| Autonomous aerial cinematography in unstructured environments with learned artistic decision‐making R Bonatti, W Wang, C Ho, A Ahuja, M Gschwindt, E Camci, E Kayacan, ... Journal of Field Robotics 37 (4), 606-641, 2020 | 99 | 2020 |
| An aerial robot for rice farm quality inspection with type-2 fuzzy neural networks tuned by particle swarm optimization-sliding mode control hybrid algorithm E Camci, DR Kripalani, L Ma, E Kayacan, MA Khanesar Swarm and evolutionary computation 41, 1-8, 2018 | 91 | 2018 |
| Can a robot become a movie director? Learning artistic principles for aerial cinematography M Gschwindt, E Camci, R Bonatti, W Wang, E Kayacan, S Scherer 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 67 | 2019 |
| Automated tuning of nonlinear model predictive controller by reinforcement learning M Mehndiratta, E Camci, E Kayacan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 48 | 2018 |
| Faster RRT-based nonholonomic path planning in 2D building environments using skeleton-constrained path biasing Y Dong, E Camci, E Kayacan Journal of Intelligent & Robotic Systems 89, 387-401, 2018 | 48 | 2018 |
| Game of drones: UAV pursuit-evasion game with type-2 fuzzy logic controllers tuned by reinforcement learning E Camci, E Kayacan 2016 IEEE international conference on fuzzy systems (FUZZ-IEEE), 618-625, 2016 | 46 | 2016 |
| Learning motion primitives for planning swift maneuvers of quadrotor E Camci, E Kayacan Autonomous Robots 43, 1733-1745, 2019 | 31 | 2019 |
| Deep reinforcement learning for motion planning of quadrotors using raw depth images E Camci, D Campolo, E Kayacan 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 16 | 2020 |
| End-to-end motion planning of quadrotors using deep reinforcement learning E Camci, E Kayacan arXiv preprint arXiv:1909.13599, 2019 | 16 | 2019 |
| Waitress quadcopter explores how to serve drinks by reinforcement learning E Camci, E Kayacan 2016 IEEE region 10 conference (TENCON), 28-32, 2016 | 15 | 2016 |
| QLP: Deep Q-learning for pruning deep neural networks E Camci, M Gupta, M Wu, J Lin IEEE Transactions on Circuits and Systems for Video Technology, 2022 | 13 | 2022 |
| Planning swift maneuvers of quadcopter using motion primitives explored by reinforcement learning E Camci, E Kayacan 2019 American Control Conference (ACC), 279-285, 2019 | 12 | 2019 |
| Is complexity required for neural network pruning? a case study on global magnitude pruning M Gupta, E Camci, VR Keneta, A Vaidyanathan, R Kanodia, A James, ... 2024 IEEE Conference on Artificial Intelligence (CAI), 747-754, 2024 | 11 | 2024 |
| Can deep models help a robot to tune its controller? A step closer to self-tuning model predictive controllers M Mehndiratta, E Camci, E Kayacan Electronics 10 (18), 2187, 2021 | 8 | 2021 |
| An introduction of deep learning methods for sensing applications K Wu, W Cui, NK Vuong, E Camci Generalization With Deep Learning: For Improvement on Sensing Capability, 3-28, 2021 | 2 | 2021 |
| Tethered multicopter guidance in GPS-denied environments through reinforcement learning A Al-Radaideh, RA Selje, D Coraspe, E Camci, R Dutta, L Sun, ... AIAA SCITECH 2023 Forum, 0507, 2023 | 1 | 2023 |
| Bio-inspired classification and evolution of multirotor Micro Aerial Vehicles (MAVs): A comprehensive review SW Hameed, N Imanberdiyev, E Camci, YW Yun, M Feroskhan Robotics and Autonomous Systems, 104802, 2024 | | 2024 |
| Reinforcement learning based motion planning of quadrotors using motion primitives E Camci Nanyang Technological University, 2020 | | 2020 |
| Reconfigurable multi-rotor for high-precision physical interaction J Taylor, N Imanberdiyev, MYM Chuah, WY Yau, G Sartoretti, E Camci | | |
