Tengfei Zhang
Papers
2
Total Citations
56
H-Index
2
About
Tengfei Zhang is a leading researcher in agricultural robotics and intelligent field management, with a focus on computer vision and precision control systems for transplanting operations. His work addresses critical challenges in automating the detection and tracking processes essential for efficient crop cultivation. Zhang’s major contributions include the development of Seedling-YOLO, a high-efficiency target detection algorithm based on YOLOv7-Tiny, which significantly improves the accuracy of identifying broccoli seedling planting quality—a task where existing algorithms often suffer from false or missed detections. This work has garnered 40 citations, underscoring its impact on advancing robotic field management. Additionally, Zhang pioneered an ultrasonic ridge-tracking method that integrates a limiter sliding window filter and fuzzy pure pursuit control, enabling ridge transplanters to navigate precisely along planting ridges. This innovation, cited 16 times, addresses a practical need for fruits and vegetables requiring specific row and seedling spacing. Through these achievements, Zhang has demonstrated a commitment to enhancing agricultural productivity and automation, making his research highly relevant for students and researchers exploring smart farming technologies.
Research Focus
Key Achievements
Top Papers
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