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Fig. 3
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Basic principle of an autoencoder. The hidden layer is a bottleneck that forces a compressed input representation. The input example is a 2D image from the MNIST dataset [42]. The 2D 28 × 28 pixels image is processed as a 784 vector. In our case, the input is a spectrum.
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