Papers
2
Total Citations
178
H-Index
2
About
Shihan Mao is a leading researcher in agricultural robotics and precision farming, specializing in the application of deep learning and computer vision for autonomous crop harvesting. His work centers on developing intelligent algorithms that enable robots to accurately detect, locate, and harvest fruits and vegetables in complex natural environments. Mao’s major contributions include pioneering multi-feature fusion techniques that combine deep learning with traditional image analysis, significantly improving recognition accuracy under variable lighting and occlusion conditions. His highly cited 2020 paper on automatic cucumber recognition, with over 104 citations, established a benchmark for non-destructive harvesting in unstructured settings. He further advanced the field with his 2022 study on clustered tomato detection and picking point localization, which integrates machine learning for precise robotic manipulation, garnering 74 citations. These innovations address critical challenges in agricultural automation—reducing crop damage and increasing harvesting efficiency. Mao’s work has direct implications for sustainable farming, labor shortages, and food security, making him a key figure in the transition toward fully autonomous agricultural systems.
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