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| DeepVO: Towards end-to-end visual odometry with deep recurrent convolutional neural networks S Wang, R Clark, H Wen, N Trigoni 2017 IEEE International Conference on Robotics and Automation (ICRA), 2043-2050, 2017 | 1040 | 2017 |
| UnDeepVO: Monocular visual odometry through unsupervised deep learning R Li, S Wang, Z Long, D Gu 2018 IEEE International Conference on Robotics and Automation (ICRA), 7286-7291, 2018 | 651 | 2018 |
| ViNet: Visual-inertial odometry as a sequence-to-sequence learning problem R Clark, S Wang, H Wen, A Markham, N Trigoni AAAI Conference on Artificial Intelligence (AAAI), 2017 | 444 | 2017 |
| Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds B Yang, J Wang, R Clark, Q Hu, S Wang, A Markham, N Trigoni Thirty-third Conference on Neural Information Processing Systems (NeurIPS …, 2019 | 365 | 2019 |
| Vidloc: A deep spatio-temporal model for 6-dof video-clip relocalization R Clark, S Wang, A Markham, N Trigoni, H Wen Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 336 | 2017 |
| Artificial intelligence enabled wireless networking for 5G and beyond: Recent advances and future challenges CX Wang, M Di Renzo, S Stanczak, S Wang, EG Larsson IEEE Wireless Communications 27 (1), 16-23, 2020 | 285 | 2020 |
| Radiate: A radar dataset for automotive perception in bad weather M Sheeny, E De Pellegrin, S Mukherjee, A Ahrabian, S Wang, A Wallace 2021 IEEE International Conference on Robotics and Automation (ICRA), 1-7, 2021 | 259 | 2021 |
| End-to-end, sequence-to-sequence probabilistic visual odometry through deep neural networks S Wang, R Clark, H Wen, N Trigoni The International Journal of Robotics Research (IJRR) 37 (4-5), 513-542, 2018 | 241 | 2018 |
| Towards monocular vision based obstacle avoidance through deep reinforcement learning L Xie, S Wang, A Markham, N Trigoni Robotics: Science and Systems (RSS), Workshop on New Frontiers for Deep …, 2017 | 224 | 2017 |
| 3D object reconstruction from a single depth view with adversarial learning B Yang, H Wen, S Wang, R Clark, A Markham, N Trigoni Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 218 | 2017 |
| Adaptive low-level control of autonomous underwater vehicles using deep reinforcement learning I Carlucho, M De Paula, S Wang, Y Petillot, GG Acosta Robotics and Autonomous Systems 107, 71-86, 2018 | 178 | 2018 |
| Robust attentional aggregation of deep feature sets for multi-view 3D reconstruction B Yang, S Wang, A Markham, N Trigoni International Journal of Computer Vision 128 (1), 53-73, 2020 | 151 | 2020 |
| Artificial intelligence to manage network traffic of 5G wireless networks Y Fu, S Wang, CX Wang, X Hong, S McLaughlin IEEE network 32 (6), 58-64, 2018 | 150 | 2018 |
| RadarSLAM: Radar based Large-Scale SLAM in All Weathers Z Hong, Y Petillot, S Wang 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020 | 141 | 2020 |
| DeepSLAM: A robust monocular SLAM system with unsupervised deep learning R Li, S Wang, D Gu IEEE Transactions on Industrial Electronics 68 (4), 3577-3587, 2020 | 127 | 2020 |
| A review of visual inertial odometry from filtering and optimisation perspectives J Gui, D Gu, S Wang, H Hu Advanced Robotics 29 (20), 1289-1301, 2015 | 122 | 2015 |
| Learning mobile manipulation through deep reinforcement learning C Wang, Q Zhang, Q Tian, S Li, X Wang, D Lane, Y Petillot, S Wang Sensors 20 (3), 939, 2020 | 106 | 2020 |
| Learning with training wheels: speeding up training with a simple controller for deep reinforcement learning L Xie, S Wang, S Rosa, A Markham, N Trigoni 2018 IEEE international conference on robotics and automation (ICRA), 6276-6283, 2018 | 100 | 2018 |
| Deep sensor fusion between 2D laser scanner and IMU for mobile robot localization C Li, S Wang, Y Zhuang, F Yan IEEE Sensors Journal 21 (6), 8501-8509, 2019 | 75 | 2019 |
