Multiframe-integrated, in-sensor computing using persistent photoconductivity  

作　　者：Xiaoyong Jiang Minrui Ye Yunhai Li Xiao Fu Tangxin Li Qixiao Zhao Jinjin Wang Tao Zhang Jinshui Miao Zengguang Cheng 

机构地区：[1]School of Microelectronics,Fudan University,Shanghai 200433,China [2]Hangzhou Institute for Advanced Study,University of Chinese Academy of Sciences,Hangzhou 310024,China [3]University of Chinese Academy of Sciences,Beijing 100049,China [4]School of Information Science and Technology,ShanghaiTech University,Shanghai 201210,China

出　　处：《Journal of Semiconductors》2024年第9期36-41,共6页半导体学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (52322210, 52172144, 22375069, 21825103, and U21A2069);National Key R&D Program of China (2021YFA1200501);Shenzhen Science and Technology Program (JCYJ20220818102215033, JCYJ20200109105422876);the Innovation Project of Optics Valley Laboratory (OVL2023PY007);Science and Technology Commission of Shanghai Municipality (21YF1454700)。

摘　　要：The utilization of processing capabilities within the detector holds significant promise in addressing energy consumption and latency challenges. Especially in the context of dynamic motion recognition tasks, where substantial data transfers are necessitated by the generation of extensive information and the need for frame-by-frame analysis. Herein, we present a novel approach for dynamic motion recognition, leveraging a spatial-temporal in-sensor computing system rooted in multiframe integration by employing photodetector. Our approach introduced a retinomorphic MoS_(2) photodetector device for motion detection and analysis. The device enables the generation of informative final states, nonlinearly embedding both past and present frames. Subsequent multiply-accumulate (MAC) calculations are efficiently performed as the classifier. When evaluating our devices for target detection and direction classification, we achieved an impressive recognition accuracy of 93.5%. By eliminating the need for frame-by-frame analysis, our system not only achieves high precision but also facilitates energy-efficient in-sensor computing.

关 键 词：in-sensor MOS2 PHOTODETECTOR persistent photoconductivity reservoir computing 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP391.41[自动化与计算机技术—控制科学与工程]