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HED-UNet

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Simultaneous Semantic Segmentation and Edge Detection

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# HED-UNet

Code for HED-UNet, a model for simultaneous semantic segmentation and edge detection.

## Glacier Fronts

This model was originally developed to detect calving front margins in Antarctica from Sentinel-1 SAR imagery.

![glaciers](https://raw.githubusercontent.com/khdlr/HED-UNet/master/figures/glaciers.jpg)

## Building Footprints

As the original dataset isn't publicly available, this repository contains an adaption of the model for building footprint extraction on the [Inria Aerial Image Labeling dataset](https://project.inria.fr/aerialimagelabeling/). Here are some example results:

##### Bloomington

![bloomington27-overview-binary](https://raw.githubusercontent.com/khdlr/HED-UNet/master/figures/bloomington27-overview-binary.jpg)

##### Innsbruck

![innsbruck20-overview-binary](https://raw.githubusercontent.com/khdlr/HED-UNet/master/figures/innsbruck20-overview-binary.jpg)

##### San Francisco

![sfo20-overview-binary](https://raw.githubusercontent.com/khdlr/HED-UNet/master/figures/sfo20-overview-binary.jpg)

## Usage

In order to use this for your project, you will need adapt either the `get_dataloader` function in `train.py` or the methods in `data_loading.py`.

## Citation

If you find our code helpful and use it in your research, please use the following BibTeX entry.

```tex
@article{HEDUNet2021,
  author={Heidler, Konrad and Mou, Lichao and Baumhoer, Celia and Dietz, Andreas and Zhu, Xiao Xiang},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline}, 
  year={2021},
  volume={},
  number={},
  pages={1-14},
  doi={10.1109/TGRS.2021.3064606}
}
```

HED-UNet

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