Jianyuan Sun
Papers
2
Total Citations
26
H-Index
2
About
Jianyuan Sun is a researcher specializing in computer vision and industrial automation, with a particular focus on depth estimation and defect detection. His major contributions include developing a two-stage deep regression framework for single-image depth estimation, a method that significantly enhances accuracy for applications in augmented reality, robotic mapping, and autonomous driving. This work, published in 2020, has garnered 15 citations, reflecting its impact on advancing depth perception from limited visual data. Additionally, Sun has applied deep learning to industrial quality control, proposing a Faster R-CNN-based approach for tire defect detection, which has earned 11 citations. His research bridges the gap between theoretical computer vision and practical industrial needs, demonstrating how deep learning can solve real-world challenges in manufacturing and autonomous systems. Sun’s work is notable for its focus on efficient, deployable solutions, making him a key figure in the integration of AI into industrial pipelines.
Research Focus
Key Achievements
Top Papers
- 1Two-stage deep regression enhanced depth estimation from a single RGB image15 citations · 2020
- 2Tire Defect Detection Based on Faster R-CNN11 citations · 2020