2 citations · 5 across the 11 of their papers we have counts for
11 papers
Spatial-Spectral Binarized Neural Network for Panchromatic and Multi-spectral Images Fusion
Yizhen Jiang, Mengting Ma, Anqi Zhu +3
Remote sensing pansharpening aims to reconstruct spatial-spectral properties during the fusion of panchromatic (PAN) images and low-resolution multi-spectral (LR-MS) images, finall…
TimeExpert: Boosting Long Time Series Forecasting with Temporal Mix of Experts
Xiaowen Ma, Shuning Ge, Fan Yang +5
Transformer-based architectures dominate time series modeling by enabling global attention over all timestamps, yet their rigid 'one-size-fits-all' context aggregation fails to add…
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…
HetSSNet: Spatial-Spectral Heterogeneous Graph Learning Network for Panchromatic and Multispectral Images Fusion
Mengting Ma, Yizhen Jiang, Mengjiao Zhao +2
Remote sensing pansharpening aims to reconstruct spatial-spectral properties during the fusion of panchromatic (PAN) images and low-resolution multi-spectral (LR-MS) images, finall…
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…
STeInFormer: Spatial-Temporal Interaction Transformer Architecture for Remote Sensing Change Detection
Xiaowen Ma, Zhenkai Wu, Mengting Ma +4
Convolutional neural networks and attention mechanisms have greatly benefited remote sensing change detection (RSCD) because of their outstanding discriminative ability. Existent 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…
DDLNet: Boosting Remote Sensing Change Detection with Dual-Domain Learning
Xiaowen Ma, Jiawei Yang, Rui Che +2
Remote sensing change detection (RSCD) aims to identify the changes of interest in a region by analyzing multi-temporal remote sensing images, and has an outstanding value for loca…
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…