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Scaling behavior of different layers of the network. (A) Scaling of the network performance with fixed number of top layer neurons and variable number of feature maps in the convolutional layers. (B) Increase in test set performance as a function of the number of neurons in the fully connected top layer (with number of feature maps fixed to 16 and 32 in the convolutional layers). The last point of Querlioz et al. (2015) is not exactly reported but likely lies between 94 and 95%.
