Hands-On Computer Vision with Julia by Dmitrijs Cudihins

Author:Dmitrijs Cudihins
Language: eng
Format: epub
Tags: COM016000 - COMPUTERS / Computer Vision and Pattern Recognition, COM051010 - COMPUTERS / Programming Languages / General, COM051070 - COMPUTERS / Programming Languages / C++
Publisher: Packt Publishing
Published: 2018-06-29T14:45:09+00:00

Questions

Please answer the following questions:

What is the purpose of corner detection?

How can corner detection help to identify areas with text?

How does the increase of the threshold value for FAST affect the number of features?

When would you use a BRIEF algorithm, and when would you use a BRISK one?

What is the primary difference between an ORB algorithm and BRISK?

Which of the three algorithms (BRIEF, ORB, and BRISK) implements FAST out of the box?

Introduction to Neural Networks

This chapter will primarily focus on understanding the difference between classic computer vision and neural networks, and also shows how to prepare images for use in deep learning models, and assist in building and training your first classifiers.

The following topics are covered in this chapter:

Introduction to MXNet and its building blocks

Building a digit classifier for the MNIST dataset

Building a multiclass image classifier with CIFAR-10

Building the cats and dogs classifier

Reusing the models

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