| # AIDERv2 Dataset |
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| ## Overview |
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| AIDERv2 (Aerial Image Dataset for Emergency Response Applications) is an aerial image classification dataset for disaster recognition. It contains 16,723 UAV and aerial images across four classes: |
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| - Earthquake |
| - Flood |
| - Fire |
| - Normal |
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| ## Statistics |
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| | Class | Train | Validation | Test | Total | |
| |---------|------:|-----------:|-----:|------:| |
| | Earthquake | 1,927 | 239 | 239 | 2,405 | |
| | Flood | 4,063 | 505 | 502 | 5,070 | |
| | Fire | 3,509 | 439 | 436 | 4,384 | |
| | Normal | 3,900 | 487 | 477 | 4,864 | |
| | **Total** | **13,399** | **1,670** | **1,654** | **16,723** | |
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| ## Image Format |
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| - RGB Images |
| - Resolution: 224 × 224 pixels |
| - Dataset split into Train, Validation, and Test sets |
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| ## Applications |
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| - Disaster Recognition |
| - Aerial Image Classification |
| - UAV-Based Emergency Response |
| - Deep Learning and Computer Vision Research |
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| ## Source |
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| Original dataset: |
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| https://zenodo.org/records/10891054 |
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| ## Citation |
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| ```bibtex |
| @inproceedings{shianios2023aider, |
| title={A Benchmark and Investigation of Deep-Learning-Based Techniques for Detecting Natural Disasters in Aerial Images}, |
| author={Shianios, Demetris and Kyrkou, Christos and Kolios, Panayiotis S.}, |
| booktitle={Computer Analysis of Images and Patterns (CAIP)}, |
| year={2023}, |
| publisher={Springer} |
| } |
| ``` |
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