Driver drowsiness detection using behavioral measures and machine learning techniques: A review of state-of-art techniques M Ngxande, JR Tapamo, M Burke 2017 pattern recognition Association of South Africa and Robotics and …, 2017 | 142 | 2017 |
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video M Jaques, M Burke, T Hospedales ICLR 2019, 2019 | 61* | 2019 |
Residual learning from demonstration T Davchev, KS Luck, M Burke, F Meier, S Schaal, S Ramamoorthy IEEE Robotics and Automation Letters, 2022, 2022 | 56 | 2022 |
Path-following control of a velocity constrained tracked vehicle incorporating adaptive slip estimation M Burke 2012 IEEE International Conference on Robotics and Automation, 97-102, 2012 | 52 | 2012 |
Estimating missing marker positions using low dimensional Kalman smoothing M Burke, J Lasenby Journal of biomechanics 49 (9), 1854-1858, 2016 | 48 | 2016 |
Bias remediation in driver drowsiness detection systems using generative adversarial networks M Ngxande, JR Tapamo, M Burke IEEE Access 8, 55592-55601, 2020 | 44 | 2020 |
Disentangled Relational Representations for Explaining and Learning from Demonstration Y Hristov, D Angelov, M Burke, A Lascarides, S Ramamoorthy Conference on Robot Learning (CoRL), 2019 | 30 | 2019 |
Vid2Param: Modelling of Dynamics Parameters From Video M Asenov, M Burke, D Angelov, T Davchev, K Subr, S Ramamoorthy IEEE ROBOTICS AND AUTOMATION LETTERS 5 (2), 2872-2872, 2020 | 29* | 2020 |
Pantomimic gestures for human–robot interaction M Burke, J Lasenby IEEE Transactions on Robotics 31 (5), 1225-1237, 2015 | 25 | 2015 |
From explanation to synthesis: Compositional program induction for learning from demonstration M Burke, S Penkov, S Ramamoorthy Robotics: Science and Systems, 2019 | 23 | 2019 |
Time-varying causality between equity and currency returns in the United Kingdom: Evidence from over two centuries of data P Kanda, M Burke, R Gupta Physica A: Statistical Mechanics and its Applications 506, 1060-1080, 2018 | 22 | 2018 |
Newtonianvae: Proportional control and goal identification from pixels via physical latent spaces M Jaques, M Burke, TM Hospedales Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 17 | 2021 |
Composing Diverse Policies for Temporally Extended Tasks D Angelov, Y Hristov, M Burke, S Ramamoorthy Robotics and Automation Letters (RA-L), 2020 | 16 | 2020 |
Challenges of driver drowsiness prediction: The remaining steps to implementation E Perkins, C Sitaula, M Burke, F Marzbanrad IEEE Transactions on Intelligent Vehicles 8 (2), 1319-1338, 2022 | 15 | 2022 |
Hybrid system identification using switching density networks M Burke, Y Hristov, S Ramamoorthy Conference on Robot Learning (CoRL), 2019 | 14 | 2019 |
Learning rewards from exploratory demonstrations using probabilistic temporal ranking M Burke, K Lu, D Angelov, A Straižys, C Innes, K Subr, S Ramamoorthy Autonomous Robots 47 (6), 733-751, 2023 | 12* | 2023 |
Detecting inter-sectional accuracy differences in driver drowsiness detection algorithms M Ngxande, JR Tapamo, M Burke 2020 International SAUPEC/RobMech/PRASA Conference, 2020 | 11 | 2020 |
DepthwiseGANs: Fast training generative adversarial networks for realistic image synthesis M Ngxande, JR Tapamo, M Burke 2019 Southern African Universities Power Engineering Conference/Robotics and …, 2019 | 11 | 2019 |
Learning structured representations of spatial and interactive dynamics for trajectory prediction in crowded scenes T Davchev, M Burke, S Ramamoorthy IEEE Robotics and Automation Letters 6 (2), 707-714, 2020 | 9* | 2020 |
Estimating Target Orientation with a Single Camera for Use in a Human-Following Robot M Burke, W Brink 21st Annual Symposium of the Pattern Recognition Association of South Africa, 2010 | 9 | 2010 |