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Python Image Processing Cookbook

You're reading from   Python Image Processing Cookbook Over 60 recipes to help you perform complex image processing and computer vision tasks with ease

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789537147
Length 438 pages
Edition 1st Edition
Languages
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Author (1):
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Sandipan Dey Sandipan Dey
Author Profile Icon Sandipan Dey
Sandipan Dey
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Toc

Table of Contents (11) Chapters Close

Preface 1. Image Manipulation and Transformation 2. Image Enhancement FREE CHAPTER 3. Image Restoration 4. Binary Image Processing 5. Image Registration 6. Image Segmentation 7. Image Classification 8. Object Detection in Images 9. Face Recognition, Image Captioning, and More 10. Other Books You May Enjoy

Image denoising with a denoising autoencoder

An autoencoder is a neural network often used to learn an efficient representation of input data (typically in a reduced dimension) in an unsupervised way. A denoising autoencoder is a stochastic version of an autoencoder that takes (similar) inputs corrupted by noise and is trained to recover the original inputs (typically using some deep learning library functions) in order to obtain a good representation. We can use denoising autoencoders to learn robust representations from a set of similar input images (corrupted with noise) and then generate the denoised images.

Getting ready

We will be using the labeled faces in the wild (lfw) face dataset from scikit-learn (it contains face...

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Python Image Processing Cookbook
Published in: Apr 2020
Publisher: Packt
ISBN-13: 9781789537147
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