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Federated Learning for Multimedia Data Processing and Security in Industry 5.0 - (Computing and Networks) (Hardcover)

Federated Learning for Multimedia Data Processing and Security in Industry 5.0 - (Computing and Networks) (Hardcover) - 1 of 1
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About this item

Highlights

  • Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process.
  • Author(s): Gautam Srivastava & Thippa Reddy Gadekallu
  • 346 Pages
  • Computers + Internet, Security
  • Series Name: Computing and Networks

Description



About the Book



This book explores how federated learning can solve multimedia data processing and security challenges in Industry 5.0, introduces new research paradigms for the security and privacy preservation of multimedia data, and explores the integration of federated learning with other disruptive technologies.



Book Synopsis



Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for mission critical applications.

Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data.

The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond.

Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.

Dimensions (Overall): 9.21 Inches (H) x 6.14 Inches (W) x .81 Inches (D)
Weight: 1.45 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 346
Genre: Computers + Internet
Sub-Genre: Security
Series Title: Computing and Networks
Publisher: Institution of Engineering & Technology
Theme: General
Format: Hardcover
Author: Gautam Srivastava & Thippa Reddy Gadekallu
Language: English
Street Date: January 28, 2025
TCIN: 1003464710
UPC: 9781839537578
Item Number (DPCI): 247-02-5154
Origin: Made in the USA or Imported
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Shipping details

Estimated ship dimensions: 0.81 inches length x 6.14 inches width x 9.21 inches height
Estimated ship weight: 1.45 pounds
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