20 citations · 33 across the 3 of their papers we have counts for
5 papers · 1 filter
Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images
Libo Wang, Ce Zhang, Rui Li +3
Assigning geospatial objects with specific categories at the pixel level is a fundamental task in remote sensing image analysis. Along with rapid development in sensor technologies…
ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images
Rui Li, Chenxi Duan
Semantic segmentation of remotely sensed images plays a crucial role in precision agriculture, environmental protection, and economic assessment. In recent years, substantial fine-…
Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal
Chenxi Duan, Rui Li
In remote sensing images, the existence of the thin cloud is an inevitable and ubiquitous phenomenon that crucially reduces the quality of imageries and limits the scenarios of app…
Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images
Rui Li, Shunyi Zheng, Chenxi Duan +2
The attention mechanism can refine the extracted feature maps and boost the classification performance of the deep network, which has become an essential technique in computer visi…
Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation
Rui Li, Jianlin Su, Chenxi Duan +1
In this paper, to remedy this deficiency, we propose a Linear Attention Mechanism which is approximate to dot-product attention with much less memory and computational costs. The e…