Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Stefano M. Canta"'
Autor:
Arien P. Sligar, Shawn Carpenter, Markus Goldgruber, Stefano M. Canta, Ushemadzoro Chipengo, Hen Leibovich
Publikováno v:
IEEE Access, Vol 9, Pp 82597-82617 (2021)
Detection and classification of vulnerable road users (VRUs) such as pedestrians and cyclists is a key requirement for the realization of fully autonomous vehicles. Radar-based classification of VRUs can be achieved by exploiting differences in the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c74d75a1848fe2df7fdf0ca4af431e6f
https://doi.org/10.1109/access.2021.3085985
https://doi.org/10.1109/access.2021.3085985
Publikováno v:
Proceedings ISBN: 9783658347536
Advanced driver assistance systems (ADAS) and autonomous vehicles (AV) require massive amounts of sensor data to test and train driving algorithms and to design sensor hardware. In many practical cases, these data must be generated at or beyond real-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2916b1c866576188a10ff3d7980de929
https://doi.org/10.1007/978-3-658-34754-3_7
https://doi.org/10.1007/978-3-658-34754-3_7
Publikováno v:
2015 IEEE Radar Conference (RadarCon).
The shooting-and-bouncing rays (SBR) method for solving large-scale scattering problems uses geometrical optics (GO) ray tracing to extend physical optics (PO) to multi-bounce geometries. In this paper, we explain how the accuracy of SBR for predicti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0116df950ac807319683005cbc9873cb
https://doi.org/10.1109/radar.2015.7131087
https://doi.org/10.1109/radar.2015.7131087
Publikováno v:
2015 IEEE Radar Conference (RadarCon); 2015, p0704-0707, 4p
Publikováno v:
2007 International Waveform Diversity & Design Conference; 2007, p358-361, 4p
Automatisiertes Fahren 2021 : Vom assistierten zum autonomen Fahren 7. Internationale ATZ-Fachtagung
Autor:
Torsten Bertram
Künstliche Intelligenz, Machine- oder Deep-Learning sind Treiber des automatisierten Fahrens. Das Zusammenspiel von künstlicher und menschlicher Intelligenz sowie die Fähigkeit von Mensch und Maschine zu kooperieren müssen in neuen Interaktionseb