Vehicles used in the automotive supply chain and for transportation must be able to operate in all types of weather and visibility. Sudden variations in fog, snow, lighting, smoke, rain, etc. are challenging conditions for the supply chain. While normal radars and cameras will work fine in most driving situations, vehicles may malfunction in some edge cases and in situations where accidents are more likely to occur. Numerous car accidents happen in mountainous areas and on ghats because it is unable to see the road well due to strong fog, smoke, and even smog. So, the suggested system can be used to solve this issue. When a person, animal, or vehicle enters the proposed system in a risky manner, it may result in an accident, hence it offers accident prevention before it happens a warning.


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    Titel :

    Object Detection System in Adverse Weather Conditions Using Ann


    Beteiligte:
    Joshua, Jeberson A (Autor:in) / Narasiman, L (Autor:in) / Yogeshwaran, V (Autor:in) / Anand, M.Vijay (Autor:in)


    Erscheinungsdatum :

    03.03.2023


    Format / Umfang :

    1246226 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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