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Robust 4D awareness via diffusion adaptation over Connected and Automated vehicles
2022
Zenodo
In this paper, we focus on enhancing the 4D situational awareness in a swarm of Connected and Automated vehicles, employing information diffusion against unsuccessful object detection. More specifically, in the perception layer we exploit model compression and acceleration techniques for the efficient execution of relevant deep learning models, and determine different probabilities of detection success. Afterwards, we integrate these success indicators in the localization layer of nodes and by
doi:10.5281/zenodo.6672942
fatcat:bnhw2ev4f5hzdinlkr7uhjyfnm