FUSING MULTI-MODAL DATA FOR SUPERVISED CHANGE DETECTION

27 citations as recorded by crossref.

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3. Fusing Sentinel-1 and Sentinel-2 Images for Deforestation Detection in the Brazilian Amazon Under Diverse Cloud Conditions F. Ferrari et al. https://doi.org/10.1109/LGRS.2023.3242430
4. Handling unexpected inputs: incorporating source-wise out-of-distribution detection into SAR-optical data fusion for scene classification J. Gawlikowski et al. https://doi.org/10.1186/s13634-023-01008-z
5. Semi-Supervised Urban Change Detection Using Multi-Modal Sentinel-1 SAR and Sentinel-2 MSI Data S. Hafner et al. https://doi.org/10.3390/rs15215135
6. GLCD-DA: Change detection from optical and SAR imagery using a Global-Local network with diversified attention J. Li et al. https://doi.org/10.1016/j.isprsjprs.2025.05.029
7. Changes detection of remote sensing images using two-stream two-stream deep neural network Y. Hasanzadeh et al. https://doi.org/10.61186/jgst.13.1.55
8. Hierarchical Feature Alignment-based Progressive Addition Network for Multimodal Change Detection T. Liu et al. https://doi.org/10.1016/j.patcog.2025.111355
9. SmaDS-SiamUnet: A Small Dual-Stream Network for Change Detection of Dual-Sensor Data Y. Huang et al. https://doi.org/10.1109/LGRS.2023.3345854
10. Confidence Estimation in Unsupervised Deep Change Vector Analysis S. Saha https://doi.org/10.1109/TGRS.2024.3504742
11. HT-HSCNet: A Lightweight Network With Heuristic Teaching and Hypergraph Structural Constraints for RS Images Change Detection Z. Wang et al. https://doi.org/10.1109/JSTARS.2026.3685469
12. Deep-Learning for Change Detection Using Multi-Modal Fusion of Remote Sensing Images: A Review S. Saidi et al. https://doi.org/10.3390/rs16203852
13. Adversarial Feature Equilibrium Network for Multimodal Change Detection in Heterogeneous Remote Sensing Images Y. Pu et al. https://doi.org/10.1109/TGRS.2024.3480091
14. Supervised Change Detection Using Prechange Optical-SAR and Postchange SAR Data S. Saha et al. https://doi.org/10.1109/JSTARS.2022.3206898
15. CDPrompt: Multimodal Change Detection With In-Domain Prompt in Missing Modality Scenarios L. Zhang et al. https://doi.org/10.1109/TGRS.2025.3598803
16. HF-MCD: A Heterogeneous Fusion Framework for Multimodal Change Detection L. Cai et al. https://doi.org/10.1109/TGRS.2025.3606546
17. A Dual-Modal Framework Integrating SAR-Based Change Screening and Optical-Scene-Informed Identification for High-Frequency Monitoring of Construction-Ready Bare Land W. Song et al. https://doi.org/10.3390/rs18081103
18. SMD-Net: Siamese Multi-Scale Difference-Enhancement Network for Change Detection in Remote Sensing X. Zhang et al. https://doi.org/10.3390/rs14071580
19. A Robust Oriented Filter-Based Matching Method for Multisource, Multitemporal Remote Sensing Images Z. Fan et al. https://doi.org/10.1109/TGRS.2023.3288531
20. Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net S. Hafner et al. https://doi.org/10.1109/LGRS.2021.3119856
21. MaCon: A Generic Self-Supervised Framework for Unsupervised Multimodal Change Detection J. Wang et al. https://doi.org/10.1109/TIP.2025.3542276
22. HAM-CD: Hybrid Attention Mamba for Remote Sensing Change Detection G. Li et al. https://doi.org/10.1109/TGRS.2026.3665418
23. Operational change detection for geographical information: Overview and challenges N. Gonthier https://doi.org/10.1016/j.jag.2026.105278
24. A practically feasible transfer learning method for deep-temporal urban change monitoring G. Zitzlsberger et al. https://doi.org/10.1080/01431161.2023.2243021
25. Neural Network Fusion Processing and Inverse Mapping to Combine Multisensor Satellite Data and Analyze the Prominent Features G. Joshi et al. https://doi.org/10.1109/JSTARS.2023.3247788
26. XFuse: Multi-sensor CNN transformer fusion with cross attention and quality aware curriculum learning for high resolution fractional snow cover mapping G. Demil & M. Oussalah https://doi.org/10.1016/j.isprsjprs.2026.05.028
27. MSCD-Net: From Unimodal to Multimodal Semantic Change Detection J. Wang et al. https://doi.org/10.1109/TGRS.2025.3591814