With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognize targets, this paper introduces a robust system for the detection and localization of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach. It compromises a window-evaluation and a window-classification subsystems. The performance of the proposed framework was evaluated on the Vaihingen dataset. Results demonstrate its superiority to the state of the art.


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    Title :

    Car Detection in Aerial Images of Dense Urban Areas


    Contributors:


    Publication date :

    2018-02-01


    Size :

    2624836 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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