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Hands-On Image Processing with Python

You're reading from   Hands-On Image Processing with Python Expert techniques for advanced image analysis and effective interpretation of image data

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789343731
Length 492 pages
Edition 1st Edition
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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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Table of Contents (20) Chapters Close

Title Page
Copyright and Credits
Dedication
About Packt
Contributors
Preface
1. Getting Started with Image Processing FREE CHAPTER 2. Sampling, Fourier Transform, and Convolution 3. Convolution and Frequency Domain Filtering 4. Image Enhancement 5. Image Enhancement Using Derivatives 6. Morphological Image Processing 7. Extracting Image Features and Descriptors 8. Image Segmentation 9. Classical Machine Learning Methods in Image Processing 10. Deep Learning in Image Processing - Image Classification 11. Deep Learning in Image Processing - Object Detection, and more 12. Additional Problems in Image Processing 1. Other Books You May Enjoy Index

Chapter 10. Deep Learning in Image Processing - Image Classification

In this chapter, we shall discuss recent advances in image processing with deep learning. We'll start by differentiating between classical and deep learning techniques, followed by a conceptual section on convolutional neural networks (CNN), the deep neural net architectures particularly useful for image processing. Then we'll continue our discussion on the image classification problem with a couple of image datasets and how to implement it with TensorFlow and Keras, two very popular deep learning libraries. Also, we'll see how to train deep CNN architectures and use them for predictions.

 The topics to be covered in this chapter are as follows:

  • Deep learning in image processing
  • CNNs
  • Image classification with TensorFlow or Keras with the handwritten digits images dataset
  • Some popular deep CNNs (VGG-16/19, InceptionNet, ResNet) with an application in classifying the cats versus dogs images with the VGG-16 network

 

 

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