Joonwhoan Lee
Papers
3
Total Citations
219
H-Index
3
About
Dr. Joonwhoan Lee is a leading researcher in precision agriculture and computer vision, whose work is revolutionizing autonomous weed management and crop disease detection. His primary research areas encompass deep learning-based semantic segmentation, plant pathology detection, and transformer architectures for agricultural robotics. Dr. Lee's most impactful contribution is his pioneering work on weed/crop segmentation, where his 2020 paper on a DNN-based semantic segmentation network has garnered 126 citations, establishing a foundational approach for deploying autonomous robots in environment-friendly weed removal. He further advanced the field with a transformer-based weed segmentation method (2022, 42 citations) that improves grass management by addressing the critical challenge of weeds competing for nutrients and water. In plant health monitoring, Dr. Lee developed an improved vision-based system for detecting strawberry diseases using deep neural networks (2021, 51 citations), enabling early-stage intervention that is crucial for preserving crop quality and farm productivity. His work directly addresses global agricultural challenges by reducing reliance on chemical herbicides and manual labor, making him a key figure in the transition toward sustainable, AI-driven farming.
Research Focus
Key Achievements
Top Papers
- 1A DNN-based semantic segmentation for detecting weed and crop126 citations · 2020
- 2
- 3Transformer-Based Weed Segmentation for Grass Management42 citations · 2022