Papers
6
Total Citations
40
H-Index
5
About
Jianhua Qin is a leading researcher at the intersection of agricultural robotics, biomedical engineering, and intelligent automation. His work primarily focuses on developing advanced deep learning and computer vision systems for practical applications, including precision agriculture, medical robotics, and environmental monitoring. Qin's major contributions include the creation of YOLO-CT, an improved YOLOv8n-Pose model for detecting multi-species mature cherry tomatoes and locating picking points in complex environments (2025, 9 citations), and YOLOv7-GCM, a detection algorithm for creek waste (2024, 6 citations). In biomedical engineering, he pioneered novel methods for back and facial acupoint location using prior information and deep learning (2023, 9 and 5 citations respectively), addressing the challenge of intelligent acupoint selection for acupuncture robots. His work on the stable balance adjustment structure of quadruped robots based on bionic lateral swing posture (2020, 8 citations) demonstrates his expertise in robotics stability. Qin also developed GSC-YOLO, a lightweight network for cup and piston head detection (2023, 3 citations). His research has accumulated significant citations, reflecting its impact on advancing intelligent systems in agriculture, healthcare, and robotics.
Research Focus
Key Achievements
Top Papers
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- 5Facial acupoint location method based on Faster PFLD5 citations · 2023
- 6GSC-YOLO: a lightweight network for cup and piston head detection3 citations · 2023