Auflistung: nach Autor Porrmann, Mario

1 bis 16 von 16 Treffer
ErscheinungsdatumTitelAutor(en)
2022A fully integrated system for hardware-accelerated TSDF SLAM with LiDAR sensors (HATSDF SLAM)Eisoldt, Marc; Gaal, Julian; Wiemann, Thomas ; Flottmann, Marcel; Rothmann, Marc; Tassemeier, Marco; Porrmann, Mario 
2023A scalable, heterogeneous hardware platform for accelerated aiot based on microserversGriessl, R.; Porrmann, F.; Kucza, N.; Mika, K.; Hagemeyer, J.; Kaiser, M.; Porrmann, M. ; Tassemeier, M.; Flottmann, M.; Qararyah, F.; Waqar, M.; Trancoso, P.; Ödman, D.; Gugala, K.; Latosinski, G.
2022A Survey of Domain-Specific Architectures for Reinforcement LearningRothmann, Marc; Porrmann, Mario 
2020Asynchronous network-on-chips (NoCs) for resource efficient many core architecturesAx, J.; Kucza, N.; Porrmann, M. ; Rueckert, U.; Jungeblut, T.
2021Energy-efficient FPGA-accelerated LiDAR-based SLAM for embedded roboticsFlottmann, Marcel; Eisoldt, Marc; Gaal, Julian; Rothmann, Marc; Tassemeier, Marco; Wiemann, Thomas ; Porrmann, Mario 
2023Evaluation of heterogeneous AIoT Accelerators within VEDLIoTGriessl, R.; Porrmann, F.; Kucza, N.; Mika, K.; Hagemeyer, J.; Kaiser, M.; Porrmann, M. ; Tassemeier, M.; Flottmann, M.; Qararyah, F.; Waqar, M.; Trancoso, P.; Ödman, D.; Gugala, K.; Latosinski, G.
2022FAQ: A Flexible Accelerator for Q-Learning with Configurable EnvironmentRothmann, M.; Porrmann, M. 
2021HATSDF SLAM - Hardware-accelerated tsdf slam for reconfigurable socsEisoldt, M.; Flottmann, M.; Gaal, J.; Buschermohle, P.; Hinderink, S.; Hillmann, M.; Nitschmann, A.; Hoffmann, P.; Wiemann, T. ; Porrmann, M. 
2023Machine Learning for the Control and Monitoring of Electric Machine Drives: Advances and TrendsZhang, Shen; Wallscheid, Oliver; Porrmann, Mario 
2022ReconfROS: An approach for accelerating ROS nodes on reconfigurable SoCsEisoldt, Marc; Flottmann, Marcel; Gaal, Julian; Hinderink, Steffen; Vana, Juri; Tassemeier, Marco; Rothmann, Marc; Wiemann, Thomas ; Porrmann, Mario 
2021ReconfROS: Running ROS on reconfigurable SoCsEisoldt, M.; Hinderink, S.; Tassemeier, M.; Flottmann, M.; Vana, J.; Wiemann, T. ; Gaal, J.; Rothmann, M.; Porrmann, M. 
2023ReDroSe - Reconfigurable Drone Setup for Resource-Efficient SLAMRahn, Sebastian; Gehricke, Philipp; Petermöller, Can-Leon; Neumann, Eric; Schlinge, Philipp; Rabius, Leon; Termühlen, Henning; Sieh, Christopher; Tassemeier, Marco; Wiemann, Thomas ; Porrmann, Mario 
2020Resource-efficient bio-inspired visual processing on the hexapod walking robot HECTORMeyer, Hanno Gerd; Klimeck, Daniel; Paskarbeit, Jan; Rueckert, Ulrich; Egelhaaf, Martin; Porrmann, Mario ; Schneider, Axel
2023STANN – Synthesis Templates forArtificial Neural Network Inference andTrainingRothmann, Marc; Porrmann, Mario 
2023VEDLIoT: Next generation accelerated AIoT systems and applicationsMika, Kevin; Griessl, René; Kucza, Nils; Porrmann, Florian; Kaiser, Martin; Tigges, Lennart; Hagemeyer, Jens; Trancoso, Pedro; Azhar, Muhammad Waqar; Qararyah, Fareed; Zouzoula, Stavroula; Ménétrey, Jämes; Pasin, Marcelo; Felber, Pascal; Marcus, Carina; Brunnegard, Oliver; Eriksson, Olof; Salomonsson, Hans; Ödman, Daniel; Ask, Andreas; Casimiro, Antonio; Bessani, Alysson; Carvalho, Tiago; Gugala, Karol; Zierhoffer, Piotr; Latosinski, Grzegorz; Tassemeier, Marco; Porrmann, Mario ; Heyn, Hans-Martin; Knauss, Eric; Mao, Yufei; Meierhöfer, Franz
2022VEDLIoT: Very Efficient Deep Learning in IoTKaiser, M.; Griessl, R.; Kucza, N.; Haumann, C.; Tigges, L.; Mika, K.; Hagemeyer, J.; Porrmann, F.; Ruckert, U.; Vor Dem Berge, M.; Krupop, S.; Porrmann, M. ; Tassemeier, M.; Trancoso, P.; Qararyah, F.; Zouzoula, S.; Casimiro, A.; Bessani, A.; Cecilio, J.; Andersson, S.; Brunnegard, O.; Eriksson, O.; Weiss, R.; McIerhofer, F.; Salomonsson, H.; Malekzadeh, E.; Odman, D.; Khurshid, A.; Felber, P.; Pasin, M.; Schiavoni, V.; Menetrey, J.; Gugala, K.; Zierhoffer, P.; Knauss, E.; Heyn, H.