Fengqiang Xu
Papers
4
Total Citations
87
H-Index
4
About
Fengqiang Xu is a prolific researcher whose work spans computer vision, marine robotics, and natural language processing, with a particular focus on developing intelligent systems for real-world applications. His most significant contributions lie in advancing object detection methodologies for challenging underwater environments, where his pioneering work on real-time marine small object detection using underwater robot vision — accumulating 26 citations since 2018 — laid critical groundwork for automating seafood harvesting in aquaculture, reducing reliance on human divers. Building on this foundation, Xu developed an intelligent detection and autonomous capture system for seafood in 2019, demonstrating a full pipeline from perception to action. His 2022 paper introducing an attention-based spatial pyramid pooling network with bidirectional feature fusion for marine object detection has become his most cited work, garnering 43 citations and reflecting the research community's recognition of its technical refinement. More recently, Xu has expanded his scope into NLP for healthcare, proposing attentive bidirectional LSTM architectures for answer selection in medical service robots. Across these domains, his research consistently bridges deep learning theory with pressing practical demands, making him a versatile contributor to intelligent robotic systems research.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4