Hands-on Java deep learning for computer vision : implement machine learning and neural network methodologies to perform computer vision-related tasks
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...
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Main Author: | |
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Format: | eBook |
Language: | English |
Published: |
Birmingham, UK :
Packt Publishing,
2019.
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Subjects: | |
ISBN: | 1838552138 9781838552138 9781789613964 |
Physical Description: | 1 online resource (1 volume) : illustrations |
LEADER | 03685cam a2200349 i 4500 | ||
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020 | |a 1838552138 | ||
020 | |a 9781838552138 |q (electronic bk.) | ||
020 | |z 9781789613964 | ||
035 | |a (OCoLC)1091373924 | ||
100 | 1 | |a Ramo, Klevis, |e author. | |
245 | 1 | 0 | |a Hands-on Java deep learning for computer vision : |b implement machine learning and neural network methodologies to perform computer vision-related tasks / |c Klevis Ramo. |
264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2019. | |
300 | |a 1 online resource (1 volume) : |b illustrations | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
520 | |a 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 Description Although 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 course 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 for This 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. | ||
590 | |a Knovel |b Knovel (All titles) | ||
650 | 0 | |a Neural networks (Computer science) | |
650 | 0 | |a Java (Computer program language) | |
650 | 0 | |a Machine learning. | |
655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
655 | 9 | |a electronic books |2 eczenas | |
856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpHOJDLCV1/hands-on-java?kpromoter=marc |y Full text |