Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction - Huang, Pei-Yu; Jiang, Bi-Yi; Chen, Hong-Ji; Xu, Jia-Yi; Wang, Kang; Zhu, Cheng-Yi; Hu, Xin-Yan; Li, Dong; Zhen, Liang; Zhou, Fei-Chi; Qin, Jing-Kai; Xu, Cheng-Yan (Nature communications, 2023)
Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing, a distributed framework that brings computation and data storage closer to the sources of data. In addition to the capability of static image sensing and processing, the hardware implementation of a neuro-inspired vision system also requires the fulfilment of detecting and recognizing moving targets. Here, we demonstrated a neuro-inspired optical sensor based on two-dimensional NbS 2 /MoS 2 hybrid films, which featured remarkable photo-induced conductance plasticity and low electrical energy consumption. A neuro-inspired optical sensor array with 10 × 10 NbS 2 /MoS 2 phototransistors enabled highly integrated functions of sensing, memory, and contrast enhancement capabilities for static images, which benefits convolutional neural network (CNN) with a high image recognition accuracy. More importantly, in-sensor trajectory registration of moving light spots was experimentally implemented such that the post-processing could yield a high restoration accuracy. Our neuro-inspired optical sensor array could provide a fascinating platform for the implementation of high-performance artificial vision systems. Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing. Here the authors, develop a neuro-inspired optical sensor based on NbS 2 /MoS 2 films that can operate with monolithically integrated functions of static image enhancement and dynamic trajectory registration.