• Acta Optica Sinica
  • Vol. 42, Issue 19, 1920001 (2022)
Xingya Zhao, Zhiwei Yang, Jian Dai, Tian Zhang*, and Kun Xu
Author Affiliations
  • State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • show less
    DOI: 10.3788/AOS202242.1920001 Cite this Article Set citation alerts
    Xingya Zhao, Zhiwei Yang, Jian Dai, Tian Zhang, Kun Xu. VGG16-Based Diffractive Optical Neural Network and Context-Dependent Processing[J]. Acta Optica Sinica, 2022, 42(19): 1920001 Copy Citation Text show less
    References

    [1] Shainline J M, Buckley S M, Mirin R P et al. Superconducting optoelectronic circuits for neuromorphic computing[J]. Physical Review Applied, 7, 034013(2017).

    [2] Zhang T, Wang J, Dan Y H et al. Efficient training and design of photonic neural network through neuroevolution[J]. Optics Express, 27, 37150-37163(2019).

    [3] Chen H W, Yu Z M, Zhang T et al. Advances and challenges of optical neural networks[J]. Chinese Journal of Lasers, 47, 0500004(2020).

    [4] Xiang S Y, Song Z W, Gao S et al. Progress and prospects of photonic neuromorphic computing (invited)[J]. Acta Photonica Sinica, 50, 1020001(2021).

    [5] Luan H T, Chen X, Zhang Q M et al. Artificial intelligence nanophotonics: optical neural networks and nanophotonics[J]. Acta Optica Sinica, 41, 0823005(2021).

    [6] Reck M, Zeilinger A, Bernstein H J et al. Experimental realization of any discrete unitary operator[J]. Physical Review Letters, 73, 58-61(1994).

    [7] Lin X, Rivenson Y, Yardimci N T et al. All-optical machine learning using diffractive deep neural networks[J]. Science, 361, 1004-1008(2018).

    [8] Yan T, Wu J M, Zhou T K et al. Fourier-space diffractive deep neural network[J]. Physical Review Letters, 123, 023901(2019).

    [9] Chang J L, Sitzmann V, Dun X et al. Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification[J]. Scientific Reports, 8, 12324(2018).

    [10] Ma S D, Zeng C M, Xu F. Teaching of 4f system with optical image encryption and decryption simulations[J]. Physical Experiment of College, 31, 39-45(2018).

    [11] Colburn S, Chu Y, Shilzerman E et al. Optical frontend for a convolutional neural network[J]. Applied Optics, 58, 3179-3186(2019).

    [12] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [13] Song F J, Jutamulia S[M]. Modern optical information processing(2014).

    [14] Zeng G, Chen Y, Cui B et al. Continual learning of context-dependent processing in neural networks[J]. Nature Machine Intelligence, 1, 364-372(2019).

    [15] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

    [16] Liu Z W, Luo P, Wang X G et al. Large-scale celebfaces attributes (CelebA) dataset[EB/OL]. http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html

    [17] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. https://arxiv.org/abs/1409.1556

    [18] Di J L, Tang J, Wu J et al. Research progress in the applications of convolutional neural networks in optical information processing[J]. Laser & Optoelectronics Progress, 58, 1600001(2021).

    [19] Guo Q, Peng L. Hyperspectral classification based on 3D convolutional neural network and super pixel segmentation[J]. Acta Optica Sinica, 41, 2210001(2021).

    Xingya Zhao, Zhiwei Yang, Jian Dai, Tian Zhang, Kun Xu. VGG16-Based Diffractive Optical Neural Network and Context-Dependent Processing[J]. Acta Optica Sinica, 2022, 42(19): 1920001
    Download Citation