2 citations · 2 across the 7 of their papers we have counts for
7 papers
Masks Can Talk: Extracting Structured Text Information from Single-Modal Images for Remote Sensing Change Detection
Kai Zheng, Hang-Cheng Dong, Jiatong Pan +3
Remote sensing change detection is pivotal for urban monitoring, disaster assessment, and environmental resource management. Yet, unimodal deep learning methods frequently confuse…
Euler-inspired Decoupling Neural Operator for Efficient Pansharpening
Anqi Zhu, Mengting Ma, Yizhen Jiang +4
Pansharpening aims to synthesize high-resolution multispectral (HR-MS) images by fusing the spatial textures of panchromatic (PAN) images with the spectral information of low-resol…
Tri-path DINO: Feature Complementary Learning for Remote Sensing Multi-Class Change Detection
Kai Zheng, Hang-Cheng Dong, Shoulei Liu +5
In remote sensing imagery, multi-class change detection (MCD) is crucial for fine-grained monitoring, yet it has long been plagued by feature ambiguity in change regions, which obs…
3DTCR: Vortex-following generative reconstruction improves tropical cyclone intensity prediction from global AI weather forecasts
Jun Liu, Xiaohui Zhong, Kai Zheng +9
Global numerical weather prediction (NWP) and artificial intelligence (AI) models often underestimate tropical cyclone (TC) intensity, partly because coarse grids underresolve fine…
Changes in Gaza: DINOv3-Powered Multi-Class Change Detection for Damage Assessment in Conflict Zones
Kai Zheng, Zhenkai Wu, Fupeng Wei +6
Accurately and swiftly assessing damage from conflicts is crucial for humanitarian aid and regional stability. In conflict zones, damaged zones often share similar architectural st…
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…
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…