Figure 3
From: Effect of data leakage in brain MRI classification using 2D convolutional neural networks
A modified ResNet-18 architecture with an average pooling layer at the end is shown. The upper box represents a residual learning block with an identity shortcut. Each layer is denoted as (filter size, # channels); layers labeled as “freezed” indicates that the weights are not updated during backpropagation, whereas when they are labeled as “fine-tuned” they are updated. The identity shortcuts can be directly used when the input and output are of the same dimensions (solid line shortcuts) and when the dimensions increase (dotted line shortcuts). ReLU rectified linear unit.
