Deep Learning, Artificial Intelligence, Convolutional Network, Semi Supervised Learning, Image Classification.
SVHN and NORB with 1% and 100% of data (mean % ± std) Dropout and random max-pooling are the only sources of variation in the above table. By using unsupervised loss functions, the accuracy of the classifier is significantly improved by trying to minimize the variation in prediction of the network.