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Advanced Deep Learning with Keras
book

Advanced Deep Learning with Keras

by Rowel Atienza, Neeraj Verma, Valerio Maggio
October 2018
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 20m
English
Packt Publishing
Content preview from Advanced Deep Learning with Keras

Denoising autoencoder (DAE)

We're now going to build an autoencoder with a practical application. Firstly, let's paint a picture and imagine that the MNIST digits images were corrupted by noise, thus making it harder for humans to read. We're able to build a Denoising Autoencoder (DAE) to remove the noise from these images. Figure 3.3.1 shows us three sets of MNIST digits. The top rows of each set (for example, MNIST digits 7, 2, 1, 9, 0, 6, 3, 4, 9) are the original images. The middle rows show the inputs to DAE, which are the original images corrupted by noise. The last rows show the outputs of DAE:

Denoising autoencoder (DAE)

Figure 3.3.1: Original MNIST digits (top rows), ...

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Publisher Resources

ISBN: 9781788629416Supplemental Content