Line Plot from Scientific Research

Evolution of the test accuracy during training for different architectures (left, early times; right, full training): without the hidden layer or with N 2 = {20, 30, 60, 80}. We compare this with a linear classifier, ANN and CNN. During one epoch, each image in the training set is shown to the network once in mini-batches of 200 randomly chosen images; the shown test accuracy is evaluated on the entire test set. Increasing the size of the hidden layer improves both convergence speed and best accuracy.

DOI