248 citations · 488 across the 5 of their papers we have counts for
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C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images
Chengxi Han, Chen Wu, Meiqi Hu +2
A high-precision feature extraction model is crucial for change detection (CD). In the past, many deep learning-based supervised CD methods learned to recognize change feature patt…
Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery
Chengxi Han, Chen Wu, Haonan Guo +3
The rapid advancement of automated artificial intelligence algorithms and remote sensing instruments has benefited change detection (CD) tasks. However, there is still a lot of spa…
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
Chengxi Han, Chen Wu, Haonan Guo +2
Benefiting from the developments in deep learning technology, deep-learning-based algorithms employing automatic feature extraction have achieved remarkable performance on the chan…
DeepCL: Deep Change Feature Learning on Remote Sensing Images in the Metric Space
Haonan Guo, Bo Du, Chen Wu +2
Change detection (CD) is an important yet challenging task in the Earth observation field for monitoring Earth surface dynamics. The advent of deep learning techniques has recently…
HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection
Chengxi Han, Chen Wu, Bo Du
Very-high-resolution (VHR) remote sensing (RS) image change detection (CD) has been a challenging task for its very rich spatial information and sample imbalance problem. In this p…