Lets say I have the cifar 10 dataset and I manipulate it in such a way that I reduce the number of frogs in the dataset from 6000 to say 600. I now consider frog as an outlier and train a two class classification problem on this modified cifar 10 dataset. All the other 9 classes as one group and the frog as a outlier. What architecture is best to detect this frog outlier? Where can I find reading materials to learn about these?
Convolutional Neural Network for outlier detection
neural network;convnet;image classification;anomaly detection