Nice informative example by @svpino.
So how much heuristics/thinking/revising goes into the choice of model architecture here?
In particular I mean number of layers and features, size of kernel and pooling.
New example on http://keras.io : a convolutional autoencoder for image denoisinghttps://keras.io/examples/vision/autoencoder/ …
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