Fourier-space Diffractive Deep Neural Network

被引:272
|
作者
Yan, Tao [1 ]
Wu, Jiamin [1 ]
Zhou, Tiankuang [1 ,2 ]
Xie, Hao [1 ]
Xu, Feng [3 ]
Fan, Jingtao [1 ]
Fang, Lu [2 ]
Lin, Xing [1 ,4 ]
Dai, Qionghai [1 ]
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China
[3] Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China
[4] Univ Calif Los Angeles, Dept Elect & Comp Engn, Los Angeles, CA 90095 USA
基金
中国国家自然科学基金;
关键词
SALIENT OBJECT DETECTION;
D O I
10.1103/PhysRevLett.123.023901
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In this Letter we propose the Fourier-space diffractive deep neural network (F-(DNN)-N-2) for all-optical image processing that performs advanced computer vision tasks at the speed of light. The F-(DNN)-N-2 is achieved by placing the extremely compact diffractive modulation layers at the Fourier plane or both Fourier and imaging planes of an optical system, where the optical nonlinearity is introduced from ferroelectric thin films. We demonstrated that F-(DNN)-N-2 can be trained with deep learning algorithms for all-optical saliency detection and high-accuracy object classification.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Saliency Segmentation with Fourier-space Diffractive Deep Neural Networks
    Yan, Tao
    Wu, Jiamin
    Zhou, Tiankuang
    Xie, Hao
    Xu, Feng
    Fan, Jingtao
    Fang, Lu
    Lin, Xing
    Dai, Qionghai
    2020 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO), 2020,
  • [2] Fourier-Space Image Restoration
    Lincoln Laboratory Journal, 8 (01):
  • [3] Fourier-space crystallography as group cohomology
    Rabson, DA
    Fisher, B
    PHYSICAL REVIEW B, 2002, 65 (02): : 242011 - 242017
  • [4] Fourier-space entanglement of spin chains
    Ibanez-Berganza, Miguel
    Rodriguez-Laguna, Javier
    Sierra, German
    JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2016,
  • [5] Orthogonality of diffractive deep neural network
    Zheng, Shuiqin
    Xu, Shixiang
    Fan, Dianyuan
    OPTICS LETTERS, 2022, 47 (07) : 1798 - 1801
  • [6] Nonlinear Fourier transform receiver based on a time domain diffractive deep neural network
    Zhou, Junhe
    Hu, Qingsong
    Pu, Haoqian
    OPTICS EXPRESS, 2022, 30 (21) : 38576 - 38586
  • [7] Thoughts about disentangling in wavelength and in Fourier-space
    Ilijic, S
    SPECTROSCOPICALLY AND SPATIALLY RESOLVING THE COMPONENTS OF CLOSE BINARY STARS, 2004, 318 : 107 - 110
  • [8] Fourier-space combination of Planck and Herschel images
    Abreu-Vicente, J.
    Stutz, A.
    Henning, Th.
    Keto, E.
    Ballesteros-Paredes, J.
    Robitaille, T.
    ASTRONOMY & ASTROPHYSICS, 2017, 604
  • [9] Unitary learning for diffractive deep neural network
    Xiao, Yong-Liang
    Li, Sikun
    Situ, Guohai
    You, Zhisheng
    OPTICS AND LASERS IN ENGINEERING, 2021, 139
  • [10] Fourier-space generalized magneto-optical ellipsometry
    Sandoval, Miguel A. Cascales
    Hierro-Rodriguez, A.
    Sanz-Hernandez, D.
    Skoric, L.
    Christensen, C. N.
    Donnelly, C.
    Fernandez-Pacheco, A.
    PHYSICAL REVIEW B, 2023, 107 (17)