5 citations · 5 across the 9 of their papers we have counts for
6 papers · 1 filter
BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness
Yabin Xu, Fangtao Zhang, Fan Wang +5
Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual characteristics of defects. In p…
Rethinking Conditional Generation for Underwater Salient Object Detection
Hua Li, Yongjie Weng, Yutong Li +3
Salient Object Detection in underwater images remains challenging due to low contrast, uneven illumination, and color distortion caused by scattering and absorption effects, which…
G2HFNet: GeoGran-Aware Hierarchical Feature Fusion Network for Salient Object Detection in Optical Remote Sensing Images
Bin Wan, Runmin Cong, Xiaofei Zhou +3
Remote sensing images captured from aerial perspectives often exhibit significant scale variations and complex backgrounds, posing challenges for salient object detection (SOD). Ex…
RDNet: Region Proportion-Aware Dynamic Adaptive Salient Object Detection Network in Optical Remote Sensing Images
Bin Wan, Runmin Cong, Xiaofei Zhou +3
Salient object detection (SOD) in remote sensing images faces significant challenges due to large variations in object sizes, the computational cost of self-attention mechanisms, a…
Tree-Mamba: A Tree-Aware Mamba for Underwater Monocular Depth Estimation
Peixian Zhuang, Yijian Wang, Zhenqi Fu +3
Underwater Monocular Depth Estimation (UMDE) is a critical task that aims to estimate high-precision depth maps from underwater degraded images caused by light absorption and scatt…
Underwater Object Detection in the Era of Artificial Intelligence: Current, Challenge, and Future
Long Chen, Yuzhi Huang, Junyu Dong +5
Underwater object detection (UOD), aiming to identify and localise the objects in underwater images or videos, presents significant challenges due to the optical distortion, water…