Engineering and TechnologyNature Machine Intelligence
Deep learning-based robust positioning for all-weather autonomous driving
Y. Almalioglu, M. Turan, et al.
Dive into the innovative world of autonomous vehicle technology with groundbreaking research by Yasin Almalioglu, Mehmet Turan, Niki Trigoni, and Andrew Markham. This study introduces a robust, deep learning-based method for ego-motion estimation under adverse weather conditions, integrating visual and radar data to enhance safety and reliability in all environments.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Engineering and Technology
A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving
D. Li and O. Okhrin
Transportation
Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments
Y. Fei, L. Xing, et al.
Computer Science
Deep learning-based multi-criteria recommender system for technology-enhanced learning
L. Salau, H. Mohamed, et al.
Engineering and Technology
Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials
S. Masubuchi, E. Watanabe, et al.
