Papers
1
Total Citations
74
H-Index
1
About
Jiasheng Tan is a rising researcher in computer vision and deep learning, with a primary focus on object detection and real-time visual analysis. His most significant contribution to date is the development of SDS-YOLO, an enhanced vibratory position detection algorithm built on the YOLOv11 architecture. This work, published in 2024 and already garnering 74 citations, addresses critical challenges in detecting dynamic, vibrating objects in industrial and robotic applications—a niche yet impactful area where precision and speed are paramount. Tan’s innovation lies in optimizing feature extraction and spatial attention mechanisms, enabling robust performance under motion blur and low-light conditions. While early in his career, the rapid citation growth of his flagship paper signals strong interest from both academia and industry, particularly in automated inspection and autonomous systems. His work bridges the gap between cutting-edge detection frameworks and practical engineering needs, positioning him as a promising voice in applied AI. For students and researchers exploring real-time object detection, Tan’s research offers a clear example of how to adapt state-of-the-art models for specialized, high-stakes environments.
Research Focus
Key Achievements
Top Papers
- 1