Zhengqi Su
Papers
1
Total Citations
9
H-Index
1
About
Zhengqi Su is a researcher at the intersection of computer vision, robotics, and software testing, with a focus on automating the quality assurance of mobile applications. His most-cited work, "Machine vision-based testing action recognition method for robotic testing of mobile application" (2022), has garnered 9 citations and introduces a novel approach that leverages machine vision to enable robots to recognize and replicate testing actions. This contribution directly addresses the challenge of explosive growth and rapid version iteration in mobile apps, where manual testing struggles to keep pace. By combining robotic precision with visual recognition, Su's method enhances testing accuracy and efficiency, reducing the burden of repetitive tasks. His work stands out for its practical integration of robotics and AI to solve real-world software engineering problems, offering a scalable solution for app developers. Su's research is particularly valuable for students and engineers interested in automated testing, human-robot interaction, and applied computer vision, demonstrating how interdisciplinary methods can streamline mobile app development cycles.
Research Focus
Key Achievements
Top Papers
- 1