Angelo Cardellicchio
Papers
2
Total Citations
6
H-Index
1
About
Angelo Cardellicchio is a leading researcher at the intersection of computer vision and precision agriculture, with a core focus on developing robust, AI-driven solutions for modern farming challenges. His primary research areas include deep learning-based object detection for agricultural robotics, particularly in unstructured and visually complex environments. Cardellicchio’s most impactful contribution is his work on fruit detection in challenging field conditions, as demonstrated by his highly cited 2023 paper on tomato detection using YOLO-based single-stage detectors. This research directly addresses critical bottlenecks in robotic harvesting and yield estimation by overcoming issues like occlusion, variable lighting, and shading, achieving 5 citations and establishing a practical benchmark for the field. He has also shaped the broader discourse on sustainable agricultural innovation, co-editing a 2025 special issue on Agriculture 4.0 approaches to climate change. Through his work, Cardellicchio has advanced the deployment of computer vision in real-world agri-robotics, providing foundational tools that enable more reliable and autonomous farming systems in the age of climate adaptation.
Research Focus
Key Achievements
Top Papers
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