AIDERV2

Aerial Image Dataset for Emergency Response Applications (version 2)

Dataset Information
Modalities
Images
Languages
English
Introduced
2024
License
Homepage

Overview

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

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

Task Model Paper Date
Image Classification TakuNet FP=16 TakuNet: an Energy-Efficient CNN for … 2025-01-10

Research Papers

Recent papers with results on this dataset: