Juwon Seo
Papers
2
Total Citations
12
H-Index
2
About
Juwon Seo is a rising researcher in precision agriculture and computer vision, whose work focuses on leveraging deep learning to enhance sustainable farming practices. His key research areas include plant disease classification, semantic segmentation for crop and weed management, and knowledge distillation techniques for efficient neural networks. Seo’s major contributions address critical bottlenecks in agricultural automation: his 2025 paper on “Estimation of Fractal Dimensions and Classification of Plant Disease with Complex Backgrounds” (7 citations) introduces a novel approach that enables farming robot cameras to accurately identify diseases in cluttered field environments, directly reducing reliance on manual inspection and unnecessary agrochemicals. Complementing this, his work on “KDOSS-net” (5 citations) pioneers a knowledge distillation-based outpainting and semantic segmentation framework that efficiently distinguishes crops, weeds, and background pixels, overcoming the computational limitations of conventional methods for real-time weed management. Though early in his career, Seo’s research has already garnered attention for its practical impact on crop yield optimization and environmental sustainability. His innovative integration of fractal geometry with deep learning, alongside his focus on model compression for edge deployment, positions him as a promising contributor to the next generation of intelligent agricultural systems.
Research Focus
Key Achievements
Top Papers
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- 2