Book Image

Hands-On Computer Vision with TensorFlow 2

By : Benjamin Planche, Eliot Andres
Book Image

Hands-On Computer Vision with TensorFlow 2

By: Benjamin Planche, Eliot Andres

Overview of this book

Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0.
Table of Contents (16 chapters)
Free Chapter
1
Section 1: TensorFlow 2 and Deep Learning Applied to Computer Vision
5
Section 2: State-of-the-Art Solutions for Classic Recognition Problems
9
Section 3: Advanced Concepts and New Frontiers of Computer Vision
14
Assessments

Section 1: TensorFlow 2 and Deep Learning Applied to Computer Vision

This section covers the fundamentals of computer vision and deep learning, with the help of concrete TensorFlow examples. Starting with a presentation of these technical domains, the first chapter will then walk you through the inner workings of neural networks. This section continues with an introduction to the instrumental features of TensorFlow 2 and Keras, and their key concepts and ecosystems. It ends with a description of machine learning techniques adopted by computer vision experts.

The following chapters will be covered in this section:

  • Chapter 1, Computer Vision and Neural Networks
  • Chapter 2, TensorFlow Basics and Training a Model
  • Chapter 3, Modern Neural Networks