Eckehard Steinbach mainly investigates Haptic technology, Computer network, Real-time computing, Network packet and Artificial intelligence. His Haptic technology research is multidisciplinary, incorporating elements of Data stream mining, Teleoperation and Human–computer interaction. His Computer network research integrates issues from Wireless network and Cross-layer optimization.
His Real-time computing research includes elements of Automatic repeat request, Encoder, Communication channel, Distortion and Bitstream. His Network packet study integrates concerns from other disciplines, such as Voice over IP and Jitter. Artificial intelligence and Computer vision are commonly linked in his work.
His scientific interests lie mostly in Artificial intelligence, Computer vision, Haptic technology, Real-time computing and Computer network. His study connects Pattern recognition and Artificial intelligence. Eckehard Steinbach regularly links together related areas like Computer graphics in his Computer vision studies.
His work deals with themes such as Deadband and Teleoperation, which intersect with Haptic technology. While the research belongs to areas of Real-time computing, Eckehard Steinbach spends his time largely on the problem of Network packet, intersecting his research to questions surrounding Transmission. His Computer network research incorporates elements of Wireless, Wireless network, Video quality and Communication channel.
Eckehard Steinbach mostly deals with Artificial intelligence, Computer vision, Haptic technology, Teleoperation and Pattern recognition. His Computer vision study frequently draws parallels with other fields, such as Surface finish. In general Haptic technology study, his work on Haptic communication often relates to the realm of Kinesthetic learning, thereby connecting several areas of interest.
His Teleoperation research incorporates themes from Transmission, Real-time computing, Simulation and Data transmission. His studies deal with areas such as Control system and Augmented reality as well as Real-time computing. His Pattern recognition study combines topics from a wide range of disciplines, such as RGB color model, Artificial neural network and Residual.
His main research concerns Artificial intelligence, Haptic technology, The Internet, Computer vision and Real-time computing. His Pattern recognition research extends to Artificial intelligence, which is thematically connected. The concepts of his Haptic technology study are interwoven with issues in Orchestration, Computer network and Teleoperation.
His work deals with themes such as Wireless and Bandwidth, which intersect with Computer network. The study incorporates disciplines such as Pipeline and Computer graphics in addition to Computer vision. His Real-time computing research integrates issues from Minification, Video Graphics Array, Transmission, Multipath propagation and Non-line-of-sight propagation.
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.
Application-driven cross-layer optimization for video streaming over wireless networks
S. Khan;Y. Peng;E. Steinbach;M. Sgroi.
IEEE Communications Magazine (2006)
Real-time compression of point cloud streams
Julius Kammerl;Nico Blodow;Radu Bogdan Rusu;Suat Gedikli.
international conference on robotics and automation (2012)
Adaptive media playout for low-delay video streaming over error-prone channels
M. Kalman;E. Steinbach;B. Girod.
IEEE Transactions on Circuits and Systems for Video Technology (2004)
Standard compatible extension of H.263 for robust video transmission in mobile environments
E. Steinbach;N. Farber;B. Girod.
IEEE Transactions on Circuits and Systems for Video Technology (1997)
Perception-Based Data Reduction and Transmission of Haptic Data in Telepresence and Teleaction Systems
P. Hinterseer;S. Hirche;S. Chaudhuri;E. Steinbach.
IEEE Transactions on Signal Processing (2008)
E. Steinbach;S. Hirche;M. Ernst;F. Brandi.
Proceedings of the IEEE (2012)
Toward Haptic Communications Over the 5G Tactile Internet
Konstantinos Antonakoglou;Xiao Xu;Eckehard Steinbach;Toktam Mahmoodi.
IEEE Communications Surveys and Tutorials (2018)
Graph-based data fusion of pedometer and WiFi measurements for mobile indoor positioning
Sebastian Hilsenbeck;Dmytro Bobkov;Georg Schroth;Robert Huitl.
ubiquitous computing (2014)
Mobile Visual Location Recognition
G Schroth;R Huitl;D Chen;M Abu-Alqumsan.
IEEE Signal Processing Magazine (2011)
Disposal of explosive ordnances by use of a bimanual haptic telepresence system
A. Kron;G. Schmidt;B. Petzold;M.I. Zah.
international conference on robotics and automation (2004)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: