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2020 – today
- 2024
[c6]Marc Rothmann, Mario Porrmann:
FPGA-based Acceleration of Deep Q-Networks with STANN-RL. FMEC 2024: 99-106- [c5]Yufei Mao, Roland Weiss, Yi Zhang, Yu Li, Marc Rothmann, Mario Porrmann:
FPGA Acceleration of DL-Based Real-Time DC Series Arc Fault Detection. IPDPS (Workshops) 2024: 92-98 - 2023
- [c4]Marc Rothmann, Mario Porrmann:
STANN - Synthesis Templates for Artificial Neural Network Inference and Training. IWANN (1) 2023: 394-405 - 2022
- [j3]Marc Rothmann
, Mario Porrmann:
A Survey of Domain-Specific Architectures for Reinforcement Learning. IEEE Access 10: 13753-13767 (2022) - [j2]Marc Eisoldt, Marcel Flottmann, Julian Gaal, Steffen Hinderink, Juri Vana, Marco Tassemeier, Marc Rothmann, Thomas Wiemann, Mario Porrmann:
ReconfROS: An approach for accelerating ROS nodes on reconfigurable SoCs. Microprocess. Microsystems 94: 104655 (2022) - [j1]Marc Eisoldt, Julian Gaal, Thomas Wiemann, Marcel Flottmann, Marc Rothmann, Marco Tassemeier, Mario Porrmann:
A fully integrated system for hardware-accelerated TSDF SLAM with LiDAR sensors (HATSDF SLAM). Robotics Auton. Syst. 156: 104205 (2022) - [c3]Marc Rothmann, Mario Porrmann:
FAQ: A Flexible Accelerator for Q-Learning with Configurable Environment. ASAP 2022: 106-114 - 2021
- [c2]Marcel Flottmann, Marc Eisoldt, Julian Gaal, Marc Rothmann, Marco Tassemeier, Thomas Wiemann, Mario Porrmann:
Energy-efficient FPGA-accelerated LiDAR-based SLAM for embedded robotics. FPT 2021: 1-6 - [c1]Marc Eisoldt, Steffen Hinderink, Marco Tassemeier, Marcel Flottmann, Juri Vana, Thomas Wiemann, Julian Gaal, Marc Rothmann, Mario Porrmann:
ReconfROS: Running ROS on Reconfigurable SoCs. DroneSE/RAPIDO@HiPEAC 2021: 16-21
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