Hello, I’m Yuhan Zheng
I am a master’s student in Artificial Intelligence at Fujian Agriculture and Forestry University. My current interests lie at the intersection of computer vision, agricultural intelligence, and robotics.
My research focuses on visual segmentation and the detection and segmentation of plant leaf diseases. I am particularly interested in developing reliable methods that can work beyond controlled datasets and remain effective in complex, real-world agricultural environments.
Research Interests
- Computer vision and image segmentation
- Plant disease detection and segmentation
- Agricultural artificial intelligence
- Robust and generalizable visual recognition
- Lightweight models and practical deployment
- Robotics and ROS2 applications
What I Write About
This blog is a record of my learning, research, and engineering practice. Here you will find notes on computer vision, agricultural AI, ROS2, robotics projects, and selected topics in software and cybersecurity.
I use this space to document experiments, explain technical ideas in my own words, reflect on failures, and turn fragmented learning into reproducible knowledge.
Research Philosophy
I believe meaningful agricultural AI should address real problems rather than simply transfer existing models to a new crop. Good research requires reliable data, careful annotation, reproducible experiments, strong baselines, honest failure analysis, and validation under realistic conditions.
My long-term goal is to build intelligent vision systems that are not only accurate in the laboratory, but also useful, efficient, and trustworthy in real agricultural scenarios.
Current Focus
I am currently exploring plant leaf disease analysis, with a particular interest in grape leaf diseases. My work is expected to investigate dataset quality, segmentation performance, robustness, generalization, and deployment efficiency.
Contact
- Email: 52562047013@fafu.edu.cn
- GitHub: S1mp11e
I am always open to thoughtful discussions about computer vision, agricultural AI, robotics, and reproducible research.
