Rui-Feng Wang (Swee-Fong Wong)
About Me
I’m currently a research assistant at University of Georgia. My current research interests include Automation, Computer Vision, Deep Learning, High-Throughput Plant Phenotyping, Precision Agriculture, and Agricultural Robots.
Research Interests
- Precision Agriculture & Agricultural Robotics: My research centers on the integration of automation and robotics into precision agriculture. I design intelligent agricultural systems capable of performing tasks such as intra-row weeding, precision spraying, and automated harvesting. I am particularly interested in developing lightweight and efficient robotic platforms that can operate reliably in unstructured field environments.
- Computer Vision & Deep Learning for Smart Farming: I focus on building high-performance computer vision models tailored to agricultural applications. My work involves optimizing CNN and Transformer-based architectures (e.g., customized YOLO variants and ViT models) for tasks such as crop/weed classification, pest detection, and growth monitoring. I aim to achieve robust performance under diverse field conditions such as variable lighting and occlusion.
- High-Throughput Plant Phenotyping (HTPP): My upcoming research explores the deployment of AI-powered phenotyping systems to extract large-scale, multi-modal plant trait data across time and space. I am particularly interested in drone and ground-platform-based imaging, multimodal sensor fusion, and deep learning-driven trait extraction for stress detection, yield estimation, and postharvest quality analysis.
- AI-Driven Control Systems in Agriculture: I also explore the use of advanced control algorithms, such as Active Disturbance Rejection Control (ADRC), to improve the real-time responsiveness and robustness of agricultural equipment. This work aims to bridge the gap between intelligent perception and autonomous action in complex agricultural environments.
Recent Publications
(* indicates equal contribution, # indicates corresponding author)
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Smart Agricultural Technology (IF : 5.7)
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Computers and Electronics in Agriculture (IF : 8.9)
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2025 ASABE Annual International Meeting
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Remote Sensing (IF : 4.1)
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Sustainability (IF : 3.3)
Preprint and In Submission
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Neural radiance field-based visual rendering: a comprehensive reviewUnder Review, 2025
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FA-YOLO: Research On Efficient Feature Selection YOLO Improved Algorithm Based On FMDS and AGMF ModulesUnder Review, 2025
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A Local Perspective-based Model for Overlapping Community DetectionAccepted by SMC 2025, 2025
Experience
- 2025.07 - now, Department of Crop and Soil Sciences (CRSS), Research Assistant, Department of Crop and Soil Sciences, College of Agriculture and Environemtal Sciences, University of Georgia, Unitied States
- 2023.11 - 2025.07, Intelligent Agricultural Product Quality Control Equipment Lab, Research Assistant, College of Engineering, China Agricultural University
- 2023.09 - 2025.07, Computer Graphic Lab, Research Assistant, College of Information and Electrical Engineering, China Agricultural University