液晶与显示2024，Vol.39Issue(4)：490-505,16.DOI:10.37188/CJLCD.2023-0144
多任务衍射神经网络系统设计与实现
Design and implementation of multi-task diffraction neural network system
摘要
Abstract
To investigate the feasibility of diffraction neural network to perform multi-task image classification recognition,a diffraction neural network system is designed and built.The system uses a spatial light modulator(SLM)to modulate the phase and amplitude weights of the diffraction neural network and the optical full connection of the network layers.A CMOS camera is adopted to realize the optical nonlinear activation of the output of each diffraction layer in the diffraction neural network and discriminate the output image recognition results.The designed system model achieves 94.1%and 92.1%accuracy in MNIST and Fashion-MNIST image classification recognition.Finally,by building optical path system,optical experiments have 91%and 81.7%accuracy respectively,which verifies that the designed diffraction neural network system can meet the requirements of various image classification and recognition applications,and provides a new idea for the design and construction of diffraction networks.关键词
衍射神经网络/光学神经网络/系统设计/图像分类识别Key words
diffraction neural network/optical neural networks/system design/image classification recognition分类
信息技术与安全科学引用本文复制引用
王子荣,张星祥,龙勇机,付天骄,张墨..多任务衍射神经网络系统设计与实现[J].液晶与显示,2024,39(4):490-505,16.基金项目
国家自然科学基金青年科学基金(No.42001345) （No.42001345）
吉林省自然科学基金(No.20220101168JC)Supported by Youth Science Foundation of National Natural Science Foundation of China(No.42001345) （No.20220101168JC）
Natural Science Foundation of Jilin Province(No.20220101168JC) （No.20220101168JC）
