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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

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781788830645

Length 372 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Computer Vision

Authors (2):

Eliot Andres

Benjamin Planche

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Table of Contents (16) Chapters

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

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Migrating TensorFlow 1 code

If the tool runs without any error, the code can be used as is. However, the tf.compat.v1 module used by the migration tool is deemed to be deprecated. Calling this module already outputs deprecation warnings, and its content will not be further updated by the community. For this reason, it is recommended that you refactor the code in order to make it more idiomatic. In the following sections, we will introduce TensorFlow 1 concepts and explain how to migrate them to TensorFlow 2. In the following examples, tf1 will be used instead of tf to denote the use of TensorFlow 1.13.

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Authors (2)

Benjamin Planche

Dr. Benjamin Planche is a passionate research scientist in computer vision and machine learning. His main research efforts focus on data scarcity problems and industrial vision systems, leading to numerous patents and publications at international conferences. He worked in various research labs around the world (including in France, Japan, Germany, and the USA). Benjamin obtained his Ph.D. summa cum laude from the Faculty of Computer Science and Mathematics at the University of Passau, under the supervision of Prof. Dr. Harald Kosch. He also has a double master's degree from INSA-Lyon (France) and the University of Passau (Germany), with first-class honors and a multinational excellence award. He also likes sharing his knowledge and experience on various platforms or applying them to the creation of aesthetic demos.

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Eliot Andres

Eliot Andres is a freelance deep learning and computer vision engineer. He has more than 3 years' experience in the field, applying his skills to a variety of industries, such as banking, health, social media, and video streaming. Eliot has a double master's degree from cole des Ponts and Tlcom, Paris. His focus is industrialization: delivering value by applying new technologies to business problems. Eliot keeps his knowledge up to date by publishing articles on his blog and by building prototypes using the latest technologies.

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