Computer vision with maker tech : detecting people with a Raspberry Pi, a thermal camera, and machine learning / Fabio Manganiello.
Manganiello, Fabio, author.
2021
TA1634
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Computer vision with maker tech : detecting people with a Raspberry Pi, a thermal camera, and machine learning / Fabio Manganiello.
Author Manganiello, Fabio, author.
ISBN 9781484268216 (electronic bk.)
1484268210 (electronic bk.)
1484268202
9781484268209
DOI https://doi.org/10.1007/978-1-4842-6821-6
Published [Berkeley, Calif.] : Apress, [2021]
Language English
Description 1 online resource : illustrations (chiefly color), charts (chiefly color)
Item Number 10.1007/978-1-4842-6821-6 doi
Call Number TA1634
Dewey Decimal Classification 006.3/7
Summary Harness the untapped potential of combining a decentralized Internet of Things (IoT) with the ability to make predictions on real-world fuzzy data. This book covers the theory behind machine learning models and shows you how to program and assemble a voice-controlled security. Youll learn the differences between supervised and unsupervised learning and how the nuts-and-bolts of a neural network actually work. Youll also learn to identify and measure the metrics that tell how well your classifier is doing. An overview of other types of machine learning techniques, such as genetic algorithms, reinforcement learning, support vector machines, and anomaly detectors will get you up and running with a familiarity of basic machine learning concepts. Chapters focus on the best practices to build models that can actually scale and are flexible enough to be embedded in multiple applications and easily reusable. With those concepts covered, youll dive into the tools for setting up a network to collect and process the data points to be fed to our models by using some of the ubiquitous and cheap pieces of hardware that make up today's home automation and IoT industry, such as the RaspberryPi, Arduino, ESP8266, etc. Finally, youll put things together and work through a couple of practical examples. Youll deploy models for detecting the presence of people in your house, and anomaly detectors that inform you if some sensors have measured something unusual. And youll add a voice assistant that uses your own model to recognize your voice. You will: Develop a voice assistant to control your IoT devices Implement Computer Vision to detect changes in an environment Go beyond simple projects to also gain a grounding machine learning in general See how IoT can become "smarter" with the inception of machine learning techniques Build machine learning models using TensorFlow and OpenCV
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed March 22, 2021).
Available in Other Form Print version: 9781484268209
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Chapter 1: Introduction to Machine Learning
Chapter 2: Neural Networks
Chapter 3: Computer Vision on Raspberry Pi.

Browse Subjects

Show more subjects...

Statistics

from
to
Export