In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.


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    Titel :

    Deep Open Space Segmentation using Automotive Radar


    Beteiligte:


    Erscheinungsdatum :

    2020-11-23


    Format / Umfang :

    571562 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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