• Journal of Terahertz Science and Electronic Information Technology
  • Vol. 21, Issue 2, 143 (2023)
YANG Moxuan1、2、3、4, ZHAO Yuanmeng1、2、3、4、*, ZHU Fengxia1、2、3、4, LIU Haoxin1、2、3、4, and ZHANG Cunlin1、2、3、4
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    DOI: 10.11805/tkyda2022208 Cite this Article
    YANG Moxuan, ZHAO Yuanmeng, ZHU Fengxia, LIU Haoxin, ZHANG Cunlin. Terahertz image segmentation for security inspection based on Generative Adversarial Network[J]. Journal of Terahertz Science and Electronic Information Technology , 2023, 21(2): 143 Copy Citation Text show less
    References

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    [3] XU J M, CHEN L, ZANG X F, et al. Triple-channel terahertz filter based on mode coupling of cavities resonance system[J]. Applied Physics Letters, 2013,103(16):161116.

    [10] DOSOVITSKIY A,BEYER L,KOLESNIKOV A.et al. An image is worth 16x16 words:transformers for image recognition at scale [C]// International Conference on Learning Representations. New Orleans:[s.n.], 2021:1-22.

    [11] GOODFELLOW I J,POUGET-ABADIE J,MIRZA M,et al. Generative adversarial nets[C]// Proceedings of the 27th International Conference on Neural Information Processing Systems. Montreal,Canada:MIT Press, 2014:2672-2680.

    [12] SZEGEDY C, LIU W, JIAY Q, et al. Going deeper with convolutions[C]// IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Boston,USA:IEEE, 2015:1-9.

    [13] VASWANI A,SHAZEER N,PARMAR N,et al. Attention is all you need[J]. Advances in Neural Information Processing Systems, 2017,22(7):139-147.

    [14] LEDIG C,THEIS L,HUSZAR F,et al. Photo-realistic single image super-resolution using a generative adversarial network[C]// IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Honolulu,USA:IEEE, 2017:105-114.

    [15] RONNEBERGER O,FISCHER P, BROX T. U-Net: convolutional networks for biomedical image segmentation[C]// International Conference on Medical Image Computing and Computer-Assisted Intervention. Munich:[s.n.], 2015:234-241.

    [16] HE K, ZHANG X, REN S, et al. Deep residual learning for image recognition[C]// IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Las Vegas:IEEE, 2016:770-778.

    YANG Moxuan, ZHAO Yuanmeng, ZHU Fengxia, LIU Haoxin, ZHANG Cunlin. Terahertz image segmentation for security inspection based on Generative Adversarial Network[J]. Journal of Terahertz Science and Electronic Information Technology , 2023, 21(2): 143
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