Jiaxi Li
Papers
1
Total Citations
7
H-Index
1
About
Jiaxi Li is a researcher specializing in computer vision and deep learning, with a particular focus on underwater object detection. Their most notable contribution is the development of U-ATSS, a lightweight and accurate one-stage detection network designed to address the unique challenges of underwater environments, such as low visibility, color distortion, and complex backgrounds. This work, published in 2024, has already garnered 7 citations, reflecting its immediate relevance and potential for applications in marine biology, underwater robotics, and environmental monitoring. Li’s research bridges the gap between efficiency and precision, making advanced detection models more accessible for resource-constrained systems. By refining the Adaptive Training Sample Selection (ATSS) framework, Li has demonstrated a commitment to improving real-time performance without sacrificing accuracy—a critical balance for autonomous underwater vehicles. Their work stands as a promising step toward more robust and deployable vision systems in challenging aquatic settings, earning recognition among peers in the field.
Research Focus
Key Achievements
Top Papers
- 1