Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kmeid Saad"'
Autor:
Stefan Muckenhuber, Martin Kirchengast, Relindis Rott, Daniel Watzenig, Hannes Holzer, Kmeid Saad, Franz Michael Maier, Birgit Schlager, Georg Stettinger, Simon Schmidt, Jonas Ruebsam
Publikováno v:
SAE International Journal of Connected and Automated Vehicles. 3:233-261
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff86fc472672284da174616909d84745
https://doi.org/10.4271/12-03-03-0018
https://doi.org/10.4271/12-03-03-0018
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
Autor:
Kmeid Saad, Stefan-Alexander Schneider
Publikováno v:
e & i Elektrotechnik und Informationstechnik. 135:328-334
This paper presents an overview of a hybrid test strategy for ADAS functions testing and validation. The hybrid test strategy represents a combination of real and virtual validation procedure providing a substitute to elaborate real tests in the deve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5c73217ac7cd0ab4c0708ebff975467
https://doi.org/10.1007/s00502-018-0622-7
https://doi.org/10.1007/s00502-018-0622-7
Autor:
Stefan-Alexander Schneider, Kmeid Saad
Publikováno v:
Transportation Research Procedia. 41:799-801
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::043e8302a1d35bbd337eff2c4322e898
https://doi.org/10.1016/j.trpro.2019.09.127
https://doi.org/10.1016/j.trpro.2019.09.127
Autor:
Kmeid Saad, Stefan-Alexander Schneider
Publikováno v:
ICCVE
In this paper, we describe a new approach for synthetic image augmentation and its advantages in training Deep Neural Networks (DNNs) for object classification and localization. To address the need for a significant amount of data when training DNNs,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8200acfee89f2d7a68c18fa62aa29224
https://doi.org/10.1109/iccve45908.2019.8965233
https://doi.org/10.1109/iccve45908.2019.8965233
Publikováno v:
Robotica & Management, Vol 20, Iss 1, Pp 54-55 (2015)
This study illustrates the usage of stacker cranes and image processing in automated warehouse systems. The aim is to use real time image processing and analysis for a stacker’s crane position fixing in order to use it as a pick-up and delivery sys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doajarticles::5264e3cc51da4896493b881b2fa09d06
http://www.robotica-management.uem.ro/fileadmin/Robotica/2015_1/Pag_54_Saad.pdf
http://www.robotica-management.uem.ro/fileadmin/Robotica/2015_1/Pag_54_Saad.pdf