Noha Radwan
Noha Radwan
Ph.D. Candidate, University of Freiburg
Verified email at informatik.uni-freiburg.de - Homepage
TitleCited byYear
Deep auxiliary learning for visual localization and odometry
A Valada, N Radwan, W Burgard
2018 IEEE International Conference on Robotics and Automation (ICRA), 6939-6946, 2018
632018
Vlocnet++: Deep multitask learning for semantic visual localization and odometry
N Radwan, A Valada, W Burgard
IEEE Robotics and Automation Letters 3 (4), 4407-4414, 2018
462018
Topometric localization with deep learning
GL Oliveira, N Radwan, W Burgard, T Brox
Robotics Research, 505-520, 2020
132020
Multimodal Interaction-aware Motion Prediction for Autonomous Street Crossing
N Radwan, A Valada, W Burgard
arXiv preprint arXiv:1808.06887, 2018
112018
Do you see the bakery? leveraging geo-referenced texts for global localization in public maps
N Radwan, GD Tipaldi, L Spinello, W Burgard
2016 IEEE International Conference on Robotics and Automation (ICRA), 4837-4842, 2016
92016
Why Did the Robot Cross the Road?-Learning from Multi-Modal Sensor Data for Autonomous Road Crossing
N Radwan, W Winterhalter, C Dornhege, W Burgard
Proc.~ of the IEEE, 0
5*
Incorporating Semantic and Geometric Priors in Deep Pose Regression
A Valada, N Radwan, W Burgard
4*
Perspectives on Deep Multimodel Robot Learning
W Burgard, A Valada, N Radwan, T Naseer, J Zhang, J Vertens, O Mees, ...
2*
Effective Interaction-aware Trajectory Prediction using Temporal Convolutional Neural Networks
N Radwan, W Burgard
Proceedings of the Workshop on Crowd Navigation: Current Challenges and New …, 2018
12018
Leveraging Sparse and Dense Features for Reliable State Estimation in Urban Environments
N Radwan
Multitask Learning for Reliable State Estimation
N Radwan, W Burgard
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Articles 1–11