Jiye Zhang
Papers
1
Total Citations
71
H-Index
1
About
Jiye Zhang is a leading researcher at the intersection of agricultural robotics and edge artificial intelligence, with a primary focus on developing intelligent perception systems for field robots. His most impactful work centers on semantic segmentation using convolutional neural networks (CNNs) deployed on edge intelligence devices, enabling real-time navigation line extraction for agricultural robots. This foundational study, cited 71 times, demonstrates how lightweight deep learning models can operate efficiently on resource-constrained hardware, bridging the gap between advanced computer vision and practical field automation. Zhang’s contributions are critical for precision agriculture, allowing robots to autonomously navigate complex crop rows without relying on cloud computing. His research addresses key challenges in real-time environment understanding, sensor fusion, and model optimization for embedded systems. By combining robotics, deep learning, and edge computing, Zhang has advanced the feasibility of low-latency, on-device decision-making in unstructured agricultural environments. His work is widely referenced by engineers and scientists developing autonomous farming equipment, and it underscores his role in shaping the next generation of intelligent, self-navigating agricultural machinery.
Research Focus
Key Achievements
Top Papers
- 1