Luigi Manfrini
Papers
6
Total Citations
187
H-Index
3
About
Luigi Manfrini is a leading researcher at the intersection of precision horticulture and agricultural robotics, whose work is fundamentally reshaping how we monitor and manage fruit crops. His primary research areas span computer vision for agriculture, deep learning applications in horticulture, and the development of low-cost sensing platforms for precision farming. Manfrini’s most impactful contribution is his seminal 2019 paper on “Single-Shot Convolution Neural Networks for Real-Time Fruit Detection Within the Tree,” which has garnered 165 citations. This work revolutionized the field by demonstrating that deep learning models could achieve real-time, accurate fruit detection—a task previously limited by computationally intensive, slow algorithms—paving the way for practical robotic harvesting and yield estimation. He has also made notable contributions to understanding fruit growth physiology and developing accessible technologies, such as a consumer-grade thermal scanning platform for sunburn detection and a lightweight method for canopy porosity estimation to enable variable-rate spraying. By bridging the gap between advanced computational methods and practical, affordable agricultural tools, Manfrini’s research is instrumental in moving toward fully automated, data-driven orchard management.
Research Focus
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Top Papers
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