Search Results for author:
Found 8 papers, 7 papers with code
C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images
A high-precision feature extraction model is crucial for change detection (CD).
Ranked #1 on
Semi-supervised Change Detection
on WHU - 40% labeled data
(F1 metric)
Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery
The rapid advancement of automated artificial intelligence algorithms and remote sensing instruments has benefited change detection (CD) tasks.
Ranked #1 on
Change Detection
on LEVIR+
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
Benefiting from the developments in deep learning technology, deep-learning-based algorithms employing automatic feature extraction have achieved remarkable performance on the change detection (CD) task.
Ranked #1 on
Change Detection
on GoogleGZ-CD
ChangeMamba: Remote Sensing Change Detection with Spatio-Temporal State Space Model
For the change decoder, which is available in all three architectures, we propose three spatio-temporal relationship modeling mechanisms, which can be naturally combined with the Mamba architecture and fully utilize its attribute to achieve spatio-temporal interaction of multi-temporal features, thereby obtaining accurate change information.
Ranked #1 on
2D Semantic Segmentation
on xBD
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
However, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks.
Ranked #1 on
Semantic Segmentation
on SpaceNet 1
(using extra training data)
Aerial Scene Classification
Building change detection for remote sensing images
+12
DeepCL: Deep Change Feature Learning on Remote Sensing Images in the Metric Space
To address these issues, we complement the strong temporal modeling ability of metric learning with the prominent fitting ability of segmentation and propose a deep change feature learning (DeepCL) framework for robust and explainable CD.
HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection
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.
Ranked #2 on
Change Detection
on LEVIR+
Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery
Considering that public transportation was mostly reduced or even forbidden, our results indicate that city lockdown policies are effective at limiting human transmission within cities.
