His primary scientific interests are in Artificial intelligence, Brain–computer interface, Electroencephalography, Computer vision and Speech recognition. His Artificial intelligence research includes themes of Machine learning, Task and Pattern recognition. The concepts of his Brain–computer interface study are interwoven with issues in Motor cortex, Electrocorticography and Aptitude.
His work deals with themes such as Pupil and Bayesian probability, which intersect with Computer vision. His Systems architecture research is multidisciplinary, incorporating perspectives in Software and System on a chip, Embedded system. In his study, Programming language is inextricably linked to Computer hardware, which falls within the broad field of Embedded system.
Embedded system, Artificial intelligence, Computer architecture, Software and Parallel computing are his primary areas of study. His Embedded system research incorporates themes from Emulation and Embedded software. His studies in Artificial intelligence integrate themes in fields like Machine learning, Brain–computer interface, Computer vision and Pattern recognition.
His Brain–computer interface study introduces a deeper knowledge of Neuroscience. Computer vision connects with themes related to Eye movement in his study. He regularly links together related areas like High-level synthesis in his Computer architecture studies.
Wolfgang Rosenstiel mainly investigates Artificial intelligence, Embedded system, Computer vision, Brain–computer interface and Eye tracking. His biological study spans a wide range of topics, including Machine learning, Interface, Task and Pattern recognition. His studies deal with areas such as Software, Fault injection and Embedded software as well as Embedded system.
His Computer vision research incorporates elements of Pupil, Smooth pursuit, Robustness and Driving simulator. In the field of Electroencephalography and Neuroscience Wolfgang Rosenstiel studies Brain–computer interface. In his study, Support vector machine is strongly linked to Speech recognition, which falls under the umbrella field of Electroencephalography.
His primary areas of study are Artificial intelligence, Computer vision, Eye tracking, Brain–computer interface and Eye movement. Wolfgang Rosenstiel has included themes like Machine learning and Pattern recognition in his Artificial intelligence study. His Computer vision study combines topics from a wide range of disciplines, such as Detector, Pupil, Saccade, Fixation and Smooth pursuit.
The study incorporates disciplines such as Chronic stroke and Aptitude in addition to Brain–computer interface. His work carried out in the field of Eye movement brings together such families of science as Audiology, Gaze, Visual perception, Visual field and Driving test. His work in Workload addresses subjects such as Computer architecture, which are connected to disciplines such as Software.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
An MEG-based brain-computer interface (BCI)
Jürgen Mellinger;Gerwin Schalk;Gerwin Schalk;Christoph Braun;Hubert Preissl;Hubert Preissl.
NeuroImage (2007)
Multilevel logic synthesis based on functional decision diagrams
U. Kebschull;E. Schubert;W. Rosenstiel.
european design automation conference (1992)
Methods Towards Invasive Human Brain Computer Interfaces
Thomas N. Lal;Thilo Hinterberger;Guido Widman;Michael Schröder.
neural information processing systems (2004)
Synthesizing circuits from behavioural descriptions
R. Camposano;W. Rosenstiel.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (1989)
Object-Oriented Bayesian Networks for Detection of Lane Change Maneuvers
Dietmar Kasper;Galia Weidl;Thao Dang;Gabi Breuel.
IEEE Intelligent Transportation Systems Magazine (2012)
EEG alpha spindle measures as indicators of driver fatigue under real traffic conditions.
Michael Simon;Michael Simon;Eike A. Schmidt;Wilhelm E. Kincses;Martin Fritzsche.
Clinical Neurophysiology (2011)
SystemC: methodologies and applications
Wolfgang Müller;Wolfgang Rosenstiel;Jürgen Ruf.
(2003)
Neural mechanisms of brain-computer interface control.
Sebastian Halder;D. Agorastos;Ralf Veit;Eva M. Hammer.
NeuroImage (2011)
Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.
Martin Spüler;Wolfgang Rosenstiel;Martin Bogdan;Martin Bogdan.
PLOS ONE (2012)
Fully Adaptive Fault-Tolerant Routing Algorithm for Network-on-Chip Architectures
T. Schonwald;J. Zimmermann;O. Bringmann;W. Rosenstiel.
digital systems design (2007)
Profile was last updated on December 6th, 2021.
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