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20182022
most citedDSDANet: Deep Siamese Domain Adaptation Convolutional Neural Network for Cross-domain Change Detection

19 citations · 51 across the 7 of their papers we have counts for

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Showing cs.CVShow all

9 papers · 1 filter

cs.CV20221 cited

Fully Convolutional Change Detection Framework with Generative Adversarial Network for Unsupervised, Weakly Supervised and Regional Supervised Change Detection

Chen Wu, Bo Du, Liangpei Zhang

Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most end-to-end networks are proposed for supervised change detection,…

cs.CV20218 cited

Unsupervised Domain Adaptation for Semantic Segmentation via Low-level Edge Information Transfer

Hongruixuan Chen, Chen Wu, Yonghao Xu +1

Unsupervised domain adaptation for semantic segmentation aims to make models trained on synthetic data (source domain) adapt to real images (target domain). Previous feature-level…

cs.CV20216 cited

Towards Deep and Efficient: A Deep Siamese Self-Attention Fully Efficient Convolutional Network for Change Detection in VHR Images

Hongruixuan Chen, Chen Wu, Bo Du

Recently, FCNs have attracted widespread attention in the CD field. In pursuit of better CD performance, it has become a tendency to design deeper and more complicated FCNs, which…

cs.CV2021

Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery

Chen Wu, Sihan Zhu, Jiaqi Yang +6

As the COVID-19 epidemic began to worsen in the first months of 2020, stringent lockdown policies were implemented in numerous cities throughout the world to control human transmis…

cs.CV202019 cited

DSDANet: Deep Siamese Domain Adaptation Convolutional Neural Network for Cross-domain Change Detection

Hongruixuan Chen, Chen Wu, Bo Du +1

Change detection (CD) is one of the most vital applications in remote sensing. Recently, deep learning has achieved promising performance in the CD task. However, the deep models a…

cs.CV2020

Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion

Lixiang Ru, Bo Du, Chen Wu

Classifying multi-temporal scene land-use categories and detecting their semantic scene-level changes for imagery covering urban regions could straightly reflect the land-use trans…