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Found 4 papers, 1 papers with code
End-to-End 3D-PointCloud Semantic Segmentation for Autonomous Driving
Imbalanced distribution of classes in the dataset is one of the challenges that face 3D semantic scene labeling task.
Meta learning Framework for Automated Driving
Under the proposed framework, we propose MetaDAgger, a novel algorithm which tackles the generalization issues in traditional imitation learning.
Deep Reinforcement Learning framework for Autonomous Driving
This is of particular relevance as it is difficult to pose autonomous driving as a supervised learning problem due to strong interactions with the environment including other vehicles, pedestrians and roadworks.
End-to-End Deep Reinforcement Learning for Lane Keeping Assist
This is of particular interest as it is difficult to pose autonomous driving as a supervised learning problem as it has a strong interaction with the environment including other vehicles, pedestrians and roadworks.
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