To improve the anti-ship missiles' ability for accurate and efficient detection of maritime targets, YOLOv4 detection network is used in this paper. By using YOLOv4 network to detect the self-built marine ship targets' data set, to verify the accuracy and speed of the ship's recognition of the network. Empirical results show that YOLOv4 network can achieve better detection results for single or multiple targets in the pictures, and had superior performance in detecting small and obscure targets. In the real-time detection link, it can quickly and accurately detect the ship target in the transformed scene. Compared with traditional marine ship targets detection methods, YOLOv4 can better avoid the influence of background, lighting, occlusion, etc. It provides the oretical and technical support for the fine selection of targets for anti-ship missiles.


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    Title :

    Detection of Self-Build Data Set Based on YOLOv4 Network


    Contributors:
    Wang, Yao (author) / Wang, Lei (author) / Jiang, Yi (author) / Li, Tianyu (author)


    Publication date :

    2020-09-27


    Size :

    1262860 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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