Jung Hoo Kook
Papers
1
Total Citations
7
H-Index
1
About
Jung Hoo Kook is a researcher advancing precision agriculture through deep learning and robotic vision. His primary focus lies in developing intelligent systems for automated fruit harvesting, with a particular emphasis on strawberry picking. Kook’s major contribution is the integration of instance segmentation and monocular depth estimation to accurately localize picking points on delicate crops. His most cited work, “Peduncle Detection of Ripe Strawberry to Localize Picking Point Using DF-Mask R-CNN and Monocular Depth” (2025, 7 citations), tackles the critical challenge of enabling robots to grasp and cut strawberry peduncles without bruising the fruit—a task requiring both precise detection and depth perception. This research directly addresses the fragility of strawberries, where traditional harvesting methods often cause damage. By combining DF-Mask R-CNN with depth sensing, Kook’s approach provides a robust solution for real-world agricultural robotics. Though early in his citation impact, his work represents a meaningful step toward reducing labor costs and improving harvest efficiency. Kook’s research is particularly relevant for students and engineers interested in the intersection of computer vision, robotics, and sustainable farming.
Research Focus
Key Achievements
Top Papers
- 1