Acta Optica Sinica, Volume. 40, Issue 11, 1111002(2020)

Infrared Target Modeling Method Based on Double Adversarial Autoencoding Network

Zhuang Miao1,2, Yong Zhang1,3、*, and Weihua Li1,2
Author Affiliations
  • 1Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083, China
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    References(12)

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    [3] Liu Q, Lu X H, He Z Y et al. Deep convolutional neural networks for thermal infrared object tracking[J]. Knowledge-Based Systems, 134, 189-198(2017).

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    [7] Goodfellow I, Pouget-Abadie J, Mirza M et al. Generative adversarial nets. [C]∥Advances in Neural Information Processing Systems 27 (NIPS 2014), December 8-13, 2014, Montreal, Quebec, Canada. New York: Curran Associates, 2672-2680(2014).

    [8] Kingma D P. -05-01)[2019-12-25]. https: ∥arxiv., org/abs/1312, 6114(2014).

    [9] Bao J M, Chen D, Wen F et al. CVAE-GAN: fine-grained image generation through asymmetric training. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice. New York: IEEE, 2745-2754(2017).

    [10] Rosca M, Lakshminarayanan B, Warde-Farley D et al. -10-21)[2019-12-25]. https: ∥arxiv., org/abs/1706, 04987(2017).

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    [12] Heusel M, Ramsauer H, Unterthiner T et al. GANs trained by a two time-scale update rule converge to a local nash equilibrium. [C]∥Advances in Neural Information Processing Systems 30 (NIPS 2017), December 4-9, 2017, Long Beach, CA, USA. New York: Curran Associates, 6626-6637(2017).

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    Zhuang Miao, Yong Zhang, Weihua Li. Infrared Target Modeling Method Based on Double Adversarial Autoencoding Network[J]. Acta Optica Sinica, 2020, 40(11): 1111002

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    Paper Information

    Category: Imaging Systems

    Received: Jan. 9, 2020

    Accepted: Mar. 10, 2020

    Published Online: Jun. 10, 2020

    The Author Email: Zhang Yong (zybxy@sina.com)

    DOI:10.3788/AOS202040.1111002

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