68 citations · 76 across the 4 of their papers we have counts for
4 papers
Unsupervised Pre-Training for 3D Leaf Instance Segmentation
Gianmarco Roggiolani, Federico Magistri, Tiziano Guadagnino +2
Crops for food, feed, fiber, and fuel are key natural resources for our society. Monitoring plants and measuring their traits is an important task in agriculture often referred to…
PhenoBench -- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain
Jan Weyler, Federico Magistri, Elias Marks +6
The production of food, feed, fiber, and fuel is a key task of agriculture, which has to cope with many challenges in the upcoming decades, e.g., a higher demand, climate change, l…
On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics
Gianmarco Roggiolani, Federico Magistri, Tiziano Guadagnino +4
Agricultural robots have the prospect to enable more efficient and sustainable agricultural production of food, feed, and fiber. Perception of crops and weeds is a central componen…
Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in the Agricultural Domain
Gianmarco Roggiolani, Matteo Sodano, Tiziano Guadagnino +3
Plant phenotyping is a central task in agriculture, as it describes plants' growth stage, development, and other relevant quantities. Robots can help automate this process by accur…