Riccardo Bertoglio

Politecnico di Milano

Papers

7

Total Citations

56

H-Index

5

About

Riccardo Bertoglio is a researcher at the forefront of precision agriculture and agricultural robotics, specializing in computer vision, autonomous navigation, and non-destructive sensing for crop management. His work addresses critical challenges in sustainable farming, from weed identification to fruit ripeness estimation. Bertoglio’s most cited paper (21 citations) presents a comparative study of Fourier transform and CycleGAN as domain adaptation techniques for weed segmentation, a key enabler for targeted herbicide spraying that reduces environmental impact. He has also developed a map-free LiDAR-based system for autonomous navigation in vineyards (7 citations), advancing the feasibility of field robots without GPS reliance. In hyperspectral imaging, Bertoglio pioneered an on-the-go method for table grape ripeness estimation (11 citations), offering a high-throughput, non-destructive alternative to lab analyses. His contributions extend to robust visual perception under domain shifts, with a surgical fine-tuning approach for grape bunch segmentation (5 citations). Bertoglio co-designed the Agri-Food Competition for Robot Evaluation (ACRE) and created the VINEPICs dataset, supporting open research in agricultural automation. With over 50 cumulative citations, his work is shaping the next generation of intelligent, environmentally conscious farming systems.

Research Focus

Key Achievements

5
H-Index
7
Papers
56
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
A comparative study of Fourier transform and CycleGAN as domain adaptation techniques for weed segmentation
21 citations · 2023
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Politecnico di Milano

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago