| A survey of deep learning techniques for autonomous driving S Grigorescu, B Trasnea, T Cocias, G Macesanu Journal of field robotics 37 (3), 362-386, 2020 | 1615 | 2020 |
| Neurotrajectory: A neuroevolutionary approach to local state trajectory learning for autonomous vehicles SM Grigorescu, B Trasnea, L Marina, A Vasilcoi, T Cocias IEEE Robotics and Automation Letters 4 (4), 3441-3448, 2019 | 50 | 2019 |
| Robust camera pose and scene structure analysis for service robotics SM Grigorescu, G Macesanu, TT Cocias, D Puiu, F Moldoveanu Robotics and Autonomous Systems 59 (11), 899-909, 2011 | 34 | 2011 |
| Cloud2edge elastic AI framework for prototyping and deployment of AI inference engines in autonomous vehicles S Grigorescu, T Cocias, B Trasnea, A Margheri, F Lombardi, L Aniello Sensors 20 (19), 5450, 2020 | 23 | 2020 |
| Deep Grid Net (DGN): A deep learning system for real-time driving context understanding LA Marina, B Trasnea, T Cocias, A Vasilcoi, F Moldoveanu, ... 2019 third IEEE international conference on robotic computing (irc), 399-402, 2019 | 19 | 2019 |
| Multiple-superquadrics based object surface estimation for grasping in service robotics TT Cociaş, SM Grigorescu, F Moldoveanu 2012 13th International Conference on Optimization of Electrical and …, 2012 | 16 | 2012 |
| Development of GTBoT, a high performance and modular indoor robot G Macesanu, TT Codas, C Suliman, B Tarnauca 2010 IEEE International Conference on Automation, Quality and Testing …, 2010 | 9 | 2010 |
| Generic fitted shapes (gfs): Volumetric object segmentation in service robotics TT Cocias, F Moldoveanu, SM Grigorescu Robotics and Autonomous Systems 61 (9), 960-972, 2013 | 6 | 2013 |
| GFPNet: A deep network for learning shape completion in generic fitted primitives T Cocias, A Razvant, S Grigorescu IEEE Robotics and Automation Letters 5 (3), 4493-4500, 2020 | 5 | 2020 |
| Stereo vision-based 3D camera pose and object structure estimation SM Grigorescu, TT Cocias, G Macesanu, F Moldoveanu Proc. VISAPP, 355-358, 2012 | 4 | 2012 |
| Generic fitted primitives (GFP): Towards full object volumetric reconstruction for service robotics TT Cocias, F Moldoveanu, SM Grigorescu Václav Skala-UNION Agency, 2013 | 3 | 2013 |
| Object volumetric estimation based on generic fitted primitives for service robotics TT Cociaș, SM Grigorescu, F Moldoveanu | 2 | 2012 |
| 3D structure estimation from a single view using generic fitted primitives (GFP) TT Cocias, SM Grigorescu, F Moldoveanu Computer Vision, Imaging and Computer Graphics. Theory and Application: 7th …, 2013 | 1 | 2013 |
| On the real-time modelling of a robotic scene perception and estimation system SM Grigorescu, G Macesanu, TT Cocias, F Moldoveanu 15th International Conference on System Theory, Control and Computing, 1-4, 2011 | 1 | 2011 |
| Generating training images for machine learning-based objection recognition systems T Cocias, C Ginerica, S Grigorescu, G Macesanu, B Transnea US Patent 10,635,935, 2020 | | 2020 |
| Sisteme incorporate: fundamentele utilizarii sistemelor cu microcontrolere TT COCIAS, SM GRIGORESCU, G MACESANU Editura Universitatii Transilvania din Brasov, 2019 | | 2019 |
| Perceptia 3D in sistemele robotice autonome SM GRIGORESCU, TT COCIAS, A RAZVANT Editura Universitatii Transilvania din Brasov, 2019 | | 2019 |
| Index of papers published in IEEE Robotics and Automation Letters and presented at IEEE/RSJ International Conference on Intelligent Robots and Sys-tems 2019 (IROS’19) TCRA Elderly | | 2019 |
| Estimarea volumetrica 3D in sistemele robotice autonome TT COCIAS, F MOLDOVEANU, SM GRIGORESCU Editura Universitatii Transilvania din Brasov, 2018 | | 2018 |
| Sisteme de vedere artificiala SM GRIGORESCU, TT COCIAS Editura Universitatii Transilvania din Brasov, 2018 | | 2018 |
Sorin GrigorescuTransilvania University of Brasov; Elektrobit Automotive在 unitbv.ro 的电子邮件经过验证
