Laser & Optoelectronics Progress, Volume. 61, Issue 12, 1237003(2024)

Few-Shot Image Classification Algorithm of Graph Neural Network Based on Swin Transformer

Kai Wang1, Jie Ren1、*, and Weichuan Zhang2
Author Affiliations
  • 1School of Electronics and Information, Xi'an Polytechnic University, Xi'an 710048, Shaanxi , China
  • 2Institute for Integrated and Intelligent Systems, Graiffith University, Brisbane 4702, Australia
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    References(30)

    [1] Li F F, Fergus R, Perona P. A Bayesian approach to unsupervised one-shot learning of object categories[C], 1134-1141(2008).

    [2] Xu Z C, Guo B F, Wu W H et al. Multiscale feature extraction method of hyperspectral image with attention mechanism[J]. Laser & Optoelectronics Progress, 60, 2410010(2023).

    [6] Snell J, Swersky K, Zemel R. Prototypical networks for few-shot learning[C], 4080-4090(2017).

    [29] Zhang R, Che T, Ghahramani Z et al. Metagan: an adversarial approach to few-shot learning[C], 2371-2380(2018).

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    Kai Wang, Jie Ren, Weichuan Zhang. Few-Shot Image Classification Algorithm of Graph Neural Network Based on Swin Transformer[J]. Laser & Optoelectronics Progress, 2024, 61(12): 1237003

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    Paper Information

    Category: Digital Image Processing

    Received: Jun. 25, 2023

    Accepted: Sep. 4, 2023

    Published Online: Jun. 3, 2024

    The Author Email: Ren Jie (renjie@xpu.edu.cn)

    DOI:10.3788/LOP231596

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