In this work, we present a learning method for lateral and longitudinal
...
Deep learning models for self-driving cars require a diverse training da...
In this work, we propose a learning based neural model that provides bot...
Traditional approaches to prediction of future trajectory of road agents...
The human brain can be considered to be a graphical structure comprising...
Existing vision based supervised approaches to lateral vehicle control a...
Vision-based learning methods for self-driving cars have primarily used
...
We present a novel dataset covering seasonal and challenging perceptual
...
The ability of deep learning models to generalize well across different
...
Direct methods for SLAM have shown exceptional performance on odometry t...
In this paper, we present a framework to control a self-driving car by f...
Semantic segmentation maps can be used as input to models for maneuverin...
Model-free reinforcement learning has recently been shown to successfull...
End-to-end supervised learning has shown promising results for self-driv...