Yuting Yao
Papers
1
Total Citations
34
H-Index
1
About
Yuting Yao is a researcher at the forefront of intelligent manufacturing and industrial automation, with a primary focus on integrating deep learning with robotic systems for smart factory applications. Yao's major contribution lies in developing an auto-sorting system that harnesses deep learning for image segmentation and object detection, enabling robotic arms to automatically and efficiently sort machine parts—a task that is both critical and monotonous in modern production lines. This work, published in 2018, has garnered 34 citations, reflecting its practical significance in advancing Industry 4.0 technologies. By bridging computer vision and robotics, Yao has addressed key challenges in real-time industrial sorting, offering a scalable solution that reduces human labor and enhances accuracy. The research demonstrates a compelling application of convolutional neural networks in manufacturing, showcasing how AI can transform traditional factory workflows. For students and researchers exploring the intersection of deep learning and automation, Yao's work provides a clear example of how theoretical models can be deployed in tangible, high-impact industrial systems.
Research Focus
Key Achievements
Top Papers
- 1