Caifei Yang
Papers
2
Total Citations
122
H-Index
2
About
Caifei Yang is a leading researcher in underwater robotics and marine vision, whose work is directly advancing the automation of open-sea farming. His primary research areas include underwater object detection, robotic manipulation, and deep learning for marine environments. Yang’s most significant contribution is the creation of the UDD (Underwater Open-sea Farm Object Detection Dataset), the first-ever 4K HD dataset collected in a real open-sea farm. This dataset, comprising 2,227 images of sea cucumbers, sea urchins, and scallops, has become a foundational resource for the field. Building on this, his seminal paper “A New Dataset, Poisson GAN and AquaNet for Underwater Object Grabbing” (2021) has garnered 109 citations, introducing the Poisson GAN and AquaNet framework to significantly boost the object-grabbing capability of underwater robots. By providing both the data and the algorithms needed for precise robotic picking in challenging underwater conditions, Yang’s work is pivotal in transforming open-sea aquaculture from a labor-intensive industry into a technologically-driven, automated one.
Research Focus
Key Achievements
Top Papers
- 1A New Dataset, Poisson GAN and AquaNet for Underwater Object Grabbing109 citations · 2021
- 2