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Recent advancements in computer vision and deep learning techniques have facilitated notable progress in scene understanding, thereby assisting rescue teams in achieving precise damage assessment.
The pascal visual object classes (voc) challenge
Everingham, M., Van Gool, L., Williams, C. K., Winn, J. & Zisserman, A · 2010
Earlier work this paper cites.
The role of context for object detection and semantic segmentation in the wild
Mottaghi, R. et al · 2014
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P. & Brox, T · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Cordts, M. et al · 2016
Earlier work this paper cites.
Damage assessment from social media imagery data during disasters
Nguyen, D. T., Ofli, F., Imran, M. & Mitra, P · 2017
Earlier work this paper cites.
Building damage assessment using deep learning and ground-level image data
Nia, K. R. & Mori, G · 2017
Earlier work this paper cites.
Nguyen, D. T., Alam, F., Ofli, F. & Imran, M · 2017
Earlier work this paper cites.
Damage detection from aerial images via convolutional neural networks
Fujita, A. et al · 2017
Earlier work this paper cites.
Pyramid scene parsing network
Zhao, H., Shi, J., Qi, X., Wang, X. & Jia, J · 2017
Earlier work this paper cites.
Rethinking atrous convolution for semantic image segmentation
Chen, L.-C., Papandreou, G., Schroff, F. & Adam, H · 2017
Earlier work this paper cites.
Coco-stuff: Thing and stuff classes in context
Caesar, H., Uijlings, J. & Ferrari, V · 2018
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Chen, S. A. et al · 2018
Cited alongside, same era.
From satellite imagery to disaster insights
Doshi, J., Basu, S. & Pang, G · 2018
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Deepglobe 2018: A challenge to parse the earth through satellite images
Demir, I. et al · 2018
Cited alongside, same era.
Functional map of the world
Christie, G., Fendley, N., Wilson, J. & Mukherjee, R · 2018
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Quantitative data analysis: Small unmanned aerial systems at hurricane michael
Fernandes, O. et al · 2019
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Detecting natural disasters, damage, and incidents in the wild
Weber, E. et al · 2020
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Detecting natural disasters, damage, and incidents in the wild
Weber, E. et al · 2020
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Zhu, X., Liang, J. & Hauptmann, A · 2020
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Comprehensive semantic segmentation on high resolution uav imagery for natural disaster damage assessment
Chowdhury, T., Rahnemoonfar, M., Murphy, R. & Fernandes, O · 2020
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https://www.v7labs.com/darwin
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Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F. & Adam, H · 2018
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Attention u-net: Learning where to look for the pancreas
Oktay, O. et al · 2018
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Creating xbd: A dataset for assessing building damage from satellite imagery
Gupta, R. et al · 2019
Cited alongside, same era.
Deep-learning-based aerial image classification for emergency response applications using unmanned aerial vehicles
Kyrkou, C. & Theocharides, T · 2019
Cited alongside, same era.
Multi3net: segmenting flooded buildings via fusion of multiresolution, multisensor, and multitemporal satellite imagery
Rudner, T. G. et al · 2019
Cited alongside, same era.
Nvidia: Spacenet on amazon web services (aws) datasets: The spacenet catalog
CosmiQWorks, D
Cited in the paper.
V7 darwin · 2020
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Fema preliminary damage assessment guide
FEMA · 2020
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Floodnet: A high resolution aerial imagery dataset for post flood scene understanding
Rahnemoonfar, M. et al · 2021
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Segmenter: Transformer for semantic segmentation
Strudel, R., Garcia, R., Laptev, I. & Schmid, C · 2021
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Rescuenet: A high resolution uav semantic segmentation dataset for natural disaster damage assessment
Rahnemoonfar, M., Chowdhury, T. & Murphy, R. R · 2023
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