Zixiang Qiu
Papers
2
Total Citations
29
H-Index
2
About
Zixiang Qiu is a leading researcher in underwater robotics and computer vision, with a focus on automated marine resource detection. His work centers on developing efficient deep learning models for real-time object detection in challenging underwater environments, particularly for sea cucumber harvesting. Qiu’s major contributions include the creation of the MD-SSD (improved MobileNet-SSD) architecture, which integrates residual structures and dilated convolutions to overcome accuracy losses in lightweight detection networks. His 2019 paper on this method has garnered 16 citations, while his complementary work on pruned SSD models, enhanced by multi-scale Retinex image preprocessing, has earned 13 citations. Together, these studies establish a robust framework for deploying detection algorithms on resource-constrained underwater robots. Qiu’s research directly addresses the practical challenges of aquaculture automation, combining algorithmic innovation with real-world application. His work is notable for bridging the gap between state-of-the-art computer vision and the unique constraints of subsea environments, paving the way for more intelligent and efficient marine harvesting systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Underwater sea cucumbers detection based on pruned SSD13 citations · 2019