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@ -35,9 +35,9 @@ Pre-trained models can be downloaded from the locations below. We also provide m
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| Version | Format | Download |
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|------------|:-------------:|------------------------------------------------------------------------------------------------------|
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| 2021-03-09 | `SavedModel` | https://github.com/qurator-spk/sbb_binarization/releases/download/v0.0.11/saved_model_2021_03_09.zip |
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| 2021-03-09 | `HDF5` | https://qurator-data.de/sbb_binarization/2021-03-09/models.tar.gz |
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| 2020-01-16 | `SavedModel` | https://github.com/qurator-spk/sbb_binarization/releases/download/v0.0.11/saved_model_2020_01_16.zip |
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| 2020-01-16 | `HDF5` | https://qurator-data.de/sbb_binarization/2020-01-16/models.tar.gz |
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| 2021-03-09 | `HDF5` | https://qurator-data.de/sbb_binarization/2021-03-09/models.tar.gz |
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| 2020-01-16 | `SavedModel` | https://github.com/qurator-spk/sbb_binarization/releases/download/v0.0.11/saved_model_2020_01_16.zip |
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| 2020-01-16 | `HDF5` | https://qurator-data.de/sbb_binarization/2020-01-16/models.tar.gz |
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With [OCR-D](https://ocr-d.de/), you can also use the [Resource Manager](https://ocr-d.de/en/models), e.g.
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@ -78,3 +78,17 @@ For simple smoke tests, the following will
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make models
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make test
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## How to cite
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If you find this tool useful in your work, please consider citing our paper:
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```bibtex
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@inproceedings{hip23rezanezhad2,
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author = {Vahid Rezanezhad and Konstantin Baierer and Clemens Neudecker},
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editor = {Apostolos Antonacopoulos and Christian Clausner and Maud Ehrmann and Kai Labusch and Clemens Neudecker},
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title = {A hybrid CNN-Transformer Model for Historical Document Image Binarization},
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booktitle = {Proceedings of the 7th International Workshop on Historical Document Imaging and Processing {HIP} 2023,
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San José, CA, USA, August 26, 2023},
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year = {2023},
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url = {https://doi.org/10.1145/3604951.3605508}
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}
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```
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