Cargando…

Machine Learning for OpenCV 4 - Second Edition /

A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4 Key Features Gain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learn Get up to spe...

Descripción completa

Detalles Bibliográficos
Autores principales: Sharma, Aditya (Autor), Beyeler, Michael (Autor), Shrimali, Vishwesh (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Packt Publishing, 2019.
Edición:2nd edition.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

LEADER 00000cam a2200000Ma 4500
001 OR_on1235775485
003 OCoLC
005 20231017213018.0
006 m o d
007 cr cn|||||||||
008 111019s2019 xx go 000 0 eng d
040 |a TOH  |b eng  |c TOH  |d OCLCO 
020 |a 1789536308 
020 |a 9781789536300 
035 |a (OCoLC)1235775485 
049 |a UAMI 
100 1 |a Sharma, Aditya,  |e author. 
245 1 0 |a Machine Learning for OpenCV 4 - Second Edition /  |c Sharma, Aditya. 
250 |a 2nd edition. 
264 1 |b Packt Publishing,  |c 2019. 
300 |a 1 online resource (420 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file 
365 |b 44.99 
520 |a A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4 Key Features Gain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learn Get up to speed with Intel OpenVINO and its integration with OpenCV 4 Implement high-performance machine learning models with helpful tips and best practices Book Description OpenCV is an opensource library for building computer vision apps. The latest release, OpenCV 4, offers a plethora of features and platform improvements that are covered comprehensively in this up-to-date second edition. You'll start by understanding the new features and setting up OpenCV 4 to build your computer vision applications. You will explore the fundamentals of machine learning and even learn to design different algorithms that can be used for image processing. Gradually, the book will take you through supervised and unsupervised machine learning. You will gain hands-on experience using scikit-learn in Python for a variety of machine learning applications. Later chapters will focus on different machine learning algorithms, such as a decision tree, support vector machines (SVM), and Bayesian learning, and how they can be used for object detection computer vision operations. You will then delve into deep learning and ensemble learning, and discover their real-world applications, such as handwritten digit classification and gesture recognition. Finally, you'll get to grips with the latest Intel OpenVINO for building an image processing system. By the end of this book, you will have developed the skills you need to use machine learning for building intelligent computer vision applications with OpenCV 4. What you will learn Understand the core machine learning concepts for image processing Explore the theory behind machine learning and deep learning algorithm design Discover effective techniques to train your deep learning models Evaluate machine learning models to improve the performance of your models Integrate algorithms such as support vector machines and Bayes classifier in your computer vision applications Use OpenVINO with OpenCV 4 to speed up model inference Who this book is for This book is for Computer Vision professionals, machine learning developers, or anyone who wants to learn machine learning algorithms and implement them using OpenCV 4. If you want to build real-world Co... 
542 |f Copyright © 2019 Packt Publishing  |g 2019 
550 |a Made available through: Safari, an O'Reilly Media Company. 
588 0 |a Online resource; Title from title page (viewed September 6, 2019). 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
700 1 |a Beyeler, Michael,  |e author. 
700 1 |a Shrimali, Vishwesh,  |e author. 
710 2 |a O'Reilly for Higher Education (Firm),  |e distributor. 
710 2 |a Safari, an O'Reilly Media Company. 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781789536300/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
994 |a 92  |b IZTAP