Acta Optica Sinica, Volume. 44, Issue 12, 1228002(2024)

Synthetic Aperture Radar Ship Detection Method Based on Highly Efficient Aggregated Feature Enhancement Network

Huilin Shan1,2, Wenxing Liu1, Xingtao Wang1, Xiangwei Fu1, Changshuai Li2, and Yinsheng Zhang1,2、*
Author Affiliations
  • 1School of Electronics & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
  • 2School of Electronic & Information Engineering, Wuxi University, Wuxi 214105, Jiangsu , China
  • show less
    References(27)

    [2] Jiang M Z. Research on ship detection and classification in SAR images[D](2016).

    [4] Wang C A. Research on target detection and fine-grained recognition of nearshore ships in remote sensing images[D](2019).

    [14] Redmon J, Farhadi A. Yolov3: An incremental improvement[J]. arXiv preprint(2018).

    [19] Lin Z K, Liu W, Niu C Y et al. Synthetic aperture radar image change detection based on difference image construction of log-hyperbolic cosine ratio and multi-region feature convolution extreme learning machine[J]. Acta Optica Sinica, 43, 1228001(2023).

    [20] Wu Y Q, Xu Q, Ma J Z et al. SAR change detection algorithm based on space-frequency dual-domain filtering[J]. Acta Optica Sinica, 43, 1228009(2023).

    [21] Du Y L, Cui J H, Wei Q M et al. Marine oil-spill detection in multi-polarization image-based SAR on improved FCN[J]. Laser & Optoelectronics Progress, 59, 0415005(2022).

    Tools

    Get Citation

    Copy Citation Text

    Huilin Shan, Wenxing Liu, Xingtao Wang, Xiangwei Fu, Changshuai Li, Yinsheng Zhang. Synthetic Aperture Radar Ship Detection Method Based on Highly Efficient Aggregated Feature Enhancement Network[J]. Acta Optica Sinica, 2024, 44(12): 1228002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jul. 18, 2023

    Accepted: Oct. 10, 2023

    Published Online: May. 23, 2024

    The Author Email: Yinsheng Zhang (yorkzhang@nuist.edu.cn)

    DOI:10.3788/AOS231285

    CSTR:32393.14.AOS231285

    Topics