Chinese Journal of Ship Research, Volume. 19, Issue 5, 180(2024)

Lightweight ship detection method based on YOLO-FNC model

Bingyan ZHANG1... Chuang ZHANG1, Zhennan SHI2 and Songtao LIU1 |Show fewer author(s)
Author Affiliations
  • 1Navigation College, Dalian Maritime University, Dalian 116026, China
  • 2Navigation Management Division, Panjin Maritime Safety Administration, Panjin 124211, China
  • show less
    References(14)

    [1] [1] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, realtime object detection[C] Proceedings of 2016 IEEE Conference on Computer Vision Pattern Recognition. Las Vegas: IEEE, 2016: 779−788.

    [9] Y YU, X YANG, J LI et al. A cascade rotated anchor-aided detector for ship detection in remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 60, 5600514(2022).

    [13] [13] NING Y, ZHAO L N, ZHANG C, et al. STDYOLOv5: a shiptype detection model based on improved YOLOv5[J]. Ships Offshe Structures, 2024,19(1): 6675.

    Tools

    Get Citation

    Copy Citation Text

    Bingyan ZHANG, Chuang ZHANG, Zhennan SHI, Songtao LIU. Lightweight ship detection method based on YOLO-FNC model[J]. Chinese Journal of Ship Research, 2024, 19(5): 180

    Download Citation

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

    Category: Weapon, Electronic and Information System

    Received: Aug. 1, 2023

    Accepted: --

    Published Online: Mar. 14, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.03487

    Topics