Milan van Bree
Papers
1
Total Citations
4
H-Index
1
About
Milan van Bree is a researcher at the forefront of agricultural robotics, with a primary focus on developing automated solutions for crop harvesting. His work addresses a critical bottleneck in the field: robust fruit detection. Van Bree’s research centers on improving the reliability of computer vision systems for identifying and localizing produce in complex, unstructured environments like greenhouses. His most cited paper, "Robotic data acquisition of sweet pepper images for research and development" (2016, 4 citations), tackles this challenge head-on by providing a systematic method for collecting high-quality image datasets. This contribution is vital for training and benchmarking detection algorithms, as van Bree highlights that current fruit detection rates (around 0.87) remain economically unfeasible for commercial harvesting. By establishing a standardized data acquisition protocol, his work lays the groundwork for advancing detection accuracy—a key step toward making robotic harvesters a practical reality. Van Bree’s research is essential reading for anyone interested in the intersection of robotics, computer vision, and precision agriculture.
Research Focus
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Top Papers
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