Zhan Yang
Papers
3
Total Citations
47
H-Index
2
About
Zhan Yang is a researcher specializing in agricultural robotics, computer vision, and human-robot interaction, with a focus on applying deep learning techniques to automate complex real-world tasks. His most influential work centers on developing intelligent detection systems for agricultural applications, demonstrating how AI can meaningfully reduce labor demands in food production environments. Yang's most cited contribution (26 citations) introduced a real-time object detection and localization framework using the SSD method for oyster mushroom harvesting robots, addressing the fundamental challenge of enabling machines to identify and precisely locate produce for autonomous picking. Building on this foundation, his 2021 work on tomato fruit maturity detection leveraged YOLOv4 combined with a statistical color model to assess ripeness in greenhouse settings, garnering 19 citations and offering growers a practical alternative to time-consuming manual inspection. More recently, Yang has expanded his research into the intersection of virtual reality and AI-driven robotics, exploring how VR users can maintain meaningful interaction with their physical surroundings through intelligent robotic arm systems. Collectively, his work reflects a consistent commitment to bridging precision agriculture and emerging technologies, making him a notable contributor to the growing field of smart farming and intelligent automation.
Research Focus
Key Achievements
Top Papers
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