Aiming at the problem of nearshore ship detection in highresolution optical remote sensing images, this paper proposed a port ship target detection method based on a lightweight multi-scale convolutional network. After verification, the method has a good detection effect on port ships. The network improves the feature expression ability without increasing the computational complexity, and can effectively capture rotation-sensitive features, thereby improving the versatility of rotating samples. The average detection rate of all types of ships in the experiment is 96.92%, and the average false alarm rate is 8.54%. High detection rate of ship target can be guaranteed and various false alarm target interference can be effectively eliminated.


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    Titel :

    Research on a port ship target detection method based on lightweight multi-scale convolutional network


    Beteiligte:
    Hu, Xiaoning (Autor:in) / Liu, ShanJunYu (Autor:in) / Wu, Zhigang (Autor:in) / Chen, Zhuo (Autor:in)

    Kongress:

    Eighth Symposium on Novel Photoelectronic Detection Technology and Applications ; 2021 ; Kunming,China


    Erschienen in:

    Proc. SPIE ; 12169


    Erscheinungsdatum :

    27.03.2022





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch