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2020 – today
- 2022
[c10]Safdar Mahmood, Stefan Scharoba
, Jonas Schorlemer, Christian Schulz, Michael Hübner, Marc Reichenbach:
Detecting Improvised Land-mines using Deep Neural Networks on GPR Image Dataset targeting FPGAs. NorCAS 2022: 1-7- [c9]Florian Fricke, Stefan Scharoba, Sebastian Rachuj, Andreas Konopik, Florian Kluge, Georg Hofstetter, Marc Reichenbach:
Application Runtime Estimation for AURIX Embedded MCU Using Deep Learning. SAMOS 2022: 235-249 - 2021
- [c8]Stefan Scharoba, Kai-Uwe Basener, Jens Bielefeldt, Hans-Werner Wiesbrock, Michael Hübner:
Towards Machine Learning Support for Embedded System Tests. DSD 2021: 166-173 - [c7]Jens Bielefeldt, Kai-Uwe Basener, Siddique Reza Khan, Mozhdeh Massah, Hans-Werner Wiesbrock, Stefan Scharoba, Michael Hübner:
Einsatz von Deep Learning für den Test Eingebetteter Systeme. GI-Jahrestagung 2021: 1859-1864 - [c6]Jens Bielefeldt, Kai-Uwe Basener, Siddique Reza Khan, Mozhdeh Massah, Hans-Werner Wiesbrock, Stefan Scharoba, Michael Hübner:
DeepTest: How Machine Learning Can Improve the Test of Embedded Systems. MECO 2021: 1-6
2010 – 2019
- 2017
- [c5]Stefan Scharoba, Heinrich Theodor Vierhaus:
Fast power overhead prediction for hardware redundancy-based fault tolerance. IOLTS 2017: 265-270 - 2016
- [c4]Stefan Scharoba, Heinrich Theodor Vierhaus:
An Interactive Design Space Exploration Tool for Dependable Integrated Circuits. DSD 2016: 714-717 - [c3]Mario Schölzel, Tobias Koal, Sebastian Müller, Stefan Scharoba, Stephanie Roder, Heinrich Theodor Vierhaus:
A comprehensive software-based self-test and self-repair method for statically scheduled superscalar processors. LATS 2016: 33-38 - 2015
- [c2]Tobias Koal, Stefan Scharoba, Heinrich Theodor Vierhaus:
Combining Correction of Delay Faults and Transient Faults. DDECS 2015: 99-102 - [c1]Sebastian Müller, Tobias Koal, Stefan Scharoba, Heinrich Theodor Vierhaus, Mario Schölzel:
A multi-layer software-based fault-tolerance approach for heterogenous multi-core systems. LATS 2015: 1-6
Coauthor Index
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