OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics (bibtex)

by Nikolaos Passalis, Stefania Pedrazzi, Robert Babuška, Wolfram Burgard, Daniel Dias, Francesco Ferro, Moncef Gabbouj, Green Ole, Alexandros Iosifidis, Erdal Kayacan, Jens Kober, Olivier Michel, Nikolaos Nikolaidis, Paraskevi Nousi, Roel S. Pieters, Maria Tzelepi, Abhinav Valada, and Anastasios Tefas

Reference:

Nikolaos Passalis, Stefania Pedrazzi, Robert Babuška, Wolfram Burgard, Daniel Dias, Francesco Ferro, Moncef Gabbouj, Green Ole, Alexandros Iosifidis, Erdal Kayacan, Jens Kober, Olivier Michel, Nikolaos Nikolaidis, Paraskevi Nousi, Roel S. Pieters, Maria Tzelepi, Abhinav Valada, and Anastasios Tefas. OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 12479–12484, 2022.

Bibtex Entry:

@InProceedings{Passalis2022IROS,
  author    = {Passalis, Nikolaos AND Pedrazzi, Stefania AND Babu\v{s}ka, Robert AND Burgard, Wolfram AND Dias, Daniel AND Ferro, Francesco AND Gabbouj, Moncef AND Ole, Green AND Iosifidis, Alexandros AND Kayacan, Erdal AND Kober, Jens AND Michel, Olivier AND Nikolaidis, Nikolaos AND Nousi, Paraskevi AND Pieters, Roel S. AND Tzelepi, Maria AND Valada, Abhinav AND Tefas, Anastasios},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  title     = {{OpenDR}: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics},
  year      = {2022},
  pages     = {12479--12484},
  doi       = {10.1109/IROS47612.2022.9981703},
  file      = {https://arxiv.org/pdf/2203.00403.pdf},
  project   = {OpenDR},
  oa        = {green},
}