Our research group collects, postprocesses and exploits large real-world datasets of driver behaviour.
We develop and evaluate state-of-the-art tehnologies for increasing driver safety in the context of semi-autonomous and fully-autonomous vehicles.
January 2016 - Abdić, I., Fridman, L., McDuff, D., Marchi, E., Reimer, B. & Schuller, B. (2016). "Driver Frustration Detection From Audio and Video in the Wild". In Proceedings 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), New York, NY. Also appears as an extended abstract in the Proceedings 39th German Conference on Artificial Intelligence, KI 2016 / ÖGAI Tagung 2016, Klagenfurt, Austria.
November 2015 - I. Abdić, L. Fridman, E. Marchi, D. E. Brown, W. Angell, B. Reimer, and B. W. Schuller, "Detecting Road Surface Wetness from Audio: A Deep Learning Approach". In Proceedings 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico.
October 2015 - L. Fridman, D. E. Brown, W. Angell, I. Abdić, B. Reimer, and H. Y. Noh, "Automated Synchronization of Driving Data Using Vibration and Steering Events" ELSEVIER Pattern Recognition Letters, 2015.
To all student, researchers and potential partners from the industry: Feel free to get in touch directly and connect with me through social media channels.