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    ARTICLE

    DuFNet: Dual Flow Network of Real-Time Semantic Segmentation for Unmanned Driving Application of Internet of Things

    Tao Duan1, Yue Liu1, Jingze Li1, Zhichao Lian2,*, Qianmu Li2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 223-239, 2023, DOI:10.32604/cmes.2023.024742

    Abstract The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology. Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis. Semantic segmentation is also a challenging technology for image understanding and scene parsing. We focused on the challenging task of real-time semantic segmentation in this paper. In this paper, we proposed a novel fast architecture for real-time semantic segmentation named DuFNet. Starting from the existing work of Bilateral Segmentation Network (BiSeNet), DuFNet proposes a novel Semantic Information Flow (SIF) structure for context information… More > Graphic Abstract

    DuFNet: Dual Flow Network of Real-Time Semantic Segmentation for Unmanned Driving Application of Internet of Things

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