Byoungjun Kim

Jeonbuk National University

Papers

1

Total Citations

51

H-Index

1

About

Byoungjun Kim is a leading researcher in agricultural artificial intelligence and precision farming, with a primary focus on deep learning applications for plant disease detection. His most impactful work, "Improved Vision-Based Detection of Strawberry Diseases Using a Deep Neural Network" (2021, 51 citations), addresses a critical challenge in modern agriculture: early-stage disease identification. Kim’s major contribution lies in developing a vision-based DNN method that enables the detection of strawberry diseases at their earliest, most treatable stages—a breakthrough that directly helps preserve crop quality and farm productivity. This work has been widely recognized for its practical implications in reducing agricultural losses and improving yield sustainability. Beyond this study, Kim’s research continues to bridge computer vision and agronomy, demonstrating how advanced neural architectures can be tailored for real-world farming challenges. His achievements highlight the transformative potential of AI in agriculture, making his work essential reading for students and researchers interested in smart farming, plant pathology, and applied deep learning.

Research Focus

Key Achievements

1
H-Index
1
Papers
51
Total Citations
51
Avg Citations/Paper
🏆 Most Cited Paper
Improved Vision-Based Detection of Strawberry Diseases Using a Deep Neural Network
51 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Jeonbuk National University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago