A two-dimensional MoS_(2) array based on artificial neural network learning for high-quality imaging

作     者：Long Chen Siyuan Chen Jinchao Wu Luhua Chen Shuai Yang Jian Chu Chengming Jiang Sheng Bi Jinhui Song Long Chen;Siyuan Chen;Jinchao Wu;Luhua Chen;Shuai Yang;Jian Chu;Chengming Jiang;Sheng Bi;Jinhui Song

作者机构：School of Mechanical EngineeringDalian University of TechnologyDalian 116024China School of Computer ScienceSouthwest Petroleum UniversityChengdu 610500China 

出 版 物：《Nano Research》 (纳米研究（英文版）)

年 卷 期：2023年第16卷第7期

页      面：10139-10147页

核心收录：

学科分类：07[理学] 070205[理学-凝聚态物理] 08[工学] 080501[工学-材料物理与化学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：This project was financially supported by the Dalian Science and Technology Innovation Fund of China(No.2019J11CY011) the Science Fund for Creative Research Groups of NSFC(No.51621064) 

主　　题：two-dimensional MoS_(2) sensing array artificial neural network individual difference imaging quality 

摘      要：As the basis of machine vision,the biomimetic image sensing devices are the eyes of artificial *** recent years,with the development of two-dimensional(2D)materials,many new optoelectronic devices are developed for their outstanding ***,there are still little sensing arrays based on 2D materials with high imaging quality,due to the poor uniformity of pixels caused by material defects and fabrication ***,we propose a 2D MoS_(2)sensing array based on artificial neural network(ANN)*** equipping the MoS_(2)sensing array with a“brain(ANN),the imaging quality can be effectively *** the test,the relative standard deviation(RSD)between pixels decreased from about 34.3%to 6.2%and 5.49%after adjustment by the back propagation(BP)and Elman neural networks,*** peak signal to noise ratio(PSNR)and structural similarity(SSIM)of the image are improved by about 2.5 times,which realizes the re-recognition of the distorted *** provides a feasible approach for the application of 2D sensing array by integrating ANN to achieve high quality imaging.