Ren Qinqi, Zhu Chaoyi, Ma Sijie, Wang Zhaoqing, Yan Jianmin, Wan Tianqing, Yan Weicheng, Chai Yang
Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, 999077, China.
Joint Research Centre of Microelectronics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, 999077, China.
Adv Mater. 2024 Jul 14:e2407476. doi: 10.1002/adma.202407476.
The demand for accurate perception of the physical world leads to a dramatic increase in sensory nodes. However, the transmission of massive and unstructured sensory data from sensors to computing units poses great challenges in terms of power-efficiency, transmission bandwidth, data storage, time latency, and security. To efficiently process massive sensory data, it is crucial to achieve data compression and structuring at the sensory terminals. In-sensor computing integrates perception, memory, and processing functions within sensors, enabling sensory terminals to perform data compression and data structuring. Here, vision sensors are adopted as an example and discuss the functions of electronic, optical, and optoelectronic hardware for visual processing. Particularly, hardware implementations of optoelectronic devices for in-sensor visual processing that can compress and structure multidimensional vision information are examined. The underlying resistive switching mechanisms of volatile/nonvolatile optoelectronic devices and their processing operations are explored. Finally, a perspective on the future development of optoelectronic devices for in-sensor computing is provided.
对物理世界精确感知的需求导致传感节点急剧增加。然而，从传感器向计算单元传输海量且无结构的传感数据在功率效率、传输带宽、数据存储、时间延迟和安全性方面带来了巨大挑战。为了高效处理海量传感数据，在传感终端实现数据压缩和结构化至关重要。传感器内计算将感知、存储和处理功能集成在传感器内部，使传感终端能够执行数据压缩和数据结构化。在此，以视觉传感器为例，讨论用于视觉处理的电子、光学和光电硬件的功能。特别地，研究了用于传感器内视觉处理的光电设备的硬件实现，这些设备能够压缩和结构化多维视觉信息。探索了易失性/非易失性光电器件的潜在电阻切换机制及其处理操作。最后，对用于传感器内计算的光电器件的未来发展提供了展望。
