Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Utilizing Neural Networks for Semantic Segmentation on RGB/LiDAR Fused Data for Off-road Autonomous Military Vehicle Perception


    Beteiligte:
    Faykus, Max Henry (Autor:in) / Selee, Bradley (Autor:in) / Smith, Melissa (Autor:in)

    Kongress:

    WCX SAE World Congress Experience



    Erscheinungsdatum :

    01.01.2023


    Format / Umfang :

    ALL-ALL



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Enhanced Surface Reconstruction and Semantic Segmentation of LiDAR Data in Autonomous Vehicle Perception Systems

    Beni Prathiba, Sahaya / Kumar Raghu Kumar, Suriya / Kumar Anandhan, Deepak et al. | IEEE | 2025


    LISEG: LIGHTWEIGHT ROAD-OBJECT SEMANTIC SEGMENTATION IN 3D LIDAR SCANS FOR AUTONOMOUS DRIVING

    Zhang, Wenquan / Zhou, Chancheng / Yang, Junjie et al. | British Library Conference Proceedings | 2018


    LiSeg: Lightweight Road-object Semantic Segmentation In 3D LiDAR Scans For Autonomous Driving

    Zhang, Wenquan / Zhou, Chancheng / Yang, Junjie et al. | IEEE | 2018


    LiDAR Data Segmentation in Off-Road Environment Using Convolutional Neural Networks (CNN)

    Goodin, Chris / Carruth, Daniel / Dabbiru, Lalitha et al. | SAE Technical Papers | 2020