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At the moment, the training set, validation set and test set are fixed, and new annotated patches are added only to the training set after each active-learning iteration, leaving the validation set unchanged.
Using K-fold cross validation would allow to make use of all the samples to train the network, especially when few data samples are available.
One potential issue coming with the K-fold cross validation is the extension of the training time.
The text was updated successfully, but these errors were encountered:
At the moment, the training set, validation set and test set are fixed, and new annotated patches are added only to the training set after each active-learning iteration, leaving the validation set unchanged.
Using K-fold cross validation would allow to make use of all the samples to train the network, especially when few data samples are available.
One potential issue coming with the K-fold cross validation is the extension of the training time.
The text was updated successfully, but these errors were encountered: