GINERICĂ Cosmin

Asistent universitar
Departamentul de Automatică și Tehnologia Informației
Facultatea de Inginerie Electrică și Știința Calculatoarelor
Contact:
Str. Politehnicii nr. 1, Brașov, Romania
Corp N
Tel. : +40 711928609
E-mail: cosmin.ginerica@unitbv.ro
Interese de cercetare:
- Inteligența Artificială
- Vedere Artificială
- Robotică
Publicații:
- C. Ginerica, M. Zaha, L. Floroian, D. Cojocaru, S. Grigorescu, “A Vision Dynamics Learning Approach to Robotic Navigation in Unstructured Environments”, Robotics 2024; 13(1):15, https://doi.org/10.3390/robotics13010015.
- C. Ginerica, M. V. Zaha, F. Gogianu, L. Busoniu, B. Trasnea and S. M. Grigorescu, "ObserveNet Control: A Vision-Dynamics Learning Approach to Predictive Control in Autonomous Vehicles," in IEEE Robotics and Automation Letters, doi: 10.1109/LRA.2021.3096157.
- C. Ginerica, D. Cojocaru, S. Grigorescu, „A Vision-Dynamics Learning Approach to Prediction-Based Control in Autonomous Vehicles”, International Symposium on Signals, Circuits & Systems - ISSCS 2021.
- C. Ginerica, V. Isofache, S. Grigorescu, „Vision Dynamics: Environment Modelling, Path Planning and Control Based on Semantic Segmentation”, International Joint Conference OPTIM-ACEMP 2021.
- S.M. Grigorescu, G. Macesanu, T.T. Cocias, B. Trasnea, C. Ginerica, „Generative training images for machine learning-based object recognition system”, European Patent Application, Patent no. EP 3 343 432 A1, Date of publication: 04.05.2017.
- S.M. Grigorescu, C. Ginerica, „Recunoașterea formelor. Îndrumar de laborator. Set de lucrări practice privind procesarea statistică a datelor pentru disciplina Machine Learning”, Editura Universității Transilvania, ISBN 978-606-19-0894-3, 2017.
- S.M. Grigorescu, C. Ginerica, M. Zaha, G. Macesanu, B. Trasnea, ”LVD-NMPC: A Learning-based Vision Dynamics Approach to Nonlinear Model Predictive Control for Autonomous Vehicles”, Advanced Robotic Systems, Sage Journals, 2021.
- B. Trasnea; C. Ginerica, M. Zaha, G. Măceşanu, C. Pozna, S. Grigorescu, OctoPath: An OcTree-Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robots. Sensors 2021, 21, 3606. https://doi.org/10.3390/s21113606.