DSGR
We introduce Domain Shift across Geographic Regions (DSGR), a new large-scale dataset designed to study the effects of real-world geospatial distribution shifts in satellite imagery classification. DSGR captures variability across diverse geographic regions, with particular emphasis on underrepresented areas such as Africa and Oceania, enabling systematic analysis of how regional differences impact model performance. This […]
AI-Driven Disaster Response and Displacement Monitoring
Noora Al-Emadi, Muhammad Imran, Yin Yang, Ingmar Weber, Fabjan Lashi, Gaia Rigodanza, Ivana Hajžmanová, Ferda Ofli.
Communications of the ACM (2025)
Analysing Satellite Imagery Classification under Spatial Domain Shift across Geographic Regions
Sara Al-Emadi, Yin Yang, Ferda Ofli.
International Journal of Computer Vision (2025)
RWDS
Object detectors achieve strong performance on benchmark datasets, yet most are trained under the i.i.d. assumption, leading to significant degradation when deployed under real-world distribution shifts. Domain Generalisation (DG) addresses this challenge by enabling models to generalise to unseen, Out-Of-Distribution data without access to target domains during training. However, evaluating object detection under realistic DG […]
Benchmarking Object Detectors under Real-World Distribution Shifts in Satellite Imagery
Sara Al-Emadi, Yin Yang, Ferda Ofli.
Computer Vision and Pattern Recognition (CVPR) (2025)
Evaluating Robustness of LLMs on Crisis-Related Microblogs across Events, Information Types, and Linguistic Features
Muhammad Imran, Abdul Wahab Ziaullah, Kai Chen, Ferda Ofli.
WWW 2025 – Proceedings of the ACM Web Conference (2025)
(Won Deployed Application Award) Flood Insights: Integrating Remote and Social Sensing Data for Flood Exposure, Damage, and Urgent Needs Mapping.
Zainab Akhtar, Umair Qazi, Aya El-Sakka, Rizwan Sadiq, Ferda Ofli, Muhammad Imran.
AAAI Conference on Artificial Intelligence (2024)
Mapping Flood Exposure, Damage, and Population Needs Using Remote and Social Sensing: A Case Study of 2022 Pakistan Floods
Zainab Akhtar, Umair Qazi, Rizwan Sadiq, Aya El-Sakka, Muhammad Sajjad, Ferda Ofli, Muhammad Imran.
ACM Web Conference 2023 – Proceedings of the World Wide Web Conference, WWW (2023)
Incidents1M: A Large-Scale Dataset of Images with Natural Disasters, Damage, and Incidents
Ethan Weber, Dim P. Papadopoulos, Agata Lapedriza, Ferda Ofli, Muhammad Imran, Antonio Torralba.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2023)
Incidents1M
Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the Earth undergoes global warming. It is difficult to predict when and where an incident will occur, so timely emergency response is critical to saving the lives of those endangered by destructive events. Fortunately, technology can play a role in these situations. Social […]