Yuan Tang

Kunming University of Science and Technology

Papers

Total Citations

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About

Yuan Tang is a researcher at the forefront of agricultural robotics and computer vision, with a primary focus on developing efficient, real-time detection systems for specialty crops. Their most notable contribution is the pioneering work on the lightweight YOLOv7 algorithm for rapid detection of Yunnan Xiaomila peppers, a critical advancement for autonomous harvesting robots. By significantly reducing computational costs while improving accuracy in detecting densely distributed and occluded fruit, Tang’s 2023 paper has already garnered 18 citations, demonstrating immediate impact in the precision agriculture community. This work addresses a fundamental bottleneck in agricultural automation—balancing model efficiency with detection reliability under challenging field conditions. Tang’s research bridges the gap between deep learning optimization and practical robotic applications, offering scalable solutions for real-time fruit recognition that can be adapted to other crops. Their achievements highlight a commitment to making intelligent harvesting systems more accessible and robust, positioning them as an emerging leader in the intersection of computer vision and sustainable agriculture technology.