2 citations · 5 across the 7 of their papers we have counts for
7 papers
Center-guided Classifier for Semantic Segmentation of Remote Sensing Images
Wei Zhang, Mengting Ma, Yizhen Jiang +4
Compared with natural images, remote sensing images (RSIs) have the unique characteristic. i.e., larger intraclass variance, which makes semantic segmentation for remote sensing im…
CD-Lamba: Boosting Remote Sensing Change Detection via a Cross-Temporal Locally Adaptive State Space Model
Zhenkai Wu, Xiaowen Ma, Rongrong Lian +4
Mamba, with its advantages of global perception and linear complexity, has been widely applied to identify changes of the target regions within the remote sensing (RS) images captu…
A Novel Scene Coupling Semantic Mask Network for Remote Sensing Image Segmentation
Xiaowen Ma, Rongrong Lian, Zhenkai Wu +8
As a common method in the field of computer vision, spatial attention mechanism has been widely used in semantic segmentation of remote sensing images due to its outstanding long-r…
CDXLSTM: Boosting Remote Sensing Change Detection with Extended Long Short-Term Memory
Zhenkai Wu, Xiaowen Ma, Rongrong Lian +2
In complex scenes and varied conditions, effectively integrating spatial-temporal context is crucial for accurately identifying changes. However, current RS-CD methods lack a balan…
Rethinking Remote Sensing Change Detection With A Mask View
Xiaowen Ma, Zhenkai Wu, Rongrong Lian +2
Remote sensing change detection aims to compare two or more images recorded for the same area but taken at different time stamps to quantitatively and qualitatively assess changes…
LOGCAN++: Adaptive Local-global class-aware network for semantic segmentation of remote sensing imagery
Xiaowen Ma, Rongrong Lian, Zhenkai Wu +6
Remote sensing images usually characterized by complex backgrounds, scale and orientation variations, and large intra-class variance. General semantic segmentation methods usually…