  | HAWLADER, F., ROBINET, F., & FRANK, R. (25 November 2023). Leveraging the edge and cloud for V2X-based real-time object detection in autonomous driving. Computer Communications, 213, 372-381. doi:10.1016/j.comcom.2023.11.025  Peer Reviewed verified by ORBi |
  | HAWLADER, F., ROBINET, F., & FRANK, R. (2023). Poster: Lightweight Features Sharing for Real-Time Object Detection in Cooperative Driving. In 2023 IEEE Vehicular Networking Conference (VNC). Peer reviewed |
 | COLOT, C., ROBINET, F., & Nichils, G. (2023). Connected Car Platforms, A Field Trial: Are they Ready for Usage Based Insurance? Advances in Transdisciplinary Engineering. doi:10.3233/ATDE230011 Peer reviewed |
 | HAWLADER, F., ROBINET, F., & FRANK, R. (2023). Vehicle-to-Infrastructure Communication for Real-Time Object Detection in Autonomous Driving. In 18th Wireless On-demand Network systems and Services Conference (WONS-23). Peer reviewed |
 | ROBINET, F. (2022). Minimizing Supervision for Vision-Based Perception and Control in Autonomous Driving [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52331 |
 | ROBINET, F., AKL, Y., ULLAH, K., Nozarian, F., Müller, C., & FRANK, R. (October 2022). Striving for Less: Minimally-Supervised Pseudo-Label Generation for Monocular Road Segmentation. IEEE Robotics and Automation Letters, 7 (4), 10628 - 10634. doi:10.1109/LRA.2022.3193463 Peer Reviewed verified by ORBi |
 | COLOT, C., ROBINET, F., Nichil, G., & FRANK, R. (2022). Connected Vehicle Platforms for Dynamic Insurance. in Proceedings of the 6th International Conference on Intelligent Traffic and Transportation. Peer reviewed |
 | ROBINET, F., PARERA, C., HUNDT, C., & FRANK, R. (2022). Weakly-Supervised Free Space Estimation through Stochastic Co-Teaching. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 2022 (pp. 618-627). Peer reviewed |
 | ROBINET, F., & Frank, R. (2022). Refining Weakly-Supervised Free Space Estimation Through Data Augmentation and Recursive Training. In Artificial Intelligence and Machine Learning (pp. 30--45). Springer International Publishing. doi:10.1007/978-3-030-93842-0_2 Peer reviewed |
 | ROBINET, F., & FRANK, R. (2021). Refining Weakly-Supervised Free Space Estimation through Data Augmentation and Recursive Training. In Proceedings of BNAIC/BeneLearn 2021. Peer reviewed |
 | Varisteas, G., FRANK, R., & ROBINET, F. (2021). RoboBus: A Diverse and Cross-Border Public Transport Dataset. In Proceedings of the 19th International Conference on Pervasive Computing and Communications (PerCom 2021). doi:10.1109/PerComWorkshops51409.2021.9431129 Peer reviewed |
 | ROBINET, F., Demeules, A., FRANK, R., VARISTEAS, G., & HUNDT, C. (2020). Leveraging Privileged Information to Limit Distraction in End-to-End Lane Following. 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC). doi:10.1109/CCNC46108.2020.9045110 Peer reviewed |