Datasets:
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---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': flooded or damaged buildings
'1': undamaged buildings
splits:
- name: train
num_bytes: 25588780
num_examples: 10000
download_size: 26998688
dataset_size: 25588780
license: cc-by-4.0
---
# Dataset Card for "Satellite-Images-of-Hurricane-Damage"
## Dataset Description
- **Paper** [Deep learning based damage detection on post-hurricane satellite imagery](https://arxiv.org/pdf/1807.01688.pdf)
- **Data** [IEEE-Dataport](https://ieee-dataport.org/open-access/detecting-damaged-buildings-post-hurricane-satellite-imagery-based-customized)
- **Split** Train_another
- **GitHub** [DamageDetection](https://github.com/qcao10/DamageDetection)
## Split Information
This HuggingFace dataset repository contains just the Train_another split.
### Licensing Information
[CC BY 4.0](https://ieee-dataport.org/open-access/detecting-damaged-buildings-post-hurricane-satellite-imagery-based-customized)
## Citation Information
[Deep learning based damage detection on post-hurricane satellite imagery](https://arxiv.org/pdf/1807.01688.pdf)
[IEEE-Dataport](https://ieee-dataport.org/open-access/detecting-damaged-buildings-post-hurricane-satellite-imagery-based-customized)
```
@misc{sdad-1e56-18,
title = {Detecting Damaged Buildings on Post-Hurricane Satellite Imagery Based on Customized Convolutional Neural Networks},
author = {Cao, Quoc Dung and Choe, Youngjun},
year = 2018,
publisher = {IEEE Dataport},
doi = {10.21227/sdad-1e56},
url = {https://dx.doi.org/10.21227/sdad-1e56}
}
@article{cao2018deep,
title={Deep learning based damage detection on post-hurricane satellite imagery},
author={Cao, Quoc Dung and Choe, Youngjun},
journal={arXiv preprint arXiv:1807.01688},
year={2018}
}
``` |