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of 45
pro vyhledávání: '"Luettin, Juergen"'
Accurate trajectory prediction is crucial for ensuring safe and efficient autonomous driving. However, most existing methods overlook complex interactions between traffic participants that often govern their future trajectories. In this paper, we pro
Externí odkaz:
http://arxiv.org/abs/2405.03809
Trajectory prediction in autonomous driving relies on accurate representation of all relevant contexts of the driving scene, including traffic participants, road topology, traffic signs, as well as their semantic relations to each other. Despite incr
Externí odkaz:
http://arxiv.org/abs/2404.19379
Autor:
Mlodzian, Leon, Sun, Zhigang, Berkemeyer, Hendrik, Monka, Sebastian, Wang, Zixu, Dietze, Stefan, Halilaj, Lavdim, Luettin, Juergen
Trajectory prediction in traffic scenes involves accurately forecasting the behaviour of surrounding vehicles. To achieve this objective it is crucial to consider contextual information, including the driving path of vehicles, road topology, lane div
Externí odkaz:
http://arxiv.org/abs/2312.09676
Autor:
Zipfl, Maximilian, Hertlein, Felix, Rettinger, Achim, Thoma, Steffen, Halilaj, Lavdim, Luettin, Juergen, Schmid, Stefan, Henson, Cory
Representing relevant information of a traffic scene and understanding its environment is crucial for the success of autonomous driving. Modeling the surrounding of an autonomous car using semantic relations, i.e., how different traffic participants
Externí odkaz:
http://arxiv.org/abs/2212.02503
Automated driving is one of the most active research areas in computer science. Deep learning methods have made remarkable breakthroughs in machine learning in general and in automated driving (AD)in particular. However, there are still unsolved prob
Externí odkaz:
http://arxiv.org/abs/2210.08119
Publikováno v:
International Journal of Semantic Computing; Jun2023, Vol. 17 Issue 2, p249-271, 23p
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2002, Iss 11, p 475826 (2002)
Externí odkaz:
https://doaj.org/article/bed763c93965467388f0f2157a4974eb
Autor:
Luettin, Juergen, Ben-Yacoub, Souheil
Publikováno v:
6th European Conference on Speech Communication and Technology (Eurospeech 1999).
This paper describes a multi-modal person verification system using speech and frontal face images. We consider two different speaker verification algorithms, a text-independent method using a second-order statistical measure and a text-dependent met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::313969a7533a5d5e373da5e0c3452d3e
https://doi.org/10.21437/eurospeech.1999-242
https://doi.org/10.21437/eurospeech.1999-242