Differential interference contrast phase edging net:an all-optical learning system for edge detection of phase objects

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外文摘要：Edge detection for low-contrast phase objects cannot be performed directly by the spatial difference of intensity distri-bution.In this work,an all-optical diffractive neural network[DPENet]based on the differential interference contrast prin-ciple to detect the edges of phase objects in an all-optical manner is proposed.Edge information is encoded into an interference light field by dual Wollaston prisms without lenses and light-speed processed by the diffractive neural network to obtain the scale-adjustable edges.Simulation results show that DPENet achieves F-scores of 0.9308[MNIST]and 0.9352[NIST]and enables real-time edge detection of biological cells,achieving an F-score of 0.7462.

外文关键词：

diffractive neural networkedge detectionphase objects

作者：

李一鸣、李然、陈泉、栾海涛、卢海军、杨晖、顾敏、张启明

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作者单位：

Institute of Photonic Chips,University of Shanghai for Science and Technology,Shanghai 200093,China

School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China

Nokia Shanghai Bell Co.,Ltd.,Shanghai 201206,China

College of Medical Instruments,Shanghai University of Medicine and Health Sciences,Shanghai 201318,China

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基金：

National Key Research and Development Program of ChinaNational Key Research and Development Program of ChinaShanghai Municipal Science and Technology Major ProjectScience and Technology Commission of Shanghai MunicipalityShanghai Frontiers Science Center Program(2021-2025)National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaScience and Technology Development Foundation of Pudong New Area

项目编号：

2021YFB28020002022YFB280430121DZ1100500206197512312072200PKX2021-D10

出版年：

2024

DOI：

10.3788/COL202422.011102

中国光学快报(英文版)

中国光学学会中国科学院上海光学精密机械研究所

中国光学快报(英文版)

CSTPCD

影响因子：1.305

ISSN：1671-7694

年,卷(期)：2024.22(1)

参考文献量40