晶体管
计算机科学
运动(物理)
光学晶体管
光电子学
电气工程
电子工程
材料科学
物理
电压
计算机视觉
工程类
作者
Xiaotao Jing,Rui Wang,Dingwei Li,Wanlin Zhang,Tonglong Zeng,Qi Huang,Xiaohua Ma,Bowen Zhu,Hong Wang,Yue Hao
标识
DOI:10.1109/led.2024.3521039
摘要
Bidirectional photoresponsive synaptic devices offer distinct advantages and significant potential for applications in artificial visual systems. However, most existing artificial optical synapses require both optical stimulation and separate electrical control to achieve bidirectional synaptic conductance modulation, thereby increasing processing time and system complexity. In this study, we developed a bidirectional photoresponsive synaptic transistor based on a heterostructure of indium oxide (In2O3) and organic semiconductor, which exhibits positive response to ultraviolet (UV) light and negative response to red-light illumination. Leveraging their reversible conductance tunability, we simulated artificial neural networks for handwritten digit recognition, achieving an accuracy of 94.7%. Furthermore, the synaptic transistors can be utilized for precise motion perception, achieving 100% prediction accuracy.
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