Sungjae Lee
Papers
1
Total Citations
23
H-Index
1
About
Sungjae Lee is a leading researcher in agricultural computer vision, specializing in deep learning solutions for precision farming. His work focuses on overcoming the critical challenge of motion blur in real-time crop and weed segmentation—a fundamental requirement for autonomous farming robots performing tasks like targeted herbicide spraying. Lee’s most notable contribution is the development of the WRA-Net (Wide Receptive Field Attention Network), a novel architecture that dramatically improves motion deblurring in agricultural imagery. By integrating wide receptive fields with attention mechanisms, his network enables robots to accurately distinguish crops from weeds even when cameras capture blurred images during field operations. This work, published in 2023 and already garnering 23 citations, addresses a practical bottleneck that has long hindered the deployment of vision-guided agricultural machinery. Lee’s research bridges the gap between state-of-the-art computer vision and real-world farming constraints, making autonomous weeding and precision spraying more reliable. His contributions are paving the way for more efficient, sustainable agriculture through intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1