Jingyong Cai

Tokyo University of Agriculture and Technology

Papers

Total Citations

H-Index

About

Dr. Jingyong Cai is a leading researcher at the intersection of computer vision and precision agriculture, with a primary focus on developing intelligent systems for crop monitoring and analysis. His most impactful work centers on applying deep learning, particularly YOLO-based transfer learning, to automate plant phenotyping and growth assessment. In his highly cited 2023 paper, "An Automatic Tomato Growth Analysis System Using YOLO Transfer Learning," Dr. Cai addresses critical challenges in Japan’s aging agricultural sector—such as labor shortages and declining production—by creating a robotic vision system that can accurately detect and track tomato growth stages. This contribution has already garnered 9 citations, demonstrating its immediate relevance to the smart agriculture community. Dr. Cai’s research bridges the gap between advanced AI algorithms and practical farming needs, offering scalable solutions for non-destructive, real-time crop analysis. His work not only advances the field of agricultural robotics but also provides a blueprint for deploying computer vision in resource-constrained environments, making him a key figure in the drive toward sustainable, technology-driven food production.