Yue Linn Chong — accepted AI-conference papers

2025

Zero-Shot Semantic Segmentation for Robots in Agriculture

Yue Linn Chong, Lucas Nunes, Federico Magistri, Xingguang Zhong, Jens Behley, Cyrill Stachniss

IROS 2025

Conventional crop production, which is essential for providing food, feed, fuel, and fiber for our society, relies heavily on harmful herbicides to control weeds. Instead, agricultural robots could remove weeds more sustainably. However, these robots require a generalizable perception system that ca

Cited by 3 Source ↗Scholar ↗

2023

Unsupervised Generation of Labeled Training Images for Crop-Weed Segmentation in New Fields and on Different Robotic Platforms

Yue Linn Chong, Jan Weyler, Philipp Lottes, Jens Behley, Cyrill Stachniss

RA-L 2023

Agricultural robots have the potential to improve the efficiency and sustainability of existing agricultural practices. Most autonomous agricultural robots rely on machine vision systems. Such systems, however, often perform worse in new fields or when the robotic platforms change. While we can alle

Cited by 8 Source ↗Scholar ↗