Book Image

Hands-On Neural Networks with TensorFlow 2.0

By : Paolo Galeone
Book Image

Hands-On Neural Networks with TensorFlow 2.0

By: Paolo Galeone

Overview of this book

TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you’ll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub. By the end of this TensorFlow book, you'll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production.
Table of Contents (15 chapters)
Free Chapter
Section 1: Neural Network Fundamentals
Section 2: TensorFlow Fundamentals
Section 3: The Application of Neural Networks

Semantic segmentation

Different from object detection, where the goal is to detect objects in rectangular regions, and image classification, which has the purpose of classifying the whole image with a single label, semantic segmentation is a challenging computer vision task, the goal of which is to assign the correct label to every pixel of the input image:

Examples of semantically annotated images from the CityScapes dataset. Every single pixel of the input image has a corresponding pixel-label. (Source:

The applications of semantic segmentation are countless, but perhaps the most important ones are in the autonomous driving and medical imaging domains.

Automated guided vehicles and self-driving cars can take advantage of semantic segmentation results, getting a complete understanding of the whole scene captured by the cameras mounted...