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Evolution of classification accuracy and loss in a train and the validation set during the visual geometry group capsule network (VGG‐CapsNet) model's training for binary class classification. Training loss decreases sharply during the first five iterations and stabilizes after 10 iterations. Training stops after 17 epochs after patience of 10 epochs [Color figure can be viewed at wileyonlinelibrary.com]
