivity performance. Our proposed ADC improves non-linearity characteristics under low illuminance by 63%. Achieving power-efficient edge computing is a challenge for the systems to be used widely in the surveillance camera market. We demonstrate that our proposed AI accelerator performs inference processing for object recognition with 1 TOPS/W. Keywords: CMOS image sensor, surveillance camera system, low light imaging, AI accelerator, edge computing
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基于边缘计算的监控摄像系统的CMOS图像传感器和AI加速器
提出了一种CMOS图像传感器和人工智能加速器,实现了基于边缘计算的监控摄像系统。对于用于监视的CMOS图像传感器,即使在低照度下也需要具有高灵敏度。为了提高CMOS图像传感器的高灵敏度性能,我们提出了一种新的时序移位ADC。我们提出的ADC在低照度下的非线性特性改善了63%。实现高效节能的边缘计算是系统在监控摄像机市场上广泛应用的一个挑战。我们证明了我们提出的AI加速器以1 TOPS/W的速度执行对象识别的推理处理。关键词:CMOS图像传感器,监控摄像系统,弱光成像,AI加速器,边缘计算
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