Papers
2
Total Citations
31
H-Index
2
About
Zhiwen Mi is a researcher advancing the frontiers of agricultural robotics and intelligent harvesting systems, with a primary focus on deep learning applications for viticulture. His work centers on two critical challenges in precision agriculture: the accurate segmentation of grape bunches in field conditions and the precise detection and localization of picking points for wine grapes. Mi’s major contributions include the development of an improved Pyramid Scene Parsing Network (PSPNet) for segmenting field grape bunches, a method that enhances the ability of picking robots to identify and target fruit in complex vineyard environments. This work has garnered 25 citations, reflecting its significance in guiding robotic harvesting. More recently, he has pioneered a dual-stage deep learning approach for detecting and locating picking points specifically for Cabernet Sauvignon grapes, achieving 6 citations since 2025. By integrating advanced computer vision with agricultural machinery, Mi is helping to drive the mechanization and intelligence of grape harvesting, addressing the growing demand for efficient, automated solutions as wine grape cultivation expands globally.
Research Focus
Key Achievements
Top Papers
- 1
- 2