Lihua Yin
Papers
2
Total Citations
8
H-Index
2
About
Lihua Yin is a leading researcher in intelligent warehouse optimization and scalable image processing systems. Her work addresses critical challenges in e-commerce logistics and surveillance robotics. In her highly cited 2019 study, Yin developed a genetic-algorithm-based method for storage location assignments in mobile rack warehouses, directly tackling the fundamental problem of order picking efficiency in automated facilities. This contribution has earned 4 citations and provides a practical solution for warehouses using auto robots and mobile racks. In 2021, she introduced Rinegan, a scalable image processing architecture designed for large-scale surveillance applications. This architecture overcomes the limitations of single-robot cameras, which offer narrow fields of view, by enabling distributed processing across multiple agents for smart buildings, industrial parks, and border ports. With 4 citations, Rinegan demonstrates her ability to bridge theoretical algorithms with real-world deployment. Yin’s work is notable for its direct industrial applicability, combining optimization theory with practical system design. Her research continues to influence the fields of logistics automation and intelligent surveillance, making her a key figure in advancing efficient, scalable solutions for modern infrastructure.
Research Focus
Key Achievements
Top Papers
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- 2