Baisheng Liu
Papers
1
Total Citations
29
H-Index
1
About
Dr. Baisheng Liu is a leading researcher at the intersection of computer vision, marine robotics, and ecological monitoring. His work primarily focuses on developing high-accuracy object detection algorithms tailored for challenging underwater environments, where traditional models struggle with fast-moving, small-scale targets. His most cited paper, "YOLO8-FASG: A High-Accuracy Fish Identification Method for Underwater Robotic System" (2024), has already garnered 29 citations, reflecting its immediate impact on the field. In this study, Liu addresses a critical bottleneck in autonomous underwater systems: the difficulty of identifying small, agile fish that occupy minimal screen space. By enhancing the model’s receptive field and detection flexibility, his method significantly improves real-time identification accuracy, enabling more reliable robotic monitoring of aquatic ecosystems. This contribution not only advances robotic perception but also supports marine biology research and sustainable fisheries management. Liu’s work exemplifies the fusion of deep learning and robotics, offering practical solutions for environmental surveillance. His growing citation record underscores his influence, making him a key figure to watch in applied AI and underwater robotics.
Research Focus
Key Achievements
Top Papers
- 1