SATELLITE IMAGE CLASSIFICATION OF BUILDING DAMAGES USING AIRBORNE AND SATELLITE IMAGE SAMPLES IN A DEEP LEARNING APPROACH

48 citations as recorded by crossref.

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27. Automatic Detection of Collapsed Buildings after the 6 February 2023 Türkiye Earthquakes Using Post-Disaster Satellite Images with Deep Learning-Based Semantic Segmentation Models K. Hacıefendioğlu et al.
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29. Lessons for Remote Post-earthquake Reconnaissance from the 14 August 2021 Haiti Earthquake M. Whitworth et al.
30. Towards Operational Satellite-Based Damage-Mapping Using U-Net Convolutional Network: A Case Study of 2011 Tohoku Earthquake-Tsunami Y. Bai et al.
31. Classification of EgyptSat-1 Images Using Deep Learning Methods H. Keshk & X. Yin
32. Leveraging Disruptive Technologies for Faster and More Efficient Disaster Response Management C. Calle Müller et al.
33. Deep Learning Models for Hazard-Damaged Building Detection Using Remote Sensing Datasets: A Comprehensive Review L. Wang et al.
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37. Detection of Collapsed Buildings in Post-Earthquake Remote Sensing Images Based on the Improved YOLOv3 H. Ma et al.
38. Damage Detection and Segmentation in Disaster Environments Using Combined YOLO and Deeplab S. Jo et al.
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47. Unsupervised learning framework for region-based damage assessment on xBD, a large satellite imagery P. Mittal et al.
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