Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications

Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications

E-book

US$207.63 excl. VAT

You and your friend both get points.

Download immediately after payment, unlimited re-downloads from your account.

By starting the download you agree that your right of withdrawal ends, because the content is delivered at once.

About this title

This book provides a structured presentation of machine learning related to vision, speech, and natural language processing. It addresses the tools, techniques, and challenges of machine learning algorithm implementation, computation time, and the complexity of reasoning and modeling of different types of data. The book covers diverse topics such as semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, natural language processing, traffic and signaling, driverless driving, and radiology. The majority of smart applications have a need for a sustainable Internet of things (IoT) and artificial intelligence. Active research trends and future directions of machine learning under big data analytics are also discussed. Machine learning is a class of artificial neural networks that have become dominant in various computer vision tasks, attracting interest across a variety of domains as they are a type of deep neural networks efficient in extracting meaningful information from visual imagery.

Details

Publisher
Springer Nature Singapore
Language
EN
Format
EPUB
Published
ISBN
9789819753659
File protection
Watermark — opens on any reader, no extra account needed