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# CHNR: An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing
This repository contains code of the paper "An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing". This work has been done at the [Remote Sensing Image Analysis group](https://www.rsim.tu-berlin.de/menue/remote_sensing_image_analysis_group/) by [Georgii Mikriukov](https://www.rsim.tu-berlin.de/index.php?id=217673), [Mahdyar Ravanbakhsh](https://rsim.berlin/team/members/mahdyar-ravanbakhsh) and [Begüm Demir](https://begumdemir.com/).
This repository contains code of the paper `An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing`. This work has been done at the [Remote Sensing Image Analysis group](https://www.rsim.tu-berlin.de/menue/remote_sensing_image_analysis_group/) by [Georgii Mikriukov](https://www.rsim.tu-berlin.de/index.php?id=217673), [Mahdyar Ravanbakhsh](https://rsim.berlin/team/members/mahdyar-ravanbakhsh) and [Begüm Demir](https://begumdemir.com/).
> Paper placeholder
......@@ -115,7 +115,11 @@ main.py --dataset ucm --bit 64 --tag my_model --noise-wrong-caption 0.2 --clean-
## License
The code is available under the terms of MIT license:
The code in this repository to facilitate the use of the `An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing` is available under the terms of **MIT license**:
```
Copyright (c) 2022 the Authors of The Paper, "An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing"
```
Copyright (c) 2021 Georgii Mikriukov
......@@ -137,4 +141,4 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
```
\ No newline at end of file
```
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