GateNet: An Efficient Deep Neural Network Architecture for Gate Perception Using Fish-Eye Camera in Autonomous Drone Racing

Authors: Huy Xuan Pham, Ilker Bozcan, Andriy Sarabakha, Sami Haddadin, Erdal Kayacan

Published in: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021, Prague, Czech Republic, September 27 - Oct. 1, 2021

DOI: 10.1109/IROS51168.2021.9636207

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If you want to cite this work, you can use the following BibTeX file:

@inproceedings{DBLP:conf/iros/PhamBSHK21,
  author       = {Huy Xuan Pham and
                  Ilker Bozcan and
                  Andriy Sarabakha and
                  Sami Haddadin and
                  Erdal Kayacan},
  title        = {GateNet: An Efficient Deep Neural Network Architecture for Gate Perception
                  Using Fish-Eye Camera in Autonomous Drone Racing},
  booktitle    = {{IEEE/RSJ} International Conference on Intelligent Robots and Systems,
                  {IROS} 2021, Prague, Czech Republic, September 27 - Oct. 1, 2021},
  pages        = {4176--4183},
  publisher    = {{IEEE}},
  year         = {2021},
  url          = {https://doi.org/10.1109/IROS51168.2021.9636207},
  doi          = {10.1109/IROS51168.2021.9636207},
  timestamp    = {Sat, 06 Sep 2025 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/iros/PhamBSHK21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}