April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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Repeat the preceding denoising process with colored images (pass color=True to the fetch_lfw_people() function). Train an overcomplete autoencoder (where the number of hidden layer nodes is greater than the number of input nodes, with a single hidden layer) using the noisy images. What happens if you train this with the original images both at input and output? Now, train a sparse overcomplete autoencoder with original images both at input and output, but using an L1 regularizer at the hidden layer.
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