Mohammed Elhenawy, Huthaifa Ashqar, Mahmoud Masoud, Mohammed Almannaa, Andry Rakotonirainy, Hesham A. Rakha
Abstract:As the Autonomous Vehicle (AV) industry is rapidly advancing, classification of non-motorized (vulnerable) road users (VRUs) becomes essential to ensure their safety and to smooth operation of road applications. The typical practice of non-motorized road users’ classification usually takes numerous training time and ignores the temporal evolution and behavior of the signal. In this research effort, we attempt to detect VRUs with high accuracy be proposing a novel framework that includes using Deep Tr…
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