Papers
1
Total Citations
54
H-Index
1
About
Yue Pan is a researcher specializing in agricultural computer vision, machine learning, and precision agriculture technologies. Their work focuses on developing intelligent image processing solutions to advance automated farming systems, with a particular emphasis on fruit detection and crop management applications. Pan's most recognized contribution is a pioneering method for apple image segmentation that integrates color-texture fusion features with machine learning techniques, published in 2020 and accumulating 54 citations. This work addresses critical challenges in modern apple cultivation, including yield estimation, robotic harvesting, and precision spraying — processes essential to China's position as the world's largest apple-producing nation. By combining color and texture information into a unified feature framework, Pan's approach significantly improves the accuracy and robustness of machine vision systems operating in complex, real-world orchard environments where lighting variation and overlapping foliage present persistent difficulties. This research sits at the intersection of computer vision and smart agriculture, contributing practical tools that support the automation of labor-intensive farming tasks. Pan's work holds particular relevance for researchers and engineers developing agricultural robotics and precision planting systems, offering methodological foundations that continue to inspire subsequent studies in fruit detection and segmentation.
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Top Papers
- 1