These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Journal Abstract Search


116 related items for PubMed ID: 38298467

  • 1. Context-aware SAR image ship detection and recognition network.
    Li C, Yue C, Li H, Wang Z.
    Front Neurorobot; 2024; 18():1293992. PubMed ID: 38298467
    [Abstract] [Full Text] [Related]

  • 2. An improved anchor-free SAR ship detection algorithm based on brain-inspired attention mechanism.
    Shi H, He C, Li J, Chen L, Wang Y.
    Front Neurosci; 2022; 16():1074706. PubMed ID: 36532272
    [Abstract] [Full Text] [Related]

  • 3. Ship Detection in Synthetic Aperture Radar Images under Complex Geographical Environments, Based on Deep Learning and Morphological Networks.
    Cao S, Zhao C, Dong J, Fu X.
    Sensors (Basel); 2024 Jul 01; 24(13):. PubMed ID: 39001068
    [Abstract] [Full Text] [Related]

  • 4. DB-YOLO: A Duplicate Bilateral YOLO Network for Multi-Scale Ship Detection in SAR Images.
    Zhu H, Xie Y, Huang H, Jing C, Rong Y, Wang C.
    Sensors (Basel); 2021 Dec 06; 21(23):. PubMed ID: 34884163
    [Abstract] [Full Text] [Related]

  • 5. R-CenterNet+: Anchor-Free Detector for Ship Detection in SAR Images.
    Jiang Y, Li W, Liu L.
    Sensors (Basel); 2021 Aug 24; 21(17):. PubMed ID: 34502583
    [Abstract] [Full Text] [Related]

  • 6. An Efficient Lightweight SAR Ship Target Detection Network with Improved Regression Loss Function and Enhanced Feature Information Expression.
    Yu J, Wu T, Zhang X, Zhang W.
    Sensors (Basel); 2022 Apr 30; 22(9):. PubMed ID: 35591135
    [Abstract] [Full Text] [Related]

  • 7. Adaptive CFAR Method for SAR Ship Detection Using Intensity and Texture Feature Fusion Attention Contrast Mechanism.
    Li N, Pan X, Yang L, Huang Z, Wu Z, Zheng G.
    Sensors (Basel); 2022 Oct 23; 22(21):. PubMed ID: 36365814
    [Abstract] [Full Text] [Related]

  • 8. A Multilayer Fusion Light-Head Detector for SAR Ship Detection.
    Gui Y, Li X, Xue L.
    Sensors (Basel); 2019 Mar 05; 19(5):. PubMed ID: 30841632
    [Abstract] [Full Text] [Related]

  • 9. Sar Ship Detection Based on Convnext with Multi-Pooling Channel Attention and Feature Intensification Pyramid Network.
    Wei F, Wang X.
    Sensors (Basel); 2023 Sep 03; 23(17):. PubMed ID: 37688096
    [Abstract] [Full Text] [Related]

  • 10. A Novel Detector Based on Convolution Neural Networks for Multiscale SAR Ship Detection in Complex Background.
    Dai W, Mao Y, Yuan R, Liu Y, Pu X, Li C.
    Sensors (Basel); 2020 Apr 30; 20(9):. PubMed ID: 32365747
    [Abstract] [Full Text] [Related]

  • 11.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 12. MSR2N: Multi-Stage Rotational Region Based Network for Arbitrary-Oriented Ship Detection in SAR Images.
    Pan Z, Yang R, Zhang AZ.
    Sensors (Basel); 2020 Apr 20; 20(8):. PubMed ID: 32325991
    [Abstract] [Full Text] [Related]

  • 13. SAR ship target detection method based on CNN structure with wavelet and attention mechanism.
    Huang S, Pu X, Zhan X, Zhang Y, Dong Z, Huang J.
    PLoS One; 2022 Apr 20; 17(6):e0265599. PubMed ID: 35657851
    [Abstract] [Full Text] [Related]

  • 14.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 15.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 16.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 17. MW-ACGAN: Generating Multiscale High-Resolution SAR Images for Ship Detection.
    Zou L, Zhang H, Wang C, Wu F, Gu F.
    Sensors (Basel); 2020 Nov 21; 20(22):. PubMed ID: 33233434
    [Abstract] [Full Text] [Related]

  • 18.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 19.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 20. An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery.
    Leng X, Ji K, Zhou S, Xing X, Zou H.
    Sensors (Basel); 2016 Aug 23; 16(9):. PubMed ID: 27563902
    [Abstract] [Full Text] [Related]


    Page: [Next] [New Search]
    of 6.