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Neural Networks with Keras Cookbook

You're reading from   Neural Networks with Keras Cookbook Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789346640
Length 568 pages
Edition 1st Edition
Languages
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Authors (2):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Srinivas Pradeep Srinivas Pradeep
Author Profile Icon Srinivas Pradeep
Srinivas Pradeep
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Toc

Table of Contents (18) Chapters Close

Preface 1. Building a Feedforward Neural Network FREE CHAPTER 2. Building a Deep Feedforward Neural Network 3. Applications of Deep Feedforward Neural Networks 4. Building a Deep Convolutional Neural Network 5. Transfer Learning 6. Detecting and Localizing Objects in Images 7. Image Analysis Applications in Self-Driving Cars 8. Image Generation 9. Encoding Inputs 10. Text Analysis Using Word Vectors 11. Building a Recurrent Neural Network 12. Applications of a Many-to-One Architecture RNN 13. Sequence-to-Sequence Learning 14. End-to-End Learning 15. Audio Analysis 16. Reinforcement Learning 17. Other Books You May Enjoy

Introduction

With the rise of autonomous cars, facial detection, smart video surveillance, and people counting solutions, fast and accurate object detection systems are in great demand. These systems include not only object recognition and classification in an image, but can also locate each one of them by drawing appropriate boxes around them. This makes object detection a harder task than its traditional computer vision predecessor, image classification.

To understand how the output of object detection looks like, let's go through the following picture:

So far, in the previous chapters, we have learned about classification.

In this chapter, we will learn about having a tight bounding box around the object in the picture, which is the localization task.

Additionally, we will also learn about detecting the multiple objects in the picture, which is the object detection task...

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