Xingyu Ling
Papers
1
Total Citations
13
H-Index
1
About
Xingyu Ling has made impactful contributions at the intersection of computer vision and industrial robotics, with a particular focus on deep learning-driven automation. Their most cited work, "Location Recognition Algorithm for Vision-Based Industrial Sorting Robot via Deep Learning" (2018, 13 citations), introduces a novel application of deep convolutional neural networks (DCNNs) to automate the precise location and recognition of complex workpieces in industrial sorting processes. A key innovation in this research is the pixel projection algorithm (PPA), which enhances the robot's ability to accurately identify and position objects in real-time. Ling's work addresses critical challenges in manufacturing efficiency, bridging the gap between advanced AI techniques and practical industrial deployment. By demonstrating how DCNNs can replace traditional, less flexible vision systems, their research has laid groundwork for smarter, more adaptive production lines. Though early in their career, Ling's focused approach to solving tangible engineering problems—combining deep learning with robotic perception—positions them as a promising voice in the field of intelligent manufacturing and automated visual recognition.
Research Focus
Key Achievements
Top Papers
- 1