Youcheng Hu

Papers

Total Citations

H-Index

About

Youcheng Hu’s research focuses on agricultural robotics and computer vision, specifically addressing the challenges of automated fruit harvesting in natural environments. His major contributions lie in developing algorithms to detect, segment, and recognize overlapping citrus fruits and occluding foliage—critical tasks for enabling harvesting robots to operate accurately in unstructured orchard settings. His most cited work, “Overlapped fruit recognition for citrus harvesting robot in natural scenes” (2017, 16 citations), introduces a convex hull-based method for localizing and reconstructing partially hidden fruits, directly tackling the visual complexity that hinders autonomous picking. In a related study (2018), he proposed a region-based segmentation approach to distinguish mature citrus from branches and leaves, further refining robotic perception. Though his citation counts are modest, these papers represent foundational steps toward practical, vision-guided harvesting systems. Hu’s work is notable for its applied focus on real-world occlusion and overlap problems, offering incremental but essential solutions that advance the precision and reliability of agricultural robots. His research is particularly relevant for students and engineers developing field-deployable computer vision systems in agriculture.