A Generalized Deep Learning-Based Pipeline for Historical Manuscript Dating

Contains all trained models for the dating pipeline

In each directory models are named as follows:

  • PyTorch Dating CNN: "model_epoch_[epoch_number]_split_[split_number].pt"
  • SVM feature aggregation: "classifier_model_split_[split_number].pkl"

CSV files indicate the performance while training.

Repository is structured as follows:

  • Binet_aug_norm: BiNet model with synthetic images
  • Binet_norm: Standard BiNet model
  • CLAMM_P1_Crossval: 5-fold cross-validation for the CLaMM dataset
  • HIMANIS_P1_Crossval: 5-fold cross-validation for the Himanis dataset
  • MPS_P1_Crossval: 5-fold cross-validation for the MPS dataset
  • SCRIBBLE_P1_Crossval: 5-fold cross-validation for the ScribbleLens dataset
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