Yingshuang Cao
Papers
1
Total Citations
17
H-Index
1
About
Yingshuang Cao is a researcher specializing in intelligent inspection systems and computer vision for power infrastructure, with a particular focus on automating substation monitoring. Her major contribution lies in developing robust algorithms for pointer meter reading recognition, addressing a critical bottleneck in substation automation. In her most cited work, she proposed an improved ORB (Oriented FAST and Rotated BRIEF) algorithm tailored for inspection robots, enabling accurate, real-time reading of analog meters—a task traditionally performed manually and prone to human error. This method enhances feature matching and recognition precision under challenging substation conditions, such as varying lighting and meter orientations. With 17 citations to this foundational paper, her work has demonstrated tangible impact in the field of robotics and power systems, offering a scalable solution to reduce labor costs and improve operational efficiency. Her research bridges the gap between advanced computer vision techniques and practical industrial applications, making her a notable contributor to the growing domain of intelligent power grid maintenance.
Research Focus
Key Achievements
Top Papers
- 1