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Advanced Deep Learning with Python

You're reading from   Advanced Deep Learning with Python Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781789956177
Length 468 pages
Edition 1st Edition
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Author (1):
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Ivan Vasilev Ivan Vasilev
Author Profile Icon Ivan Vasilev
Ivan Vasilev
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Core Concepts
2. The Nuts and Bolts of Neural Networks FREE CHAPTER 3. Section 2: Computer Vision
4. Understanding Convolutional Networks 5. Advanced Convolutional Networks 6. Object Detection and Image Segmentation 7. Generative Models 8. Section 3: Natural Language and Sequence Processing
9. Language Modeling 10. Understanding Recurrent Networks 11. Sequence-to-Sequence Models and Attention 12. Section 4: A Look to the Future
13. Emerging Neural Network Designs 14. Meta Learning 15. Deep Learning for Autonomous Vehicles 16. Other Books You May Enjoy

Introduction to 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 score) in the [0, 1] range, which conveys how confident the detector is that the object exists in that location. This is similar to the output of a regular classifier.
  • The coordinates of the rectangular region of the image where the object is located. This rectangle is called a bounding box.

We can see the typical output of an object-detection algorithm in the following photograph. The object type and confidence score are...

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