Mingdeng Shi
Papers
1
Total Citations
1
H-Index
1
About
Mingdeng Shi is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent fruit detection and harvesting systems. His most impactful work centers on developing deep learning-based object detection models, particularly YOLO variants, to overcome the challenges of fruit recognition in complex, natural orchard environments. Shi’s major contribution is the application of YOLO v8 for accurate apple estimation and recognition under difficult conditions like shading, occlusion, and variable lighting—a critical step toward fully autonomous fruit-picking robots. This work, published in 2025, has already garnered 1 citation, signaling early influence in the field. Beyond apples, his research aims to create adaptable solutions that can be extended to other fruits, addressing a key bottleneck in agricultural automation. Shi’s contributions are notable for bridging the gap between state-of-the-art computer vision and practical, real-world agricultural needs, making him a rising figure in precision agriculture and robotic harvesting.
Research Focus
Key Achievements
Top Papers
- 1Apple estimation and recognition in complex scenes using YOLO v81 citations · 2025