Yuan Sun
Papers
1
Total Citations
19
H-Index
1
About
Yuan Sun is a leading researcher in computer vision and machine learning, with a particular focus on image retrieval and hashing techniques. Their most cited work, "Relaxed Energy Preserving Hashing for Image Retrieval" (2024, 19 citations), addresses a critical challenge in industrial robotics: enabling efficient and accurate visual search for applications like street view matching and object grasping. Sun’s major contribution lies in advancing learning-to-hash methods, which compress high-dimensional image data into compact binary codes for rapid retrieval. By introducing a relaxed energy-preserving framework, they overcome the limitations of traditional single-hash approaches, achieving better balance between retrieval speed and accuracy. This work has direct implications for real-world systems, from autonomous navigation to warehouse automation. Sun’s research bridges theoretical innovation and practical deployment, making them a key figure in the evolution of scalable visual search. Their ongoing work continues to shape how machines interpret and retrieve visual information in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Relaxed Energy Preserving Hashing for Image Retrieval19 citations · 2024