Hands-On Java Deep Learning for Computer Vision
Implement machine learning and neural network methodologies to perform computer vision-related tasks
Seiten
2019
Packt Publishing Limited (Verlag)
9781789613964 (ISBN)
Packt Publishing Limited (Verlag)
9781789613964 (ISBN)
This book will take you through the process of efficiently training deep neural networks in Java for Computer Vision-related tasks. You will build real-world applications ranging from simple Java handwritten digit recognition models to real-time autonomous car driving systems and face recognition models using the popular Java-based libraries.
Leverage the power of Java and deep learning to build production-grade Computer Vision applications
Key Features
Build real-world Computer Vision applications using the power of neural networks
Implement image classification, object detection, and face recognition
Know best practices on effectively building and deploying deep learning models in Java
Book DescriptionAlthough machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning.
The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The book is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models.
By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy.
What you will learn
Discover neural networks and their applications in Computer Vision
Explore the popular Java frameworks and libraries for deep learning
Build deep neural networks in Java
Implement an end-to-end image classification application in Java
Perform real-time video object detection using deep learning
Enhance performance and deploy applications for production
Who this book is forThis book is for data scientists, machine learning developers and deep learning practitioners with Java knowledge who want to implement machine learning and deep neural networks in the computer vision domain. You will need to have a basic knowledge of Java programming.
Leverage the power of Java and deep learning to build production-grade Computer Vision applications
Key Features
Build real-world Computer Vision applications using the power of neural networks
Implement image classification, object detection, and face recognition
Know best practices on effectively building and deploying deep learning models in Java
Book DescriptionAlthough machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning.
The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The book is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models.
By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy.
What you will learn
Discover neural networks and their applications in Computer Vision
Explore the popular Java frameworks and libraries for deep learning
Build deep neural networks in Java
Implement an end-to-end image classification application in Java
Perform real-time video object detection using deep learning
Enhance performance and deploy applications for production
Who this book is forThis book is for data scientists, machine learning developers and deep learning practitioners with Java knowledge who want to implement machine learning and deep neural networks in the computer vision domain. You will need to have a basic knowledge of Java programming.
Klevis Ramo is a highly motivated software engineer with a solid educational background who loves writing. He aims to create stable and creative solutions with performance in mind. Klevis is passionate about coding and machine learning with several open source contributions and is experienced at developing web services and REST API. He is always eager to learn new technologies and to improve system performance and scalability.
Table of Contents
Introduction to Computer Vision and Training Neural Networks
Convolutional Neural Network Architectures
Transfer Learning and Deep CNN Architectures
Real-Time Object Detection
Creating Art with Neural Style Transfer
Face Recognition
| Erscheinungsdatum | 25.02.2019 |
|---|---|
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 75 x 93 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-13 | 9781789613964 / 9781789613964 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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