336 citations · 1.3k across the 7 of their papers we have counts for
7 papers
Few-shot semantic segmentation via mask aggregation
Wei Ao, Shunyi Zheng, Yan Meng
Few-shot semantic segmentation aims to recognize novel classes with only very few labelled data. This challenging task requires mining of the relevant relationships between the que…
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images
Rui Li, Shunyi Zheng, Ce Zhang +2
Semantic segmentation using fine-resolution remotely sensed images plays a critical role in many practical applications, such as urban planning, environmental protection, natural a…
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…
Multi-Attention-Network for Semantic Segmentation of Fine Resolution Remote Sensing Images
Rui Li, Shunyi Zheng, Chenxi Duan +3
Semantic segmentation of remote sensing images plays an important role in a wide range of applications including land resource management, biosphere monitoring and urban planning.…
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…
Land Cover Classification from Remote Sensing Images Based on Multi-Scale Fully Convolutional Network
Rui Li, Shunyi Zheng, Chenxi Duan +1
In this paper, a Multi-Scale Fully Convolutional Network (MSFCN) with multi-scale convolutional kernel is proposed to exploit discriminative representations from two-dimensional (2…
MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images
Rui Li, Chenxi Duan, Shunyi Zheng +2
Semantic segmentation of remotely sensed images plays an important role in land resource management, yield estimation, and economic assessment. U-Net, a deep encoder-decoder archit…