68 citations · 68 across the 2 of their papers we have counts for
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cs.CV2023★ 68 cited
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…
cs.CV2023
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…