Jean-Michel Fortin

Jean-Michel Fortin

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jean-michel.fortin@norlab.ulaval.ca

Expertise: Computer vision, Deep learning, Terrain traversability

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Jean-Michel Fortin is a Ph.D. student at Norlab under the supervision of Prof. Philippe Giguère.

He holds a bachelor’s degree in Electrical Engineering and a master’s degree in Computer Science from Université Laval. His master’s research focused on the automation of forestry operations, specifically on the detection and localization of logs for automated collection, in collaboration with FPInnovations.

At the Ph.D. level, his interests lie in the use of self-supervised learning methods for terrain traversability prediction. His work has demonstrated the benefits of using a drone equipped with a downward-facing camera as an additional sensor for ground vehicles.

Education

  • M.Sc. in Computer Science, Université Laval (fast-track to Ph.D.), 2023
  • B.Eng. in Electrical Engineering, Université Laval, 2020

Implication

  • Treasurer of the Université Laval Computer Science Graduate Students’ Association AGIL 2024–2025
  • President of the student project VAUL (Université Laval Autonomous Vehicle) 2022–2024
  • Competed at Roboracer in London (ICRA 2023), Detroit (IROS 2023), and Yokohama (ICRA 2024)

Publications

Journal Articles

  1. Grondin, V., Fortin, J.-M., Pomerleau, F., & Giguère, P. (2022). Tree Detection and Diameter Estimation Based on Deep Learning. Forestry: An International Journal of Forest Research, 96(2), 264–276. https://doi.org/10.1093/forestry/cpac043
     Publisher    Bibtex source

Conference Articles

  1. Gamache, O., Fortin, J.-M., Boxan, M., Vaidis, M., Pomerleau, F., & Giguère, P. (2024). Exposing the Unseen: Exposure Time Emulation for Offline Benchmarking of Vision Algorithms. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 11110–11117. https://doi.org/10.1109/IROS58592.2024.10803057
     Publisher    Bibtex source
  2. Guimont-Martin, W., Fortin, J.-M., Pomerleau, F., & Giguère, P. (2023). MaskBEV: Joint Object Detection and Footprint Completion for Bird’s-eye View 3D Point Clouds. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS). Accepted for oral presentation
     Bibtex source
  3. Fortin, J.-M., Gamache, O., Grondin, V., Pomerleau, F., & Giguère, P. (2022). Instance Segmentation for Autonomous Log Grasping in Forestry Operations. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 6064–6071. https://doi.org/10.1109/IROS47612.2022.9982286. Finalist for Best Paper Award on Agri-Robotics! Accepted for oral presentation, arXiv preprint arXiv:2203.01902
     Publisher    Bibtex source

Miscellaneous

  1. Gamache, O., Fortin, J.-M., Boxan, M., Pomerleau, F., & Giguère, P. (2024). Field Report on a Wearable and Versatile Solution for Field Acquisition and Exploration. In presented to the 2024 Workshop on Field Robotics from IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.48550/arXiv.2405.00199
     Publisher    Bibtex source
  2. Guimont-Martin, W., Fortin, J.-M., Pomerleau, F., & Giguère, P. (2023). MaskBEV: Joint Object Detection and Footprint Completion for Bird’s-eye View 3D Point Clouds. Colloque REPARTI, Université Laval.
     Bibtex source