Jinmeng Wei
Papers
1
Total Citations
45
H-Index
1
About
Jinmeng Wei is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent fruit detection and segmentation for automated harvesting systems. His most impactful work addresses the critical challenge of enabling robots to accurately recognize and segment green fruit in complex, unstructured orchard environments—a task made difficult by variable lighting, occlusions, and color similarity between fruit and foliage. Wei’s landmark 2022 study, “Accurate segmentation of green fruit based on optimized mask RCNN application in complex orchard,” has garnered 45 citations and demonstrates his expertise in deep learning architectures tailored for precision agriculture. By refining the Mask R-CNN framework to handle dynamic lighting and background clutter, he has significantly improved the robustness of vision systems for fruit-picking robots. His contributions are vital to advancing autonomous agriculture, directly impacting yield estimation and harvesting efficiency. Wei’s work is widely recognized in the agricultural robotics community, and his methodologies serve as a foundation for subsequent research in real-time, field-deployable fruit segmentation.
Research Focus
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Top Papers
- 1