Packt+ | Advance your knowledge in tech

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

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

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

View More author details

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

Leave a review - let other readers know what you think

Technical requirements

Once again, several Jupyter notebooks and related source files to illustrate the chapter can be found in the Git repository dedicated to this book: https://github.com/PacktPublishing/Hands-On-Computer-Vision-with-TensorFlow-2/tree/master/Chapter07.

Some additional Python packages are required for the notebook demonstrating how to render synthetic images from 3D models, such as vispy (http://vispy.org) and plyfile (https://github.com/dranjan/python-plyfile). Installation instructions are provided in the notebook itself.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Benjamin Planche

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.

See other products by Benjamin Planche

Eliot Andres

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.

See other products by Eliot Andres

Other recommended products

Related to this chapter

Mastering Computer Vision with TensorFlow 2.x

Mastering Computer Vision with TensorFlow 2.x

You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.

May 2020 14h 20m

Mastering Computer Vision with TensorFlow 2.x

Mastering Computer Vision with TensorFlow 2.x

You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.

May 2020 14h 20m

Mastering Computer Vision with TensorFlow 2.x

Mastering Computer Vision with TensorFlow 2.x

You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.

May 2020 14h 20m

Mastering Computer Vision with TensorFlow 2.x

Mastering Computer Vision with TensorFlow 2.x

You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.

May 2020 14h 20m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Deep Learning from the Basics

Deep Learning from the Basics

Deep Learning from the Basics provides a step-by-step guide to these complex algorithms, from the ground up. From the basics of machine learning to multilayer neural networks, this book presents a thorough overview of these technologies enabling you to implement your own programs right away.

Mar 2021 10h 32m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m