Fig. 1.

Convolutional neural net architecture for image classification. a The neural network algorithm used for classification included six convolutional layers and two fully-connected layers of 1028 and 512 nodes, respectively. The softmax classifier (pink circles) consisted of up to 15 nodes, depending on the classification task at hand. b Training, validation, and test data were split by study, and test data was not used for training or validating the model. The model was trained to classify images, with video classification as a majority rules vote on related image frames. Conv convolutional layer, Max Pool max pooling layer, FC fully connected layer