Min Jin
Papers
1
Total Citations
2
H-Index
1
About
Dr. Min Jin is a researcher at the forefront of agricultural artificial intelligence, specializing in computer vision and deep learning for precision agriculture. Her primary research focuses on developing efficient, lightweight object detection models for crop monitoring and maturity assessment, with a particular emphasis on lotus seedpod analysis. Dr. Jin's most notable contribution is her pioneering work on compressed neural network architectures, which enables real-time, accurate detection of lotus seedpod maturity in complex field environments—a critical advancement for automated harvesting systems. Her 2025 study on efficient maturity detection using compressed models has already garnered 2 citations, highlighting its early impact in the field. By tackling the dual challenges of high computational load and excessive model parameters that hinder deployment on resource-constrained devices, Dr. Jin's research bridges the gap between cutting-edge AI and practical agricultural applications. Her work promises to revolutionize smart farming by making sophisticated computer vision accessible for on-site, real-time crop management.
Research Focus
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Top Papers
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