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AI and Generative AI Transforming Disaster Management: A Survey of Damage Assessment and Response Techniques

AI and Generative AI Transforming Disaster Management: A Survey of Damage Assessment and Response Techniques

13 May 2025
Aman Raj
Lakshit Arora
Sanjay Surendranath Girija
Shashank Kapoor
Dipen Pradhan
Ankit Shetgaonkar
ArXiv (abs)PDFHTML

Papers citing "AI and Generative AI Transforming Disaster Management: A Survey of Damage Assessment and Response Techniques"

23 / 23 papers shown
Title
A Survey of Reinforcement Learning from Human Feedback
A Survey of Reinforcement Learning from Human Feedback
Timo Kaufmann
Paul Weng
Viktor Bengs
Eyke Hüllermeier
OffRL
102
155
0
22 Dec 2023
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
348
30,174
0
01 Mar 2022
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Ze Liu
Yutong Lin
Yue Cao
Han Hu
Yixuan Wei
Zheng Zhang
Stephen Lin
B. Guo
ViT
540
21,856
0
25 Mar 2021
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene
  Understanding
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
Maryam Rahnemoonfar
Tashnim Chowdhury
Argho Sarkar
D. Varshney
M. Yari
Robin Murphy
96
258
0
05 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
801
41,948
0
22 Oct 2020
An Introduction to Variational Autoencoders
An Introduction to Variational Autoencoders
Diederik P. Kingma
Max Welling
BDLSSLDRL
250
2,385
0
06 Jun 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan
Quoc V. Le
3DVMedIm
303
18,360
0
28 May 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CEGNN
1.2K
5,605
0
20 Dec 2018
Image Super-Resolution Using Very Deep Residual Channel Attention
  Networks
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Yulun Zhang
Kunpeng Li
Kai Li
Lichen Wang
Bineng Zhong
Y. Fu
SupR
216
4,363
0
08 Jul 2018
Restricted Boltzmann Machines: Introduction and Review
Restricted Boltzmann Machines: Introduction and Review
Guido Montúfar
AI4CE
77
51
0
19 Jun 2018
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDLSSLOCL
291
5,093
0
02 Nov 2017
Enhanced Deep Residual Networks for Single Image Super-Resolution
Enhanced Deep Residual Networks for Single Image Super-Resolution
Bee Lim
Sanghyun Son
Heewon Kim
Seungjun Nah
Kyoung Mu Lee
SupR
231
5,951
0
10 Jul 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.4K
22,397
0
22 May 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.2K
20,998
0
17 Apr 2017
SenseGen: A Deep Learning Architecture for Synthetic Sensor Data
  Generation
SenseGen: A Deep Learning Architecture for Synthetic Sensor Data Generation
M. Alzantot
Supriyo Chakraborty
Mani B. Srivastava
76
127
0
31 Jan 2017
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
856
39,704
0
09 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.3K
17,241
0
16 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.7K
195,310
0
10 Dec 2015
You Only Look Once: Unified, Real-Time Object Detection
You Only Look Once: Unified, Real-Time Object Detection
Joseph Redmon
S. Divvala
Ross B. Girshick
Ali Farhadi
ObjD
816
37,273
0
08 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
2.1K
77,890
0
18 May 2015
Image Super-Resolution Using Deep Convolutional Networks
Image Super-Resolution Using Deep Convolutional Networks
Chao Dong
Chen Change Loy
Kaiming He
Xiaoou Tang
SupR
246
8,137
0
31 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
2.1K
100,836
0
04 Sep 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
325
15,004
1
21 Dec 2013
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