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The architecture of the Convolutional Autoencoder. It contains seven convolutional layers. The input is of dimensions 592 × 192 and through the convolutional and max pooling layers is transformed into a 74 × 24 × 8 array. From this 74 × 24 × 8 array, the input is recreated through convolutions and up sampling.
