Computer vision in self-driving vehicles can lead to research and development of futuristic vehicles that can mitigate the road accidents and assist in a safer driving environment. By using the self-driving technology, the riders can be roamed to their destinations without using human interaction. But in recent times self-driving vehicle technology is still at the early stage. Mostly in the rushed areas like cities it becomes challenging to deploy such autonomous systems because even a small amount of data can cause a critical accident situation. In Order to increase the autonomous driving conditions computer vision and deep learning-based approaches are tended to be used. Finding the obstacles on the road and analyzing the current traffic flow are mainly focused areas using computer vision-based approaches. As well as many researchers using deep learning-based approaches like convolutional neural networks to enhance the autonomous driving conditions. This research paper focused on the evaluation of computer vision used in self-driving vehicles.


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    Titel :

    Computer Vision for Autonomous Driving


    Beteiligte:


    Erscheinungsdatum :

    09.12.2021


    Format / Umfang :

    1597994 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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