Ningning Pan
Papers
1
Total Citations
45
H-Index
1
About
Ningning Pan is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent fruit recognition and segmentation for automated harvesting systems. Her most impactful work centers on developing deep learning-based approaches to overcome the challenges posed by complex orchard environments, such as variable lighting, occlusions, and color similarities between fruit and foliage. Pan’s landmark 2022 paper, “Accurate segmentation of green fruit based on optimized mask RCNN application in complex orchard,” has garnered 45 citations, demonstrating its significance in advancing the precision of vision systems for fruit-picking robots. By optimizing the Mask R-CNN architecture, she significantly improved the segmentation accuracy of green fruits against intricate backgrounds—a notoriously difficult task due to the lack of distinct color contrast. This contribution directly addresses a critical bottleneck in agricultural automation, enabling more reliable fruit detection under real-world conditions. Pan’s work is essential reading for researchers in precision agriculture, robotics, and applied deep learning, offering practical solutions that bridge the gap between laboratory models and field deployment.
Research Focus
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Top Papers
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