Vision-based UAV (Unmanned Aerial Vehicle) landing on runways is an emerging topic, because of the possible wide range of applications. Vision-based landing technology can also give an additional independent source of information for civil aviation landing systems. The core of the problem is the detection of the runway and other possible features. This paper introduces a simple framework for runway detection, in the case when only the threshold marker is painted. The approach utilizes corner features and convolutional neural nets for ROI classification.


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    Title :

    Runway detection for UAV landing system


    Contributors:

    Conference:

    CNNA 2018 - The 16th International Workshop on Cellular Nanoscale Networks and their Applications ; 2018 ; Budapest, Hungary


    Published in:

    Publication date :

    2018-01-01


    Size :

    4 pages



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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