Shanhao Mou
Papers
1
Total Citations
36
H-Index
1
About
Shanhao Mou is a leading researcher in agricultural robotics and intelligent fruit recognition systems. His work focuses on integrating advanced neural network architectures to enhance the efficiency of automated harvesting technologies. Mou’s most cited paper, "Fruit recognition based on pulse coupled neural network and genetic Elman algorithm application in apple harvesting robot" (2020), has garnered 36 citations, marking a significant contribution to precision agriculture. In this study, he pioneered a hybrid approach combining pulse coupled neural networks (PCNN) for image segmentation with a genetic algorithm-optimized Elman neural network (GA-Elman) for accurate apple recognition. By analyzing 150 field-captured images, Mou demonstrated how this method improves harvesting robot performance under complex orchard conditions, addressing critical challenges in fruit detection and real-time decision-making. His work bridges computational neuroscience and agricultural engineering, offering scalable solutions for autonomous crop harvesting. Mou’s research not only advances robotic vision systems but also supports sustainable farming practices by reducing labor dependency and post-harvest losses. His contributions continue to inspire innovations in smart agriculture and machine learning applications.
Research Focus
Key Achievements
Top Papers
- 1