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Python Deep Learning

You're reading from   Python Deep Learning Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789348460
Length 386 pages
Edition 2nd Edition
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Authors (5):
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Gianmario Spacagna Gianmario Spacagna
Author Profile Icon Gianmario Spacagna
Gianmario Spacagna
Daniel Slater Daniel Slater
Author Profile Icon Daniel Slater
Daniel Slater
Valentino Zocca Valentino Zocca
Author Profile Icon Valentino Zocca
Valentino Zocca
Peter Roelants Peter Roelants
Author Profile Icon Peter Roelants
Peter Roelants
Ivan Vasilev Ivan Vasilev
Author Profile Icon Ivan Vasilev
Ivan Vasilev
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Toc

Table of Contents (12) Chapters Close

Preface 1. Machine Learning - an Introduction 2. Neural Networks FREE CHAPTER 3. Deep Learning Fundamentals 4. Computer Vision with Convolutional Networks 5. Advanced Computer Vision 6. Generating Images with GANs and VAEs 7. Recurrent Neural Networks and Language Models 8. Reinforcement Learning Theory 9. Deep Reinforcement Learning for Games 10. Deep Learning in Autonomous Vehicles 11. Other Books You May Enjoy

Advanced computer vision tasks

So far, we've discussed classification tasks ; a CNN can tell us what object is in the image and a confidence score, but nothing more. In this section, we'll discuss two more advanced and interesting tasks: object detection and semantic segmentation.

Object detection

Object detection is the process of finding object instances of a certain class, such as faces, cars, and trees, in images or videos. Unlike classification, object detection can detect multiple objects, as well as their location in the image.

An object detector would return a list of detected objects with the following information for each object:

  • The class of the object (person, car, tree, and so on).
  • Probability (or confidence...
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