This paper presents a deep learning architecture to map the vehicle detection in the frontal view onto a bird’s eye view of the road scene, while preserving the size and direction of the moving vehicle.
One crucial standard in measuring autonomous vehicles is whether the autonomous vehicles can go through intersections with no signals. In this paper, the authors provide us with a new strategy of using Deep Reinforcement Learning.
In his blog post “How Data Science Apply to Robotics” on Data Science Central, Dr. Ammar A. Raja points out that there are two major problems scientists have encountered while applying data science to robotics.
Although no innovations for the NMT architecture was introduced, the authors claim that a classic NMT baseline system with carefully tuned hyperparameters can still achieve comparable result to the state-of-the-art.