Papers
1
Total Citations
45
H-Index
1
About
Li Mao is a researcher specializing in agricultural robotics and intelligent perception systems, with a particular focus on orchard environments. His most-cited work, "Detection of typical obstacles in orchards based on deep convolutional neural network" (2021), has garnered 45 citations, reflecting its practical significance in precision agriculture. In this study, Mao pioneered the application of deep convolutional neural networks to identify common obstacles—such as rocks, tree trunks, and irrigation equipment—that hinder autonomous navigation in orchards. This contribution directly addresses a critical bottleneck in field robotics, enhancing the safety and efficiency of automated farming equipment. By integrating computer vision with real-world agricultural challenges, Mao's research bridges the gap between theoretical AI models and deployable solutions for complex, unstructured outdoor settings. His work is particularly notable for its emphasis on real-time detection and robustness under varying lighting and terrain conditions, making it a valuable reference for both academic researchers and engineers developing next-generation agricultural robots. Through this focused yet impactful study, Li Mao has established himself as a key contributor to the growing field of intelligent agricultural systems.
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Top Papers
- 1