Bolstering the Safety of Self-Driving Cars with a Deep Learn

Self-driving cars need to implement efficient, effective, and accurate detection systems to provide a safe and reliable experience to its users. To this end, an international research team has now developed an end-to-end neural network that, in conjunction with the Internet-of-Things technology, detects object with high accuracy (> 96%) in both 2D and 3D. The…

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Incheon , Inch On Gwangyoksi , South Korea , Canada , Imran Ahmed , Abdellah Chehri , Gwanggil Jeon , Incheon City College , Royal Military College Of Canada , School Of Computing , Anglia Ruskin University , Information Sciences , Department Of Mathematics , Incheon National University , Self Driving Cars , Deep Learning Based Object Detection , Light Detection , Intelligent Transport Systems , Professor Gwanggil Jeon , Smart Iot Enabled End To , Object Detection System , Intelligent Transport , Anglia Ruskin , Embedded Systems Engineering , Incheon National , Computer Science , Royal Military College , National University ,