Remote sensing technology for detecting ships at sea can be widely used in maritime supervision, military reconnaissance, and ship rescue. It has very important application value. In this paper, we propose the YOLOv3-RS algorithm based on YOLOv3 algorithm to precisely detect small ships in remote sensing images. The YOLOv3-RS algorithm uses the K-medians algorithm to improve the clustering effect of the data set, and then uses DenseNet to increase the feature reuse rate, and finally improves the ResNet module to enhance the expressive ability of the network. The final results show that YOLOv3-RS algorithm has better detection performance than YOLOv3 algorithm.


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    Title :

    Detection of Small Ships in Remote Sensing Images based on Deep Convolutional Neural Network


    Contributors:
    Shi, Tingchao (author) / Liu, Mingyong (author) / Niu, Yun (author) / You, Lianggen (author) / Xuan, Liwei (author) / Wang, Cong (author)


    Publication date :

    2020-10-05


    Size :

    754089 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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