Kairan Lou
Papers
3
Total Citations
35
H-Index
3
About
Kairan Lou is a researcher at the forefront of agricultural robotics and intelligent plant disease detection. Their work centers on two critical challenges in modern agriculture: automating the harvesting of complex crops and diagnosing plant diseases using deep learning. Lou’s most cited paper, “Classification of infection grade for anthracnose in mango leaves under complex background based on CBAM-DBIRNet” (2024, 19 citations), introduces a novel convolutional neural network that accurately grades mango anthracnose severity, even in cluttered field conditions—a significant step toward precision disease management. In parallel, Lou has made substantial contributions to robotic harvesting. Their studies on a six-degrees-of-freedom dragon fruit picking robot address the adaptive motion challenges posed by the fruit’s irregular growth positions. By proposing a compliant picking control strategy based on adaptive variable impedance (2025, 8 citations), Lou enables safer, more reliable robotic manipulation. With a growing citation impact and a focus on translating AI and robotics into practical agricultural tools, Kairan Lou is helping to shape the future of smart farming and automated crop care.
Research Focus
Key Achievements
Top Papers
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