Short CV

Jan Weyler is a PhD student at the Photogrammetry Lab at the University of Bonn since February 2019. He received his master’s degree at the Institute of Geodesy and Geoinformation in 2019. Before starting his Ph.D., he was working as a student assistant for the EU funded project FLOURISH at the Institute of Photogrammetry.

Research Interests

• Machine Learning
• Computer Vision
• Agricultural Robotics

Publications

2023

• F. Magistri, J. Weyler, D. Gogoll, P. Lottes, J. Behley, N. Petrinic, and C. Stachniss, “From one field to another – unsupervised domain adaptation for semantic segmentation in agricultural robotics,” Computers and electronics in agriculture, vol. 212, p. 108114, 2023. doi:https://doi.org/10.1016/j.compag.2023.108114
  [BibTeX] [PDF]

  @article{magistri2023cea,
  author = {F. Magistri and J. Weyler and D. Gogoll and P. Lottes and J. Behley and N. Petrinic and C. Stachniss},
  title = {From one Field to Another – Unsupervised Domain Adaptation for Semantic Segmentation in Agricultural Robotics},
  journal = cea,
  year = {2023},
  volume = {212},
  pages = {108114},
  doi = {https://doi.org/10.1016/j.compag.2023.108114},
  }

• Y. L. Chong, J. Weyler, P. Lottes, J. Behley, and C. Stachniss, “Unsupervised Generation of Labeled Training Images for Crop-Weed Segmentation in New Fields and on Different Robotic Platforms,” IEEE Robotics and Automation Letters (RA-L), vol. 8, iss. 8, p. 5259–5266, 2023. doi:10.1109/LRA.2023.3293356
  [BibTeX] [PDF] [Code]

  @article{chong2023ral,
  author = {Y.L. Chong and J. Weyler and P. Lottes and J. Behley and C. Stachniss},
  title = {{Unsupervised Generation of Labeled Training Images for Crop-Weed Segmentation in New Fields and on Different Robotic Platforms}},
  journal = ral,
  volume = {8},
  number = {8},
  pages = {5259--5266},
  year = 2023,
  issn = {2377-3766},
  doi = {10.1109/LRA.2023.3293356},
  note = {accepted},
  codeurl = {https://github.com/PRBonn/StyleGenForLabels}
  }

• J. Weyler, F. Magistri, E. Marks, Y. L. Chong, M. Sodano, G. Roggiolani, N. Chebrolu, C. Stachniss, and J. Behley, “PhenoBench –- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain,” Arxiv preprint, vol. arXiv:2306.04557, 2023.
  [BibTeX] [PDF] [Code]

  @article{weyler2023arxiv,
  author = {Jan Weyler and Federico Magistri and Elias Marks and Yue Linn Chong and Matteo Sodano
  and Gianmarco Roggiolani and Nived Chebrolu and Cyrill Stachniss and Jens Behley},
  title = {{PhenoBench --- A Large Dataset and Benchmarks for Semantic Image Interpretation
  in the Agricultural Domain}},
  journal = {arXiv preprint},
  volume = {arXiv:2306.04557},
  year = {2023},
  codeurl = {https://github.com/PRBonn/phenobench}
  }

• J. Weyler, T. Läbe, F. Magistri, J. Behley, and C. Stachniss, “Towards Domain Generalization in Crop and Weed Segmentation for Precision Farming Robots,” IEEE Robotics and Automation Letters (RA-L), vol. 8, iss. 6, pp. 3310-3317, 2023. doi:10.1109/LRA.2023.3262417
  [BibTeX] [PDF]

  @article{weyler2023ral,
  author = {J. Weyler and T. L\"abe and F. Magistri and J. Behley and C. Stachniss},
  title = {{Towards Domain Generalization in Crop and Weed Segmentation for Precision Farming Robots}},
  journal = ral,
  pages = {3310-3317},
  volume = 8,
  number = 6,
  issn = {2377-3766},
  year = {2023},
  doi = {10.1109/LRA.2023.3262417}
  }

• G. Roggiolani, F. Magistri, T. Guadagnino, J. Weyler, G. Grisetti, C. Stachniss, and J. Behley, “On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics,” in Proc. of the ieee intl. conf. on robotics & automation (icra), 2023.
  [BibTeX] [PDF] [Code] [Video]

  @inproceedings{roggiolani2023icra-odsp,
  author = {G. Roggiolani and F. Magistri and T. Guadagnino and J. Weyler and G. Grisetti and C. Stachniss and J. Behley},
  title = {{On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics}},
  booktitle = icra,
  year = 2023,
  codeurl= {https://github.com/PRBonn/agri-pretraining},
  videourl = {https://youtu.be/FDWY_UnfsBs}
  }

2022

• J. Weyler, J. Quakernack, P. Lottes, J. Behley, and C. Stachniss, “Joint Plant and Leaf Instance Segmentation on Field-Scale UAV Imagery,” IEEE Robotics and Automation Letters (RA-L), vol. 7, iss. 2, pp. 3787-3794, 2022. doi:10.1109/LRA.2022.3147462
  [BibTeX] [PDF]

  @article{weyler2022ral,
  author = {J. Weyler and J. Quakernack and P. Lottes and J. Behley and C. Stachniss},
  title = {{Joint Plant and Leaf Instance Segmentation on Field-Scale UAV Imagery}},
  journal = ral,
  year = 2022,
  doi = {10.1109/LRA.2022.3147462},
  issn = {377-3766},
  volume = {7},
  number = {2},
  pages = {3787-3794},
  }

• J. Weyler, F. Magistri, P. Seitz, J. Behley, and C. Stachniss, “In-Field Phenotyping Based on Crop Leaf and Plant Instance Segmentation,” in Proc. of the winter conf. on applications of computer vision (wacv), 2022.
  [BibTeX] [PDF]

  @inproceedings{weyler2022wacv,
  author = {J. Weyler and F. Magistri and P. Seitz and J. Behley and C. Stachniss},
  title = {{In-Field Phenotyping Based on Crop Leaf and Plant Instance Segmentation}},
  booktitle = wacv,
  year = 2022,
  }

2021

• J. Weyler, A. Milioto, T. Falck, J. Behley, and C. Stachniss, “Joint Plant Instance Detection and Leaf Count Estimation for In-Field Plant Phenotyping,” IEEE Robotics and Automation Letters (RA-L), vol. 6, pp. 3599-3606, 2021. doi:10.1109/LRA.2021.3060712
  [BibTeX] [PDF] [Video]

  @article{weyler2021ral,
  author = {J. Weyler and A. Milioto and T. Falck and J. Behley and C. Stachniss},
  title = {{Joint Plant Instance Detection and Leaf Count Estimation for In-Field Plant Phenotyping}},
  journal = ral,
  volume = 6,
  issue = 2,
  pages = {3599-3606},
  doi = {10.1109/LRA.2021.3060712},
  year = 2021,
  videourl = {https://youtu.be/Is18Rey625I},
  }

2020

• D. Gogoll, P. Lottes, J. Weyler, N. Petrinic, and C. Stachniss, “Unsupervised Domain Adaptation for Transferring Plant Classification Systems to New Field Environments, Crops, and Robots,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2020.
  [BibTeX] [PDF] [Video]

  @inproceedings{gogoll2020iros,
  author = {D. Gogoll and P. Lottes and J. Weyler and N. Petrinic and C. Stachniss},
  title = {{Unsupervised Domain Adaptation for Transferring Plant Classification Systems to New Field Environments, Crops, and Robots}},
  booktitle = iros,
  year = {2020},
  url = {http://www.ipb.uni-bonn.de/pdfs/gogoll2020iros.pdf},
  videourl = {https://www.youtube.com/watch?v=6K79Ih6KXTs},
  }

Teaching

B36 – 20191/20192 – Photogrammetry

B36 – 20201/20202 – Photogrammetry

B29 – 20202/20211 – 3D Koordinatensysteme

B36 – 20211/20202 – Photogrammetry