Kontakt und Affiliationen
- E-Mail:
- platzner@uni-paderborn.de
- Telefon:
- +49 5251 60-5250
- Web:
- Homepage
- Büroanschrift:
-
Pohlweg 51
33098 Paderborn - Raum:
- O3.207
- Sprechstunden:
by appointment
- E-Mail:
- eim-forschungsdekan@lists.uni-paderborn.de
- Telefon:
- +49 5251 60-5250
- Web:
- Homepage
- Büroanschrift:
-
Pohlweg 51
33098 Paderborn - Raum:
- O3.207
- Sprechstunden:
by appointment
- E-Mail:
- platzner@uni-paderborn.de
- Telefon:
- +49 5251 60-5250
- Web:
- Homepage
- Büroanschrift:
-
Pohlweg 51
33098 Paderborn - Raum:
- O3.207
- Sprechstunden:
by appointment
Publikationen
Aktuelle Publikationen
Empirical QoR Estimation Flow for Fast Design Space Exploration of DNN Dataflow Accelerators
F. Jentzsch, M. Platzner, in: 2025 International Conference on Field Programmable Technology (ICFPT), IEEE, 2026.
A Two-Stage Approximation Methodology for Efficient DNN Hardware Implementation
A.H. Hadipour, A. Jafari, M. Awais, M. Platzner, in: 2025 IEEE 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS), IEEE, 2025.
Post-configuration Activation of Hardware Trojans in FPGAs
Q.A. Ahmed, T. Wiersema, M. Platzner, Journal of Hardware and Systems Security (2024).
DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing
M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: To Apear in IEEE ISVLSI 2024, 2024.
FINN-T: Compiling Custom Dataflow Accelerators for Quantized Transformers
C. Berganski, F. Jentzsch, M. Platzner, M. Kuhmichel, H. Giefers, in: 2024.
Alle Publikationen anzeigen
Lehre
Laufende Lehrveranstaltungen
- Embedded Machine Learning(in English)
- Eingebettete Systeme
- Approximate Computing(in English)