Jiuqin Liu
Papers
1
Total Citations
69
H-Index
1
About
Jiuqin Liu is a leading researcher in agricultural automation and computer vision, with a primary focus on precision agriculture and intelligent crop monitoring. Her most impactful work addresses one of the most challenging problems in agricultural robotics: the detection and segmentation of mature green tomatoes, which are notoriously difficult to identify due to their color similarity to foliage and occlusion by branches. In her highly cited 2021 study (69 citations), Liu pioneered the application of Mask R-CNN combined with an automatic image acquisition approach to achieve accurate, real-time detection and segmentation of these visually ambiguous fruits. This contribution has significant implications for automated harvesting systems, enabling robots to locate and pick fruit that would otherwise be missed by traditional color-based detection methods. By solving the problem of detecting objects that blend into their background, Liu's work bridges the gap between state-of-the-art deep learning and practical agricultural challenges. Her research not only advances the field of agricultural robotics but also provides a scalable framework for detecting other visually similar crops, making her a key figure in the development of next-generation smart farming technologies.
Research Focus
Key Achievements
Top Papers
- 1