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Hands-On Transfer Learning with Python

You're reading from   Hands-On Transfer Learning with Python Implement advanced deep learning and neural network models using TensorFlow and Keras

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781788831307
Length 438 pages
Edition 1st Edition
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Authors (4):
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Nitin Panwar Nitin Panwar
Author Profile Icon Nitin Panwar
Nitin Panwar
Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
Tamoghna Ghosh Tamoghna Ghosh
Author Profile Icon Tamoghna Ghosh
Tamoghna Ghosh
Dipanjan Sarkar Dipanjan Sarkar
Author Profile Icon Dipanjan Sarkar
Dipanjan Sarkar
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Table of Contents (14) Chapters Close

Preface 1. Machine Learning Fundamentals FREE CHAPTER 2. Deep Learning Essentials 3. Understanding Deep Learning Architectures 4. Transfer Learning Fundamentals 5. Unleashing the Power of Transfer Learning 6. Image Recognition and Classification 7. Text Document Categorization 8. Audio Event Identification and Classification 9. DeepDream 10. Style Transfer 11. Automated Image Caption Generator 12. Image Colorization 13. Other Books You May Enjoy

Understanding image captioning

By now, you should understand the significance and meaning of image captioning. This task can be simply defined as writing and recording a free-flowing and natural text description for any image. It is usually used to describe various scenes or events in images. This is also popularly termed scene recognition. Let's look at the following example:

Looking at this scene, what could be a suitable caption or description? The following are all valid descriptions of the scene:

  • A motocross rider is on a dirt hill
  • A guy on a bicycle midair above a hill
  • A dirt bike rider is moving fast down a dirt path
  • A biker riding a black motorbike in midair

You can see that all of these captions are valid and are similar yet use different words to convey the same meaning. This is why generating image captions automatically is not an easy task.

In fact, the...

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