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  Dominik J. Mühlematter, Sebastian Schweizer, Chenjing Jiao, Xue Xia, Magnus Heitzler, Lorenz Hurni - 2024
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  [[Paper on ArXiv]](https://arxiv.org/abs/)
 
 
 
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  In correspondence with the code we released on [GitHub](https://github.com/), the usage of the models within our pipeline is described in the repository. Please note that this repository contains only the models for our final results, not for all intermediate results.
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  ## Pretraining
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  ## Road_classification_ensemble
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  This folder contains all the model weights for the final road classification ensemble trained on the [Siegfried Map](https://www.swisstopo.admin.ch/en/digital-siegfried-map-1-25000).
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- ## Citation
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- If you find our work useful or interesting, or if you use our code, please cite our paper as follows:
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-
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- ```latex
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- @misc{muhlematter2024probabilistic,
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- title = {Probabilistic road classification in historical maps using synthetic data and deep learning},
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- author = {Dominik J. Mühlematter, Sebastian Schweizer, Chenjing Jiao, Xue Xia, Magnus Heitzler, Lorenz Hurni},
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- year = {2024},
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- note = {arXiv:xxxx.xxxxx}
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- }
 
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  Dominik J. Mühlematter, Sebastian Schweizer, Chenjing Jiao, Xue Xia, Magnus Heitzler, Lorenz Hurni - 2024
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  [[Paper on ArXiv]](https://arxiv.org/abs/)
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+
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+ ## Citation
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+ If you find our work useful or interesting, or if you use our code, please cite our paper as follows:
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+ ```latex
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+ @misc{muhlematter2024probabilistic,
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+ title = {Probabilistic road classification in historical maps using synthetic data and deep learning},
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+ author = {Dominik J. Mühlematter, Sebastian Schweizer, Chenjing Jiao, Xue Xia, Magnus Heitzler, Lorenz Hurni},
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+ year = {2024},
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+ note = {arXiv:xxxx.xxxxx}
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+ }
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+ ```
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+
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  In correspondence with the code we released on [GitHub](https://github.com/), the usage of the models within our pipeline is described in the repository. Please note that this repository contains only the models for our final results, not for all intermediate results.
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  ## Pretraining
 
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  ## Road_classification_ensemble
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  This folder contains all the model weights for the final road classification ensemble trained on the [Siegfried Map](https://www.swisstopo.admin.ch/en/digital-siegfried-map-1-25000).
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