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A 0.5V Real-Time Computational CMOS Image Sensor with Programmable Kernel for Always-On Feature Extraction
Conference paper

A 0.5V Real-Time Computational CMOS Image Sensor with Programmable Kernel for Always-On Feature Extraction

Tzu-Hsiang Hsu, Yen-Kai Chen, Tai-Hsing Wen, Wei-Chen Wei, Yi-Ren Chen, Fu-Chun Chang, Hyunjoon Kim, Qian Chen, Bongjin Kim, Ren-Shuo Liu, …
Proceedings - 2019 IEEE Asian Solid-State Circuits Conference, A-SSCC 2019, pp.33-36
11/2019
DOI: https://doi.org/10.1109/A-SSCC47793.2019.9056945

Abstract

Always-on computational CMOS image sensor convolution feature extraction processing-in-sensor Computer Networks and Communications Hardware and Architecture Electrical and Electronic Engineering Safety Risk Reliability and Quality Electronic Optical and Magnetic Materials
This paper presents a 0.5V computational CMOS image sensor (C 2 IS) with array-parallel computing capability for always-on feature extraction. By applying the developed pulsed-width modulation (PWM) pixel and switch-current integration (SCI), the in-sensor 8-directional matrix-parallel multiply-accumulate (MAC) operation is realized. Moreover, the analog-domain convolution-on-readout (COR) operation, the programmable 3x3 kernel with 3-bit weights, and the tunable-resolution column-parallel ADC (1b to 8b) are implemented to achieve the real-time feature extraction without use of additional memory. The C 2 IS prototype has been fabricated and verified to demonstrate the raw and feature images at 480 fps with a power consumption of 77/91 (uW and the resultant FoM of 9.8/11.6 (pJ/pix/frame), respectively.

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