This paper gives insights on identification and feature extraction of vehicle damage caused by numerous obstacles and other impending cars. In the past, automotive specialists mostly used physical examinations to find automobile defects and scratches. This procedure entailed visually inspecting the whole vehicle’s surface under lighting conditions to find flaws. These systems can analyse enormous volumes of data quickly and find flaws with higher precision and consistency by utilising the power of computer vision. We used Yolov8 architecture to identify the dents and scratches of vehicles and achieved an mean average precision of 0.579 with threshold value of 0.5.


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    Titel :

    Dent and Scratch Detection using Computer Vision


    Beteiligte:
    Raju, Manu (Autor:in) / S, Goutham (Autor:in) / S, Dhanushya (Autor:in)


    Erscheinungsdatum :

    09.12.2023


    Format / Umfang :

    670101 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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