Building Computer Vision Applications Using Artificial Neural Networks
- Author: Shamshad Ansari
- ISBN: 148425886X
- Year: 2020
- Pages: 473
- Language: English
- File size: 15.7 MB
- File format: PDF, ePub
- Category: Networking & Cloud Computing
Apply computer vision and machine learning concepts in creating business and industrial applications utilizing a practical, step-by-step strategy.
The book comprises four main segments starting with setting up your programming environment and configuring your computer with all the prerequisites to run the code examples. Part 1 covers the fundamentals of video and image processing with code examples of how to control and extract useful information in the pictures. You are going to mainly use OpenCV with Python to work with examples within this section.
Section 2 describes machine learning and neural network theories as applied to computer vision. You will learn different algorithms of this neural network, for example, convolutional neural network (CNN), region-based convolutional neural network (R-CNN), and YOLO. Section 3 provides step-by-step examples of creating business and industrial applications, such as facial recognition in video surveillance and surface flaw detection in production.
The final part is about training neural networks between a high number of pictures on cloud infrastructure, such as Amazon AWS, Google Cloud Platform, and Microsoft Azure. It walks through the procedure of training dispersed neural networks for computer vision on GPU-based cloud infrastructure. From the time you finish reading Building Computer Vision Software Using Artificial Neural Networks and working through the code examples, you’ll have developed some real-world use instances of personal vision with deep learning.