248 citations · 519 across the 10 of their papers we have counts for
10 papers
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…
An Investigation of Face Mask Use with Busking Videos on YouTube during COVID-19: a Case Study in South Korea
Chen Wu, Xingjie Hao, Meiqi Hu +3
Wearing face mask is an effective measure to reduce the risk of COVID-19 infections and control its transmission, thus its usage survey is important for better policy decision to m…
GlobalMind: Global Multi-head Interactive Self-attention Network for Hyperspectral Change Detection
Meiqi Hu, Chen Wu, Liangpei Zhang
High spectral resolution imagery of the Earth's surface enables users to monitor changes over time in fine-grained scale, playing an increasingly important role in agriculture, def…
EMS-Net: Efficient Multi-Temporal Self-Attention For Hyperspectral Change Detection
Meiqi Hu, Chen Wu, Bo Du
Hyperspectral change detection plays an essential role of monitoring the dynamic urban development and detecting precise fine object evolution and alteration. In this paper, we hav…
HyperNet: Self-Supervised Hyperspectral Spatial-Spectral Feature Understanding Network for Hyperspectral Change Detection
Meiqi Hu, Chen Wu, Liangpei Zhang
The fast development of self-supervised learning lowers the bar learning feature representation from massive unlabeled data and has triggered a series of research on change detecti…
Multi-Temporal Spatial-Spectral Comparison Network for Hyperspectral Anomalous Change Detection
Meiqi Hu, Chen Wu, Bo Du
Hyperspectral anomalous change detection has been a challenging task for its emphasis on the dynamics of small and rare objects against the prevalent changes. In this paper, we hav…
Binary Change Guided Hyperspectral Multiclass Change Detection
Meiqi Hu, Chen Wu, Bo Du +1
Characterized by tremendous spectral information, hyperspectral image is able to detect subtle changes and discriminate various change classes for change detection. The recent rese…
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…
Hyperspectral Anomaly Change Detection Based on Auto-encoder
Meiqi Hu, Chen Wu, Liangpei Zhang +1
With the hyperspectral imaging technology, hyperspectral data provides abundant spectral information and plays a more important role in geological survey, vegetation analysis and m…