• Electronics Optics & Control
  • Vol. 29, Issue 2, 58 (2022)
LI Yonggang1 and ZHU Weigang2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2022.02.013 Cite this Article
    LI Yonggang, ZHU Weigang. A Review of SAR Image Target Recognition Based on Deep Learning[J]. Electronics Optics & Control, 2022, 29(2): 58 Copy Citation Text show less
    References

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    [3] PAN Z X, LIU L, QIU X L, et al.Fast vessel detection in Gaofen-3 SAR images with ultrafine strip-map mode[J].Sensors, 2017, 17(7).doi: 10.3390/s17071578.

    [4] AN Q Z, PAN Z X, YOU H J.Ship detection in Gaofen-3 SAR images based on sea clutter distribution analysis and deep convolutional neural network[J].Sensors, 2018, 18(2).doi: 10.3390/s18020334.

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    [10] HOU X Y, AO W, SONG Q, et al.FUSAR-Ship: building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition[J].Science China Information Sciences, 2020, 63(4): 140303-1-140303-19.

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    [19] HUANG Z, PAN Z, LEI B.What, where, and how to transfer in SAR target recognition based on deep CNNs[J].IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2324-2336.

    [22] PAN Z X, BAO X J, ZHANG Y T, et al.Siamese network based metric learning for SAR target classification[C]//IEEE International Geoscience and Remote Sensing Symposium.Yokohama: IEEE, 2019: 1342-1345.

    LI Yonggang, ZHU Weigang. A Review of SAR Image Target Recognition Based on Deep Learning[J]. Electronics Optics & Control, 2022, 29(2): 58
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