Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence
By 作者: Dmitrijs Cudihins
ISBN-10 书号: 1788998790
ISBN-13 书号: 9781788998796
Release Finelybook 出版日期: 2018-06-29
pages 页数: (202 )

$39.99

Book Description to Finelybook sorting

Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code.
This book begins by introducing you to Julia’s image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia’s interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned.
By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease.
Contents
1: GETTING STARTED WITH JULIAIMAGES
2: IMAGE ENHANCEMENT
3: IMAGE ADJUSTMENT
4: IMAGE SEGMENTATION
5: IMAGE REPRESENTATION
6: INTRODUCTION TO NEURAL NETWORKS
7: USING PRE-TRAINED NEURAL NETWORKS
8: OPENCV
What You Will Learn
Analyze image metadata and identify critical data using JuliaImages
Apply filters and improve image quality and color schemes
Extract 2D features for image comparison using JuliaFeatures
Cluster and classify images with KNN/SVM machine learning algorithms
Recognize text in an image using the Tesseract library
Use OpenCV to recognize specific objects or faces in images and videos
Build neural network and classify images with MXNet
Authors
Dmitrijs Cudihins
Dmitrijs Cudihins is a skilled data scientist, machine learning engineer and software developer with more than eight years of commercial experience. He started his career as a web-developer, but after a while switched to data science and computer vision.
For the past three years, Dmitrijs is working as a Senior Data Scientist providing consultancy services for the state-owned enterprise, where he uses Julia to automate communication with citizens by applying different Computer Vision techniques, including photo and scanned image processing, neural network classification and text retrieval.

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