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Hands-On Computer Vision with TensorFlow 2

You're reading from   Hands-On Computer Vision with TensorFlow 2 Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781788830645
Length 372 pages
Edition 1st Edition
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Authors (2):
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Eliot Andres Eliot Andres
Author Profile Icon Eliot Andres
Eliot Andres
Benjamin Planche Benjamin Planche
Author Profile Icon Benjamin Planche
Benjamin Planche
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: TensorFlow 2 and Deep Learning Applied to Computer Vision FREE CHAPTER
2. Computer Vision and Neural Networks 3. TensorFlow Basics and Training a Model 4. Modern Neural Networks 5. Section 2: State-of-the-Art Solutions for Classic Recognition Problems
6. Influential Classification Tools 7. Object Detection Models 8. Enhancing and Segmenting Images 9. Section 3: Advanced Concepts and New Frontiers of Computer Vision
10. Training on Complex and Scarce Datasets 11. Video and Recurrent Neural Networks 12. Optimizing Models and Deploying on Mobile Devices 13. Migrating from TensorFlow 1 to TensorFlow 2 14. Assessments 15. Other Books You May Enjoy

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, folder names, filenames, file extensions, pathnames, dummy URLs, and user input. Here is an example: "The .fit() method of the Model object starts the training procedure."

A block of code is set as follows:

import tensorflow as tf

x1 = tf.constant([[0, 1], [2, 3]])
x2 = tf.constant(10)
x = x1 * x2

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

neural_network = tf.keras.Sequential(
[tf.keras.layers.Dense(64),
tf.keras.layers.Dense(10, activation="softmax")])

Any command-line input or output is written as follows:

$ tensorboard --logdir ./logs

Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "You can observe the performance of your solution on the Scalars page of TensorBoard."

Warnings or important notes appear like this.
Tips and tricks appear like this.
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