Users can look into other popular networks such as VGG and ResNet. They are also widely used in the deep learning community.

Hands-On Computer Vision with Julia
By :

Hands-On Computer Vision with Julia
By:
Overview of this book
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.
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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.
Table of Contents (11 chapters)
Preface
Getting Started with JuliaImages
Image Enhancement
Image Adjustment
Image Segmentation
Image Representation
Introduction to Neural Networks
Using Pre-Trained Neural Networks
OpenCV
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