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After a hurricane, damage assessment is critical to emergency managers for efficient response and resource allocation. One way to gauge the damage extent is to quantify the number of flooded/damaged buildings, which is traditionally done by…

Computer Vision and Pattern Recognition · Computer Science 2020-07-09 Quoc Dung Cao , Youngjun Choe

Post-hurricane damage assessment is crucial towards managing resource allocations and executing an effective response. Traditionally, this evaluation is performed through field reconnaissance, which is slow, hazardous, and arduous. Instead,…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Jimmy Bao

Damage assessment after natural disasters is needed to distribute aid and forces to recovery from damage dealt optimally. This process involves acquiring satellite imagery for the region of interest, localization of buildings, and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Eugene Khvedchenya , Tatiana Gabruseva

Natural disasters ravage the world's cities, valleys, and shores on a regular basis. Deploying precise and efficient computational mechanisms for assessing infrastructure damage is essential to channel resources and minimize the loss of…

Computer Vision and Pattern Recognition · Computer Science 2022-01-28 Thomas Y. Chen

Fast and effective responses are required when a natural disaster (e.g., earthquake, hurricane, etc.) strikes. Building damage assessment from satellite imagery is critical before relief effort is deployed. With a pair of pre- and…

Computer Vision and Pattern Recognition · Computer Science 2022-02-16 Yu Shen , Sijie Zhu , Taojiannan Yang , Chen Chen , Delu Pan , Jianyu Chen , Liang Xiao , Qian Du

Satellite imagery has played an increasingly important role in post-disaster building damage assessment. Unfortunately, current methods still rely on manual visual interpretation, which is often time-consuming and can cause very low…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Irene Alisjahbana , Jiawei Li , Ben , Strong , Yue Zhang

When major disaster occurs the questions are raised how to estimate the damage in time to support the decision making process and relief efforts by local authorities or humanitarian teams. In this paper we consider the use of Machine…

Computer Vision and Pattern Recognition · Computer Science 2018-03-02 Alexey Trekin , German Novikov , Georgy Potapov , Vladimir Ignatiev , Evgeny Burnaev

When disaster strikes, accurate situational information and a fast, effective response are critical to save lives. Widely available, high resolution satellite images enable emergency responders to estimate locations, causes, and severity of…

Computer Vision and Pattern Recognition · Computer Science 2020-04-15 Hanxiang Hao , Sriram Baireddy , Emily R. Bartusiak , Latisha Konz , Kevin LaTourette , Michael Gribbons , Moses Chan , Mary L. Comer , Edward J. Delp

Gaining timely and reliable situation awareness after hazard events such as a hurricane is crucial to emergency managers and first responders. One effective way to achieve that goal is through damage assessment. Recently, disaster…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Quoc Dung Cao , Youngjun Choe

The use of satellite imagery has become increasingly popular for disaster monitoring and response. After a disaster, it is important to prioritize rescue operations, disaster response and coordinate relief efforts. These have to be carried…

Computers and Society · Computer Science 2018-12-19 Jigar Doshi , Saikat Basu , Guan Pang

Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete and potentially biased. This lack of reliable data imposes severe limitations for media…

General Economics · Economics 2021-07-07 Hannes Mueller , Andre Groger , Jonathan Hersh , Andrea Matranga , Joan Serrat

Humanitarian disasters and political violence cause significant damage to our living space. The reparation cost to homes, infrastructure, and the ecosystem is often difficult to quantify in real-time. Real-time quantification is critical to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 Lili Lu , Weisi Guo

In the aftermath of disasters, building damage maps are obtained using change detection to plan rescue operations. Current convolutional neural network approaches do not consider the similarities between neighboring buildings for predicting…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Ali Ismail , Mariette Awad

This study aims to enable more reliable automated post-disaster building damage classification using artificial intelligence (AI) and multi-view imagery. The current practices and research efforts in adopting AI for post-disaster damage…

Computer Vision and Pattern Recognition · Computer Science 2022-08-26 Asim Bashir Khajwal , Chih-Shen Cheng , Arash Noshadravan

Rapid identification of damaged buildings after natural disasters or on war areas is crucial to support emergency response and prioritize interventions. Earth Observation constellations provide timely, large-scale coverage, but actionable…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Thomas Goudemant , Benjamin Francesconi

Classification of the extent of damage suffered by a building in a seismic event is crucial from the safety perspective and repairing work. In this study, authors have proposed a CNN based autonomous damage detection model. Over 1200 images…

Computer Vision and Pattern Recognition · Computer Science 2019-07-19 Dhananjay Nahata , Harish Kumar Mulchandani , Suraj Bansal , G Muthukumar

Accurate assessment of post-disaster damage is essential for prioritizing emergency response, yet current practices rely heavily on manual interpretation of satellite imagery.This approach is time-consuming, subjective, and difficult to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Sreesritha Sai , Sai Venkata Suma Sreeja , Sai Sri Deepthi , Nikhil

Automatic change detection and disaster damage assessment are currently procedures requiring a huge amount of labor and manual work by satellite imagery analysts. In the occurrences of natural disasters, timely change detection can save…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Ethan Weber , Hassan Kané

Fast and effective responses are required when a natural disaster (e.g., earthquake, hurricane, etc.) strikes. Building damage assessment from satellite imagery is critical before an effective response is conducted. High-resolution…

Computer Vision and Pattern Recognition · Computer Science 2020-11-20 Yu Shen , Sijie Zhu , Taojiannan Yang , Chen Chen

High-resolution satellite imagery available immediately after disaster events is crucial for response planning as it facilitates broad situational awareness of critical infrastructure status such as building damage, flooding, and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-09 Danil Kuzin , Olga Isupova , Brooke D. Simmons , Steven Reece
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