Time-to-lane-change prediction with deep learning HQ Dang, J Fürnkranz, A Biedermann, M Hoepfl 2017 ieee 20th international conference on intelligent transportation …, 2017 | 65 | 2017 |
Driver information embedding with siamese LSTM networks H Dang, J Fürnkranz 2019 IEEE Intelligent Vehicles Symposium (IV), 935-940, 2019 | 16 | 2019 |
Using past maneuver executions for personalization of a driver model H Dang, J Fürnkranz 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 11 | 2018 |
ITS+ DM Hackathon (ITSC 2017): Lane departure prediction with naturalistic driving data A Alekseenko, HQ Dang, G Bansal, J Sanchez-Medina, C Miyajima, ... IEEE Intelligent Transportation Systems Magazine 11 (4), 78-93, 2018 | 8 | 2018 |
The PRORETA 4 City Assistant System: Adaptive maneuver assistance at urban intersections using driver behavior modeling J Schwehr, S Luthardt, H Dang, M Henzel, H Winner, J Adamy, ... at-Automatisierungstechnik 67 (9), 783-798, 2019 | 6 | 2019 |
Exploiting Maneuver Dependency for Personalization of a Driver Model. HQ Dang, J Fürnkranz LWDA, 93-97, 2018 | 4 | 2018 |
Time series outlier detection in spacecraft data H Dang Knowledge Engineering Group, TU Darmstadt, 2014 | 4 | 2014 |
Adaptive Personalization in Driver Assistance Systems H Dang Technische Universität Darmstadt, 2021 | 1 | 2021 |