Semantic segmentation is one of the basic themes in computer vision. Its purpose is to assign semantic tags to each pixel of an image, which has been applied in many fields such as medical field, intelligent transportation and remote sensing image. In this paper, we use deep learning to solve the task of remote sensing semantic image segmentation. We propose an algorithm for semantic segmentation of the Attention Seg-Net network combined with SegNet and attention gate. Our proposed network can better segment vegetation, buildings, water bodies and roads in the test set of remote sensing images.


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    Titel :

    Semantic image segmentation network based on deep learning


    Beteiligte:
    Chen, Bo (Autor:in) / Zhang, Jiahao (Autor:in) / Zhou, Jianbang (Autor:in) / Chen, Zhong (Autor:in) / Yang, Jian (Autor:in) / Zhang, Yanna (Autor:in)

    Kongress:

    MIPPR 2019: Automatic Target Recognition and Navigation ; 2019 ; Wuhan,China


    Erschienen in:

    Proc. SPIE ; 11429


    Erscheinungsdatum :

    2020-02-14





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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