Figure 3 | Scientific Reports

Figure 3

From: 2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma

Figure 3The alternative text for this image may have been generated using AI.

Architecture of the applied autoencoder. Numbers describe the shapes of computed feature maps. Convolutional layers ('conv’) are comprised of convolutional filters (light orange) and Leaky ReLU (\(\alpha =0.01\)) activation functions (orange). Spatial downsampling is performed using max-pooling layers (red), resulting in a set of bottleneck features. Upsampling operations ('up’, blue), and convolutional layers are then used to reconstruct the input image. A sigmoid activation (purple) is used as model output to match the range of the input data.

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