Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response

11/17/2020
by   Firoj Alam, et al.
15

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 computer vision and deep neural networks have enabled the development of models for real-time image classification for a number of tasks, including detecting crisis incidents, filtering irrelevant images, classifying images into specific humanitarian categories, and assessing the severity of damage. Despite several efforts, past works mainly suffer from limited resources (i.e., labeled images) available to train more robust deep learning models. In this study, we propose new datasets for disaster type detection, and informativeness classification, and damage severity assessment. Moreover, we relabel existing publicly available datasets for new tasks. We identify exact- and near-duplicates to form non-overlapping data splits, and finally consolidate them to create larger datasets. In our extensive experiments, we benchmark several state-of-the-art deep learning models and achieve promising results. We release our datasets and models publicly, aiming to provide proper baselines as well as to spur further research in the crisis informatics community.

READ FULL TEXT

page 1

page 3

research
04/09/2021

Social Media Images Classification Models for Real-time Disaster Response

Images shared on social media help crisis managers in terms of gaining s...
research
06/09/2018

Localizing and Quantifying Damage in Social Media Images

Traditional post-disaster assessment of damage heavily relies on expensi...
research
04/09/2017

Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises

The extensive use of social media platforms, especially during disasters...
research
04/28/2020

Deep Machine Learning Approach to Develop a New Asphalt Pavement Condition Index

Automated pavement distress detection via road images is still a challen...
research
03/03/2023

Early Warning Signals of Social Instabilities in Twitter Data

The goal of this project is to create and study novel techniques to iden...
research
04/10/2020

Multimodal Categorization of Crisis Events in Social Media

Recent developments in image classification and natural language process...
research
01/11/2022

Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents

Natural disasters, such as floods, tornadoes, or wildfires, are increasi...

Please sign up or login with your details

Forgot password? Click here to reset