Jianshuang Guo
Papers
2
Total Citations
14
H-Index
2
About
Jianshuang Guo is a researcher whose work lies at the intersection of computer vision and environmental engineering, with a primary focus on automated solid waste analysis. Guo’s major contribution is the development of a novel three-dimensional object segmentation method based on spatial adaptive projection, designed specifically to improve the identification and separation of waste materials. This technique addresses the critical challenge of accurately segmenting irregularly shaped objects in cluttered environments, offering a robust solution for recycling and waste management automation. While Guo’s citation counts—9 and 5 for the two versions of the seminal 2017/2018 paper—reflect a growing niche impact, the work is notable for its practical application in smart waste sorting systems. By bridging 3D vision algorithms with real-world environmental challenges, Guo has laid groundwork for more efficient, sensor-driven recycling technologies. This research is particularly relevant for students and engineers exploring the intersection of deep learning, point cloud processing, and sustainable infrastructure.
Research Focus
Key Achievements
Top Papers
- 1
- 2