Aerial Image Dataset for Emergency Response Applications (version 2)
The dataset contains aerial images containing three commonly occurring natural disasters
earthquake/collapsed buildings, flood, wildfire/fire, and a normal class; do not reflect any disaster. It consist of 167723 aerial images divided into 4 classes. The dataset is an extension of the AIDER dataset (Aerial Image Dataset for Emergency Response Applications).
if you use this dataset please cite the following publications:
[1] Shianios, D., Kyrkou, C., Kolios, P.S. (2023). A Benchmark and Investigation of Deep-Learning-Based Techniques for Detecting Natural Disasters in Aerial Images. In: Tsapatsoulis, N., et al. Computer Analysis of Images and Patterns. CAIP 2023. Lecture Notes in Computer Science, vol 14185. Springer, Cham. https://doi.org/10.1007/978-3-031-44240-7_24
Link: https://link.springer.com/chapter/10.1007/978-3-031-44240-7_24
[2] D. Shianios, P. Kolios, C. Kyrkou, "DiRecNetV2: A Transformer-Enhanced Network for Aerial Disaster Recognition", SN Computer Science, 2024 (Accepted to Appear)
Variants: AIDERV2
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Image Classification | TakuNet FP=16 | TakuNet: an Energy-Efficient CNN for … | 2025-01-10 |
Recent papers with results on this dataset: