Dmitrijs Cudihins - Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

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Dmitrijs Cudihins is a skilled data scientist, machine learning engineer, and software developer with more than eight years' commercial experience. His started off as a web developer, but later switched to data science and computer vision. He has been a senior data scientist for the last three years, providing consultancy services for a state-owned enterprise. There, he uses Julia to automate communication with citizens, applying different CV techniques and scanned image processing.

Zhuo Qingliang (KDr2 online) works for paodingai, a fintech start-up in China that is dedicated to improving the financial industry using AI technologies. He has over 10 years' experience in Linux, C, C++, Java, Python, and Perl development. He is interested in programming, consulting, and participating in, and contributing to, the open source community (which naturally includes the Julia community). He maintains a website, KDr2 , where you can find out more about him.

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Through this book, there will be a thorough guidance for all developers who want to get started with building computer vision applications using Julia. Julia is well suited for image processing because of its ease of use and the fact that it lets you write easy-to-compile and efficient machine code.

Readers will be taken through various packages that support image processing in Julia, and will also tap into open source libraries such as Open CV and Tesseract to find optimum solutions to problems encountered in computer vision. They will learn to build a full-fledged image processing application using JuliaImages, perform basic to advanced image and video stream processing with Julia's APIs, and much more.

This book is for all those Julia developers who are interested in learning how to perform image processing, for those who want to explore the field of computer vision and wish to benefit from this book. A basic knowledge of Julia will help you understand concepts more effectively.

, Getting Started with JuliaImages, is about getting your first introduction to JuliaImages and ImageCore packages. We will be loading images from various sources and creating thumbnails, that is resizing and saving them back on disk in a different file format.

, Image Enhancement, is all about working with the ImageFiltering package. We will understand what linear and nonlinear filtering operations are and how they can be used to transform images, such as sharpening, blurring, and smoothing.

, Image Adjustment , will guide you through the ImageMorphology package. Morphological transformations are some simple operations based on the image shape that allow you to remove small noise, shrink objects, separate objects, and increase the object size or background space.

, Image Segmentation , will explore the ImageSegmentation package. Readers will learn how to use supervised and unsupervised methods to simplify or represent an image into something that is more meaningful and easier to analyze.

, Image Representation , will explore the ImageFeatures package. We will learn to compute compact descriptors or "features" in a form that permits comparison and matching of two images.

, Introduction to Neural Networks , will demonstrate the need for neural networks. We'll cover getting, preparing the data, and improving and predicting the images. This chapter will also teach you to classify datasets, training and putting it all together.