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20202024
most citedHANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images

248 citations · 500 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024★ 164 cited

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…

cs.CV2024★ 248 cited

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…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2022★ 86 cited

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…

cs.CV2022

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…