• Electronics Optics & Control
  • Vol. 26, Issue 9, 90 (2019)
SHAO Jiaqi, QU Changwen, LIJianwei, and PENG Shujuan
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3969/j.issn.1671-637x.2019.09.019 Cite this Article
    SHAO Jiaqi, QU Changwen, LIJianwei, PENG Shujuan. CNN Based Ship Target Recognition of Imbalanced SAR Image[J]. Electronics Optics & Control, 2019, 26(9): 90 Copy Citation Text show less
    References

    [4] WISSINGER J, RISTROPH R, DIEMUNSCH J R, et al. MSTAR's extensible search engine and model-based infe-rencing toolkit[J]. International Society for Optics and Photonics, 1999, 3721: 554-570.

    [5] CHEN S Z, WANG H P. SAR target recognition based on deep learning[C]//International Conference on Data Science and Advanced Analytics, IEEE, 2015: 541-547.

    [6] WANG H D, CHEN S Z, XU F, et al. Application of deep-learning algorithms to MSTAR data[C]//International Geoscience and Remote Sensing Symposium, IEEE, 2015: 3743-3745.

    [7] ZHAO Q, PRINCIPE J C. Support vector machines for SAR automatic target recognition[J]. IEEE Transactions on Aerospace and Electronic Systems, 2001, 37(2): 643-654.

    [8] O, SULLIVAN J A, DEVORE M D, KEDIA V, et al. SAR ATR performance using a conditionally Gaussian model[J]. IEEE Transactions on Aerospace and Electronic Systems, 2001, 37(1): 91-108.

    [9] SUN Y J, LIU Z P, TODOROVIC S, et al. Adaptive boosting for SAR automatic target recognition[J]. IEEE Tran-sactions on Aerospace and Electronic Systems, 2007, 43(1): 112-125.

    [12] SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition[J]. Computer Science, 2014, 1409: 1-14.

    [13] SHEN L, LIN Z C, HUANG Q M. Relay backpropagation for effective learning of deep convolutional neural networks[C]//ECCV-2016, 2016: 467-482.

    [14] KRIZHEVSKY A, SUTSKEVER I, HINTON G. ImageNet classification with deep convolutional neural networks[J]. Advances in Neural Information Processing Systems, 2012, 25(2): 1097-1105.

    [15] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]//Conference on Computer Vision and Pattern Recognition, IEEE, 2016: 770-778.

    [16] SIFRE L, MALLAT S G. Rigid-motion scattering for texture classification[J]. Computer Science, 2014, 3559: 501-515.

    [17] CHOLLET F. Xception: deep learning with depthwise separable convolutions[C]//Conference on Computer Vision and Pattern Recognition, IEEE, 2017: 1800-1807.

    [18] HUANG L Q, LIU B, LI B Y, et al. OpenSARShip: a dataset dedicated to sentinel-1 ship interpretation[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2018, 11(1): 195-208.

    CLP Journals

    [1] TONG Yu, SUO Jidong, REN Shuoliang. A Ship Detection Algorithm of Remote Sensing Technology Based on Ship Saliency in Candidate Regions[J]. Electronics Optics & Control, 2021, 28(2): 48

    SHAO Jiaqi, QU Changwen, LIJianwei, PENG Shujuan. CNN Based Ship Target Recognition of Imbalanced SAR Image[J]. Electronics Optics & Control, 2019, 26(9): 90
    Download Citation