Extended Data Fig. 8: Training and inference performance of the nnU-Net model. | Nature Methods

Extended Data Fig. 8: Training and inference performance of the nnU-Net model.

From: Smart parallel automated cryo-electron tomography

Extended Data Fig. 8

a. Loss values for training dataset (train loss) and validation dataset (val loss) of the 5-fold cross-validated training of the nnU-Net model. All 5 folds (fold_0-4) were provided by nnU-Net during the training process for 1000 epochs. b. Mean segmentation inference time in minutes per 100 µm2 obtained from inferences of MM maps (n = 8) of sizes between 300 and 1000 µm2. Error bars show the standard deviation.

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