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@@ -30,10 +30,19 @@ Trained on ImageNet-1k and fine-tuned on gold standard annotations and outputs f
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  - **Model type:** Image classification /feature backbone
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  - **Finetuned from model:** https://pytorch.org/vision/main/models/generated/torchvision.models.resnet152.html
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- ## Uses
 
 
 
 
 
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- This fine-tuned version of the model is an output of the MapReader pipeline. It was used to classify 'patch' images (cells/regions) of scanned nineteenth-century series maps of Britain provided by the National Library of Scotland (learn more [here](https://maps.nls.uk/os/)). We classified patches to indicate the presence of buildings and railway infrastructure. See [our paper](https://dl.acm.org/doi/10.1145/3557919.3565812) for more details about labels.
 
 
 
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  ## How to Get Started with the Model in MapReader
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  - **Model type:** Image classification /feature backbone
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  - **Finetuned from model:** https://pytorch.org/vision/main/models/generated/torchvision.models.resnet152.html
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+ ### Classes and labels
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+
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+ - 0: no
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+ - 1: railspace
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+ - 2: building
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+ - 3: railspace & building
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+ ## Uses
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+ This fine-tuned version of the model is an output of the MapReader pipeline.
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+ It was used to classify 'patch' images (cells/regions) of scanned nineteenth-century series maps of Britain provided by the National Library of Scotland (learn more [here](https://maps.nls.uk/os/)).
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+ We classified patches to indicate the presence of buildings and railway infrastructure.
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+ See [our paper](https://dl.acm.org/doi/10.1145/3557919.3565812) for more details about labels.
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  ## How to Get Started with the Model in MapReader
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