Shengwei Xu

Papers

Total Citations

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About

Dr. Shengwei Xu is a leading researcher in computer vision and marine artificial intelligence, with a primary focus on underwater object detection and ecological monitoring. His most influential work, "Underwater Species Detection using Channel Sharpening Attention" (2021, 74 citations), addresses the formidable challenges of detecting marine life in complex underwater environments—where irregular movement, occlusion, and poor visibility degrade traditional models. By introducing a novel channel sharpening attention mechanism, Dr. Xu significantly improved detection accuracy for autonomous underwater robots, directly advancing sustainable fisheries and marine resource exploration. His contributions bridge deep learning with real-world aquatic applications, enabling more robust and intelligent underwater surveillance systems. Beyond this flagship paper, his research portfolio consistently targets the intersection of attention-based neural architectures and environmental sensing, earning recognition for solving domain-specific problems in computer vision. With a growing citation impact and a clear trajectory toward applied AI in marine science, Dr. Xu’s work is essential reading for researchers developing autonomous systems for challenging, unstructured underwater habitats.