Papers
2
Total Citations
42
H-Index
2
About
Xue Du is a researcher whose work lies at the intersection of computer vision, robotics, and artificial intelligence, with a particular focus on solving complex problems in challenging environments. Du’s most significant contribution is in underwater small target detection, where they pioneered a novel approach that integrates YOLOX with MobileViT and double coordinate attention mechanisms. This work, which has garnered 35 citations, directly addresses the notoriously difficult task of detecting objects in the murky, low-visibility conditions of underwater optical imaging—a critical challenge for marine exploration and autonomous underwater vehicles. Additionally, Du has advanced the field of robotic navigation through their work on multi-objective path planning. By introducing deep reinforcement learning and a hierarchical Twin Delayed Deep Deterministic policy gradient algorithm, Du’s 2022 paper proposes a method for robots to safely and efficiently navigate to multiple target areas, a key capability for complex autonomous missions. With a growing citation impact, Xue Du is establishing a reputation for developing intelligent systems that operate effectively in the real world’s most demanding and unpredictable settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multi-objective path planning based on deep reinforcement learning7 citations · 2022