102 citations · 428 across the 18 of their papers we have counts for
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Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response
Firoj Alam, Ferda Ofli, Muhammad Imran +2
During a disaster event, images shared on social media helps crisis managers gain situational awareness and assess incurred damages, among other response tasks. Recent advances in…
Detecting natural disasters, damage, and incidents in the wild
Ethan Weber, Nuria Marzo, Dim P. Papadopoulos +5
Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emer…
GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information
Umair Qazi, Muhammad Imran, Ferda Ofli
The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disaster…
Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response
Ferda Ofli, Firoj Alam, Muhammad Imran
Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people,…
Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence
Muhammad Imran, Firoj Alam, Umair Qazi +2
Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads,…
CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing
Firoj Alam, Hassan Sajjad, Muhammad Imran +1
Time-critical analysis of social media streams is important for humanitarian organizations for planing rapid response during disasters. The \textit{crisis informatics} research com…