Andres Milioto
Papers
15
Total Citations
799
H-Index
9
About
Andres Milioto is a robotics and computer vision researcher whose work sits at the compelling intersection of deep learning, autonomous systems, and precision agriculture. He is best known for pioneering machine learning approaches that enable agricultural robots to distinguish crops from weeds with high accuracy, contributing directly to the reduction of harmful agrochemical use in farming. His 2018 paper on fully convolutional networks with sequential information for crop and weed detection has garnered over 270 citations, establishing him as a leading voice in agricultural robotics. Milioto has made significant contributions to semantic and instance segmentation, plant phenotyping, stem detection, and active learning strategies that minimize costly data annotation — work collectively cited hundreds of times across the research community. His involvement in the Flourish project further showcases his systems-level thinking, integrating aerial and ground robots into cohesive precision farming platforms. Beyond agriculture, Milioto has tackled challenges in 3D point cloud compression for robotics mapping and humanoid robot navigation, demonstrating impressive breadth. With over 770 total citations, his research offers practical pathways toward sustainable, data-driven agriculture and intelligent autonomous systems, making his work essential reading for students in robotics, computer vision, and agricultural technology.
Research Focus
Key Achievements
Top Papers
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- 3Deep Compression for Dense Point Cloud Maps99 citations · 2021
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