Jan Pieters
Papers
5
Total Citations
74
H-Index
3
About
Jan Pieters is a researcher at the forefront of precision agriculture, with expertise spanning agricultural robotics, computer vision, deep learning, and soil sensing technologies. His work focuses on developing intelligent systems that enable smarter, more sustainable farming practices by minimizing inputs while maximizing crop yield and environmental outcomes. Pieters is perhaps best known for his contributions to weed and crop segmentation using deep learning and UAV imagery. His 2023 paper on cross-domain transfer learning for weed segmentation and mapping has garnered 57 citations, establishing him as a significant voice in applying computer vision to precision farming challenges. This line of research, extended in a 2022 study on transferring ground-based imagery patterns to UAV platforms, demonstrates his commitment to bridging practical field conditions with cutting-edge AI methods. Beyond imaging, Pieters has made notable strides in agricultural robotics, including robotic intrarow weeding guided by 3D cauliflower tracking, autonomous soil compaction sensing, and a task-map operation framework that coordinates robotic field interventions. Together, these contributions reflect a cohesive research vision: equipping modern farms with autonomous, data-driven tools capable of operating precisely and efficiently across diverse agricultural environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Development of an Agricultural Robot Taskmap Operation Framework3 citations · 2025