Electronics Optics & Control, Volume. 32, Issue 5, 79(2025)

SAR Image Ship Detection in Complex Inshore Scenarios

WANG Xiaoyi1...2, LIU Lin1,2, XIAO Jiarong1 and LIU Xiang1 |Show fewer author(s)
Author Affiliations
  • 1Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100000, China
  • 2School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100000, China
  • show less
    References(18)

    [5] [5] LU Z, WANG P F, LI Y J, et al. A new deep neural network based on SwinT-FRM-ShipNet for SAR ship detection in complex near-shore and offshore environments[J]. Remote Sensing, 2023, 15(24): 5780.

    [6] [6] TONG Z J, CHEN Y H, XU Z W, et al. Wise-IoU: bounding box regression loss with dynamic focusing mechanism[R]. Los Alamos: arXiv Preprint, 2023: arXiv: 2301. 10051.

    [7] [7] REN S Q, HE K M, GIRSHICK R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1149.

    [8] [8] CAI Z W, VASCONCELOS N. Cascade R-CNN: delving into high quality object detection[C]//Conference on Computer Vision and Pattern Recognition(CVPR). Salt Lake City: IEEE, 2018: 6154-6162.

    [9] [9] REDMO J, DIVVAL S, GIRSHIC R, et al. You only look once: unified, real-time object detection[C]//Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas: IEEE, 2016: 779-788.

    [10] [10] LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multibox detector[C]//European Conference on Computer Vision (ECCV). Amsterdam: IEEE, 2016: 21-37.

    [11] [11] SANDLER M, HOWARD A, ZHU M L, et al. MobileNetV2: inverted residuals and linear bottlenecks[C]//Conference on Computer Vision and Pattern Recognition (CVPR). Salt Lake City: IEEE, 2018: 4510-4520.

    [12] [12] WOO S, PARK J, LEE J-Y, et al. CBAM: convolutional block attention module[C]//European Conference on Computer Vision (ECCV). Cham: Springer, 2018: 3-19.

    [13] [13] MENG W, ZHANG Q H, MA S M, et al. A lightweight CNN and Transformer hybrid model for mental retardation screening among children from spontaneous speech[J]. Computers in Biology and Medicine, 2022, 151(PA): 106281.

    [14] [14] CHEN J R, KAO S-H, HE H, et al. Run, don't walk: chasing higher FLOPS for faster neural networks[C]//2023 IEEE/CVF Conference on Computer Vision and Pattern Recognitio (CVPR). Vancouver: IEEE, 2023: 12021-12031.

    [15] [15] SU P, HAN H Z, LIU M, et al. MOD-YOLO: rethinking the YOLO architecture at the level of feature information and applying it to crack detection[J]. Expert Systems with Applications, 2024, 237(PA): 121346.

    [16] [16] LI H L, LI J, WEI H B, et al. Slim-Neck by GSConv: a better design paradiam of detector architectures for autonomous vehicles[R]. Los Alamos: arXiv Preprint, 2022: arXiv: 2206. 02424.

    [17] [17] ZHANG X, SONG Y G, SONG T T, et al. AKConv: convolutional kernel with arbitrary sampled shapes and arbitrary number of parameters[R]. Los Alamos: arXiv Preprint, 2023: arXiv: 2311. 11587.

    [18] [18] ZHENG Z H, WANG P, LIU W, et al. Distance-IoU Loss: faster and better learning for bounding box regression[C]//Proceedings of the AAAI Conference on Artificial Intelligence. New York: AAAI, 2020. doi:10.1609/AAAI.V34I07.6999.

    [19] [19] ZHANG T W, ZHANG X L, LI J W, et al. SAR ship detection dataset (SSDD): official release and comprehensive data analysis[J]. Remote Sensing, 2021, 13(18): 3690.

    [20] [20] LI J W, QU C, SHAO J Q. Ship detection in SAR images based on an improved Faster R-CNN[C]//SAR in Big Data Era: Models, Methods & Applications (BIGSARDATA). Piscataway: IEEE, 2017. doi:10.1109/BIGSARDATA.2017.8124934.

    [21] [21] WEI S J, ZENG X F, QU Q Z, et al. HRSID: a high-resolution SAR images dataset for ship detection and instance segmentation[J]. IEEE Access, 2020, 8: 120234-120254.

    [22] [22] SELVARAJU R R, COGSWELL M, DAS A, et al. Grad-CAM: visual explanations from deep networks via gradient-based localization[C]//IEEE International Conference on Computer Vision(ICCV). Venice: IEEE, 2017: 336-359.

    Tools

    Get Citation

    Copy Citation Text

    WANG Xiaoyi, LIU Lin, XIAO Jiarong, LIU Xiang. SAR Image Ship Detection in Complex Inshore Scenarios[J]. Electronics Optics & Control, 2025, 32(5): 79

    Download Citation

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

    Category:

    Received: Apr. 8, 2024

    Accepted: May. 13, 2025

    Published Online: May. 13, 2025

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2025.05.013

    Topics